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Über dieses Buch

This book presents the combined proceedings of the 8th International Conference on Computer Science and its Applications (CSA-16) and the 11st International Conference on Ubiquitous Information Technologies and Applications (CUTE 2016), both held in Bangkok, Thailand, December 19 - 21, 2016.

The aim of these two meetings was to promote discussion and interaction among academics, researchers and professionals in the field of ubiquitous computing technologies.

These proceedings reflect the state-of-the-art in the development of computational methods, involving theory, algorithm, numerical simulation, error and uncertainty analysis and novel application of new processing techniques in engineering, science, and other disciplines related to ubiquitous computing.



Advances in Information Technologies and Applications


Design and Development of a Robotic Arm for Rehabilitation and Training

This proposed research proposes the design and development of a robotic arm for rehabilitation and training. This wearable robot arm can easily be used with either the user’s left or right arm. Each joint of exoskeleton motion can be rotated from −90° to 90° which cover all motions of human arm. The virtual reality technique is used to provide the 3D graphics to motivate the patient during the rehabilitation. The designed robot arm will support the patient’s arm during rehabilitation or training which is a repetitive task over a period of time. Furthermore, this exoskeleton arm can be utilized for training purpose.

Sarut Panjan, Siam Charoenseang

Detection of a Robust High-Frequency Range via Noise Analysis in a Real-World Environment

Recently, many studies have been conducted on using inaudible high frequencies for wireless communication based on smart devices and data transmission algorithms. However, many studies have identified a problem such that transmission accuracy is extremely low because of ambient noise in the real-life environment. To solve this problem, we proposed an application and server system. The proposed application can gather many sounds, including those with high frequencies; the gathered high frequencies are sent to a server system that can detect a robust high-frequency range via statistical processing. We tested the proposed application’s ability to gather noise and high frequencies for a certain period of time to evaluate performance. According to the testing results, the proposed application and server system could detect a robust high-frequency range via noise analysis in real life. Therefore, the proposed application and server could be a useful technology for future research on inaudible high frequencies.

Myoungbeom Chung, Ilju Ko

Intelligent Food Distribution Monitoring System

Food quality and safety has gained main attention, due to increasing health awareness of customer, improved economic standards and lifestyle of modern societies. Thus, it is important for consumers to purchase good quality products in order to keep the customer satisfaction level. In this study, we propose traceability system for food by monitoring the location as well as temperature and humidity. The RFID technology and wireless sensor network are utilized in this study to perform the experiment. The real testbed implementation has been performed in one of the Korean Kimchi Supply Chain. The result showed that our proposed system gave the benefit to the manager as well as customer by providing real time location as well as temperature-humidity history. It will help manager to optimize the food distribution while for the customer it will increase the satisfaction by maintaining the freshness of product.

Ganjar Alfian, Hyejung Ahn, Yoonmo Shin, Jaeho Lee, Jongtae Rhee

Design of Sudden Unintended Acceleration Check System Using Distance Measurement Sensor

Today, various models of automobiles based on diverse motifs, such as eco-friendly car, autonomous car, connected car, and smart car, are produced in Korea. With the increased competitiveness of the automobiles, highly-advanced automobiles are developed.Although the automobiles have positive aspects, their sudden unintended acceleration (SUA) accidents bring about people’s negative perception of the vehicles.It has been analyzed that the SUA is attributable to defects of electric devices or brakes and other factors in the development of automobile parts and technology. Nevertheless, it is impossible to define the causes of the SUA accurately, and manufacturers also try to avoid their responsibility. As a result, more burden has been imposed on drivers.Therefore, this study designs the system that has a camera and a distance sensor attached to a driver’s seat and helps to respond to the SUA and find its cause in the way of checking the operation states of a vehicle’s control parts including accelerator and brake and sensor images.

Jea-Hui Cha, Tae-Hyoung Kim, Jong-Wook Jang

Real-Time Dynamic Motion Capture Using Multiple Kinects

The present paper proposes a method of capturing real-time motions without any inconvenient suit by using several inexpensive sensors vulnerable to joint occlusion and body rotation. Depth data and ICP algorithm are used for calibration. Then, the left and right sides of joints are determined, and the optimal joints are chosen based on the variation in rotation to restore postures. The similarity between the motions captured by the proposed multiple sensors and those captured by a commercial motion capture system is over 85 %.

Seongmin Baek, Myunggyu Kim

Cell-Based Indexing Method for Spatial Data Management in Hybrid Cloud Systems

In order to efficiently support various spatial and non-spatial queries over geographic heterogeneous cloud environments, we propose a cell-based inverted list index method. Our proposal includes a spatial keyword cell structure for simultaneously managing spatial and non-spatial keywords. An extended inverted list is constructed in order to support robust indexing of loosely coupled collections of heterogeneity spatial objects; therefore, our method can support flexible queries efficiently, such as keyword spatial and non-spatial queries and nearest neighbor queries. Experiment results show that the proposed indexing method can support quick answer of spatial queries compared with several typical existing indexing methods.

Yan Li, Byeong-Seok Shin

SOA Based Equipment Data Management System for Smart Factory

In this paper we introduce a SOA based EDA system complied with SEMI Standards for smart factory in semiconductor manufacturing filed To design the system that is used to integrate information systems in the factory, we analyze the requirements of EDA system in the prospect of the components of the information systems. We build a prototype for an EDA system including EDA Host and EDA Client in EDA SEMI standards.

YunHee Kang, Soong-ho Ko, Kyoungwoo Kang

The Problem Analysis of Specific Personal Information Protection Assessment in Japan Case

In this paper, we analyze the total item assessment reports that have been published by municipalities for the mandated implementation of the specific personal information assessment in three perspectives. The three perspectives are (1) Adequacy of risk items, (2) Re-use of the assessment report, and (3) Classification of the assessment model. As a result, for example, in risk measures where there are many assessment reports, there is a description of the measures in the system but there are missing measures outside the system such as operation, etc.

Sanggyu Shin, Yoichi Seto, Mayumi Sasaki, Kei Sakamoto

Using a Fine-Grained Hybrid Feature for Malware Similarity Analysis

Nowadays, the dramatically increased malware causes severe challenges to computer security. Most emerging instances are variants of previously encountered malware through polymorphism and metamorphism techniques. The traditional signature-based detecting methods are ineffective to recognize the enormous variants. Malware similarity analysis has become the mainstream technique of identifying variants. However, most existing methods are either hard to handle polymorphic and metamorphic samples based on static structure feature, or time consuming and resource intensive by using dynamic behavior feature. In this paper, we propose a novel malware similarity analysis method based on a fine-grained hybrid feature by exploiting the complementary nature of static and dynamic analysis. We integrate dynamic runtime behavior with static function-call graph. The hybrid feature overcomes the limitation of using static and dynamic feature separately and with more accuracy. Furtherly, we use graph edit distance, and inexact graph matching algorithm as metric to measure the distance between malicious instances. We have evaluated our algorithm on real-world dataset and compared with other approach. The experiments demonstrate that our method achieves higher accuracy.

Jing Liu, Yongjun Wang, Peidai Xie, Xingkong Ma

A Wireless Kinect Sensor Network System for Virtual Reality Applications

Currently, Microsoft Kinect, a motion sensing input device, has been developed quickly in research for human gesture recognition. The Kinect integrating into games and Virtual Reality (VR) improves the immersion sense and natural user experience. However, the Kinect is able to accurately measure a user within five meters, while the user must face to the sensor. To solve this problem, this paper develops a wireless Kinect sensor network system to detect users at several viewports. This system utilizes multiple Kinect clients to sense user’s gesture information, which is transmitted to a VR managing server for the integration of the distributed sensing datasets. Different from the VR application with a single Kinect, our proposed system is able to support the user’s walking around no matter whether he is facing the sensors or not. Meanwhile, we developed a virtual boxing VR game with two Kinects, Samsung Gear VR and Unity3D environment, which verified the effective performance of the proposed system.

Mengxuan Li, Wei Song, Liang Song, Kaisi Huang, Yulong Xi, Kyungeun Cho

Finding Comfortable Settings of Snake Game Using Game Refinement Measurement

This paper explores the attractiveness and sophistication of Snake game which originated as an arcade maze game and has been very popular for the decades on mobile phones platform. It presents an approach to find comfortable settings of Snake game by using game refinement theory. Basic AI is created for collecting the data instead of human in this research. The results obtained show the reason why Snake game has been so popular on mobile phones and people can feel entertaining and excited.

Anunpattana Punyawee, Chetprayoon Panumate, Hiroyuki Iida

Code Modification and Obfuscation Detection Test Using Malicious Script Distributing Website Inspection Technology

The use of non-standard plug-ins has been unavoidable in existing HTML. Accordingly, the rising dependence of web content on plug-ins increased and need for additional development suited to platform incurred considerable developmental expenses and time. HTML5 was a suggested solution to this problem, but could cause new security threats through newly added technologies, meaning that web-related elements such as websites, web content, devices and others are exposed to a new type of threat. In this thesis, we suggest a technology to detect website security threats in advance that includes HTML5.

Seong-Min Park, Han-Chul Bae, Young-Tae Cha, Hwan-Kuk Kim

Initialization of Software Defined Wireless Bacteria-Inspired Network Platform

Fifth generation mobile network is a development trend for information and communication industry. In order to meet requirement which presented by some organizations which are working on 5 G standards and regulations, we had proposed a Software-Defined Wireless Bacteria-Inspired Network (SDWBIN) platform. In this paper, we will introduce how we initialize this prospective platform.

Shih-Yun Huang, Hsin-Hung Cho, Yu-Zen Wang, Timothy K. Shih, Han-Chieh Chao

An Extension of QSL for E-voting Systems

E-voting is an electronic way to provide voting processes beginning from preparing ballots, following by authenticating voters and candidate registrations, through casting votes, and ending to tallying and declaring collected answers. Nowadays, there are many kinds of e-voting systems implemented to provide e-voting services over the Internet. However, there is no ad hoc method to cover the gap caused by difficult communications. QSL is a specification language for e-questionnaire systems that serves as a communication tool for specifying e-questionnaires and e-questionnaire systems. QSL is an ideal candidate because of similar processes between e-questionnaire and e-voting. The current version of QSL is reckoned without e-voting and e-voting systems. This paper proposes an extension of QSL for specifying e-voting and e-voting systems, and presents two cases using QSL for e-voting systems to show its effectiveness.

Yuan Zhou, Hongbiao Gao, Jingde Cheng

Behavior-Based Detection for Malicious Script-Based Attack

Several DoS attacks have occurred through web browsers, not from malicious executable files. Most tools used in web attacks are downloaded malware. As the dynamic functions of HTML5 can be performed on a web browser, however, the latter can be abused as an attack tool. The features of web browser-based attacks are different from those of previous attacks, so a different detection method is needed for malicious behavior on web browsers. This paper introduces script-based attacks made through web browsers, and proposes a detection method based on a web browser’s behavior.

Soojin Yoon, Hyun-lock Choo, Hanchul Bae, Hwankuk Kim

The SP-tree: A Clustered Index Structure for Efficient Sequential Access

We introduce the SP-tree that is a variant of a multidimensional index structure, with the object of offering efficient sequential disk access. The SP-tree is based on the index clustering technique called the segment-page clustering (SP-clustering). Most relevant index pages are widely scattered on a disk due to dynamic page allocation, and thus many random disk accesses are required during the query processing. The SP-clustering avoids the scattering by storing the relevant nodes contiguously in a segment that contains a sequence of contiguous disk pages and improves the query performance by offering sequential disk access within a segment. Experimental results demonstrate that the SP-clustering improves the query performance up to several times compared with the traditional ones with respect to the total elapsed time.

Guang-Ho Cha

An Address Conflict Resolving Scheme of Inter-drone Ad Hoc Communications for Hide Densely Deployed Low Power Wide Area Networks

Most of many communication technologies employed address identification method but many of them have not presented appropriate solution in which communication nodes would be widely and densely deployed. In this case, manually assigned ID generation method can be aggravately inefficient where there can have heterogeneously manufactured devices. In swarm flight of drone environmet, it can be high probability that multiple drones which were individually manufactured by different manufactural companies can configured with the same ID values, however, there is nothing solution in the current standard specifications of ad hoc communications, representatively as IEEE 802.15.4 or Zigbee standard. In order to find practical solution on the real world, we present an appropriate solution for dynamic ID generation with low conflict probability and for detection and avoidance method of ID conflict.

Jaeho Lee, Bong-Ki Son

State-of-the-Art Algorithms for Mining Up-to-Date High Average-Utility Patterns

High average-utility pattern mining is an emerging issue in the association rule mining area due to its meaningful mining results reflecting the characteristics of items such as their importance and quantities, and consideration on lengths of patterns. Recently, various studies have been dedicated to the researches of mining methods that extract up-to-date patterns from stream data, which are continually generated from various sources without limitations. A sliding window technique is one of methods for handling such stream data and mining up-to-date patterns. In this paper, we introduce state-of-the-art algorithms for finding up-to-date high average-utility patterns over data stream by using the sliding window method.

Donggyu Kim, Unil Yun

Design of Shoot’em up Game Using OpenGL

The OpenGL is an Open Graphics Library developed for rendering 2D and 3D vector graphics. This library has been widely used in various areas such as game development, simulation, and visualization. In this paper, we aim to design a shooting simulation program with three objects based on the OpenGL. For this purpose, we analyze collision detection techniques that are an essential element in shooting game development and suggest an appropriate method.

Unil Yun, Heungmo Ryang

Performance Analysis of Tree-Based Algorithms for Incremental High Utility Pattern Mining

To overcome drawbacks of traditional pattern mining such as difficulty reflecting characteristics of real-world databases to pattern mining, high utility pattern mining has been proposed and researched. Since database sizes become larger incrementally in many real-world applications, there is a need of appropriate methods to deal with such databases for discovering useful information from them efficiently. For this purpose, various approaches have been suggested. In this paper, we compare and analyze algorithms for high utility pattern mining from dynamic databases by considering characteristics of incremental databases and utilizing tree-based data structures. Moreover, we study their characteristics and direction of improvements based on experimental results of performance evaluation.

Heungmo Ryang, Unil Yun

Development of 2D Side-Scrolling Running Game Using the Unity 3D Game Engine

The Unity 3D game engine, which can develop games on most platforms such as IOS, Android, and web browsers, is known for a tool easier to use than other engines. In this paper, we develop a game where a sheep runs away from the threat of a rancher on the basis of the Unity game engine. The game is developed in order that a player feels thrill and tension by manipulating the sheep to pass obstacles, avoid projectiles, and run away from the chasing owner.

Wooseong Jeong, Unil Yun

EPD Noticeboard for Posting Multiple Information

In this paper, we propose an EPD noticeboard for effectively managing notice objects from various users and minimizing power consumption. The system posts more important and newer information based on authority level of the user, posting term and priority of the notice object. Because noticeboard with EPD requires power supply when data is updated, the power consumption is relatively low compared to LCD or OLED based systems. We also present one example implementation for managing digitalized notice objects in Korean university. E-paper display is quite suitable to be used for applications requiring low power and mainly using image data. We expect that our study shall be applied to mobile billboards, label, post-it and so on.

Bong-Ki Son, Jaeho Lee

Design of Processing Model for Connected Car Data Using Big Data Technology

Recently, we have witnessed a period which things are connected to the Internet. Connected cars are currently among things connected to the Internet. Wireless communications technologies built-in or brought in connected cars enable data generated by in car sensors to be transmitted to external computers where it is analyzed. The main challenge for connected cars services providers is that the collection of same vehicle’s data such as engine temperature, engine Revolutions per minute (RPM), vehicle speed are subjected to different connected cars applications which the final purpose of each of them differs. This paper studies design steps to take in consideration when implementing Map Reduce patterns to analyze vehicle’s data in order to produce accurate useful outputs. These outputs obtained through big data technology forms a storage repository for the automakers and connect cars services providers. The proposed analytical model is based on a data-driven approach. This approach consists of collecting data sets uploaded from connected cars. Those data are then monitored based on different aspects of activity of the vehicles that we quote as “Events”. Hadoop supplements by Map-Reduce functions based reduce side joins with One-To-One joins has been deployed to process a large data and delivered useful outputs. The outputs merged with external information constitute a great insights to connected cars in order to afford connected cars applications.

Lionel Nkenyereye, Jong Wook Jang

Efficient Path Selection for IoT Devices in Heterogeneous Service Environments

Internet of Things (IoT) services are based on information of IoT devices adopted various sensors. The sensed data by the sensors of devices is delivered to a data server, which is placed in Cloud, for intelligent services. IoT devices serve heterogeneous services using the data. For the connectivity of the IoT devices, wireless sensor networks are exploited as an access network technology for the services. In the wireless sensor networks, energy efficiency is the important issue. Thus, the efficient path selection should be considered. Data transmission in heterogeneous service environments employs aggregation and piggybacking functions. To maximize the energy efficiency, the functions are properly used for data delivery. In this paper, similarity of transmission data in devices is exploited. By the similarity value, the efficient path is selected and one of the functions is used. That is, this paper proposes the path selection to mainly use the aggregation function by high similarity in order to obtain the energy efficiency.

Dae-Young Kim, Seokhoon Kim

Forecasting Sugarcane Yield Using (μ+λ) Adaptive Evolution Strategies

Sugarcane is a very important crop in the sugar industry. However, the annual amount of harvested sugarcane is oftentimes uncertain, posing risks to sugarcane mills in terms of raw material supply. The forecast for the sugarcane yield would allow the mills to plan sugar production accordingly. This paper proposes (μ+λ) adaptive evolution strategies, which generate equations for accurately forecasting the sugarcane yield. Our proposed scheme combines the advantages of two algorithms: genetic algorithm and evolution strategies. Specifically, the genetic algorithm is good for determining patterns of forecasting equations, while the evolution strategies are used to tune the equations’ coefficients. The test data is collected from sugarcane farmers in 24 provinces of Thailand during 2010–2014. The equations obtained by the proposed method are 80 % accurate on average, outperforming the previous method (back propagation neural network) in all data set.

Supawadee Srikamdee, Sunisa Rimcharoen, Nutthanon Leelathakul

Resource Pooling Mechanism for Mobile Cloud Computing Service

Cloud computing services enable virtual services with physical resources consisting of workstations and clusters having storages, processes, and memories. Unlike general resources, mobile devices have such features as miniaturized hardware, embedded sensors, and touch screen. Furthermore, mobile devices have mobility and portability which are lacking in general workstations and clusters. Mobile cloud computing services organize physical resources with mobile devices which have low hardware performance and are sporadically connected to the network. Therefore, it is difficult to integrate resources if they are organized as in general cloud computing services. Resource pooling management is required to manage and provide the resources of mobile devices dynamically in an integrated manner and provide them to users without work loss. This research proposes Mobile Resource Integration – Manager (MRI-M) which checks and manages the resource status of mobile devices in mobile cloud computing services and considers the organization of resource pooling.

Seok-Hyeon Han, Hyun-Woo Kim, Young-Sik Jeong

IPC Multi-label Classification Applying the Characteristics of Patent Documents

Most of research on the IPC automatic classification system has focused on applying various existing machine learning methods to the patent documents rather than considering the characteristics of the data or the structure of the patent documents. This paper, therefore, proposes using two structural fields, a technical field and a background field which are selected by applying the characteristics of patent documents and the role of the structural fields. A multi-label classification model is also constructed to reflect that a patent document could have multiple IPCs and to classify patent documents at an IPC subclass level comprised of 630 categories. The effects of the structural fields of the patent documents are examined using 564,793 registered patents in Korea. An 87.2 % precision rate is obtained when using the two fields mainly. From this sequence, it is verified that the technical field and background field play an important role in improving the precision of IPC multi-label classification at the IPC subclass level.

Sora Lim, YongJin Kwon

A Comparison of Data Mining Methods in Analyzing Educational Data

Although data mining has been considered as a silver bullet which magically extracts valuable information from the stacked and unused data, its too many methods frequently confuse and mislead researchers. Therefore, in order to get a satisfying result, researchers need plenty of experience to choose a proper data mining method suitable to the purpose of their research. Unfortunately, in the education field, there are a few studies to point out this problem. In order to resolve this issue, in this paper, a study was conducted to compare Neural Network, Logistic Regression, and Decision Tree on educational data from Korea Youth Panel Survey (KYPS). The result showed the prediction accuracies of the methods were meaningfully different, but it doesn’t mean that the prediction accuracy is the only factor in decision of a specific method. Rather, the result suggested that researchers should consider various aspects of the methods to choose a specific method because each method has its own pros and cons.

Euihyun Jung

A New Secure Android Model Based on Privilege

Android is the most popular smartphone operating system in the world. There are many people who focus on Android security and dedicated to improve android security. There are many android vulnerabilities exposed online and attackers can use these vulnerabilities to steal our private and sensitive information and attack our device. In the paper, we propose a novel secure android model based on privilege. We create three kinds of users and grant different users different permissions. Thus, users can have more freedom and control over their android device in the model we proposed. In our secure model, users can upgrade their android operating system in time, which may enhance the security of their smartphones and protect users’ sensitive information better.

Tao Zhang, Zhilong Wang

Survey of MCC Architectures for Computing Service

Following the growth of mobile device applications in the past years, mobile computing and cloud computing are suggesting a new computing paradigm. Demands for computing capability regarding potential technologies that are provided as mobile service are also growing. Meanwhile, necessity of Mobile cloud computing (MCC) is increasing due to the problems of mobile devices, such as resource poverty, battery constraint. However, clear definition is required as the concept of MCC is still ambiguous. Currently, it is necessary to classify the configuration methods of the resource-providing infrastructure environment of MCC. This paper provides a comprehensive overview of MCC and proposes a basic scheme. We suggest instance MCC (iMCC), which is a framework implementing offloading for the purpose of achieving efficient computing process and service provision. iMCC includes improved resource allocation method in MCC infrastructure as well as efficient offloading method. Finally, we summarize the conclusion and discuss future research.

Byeong-Seok Park, Yoon-A Heo, Young-Sik Jeong

Measurement of Enterprise Smart Business Capability in a Global Management Environment

Enterprises are endeavoring to effectively apply smart business technology to their management activities in order to raise their business results in a smart business environment. Enterprise’s smart business capability is very critical for the efficient execution of its management activities and to improve the performance of business tasks in a global management environment. An efficient measurement framework is necessary for efficiently measuring a firm’s smart business capability to manage and improve its smart business capability. The developed 12-item scale was verified based on previous literature. We found a 12-item framework that can reasonably gauge an enterprise smart business capability. This framework can be used for efficiently measuring a firm’s smart business capability in a comprehensive perspective.

Chui Young Yoon

Occluded Pedestrian Classification Using Gradient Patch and Convolutional Neural Networks

Occlusion handling has been an important topic in pedestrian recognition. This paper proposed new approach for occlusion handling by Gradient Patch and Convolutional Neural Network (CNN). There are several researches of occlusion handling use parts annotations or manual labeling of body parts. However our method is learning partial features without any prior knowledge. Our model is trained parts detector with multiple of partial features that selected by gradient patch. Gradient patch compute the orientation of the edge in sub-region and find the extra partial features along the edge directions. Our experiments represented the effectiveness of Gradient Patch for occlusion handling in the INRIA and Daimler pedestrian dataset.

Sangyoon Kim, Moonhyun Kim

A Design of Secure Authentication Method with Bio-Information in the Car Sharing Environment

Car sharing services have become a new form of public transport after the financial crisis as consumers’ perceptions changed and their consciousness about environmental preservation and smart phone penetration increased. Countries overseas have already seen these services catch on with many users. In Korea, too, a pilot operation started in 2013 and now car sharing services boast about 200,000 members. Although the market evolved with many users, the security part is lagging behind. To rent a car, you only need to log in and you can use a smart key to open the car door and drive it. Since the simple ID/PW authentication method has many issues, a stronger authentication is needed to offer reliable services.

Sang-Hyeon Park, Jeong-Ho Kim, Moon-Seog Jun

A Design of Certificateless-Based Device Authentication Scheme in the SmartHome Environment

Recently, the wireless communication technology and sensor devices are utilized in many fields with smart-home market growth. The IoT environment collects various and vast range of device information for intelligent service, provides service based on user information, controls devices, and utilizes dissimilar devices. However, along with the development, the security threat in smart-home environment occurs frequently. In reality, the proof point and HP published the seriousness of weak security and damage cases in smart-home environment. Therefore, this study proposes smart node and certification method based on Certificateless signcryption between smart devices for remote control to solve the security problem occurring in smart-home environment.

Jae Seung Lee, Jaehwa Chung, Sangkee Suk

A Design of Secure Authentication Method Using Zero Knowledge Proof in Smart-Home Environment

As the IoT technology is being changed, diverse services are being developed. The smart home environment, which is the representative IoT technology, is facilitating the life more convenient and the smart home market is emerged rapidly while the IoT technologies are applied, but when authenticating in smart home network, the authentication should be made using the secret key of the node. In the smart home network environment, the more the nodes are increased, the more the burden of home gateway to manage the secret key of the nodes is increased. To solve this problem, this study suggests secure and efficient authentication technique through the zero-knowledge proof without using the secret key between the node and the home gateway.

Geunil Park, Bumryoung Kim, Moon-seog Jun

Drone Classification by Available Control Distances

A drone industry which started for military purposes is growing and are being spread in the private market as ICT technologies are developing. For example, it includes various industries such as leisure, construction, delivery, military, etc. and there are plenty of pioneer areas for future. However the researches for future drone developments have some challenges because there are no standards for drone developments, so the environment should be provided to develop and design them properly. This paper categorizes various purpose drones into 3 kinds of control distances by features, so it will help future drone development researches.

Mansik Kim, Hyungjoo Kim, Jungho Kang, Jaesoo Kim

A Design of Key Agreement Scheme Between Lightweight Devices in IoT Environment

The IoT (Internet of Things) environment develops in which all the necessary information among things is exchanged due to the development of information and communications. The home IoT continuously develops, because of a merit that a user can control the home IoT remotely in the IoT environment. As the home IoT environment is built, communications using low specification devices, as well as high specifications devices, also increase. For safety communications in the home IoT environment, encryption algorithms, such as RSA providing message encryption and authorization, are required. However, they are difficult to be used for the low specification devices, where calculation function is limited in the home IoT environment. This study actually proposes the protocol by which low power and low specification devices communicate with user’s smart devices through safe authorization procedure in the home IoT environment. The protocol proposed in this paper has a merit that it is safe, and it protects the re-use attack and middle attack.

Hague-Chung, Keun-Chang Choi, Moon-Seog Jun

Platform Independent Workflow Mechanism for Bigdata Analytics

The present paper allows to platform independent process based Workflow mechanism for big-data analytics. The Bigdata Workflow Tool is to provide a system and a method for data analysis services which is able to select data corresponding to a user requirement and an analysis algorithm which is able to analyze the data and let an analysis service selected by the user among a plurality of analysis services be automatically performed in a big data platform. A system and method for combining a workflow is provided. This paper is directed to a system and method for combining a workflow capable of providing a big data analysis more easily and rapidly and recognizing an analysis flow more easily by combining a model-based workflow.

Tai-Yeon Ku, Hee-Sun Won, Hoon Choi

Water Surface Simulation Based on Perlin Noise and Secondary Distorted Textures

Simulation of water surface is an important topic in computer graphic. In this paper we propose a fast method to simulate the reflection and refraction of water surface in high quality based on Perlin noise. This method generates the first reflect mapping through mirror reflect. Then the Perlin noise is used to distort the first texture map to generate the secondary reflect mapping which is prospectively projected onto the final surface. Experiment results show that our method can generate high quality reflection with fewer artifacts of reflection.

Hua Li, Huamin Yang, Chao Xu, Yuling Cao

Optimization for Particle Filter-Based Object Tracking in Embedded Systems Using Parallel Programming

Object tracking is a common task in computer vision, an essential part of various vision-based applications. After several years of development, object tracking in video is still a challenging problem because of various visual properties of objects and surrounding environment. Particle filter is a well-known technique among common approaches, has been proven its effectiveness in dealing with difficulties in object tracking. In this research, we develop an particle filter-based object tracking method using color distributions as features. Moreover, recently embedded systems have become popular because of the rising demand of portable, low-power devices. Therefore, we also try to deploy the particle filter-based object tracker in an embedded system. Because particle filter is a high-complexity algorithm, we will utilize computing power of embedded systems by implementing a parallel version of the algorithm. The experimental results show that parallelization can increase performance of particle filter when deployed in embedded systems.

Mai Thanh Nhat Truong, Sanghoon Kim

Generalized Multi-linear Mixed Effects Model

Recently, many applications tend to find common and distinctive features from a group of datasets, of which distributions and structures are generally various. However, most existing methods can just cope with specific problems with fixed distributions and structures. In this paper, a more flexible framework for multi-block data learning is proposed. There are mainly two advantages compared with previous methods: (a) the proposed method can extract global common, local common, and distinctive features automatically; (b) various distributed datasets can be processed simultaneously as long as distributions are in exponential family. The results of numerical experiments demonstrate that the proposed method outperforms conventional methods for recommendation system problems.

Chao Li, Lili Guo, Zheng Dou, Guangzhen Si, Chunmei Li

Anomaly Detection of Spectrum in Wireless Communication via Deep Autoencoder

Anomaly detection has been a typical task in many fields, as well as spectrum monitoring in wireless communication. In this paper, we apply a deep-structure autoencoder neural network to spectrum anomaly detection, and the time-frequency diagram is used as the feature of the learning model. In order to evaluate the performance of the model, the accuracy of the output is considered. We compare the performance of both our proposed model and conventional one-layer autoencoder. The results of numerical experiments illustrate that our model outperforms the one-layer autoencoder based method.

Qingsong Feng, Zheng Dou, Chunmei Li, Guangzhen Si

A Modified Complex ICA for Blind Source Separation and the Application in Communication Reconnaissance

This paper proposes a modified complex ICA algorithm for blind source separation and we apply it in the field of communication reconnaissance. First, Generalized Information Criterion (GIC) and Minimum Description Length (MDL) are used to estimate source signals number. Second, we propose a novel complex independent component analysis (Improved TCMN). The innovation appears in the whitening pre-treatment of TCMN by using the number estimation result of source signals. Finally, this paper gives an application in communication reconnaissance system. Simulation results demonstrate the effectiveness of the new method.

Zheng Dou, Zi Xiao, Yang Zhao, Jinyu Wang

Sensor Coverage Problem in Sparse MANET Environments

In this paper, we define the problem of sensor coverage in sparse mobile ad hoc networks. Previously, the nodes are assumed static or the number of nodes is large enough to cover the area for the coverage problem in wireless sensor networks. However, in sparse mobile ad hoc network environments, the semantics of the coverage problem differ in that the nodes are free to move in the area and the distance between the nodes should be long enough in order not to overlap the nodes’ coverage to maximize the total coverage area in the network. We formulate the sensor coverage problem in sparse mobile ad hoc network environments.

JongBeom Lim, HeonChang Yu, JoonMin Gil

Design of Jitter Buffer Control Algorithm for Guaranteeing the Medical Information Data Transmission Quality in Wireless Network Environment

Telemedicine that reduces the time and spatial restrictions on healthcare is expected to be broadly activated due to the recent development of ICT convergence technologies. The VoIP technology is being used for data transfer in the telemedicine environment. In the IP network that uses the packet exchange method, however, problems of delay, jitter, and packet loss, among others, are occurring. Therefore, the condition of the VoIP network was predicted in this study using a network condition prediction algorithm. A VoIP-based dynamic jitter buffer control algorithm that addresses transfer quality problems through dynamic jitter buffer control was proposed.

Dong-Wan Joe, Jae-Sung Shim, Yong-Wan Ju, Seok-Cheon Park

Student’s-t Mixture Model Based Excepted Patch Log Likelihood Method for Image Denoising

Recently, patch priors based image denoising method has received much attention in recent years. Expected patch log likelihood (EPLL) is a popular method with the patch priors for image denoising, which achieves image noise removal using the Gaussian mixture priors learned by the Gaussian mixture model (GMM). In this paper, with observation that the student’s-t distribution has a heavy tail and is robust to noise compared with the GMM, we attempt to learn image patch priors using the student’s-t mixture model (SMM), which is an extension of the GMM. Experiment results demonstrate that our proposed method performs an improvement than the original EPLL.

J. W. Zhang, J. Liu, Y. H. Zheng, J. Wang

Regularization Parameter Selection for Gaussian Mixture Model Based Image Denoising Method

Regularization parameter selection for image denoising has always been a hot issue. In this paper, an adaptive regularization parameter selection method is exploited for the Gaussian Mixture Model (GMM) based image restoration by combining the gradient matching and the local entropy of the image, which varies with different regions of the image and has a good robustness to noise. Experiment results demonstrate that our proposed adaptive regularization parameter for GMM based image restoration method performs comparatively well, both in visual effects and quantitative evaluations.

J. W. Zhang, J. Liu, Y. H. Zheng, J. Wang

Restoration Method for Satellite Image Based on Content-Aware Reciprocal Cell Pool

The challenge for the VHR satellite image restoration is how to cope with the simultaneous deblurring and denoising problem. Although the adaptive reciprocal cell (AR-cell) can be used to suppress noise in image restoration, it is an isotropic linear filter. In this letter, we analyze the AR-cell model, and then a piecewise linear version is developed to adapt to different similar image structures, giving rise to an AR-cell bank. Lastly, based on the bank, a group-wise regularization model is introduced for image restoration. Experimental results demonstrate the promising performance of the proposed method.

Yuhui Zheng, Xiaozhou Zhou, Tong Li, Jin Wang

Student’s-t Mixture Model Based Image Denoising Method with Gradient Fidelity Term

The mixture models based structured sparse representation (MM-SSR) method has received much attention in recent years. Especially, the student’s-t mixture model based structured sparse representation (SMM-SSR) has been widely used due to the fact that it has a heavy tail and is robust to noise. In this paper, for further enhancing the performance of SMM-SSR, we attempt to incorporate the gradient fidelity term with the student’s-t mixture model for image denoising. Experiment results show that our proposed method outperforms the traditional SMM-SSR method.

J. W. Zhang, J. Liu, Y. H. Zheng, J. Wang

Classification Algorithms for Privacy Preserving in Data Mining: A Survey

In the wake of the development in science and technology, consumer or user has produced a large quantity of the information source, whether it is the mobile terminals or the client terminals. When face with such enormous data volume, some people discover the value of the data information for data mining. There are others who initiate be afraid to their privacy information learned or obtained by adversary during data propagation. On top of this, more and more people have undergone threaten of sensitive information loss exactly. Some of them, not only damnify the reputation, but also lose the benefit. Now the challenge is how to balance the security of data and the validity of it. Recently, a large amount of classification algorithms have been applied to process the data to protect data privacy and practicability, such as decision tree, Bayesian networks, support vector machine. In this paper, we overview the learning classification algorithms for privacy preserving in data mining, then make some description with the methods, function, performance evaluation.

Sai Ji, Zhen Wang, Qi Liu, Xiaodong Liu

Exploiting Group Signature to Implement User Authentication in Cloud Computing

Cloud computing is a technology which is developed from the distributed computing. The cloud server provider gathers the redundant storage and computing resource to realize the goal of providing scalable computing resources to consumers. The infrastructures of the cloud computing are virtualized and they can be considered infinite. Therefore, the user side does not need to consider the local storage and computing resource. However, the cloud services are provided by the third party. As a general rule, the user who stores the data in the cloud is not safe. The security of the data is really concerned by the user. In other words, the cloud is interested in the data. We proposed a scheme that can support cloud user’s identity authentication, which is based on the group signature. From the security analysis, our scheme can resist some possible attacks.

Sai Ji, Dengzhi Liu, Jian Shen

A Secure System Framework for an Agricultural IoT Application

The applications of Internet of Things (IoT) permeate to every walk of life due to the development of cheap and efficient electronic components and the increasingly ubiquitous network. Thus it is possible to apply the IoT technologies into agriculture commencing an automated farming method. This paper proposes an IoT framework that can be used to assist in traditional agricultural planting. It integrates two major functions including environment data sensing by a wide variety of sensors and environment factors control with some mechanics driven by intelligent circuits. For example, soil moisture can be monitored and controlled by turning on/off sprinkling irrigation equipment when monitored factors are out of a certain range. In addition, this framework is realized at low cost and easy to deploy. A light-weight data encryption transmission solution based on SSL at the TCP/IP layer is designed to ensure the security of data transmission. A practical testbed based on Ali-Cloud is established to carry huge load of communication and data from an actual deployed agricultural IoT application.

Hao Wu, Fangpeng Chen, Hanfeng Hu, Qi Liu, Sai Ji

Localization Technology in Wireless Sensor Networks Using RSSI and LQI: A Survey

For Wireless Sensor Networks (WSN), low-cost precise localization is the most essential requirement. Localization techniques based on RSSI is cost effective when be in comparison with TDOA, TOA and AOA. Because it doesn’t need any extra power, hardware or bandwidth. In this paper, we simply introduce some related theory and techniques, such as TDOA, TOA and AOA in Wireless Sensor Networks. Localization error can be declined by observing both RSSI and LQI at the same time. We survey a dynamic distance estimation method based on RSSI and LQI, and present a comparison of some algorithms based on the theory. By analyzing the model of radio wave propagation loss and empirical data from real measurement, the method is to use discrete linear lines to approximate the real attenuation of RSSI and LQI.

Sai Ji, Dengzhi Liu, Jian Shen

Energy-Balanced Unequal Clustering Routing Algorithm for Wireless Sensor Networks

In wireless sensor networks (WSNs), the clustering routing technology can improve the scalability of the network. When the cluster head transmits data to the base station in a multi hop manner, the residual energy of cluster head and path condition are not considered. So it can reduce the lifetime of cluster head and seriously affect the network lifetime. We propose an energy-balanced unequal clustering routing algorithm for wireless sensor networks. Firstly, the non-uniform clustering method is applied to the network. Secondly when calculating the cluster radius, the residual energy of nodes, the density of nodes and the distances between the nodes and base station will be taken into account. Then, the algorithm establishes the shortest path tree to search the optimal multi-hop transmission paths to realize efficient data transmission from sensor nodes to base station. Simulation results demonstrate that the improved algorithm can efficiently decrease the dead speed of the nodes, balance the energy dissipation of all nodes, and prolong the network lifetime.

Jin Wang, Yiquan Cao, Jiayi Cao, Huan Ji, Xiaofeng Yu

The Agent Communication Simulation Based on the Ego State Model of Transactional Analysis

Inter-agent interaction plays an important role in cyberspace, which has recently been receiving attention as a space for social interaction. These interactions can occur between agents as well as between agents and people. However, for this, agents must be developed to the extent that they do not differ noticeably from human beings; that is, computers must be able to exhibit the same behaviors as humans. To achieve this, we developed a simulation in which human communication is replaced by a card game that corresponds to the ego state model of transactional analysis (TA). The agent communication module that we developed expresses agent-agent transactions based on the ego state model, as adapted to computer agents. The agents, the attacker and defender, continue the simulation with the cards that have messages and personalities. To win this simulation, the agents should find out their opponent’s intentions and show a card that is suitable for their opponent’s sample word or personality.

Mi-Sun Kim, Green Bang, Il-Ju Ko

Design of Software Reliability Test Architecture for the Connected Car

Recently, the connected car is one of the hot topic in related business and industry. Although there have been many technical problems up to now, the evolution of various technologies has been resolved them. However, the software reliability and its test method in the connected car fields is very inadequate, because it is in the infancy step. To solve this problem, we propose the software reliability test architecture which can be applied to the connected car software. The proposed software reliability test architecture is designed to satisfy to 6 features which are functionality, reliability, usability, efficiency, maintainability, and portability. Based on this architecture, the software reliability test for a connected car can be used to verify a software, which is adapted to the connected car. In addition, the proposed test architecture can be supported or utilized a formal test procedure to the software in the connected car.

Doo-soon Park, Seokhoon Kim

Network Activation Control According to Traffic Characteristics in Sensor Networks for IoT

Sensor networks are an important technology for Internet of Things (IoT) connectivity. Sensor networks consists of numerous objects and the objects named sensor nodes collect information in access networks of IoT. They are transmitted the information to a network server which is placed in Cloud. In the sensor field (i.e., the access network of IoT), there are three kinds of traffic can be generated: event-driven, query-driven and periodic traffic. The traffic is classified and analyzed at the network server. The most of monitoring applications for IoT employs cluster-based network architecture. Each cluster gathers local sensing data and traffic characteristic of clusters is determined by the collected local data. This paper proposes network activation control of the clusters according to the traffic characteristic in order to minimize power consumption of sensor networks.

Dae-Young Kim, Young-Sik Jeong, Seokhoon Kim

Data Mining Techniques to Facilitate Digital Forensics Investigations

Digital forensics is an essential discipline for both law enforcement agencies and businesses. It makes possible to investigate electronic related crimes aka cybercrime such as fraud, industrial espionage and computer misuse. However, encryption, anti-forensic tools and the ever increasing amount of volume of data to analyse creates a wide range of challenges to overcome. Fortunately, other computer fields can be applied to overcome those challenges. This paper will explore some data mining techniques to address most common issues in Digital Forensics.

Erik Miranda Lopez, Yoon Ho Kim, Jong Hyuk Park

Solving Standard Cell Placement Problem Using Discrete Firefly Algorithm: A Nature Inspired Approach

Standard Cell Placement is a vital step in the digital circuit layout that allots positions for several circuit components within the chip’s core region. Placement problem has drawn broad explores tending in the VLSI CAD domain. The purpose of this research is to present a discrete approach based on firefly algorithm for standard cell placement problem. The results show that the proposed DFCP approach are better than mete genetic approach for the placement instances of MCNC benchmark. The research testifies that the DFCP approach provides effective cell locations, giving a super-ordinate performance in terms of time and quality of the solution.

Pradip Kumar Sharma, Saurabh Singh, Jong Hyuk Park

A Security Model for Protecting Virtualization in Cloud Computing

Virtualization is the key component of cloud computing that refers to the abstraction of sharing resources. The basic idea is to implement the virtualization in cloud computing environment because of its flexibility, scalability, its cost-reducing and resource utilization. Instead of many good attributes virtualization still facing with security flaws like availability, mutual authentication, potential attack in the virtual network, DoS attack on virtual servers and storage also. In the paper, we propose a general security model to protect the virtual environment and also discuss the flow of data which is monitored by hypervisors.

Saurabh Singh, Pradip Kumar Sharma, Jong Hyuk Park

Effective Pre-processing Methods with DTG Big Data by Using MapReduce Techniques

A huge amount of sensing data is generated by a large number of pervasive IoT devices. In order to find a meaningful information from the big data, pre-processing is essential, in which many outlier data need to be removed because those are deteriorated as time passes. In this paper, big data pre-processing methods are investigated and proposed. To evaluate the pre-processing methods for accurate analysis, we use collection of digital tachograph (DTG) data. We obtained DTG sensing data of six-thousand driving vehicles over a year. We studied five kinds of pre-processing methods: filtering ranges, excluding meaningless values, comparing filters from variables, applying statistical techniques, and finding driving patterns. In addition, we developed MapReduce programming using a Hadoop ecosystem, and deployed a big data to perform pre-processing analysis. Out of the pre-processing steps, we confirmed the proportion of DTG sensing data including any errors is up to 27.09 %. In addition, we approved that outlier data can be well detected, which is difficult to detect through simple range error pre-processing.

Wonhee Cho, Eunmi Choi

Security Requirements and Countermeasures for Secure Home Network in Internet of Things

The home network share the data with each other to configure a network after connecting many devices that wired or wireless in the home. Recently the home network has increased as internet of things service extension. But this is not achieved strong security because due to this, each device has the function deterioration problem in home network. Therefore it is necessary to determine the wired or wireless network security vulnerabilities and countermeasures to prevention for cybercrime privacy leakage. In this paper analyzes the factors of home network vulnerabilities and middleware security in internet of things. Also it presents a security vulnerability improvement.

Seo Yeon Moon, Saurabh Singh, Jong Hyuk Park

Machine Learning for Trajectory Generation of Multiple-pedestrians

In this paper, we provide an algorithm for generating a trajectory in real time to identify the pedestrians. Typically, the contours for the extraction of pedestrians from the foreground of images are not clear due to factors including brightness and shade; furthermore, pedestrians move in different directions and interact with each other. These issues mean that the identification of pedestrians and the generation of trajectories are somewhat difficult. We propose a new method for trajectory generation regarding multiple pedestrians. The first stage of the method distinguishes between those pedestrian blob situations that need to be merged and those that require splitting, followed by the use of trained decision trees to separate the pedestrians. The second stage generates the trajectories of each pedestrian by using the point-correspondence method; however, we introduce a new point correspondence algorithm for which the A* search method has been modified. By using fuzzy membership functions, a heuristic evaluation of the correspondence between the blobs was also conducted. The proposed method was implemented and tested with the PETS 2009 dataset to show an effective multiple-pedestrian-tracking capability in a pedestrian interaction environment.

Hye-Yeon Yu, Young-Nam Kim, Moon-Hyun Kim

A Deep Learning-Based Gait Posture Recognition from Depth Information for Smart Home Applications

Gait posture recognition at smart environment is considered as a primary function of the smart healthcare nowadays. The significance of gait posture recognition is great especially for the elderly as it is one of the basic activities to promote and preserve their health. In this work, a novel method is proposed for gait posture recognition that utilizes Local Directional Patterns (LDP) for the local feature extraction of depth silhouettes. Then, DBN is trained to be applied for the posture recognition later. The proposed approach shows superior recognition performance over other traditional methods of gait posture recognition.

Md. Zia Uddin, Mi Ryang Kim

Implementation of an Image Restoration with Block Iteration Method for Spatially Variant Blur Models

In image restoration, for spatially variant blur, block-wise iterative method have been proposed. Block-wise iterative method is based on the assumption that the blur approximates to spatially invariant in a small region of the blurred images. These approaches show approximation errors and block artifacts. In this work, we suggest to use block iterative method without approximates to spatially invariant blur considering arbitrary shaped blocks related to shapes of blur models. We can reduce the approximation errors and block artifacts with high speed of iteration convergence. This proposed image restoration method can reduce the computational efforts and is useful to embedded system such as mobile phone and embedded vision system.

Ji Yeon Lee, Kuk Won Ko, Sangjoon Lee

Analysis of Hard Shadow Anti-aliasing

Shadows are essential elements in computer-generated scenes. Shadow mapping is one of the most popular techniques for rendering shadows in real-time applications which is widely supported in current graphics hardware with its flexibility independence to the complexity of the scene. However, the standard shadow maps suffer from aliasing artifacts due to finite resolution and bias problems. In this paper, we survey the most promising research results that have been achieved recently and conclude by discussing some of the most important challenges of shadow aliasing.

Hua Li, Yuling Cao, Xin Feng

Cascade-Adaboost for Pedestrian Detection Using HOG and Combined Features

Over the recent years, pedestrian detection beings in a video surveillance system is attracting more attention due to its wide range of applications. In this paper, we propose an efficient two-phase pedestrian detector using HOG and combined features. The detector finds pedestrian candidate regions with a cascade-adaboost on HOG features. It then verifies each candidate using a combined features, which is local (SURF) and global features (RGB histogram), and then a classification based on MLP. It obtains a better detection rate and false-positive rate. The pedestrian detection system experimented with PETS 2009 dataset proves the effectiveness of our detection model.

Gyujin Jang, Jinhee Park, Moonhyun Kim

Portable Hypervisor Design for Commercial 64-Bit Android Devices Supporting 32-Bit Compatible Mode

We present a hypervisor design that can be applied to any commercial 64-bit Android devices without support of set makers. We achieved the portability by using pure software virtualization while preserving high performance. The contribution of the design is to put the guest OS and the hypervisor together into a single address space which results in avoiding the address space compression problem and reducing major virtualization costs, using 32-bit compatible mode. The design using the single address space makes the hypervisor simple and run fast even with pure software technologies. Prototypical implementation of the design is composed of one kernel module and one user-level program managing virtual machines for Android OS. We have evaluated our design on a commercial mobile phone, Nexus 6P. Since any Android device allows inserting kernel modules and installing user programs on it, we think that our hypervisor can be utilized on any 64-bit ARM-based mobile phones.

Kangho Kim, Kwangwon Koh, Seunghyub Jeon, Sungin Jung

Concept-Based Compound Keyword Extraction Based on Using Sentential Distance, Conceptual Distance and Production Rules: Calculation of the Keyword Importance

Humans can read a document and conceptually organize its contents into few compound keywords that capture the essence of the topic of a document. Based on this information, this study proposes a method for extracting keywords that gives the gist of a document. It uses a set of academic papers as test data to set up a concept-based production rule for forming compound keywords even when author-provided keywords do not appear in the text body of a document. It also proposes a method of calculating the importance of keyword in order to refrain from extracting meaningless keywords. Also the validity of extracted keywords was tested using a data set of thesis paper titles and summaries in the field of natural language processing and speech recognition. Comparison of the author-provided keywords to the keyword results of the developed system showed that the developed system was very useful with an accuracy rate as good as up to 96 %.

Samuel Sangkon Lee

Coarse-Grained 2.5-D CSAMT Parallel Inversion Method Based on Multi-core CPU

In this paper, a 2.5-D controlled source audio-frequency magnetotelluric (CSAMT) reversed parallel method based on multi-core CPU is achieved, aiming to the low efficiency of the large-scale computation in geophysical exploration. This parallel algorithm allocates the different waves to each thread of cores under the coarse-gained mode. The master thread deal with all parallel tasks and other slave threads compute the electromagnetic field values of each wave in parallel Fork-join model. The experiments demonstrate that our parallel algorithm can not only acquire the effective data accuracy, but also obtain about three times than the serial version.

Lili He, Hongtao Bai, Jin Wang, Yu Jiang, Tonglin Li

Virtual Force and Glowworm Swarm Optimization Based Node Deployment Strategy for WSNs

Wireless Sensor Networks (WSNs) can be viewed as a network with hundreds or thousands of randomly deployed sensors, whose coverage control problem has the characteristics of self-organized groups. This paper studies the coverage optimization strategy based on swarm intelligence for wireless sensor networks. In WSNs, the random deployment of nodes causes the coverage of the blind area and the redundancy of the coverage. We propose a new algorithm based on virtual force and glowworm swarm optimization algorithm. Firstly, the utilization rate of the nodes and the effective coverage of the network are the optimization objectives and the corresponding mathematical model is established. Then, the virtual force algorithm and the glowworm swarm optimization algorithm are used to solve the problem of modeling, and the optimal coverage scheme for WSNs is obtained. Simulation results show that the virtual force and glowworm swarm optimization algorithm can effectively improve the coverage of WSNs nodes, reduce the redundancy of sensor nodes, and reduce the cost of network effectively. Besides, the network survival time can get prolonged.

Jin Wang, Yiquan Cao, Jiayi Cao, Huan Ji, Xiaofeng Yu

Comparison with Recommendation Algorithm Based on Random Forest Model

Product recommendation based on user behavior is a hot research topic In the Internet era in the same data set, the features that the results of the various classifications are a greater difference were handled with random forest model. This paper compares the mainstream classification algorithm C4.5 and CART and analyzes 578,906,480 user behavior records on the results of actual transaction in Alibaba. The results show that CART decision tree algorithm is more suitable for large e-commerce data mining.

Yu Jiang, Lili He, Yan Gao, Kai Wang, Chengquan Hu

Risk Factors and the Difference Among Hypertension, Diabetes and Heart Disease

To investigate the prevalence of hypertension, diabetes and heart disease in the Jilin province of northeast of China and the association with biochemical targets and lifestyles. Subjects and methods: A community-based survey of 5953 adults through 2015 was following a crossing subject on the Chronic Disease Risk Factor Surveillance of China by stepwise. The characteristics are collected by one-to-one interview. Binary logistic regression analysis is conducted to explore the independent factors of the three diseases separately. Results: Prevalence of hypertension, heart disease and diabetes in the northeast of China was 16.1 %, 8.3 % and 5.0 % respectively. Family history and sleep time were independently associated with both hypertension (paternal OR = 2.37, 95 % CI: 1.96–2.79; maternal OR = 1.95, 95 % CI: 1.64–2.31; sleep time OR = 1.24, 95 % CI: 1.11–1.40) and heart disease (paternal OR = 2.20, 95 % CI: 1.72–2.83; maternal OR = 2.82, 95 % CI: 2.25–3.53; sleep time OR = 1.24, 95 % CI: 1.07–1.43). The prevalence of hypertension (OR: 0.68, 95 % CI: 0.55–0.83) and diabetes (OR: 0.67, 95 % CI: 0.50–0.92) in female was lower. Conclusions: Modifiable health risk behaviours are essential for preventing a series of chronic diseases, especially to the people of old age with family history.

Xue Wang, Lili He, Hongtao Bai

Linear Programming Computation Model Based on DPVM

Matrix manipulation of Linear Programming (LP) problems is a performance bottleneck in Single Instruction Single Data (SIMD) pattern. While, GPU is specialized for this compute-intensive and highly parallel computation, which is exactly what graphics rendering is about, due to the Single Instruction Multiple Data (SIMD) architecture. This paper introduces a Revised Simplex Method (RSM) on a GPU–Data Parallel Virtual Machine (DPVM). It assigns different routines for CPU and GPU according to respective characteristics: Iteration control and minimum value obtained are completed by CPU and Matrix multiplication by DPVM. In detail, we carefully organize the data as 4-channel textures, and efficiently implement the computation using Fetch4 technology of pixel shader. Numerical experiments are presented to verify the practical value and performance of this algorithm. The results are very promising. In particular, they reveal that our method not only can get correct optimal solution, but also is sixty-six faster than a traditional method on CPU, near 2.5 times faster than a lasted released MATLAB when LP problem size reaches 1200.

Hongtao Bai, Lili He, Yu Jiang, Jin Wang, Shanshan Jiang

A Study on the Effective Communication Protocol of the Surface Inspection Rail Robot that it can be a Self-checking

The robots that they inspect the rail surface with running above the rail will be a means to replace the existing expensive equipments. This can be very effectively used in the process of construction and maintenance of continuous increased rail industry. Especially, it can detect the small change via the build of database for detecting the state of the rail. And it is possible the continuous management by recording this information. However, these rail robots are attached a number of different rail parts. Thus, if these components are not gonna work, it can occur problems such as stop on the rail or derailed. These issues can be occurred to other train that it runs above the rail. Therefore, it needs the method for ensuring the safety. In this paper, in order to solve these problems, we define the components and performance parts that rail robot should have it. And also, we divide into three groups of devices by analyzing the properties of each of the components. Each of the group was divided according to the calculation processing capability and communication capability. The self-verification of equipments performs with fitting the framework. And they examine its own equipment validation and review whether the operation is enabled or impossible to perform in accordance with the information. In addition, the rail robot continues send the information for the rail status via wireless network with control center. Thus, we propose an efficient communication protocol in consideration of security issues that there may occur in sending process and the scalability of the function side for rail robot.

Yun-Seok Lee, Eun Kim, Sungyun Kim, Seokhoon Kim

The Efficient Multimedia Transmission Services for the E-learning System with Sensor

In this paper, we define and implement the protocol to manage networks in USN (ubiquitous sensor network). Although network management system in USN related with this paper is being progressed for the purpose of independent projects, protocol interfaces and message systems have not clearly defined yet such as general-purpose network or extension into heterogeneous kinds, communication support, etc. Therefore, USN network management should be conducted for the management of fault, composition, power, and applications. In this paper, we design the ubiquitous sensor network based on u-learning processing for multiple devices in order to connect other devices for the multimedia services, allowing the characteristics of existing network protocols.

Sung-Hwa Hong, Joon-Min Gil

A Quality Model for IoT Service

In this paper, We focuses on suggestion to Quality model of IoT Services which are popularly used in the characteristics defined in the quality model of IoT Services. In order to achieve this purpose, we propose Quality model for IoT Services. These technologies involves utilization and mobility in addition to quality characteristics in existing software, application of ISO 9126 is not perfect when evaluating a Quality model. This paper proposes a security set out in ISO25000 quality factors and assessment of the existing traditional software application of ISO 9126 quality model. We suggested new quality model for IoT Services by quality attribute in ISO 9126. We validated that the proposed model can be realized it was applied to evaluate the 4 elements and added security in Metrics. The quality model for IoT Services using the IS-QM proposed in this paper it can be measured relatively accurately.

Mi Kim, Jin Ho Park, Nam Yong Lee

An Empirical Study of Risk Factors for the Development Methodology for Small-Size IT Projects

The existing theoretical methodology or development methodology for small-size IT project when applied to the creation of project development deliverables, and many people are spending time. Because of enterprise projects to proceed in accordance with the procedures of the methodology, the lack of induction person or projects develop document written with experienced personnel is insufficient. In addition, when applied to development methodology of enterprise submitted a large amount of project development deliverables, and development of personnel development should be put into a lot of time on unnecessary paperwork to consume the result is displayed. This in the Dissertation, theoretical development methodologies and development methodology of domestic enterprises to use seven mandatory development deliverables and options development deliverables by analyzing the derives. In addition, client and expert of interviews, the developers from the survey will provide current problem and direction. Through which small businesses can easily leverage the development of the project development methodology, and short-term projects, while small and medium enterprises development deliverables written to create an efficient procedure is defined. Each stage through which small businesses can derive an important development deliverables, -based project development methodologies suitable for small and medium enterprises can take advantage of the methodology.

Joon Ho Park, Nam Yong Lee, Jin Ho Park

Nack-Based Broadcast Mechanism for Isochronous Audio Stream Transmission Using Bluetooth Low Energy

Bluetooth Low Energy which has been developed and deployed into the real home environment provided high energy efficiency where only low traffic environment was needed. However, the current version of this technology couldn’t support audio broadcast stream transmission because this environment requires classified isochronous data channel. For addressing this issue, this paper propose a new broadcast mechanism under the assumption of the next generation technology of Bluetooth Low Energy, using Nack mechanism combined with energy detection mechanism, in order to support seamless broadcast transmission of audio data stream. For further study, this paper designed energy detection for Nack reception without awareness of the number of slave nodes.

Jaeho Lee

Empirical Study on IoT-Learning for the Rehabilitation Treatment of Chronic Low Back Pain Patients

As the study of the IoT evolves, it is naturally used in everyday life. It is common situation that we can easily turn off the light as well as increase the temperature in the house by using a mobile phone. As e-learning has been converted to u-learning, it is expected to change to IoT-learning. This study analyzed IoT and learning system in accordance with the changes, applied the new concept of “IoT-learning”, and investigated the current situation and the case to study.

Seul-Ah Shin, Ji-Soo Choi, Young-Jong Kim, Nam-Yong Lee, Jin-Ho Park

A Theoretical Study of Hardware Architecture for Network Security Server

Development of IT led to changes in the Infra architecture and the area of information security has been especially emphasized. With the rapidly growing Data, the area of Information Security has established itself as an essential, and the Network Security Field is expected to be developed and elaborated also for the private and public peace and the establishment of social order. The purpose of this study is to consider the architecture of high-performance hardware architecture that can process large amounts of Data, and also to study the architecture of the hardware with flexible architecture in accordance with the amount of network traffic.

Joong-Yeon Lee, In-Taek Oh, Nam-Yong Lee, Jin-Ho Park

An Empirical Study of the Relationship Between DISC Behavioral Style of Application Programmer and Quality of Software Development

A number of application programmers’ factors influence the quality of software development. The purpose of this study was to examine the relationship between the DISC behavioral styles of application programmers and the quality of software development for identifying how the factors affect the quality of software development. We conducted a field experiment with 34 application programmers working for a certain company. In conclusion, it may be said that the quality of software development is affected by the working periods of application programmers rather than their DISC behavioral styles.

In-Taek Oh, Joong-Yeon Lee, Jae-Yoon Cheon, Nam-yong Lee, Jin-Ho Park

Advances in Computer Science and Ubiquitous Computing


The Development of COB Type LED Lighting System for High Temperature Machine Vision

In the machine vision system of steel production line, the obtained image qualities are greatly affected by brightness and wavelength band of illumination. The surface temperature of a continuous casting material is very high, 600~1000 °C. But the operation temperature of COB type LED is maximum 90 °C. Therefore, any special cooling systems are needed to use in these high temperature environment. In this paper, we have developed COB type LED lighting system for high temperature machine vision equipment. Our LED lighting system consist of air filter module, heat sink module, reflector and reflecting plate, heat blocking glass, air injector and circulation module. We suggest air curtain system to heat block in front of heat-blocking glass. Through the test, we have confirmed that our air curtain system will drop the internal temperature to below 80 °C in the circumstance of high temperature 600~1000 °C.

Park Sanggug

An Alternative Management Scheme of DHCP Lease Time for Internet of Things

In this paper, an alternative management scheme is proposed for the DHCP lease time in Internet of Things(IoT) environment. In the proposed scheme, the Dynamic Host Configuration Protocol(DHCP) server manages addresses as well as lease time using the type of IoT device. The MAC header of DHCP message sent by IoT device is modified newly by adding specific information to reflect the type of IoT device. The DHCP server can recognize the type of IoT device from the newly defined MAC header and return an address to the IoT device with a lease time determined by the type of IoT device. For the efficient management, a policy for allocating address and lease time should be required. According to this policy, allocated addresses and lease times are stored in a lease database. Examples of the table for diverse IoT types and the policy for allocating address and lease time are given.

Pyung Soo Kim, Eung Hyuk Lee, Eung Tae Kim

A User Empirical Context Model for a Smart Home Simulator

This dissertation aims to quantify the consumer experience in reality by building a real-space information based space model and consumer behavior model. We applied the models and used it to implement the simulator. The developed simulator collects the information generated in the virtual living space for the purpose of developing a smart home simulator. To predict user behavior, data is compiled from experiment panels. By using weka, features are extracted from the amassed data and the feature value’s complexity is reduced. Through optimal subsets of the feature values we could make a judgment on the accuracy of the predicted behaviors.

Green Bang, Ilju Ko

Co-display Content Service for First-Person Videos of Smart Glass

A smart glass is a personalized device, which has features that enable it to record and share a user’s experience of specific events in first-person view (FPV). FPV videos recorded from identical events can be watched interactively, for example, it is possible to switch between FPV videos of several people through synchronization based on an actual event timeline. This paper proposes a co-display content service for watching interactive, synchronized FPV videos in second screen environments and presents a prototype of the system.

Bokyung Sung, Ilju Ko

Probabilistic Analysis for the Relationship Between Min-Entropy and Guessing Attack

Recently NIST has published the second draft document of recommendation for the entropy sources used for random bit generation. In this document NIST has provided a practical and detailed description about the fact that the min-entropy is closely related to the optimum guessing attack cost. However the argument lacks the mathematical rigour. In this paper we provide an elaborate probabilistic analysis for the relationship between the min-entropy and cost of optimum guessing attack. Moreover we also provide some simulation results in order to investigate the practicality of optimum guessing attack.

Ju-Sung Kang, Hojoong Park, Yongjin Yeom

Dynamic QoS Scheme for InfiniBand-Based Clusters

Cluster-based computing systems are very widely used in various fields, including simulations and big data processing. InfiniBand is de-facto interconnect technology for cluster-based computing. QoS is a very important issue in data communication of cluster-based computing systems. In this paper, we propose dynamic QoS scheme for InfiniBand-based clusters. The proposed scheme can change QoS level in terms of the bandwidth. The proposed QoS scheme can get more bandwidth by changing the QoS level. The prototype of the proposed scheme was implemented in a real InfiniBand-based clusters. By using the prototype implemented, we confirmed and evaluated the usefulness and effectiveness of the proposed scheme.

Bongjae Kim, Jeong-Dong Kim

Applying PE-Miner Framework to Software Defined Network Quarantine

As increasing the size of network, the malware propagates to other network easily. Moreover, malware is hard to detect if it is modified. The complexity of current network also causes the weakness for malware detection. Therefore, SDN quarantine network architecture has been researched. We applied the improved PE-miner framework that is malware detection mechanism based on machine learning algorithm to the SQN 1st quarantine. 1st quarantine is the system that filtering the malware using static mechanism. In this paper, detection rate of the improved PE-miner framework was evaluated and the real-time performance was also tested. Referring the result, we have proved that applying the PE-miner framework to SQN 1st quarantine is permissible.

Dong-Hee Kim, Soo-Hwan Lee, Won-Sik Doo, Sang-Il Ahn, Tai-Myoung Chung

A Novel Method for Eliminating Duplicated Frames in Ethernet Standard (IEEE 802.3) Networks

If assumed that each Ethernet standard (IEEE 802.3) node has more than one port connected to the network and the node duplicates each sent frame, then an active or a seamless redundancy will be established because the destination node will receive at least two frame copies with zero recovery time. In this paper, we present a novel method for eliminating the duplicated frames in any Ethernet network type. This will ensure that the destination node will only consume one frame copy from each sent frame and eliminate the other copies. The proposed method will set a counter on each receiving port in the destination node. The destination node will consume the copy that arrives through the fastest path, or in other words, through the port that has the fastest counter value. The proposed method does not need to disable ports as required by rapid spanning tree protocol (RSTP) or the media redundancy protocol (MRP), to avoid looping issues; instead, it activates all ports to provide a type of better traffic distribution among the network links.

Saad Allawi Nsaif, Jong Myung Rhee

A Study of Malicious Code Classification System Using MinHash in Network Quarantine Using SDN

Thanks to the development of IT technology, information systems have been growing continuously. However, there are threats behind the convenience. There is a possibility of malicious users to steal sensitive information and malware can lead to social chaos by paralyzing the information systems. Several solutions to prevent these attacks have been introduced. In this paper, we introduce malware detection technique using Minhash and evaluate the performance of it and suggest the cyber quarantine system applied this technique. It contributes to detect not only known malware but unknown malware.

Soo-Hwan Lee, Myeong-Uk Song, Jun-Kwon Jung, Tai-Myoung Chung

Application of RFID and Computer Vision for the Inventory Management System

The RFID technology can be used for item tracking and inventory control. However, the problem such as miss reading and ghost reading usually occur in RFID implementation and has impact on low accuracy of inventory management system. In this study, the computer vision is used to solve the problem of miss reading and ghost reading in RFID. The RFID and computer vision can act as ears and eyes respectively, thus by combining both technologies; it is expected to increase the accuracy of system. The result of experiment has showed that the combination of RFID and computer vision has increased the system accuracy, as the computer vision can help the RFID system to detect the miss reading and ghost reading.

Ganjar Alfian, Jaeho Lee, Hyejung Ahn, Jongtae Rhee

Prediction Method for Suspicious Behavior Based on Omni-View Model

Recently, CCTV is being applied to prevent crimes. It senses the level of danger as being searching criminal records, a wanted one’s montage and so on through mainly Facial recognition. However, it needs additional judging to provide against emergencies, because it cannot predict every criminal situation. In the cause of it, a computer is being fed three-dimensional coordinates from CCTV into a device, and catches not only motion of body or arms but also pattern of hand that were grasped by ConvexHull. And then it predicts suspicious behaviors via judging the movements of an object. Furthermore, to add information about surroundings and location, preventing crimes with more exact judging is the aim on this research.

Ji-Hyen Choi, Jong-Won Choe, Yong-Ik Yoon

Optimal 3D Printing Direction for Stability of Slanted Shapes

The Fused Deposition Method (FDM) constructs objects in layers of melted material. Because the layer-by-layer construction of slanted shapes introduces a smaller bonding area between layers and significant warping, users often heuristically optimize the printing direction. We propose a novel method for selecting the optimal 3D printing direction to increase the stability of slanted shapes. Our optimal direction leads slanted subparts to be oriented either perpendicular or parallel to the build plate as much as possible. We first find a set of stable directions for the input model and then validate each of them using the following three criteria: similarity to dominant directions, stability and material cost. The experiments show that our optimal printing direction enables the given shape to be printed without undesired deformation during printing process.

Jiyoung Park, Hwa Seon Shin

A Study on DDS-Based BLE Profile Adaptor for Solving BLE Data Heterogeneity in Internet of Things

For communication between heterogeneous objects there is a heterogeneity problem that needs to be solved and to do this interoperability between different protocols has to be secured using a middleware structured adaptor. In this paper we suggest using a BLE(Bluetooth Low Energy) profile adaptor which Interoperates data between objects based on DDS(Data Distribution Service), a real time standard middleware. With this BLE profile adaptor, BLE devices and other protocoled devices can interoperate data and by using the profile based Standard data format we can obtain wide interoperability between devices regardless of the BLE device’s type or manufacturer.

Jung-Hoon Oh, Moon-Ki Back, Gil-Tak Oh, Kyu-Chul Lee

A Study of Environment-Adaptive Intrusion Detection System

Recently, the intrusion cases by hackers are growing fast. In order to prevent such intrusions, it is common to install a firewall or an intrusion detecting system to be employed. However, since traditional intrusion detecting system detects attacks by using static attack signatures, there are limits in coping with changes of environment or methods of sneaking in. For these problems to be solved, this paper suggests Environment Adaptive Intrusion Detection System using MAPE model. The system identifies the changes of external environment from MAPE’s acts; through the recognized change values of environment, it creates a proper attack sign and applies to the intrusion detecting system. It is expected to operate the Environment Adaptive Intrusion Detection System by using this method.

Ki-Hyun Lee, Young B. Park

OFART: OpenFlow-Switch Adaptive Random Testing

In the advent of SDN paradigm, the accumulated verification technologies in the existing software fields are being used to verify the SDN. Data Plane consists of Forwarding Devices and is controlled by Control Plane. If correctness of the Forwarding Device is not verified, it affects to the whole network. However, doing every testing by manually is a huge time-cost consuming act, so it requires an automation. In this paper, it suggests a framework which applies ART (Adaptive Random Testing) technique which considers OpenFlow Switch to be Black Box from the Controller point of view and is easy to do a testing automation.

Dong-Su Koo, Young B. Park

An Evaluation of Availability, Reliability and Power Consumption for a SDN Infrastructure Using Stochastic Reward Net

Networking infrastructure of a software defined network (SDN) is demanding further studies to achieve continuity and high availability of data transactions for cloud computing services. Nevertheless, the high-speed and complicated network of hosts and network devices often encounters with a variety of failures either of links or system components. This paper aims to study the specific characteristics of and the impact of various failures on a typical SDN infrastructure. We propose a stochastic model using stochastic reward nets (SRN) with the incorporation of hardware failures (of hosts, switches, storages and links) and software failures (virtual machines (VM). The system model is analyzed based on steady state availability in the case of default parameters. Comprehensive sensitivity analyses are conducted to study the system behaviors with regard to different major impacting factors. Reliability analysis is also carried out to pinpoint the role of VM migration in extending the system lifetime. System power consumption based on availability of every module is also conducted to examine the power allocation on system devices and operations. This study provides a helpful basis for network design and implementation in SDN infrastructure.

Kihong Han, Tuan Anh Nguyen, Dugki Min, Eun Mi Choi

A Dynamic Service Binding Scheme with Service OID for IoT

Object Identifier (OID) has been used in various areas, but its usage has been limited to naming things for a long time. In order to extend OID for identifying Web services, we suggested a new kind of OID named Service OID and its relevant resolution scheme. It is expected for devices to easily collaborate by resolving a simple number-shaped Service OID to the corresponding URI. This simple resolution seems straightforward, but it is not enough for a caller to use the converted URI because every URI needs its unique parameter signature. For this, in the proposed resolution scheme, a data schema was designed and used to provide the binding information of URI.

Euihyun Jung

A Context-Aware Architecture Pattern to Enhance the Flexibility of Software Artifacts Reuse

In software development approaches including open source-based development, new version development of software product, reuse has become a useful and common approach. However, the problem of traditional reuse approach is not easy to find reusable components that software engineers want, or difficult to reuse the components without any modification. This paper proposes an ICFP (Imparter-Collector-Fetcher-Presenter) architectural pattern that supports context-aware reuse in order to solve the existing problems in the reuse process for the software artifacts. The proposing reuse approach based on the ICFP pattern provides the benefits of improving the flexibility of reusing methods as well as enhancing precision of component retrieval.

Doohwan Kim, Soon-Kyeom Kim, Woosung Jung, Jang-Eui Hong

Deep Analysis of Tag Interference by Tag to Tag Relative Angles with Passive Far Field UHF RFID System

This paper study about Passive UHF RFID tag to tag interference with consideration of tags’ relative angle and distance. According to the analysis results of the measurement, the RSSI values under tag interference are significantly affected by tags’ posture angles. And this analysis will be used for tag interference model developments.

Jae Sung Choi, Hyun Lee

Simple Method of Video Mapping of Multiple Targets

In this paper, a simple and efficient projection mapping framework is proposed so that even a projection mapping novice can easily map multiple video clips onto multiple different flat surfaces of the real world, which are not orthogonal to the projection direction. We also propose a symmetrical mesh refinement method to reduce the severe distortion of each image resulting from a flat surface having a certain angle to the projection direction. Through experiments, we proved that the proposed method reduced the image distortion error by 95.19 %.

In-Jae Jo, Joohun Lee, Yoo-Joo Choi

Evolutionary Test Case Generation from UML-Diagram with Concurrency

To find equality between software products and artifacts, model-based test (MBT) handles specific representations of software requirement. When those conclude concurrency and loop in MBT, it explosively increases a number of paths are applied by existing coverage criteria. Therefore, in this paper, we propose exploration method to avoid path explosion problem, and solution to generate test data automatically using evolutionary algorithm. The result of practical study shows our proposal’s efficiency. Testers, who deal with their project through our approach, could find necessary test path. And our approach makes it possible to generate test data according to various test coverage criteria.

Seungchan Back, Hyorin Choi, Jung-Won Lee, Byungjeong Lee

Evaluating the Effectiveness of the Vector Space Retrieval Model Indexing

Modern information retrieval activities are supported with software systems that facilitate the users’ information searching. Information retrieval systems are significantly improved in the past few decades. Now days, there are three types of retrieval models: Boolean, Vector Space and Probabilistic. In this study, we examined the vector space model where documents and queries are represented as vectors. We conducted a number of experiments on the indexing technique of the vector space model to quantitatively describe the effectiveness of the techniques using Lemur Toolkit. The result indicates that stop word removal and steaming techniques improve the quality of the index terms.

Jung-Hoon Shin, Mesfin Abebe, Cheol Jung Yoo, Suntae Kim, Jeong Hyu Lee, Hee-Kyung Yoo

Active Tracking Strategy with Multiple Cameras in Large Areas

This paper presents a distributed multiple camera collaboration strategy for active tracking in large areas. Their collaboration utilizes a sector-based mechanism in which the visual correspondences among different cameras are determined. In order to emulate the master-slave operations, the proposed method combines the local data to construct the global information. Based on the global information, the loads are evenly distributed to avoid tracking misses due to the dynamic behaviors of the objects. The trajectories of all objects visible in the local cameras are estimated for actual tracking and the estimated dynamics are used for scheduling of the cameras. The active tracking triggering timing is carefully chosen to maximize the overall monitoring time for general surveillance operations.

Sangjin Hong, Nammee Moon

A Survey and Design of a Scalable Mobile Edge Cloud Platform for the Smart IoT Devices and It’s Applications

Mobile Edge Computing offers real time RAN information (like network load, user’s location) to the application developers and content developers. These real time network information are used to provide context aware services to the mobile subscribers, thereby enriching user’s satisfaction and improving Quality-of-Experience. Mobile edge computing platform increases the edge responsibility and allows computation and services to be hosted at the edge, which reduces the network latency and bandwidth computation of the subscribers. In this research paper, we designed the scalar mobile edge cloud platform and it’s appropriate edge applications, such as 360° panorama image processing, which has a special characteristics and challenges to extend an edge servers on edge cloud by the subscribers demands. This research paper challenges capable to overcome the static al constrains of edge serve capacities and supports flexible computing facilities.

Yeongpil Cho, Yunheung Paek, Ejaz Ahmed, Kwangman Ko

Network Anomaly Detection Based on Probabilistic Analysis

In this paper, we provide a detection technology for a common type of network intrusion (traffic flood attack) using an anomaly data detection method based on probabilistic model analysis. Victim’s computers under attack show various symptoms such as degradation of TCP throughput, increase of CPU usage, increase of RTT (Round Trip Time), frequent disconnection to the web sites, and etc. These symptoms can be used as components to comprise k-dimensional feature space of multivariate normal distribution where an anomaly detection method can be applied for the detection of the attack. These features are in general correlated one another. In other words, most of these symptoms are caused by the attack, so they are highly correlated. Thus we choose only a few of these features for the anomaly detection in multivariate normal distribution. We study this technology for those IoT networks prepared to provide u-health services in the future, where stable and consistent network connectivity is extremely important because the connectivity is highly related to the loss of human lives eventually.

JinSoo Park, Dong Hag Choi, You-Boo Jeon, Se Dong Min, Doo-Soon Park

Hedonic Model Study for Retargeting Advertising Based on Space-Centered Internet of Things

This paper is focused on hedonic model study for retargeting advertising Based Internet of Things using useful information. Many research related to the existing Internet of things, relatively not many study for effective advertising model based Internet of Things. So, this paper is designed more information, fun, interactive advertising model based on Internet of Things. Therefore, result of this paper show that implication to produce advertising based on Internet of Things provides a practical guide.

Bo-Ram Kim, Man-Soo Chung, Yong-Ik Yoon

A New Automated Cell Counting Program by Using Hough Transform-Based Double Edge

A suitable amount of cells in a range is necessary in order to conduct the experiment. In addition, various methods are being performed to counter the number of cells. However, there are still some problems. We propose a new automated cell counting program by using Hough Transform-based double edge. The proposed algorithm can distinguish between dead cells and living cells automatically. Finally, we will show the improvement of our work by reducing the range of error rates.

Jae Sung Choi, Moon Jong Choi, Jung-Min Lee, Hyun Lee

An Approach for Interworking Heterogeneous Networks with DTN and IP Routing in Space Internet

In a space mission, there are various types of nodes which can adopt individual communication protocols for aircraft on Delay Tolerant Network (DTN) and terrestrial control center on TCP/IP. For efficient routing between heterogeneous networks, we propose an approach for interworking heterogeneous networks with DTN and IP routing in space Internet. We design it by configuring Interplanetary Overlay Network (ION), based on IP forwarding rule and gateway. Also, we design scenarios to evaluate its performance. The experimental results verify the proposed protocol is suitable for interworking heterogeneous networks in space Internet.

Euiri An, Kyungrak Lee, Jaewon Lee, Inwhee Joe

Implementation of Recommender System Based on Personalized Search Using Intimacy in SNS

Recently, a search system has been a trend of personalization such as recommendation systems and social searches. Because, each users receive different results for the same queries by using user preference and interesting. Specially, a social relation is a most important factor of search system, and therefore, many recommender system using have been proposed. However, existing recommender systems typically return a set of search results based on a user’s query without considering user interests and preference. Therefore, the identical query from each user will generate the same set of results displayed in the same way for all users. To overcome this restriction, this paper proposes a recommender system based on personalized search using intimacy in SNS and describe a prototype of our recommender system.

Jeong-Dong Kim, Bongjae Kim, Jeong-Ho Park

Measuring Similarity Between Graphs Based on Formal Concept Analysis

Graph, an important information organizational structure, is commonly used for representing the social networks, web, and other internet applications. This paper tackles a fundamental problem on measuring similarity between graphs that is the essential step for graph searching, matching, pattern discovery. To efficiently measure the similarity between graphs, this paper pioneers a novel approach for measurement of similarity between graphs by using formal concept analysis that can clearly describe the relationships between nodes. A case study is provided for demonstrating the feasibility of the proposed approach.

Fei Hao, Dae-Soo Sim, Doo-Soon Park

TEXAS2: A System for Extracting Domain Topic Using Link Analysis and Searching for Relevant Features

It is very important to understand the domain topic of software to maintain and reuse it. However, the continual development and change in its size makes it difficult to understand it. To solve this problem, researches have been recently conducted to extract the domain topic using various information search techniques such as LDA, with the researches on LDA-based techniques being especially active. However, since only unstructured information such as an identifier or note is used in most research, without including structured ones like information calling, problems in which extracted topics are different from the characteristics of the program can occur. In this paper, we propose a method to generate documents and extract topics using both structured and unstructured information. We also generate indexes based on the frequency of the identifier of the source code, and propose a system that extracts an association rule based on the simultaneous generation of the method. We as well establish a system that provides highly reliable search results to user queries by combining domain topics, indexes with scores, and the association rule information. Consequently a TEXAS2 system for this study was established and confirmed a high user satisfaction on search results to the queries in a performance test.

SangWon Hwang, YongSeok Lee, YoungKwang Nam

Ubiquitous Computing for Cloud Infrastructure to Mobile Application in IoT Environment

The growth of the Internet of Thing (IoT) ability up all types of service driven to ubiquitous cloud infrastructure different access methods are analyses to understand new message protocols that are used ubiquitous IoT mobile application environment that presented the cloud computing platform for mobile application. It supports a combined architecture of ubiquitous and cloud computing which provides a how device can grow in intelligence, interoperability with other IoT environment, system and service. The Cloud Infrastructure for ubiquitous computing environment mobile application (CI-UCEMA), which consist of three layers it Cloud Service Layer (CSL), M2M Service Layer (MSL) and Ubiquitous Service Layer (USL). The M2M consists of IoT Services layer (MSL) will involve a decrease in complexity of both the improvement and controlling of IoT systems. Realizing the full potential of the Internet of Thing requires that we change how we view and build ubiquitous environment which provide the core foundation of service.

DongBum Seo, Keun-Ho Lee, You-Boo Jeon

What Are Learning Satisfaction Factors in Flipped Learning?

Flipped learning is an effective teaching-learning method implemented with learner centered interactive learning instead of teacher centered cramming methods of lecturing. Despite that it is an effective learning method, studies of flipped learning are not sufficient. The present study analyzed factors that affect flipped learning satisfaction. According to the results of analysis, satisfaction with interactions was directly affecting learning satisfaction and indirectly affecting learning satisfaction mediated by satisfaction with assistance services. Based on the present study, flipped learning is believed to creatively help the development of learning as an effective learning method and expected to become a new alternative education method with student centered learning.

Kyung Yeul Kim, Yong Kim

Development of UI Guideline for Senior Citizens’ e-Learning Content

The speed of aging increases day by day leading to changes in many shapes of society. In particular, the field of lifelong education out of the field of education has been expanded to diverse ranges and e-learning, which is a field of lifelong education and recognized as an alternative, is becoming gradually more important. In this situation, e-learning guidelines for silver generations are an essential element of the development of contents. The purpose of the present paper is to develop guidelines for e-learning UI designs for silver generation with verified validity. This author expects that e-learning sites applied with guidelines designed based on the present study will become more useful to silver generations and utilized by them.

Myung In Kim, Yong Kim

Full Duplex Relaying with Buffer Based on Cognitive Radio Technique

In this paper, we propose a cognitive radio based power control scheme for full duplex relaying (FDR) system with buffer. The proposed scheme maximizes the system throughput by adaptively controlling the transmit power of relay by using underlay cognitive radio (CR) technique. We verify the performance of the proposed system with intensive simulations.

Junsu Kim, Doo-Hee Jung, Jeho Lee, Su Min Kim

Design of Docking Drone System Using P-PID Flight Controller

Recently, drones have been used widely because of low-cost, mobility and high utility, and it can be applied in many fields such as surveillance, guidance, military and hobby, etc. using docking modules. This paper proposes a control method for docking drones using P-PID controller. This drone is applied the docking method using marker detection, and it is made for several experiments for stable docking. In this paper, we also describe a P-PID controller for docking drones’ flight. Experimental results have shown docking drones’ considerable material and the proposed method is more efficient than single PID method.

Beck Jong-Hwan, Pak Myeong-Suk, Kim Sang-Hoon

Lightweight Security for Underwater IoT

Becoming IoT era, RF communication on terrestrial network gets faster speed and wide communication coverage. However, because of RF has vulnerability on underwater environment, the underwater acoustic is widely adopting for replacing RF. As a result of efforts, we can suggest ‘underwater IoT’ model and its security challenge by listing UIoT security consideration and comparing underwater security protocols which are presented. Additional, we discuss side channel attack issues.

Sun-Ho Yeom, Jung-Il Namgung, Soo-Young Shin, Soo-Hyun Park

Image Based Video Querying Algorithm Using 3-Level Haar Wavelet Transform Features

Surveillance cameras and smartphone cameras produce huge amount of video data in our daily life. Effective utilization of huge video data is emerging as a new big problem in the ubiquitous video intelligent systems. Searching for a specific frame in video stream is one of challenging issues in this area. This paper proposes an image based video querying algorithm using 3-level Haar wavelet transform features. Hierarchical decomposition of wavelet transform enables to use features in both space and scaling domains. This paper employs 3-level Haar wavelet feature of an image to query matched frame in a video stream. In experimental results, we can find that the proposed algorithm shows about 1–8% better performance in accuracy than other algorithms.

Changseok Bae, Yuk Ying Chung, Jeunwoo Lee

Design and Implementation of the Mobile Learning App for Creative Problem Solving Activities

To cope with the age of ubiquitous environment, a supply of smart media devices has been indicating a rapid increase due to the development of smart devices as well as the market expansion. The purpose of this study is to propose a method for designing an educational app that uses the mobile learning-based CPS (Creative Problem Solving) model in order to design a mobile learning-based learning environment which contributes to enhancing creative thinking and problem solving ability of the students in college education. The proposed learning support tool is developed in a form of mobile app and is designed to be used as a cognitive tool that enhances the high-dimensional thinking ability of learners through functions such as creative thinking, thinking process, expression method and interactivity in terms of learning activities. As a result of conducting a test by demonstratively applying this app to the actual field of education, the satisfaction rate in participation and learning effect was greater than 90 %.

Ji-Hye Bae, Hyun Lee

IoT-Based Smart Photo Frame

In IT Industry, although ‘Digital Picture Frame’ has advantage of not only bringing the nostalgic memories of classic desk frame but also using smart way to change the picture, it did not become a new trend. It was because there were several problems in digital picture frame such as an expensive price of most importantly, inconvenience of picture transmission system. In this paper, we provide a solution for picture transmission system, and more than that, we add various functions that could use with pictures such as widget and security function. In particular, we use AWS server in the transmission system, and it allows using data in the Wi-Fi environment to transmit pictures whenever and wherever people want it. The proposed system will be the great solution for the discomfort of the current digital picture frame’s transmission system which is using USB or SD card. Also, by using this digital picture frame at home or work.

Ji-Hye Bae, In-Hwan Kim, Yong-Tae Jeon, Hyun Lee

A Fast Algorithm for Generating Virtual Dedicate Network Based on Software-Defined Wide Area Network

Various needs of new network services have rapidly proliferated over the past few years. To catch up with major requirements, that is, time-to-research and time-to-collaboration, we propose a fast virtual dedicate network generation algorithm based on network abstraction with pruning strategy, unification of multiple links, and an improved spanning tree algorithm.

Yong-hwan Kim, Buseung Cho, Dongkyun Kim

Detection of Content Changes Based on Deep Neural Networks

On R&D projects, automated analysis of implicational and morphological changes between two documents helps managers and researchers to understand projects. However, it is not easy to manually analyze changes between two documents. In this paper, we define text operations which represent changes of texts and make multi-labeled dataset by applying several text operations. Lastly, we propose a method to detect changes of contents. Proposed method represents two documents into an S-matrix first. Next, we use S-matrix as input of Deep Convolutional Neural Networks to identify text operations on the multi-labeled dataset. Experimental results show the effectiveness of our proposed method.

Noo-ri Kim, YunSeok Choi, HyunSoo Lee, Jee-Hyong Lee

Resource Allocation in D2D Networks with Location Based Distance Information

Recently, mobile internet traffic has rapidly increased as the huge increase of the smart phone and mobile devices. D2D (Device to Device) is known that it reduce the traffic load of the base station and also improves the reliability of the network performance. However, D2D has a problem that the efficiency decreases as interference is increased. In this paper, we propose a resource allocation scheme to use the resources efficiently when the D2D link share the resources of the cellular network in the uplink. D2D communication utilizes the location information for allocating resources when the eNB know the location of all devices. The proposed scheme not only ensures the performance of the D2D communication but also decrease the computational complexity Simulation results show that the proposed scheme attains the comparable throughput over optimal scheme with a very small computational complexity.

Soo Hyeong Kang, Pyung Soo Kim, Bang Won Seo, Jeong Gon Kim

Design of Corporate Business Card Management System

Applying and ordering business card, which are mostly handled manually, cause such problems as work overload, a long time (about a week) till delivery, and hardship in designing several business cards and change designs due to omission in application and the occurrence of miscellaneous work caused by unestablished work process and organizational change which pushes out a large quantity of order at a time. In this respect, the present study suggests a business card management system that is totally computerized so that work process, cost and delivery can be improved. Especially, it connects a company’s database with web business card editor to increase to combine convenience and efficiency in applying and ordering business card.

Seok-heon Ko, Gil-mo Yang, Jun-dong Lee

The OpenWRT’s Random Number Generator Designed Like /dev/urandom and Its Vulnerability

OpenWRT is an open source router firmware based on embedded Linux that uses a dedicated random number generator for the WPA/WPA2 authentication protocol. Its main purpose is to generate a nonce that can be used in a WPA/WPA2 handshake. If the output of the random number generator can be predicted by an attacker, the relevant protocol will not be able to authenticate securely. According to previous studies on Linux, it is well known that a random number generator implemented in an embedded Linux environment does not collect sufficient entropy from noise sources. The lack of entropy increases the potential vulnerability for the random number generator and the Linux protocol. Therefore, we analyzed the WPA/WPA2 authentication protocol and its random number generator. In our results, we point out some potential cryptographic weaknesses and vulnerabilities of the OpenWRT random number generator.

Dongchang Yoo, Yongjin Yeom

Implementation of the Block2 Option Transfer for Resource Observing with the CoAPthon Library

Utilization of the Constrained Application Protocol (CoAP) that is an important protocol of the Internet of Things (IoT) has increased. So the many associated libraries related with CoAP are also emerging. Among those libraries, CoAPthon, a representative Python-based CoAP library, has advantage in aspect of easy-to-use programming interface to exploit CoAP. However, the current version of CoAPthon has not been implemented correctly in terms of (1) the Block2 option of a block-wise transfer and (2) the transfer for resource observing. In this paper, we implement them and verify the functions in our experiment using the Raspberry PI 2.

Kyoung-Han Kim, Hyun-Kyo Lim, Joo-Seong Heo, Youn-Hee Han

Hive-Based Anomaly Detection in Hadoop Log Data Management

In this paper, we address how to manage and analyze a large volume of log data, which have been difficult to be handled in the traditional computing environment. To handle a large volume of Hadoop log data, which rapidly occur in multiple servers, we present new data storage architecture to efficiently analyze those big log data through Apache Hive. We then design and implement a simple but efficient anomaly detection method, which identifies abnormal status of servers from log data, based on moving average and 3-sigma techniques. We also show effectiveness of the proposed detection method by demonstrating that it properly detects anomalies from Hadoop log data.

Siwoon Son, Myeong-Seon Gil, Seokwoo Yang, Yang-Sae Moon

HIM-PRS: A Patent Recommendation System Based on Hierarchical Index-Based MapReduce Framework

Intellectual Property (IP) data, such as patent documents, grows inconceivably in recent years. Therefore, discovering valuable information from those huge number of data becomes a challenge. This paper introduces a novel patent recommendation system called HIM-PRS which is built on top of hierarchical index based big data processing platform. HIM-PRS integrates with linked data to provide an efficient patent recommendation service. Our result shows that HIM-PRS is able to find more semantically similar patents than other systems. Additionally, HIM-PRS launches query jobs at least 2 times faster than original Hadoop MapReduce framework.

Xuhua Rui, Dugki Min

Finding Meaningful Chronological Pattern of Key Words in Computer Science Bibliography

In order to find meaningful patterns of research trends in the computer science and engineering field, we crawl a significant amount of bibliographic information, 3 million or more scholarly papers published from 1956 to 2015. We also make a list of target key words and analyze their frequency rate over the past 60 years based on the terms extracted from the titles and abstracts of the papers. We apply k-means clustering analysis for the target key words, and present a meaningful chronological pattern of target key words in the computer science engineering field over the past 60 years.

Joo-Seong Heo, Hyun-Kyo Lim, Kyong-Han Kim, Youn-Hee Han

The Design of Intelligent Video Analytics System Performing Automatic Noise Rejection by Comparing Distribution of Metadata of Moving Object

For growing interest in public safety in Korea, the number of CCTV to be monitored is rapidly increasing. It’s impossible to monitor all CCTV cameras with limited monitoring agents. So, computer video analysis solution is essential. A lot of research concerning this demand is conducted but it’s not enough for them to analyze lots of videos in integrated control centers because most of them use heavy algorithm for analysis. For this reason, we implemented an intelligent video analytics system which employs engine with light algorithm and data analysis of metadata from that engine to analyze thousands of CCTV videos for detecting object of interest. Also, we introduce technique for automatically rejecting noise object from that engine.

Taewoo Kim, Hyungheon Kim, Pyeongkang Kim

Dependability Analysis of Digital Library Cloud Services with Load Sharing

Cloud service utilizes computing resources to store all of information on the Internet. It means that we can use the service anytime, in anywhere through a variety of IT equipment. For reliable operations of digital library cloud services, it is necessary to ensure dependability. In this paper, we apply the cold standby, hot standby, and load sharing in the system and compare our system with existing systems to measure the availability and reliability of dependability characteristic.

Dongseok Lee, Sungsoo Kim, Tae-Sun Chung

Document Classification Using Word2Vec and Chi-square on Apache Spark

Text mining is a mechanism to find information by extracting resources from natural language. Compared with structured data in databases, text is unstructured and difficult to be dealt with for analyzing. Additionally, it is tedious tasks for users to identify accurate data. Text mining algorithm is similar to data mining, except that it processes data in database and aims to determine whether any document belongs to a specific topic. There are some classification algorithms. To identify which classifier is efficient, we compare SVM (Support Vector Machine) and Naïve Bayes, and use Apache Spark which is distributed system environment, to classify a large number of documents efficiently.

Mijin Choi, Rize Jin, Tae-Sun Chung

Analysis of Recent Maximal Frequent Pattern Mining Approaches

Since the concept of representative pattern mining was proposed to solve the limitations of traditional frequent pattern mining, a variety of relevant approaches have been developed. As one of the major techniques in representative pattern mining, maximal frequent pattern mining provides users with a smaller number of more meaningful pattern mining results. In this paper, we analyze characteristics of recent maximal frequent pattern mining methods using various concepts and techniques.

Gangin Lee, Unil Yun

Design of Noise Information Storage System Using IoT Devices

Recently, many issues caused by noise have been on the rise in quite places such as reading room and a library where personal desks are used. In this paper, we design a system for collecting and storing noise-data into a database using Internet of Things (IoT). The data can be used for restraining the issues and addressing noise sources. Thus, our system performs sensing raw noise with IoT devices, transmitting noise-data from IoT devices to a server, processing the noise-data at the server, and storing the processed data in a database.

Judae Lee, Unil Yun

Analysis of Privacy Preserving Approaches in High Utility Pattern Mining

With the significant increase of information sharing in various areas, it has been an important issue to prevent personal information from being disclosed to abnormal users. Pattern mining is one of data mining technique for extracting interesting pattern information from massive databases. Therefore, sensitive patterns belonging to personal information can be disclosed to abnormal users through pattern mining methods. A sanitization approach that modifies a given database is one of the most common approach for achieving privacy preserving. In this paper, we introduce and analyze various methods for achieving privacy preserving in high utility pattern mining based on sanitization approaches.

Unil Yun, Donggyu Kim

An Agent-Based Remote Operation and Safety Monitoring System for Marine Elevators

The reliability of marine elevators are important because of the tough conditions in the marine environment. For the safety purpose, more than 26 safety lists shall be checked by persons when the ship is docked. However, its maintenance costs of the elevator increases as the rise of personnel expenses increases. Also the efficiency is highly dependent on the ability of the personnel but it is not feasible to provide expert maintenance services all the time. Therefore we propose an agent-based remote operation and safety monitoring system for the marine elevators through a shipborne gateway, called MariComm. So expert A/S personnel can inspect status of marine elevators and provide best maintenance service through the marine elevator management server whenever and wherever he wants. In our experimental analysis, we illustrated that the performance and reliability of the elevator can be improved through analyzing the accumulated data.

Hyung-Joo Kim, Kwangil Lee

Survey on CPN Applications in Cloud Computing

The multiple issues in a Cloud-computing environment require formal verification and validation methods. Dozens of research works have been done in order to refer this topic. In this paper we would like to emphasis the CPN (Colored Petri Nets) based formal analysis of different aspects in cloud computing. Research works regarding to CPN applications in cloud computing were categorized into four classes. The paper also covers the CPN modelling approaches specifically oriented to solve issues in cloud environments.

Rustam Rakhimov Igorevich, Dugki Min

An Observation Method for Estimating Carrier Frequency Offset in OFDM Systems

Orthogonal Frequency Division Multiplexing (OFDM) is widely considered as an effective approach for current and future high-speed wireless communication. However, one of the main drawbacks of the OFDM is that it is sensitive to carrier frequency offset (CFO). The CFO causes interference among the multiplicity of carriers in the OFDM signal. Thus, the CFO must be estimated and compensated for in OFDM communication systems to minimize adverse effects of inter-carrier interference on the signal and maintain orthogonality. We propose a method based on observation training symbols for estimating CFO by employing block-by-block estimation. An analytical expression for the mean squared error of the frequency synchronization scheme is given and the results show that the proposed method has a superior performance compared to the conventional methods.

Mustafa Altaha, Humor Hwang

Korean-to-Korean Translation Based Learning Contents Management System for Parents of Multi-cultural Family

Language barrier, the major cause of information divide in multi-cultural families, has a close relationship with the low education level of children in multi-cultural families, which is foreseen to be an additional social problem resulted from aggravating economic inequality. Parents of multi-cultural families have restrictions in making efficient utilization of existing educational contents caused by remarkably falling behind information divide comparing with those ordinary families in terms of accessibility to digital devices and data utilization ability. In order to overcome these restrictions, it is imperative to build up a customized learning contents supporting system that provides contents appropriate to the understanding level of the learners. This paper designs the Korean-to-Korean Translation based learning contents system to dissolve the information divide in the parents of the multi-cultural families and as a result, it suggests the prototype of the Korean-to Korean Translation System to support the user customized learning contents for it.

YunHee Kang, Myung Ju Kang, WooSik Kim

A Distributed Survey Automation Based on a Customizable Form Template

The survey is a common approach to checking the validity and reliability of specific opinions, where a large enough number of samples is required to provide its statistical significance. However, if the survey data is too big for one person to handle and takes too much time, the questionnaire set should be divided into small pieces to reduce the respondent’s burden. In this paper, we propose a novel and practical approach to distribute survey data and generate questionnaires automatically based on customizable form templates. The separately collected results are merged into predefined repositories for further research. We apply the proposed method to evaluate the quality of bug reports. The experimental results show that it is relatively more effective than the manual process.

Jaekwon Lee, Kisub Kim, Jang-Eui Hong, Woosung Jung

Mobile Agent Oriented Service for Offloading on Mobile Cloud Computing

With the performance development of mobile devices, applications requiring high computing power are increasing. Therefore, the need for mobile cloud computing (MCC) is emerging to improve the computing. MCC can enhance performance for the required resources by integrating, managing and using the resources of many mobile devices. MCC models that are being serviced now use various offload processing methods, but no offload method considering the characteristics of mobile device has been defined yet. In this paper, offload methods that transfer the tasks of mobile devices from the MCC environment to the cloud are classified into Client-Server Communication, Virtual Machine Migration, and Mobile Agent, and Mobile Agent is subdivided into Client Mobile Agent and Server Mobile Agent. Thus, a total of five offload methods are defined. Instead of the offload methods that do not consider the mobile environment, the Mobile Agent Oriented Service (MAOS) is proposed as a new offload method.

HwiRim Byun, Boo-Kwang Park, Young-Sik Jeong

Unstructured Data Service Model Utilizing Context-Aware Big Data Analysis

Recently, the analysis of the structured data and the unstructured data in the various domains such as transportation and health care is essential. Especially, it requires intelligence and/or needs analyzing unstructured data, which accounts for a large proportion from big amount of information for the purpose of a more accurate information. Therefore, in this paper, we propose a unstructured data service model which provides a reliable and more precise information by using unstructured data analysis, and we try to show an example of application of the transportation system. We use KO-NLP, LSA, FCM Clustering, and machine learning techniques. We expect the proposed model might be used in the complex domains including too much unstructured data.

Yonghoon Kim, Mokdong Chung

Information Reminder System Based on Word Registered by User

According to the Hermann Ebbinghaus’s forgetting curve, the memory of people starts forgetting after 10 min more than 50 % after one hour. The reason that people typically record words on note is for reminding the words. If people don’t consciously search the recorded words on note, the words will be forgotten. This paper presents the information reminder system that helps a user to remind words. This system helps a user by giving the word highlighting the shades in case of a word that appear during web surfing.

KyeYoung Kim, Byeong-Eon Ahn, Suk-Young Lim, Daejin Moon, Dae-Soo Cho

A Study of Determining Abnormal Behaviors by Using System for Preventing Agricultural Product Theft

At present, the environment of agricultural production faces reduced productivity due to population decline and aging population, and agricultural products may be stolen anytime. To solve such problems, researchers have studied IoT-based smart farms. A smart farm is a system for enabling users to manage and control agricultural crops anytime anywhere on the basis of IoT (Internet of Things). This study aims to examine a system for preventing agricultural product theft by using an image monitoring system, for example, CCTV, which is part of the smart farm 1st model functions. First, the system uses image information inputted by the image monitoring system to detect objects loitering agricultural crops, and then uses directional change information to determine objects loitering the crops as abnormal behaviors. The system then uses the single-board computer, Raspberry Pi, to output real-time warning sounds and send the information of the object determined as abnormal behaviors to the user to prevent agricultural product theft.

Jin Su Kim, Min-Gu Kim, Byung Rae Cha, Sung Bum Pan

A Study of Simple Classification of Malware Based on the Dynamic API Call Counts

Recently, as the rapid development of the Internet enabled easy downloading of diverse files, the number of cases of file download from unreliable paths has been increasing. This situation is advantageous in that accessibility to information is improved while being disadvantageous in that there is no defense against exposure to malware. The present paper proposes a method of judging whether programs are malicious based on Cuckoo Sandbox, which is a dynamic malware analysis system and classify the programs by comparing malware programs collected and classified in advance based on the dynamic API call counts of the programs.

Jihun Kim, Seungwon Lee, Jonghee M. Youn, Haechul Choi

A Low-Power Sensing Management Method for Sustainable Context-Awareness in Exclusive Contexts

A context-aware service makes the assumption that two or more exclusive contexts are not inferred simultaneously such as driving and studying, indoor and outdoor. However, in practice they are sometimes inferred at the same time, and it causes inefficient power consumption because it does not make sense. To handle this problem and improve power efficiency, we propose a low-power sensing management method for sustainable context-awareness in exclusive contexts. In our method, we identify the exclusive contexts by using sensing models. Then, we determine next sensing time by utilizing supplementary sensor or increase the period of sensing in the exclusive contexts (i.e., back off). The results of our preliminary application show that the power efficiency is improved to 21 % in the exclusive contexts. The proposed method will be more effective when the exclusive contexts are inferred more frequently according to diffusion of context-aware services in the future.

Dusan Baek, Jae-Hyeon Park, Byungjeong Lee, Jung-Won Lee

Content-Based Conformance Assurance Between Software Research Documentation and Design Guideline

Research-oriented software groups are groups that carry out research on original technology for software. The groups on development phase experience poor documentation because of two reasons. One is the lack of resources (i.e. time, costs) since the development phase is much shorter than their research phase. The other one is that the artifacts they worked on research phase are rarely used on the development documents. Therefore, we propose a method that can reduce poor documentation regarding their research documents and development (R&D) documents. We construct design guidelines from best practices and represent it by queries of semantics-aware traceability links. Then, we use a semi-automated method of conformance assurance between R&D documents with guidelines. Finally, we provide an explanatory guideline to assessment results. We evaluated documents generated from our previous R&D project to show the possibility of our method. Our method can help software R&D project documents for better quality with reduced time.

Jong-Hwan Shin, Du-San Baek, Byungjeong Lee, Jung-Won Lee

Development of the Vision System and Inspection Algorithms for Surface Defect on the Injection Molding Case

The surface defects of plastic after the injection molding process have been inspected human inspector. In this paper, we propose the automated surface inspection system to detect 3D defects on injection molding objects. This vision system is equipped with 4-cameras and 8-illuminations and is designed to find optimal configuration between camera, illumination and object to detect the defects on an object. Also we develop algorithms to detect defects in captured images. The developed surface inspection system reduce the labor costs and time, whereas increase the detection accuracy of the surface defects such as scratch. The proposed algorithm uses the difference of the brightness of the obtained image by the camera and illumination system for acquiring data of the surface of the object. We focus on the surface defect detection of black molding object. Scratch detection is performed by the developed vision inspection system.

Ji Yeon Lee, Wonwoo Bong, Sangjoon Lee, Chang Ho Han, Kuk Won Ko

Implementation of the Smart System for Monitoring the PCG

In this paper, we implement the smart system for monitoring the phonocardiogram of a patient. The proposed system consists of a module to measure the phonocardiogram with Bluetooth communication and an encoder module for storing the measured phonocardiogram to a standard protocol. The system enables real time monitoring while following the international standards to store the health signals. Especially, we implement the system to monitor the PCG, and we show that the smart system can be utilized to monitor phono- cardiogram of patients in a mobile environment.

Sunho Kim, Kangwoo Lee, Yonghee Lee

The Effect of Introducing Small Cells in Wireless Networks

The use of small cells is one of the key elements for future wireless networks, which face ever-increasing demand for higher capacity. In this paper, we investigate the effect of introducing small cells in IEEE 802.11 wireless networks where access points of low transmit powers are mixed with access points of normal transmit powers. We use Poisson point processes to randomly locate normal access points, low-powered access points for small cells, and wireless users in a given area. We evaluate the effect of introducing small cells in the point of fairness among the wireless network users through simulations.

Soohyun Cho

An Enhanced Reliable Message Transmission System Based on MQTT Protocol in IoT Environment

IoT devices are widely used in everywhere for collecting data, controlling home equipment and so on. Also, MQTT protocol is used for sending a message in IoT devices because it is designed for a light-weight device and unreliable network condition. However, MQTT protocol has vulnerability to maintain order between messages against messages order is very important in some home automation such as controlling gas valve. In this paper, we design and implement a reliable message transmission system using MQTT protocol to maintain messages order.

Hyun Cheon Hwang, Ji Su Park, Byeong Rae Lee, Jin Gon Shon

Implementation of a Smart IoT Factory Using an Agricultural Grade Sorting Device

The purpose of this study is to implement the smart IoT factory through developing an automatic 6-years fresh ginseng grade classification device. The washed 6-years ginseng from farmland should be sorted 3 rating by a classification criterion such as weight and shape but this classification process has been conventionally performed manually and there are increasing sorting process costs. To overcome this disadvantage, we developed an automatic gin-seng sorting device. The 6 years ginseng put into the device for the classification is designed to perform such as the weight estimation and the shape analyzed by the image processing procedure, and classification result is sent to the factory server over the network. Evaluating the performance of developing machine experiment with 100 6-years ginseng showed a high recognition rate for 94 % for grade 1, 98 % for grade 2, and 90 % for grade 3.

Seokhoon Jeong, Ji Yeon Lee, Kuk Won Ko, Sangjoon Lee

Segmentation and Counting of Cell in Fluorescence Microscopy Images Using Improved Chain Code Algorithm

This study aims to automatically segment of oval cell in fluorescence stained cell image and quantify cell counts. For this study, an algorithm for oval cell contour tracking was suggested based on the classic chain code method and overlapped cells were segmented using border line angle variation information. For verifying the accuracy of the suggested method, our method and Freeman’s chain code method were applied to the same oval cell images. Then the border line tracking results were identified and the execution speed and computation per pixel were compared. Also, it was compared with the segmentation result of the Watershed technique, which is a general region-based segmentation, for evaluating the cell segmentation result with the naked eye. We applied an automatic algorithm to quantify cell counts in 20 cell images. For verifying the accuracy of cell counting, our algorithm was compared with the result of the manual counting method and ImageJ tool-based counting method.

Yeji Na, Sangjoon Lee, Jonggab Ho, Hwayung Jung, Changwon Wang, Se Dong Min

Empirical Study of the IoT-Learning for Obese Patients that Require Personal Training

Modern people are spending a lot of time and money for weight management, among them an increasing number of people to the personal training for the balance of his body. However, the public does not have the expertise are not easy to analyze the state of his body to find exercises in your body. So look for a lot of people to a personal training fitness center. However, personal training is difficult to continue to exercise because lifting is expensive. Therefore, we define a new concept of IoT-learning by integrating the IoT technologies and U-learning in this paper. We also propose a personalized personal training using IoT-learning. And it was mainly practices that can be applied.

Seul-Ah Shin, Nam-Yong Lee, Jin-Ho Park

Detection of Optimal Activity Recognition Algorithm for Elderly Using Smartphone

This is a preliminary study regarding the design of a fall prediction system. The purpose of this work is to determine an optimal classification algorithm for a fall prediction system that is able to recognize the gait difference between healthy and elderly people using a triaxial accelerometer sensor on a smartphone. To evaluate our approach, 19 people participated in our experiments. We collected accelerometer data as they performed daily activities such as walking, hobbling, and sticking, and features including the mean, standard deviation, and horizontal and vertical components were calculated. A Naïve Bayes classifier, a Bayesian network, a support vector machine, the k-nearest neighbors (k-NN) algorithm, a decision tree, multilayer perception, and logistic regression were used to classify these features using the Weka assessment tool. An 10-fold cross-validation method was carried out to classify daily activities and to compare the accuracy of the classification of daily activities for healthy and elderly people. As a result, the overall accuracy of recognition was 97.4 % for healthy adults and 71.1 % for elderly people, and the k-NN algorithm was higher than the other classification algorithms with accuracies of 99.5 % and 81.4 %.

Changwon Wang, Sangjoon Lee, Jonggab Ho, Yeji Na, Se Dong Min

Method of Detecting Malware Through Analysis of Opcodes Frequency with Machine Learning Technique

As the evolution of malware, vast damages are occurred in various industry fields. For this reason, research on malware detection has conducted actively. To improve the security of the network, SDN Quarantined Network (SQN) has been proposed. In this paper, we developed one of malware detection modules in first quarantine station in SQN by using the fact that benign and malicious files have different opcode frequency. And we applied machine learning technique as different way compare to conventional method. we verified that our module is valuable as one of detection modules and our final aim is to mount this module on the SQN system. Therefore, it would be possible more accurate inspection for new type of security attack with multiple detection modules.

Sang-Uk Woo, Dong-Hee Kim, Tai-Myoung Chung

Study of Big Data Analysis Procedures

In recent years companies and public institutions have long been accumulating and analyzing log data, and various types of data. It is building big data analytics platform for a variety of data analysis. Big data analysis platform may consist of distributed processing type quickly analysis large amounts of data. Recently, build a big data systems for companies and public institutions in the analysis of large amounts of data. Companies are providing a variety of services to users through data analysis. The public institutions are used to analysis a specific period of time and is useful in transportation, urban design, and commercial area analysis. In addition, national authorities to share that holds the data and the public and various analysis. However, it is a big data analytics projects that emerged as an issue in recent years this trend. Big Data Analytics project is to derive business results through data collection, data analysis and then build a big data platform. Currently, many companies have problems with the case of big data analysis projects using a methodology developed its own methodology and the CBD doing business. In this paper defines big data Analysis Methodology, and suggests construct standards and construct procedures.

Joon Ho Park, Jin Ho Park, Nam Young Lee

Design and Implementation of Authentication Information Synchronization System for Providing Stability and Mobility of Wireless Authentication

According to increasing the wireless network infrastructure and diffusion of mobile devices, the education environments equipped with mobile devices are gradually spreading in the field. The basic method to support stable wireless services in these education environments is to use wireless authentication technologies. The current education environments in Korea have been provided wireless authentication services with only unit of local areas. Accordingly, users cannot access the wireless network infrastructure for education in other areas outside local areas and thus the infrastructure is vulnerable to failures due to the lack of resource management and the absence of a backup authentication system for entire areas. In this paper, we suggest a Authentication Information Synchronization System (AISS) for stability and mobility.

Yong-hwan Jung, Jang-won Choi, Hyung-ju Lee, Joon-Min Gil, Haeng-gon Lee

Study on the Generic Architecture Design of IoT Platforms

A variety of application platform resulted in a variety of requirements that IoT systems should comply with. Due to the heterogeneity of the environments, the requirements varied significantly, and demanding more or less complex systems with varied performance expectations. This situation affected the architecture design and resulted in a range of IoT architectures with not only configuration setting of IoT devices and resources, but also varied environments of collaboration each devices. A number of things connecting it proposes a generic architecture design platform to useful the common characteristics which internet of things to control the flow of data.

Mi Kim, Nam Yong Lee, Jin Ho Park

A Study on Digitalization of Seafarer’s Book Republic of Korea for e-Navigation: Focusing on Wireless Network

Most of nations including the Republic of Korea require that the captain or the chief engineer of the ship who is in charge of safe navigation must carry a Seafarer’s certificate. However, different from the merchant seamen, a considerable number of Korean fishermen do not follow such a rule as the procedure to obtain the certificate is too inconvenient so that the certification system is in a way creating offenders unintentionally. Thus, this study focuses on digitalization of Seafarer’s certificate to adapt to forthcoming e-Navigation era. As a result/contribution, it became clear that the current BLE technology (2016) was most efficient in achieving this goal among various wireless network-oriented technologies. The author intends to introduce a prototype in the future study after applying for a patent.

Jun-Ho Huh

A PMIPv6-Based Auxiliary Mobility Management Considering Traffic Locality

Proxy mobile IPv6 (PMIPv6), which is a centralized mobility management protocol, is dependent on a local mobility anchor (LMA) to process all the data and control traffics. Therefore, it has serious problems such as the tremendous traffic concentration into the core network and the triangle routing that causes inefficient and non-optimized routing path. In this paper, therefore, in order to alleviate these drawbacks, we propose a PMIPv6-based auxiliary distributed mobility management scheme considering each mobile node (MN)’s traffic locality. Performance evaluation results indicate that in most cases, except for when the MN’s mobility rate is relatively very higher than the traffic rate, the proposed scheme shows better performance result than that of PMIPv6. Besides, it is demonstrated that the proposed scheme can be an effective alternative that can distribute significant loads on the LMA of the core networks to the MAGs of the edge networks.

Ki-Sik Kong

A Study on Worker’s Positional Management and Security Reinforcement Scheme in Smart Factory Using Industry 4.0-Based Bluetooth Beacons

The industrial accidents in the factories are continuously occurring globally and accordingly, the property damages and the number of human casualties are also increasing. The potential for the accidents at chemical plants are especially high as these factories heavily use or store many kinds of hazardous substances. Thus, separate preventive measures or tools are required. This study focused on a system that can prevent accidents and reinforce the security in a Smart Factory. The system uses Industry 4.0-based Bluetooth beacons to determine a worker’s position and enhance the security level. Converting to a Smart Factory, globally located factories are adding variety to all the processes in manufacturing and logistics. At the same time, some new and innovative methods are required to adapt to such changes, especially in the fields of safety and security. The existing communication method between beacons is that relevant application will be installed in the Bluetooth-activated devices such as Smart Pad, smart phone or other similar device to calculate the distance between the device and the beacon. The distance information will be then delivered to the server to control other devices/equipments in the factory. However, this method has a problem of using the Smart Pads in the factory due to the security or spatial characteristics of the factory and the system will cease to operate when battery life expires. To deal with such problems, a beacon has been attached on the worker’s safety helmet and synchronize beacon’s ID with worker’s ID so that the system can check the both signals to control worker’s access to the factory or let the security to take measures. Thus, this system allows an effective worker access control, notifications of entering danger zones, establishment of an efficient working condition through evaluating worker’s movements, estimating the positions of workers in the event of accident, and safe log-ins for factory’s security. Just by attaching the beacon on the worker’s helmet, no additional application installations, devices, and external network or GPS system will be needed so that an independent network can be established at the factories distant from cities.

SangIl Park, SeoukJoo Lee

A Study of the Extended Definition of Relation for Research Content Based Traceability

Trace artifacts refer to any residual data or marks of the R&D process that are made amenable to being trace. we applied this term to Research Contents for R&D project in our previous research. It is called Research Descriptor also known as RD. Furthermore, the existing researches failed to fully consider the research items existing in the form of various document files and SW configuration items, for example, the support for traceability among SW UML models and source codes, UI Form and test cases and issues on traceability with the conducted R&D process to make such outcomes. In this paper, we proposed extended definitions of various perspective relationship which to support traceability for research documents, processes and source codes during the whole period of the R&D project. Also, we considered definition of logical relationship between research contents and discussed how to manage the R&D project by tracking the RD relation type.

Jong-Won Ko, Jae-Young Choi, Young-Hwa Cho

Transforming Algorithm of 3D Model Data into G-code for 3D Printers in Distributed Systems

3D printing is a process of making 3D solid object from a digital STL file. 3D printer operates according to G-code. A STL file is composed of lots of facets, and the number increases depending on the size or precision of 3D model. In this paper, we have interests on devising an algorithm to transform STL file into G-code in distributed systems. The algorithm is divided into two steps: first, grouping facets according to Z-axis value, and second, generating G-code from facets. Through the simulation works, we come to know that the transformation can be done well in distributed manner.

Sungsuk Kim, Sun Ok Yang

Cache Aware Web-Based Dynamic Adaptive Streaming Algorithm in Information Centric Networks

Information Centric Networking (ICN) has attracted researchers as a future Internet architecture, because of its content dissemination based on names and ubiquitous in-network caching. Dynamic Adaptive Streaming over HTTP (DASH) has been deployed widely to provide video streaming in the Internet with high Quality of Experience (QoE) reflecting the heterogeneity of network connections and user devices. From reviewing previous studies on the effect of the cache to the dynamic adaptive streaming, pre-fetching of appropriate representations is a key issue. This paper proposes a client assisted dynamic rate adaptation mechanism that could invoke pre-fetching the anticipating representations to in-network cache. Simulation result shows our solution reduces the bit rate oscillations.

Geun-Hyung Kim

Background Subtraction Framework for Mobile 3D Sensor Data

The latest developments in artificial intelligence and sensors have been stimulating research on intelligent service robots and self-driving car technology. Such service robots and self-driving cars must take actions according to the situation by detecting human beings or dynamic environments. This paper proposes a framework that eliminates the background area to facilitate detection of moving robots or vehicles in a dynamic environment. The approach proposed in this paper can eliminate the background at high speed by analyzing an accumulation of 3D data through parallel processing using the voxel data.

Seongjo Lee, Seoungjae Cho, Nguyen Trong Hieu, Phuong Chu, Kyungeun Cho

A Method for Multi-user Re-identification in Invoked Reality Space

Natural user interfaces (NUIs) are commonly employed to allow multiple users to interact with each other in a defined space when implementing invoked reality. This has led to the investigation of user identification approaches as the basic technology enabling this interaction. However, the use of a single sensor complicates the accurate extraction of user-specific data because of the limited sensing scope and the occurrence of overlap among users. This paper proposes an approach based on the use of multiple sensors to re-identify users when multiple users repeatedly exit and re-enter the sensing scope.

Yunji Jeong, Yulong Xi, Jisun Park, Kyhyun Um, Kyungeun Cho

A Design Scheme of Combined Syllable Fonts for Hunminjeongeum

Hunminjeongeum can produce about 39.9 billion syllables formed from the combination of relevant fonts are needed in order to represent texts on the computer system. Due to the astronomical number of syllables, the design way is proper for the use of combined-style syllable fonts although fonts are represented in a somewhat less elegant way. In this paper, we analyze the structures of all syllables and propose a font design way that guarantees its completeness by identifying the number of basic glyphs of design target graphemes. And also we will show their efficiency through reduction rate.

Jeongyong Byun, Seongbum Hong, Hoyoung Kim

Proposal of a Resource-Monitoring Improvement System Using Amazon Web Service API

Cloud computing uses virtualization technology to segment mass computing resources into various service types, such as Infrastructure as a Service, Platform as a Service, and Software as a Service. The system manager does not need to manage hardware, resource expansion and reduction are convenient, and management is not restricted by time or space. The initial cost for installing mass servers and establishing service infrastructure can be effectively reduced. Amazon, IBM, and Microsoft are the main global vendors that provide the cloud computing service. They globally distribute and manage high-availability cloud service resources. However, when resources generated by users are in different management regions, they cannot be integrated and monitored in the management page provided by the service vendor. In this study, a resource-monitoring service using an API provided by the Amazon Web Service (AWS) was implemented; however, the reception latency time occurred continuously because information is received through the API every time the page changes from the actual service step. To solve these problems, the current condition collector that collects resource information was linked with database management system to enhance the performance by reducing unnecessary requests of calling the AWS API.

Kyu Ik Kim, Musa Ibrahim M. Ishag, Myungsic Kim, Jin Suk Kim, Keun Ho Ryu


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