Information Technology Convergence

In the vehicular area networks (VANETs), mobile station will frequently switch the associated base station. Reducing the number of handoff times is an import issue on retaining the quality of connection. In this paper, we propose two algorithms to solve this issue. The first one is named the Longest Distance Algorithm (LDA). We transform the handoff problem as finding the cross points of multiple circles and a line in a graph. The base station whose cross point is closest to the destination will be the candidate. The second one is called as Least Handoff Frequency Algorithm (LHFA). In the LHFA, the base stations are treated as the vertices. The link between two base stations implies mobile station can perform the handoff operation. The LHFA uses the Dijkstra’s shortest path algorithm to optimize the number of handoff times. The simulation results show that both the proposed LDA and LHFA algorithms can greatly reduce the numbers of handoff operations than the signal-strength algorithm.

One of the most important symmetric cryptographic algorithms is Rivest Cipher 4 (RC4) stream cipher which can be applied to many security applications in real time security. However, RC4 cipher shows some weaknesses including a correlation problem between the public known outputs of the internal state. We propose RC4 stream cipher with two state tables (RC4-2S) as an enhancement to RC4. RC4-2S stream cipher system solves the correlation problem between the public known outputs of the internal state using permutation between state 1 (

S

1

) and state 2 (

S

2

). Furthermore, key generation time of the RC4-2S is faster than that of the original RC4 due to less number of operations per a key generation required by the former. The experimental results confirm that the output streams generated by the RC4-2S are more random than that generated by RC4 while requiring less time than RC4. Moreover, RC4-2S’s high resistivity protects against many attacks vulnerable to RC4 and solves several weaknesses of RC4 such as distinguishing attack.

This paper designs a genetic algorithm-based relocation scheme for electric vehicle sharing systems, which suffer from the stock imbalance problem due to different rent-out and return patterns in different stations. To improve the service ratio, the relocation scheme explicitly moves vehicles from overflow stations to underflow stations. Each relocation plan is encoded to an integer-valued vector, based on two indexes, one for the overflow list, and the other for the underflow list. In each list, stations are bound to specific locations according to the number of surplus or needed vehicles. For a vector element, its location is the overflow station index, while the value is the underflow index. Iterative genetic operations improve the population quality, computed by the relocation distance, generation by generation. The simulation result shows that the proposed relocation scheme finds an efficient relocation plan in the early stage of iterations for the given parameter set.

By rapid evolution of information terminals, such as tablets and smart phones, people having multiple wireless communication terminals are expected to increase the information access and traffic amount. In public facilities, hot spots, and university campuses, the coverage area of the wireless Access Points (APs) is limited because of high cost. Therefore, it is difficult to provide stable network connectivity. In this paper, we focus on measurement of the coverage in our university campus. Using network simulation, we measured field strength and throughput for wireless APs. We optimized AP placement and improved the connectivity in our campus.

In this work, we evaluate the performance of OLSR and AODV protocols in a VANET crossroad scenario. As evaluation metrics, we use Packet Delivery Ratio (PDR), Throughput and Delay. We analyse the performance of the network by sending Constant Bit Rate (CBR) traffic and considering different number of connections. The simulation results show that when the number of connections is high, OLSR performs better than AODV protocol in this VANET scenario.

In WMNs mesh routers provide network connectivity services to mesh client nodes. The good performance and operability of WMNs largely depends on placement of mesh routers nodes in the geographical deployment area to achieve network connectivity, stability and user coverage. In this paper, we evaluate the performance of WMN-GA system for node placement problem in WMNs. For evaluation, we consider Normal, Exponential and Weibull Distribution of mesh clients and different grid size. The simulation results show that the grid size effects in the performance of WMN-GA. The system performs better for Normal distribution.

In this paper, we propose a watermarking algorithm based on Discrete Cosine Transform (DCT) using Two-dimensional Linear Discriminant Analysis (2DLDA) for color images. At first, the color image is converted into the YIQ color space and then transformed into the frequency domain by DCT. During the embedding stage, two watermarks of reference and logo are embedded into the Q component. Then, watermark extraction is done by 2DLDA from the Q component based on the frequency domain of DCT. By considering the Human Visual System (HVS), experimental results have shown that the watermark can be correctly extracted and better robustness is provided after various image attacks.

This paper presents a human action recognition algorithm using a depth image. First, 3D coordinates of the body’s joints of each frame are generated from the depth image. Then, the proposed method applies normalization and quantization processes to the body joints of all frames of the action video to obtain a 3D histogram. The histogram is projected onto xy, xz, and yz plans sequentially and combined into a one-dimensional feature vector. For dimension reduction, the principal component analysis (PCA) technique is applied to the feature vector to generate an action descriptor. To further improve the recognition performance, a decision tree method is developed to divide input actions into four main categories. The action description vectors of each category are used to design its respective support vector machine (SVM) classifier. Each SVM classifies the actions of a category into one type of actions. Experimental results verify that our approach effectively rules out the interference of background and improves the recognition rate.

Recently, Mobile Ad-hoc Networks (MANETs) have an increased interest in applications for covering rural areas due to the possibility of usage of low-cost and high-performance mobile terminals, without having to depend on the network infrastructure. Because the terminals are mobile, the routes change dynamically, so routing algorithms are very important for operation of MANETs. In this paper, we investigate the performance of Optimized Link State Routing (OLSR) protocol with ETX_ff, for different scenarios in indoor and outdoor environment considering throughput and packetloss metrics. We design and implement two experimental scenarios in our academic environment and compare their performance behaviour for different HELLO packets interval of OLSR protocol.

Recently, wireless communication systems are oriented to mobile communications, because of the increasing number of smart phones and tablets in today’s market. The interest on Mobile Ad hoc Networks (MANETs) is also increasing due to their potential use in several fields such as collaborative computing and multimedia communications. Thus, there is an increasing need to minimize the overhead introduced by routing protocols in the network. In this paper, we analyze the performance of a MANET by simulations, investigating the effects of RREQ, RREP and RERR, considering Random Waypoint Mobility (RWM) model. We consider the case when source and destination nodes are static. We evaluate the performance by measuring the throughput and AODV control packets, for single-flow and multiple-flow communication.

This paper is concerned with a numerical simulation of electric field distributions in urban areas by using the 1-ray model combined with 2-ray model. Introducing amplitude modification factor

$$ \alpha $$

and propagation order

$$ \beta $$

of distance, this model is arranged so that we can deal with propagation in complicated electromagnetic environments. We show that the two parameters

$$ \alpha $$

and

$$ \beta $$

can be obtained from Hata’s empirical equations. In this paper, we propose an estimation method for the electric field distributions in complicated propagation environments in addition to those areas defined by the Hata’s equations by employing statistical data such as building coverage and floor area ratios. Numerical analyses are carried out to show an example of distribution of amplitude modification factor

$$ \alpha $$

in Fukuoka city.

Buildings plays a very important role in the development of culture, art, history, and in our daily life. If we can retrieve unique features for describing a building, it might have some helps for architecture history, digital resources of architecture, even for determining the position of a person in the urban area. As the popularity of smart mobile devices, if we could have some interesting application for getting information of buildings around user, by captured building images in any direction and view, it will be a great help for the promotion of culture and tourism industry. In this paper, we propose a preliminary building recognition system using the SURF and color features for distinctive buildings in a city. This system using Google Street View’s images as a feature learning database. Based on the research of buildings’ characteristics in a modern city, the recognition system can identify buildings efficiently in different scales, rotation, and partial occlusion of the building’s image in this system.

Golf is well known worldwide as a prestigious and enjoyable sport. However, access to golf has been limited by high training costs, such as coaching fees, equipment, and course/driving range fees. This paper proposed a cost-effective golf assistive system, which is designed for golf beginners. This system uses Kinect sensor to detect beginners common swing mistakes. The experimental results indicate that the accuracy ratio in detection of errors is over 80 %. This paper provides a useful alternative assistive system for improving golf swings.

Ground Station Scheduling arises in satellite mission planning and belongs to scheduling family with time windows. It is know for its high computational complexity and hardness to solve to optimality. In fact, in some cases it is even hard to find a feasible solution that satisfies all user requirements and resource constraints. In this paper we present a Hill Climbing (HC) algorithm for the problem, which is a fast local search algorithm. Despite of being a simple search method, HC showed a good performance for small size instance while could not cope with medium and large size instances. The Satellite Toolkit is used for its experimental study and performance evaluation.

A virtual multiple message ferry backbone routing scheme dynamically adopts roaming mobile nodes as Virtual Message Ferries (VMFs) to be responsible for the message carrying and relaying tasks, but it does not alter the moving direction or speed of the chosen mobile nodes. In this routing scheme, the intermittent connected routing problem of a Mobile Ad-hoc Network (MANET) can be much relieved by properly planned multiple VMF trajectories and the respective VMF dispatch time scheduling. In our previous research works [

1

], we discussed a VMF dispatch time scheduling optimization problem called the Virtual Multiple Message Ferry Dispatch Scheduling (VMMFDS) problem to minimize the total transfer waiting time of all-pair source–destination paths. In this paper, we provide a further theoretical property of the VMMFDS solution. Besides, a ring-based VMF backbone routing scheme, which includes the ring pattern VMF trajectory planning and the respective VMF dispatch time scheduling is also addressed.

This paper presents a location-estimation experimental platform based on the error propagation approach to reduce the computational load of traditional algorithms. For the experimental platform with the scalar information, the proposed technique based on the Bayesian approach is handled by a state space model; a weighted technique with the reliability of the information passing is based on the error propagation law. As compared with a traditional Kalman filtering (KF) algorithm, the proposed algorithm has much lower computational complexity with the decoupling approach. Numerical simulations and experimental results show that the proposed location-estimation algorithm can achieve the location accuracy close to that of the KF algorithm.

In this paper, we propose and implement a system based on Hill Climbing algorithm, called WMN-HC. We evaluate the performance of the proposed system by different scenarios using giant component and different distribution of mesh clients. We present some evaluation scenarios and show that the proposed approach has a good performance.

Wireless Mesh Networks (WMNs) currently have a lot of attention in wireless research and technology community due to their importance for providing cost-efficient broadband connectivity. Issues for achieving the network connectivity and user coverage are related with the node placement problem. In this work, we consider the router node placement problem in WMNs. We want to find the most optimal distribution of router nodes in order to provide the best network connectivity and provide the best client coverage in a set of uniformly distributed clients. We use our WMN-SA simulation system to calculate the size of Giant Component (GC) and number of covered users with different number of iterations per phase of Simulated Annealing (SA) algorithm calculations. From results, SA is good algorithm for optimizing the size of GC. While in terms of number of covered users, it does not cover all users. The performance of WMN-SA system increases when we use more iterations per phase.

Intelligent information management systems that analyse management processes and support strategic decision taking will be discussed based on the example of cognitive data management systems. This group of information management systems is about taking strategic decisions at enterprises by semantically analysing selected groups of economic and financial ratios. This publication will discuss systems classed as UBMLRSS (

Understanding Based Management Liquidity Ratios Support Systems

)–cognitive systems for analysing enterprise liquidity ratios which will reason about the resources and the solvency of the working capital of the company as well as about its current operations based on a semantic analysis of a set of selected ratios. UBMLRSS systems represent one of four classes of Cognitive Financial Analysis Information Systems.

In this paper, we proposed a tool framework of static analyzer for taint analysis of binary executable file. Dynamic taint analysis is becoming principal technique in security analysis. In particular, proposed system focuses on tracing a dynamic taint analysis. Moreover, most existing approaches are focused on data-flow based tainting. The modules of this paper use two kinds of input file type which are taint_trace file and binary executable file. Proposed system analyzes the result of dynamic taint analysis and makes control flow graph. Our proposed system is divided by three modules; taint reader, crash analyzer and code tracker. Trace reader converts trace file into readable/traceable information for a manual analyzer. Crash analyzer find out a vulnerability that is a causative factor in accrued crash. Code tracker supports a variety of binary executable file analysis. In this paper, we suggest a tool framework for dynamic taint analysis.

In this paper, we propose a framework based on Internet of Things (IoT) and P2P technology for supporting learning and improving the quality of life for children with Autism Spectrum Disorder (ASD). Many children with autism are highly interested and motivated by smart devices such as computers and touch screen tablets. These types of assistive technology devices get children with autism to interact, make choices, respond, and tell parents what they want, need, think, and maybe even feel. Out framework uses JXTA-Overlay platform and smartbox device to monitor the children and create P2P communication between children, parents and therapists. Various visual systems, such as objects, photographs, realistic drawings, line drawings, and written words, can be used with assorted modes of technology, as long as the child can readily comprehend the visual representation. Vocabulary skills such as names of common everyday objects, fruits, animals, toys, names of familiar people can be taught through our proposed framework.

Mobile devices, with their excellent portability and increasing computational power, are increasingly being used for communication and financial transactions. As they are used in close relation to people, their security is becoming more important. Faceless verification systems with improved security performance, including face or fingerprint verification, are recently being required. Fingerprint verification is a suitable method in a faceless environment. However, the commonly used Minutiae-based fingerprint verification shows a drop in the performance of fingerprint verification, due to the decreased number of minutiae, when the number of acquired images is small. Especially since the values around the threshold of similarity are similar in the genuine and imposter, many errors could occur here. The minutiae-based fingerprint verification has a limitation in addressing these problems. A hybrid-based verification method that uses two or more fingerprint matching methods can address these problems better. Therefore, this paper has conducted the binary-image-based fingerprint verification in the partial band around the threshold. From the results of the experiment, it can be seen that the Equal Error Rate (EER) was improved by a total of 42 %, from 3.01 % to 1.73 %, by reducing the False Match Rate (FMR) in the partial band area around the threshold. In addition, it was improved by reducing the FMR by a total of 89 % from 2.77 % to 0.28 %.

Medical image segmentation is an image processing technology prior to performing a variety of medical image processing. Therefore, a variety of methods have been researched for fast and accurate medical image segmentation. Performing segmentation in various organs, you need the accurate judgment of the interest region in medical image. However, the removal of interest region occurs by the lack of information to determine the interest region in a small region. In this paper, we improved segmentation results in a small region in order to improve the segmentation results using volume data with a linear equation. In order to verify the performance of the proposed method, lung region by chest CT images was segment. As a result of experiments, volume data segmentation accuracy rose from 0.978 to 0.981 and from 0.281 to 0.187 with a standard deviation improvement was confirmed.

In this paper, we evaluate the performance of WMN-GA system for node placement problem in WMNs. For evaluation, we consider Weibull Distribution of mesh clients and different selection and mutation operators. The population size is considered 64 and the number of generation 200. For evaluation, we consider the giant component and the number of covered users metrics. The simulation results show that the WMN-GA system performs better for Single Mutation and Linear Ranking.

Recently, in order to assist the disabled people moving around, many support systems and tools have been developed. However, a moving person supported by wheelchairs in the building has a significant problem of lacking GPS signal. This paper presents a new indoor navigation system for wheelchairs, using smartphones as a sensor and navigation medium. In this navigation system, the wheel sensor in the wheelchair and the digital compass of the smartphone are used to calculate the current location accurately. Moreover, the navigation system provides a map function that displays possible and optimum routes of passage in a wheelchair from the current location to a destination in the building. The experimental results and evaluation are also presented.

Wireless Sensor Networks (WSNs) have become a hot research topic in academia as well as in industry in recent years due to its wide range of applications ranging from medical research to military. In this paper, we study the effect of mobile sink in WSN performance. The WSNs should allow a systematic deployment of sensor nodes including mobility among the sensor nodes. The disseminated data from the sensor nodes are gathered at the sink node. Data dissemination is the major source for energy consumption in WSNs. We consider as evaluation parameter goodput and depletion to evaluate the performance of WSNs considering different speeds of mobile sink. The simulation results show that, when the

$$ T_{r} $$

is lower than 10 pps, the network is not congested and the goodput is higher when the sink node moves faster (20 m/s). When

$$ T_{r} $$

is lower than 10, the depletion is higher when sink moves with lower speed (5 m/s). But, when

$$ T_{r} $$

is larger than 10, the depletion is higher for higher values of the sink speed (20 m/s).

A neural network based direct torque control of an induction motor was presented in this paper. The paper trained a neural network for speed controller of the machine to use in the feed-back loop of the control system. The description of the control system, training procedure of the neural network is given in this paper. The complete neural network based direct torque control scheme of induction motor drive is simulated using MATLAB. The acquired results compared with the conventional direct torque control reveal the effectiveness of the neural network based direct torque control schemes of induction motor drives. The proposed scheme improved the performance of transient response by reduces the overshoot. The validity of the proposed method is verified by the simulation results.

As the Big Data is handled in the modern Internet, it needs various efficient search methods to retrieve the required information in the flood of information. In this paper, we propose a new Hierarchical Search Interface by Self-Organizing search method with a smartphone. The users can search the objective terms by pushing buttons for each adaptive hierarchical categories without any input of keyword. We describe the experimental results and the effectiveness of the proposed system is confirmed by the prototype simulation.

This paper focuses on improving induction motor performance by controlling its speed. The induction motor speed is controlled using field oriented control based structure associated with an induction motor. The field oriented control is implemented by combining with fuzzy logic control to reduce the uncertainties factors. The fuzzy logic control is developed based on Mamdani method. The inputs of fuzzy logic control are the error and derivative error between actual and reference speed of induction motor. The output of fuzzy logic control is the reference electric torque. The fuzzy logic control input output variables membership functions are chosen based on the parameters of the motor model. Motor state variables are identified indirect from induction motor model. The controller develops is implemented MATLAB Simulink. The simulation result shows that the fuzzy logic control is a suitable controller for improving induction motor performance with gives less settling time and steady state error than Proportional Integral Derivative control.

In Wireless Sensor Networks (WSN), cluster formation and cluster head selection are critical issues. They can drastically affect the network’s performance in different environments with different characteristics. In order to deal with this problem, we have proposed a fuzzy-based system for cluster-head selection and controlling sensor speed in Wireless Sensor Networks (WSNs). The proposed system is constructed by two Fuzzy Logic Controllers (FLC). We use four input linguistic parameters for evaluating lifetime of a sensor in FLC1. Then, we use the output of FLC1 and two other linguistic parameters as input parameters of FLC2 to control the probability of headcluster selection. By considering the moving speed of the sensor we are able to predict whether the node will leave or stay in the cluster. In this paper, we evaluate FLC1 and FLC2 by simulations and show that they have a good behavior.

This paper presents the performance analysis of the field oriented control for a permanent magnet synchronous motor drive with a proportional-integral-derivative and artificial neural network controller in closed loop operation. The mathematical model of permanent magnet synchronous motor and artificial neural network algorithm is derived. While, the current controlled voltage source inverter feeding power to the motor is powered from space vector pulse width modulation current controlled converter. The effectiveness of the proposed method is verified by develop simulation model in MATLAB-Simulink program. The simulation results prove the proposed artificial neural network controller produce significant improvement control performance compare to the proportional-integral-derivative controller for both condition controlling speed reference variations and constant load. It can conclude that by using proposed controller, the overshoot, steady state error and rise time can be reducing significantly.

The number of smartphonesis increased exponentially and they are promising tools for interactive learning during lectures in the universities. However, when in a lecture roomtens of sets of smartphones want to make simultaneous connection by Wi-Fi, the traffic will be increased and the network will be congested. In this study, we examined the effective use of the smartphones during the lectures. We considereda method of acquiring/utilizing the study records, which improves the students’learning motivation. In this research, we use smartphones as information terminals and carried out experiments in a real lecture room. The proposed method improves the degree of lecture understanding, thus improving students’ learning motivation.

Evolved from conventional Flexible Macroblock Ordering (FMO) that is coded out of raster sequence in spatial domain, this paper presents Wavelet-domain slice group partition and unequal error protection for H.264/AVC video communication. In detail, this paper develops Wavelet-based FMO (WFMO) algorithm to adaptively allocate macroblocks into 4 slice groups based on Reverse Biorthogonal (rbio) Wavelet transform, and then adopts unequal Reed-Solomon error correction to enhance the robustness of the packet carrying the slice group of most significance and psychovisual sensitivity. Experimental results show H.264/AVC codec with proposed Reverse Biorthogonal (rbio) WFMO can achieve better subjective and objective video quality under various packet loss conditions than that without FMO and that with conventional FMO. On the other hand, a DaVinci embedded platform implementation of H.264/AVC surveillance camera featuring rbio WFMO is accomplished. Implementation results demonstrate the video communication quality of H.264/AVC surveillance camera featuring rbio WFMO is superior under error-prone network environments and feasible for embedded real-time applications.

In recent years, QR code is widely used in the accessing to the Internet by cellular phones. As this code is a set symbol of simply black and white dots, it is very simple and insipid. In order to improve this weakness, a color two-dimensional color code editor with dotted images has been developed. This paper presents the design method and reading characteristics of the code editor. The experimental results show good performances of the decoding characteristics by the existing QR decoder and the effectiveness of the editor is also confirmed.

Post wall waveguide is important structure for microwave transmission of integrated circuits with multi-layered substrates. It has simple periodic array of metallic or dielectric cylinders between parallel conducting plates. In this study, loss of bending part with the angle of 120° in post wall waveguide was evaluated both numerically and experimentally for microwave. We proposed the best configuration for bending part of the post wall waveguide.

The UMTS and LTE/LTE-Advanced specifications have been proposed to offer high data rate for the forwarding link under high-mobility wireless communications. The keys include supporting multi-modes of various coding schemes (e.g., VSF-OFCDM, OFDM, OFDMA), multiple-input multiple-output, relay networks, etc. To balance loads among different communication interfaces is one of the most important issues that should be addressed for achieving efficient radio resource allocations. In a shared packet service, the 3GPP UMTS adopts the VSF-OFCDM interface to allocate orthogonal codes of an OVSF code tree in two-dimension (2D) spreading of the time and frequency domains. Conversely, although the LTE/LTE-Advanced interface offers a high data rate, it suffers from unbalanced loads and moderate reward. This paper thus proposes an adaptive radio resource allocation for balancing loads between the UMTS and LTE/LTE-Advanced interfaces according to various interference and mobility environments. Additionally, an adaptive multi-code allocation is proposed for the UMTS to minimize the bandwidth waste rate while guaranteeing quality of service. Numerical results indicate that the proposed approach outperforms other approaches in fractional reward loss and system utilization.

It is very convenient to carry smartphones and take photos on the trip. With Apps installed in smartphones, users can easily share photos to friends on social networks. Huge amount of interesting photos are therefore accumulated through smartphones without facilities to manage these photos. We propose an integrated system that provides a mobile App for photographing on the trip, a desktop App for synchronizing photos with the web platform for sharing and organizing photos. While photographing, the web service recommends significant tags to photos and gets manual tags, the App transparently accumulates context-information for travel photos. Then, the desktop App facilitates users to collect and choose interesting photos for sharing and storing on the web platform. Finally, the system applies search engine and web mining techniques to extract textual sentences from pages that contain relevant information about photos for writing travel blogs easily and efficiently.

The paper presents a framework that exploits the Thai Wikipedia articles as a knowledge source to train the machine learning classifier for link suggestion purpose. Given an input document, important concepts in the text have been automatically extracted, and the chosen corresponding Wikipedia pages have been determined and suggested to be the destination links for additional information. Preliminary experiments from the prototype running on a test set of Thai Wikipedia articles show that this automatic link suggestion framework provides reasonably up to 90 % link suggestion accuracy.

Dynamic behaviors of World Wide Web is one of the most important characteristics that challenge search engine administrators to manipulate their search collection. Web content and links are changed each day to provide up-to-date information. In addition, a fresh web page, like new news article, is often more interesting to web users than a stale one. Thus, an analysis of temporal activities of the Web can contribute to improve better search and result ranking. In this paper, we propose a web personalized link-based ranking scheme that incorporates temporal information extracted from historical page activities. We first quantify page modifications over time and design a time-proximity model used in calculating inverse propagation scores of web pages. These scores are then used as a bias of personalized PageRank for page authority assessment. We conduct the experiments on a real-world web collection gathered from the Internet Archive. The results show that our approach improves upon PageRank in ranking of search results with respect to human users’ preference.

The most of very large traffic system by growing the variety of services, the relationships between the vehicle network and the infrastructure are more complex. Moreover, intelligent transportation systems are getting more and more to develop a better combination of travel safety and efficiency since long time ago. Vehicle is being evolved and traffic environment is especially also organized well-defined schedules priorities, which is real time based wireless network traffic condition, variable traffic condition, and traffic pattern from the vehicle navigation system. Accordingly, we propose to Knowledge-based Self-adaptive Vehicle Trajectory Service using genetic algorithm in this paper.

This work considers the secure and reliable information transmission in two-hop relay wireless networks without the information of both eavesdropper channels and locations. This papers focuses on a more practical network with finite number of system nodes and explores the corresponding exact results on the number of eavesdroppers the network can tolerant to ensure a desired secrecy and reliability. For achieving secure and reliable information transmission in a finite network, two transmission protocols are considered in this paper, one adopts an optimal but complex relay selection process with less load balance capacity while the other adopts a random but simple relay selection process with good load balance capacity. Theoretical analysis is further provided to determine the exact and maximum number of independent and also uniformly distributed eavesdroppers one network can tolerate to satisfy a specified secrecy and reliability requirements.

Rivest Cipher 4 (RC4) is one of the modern encryption techniques utilized in many real time security applications; however, it has several weaknesses including a correlation problem in the initially generated key sequences. In this paper, we propose RC4 stream cipher with a random initial state (RRC4) to solve the RC4’s correlation problem between the public known outputs of the internal state. RRC4 solves the weak keys problem of the RC4 using random initialization of internal state

S

. Experimental results show that the output streams generated by RRC4 are more random than that generated by RC4. Moreover, RRC4’s high resistivity protects against many attacks vulnerable to RC4 and solves several weaknesses of RC4 such as predictable first bytes of intermediate outputs by RC4.

A client usually issues a request to one server in a cluster of servers and the server sends a reply to the client. Once the server stops by fault, the client is suspended to wait for a reply. In order to be tolerant of server faults, each request is redundantly performed on multiple servers. Here, the more number of servers a request process is redundantly performed, the more reliable but the more amount of electric energy is consumed. Thus, it is critical to discuss how to realize energy-aware, robust clusters of servers. In this paper, we newly propose the improved redundant power consumption laxity-based (IRPCLB) algorithm where once a process successfully terminates on one server, meaningless redundant processes are not performed on the other servers. We show the total power consumption of servers is reduced in the IRPCLB algorithm.

In this publication will be described the most important security issues connected with a new generation of information systems focused on cognitive information systems (CIS). Such systems are mainly designed to perform a semantic analysis of complex visual structures, as well as human-being behavioral analysis. In our paper will be presented the ways of ensuring the secrecy of information processing in such systems, as well as some new opportunities of using semantic information processed by CIS to develop a new cryptographic protocol for personal authentication and secret information distribution. The paper will describe both CIS internal security features, and external possible application of authentication procedures along with intelligent information management.

In order to identify and reduce the chance of vulnerability, a novel policy-based intrusion tolerant system (ITS) is studied in this paper. The suggested scheme quantifies the vulnerability level first, and then applies it to decide the candidate of the next rotation based on a policy. Experiments using CSIM 20 proved that it has enough capability to hide the VM rotation pattern which attackers are generally interested in and reduces the data leakage of the system greatly in spite of increasing the number of exposures.

Due to the prevalence of e-learning and information technology, a wide choice of various learning styles is offered. So we might have multiple learning paths for a teaching material. However, learners differ from one another in their information literacy and cognitive load. These will influence the learning achievements greatly. Learners lacking information literacy are probably not able to determine their leaning paths easily. For example, obligatory courses, precedence relationship, time limit, and leaning effect should be taken into account. In light of these observations, we propose a genetic algorithm for determining leaning paths with many topics and a branch-and-bound algorithm for providing optimal learning paths of few learning topics.

In this paper, we propose a new fuzzy-based trustworthiness system for P2P Communications in JXTA-Overlay. This system decides the Peer Reliability (PR) considering three parameters: Actual Behaviour Criterion (ABC), Reputation (R) and Peer Disconnections (PD). We evaluate the proposed system by computer simulations. The simulation results have shown that when there are too many peer disconnections, although the reputation and the ABC are improved, the peer reliability remains very low. For few peer disconnections, peer reliability is increased with the increasing of ABC, R and PD and the system have a good performance.

Clustering is the most important task in unsupervised learning and applications is a major issue in cluster analysis. Digital learning, which arises in recent years, has become a trend of learning method in the future. The environment of digital learning may enable the learners work anytime and everywhere without the limitation of time and space. Another great improvement of digital learning is the ability of recording complete portfolio. These portfolios may be used to gain critical factors of learning if they are analyzed by data mining methods. Therefore, in this research will to analyze the records of students’ portfolios of game-based homework by using Clustering Algorithm Based on Histogram Threshold (HTCA) method of data mining. The HTCA method combines a hierarchical clustering method and Otsu’s method. The result indicates that the attributes or categories of impacting factors and to find conclusions of efficiency for the learning process.

Recent rapid evolution of networking technologies and computing service technologies has lead a wide variety of Social Networking Services (SNS). In campus education environment, there are several specific social networking services for campus community members, which include teaching, class schedule, club activities, and practical use of campus buildings. In this paper, we have designed and implemented dedicated social network service systems for small grouped campus networks. The designed SNS systems, called

CamBook

, supports easy campus-based SNS services. It supports class management, club management, and augmented reality-based navigation services. With the services, campus members can use their campus lives efficiently.

Removable Storage provides excellent portability with lightweight and small size to fit into one’s hand. Many users have turned their attention to high-capacity products. However, Removable Storage devices are frequently lost and stolen due to their easy portability. Many problems, such as the leaking of private information to the public, have occurred. The advent of remote storage services, where data is stored throughout the network, has allowed an increasing number of users to access data. The main data of many users is stored together on remote storage, but this has the problem of disclosure by an unethical administrator or attacker. Data encryption on the server is necessary to solve this problem. A searchable encryption system is needed for efficient retrieval of encrypted data. However, existing searchable encryption systems have low efficiency for data insert/delete operations and multi-keyword search. This paper proposes an efficient searchable encryption system.

Data outsourcing services have emerged with the increasing use of digital information. They can be used to store data via networks and various devices, which are easy to access. Unlike existing removable storage systems, storage outsourcing is available to many users because it has no storage limit and does not require a storage medium. However, the reliability of storage outsourcing has become an important topic because many users employ it to store large volumes of data. To protect against unethical administrators and attackers, a variety of cryptography systems are used, such as searchable encryption and proxy re-encryption. However, existing searchable encryption technology is inconvenient for use in the storage outsourcing environments where users upload their data, which are shared with others as necessary. The users also change frequently. In addition, some existing methods are vulnerable to collusion attacks and have computing cost inefficiencies. In this paper, we propose a secure and efficient method for data storage and sharing during data outsourcing.

There has been an increase in the use of mobile devices. Further, the Internet environment has changed from a wired network to a wireless one. However, the existing wired security solutions are difficult to apply to the wireless network. In this paper, we propose a model for using enhanced mobile office service in a wireless network. This model also provides greater access control and a more secure mobile office.

Cloud computing is a new trend that is expected to reshape the information technology landscape. It can provide a new process to user such as software, infrastructure and platforms as a service over the Internet. In this trend, traditional way for manufacturing system has been changed from set up the system software in the machine to access internet and use it at anytime. Manufacturing system has process consists of many production parts and stages. And control and operate status is necessary to monitor, observe and mange the system very often. In this paper, we propose component model for manufacturing system in cloud computing environment. This model consists of three layers; manufacturing cloud, service cloud and user cloud. And each layer relate their role to other factor in the cloud.

This research aims to develop Korean traditional culture’s learning system. This system was processed using internet. And the target is folk literature, Pansori. Actually, in spite of Pansori is one of famous folk literature, it is not familiarly area on peoples due to difficult learning and understanding them. Our system attempt to provide Pansori’s learning materials to user very easily and conveniently. The learning materials were managed by learning meta data in LCMS and learning process data was controlled by LMS.

First-come-first-serve (FCFS) scheme is used for selling the tickets in ticket market that is a multi-million dollar industry for any popular event. But in a competitive environment is this FCFS efficient? In earlier literature it has been shown that the auction based alternative solutions using the framework of mechanism design, a sub field of game theory, can provide better results against FCFS in terms of profit making and efficiency in allocation. However the solution proposed in the earlier literature can address the ticket selling environment where an agent can give demand for a single ticket in static environment. In many situations a single agent can give demand for multiple tickets in static environment. In this paper, with the use of mechanism design framework some elegant solutions are proposed in static environment where an agent can give demand for multiple tickets.

The growing availability of information technologies has enabled law enforcement agencies to collect detailed data about various crimes. Classification techniques can be applied to these data to build decision-aid tools and facilitate investigations of law enforcement agencies. In this paper, we propose an approach for constructing a decision tree based classification model for a crime prediction. Proposed model assists law enforcement agencies in discovering crime patterns and predicting future trends. We provide an implementation and analysis of our proposed method.

Theoretical suggestions are inconsistent with empirical findings about whether patent pools encourage innovation domain. This paper empirically examines the firm-level innovation on patent pool formation. In order to empirically investigate the variance of the innovation performance of patent pool, this paper proposes hypothesis for post-formation innovation performance in comparison to pre-formation one in the DVD (Digital Versatile or Digital Video Discs) 3C pool members. This paper employs well-used patent quality indicator- forward citation count as patent quality measurement. To further test the hypothesis, this paper will apply one-sample

t

-test to conclude whether the mean of the post-formation forward citation count significantly declines comparing with the pre-formation one. Based on the result, this paper aims to verify whether patent pools formation slow down patent innovation performance from firm-level perspective and contribute to the growing literature on the effect of institutional innovations on the follow-on innovation.

A wireless sensor database differs from a relational database, in that it is comprised of a wireless sensor network (WSN), not disks. Nevertheless, the sensing data in the wireless sensor database still are represented as tables. Abstracting the sensing data as the table, end users are able to use SQL to retrieve the required sensing data and do not become aware of the WSN. In the wireless sensor database, top-k monitoring query is an important application and has received much attention in the research community. This research builds on an existing wireless sensor database, TinyDB, and equips TinyDB with the function of performing top-k monitoring queries. The end users finally are able to submit a top-k SQL statement to the wireless sensor database and indeed retrieve the required top-k sensing readings from the WSN.

There are many endpoints such as notebooks and desktop computers in the internal environment of modern enterprise. However, convenient network applications accompanied by the threat of various forms of information, such as computer viruses, spyware, operating system vulnerabilities, a malicious web site, attack of malware. The endpoints are the largest number of the subject in the corporate computer environment. If information threats affect the endpoint operation, the business operations and revenue will suffer the loss. The main purpose of this study is focus on the endpoint protection for enterprises. The research adopts ITIL management framework approach to provide endpoint protection management and assessment methodology of effectiveness. The proposed approach could be regarded as planning reference for information department during endpoint protection management. Besides, the proposed approach provides protection mechanisms for enterprise endpoint to reduce the impact from information threats.

Traditionally, e-services are composed to assist the enterprise business process. In recent years, Software as a Service (SaaS) model in cloud computing enriches the mobile commerce. Mobile commerce promotes the service providers building an application market platform to serve customers. However, an application market platform may collect a huge number of mobile application services (mobile Apps) and each App is usually designed with little functionality. A customer may fetch a number of Apps to mash up in order to satisfy his/her comprehensive requirements. How to mash up the Apps to provide a feature-rich composition for a customer becomes an interest research issue. In this work, we explore an approach of Apps mash-up composition in a service platform for adaptive content recommendation. A user profile conducts the service level agreements in evaluating the service quality. An Apps mash-up composition is recommended to the customer an adaptive content in a ubiquitous environment.

Global navigation satellite system is fully well developed in outdoor positioning nowadays; however, it cannot be applied in indoor positioning. The research of indoor positioning is rapidly increasing in recent years, and most researchers have paid much attention to RFID technology in indoor positioning; however, RFID is restricted by hardware characteristics and the disturbance of wireless signals. It is difficult to deal with the RFID positioning method. Therefore, this paper proposed an indoor real-time location system combined with active RFID and Kinect. Based on the identification and positioning functions of RFID, and the effective object extraction ability of Kinect, the proposed system can analyze the identification and position of persons accurately and effectively.

Most of the museum navigation systems lack the function of user interaction. Even the small number of systems with user interaction functions, but required special and expensive devices, or may use non-intuitional operation methods. This paper used popular and economic Microsoft Kinect devices to establish an interactive 3D museum navigation system that supports intuitional commands. The users are allowed to intuitively control the 3D navigation system by physical motions and voice commands without wearing any additional appliances. The experiments show that the proposed system improves the effect of navigation satisfactorily.

Quick response (QR) code is a convenient product for mobile phone user. People can use the Smartphone camera to capture the code, and then decode it through dedicated reader application. Usually the code stands for text, contact information, or a web hyperlink. Users scan the image of QR code to display information or open a website page in the phone’s browser. QR codes appear everywhere on posters, publicity flyers, TV advertisements, and even business cards. Since QR code looks like random noise, its existence may hurt the picture of commodities. In this paper, we propose a data embedding scheme to camouflage the existence of QR code. Experimental results showed that the proposed scheme hides the QR code successfully. Moreover, the quality of stego-images is nearly to 30 dB.

People living become highly informationized, resulting in Tablet PC has developed vigorously in recent years. To understand the consideration of the customers when purchasing Tablet PC is getting important. This study applies Fuzzy Analytic Hierarchy Process (FAHP) to find out the key factors affecting the consumer’s purchasing of Tablet PC. Further, combining Multidimensional Scaling (MDS), decision maker can realize that the similarity and difference among the consumer groups. Through literature review and expert interview, we select appropriate evaluation components to construct the hierarchical structure of evaluation and conduct the AHP questionnaire on 15 experts. The FAHP analysis results show that the importance of evaluation criteria in following order: operating system, color and hardware while customer intend to buy a Tablet PC. Furthermore, through the perceptual map of MDS, we could be find out the consumer groups of Businessman and Officer, as well as Student and Housewife, have similar demands when purchasing Tablet PC.

Game based learning involves interesting story, interaction and competition elements which promote the imagination, interest, concentration and creativity of the learner. Besides, ubiquitous learning integrates location-aware and context-aware technology in our living environment. Learners are motivated by firsthand or second historical relics. Visiting and interview activities with old people also promote learners have history thinking. Combining the u-learning environment and cognitive apprenticeship which reveals the solving problem inner progress from the expert, learners observe, learn, scaffold and exploration in the proposed system. The game-based history ubiquitous learning environment integrated into cognitive apprenticeship theory. The learners can challenge the game tasks by their own group or compete with other teams or collaborate with other teams.

According to the empirical observation that group decision making can not only provides people much comprehensive information and knowledge to face the rapid development of modern sciences and technologies, but also provides people much different and various point of view. Participants are 106, belong to two classes of undergraduate students, to discuss sharing of content online for corporate communications issues, web content, text to speech acts to quantify the qualitative coding analysis, sequence analysis of the behavior of the conversion, is used explore discuss the generation of behavior patterns. The study looked at students’ learning to the corporate communications knowledge sharing activities online, so its contents and recommendations of the results thus affecting the limit.

From the perspective of instructional design, when facing the different knowledge domains, the instructional strategies and activities should be matched for the different contents It is equally important when using LMS as a delivering platform for the web-based learning. However, regardless the popular mutual functions, most of LMSs do not provide teaching supporting tools or activities in particular knowledge domains for instructor to use. Therefore, LMS is only working as a better looking FTP, but not able to help instructors to deliver better instruction.In order to tackle this issue, this study first employed content analysis to induce the teaching strategies of conceptual knowledge domain and analyze the basic functions of LMSs on market. Then, following the content analysis, based on the open source code LMS Moodle, a plug in, strategical learning tool “concept pointer” has be designed and developed. Via the formative evaluation from experts, instructors and students, its advantage and usage have been discussed.According to the formative evaluation, the “concept pointer” could help instructors to highlight the learning content and inspire learners’ understanding. As the results, the strategical learning tool “concept pointer” provided the positive effects to teaching and learning in the conceptual knowledge domain.

Some Web sites, such as google bookmark, evernote, or online calendar provides, are actually Web-based tools helping users complete their tasks and are regarded to as application-oriented Web sites. Today, the infrastructure support for building such Web sites is poor. What is the best approach to construct application-oriented Web sites? Perhaps some paradigms and generic guidelines will be helpful. In this paper, the researcher proposes preliminary results on some guidelines and infrastructure supports of application-oriented Web sites construction. The proposed solution is based on VWBE, which is the author’s previous research result. Several issues such as application interface definition and application state management are addressed in this paper.

The article aims to analyze the personality traits between the winners from the Golden Hands Award of National Skills Competition and the other students under the Industry-Related, Agriculture-Related, and Marine Fisheries-Related. This paper undergoes the Independent Samples

t

Test and One-Way ANOVA on the data by using SPSS. The experiment results showed that there are a number of variations in personality traits for different vocational categories. The forward personality of skills competition award winners are significantly higher than the student without participating in the skills competition training. Moreover, the profile data on gender under different vocational categories, family background, and birth order, were also observed with several personality traits showing significant differences. Hence, this study aims to find out the personality traits of the previous award winners and recommend suitable students to participate in the National Skills Competition.

More and more video streaming technologies supporting for E-learning systems are popular among distributed network environment. The Web’s Information Seeking System as the main provider of information is indisputable. How to provide multimedia Information seeking support E-learning system is becoming more and imperative. In this paper, we provided a multimedia information system for e-learning. This system requires adaptable and reusable support for the modeling of multimedia content models and also supports possible interactive, transfer of streams multimedia data such as audio, video, text and annotations using with network facilities. However, we investigated these existed standards and applications for multimedia documents models such as HTML, MHEG, SMIL, HyTime, RealPlay and MS Windows Media that let us to find that these standards and applications models do not provide adequate support for advanced reuse and adaptation. Consequently, we proposed a new approach for the modeling of reusable and adaptable multimedia content. We developed a comprehensive system for advanced multimedia content production: support for recording the presentation, retrieving the content, summarizing the presentation, weaving the presentation and customizing the representation. This approach significantly impacts and supports the multimedia presentation authoring processes in terms of methodology and commercial aspects.

The key successful factor of the new product design (NPD) of sensor manufacturing industry is the selections of the best parameter level. For above reasons, the selection of best parameter level sometimes causes more cost increasing and job reworking. Previous studies focus on try and error test and structured approach for the replacement and management of selection of the parameter level in product design, but rarely on a dynamic environment. Therefore, this work presents a novel algorithm, the Taguchi System-two steps optimal algorithm, which combines the Taguchi System (TS) with neural network (NN) method, which is shown how product adjusted under a dynamic environment in product design. From the results, the proposed method might possibly be useful for our problem by selecting of parameter level size and adjusting the parameters by NN in the DSPDS is observed in this study.

The article aims to find the pivotal personality traits which can influence on winning a prize, compare the difference between the winning participants and the non-winning participants, and finally construct decision trees to achieve classification and prediction by using the Big Five personality traits to analyze the performance of senior and vocational high school students in Taiwan in National Skills Competition. The research utilizes t-Test and C4.5 Decision Tree to analyze commerce-related and home economics-related students. The experiment results showed that it has statistical significances on several personalities in statistical analysis between commerce-related and home economics-related students. However, because the personalities which have statistical significances are the key factor to affect whether a participant can win a prize, I go one step further to construct decision trees to predict the winner of National Skills Competition effectively in the future.

This research is originally creative research, and already applied patent under authority of Patent Bureau of Taiwan (applying case number: 095121418). People living in modern society are full of much pressure from all kinds of environment everyday and with the great change of dining habit people easily have many chronic diseases. In addition to causing huge damage to individual health, it also cost much society medical resource. Most chronic diseases need special care from nursing staff to remind of when to have the correct medicine. It is naturally proceeding in wards but patients usually forget to punctually have medicine once they leave the hospital and get back home, and this situation neglecting or forgetting to have medicine according to doctors’ instruction often causes many un-fortunate deaths of patients resulting in offsetting-less for individual and family. Owing to the speedy development of communication technology and semiconductor, GSM communication module can be integrated and embedded into single chip and let GSM be carried into many products to increase the added-value of products. So how to combine microprocessor with communication module to construct a safe, intelligent, and full-purpose monitoring system for individual to have medicine to solve the problem mentioned above becomes an interesting issue for us. The research category of this study are including a medicine box as the main part of product which includes GSM module, speech-functional DSP, control panel displaying all information for patients, medicine detecting function, and a single chip microprocessor to operate the monitoring function. On the other hand, the interface of the commander terminal PC in nursing center, instructing all information for patients to punctually have medicine, is developed by us programing with VB language. The system function was verified completed successful and could be published for commercials for its creativity and practical purpose.

Location-based services (LBSs) via wireless data broadcast can provide a huge number of mobile clients for simultaneously accessing spatial data according to their current locations. A continuous window query is one of the important spatial queries for LBSs. It retrieves spatial objects in a fixed window region of every point on a line segment and indicates the valid segments of them. In this paper, we propose a skewed spatial index for continuous window queries considering skewed access patterns in the wireless broadcast environments.

Cloud computing has become one of the most important information technologies due to the development of Internet technologies. Accordingly, cloud computing has been applied to various fields, in which many researchers have also tried to apply cloud computing to education field. Despite much research on cloud to education, little effort has been devoted to applying them to a course in programming. Programming is a subtle and serious work, which requires a lot time to think, design, implement, testing and debugging. Hence, teachers often teach students to collaboratively engage in programming. Among the applications of cloud computing, collaborative service is the most potential applications for achieving collaborative learning, in which they can be used to assist students in collaboratively accomplishing a learning task. Accordingly, we explore how to use such services to assist students in learning programming. Three collaborative services are used in this study, in which Simplenote is used to support students in discussing; Google Docs is used to support students in designing; CodeRun is used to support students in programming.

Data mining in knowledge discovery helps people discover unknown patterns from the collected data. PIETM (Principle of Inclusion–Exclusion and Transaction Mapping) algorithmis a novel frequent item sets mining algorithm, which scans database twice. To cope with big transaction database in the cloud, this paper proposes a method that parallelizes PIETM by the MapReduce framework. The method has three modules. Module I counts the supports of frequent 1-item sets. Module II constructs transaction interval lists. Module III discovers all the frequent item sets iteratively.

This paper develops a cloud based parallel and distributed evolutionary hybrid algorithm with feedback assistance to help planners solve the data optimal problems such as travel salesman problems. Each step and type of evolution algorithm is established via various virtual machines in cloud. The proposed feedback assistance is based on the fitness evaluation result and survival ratio of evolution algorithm. The feedback assistance can interact with the evolution algorithm and emphasize the process with more survival individuals in the next generation of evolution algorithm. Taking the advantage of cloud and the proposed feedback assistance, system users can take less effort on deploying both computation power and storage space. The convergency of optimal solution can be enhanced.

To study and compare the simulation methods on the different scoring functions to analyze the consistency of the Docking score between the aptamers and protein. Thrombin is well characterized and has been studied with the thrombin binding aptamer (TBA) and mutated TBA sequences in a previous report, which finds three representative aptamers have best, medium, and worst binding interactions with thrombin. Discovery Studio 3.5 is a useful modeling and simulation software. The ZDOCK in this package incorporates a simple and novel scoring function: Pairwise Shape Complementarity. By using ZDOCK, we also can evaluate the differences in the binding ability between the interactions of the thrombin and aptamers. Basically, our results are consistent with the previous report. From this study, we make sure that the ZDOCK can provide reliable results and able be used as an alternative method in performing

in silico

selection of aptamer.

Web 2.0 describes a collection of web-based technologies which share a user-focused approach to design and functionality. Under the supporting of Web 2.0 technologies (e.g., HTML5), there are many applications, e.g., seamless reader over equipment, collaborative editing with multiple members, portable multimedia over devices, on browsers become feasible. In one of our previous works, we proposed a two-factor authentication with key agreement scheme for web-based collaborative systems. This paper further extends it to have secure group communication for web-based collaborative systems. With the proposed mechanism, members of the collaborative work could be share their messages easily and co-work securely. In order to provide high efficiency and data confidentiality, this paper presents an efficient group key agreement scheme for group members. The group members can join/leave the group easily.

In today’s fast-paced and competitive environment, mental stress has become a part and parcel of our daily life. However, mental stress can have serious effects on both our psychological and physical health. People under long-term stress can cause mental disorders, and cardiovascular disease. Moreover, people often ignore the symptoms of stress from their own bodies. Therefore, many chronic disease and mental illness are more and more serious gradually and damaging their body. The prior studies are interest in the diagnosis of metal stress. Some physiological parameters are used for the diagnosis of mental stress. However, these parameters pattern recognition is a difficult problem due to they have a time varying morphology subject to physiological conditions and the presence of noise. Therefore, how to capture and analyze personal physiological signals to assessment of mental stress under different conditions is a recurrent issue in many engineering and medicine fields. In addition, it is also important how to provide appropriate ways for stress relief under different the mental stress level. This study will evaluate different classification methods and understand which one is appropriate to detect the mental stress. Three data mining technologies are used to detect the mental stress level and have an experiment to evaluate the performance of the mental stress diagnosis. The heart rate, blood pressure, heart rate variability and autonomic nervous system are used to assess the level of mental stress. It might be helpful to assess mental condition in clinical practice.

Global climate change has given rise to disastrous heavy rainfall during typhoon seasons, wreaking havoc on our living environments. The electric power transmission lines in Taiwan are spread throughout the island, while some towers are located in high-altitude mountains, calling for good early warning and monitoring mechanisms in the face of natural disasters. This study integrates the QPESUMS radar echo system adopted by the Central Weather Bureau to develop an automatic real-time rainfall estimation and monitoring system, which takes advantage of intelligent agents to handle the massive volume of rainfall information for analysis. Rainfall estimation using adaptive algorithms monitoring the rainfall fluctuations at remote towers can provide maintenance crews with real-time information for timely repairs.

This paper aims to develop a generic and complete computation model toward scheduling, resource allocation, and action model of agents and to design the relevant simulated intelligent agent framework for agent applications. We propose a computation model and development tools to deal with dynamic data, translation of data models, qualitative information, time quantity, uncertainty, functionality, and semantic analysis. We also develop the relevant grammar and algebra system to locate resources and maintain constrains. The system allow user to define percepts and actions of agents. Script language with percept lists are integrated with scheduling and resource allocations. Several computation algorithms and operation tables which include a set of complete temporal logics are proposed. The combined temporal data models are generalized by composing point and interval algebra with qualitative and quantitative functions. The table look-up mechanism has the advantages for computation and realization.

This paper focuses on developing an intelligent energy-saving information interface agent system with Web service techniques in cloud environments. This system contains two main portions: an information processing and decision-making platform, and a cloud information interface. The proposed system architecture not only satisfies a lot of interface system designs, but also presents unique functions of interface agents, and then shows that the decision-making precision, system reliability and system validity yield excellent system qualities. In terms of user satisfaction according to Quesenbery and Nielsen, the proposed system can score as high as 73 %.

In this article we will study the end effector motion control for a series robot with 6 rotational joints to move on a predetermined 3-dimensional trajectory. Since for any end effector there are more than a single set of answers regarding to robot parts orientation, finding a method which gives designer all existing states will lead to more freedom of action. Two different methods were used to solve robot inverse kinematic. In the first method ADAMS software was considered, which one of the common software is in order to solve inverse kinematic problems. Then bee algorithm (BA) is used which is an intelligent method. This method is the one of the fastest and most efficient method among existing method for solving non-linear problems. Hence problem of inverse kinematic solution is transformed into an affair of optimization. Comparison of results from both models shows the reasonable performance of BA method in solution of robot inverse kinematic because of its capability in providing the answer from all existing states along with the privilege of no need to 3D modeling.

In the thermal imaging, human object detection is difficult when the temperatures of surrounding objects are similar to or higher than human’s. In this paper, we propose a novel algorithm suitable to those environments. The proposed method first compute a mean and variance of each pixel value from the initial several frames, assuming that there is no object in those frames. Then for each frame after the initial frames, the Mahalanobis distance is computed between the mean value and the current frame at each pixel, and the region of interest (ROI) is estimated. Finally, using the aspect ratio and edge orientation histogram, we determine if the ROI is human or not. The experimental results show that the proposed method is effective in both summer and autumn.

This paper studies the feedforward position control induced by the redundancy in a non-pulley-musculoskeletal system. Targeting a planar two-link musculoskeletal system with six muscles as a case study, the motion convergence depending on the muscular arrangement is examined. The results indicate that the motion convergence is extremely sensitive to the muscular arrangement and that adding small offsets for the points of muscle connection can remarkably improve the positioning performance.

Detection and localization of illegal electricity usage are important issue for power delivery companies of power system. In order to detect illegal electricity usage, network current-based methods using smart meter were mostly used in previous researches. Two main disadvantages of these methods are that they are unable to detect the exact location of illegal electricity usage. The latter is all users must be disconnected from the power system to detect the location. In this research, inspection robot can be used for detecting of illegal electricity usage. The inspection robot can define location of illegal electricity usage on the air transmission line without disconnection. In addition, this method can indicate fault location of transmission line. This paper presents a novel mobile sensing-based localization method for illegal electricity usage by using inspection robot, and it is verified through simulation results.

This paper aims to estimate age groups by walking data using pressure sensors array. Techniques of the age groups estimation in many retail businesses (for example, convenience stores, supermarkets, shopping malls, etc.) are marketable. There are many researches of the age estimation using face images, walking silhouette data, etc. However, there are some problems too. One of problem is that the estimation classes are a few. Moreover, many age estimation systems use some video cameras. Therefore, these systems may invade surveyed person’s privacy by taking one’s face images. In this study, this fact is one of merit in using the pressure sensors. The pressure sensors array gets feature quantity including center of gravity, pressure value, etc. In this study, our system classifies surveyed persons to 7 age groups as each decade. Here, surveyed persons are 20–80 s. Average estimation accuracy of all age groups is 72.86 %. The highest estimation accuracy is 86.67 % at 70 s.

Cells construct is made by spheroid-culturing the cells and collecting the spheroids. The spheroids are manufactured by dispensing cell turbid liquid into a special multiwell plate. If there is a difference in the number of cells when dispensing the cells turbid liquid, spheroids in different sizes are generated. Moreover, spheroids are not generated if the number of cells is extremely small, and if large, spheroids in distorted shapes are generated. Therefore, this study was aimed to develop a system that generates similar spheroids. In result, all the spheroids generated using developed system came in a pure spherical shape, and generation of spheroids is confirmed on all the wells.

This paper surveys and analyzes the relevant literature on robot control architectures. The design of an efficient collaborative multi-robot framework that ensures the autonomy and the individual requirements of the involved robots is a very challenging task. This requires designing an efficient platform for inter-robot communication. P2P is a good approach to achieve this goal. P2P aims at making the communication ubiquitous thereby crossing the communication boundary and has many attractive features to use it as a platform for collaborative multi-robot environments.

Authors have been developing the underwater robot that can be used for environmental protection work in the sea near Okinawa. It is difficult to get the position of underwater robot, because it cannot use GPS in sea. Authors have been developing the underwater robot to work in the sea near Okinawa with a high radree of transparency, so we try to develop the inexpensive measurement for underwater robot using a monocular camera. In this paper, we illustrate the measurement method and the basic experiment on land and underwater.

This paper proposes a method to detect emergency situations in a video stream using a Motion History Image (MHI) and AdaBoost for a video-based intelligent surveillance system. The proposed method creates a MHI of each human object through an image processing technique entailing background removal based on Gaussian Mixture Model (GMM) followed by labeling and accumulating the foreground images. The obtained MHI is then compared with the existing MHI templates to detect emergency situations. To evaluate the proposed emergency detection method, a set of experiments on a dataset of video clips captured from a surveillance camera were conducted. The results show that we successfully detected emergency situations using the proposed method.

We describe here a marker tracking algorithm for indirect positioning during planar fabric manipulation. Indirect positioning is a unique problem during manipulations of deformable objects. Improving the tracking of position by a robotic system contributes to the dexterous manipulation of deformable objects. To formulate this algorithm, we assessed the movement of a single robotic finger moving one manipulated point on a fabric to one positioned point or marker, to the desired point on a floor. To select an appropriate algorithm, we classified disturbances during the positioning of fabrics. To precisely detect the position of the marker during these disturbances, we applied the combination of a particle filter and a labeling processing to the algorithm. Experimental evidence showed that, due to its precision in detecting position, this algorithm was suitable for indirect positioning.

This paper presents a method of vision based human following for a mobile robot to trace a given human in an indoor environment. For a mobile robot to perform vision based human tracing reliably, we combined a silhouette based human detection and two-stage face detection technique. In this paper, the human detection uses a Histogram of Oriented Gradient (HOG). The face detection is composed of two stages, face detection using a Haar-like wavelet feature and AdaBoost and face detection using skin color with motion information and validation of contour shape. Finally, the performance of the proposed system is verified by conducting experiments where a mobile robot follows a human successfully in a real indoor environment.

Simultaneous localization is the most important research topic in mobile robotics. In this study, we propose a precise location estimation algorithm for a mobile robot based on a localization sensor and artificial landmarks in the ceiling in order to achieve point tracking. The proposed technique estimates the location of landmarks in the ceiling, generates the global ceiling and the global ceiling map for landmarks, and estimates the location of a mobile robot based on the ceiling map. The localization algorithm effectively removes incorrectly recognized landmarks using a histogram. In addition, the algorithm removes the measurement noise based on a Kalman filter. In order to evaluate the performance of the proposed precise localization technique, we performed several experiments using a mobile robot. The experimental results demonstrated the feasibility of the proposed localization algorithm.

This paper proposes a Motion Capture Based Dual Arm Control Method for a humanoid robot using a Microsoft depth camera called Kinect. A system that controls a humanoid robot by imitating a human’s motion can be applied to various areas of tele-robotic applications due to its intuitive operation and convenience. Therefore, we developed a remote dual arm control system to process data captured from a depth camera and to control the joint angles of motors of dual arms of a humanoid robot using a human gesture based non-contacting motion capture method. In experiments, we successfully demonstrated dual arm control of a robot using the proposed motion capture based method using Kinect.

This paper proposes a scalable building facade recognition and tracking system for outdoor augmented reality enabling real time augmentation of various information onto the facade. The system is composed of three modules: recognition and tracking module, server-client module and GPS module. In the recognition and tracking module, Generic Random Forest was used for real time recognition and three-dimensional pose estimation of facades. For scalable recognition, global region is divided into multiple local regions and then, same regional buildings are trained separately into a forest. In the server-client module, client maintains own travel map in order to choose proper forest by employing GPS sensor, and server transmits a new forest when client detects never visited regions. This makes our system scalable and also expansible to new regions.

We address the problem of head pose estimation from a facial RGB image as a multiclass classification problem. Head pose estimation continues to be a challenge for computer vision systems due to extraneous characteristics and factors that do not contain pose information and affect changing pixel values in a facial image. To achieve robustness against variations in identity, illumination condition, and facial expression, we propose an image abstraction method that can reduce unnecessary information and emphasize important information for facial pose classification. Experiments are conducted to verify that our head pose estimation algorithm is robust against variations in the input images.

This paper focuses on an ill-posed problem of recovering a human-like drawing order from static handwritten images with double-traced lines. The problem is analyzed and solved by employing a method based on the graph theoretic approach. Then, a main issue is to obtain the smoothest path of stroke from a graph model corresponding to input image. First, we develop an index on double-traced lines “D-line index” by employing the spline curves. Then, it is shown that the graph is transformed to a semi-Eulerian graph. The restoration problem reduces to maximum weight matching problem and is solved by a probabilistic tabu search. We examine the effectiveness and usefulness by some experimental studies.

This paper proposes an efficient noise reduction scheme for speech recognition in mobile devices. Due to the limited capacity of mobile devices, the speech recognition system requires a noise reduction module processed with low computational intensity. For noise reduction in mobile devices, the proposed approach directly utilizes packet data estimated by a speech coder. In particular, we apply pitch information for comb filtering, a well-known noise reduction method.

This paper presents a large-scale language model for daily-generated large-size text corpora using Hadoop in a cloud environment for improving the performance of a human–robot interaction system. Our large-scale trigram language model, consisting of 800 million trigram counts, was successfully implemented through a new approach using a representative cloud service (Amazon EC2), and a representative distributed processing framework (Hadoop). We performed trigram count extraction using Hadoop MapReduce to adapt our large-scale language model. Three hours are estimated on six servers to extract trigram counts for a large text corpus of 200 million word Twitter texts, which is the approximate number of daily-generated Twitter texts.

In this paper, we propose a new mothod using the PID controller gain value from rotatation of wheels according to rotation momentum characteristics for an educational mobile robot. P-Gain, I-gain and D-gain have been changed from the mobile robot via wireless remote control in a real-time basis. The transmitted gain value is calculated by real-time operation of embedded software in the robot. Experiments are carried out to find the optimized gain value of two conditions, maximum speed and minimum speed. The gain of intermediate velocity region is calculated from this gain value using primary curve fitting. The intermediate region gain value is calculated by real-time transmission of the mobile robot. Successful results are demonstrated with PID control using the calculated intermediate region gain value.

Many technical papers have been published related to music identification. However, most of these papers have focused on describing their algorithms and their overall performance. When music identification is applied to embedded devices, the performance is affected by the level of frame boundary desynchronization, environmental noise, and channel noise. This paper presents an empirical performance analysis of music identification, in terms of its Peak Point Hit Ratio (PPHR). In theory, music identification systems guarantee a 100 % accurate PPHR between the queried music and its reference. However, PPHR falls to 40.8 % by desynchronization when a frame boundary is desynchronized by half the frame shift. In addition, due to environmental noise, PPHR decreases to 69.6, 59.4, 46.1, and 24.3 % at SNR 15 dB, 10 dB, 5 dB, and 0 dB, respectively. For music clips recorded in an office environment, PPHR is 58.7 % due to environmental and channel noise.

In this paper, we propose a dynamic buoyancy adjusting device with an assist spring for underwater robot survey. The purpose of this device is to prevent underwater robots from agitating the water and sand during underwater survey and sampling. The proposed buoyancy adjusting device is actuated by an electric motor with a passive spring that provides some assistance to the motor. The assist spring supports actuator torque and allows low gear. As a result, the proposed device would achieve better energy efficiency and higher speed for dynamic control. To evaluate the performance of the proposed device, we designed and developed a dynamic buoyancy adjusting device as a prototype. Preliminary experiments indicate that the proposed device could be used for dynamic control of underwater robots.

Given a set of rectangular-shaped items such as dishes, cups, saucers, or forks and a rectangular tray of a cart, the three-dimensional single bin packing problem (3D-BPP) involves orthogonally packing a subset of the items within the tray. If the value of an item is given by its volume, the objective is to maximize the covered volume of the tray. Thus, this paper aims to optimize the transport capacity of a serving robot carrying a cart. This experiment, the first of its type, proves the feasibility of this endeavor efficiently.

In this study, for analysis speech signal the 10th order LPC synthesis filter is split into five 2nd order filters to avoid the nonlinear interactions of the poles. This novel algorithm allows us to reconstruct the wideband speech signal from the narrowband one by using the relationship between AR coefficients and its corresponding analog poles. The relationships between AR parameters and the continuous poles are presented.

Teleoperation of pneumatic robots is desired in the fields of rescue, surgery, and rehabilitation therapy. In the present study, teleoperation control of a four-DOF robot arm system incorporating pneumatic artificial rubber muscles is proposed. In the experiment of the present study, the distance between the master and the slave systems is approximately 8600 km. Signals and images from the master controller side are sent over the Internet using user datagram protocol (UDP). The effectiveness of the proposed system is discussed by the experimental results.

Maxillofacial palpation is a physical examination technique where face or jaw are touched with fingers to determine their shape, consistency and location. Dentists utilizes palpation to diagnose pathological condition of a patient suffered from maxillofacial diseases. This paper proposes a virtual training system for maxillofacial palpation. To provide a virtual palpation system, a basic patient model is constructed based on linear elastic finite element method. Finally the simulation results and the remained issues making the system more practical are discussed.

A 2-DOF wearable mechanism for support of human elbow and forearm is proposed in this paper. An advantage of the mechanism is easy attachment to a human arm: rigorous adjustment of attachment positions is unnecessary when the mechanism is attached. This paper firstly illustrates design and a model of the mechanism, and then derives kinematics. A supporting method applicable to the mechanism is secondly described. Thirdly, a mockup for future design of a prototype is shown. An issue for future development of the mechanism is finally discussed.

This paper addresses the issues of single microphone based noise estimation technique for speech recognition in noisy environments. Many researches have been performed on the environmental noise estimation; however, most of them require voice activity detection (VAD) for accurate estimation of noise characteristics. We propose an approach for efficient noise estimation without VAD, aiming at improving the conventional quantile-based noise estimation (QBNE). We fostered the QBNE by adjusting the quantile level according to the relative amount of added noise to the target speech. From the observation that the power spectral density (PSD) of noise is close to the Gaussian distribution, while that of speech is more narrowly populated, the level of additive noise is measured by the selected Gaussianity functions. We compared the proposed method with the conventional QBNE and minimum statistics based method on a simple speech recognition task in various SNR levels. The experimental results show that the proposed method is superior to the conventional methods.

In a mobile environment, there are limitations: limited power supply, smaller user interface, limited computing power, limited bandwidth and limited storage space; and above limitations must be considered for deploying a p2p overlay network. Locality and mobility are important factors as well as the limitations in a mobile environment. Based on the above assumption, we propose a mobile locality-based hierarchical p2p overlay network (MLH-Net) to address locality problems without any other services. In this paper, we introduce a novel profile called PCSN-List and node management scheme. MLH-Net is constructed as two layers, an upper layer formed with super-nodes and a lower layer formed with normal-nodes. Because super-nodes can share advertisements, we can guarantee physical locality utilization between a requestor and a target during any discovery process. To overcome a node failure, we propose a simple recovery mechanism. The simulation results demonstrate that the hop value of MLH-Net is 21 % decreased compared with JXTA when discovering nodes. And also, the average distance is decreased by 45 % as the number of max-hop is increased.

The depth map extraction from stereo video is a key technology of stereoscopic 3D video as well as view synthesis and 2D-3D video conversions. Sum of Absolute Differences (SAD) is a representative method to reconstruct disparity map. However, dense disparity map implementation requires heavy computations and extensive memory accesses. In this situation, the rapid advance of computer hardware and popularity of multimedia applications enable multi-core processors to become a dominant market trend in desk-top PCs as well as high end mobile devices; this movement allows many parallel programming technologies to be realized in users computing devices. Therefore, this paper proposes a parallel algorithm for SAD operation using a shared memory programming, OpenMP, which can provide the advantage to simplify managing and synchronization of program threads. The parallel implementation results show the 2.5 times of performance improvements on the processing speed compared with the serial implementation.

In this study, an object contour tracking method is proposed for an object with large motion and irregular shapes in video sequences. To track object contour accurately, an active contour model was used, and the initial snake point of the next frame is set by calculating an optical flow of feature points with changing curvature in the object contour tracked from the previous frame. Here, any misled optical flow due to irregular changes in shapes or fast motion was filtered by producing an edge map different from the previous frame, and as a solution to the energy shortage of objects with complex contour, snake points were added according to partial curvature for better performance. Findings from experiments with real video sequences showed that the contour of an object with large motion and irregular shapes was extracted precisely.