IT Convergence and Security 2012

Malware attacks that use document files like PDF and HWP have been rapidly increasing lately. Particularly, social engineering cases of infection by document based malware that has been transferred through Web/SNS posting or spam mail that pretends to represent political/cultural issues or a work colleague has greatly increased. The threat of document malware is expected to increase as most PC users routinely access document files and the rate of this type of malware being detected by commercial vaccine programs is not that high. Therefore, this paper proposes an automatic document malware analysis system that automatically performs the static/dynamic analysis of document files like PDF and HWP and provides the result. The static analysis of document based malware identifies the existence of the script and the shell code that is generating the malicious behavior and extracts it. It also detects obfuscated codes or the use of reportedly vulnerable functions. The dynamic analysis monitors the behavior of the kernel level and generates the log. The log is then compared with the malicious behavior rule to detect the suspicious malware. In the performance test that used the actual document malware sample, the system demonstrated an outstanding detection performance.

While the Web provides much convenience and many people all over the world use it almost every day, it is often misused as a medium for distributing malware without users’ knowledge. Special care is particularly needed with regard to Websites that are popular with users, since their infection with malware can greatly extend the scope of any damage. Damage caused by malware can be minimized by detecting malicious sites and taking the necessary countermeasures early on. As attack techniques have been evolving, including the abuse of unknown vulnerabilities and the application of detection evasion technology, the advancement of detection technology is urgently required. Leading methods of inspecting the malware concealed in websites include low interaction Web crawling detection, which is fast but dependent upon the signature, and high interaction behavior-based detection, which offers a wide detection range and enables the detection of unknown attacks, although it is somewhat slow. This paper proposes a technology that can visit and quickly inspect large websites to more accurately detect unknown attacks and detection-evading attacks.

This paper proposes a secure and efficient one-way hash function based on a linear group and nonlinear non-group cellular automata (CA). The proposed architecture is based on parallelism and logical bitwise operation on CA so that our function forms remarkably simple structure. We show that the proposed one-way hash function based on a CA satisfies the secure properties and produces an excellent quality of message digest in spite of a low construction cost.

Artificial immune system (AIS) is a computational system inspired by the principles and processes of the Biological immune system which has the capabilities to learn, adapt, self tolerance and memories actions, which make it a good example that we can take for solving some major problems in many fields, including the problem of malware detection in the field of computer security. The main idea is to detect any type of files that trying to harm the computer system by infecting some executable software when these files running, spread it to other files or computers. In this paper, we proposed a framework to detect malware using the innate immune system combined with danger theory to eliminate tow major drawbacks of current malware detection methods; detection accuracy and high false positive alarms.

As the Smart phone becomes gradually generalized and expands its influence on daily life, the digital evidential matter could be an important clue to prove criminal charge in the forensic process of criminal accident. Since the digital evidential matter could be easily spoiled, fabricated and disappeared, it needs to secure the criminal related evidence promptly as applicable according to clear procedures when investigate the initial scene of accident. Thus, this paper induces forensic procedures and items which a digital forensic investigator should take when it seizes, searches and verifies the Smart phone in the scene of accident considering characteristics of the Smart phone and establishes a criminal related search database and shows what kind of evidential matter for criminal charge could be collected through the applications implemented based on the said search database.

Many companies are using a large network, and this helps facilitate information exchange and business corporate. But the use of the intranet cause often the secrets leaked or waste of computer resources of corporate and then this cause the huge social losses. In order to protect the company’s high technology and information the companies should take appropriate information security measures for information security themselves. In this paper, we would like to emphasize the necessity of establishing the concept of Network Access Control (NAC) system. For this, we analyze the features of commercial systems, and we propose the enhanced NAC model with its own security features.

The increased application of sensor network introduces new security challenges. In this paper, we analyze the detection methods of compromised nodes and its countermeasure in the sensor network. We first review common attacks in the sensor network application which can compromise a valid, resource-constrained node (or called device). Then, we introduce several standard detection approaches to show their characteristics in different applications of the sensor network. Finally, we summarize and discuss existing countermeasures to the compromised nodes.

Click frauds are Internet crimes where clicks are deliberately performed to increase the publisher’s earnings or to deplete an advertising budget of the advertiser’s competitor. This paper presents an approach to automatically detecting click frauds by using a mathematical theory of evidence to estimate the likelihood of the frauds from click behaviors. Unlike most existing work, our approach provides online computation that incorporates incoming behaviors on real-time. It is theoretical-grounded, easily extensible and employs only data available at the advertiser’s site. The latter makes the approach feasible for the advertisers to guard themselves against the frauds. The paper describes the approach and evaluates its validity using real-world case scenarios.

Nowadays, as many information systems are connected to Internet and provide useful services to people through Internet, this openness makes the systems as targets of attackers. Even though conventional security solutions such as intrusion detection system (IDS) or firewall were designed to protect such attacks, it is impossible to block all the attacks. The researches on intrusion tolerant system (ITS) have been conducted in order to keep the proper services in the threatening environments. In this paper, we propose a novel Adaptive Recovery Scheme (ARS) which can be applied to intrusion tolerant architecture. ARS has proactive recovery scheme and reactive recovery scheme including self-recovery and emergency recovery. ARS selects appropriate recovery scheme according to internal and external factors to maintain required security and performance level. Additionally, ARS protects an integrity of critical files through snapshot technology. The performance of ARS is compared with existing recovery-based intrusion tolerant system by CSIM 20.

In this study a Linked Network Security system based on Virtualization (LNSV) is proposed to effectively perform data transmissions in a network separated environment under the aspects of management, operation, and cost. The LNSV proposed in this study represents an open architecture in accessing its system through network connectors for all users in individual networks and can be used as a general purposed system for storing all data to be transmitted. It is possible to prevent the access of unauthorized users because the stored data files include source IP/PORT, destination IP/PORT and Hash Values. Also, it can guarantee the security of communication through transmitting and receiving data using encryption/decryption functions. Thus, the LNSV can provide safe connection services between separated networks.

In this study, a security method that protects data from an information system accessed by unauthorized persons through physical ways like eye contacts is proposed. In addition, it is applied to security awareness programs for improving security recognition and to contribute to the protection of important information. The security awareness program proposed in this study is able to detect the violation in physical security policies and to implement additional training related to warning messages or such violated security policies and that leads to present positive effects of changing user security awareness and corresponding works. It is expected that these effects are to be spreaded to the whole organization and influence for all members.

Nowadays, security incidents of financial IT services and internet banking hacking against the financial companies have occurred continuously, resulting in a loss of the financial IT systems. Accordingly, this paper based on ‘framework standards of financial transaction detection and response’ was designed to propose of anomaly Electronic Financial Transaction (EFT) pattern recognition and response for the method to detect anomaly prior behaviors and transaction patterns of users. It was applied to moving average based on the statistical basis.

This study is designed to investigate the trend of information systems (IS) research in relation to supply chain management (SCM). The purpose of this research is to predicthow IS research is likely to evolve in the near future and to suggest to which direction it should be further conducted. We attempted to investigate the previous research topics about information systems in the fields of SCM on the basis of 96 journal articles published between the year of 2006 and 2010 including the database of ScienceDirect. The most frequently appeared keywords in the titles and abstracts were searched by two different categories: “business, management and account” and “decision science”. As a result we found that the most popular research topics appeared in the articles were “impacts of IS on the performance of SC and enterprise”“framework and model of IS in SCM”. We also suggested the future research implications of the current research trend or preference. This study academically and practically contributes to deepening our understanding of the on-going issues discussed on the current IS papers in the field of SCMby suggesting the future direction of studies.

This thesis aims to solve a problem that, even though the existing auction recommending system provides auction property based on the conditions and contexts users prefer, users cannot rely on the recommended property, but must analyze its investment value or request experts to analyze it. To solve this problem, advanced information in the real estate auction, an analysis of rights, an analysis of commercial quarters, and a development plan, are classified into 5 levels indicating investment value, which will be applied at the recommendation phase. This reliable recommending service is designed to be incorporated in the current context awareness system under a smart mobile environment. Therefore, we call it context awareness-based reliable auction recommending system (CARARS).

Recently, IT and mobile technology are developed rapidly. Mobile devices such as a smartphone and tablet PC have become widely popular, and many people store their private information into the devices. However, the portability and mobility of devices take risks such as being lost or stolen. These devices are the one of main cause to leak the sensitive and confidential information. To protect the information leakage from devices, the encryption algorithm is required. The existing encryption algorithms take long delay time and heavy battery consumption in mobile devices with restricted resources. Previously, the Self-Encryption (SE) which is a lightweight encryption algorithm for mobile devices was proposed, which had critical weaknesses. This paper proposes a novel SE scheme with a random permutation and bit-flipping process. Our proposed scheme derives the keystream from the plaintext itself, but the statistical correlations are effectively removed from the novel randomization process. It gives a solution to overcome weaknesses of the original SE scheme and the complexity to make adversaries it difficult to launch a brute force attack, and satisfies a 0/1 uniformity of key and cipher stream, which is an important property of the secure stream cipher. Moreover, it is faster and more energy-efficient than other ciphers such as AES and RC4. The evaluation is performed by the Android platform. The delay time and the battery consumption are measured and analyzed, which show that the proposed scheme is secure and best suited to the mobile platform.

The concept of network stability has been introduced to ensure the easy management of the actual complex networks. The network stability is a concept that allows the network administrator to easily provide the network management. There have been relevant advanced studies, which were meaningful in that they measured the network stability, but they did not address the subject deeply enough. In this study, a new network stability calculation method was proposed using the weight of the articulation node based on the existing studies. The method proposed in this study offers more precise information about the weakness of the network, and is expected to provide more accurate stability and weakness information than those from the existing method.

The concept of forward secrecy is extended to wireless sensor networks where it is frequent that nodes run out of energy and new nodes join the network. However it should not be able to retrieve the previous session key or some crucial information. In 2011 Hagras et al. proposed a key management scheme for heterogeneous wireless sensor networks, which satisfies confidentiality, authentication, integrity and unforgetability but lacks forward secrecy. In this paper, the shortcomings of the victim scheme has been extricated and repaired with the help of Elliptic Curve Discrete logarithm problem (ECDLP). An elliptic curve based signcryption key management scheme has been proposed which includes forward secrecy.

Signcryption enables a user to perform digital signature for providing authenticity and public key encryption for providing message confidentiality simultaneously in a single logical step with a cost lesser than sign-then- encrypt approach. As the concept of ring signcryption emerged, various practical applications like electronic transaction protocol and key management protocols, felt the requirement of signer’s privacy, which was lacking in normal signcryption schemes. Without revealing the users’ identity of the ring signcryption can provide confidentiality and authenticity both. In this paper, we present a new ID-based ring signcryption scheme, motivated to the scheme provided by Zhu et al. [

1

]. Selvi et al. [

2

] and Wang et al. [

3

] found some security flaws in the Zhu’s scheme [

1

], which is being considered and repaired in this paper. The proposed scheme is proven to be secure against adaptive chosen ciphertext ring attacks (IND-IDRSC-CCA2) and secure against an existential forgery for adaptive chosen message attacks (EF-IDRSC-ACMA).

In wireless ad hoc networks, the Direct Sequence Code Division Multiple Access (DS-CDMA) is the most promising candidate for wideband data access. The reasons are the high security, high throughput and soft limit on the number of active mobile devices. Soft limit on the network capacity means degradation of the performance by increasing the number of mobile devices. In many ad hoc networks, it is required to maintain the Bit Error Rate (BER) within some tolerable limits for a given SNR. This results in restriction on the number of mobile devices in the network. The number of active mobile devices or network capacity is further reduced by the mutual interference among the users caused due to multipath fading effects and synchronization problems. This paper presents an effective method of capacity enhancement of CDMA based wireless ad hoc networks by using a multiuser detection based power management framework. The system is simulated in the multipath channel models for fixed wireless applications. The proposed scheme increases the capacity two times as compared to the conventional CDMA based networks. Simulation results have been presented to demonstrate the effectiveness of the proposed scheme.

As sharing illegal digital contents using torrent increases, the need for technology which traces the first-seeder and the seeder changed from originally a leecher is magnified to eradicate that. But it is even more difficult tracing them as the proxy software such as Easy-Tor, etc. Based Tor using anonymity network technology becomes. This paper analyzes structure and communication process of BitTorrent protocol and Tor. And based on that, this suggests the methodology for tracing the first-seeder and the seeder changed from originally a leecher in packet level and countermeasures for blocking sharing illegal digital contents.

Surfing the web without anonymity in Syria has risked many activists and journalists’ lives. Furthermore, using the available anti-censorship techniques is challenging in such country due to Internet bandwidth limitations and the extensive filtering performed by Syria‘s licensed Internet service providers. In this paper, we highlight the Internet censorship in Syria. We propose a solution that provides suitable anti-censorship for Syrian activists based on TOR. We shift most of the heavy computational tasks from the client to our network nodes. The cryptography tasks are chosen lightweight to suit the bandwidth limitations. We show that our solution can provide safe web surfing in Syria.

RFID is a widely adopted in the field of identification technology these days. Radio Frequency Identification (RFID) has wide applications in many areas including manufacturing, healthcare, and transportation. Because limited resource RFID tags are used, various risks could threaten their abilities to provide essential services to users. Existing RFID protocols are able to resolve a number of security and privacy issues, but still unable to overcome other security & privacy related issues. In this paper, we analyzed the associated vulnerability and threat to the confidentiality, availability of the information assets for privacy, and mitigate the risks in RFID application. Considering this RFID security issues, we survey the security threats and open problems related to issues by means of information security and privacy. The security functions to be adopted in a system, strongly depend on the application.

Network technology is developing rapidly and attack technique using this is diverse and the damage is growing. Therefore, collection of attack information and its active coping in order to handle to diverse attack become necessary urgently. Honeypot to collect attack information of attacker must provide many of the same actual resources, but it is not easy. In this paper, multiple virtual machines which utilize resources efficiently using low cost are generated by means of dynamic allocation technology and dynamic honeypot system using this is proposed. Distributed IDS by protocols is used to detect accurate intrusion of collected information. Performance of the proposed system was confirmed by the experiments.

There is growing need for digital content distribution system in the IPTV market so that the content providers can make digital content available to users in a controlled manner. Digital right management technologies allow being able to restrict access to a content giving an access policy so content is available only to fair user. However, such a previous system has some problem in terms of management of user’s access information and computational cost for server. One of solutions to overcome the abovementioned problem is attribute-based encryption scheme providing access control to the encryption system. In this paper, we propose attribute based encryption scheme which is useful in contents distribution for IPTV, DVD and access control in encrypted file systems. Our attribute based encryption scheme allows for AND, OR, threshold and wildcard operations over attribute. Furthermore, our scheme achieves 0(1) pairings for decryption, regardless of any number of attributes.

Providing sensibility design using information convergence technology is an important factor in product service strategies. It is possible to ensure future competitiveness in bicycle industries by developing and specializing highly sensibility bicycle design. The necessity arises of creating a sensibility engineering approach to develop products that appeal to a wide variety of customers by stimulating their senses and creating emotional satisfaction. In this paper, we proposed a bicycle design recommendation using RFID tag-attached crayons. The proposed method obtains visual appeal using these RFID tag-attached crayons. Associative color patterns are analyzed using data mining, which extracts conceptual information from the collected data that is not easily exposed. The association can be determined as crayon colors are presented in a specific transaction, and different crayon colors are presented in the same transaction. The association rule represents a strong relationship between color sets. Designing frames, saddles, pedals, wheel sets, tires, cranks, and other parts of a bicycle based on visual sensibility represents a final shape by advancing through an application to a virtual model. By providing bicycle design adapted to one’s own design, it reduces cost and time and makes it possible to apply it to the desired styles.

Because of its convenience and environmental benefits, public transportation like railroad transportation is getting more attention. Railroad communication has its unique characteristics because of its unique network configuration. This paper proposes novel handover schemes for railroad communications. Railroad communication network configuration is explained in order to utilize favorable characteristics of railroad communications. In this paper, railroad handover zone is newly proposed for efficient handover and group handover is also proposed in order to reduce handover control overhead. With little modification, the proposed schemes can be applied to machine-to-machine vehicular communications where devices in a moving vehicle communicate with a server in the network.

There was a large scale of DDoS(Distributed Denial of Service) attacks mostly targeted at Korean government web sites and cooperations on March 4, 2010 (3.4 DDoS attack) after 7.7 DDoS on July 7, 2009 in South Korea. To detect and respond to them, malwares must first be detected by security monitoring system. In particular, availability of a method to detect and predict such malwares in advance will lead to preventing security incidents. This study will propose a method of prediction based on security monitoring event in Security Monitoring system and a functional configuration to realize the method and will assess the prediction model based on security monitoring events proposed through a test consisting of the stages of learning, prediction and evaluation.

Recently the convergence of IT Services is using much information. Fusion of vehicle information technology and IT services are developing very fast. In this paper is about car insurance service used vehicle information and user information. In this paper, the car insurance service is convergence that vehicle information and user information. We propose accident service, eco-driving service, breakdown service based on the information collected from the vehicle.

Recently various virtualization techniques have been applied to embedded systems. Among various hardware resources, memory is one of the most important components to virtualize an embedded system. In this paper, we modify an existing virtual machine monitor (VMM) in order to support MMU functionality. The proposed VMM can support many guest operating systems, which are based on flat memory model, at the same time. The measurement study shows that the proposed scheme does not degrade performance of VMM significantly, while restrict memory access of each guest OS in order to protect the rest of the system effectively.

The researches on the start stop system, which stops the engine on idle, have been briskly carried out around the automobile makers before the appearance of the alternative energy along with the growing needs for the low energy consumption technology and the strengthening vehicle environmental regulations. In addition, the automobile makers are trying to make the start stop system general and encourage purchasing by combining the system to the popular smart key system to not only provide the convenience but reduce the energy consumption as well. In this paper, we designed and implemented the start stop system with multi-protocol that is capable of providing both an eco-friendly start stop system and a convenient smart key system on a single electronic control unit. For performance evaluation, we gathered the necessary data with a software tool for monitoring the vehicle’s network, installed the proposed system on a real vehicle, measured the calculated worst case response time of the multi-protocol on the idle state control module, and compared the results with the benchmark data from the society of automotive engineers. The results show that the proposed system satisfies every time restriction that is related with the proposed system.

Dazzling development of the automotive industry as a new system for the driver’s convenience and security are being applied to the vehicle. In vehicle access and start-up that occurs most frequently before and after the operation of the vehicle, continually raised the needs of the customers for inconvenience related to user authentication as to compensate for the user’s convenience and improve the security of the vehicle, the smart-key system for the vehicle have emerged, Because many of the FOB key, anti-collision algorithm for a seamless multi-access is applied to the smart-key system. In this paper, we have designed and implemented improved anti-collision algorithm that dramatically reduces the communication response time required in the user authentication process immediately after by dynamically changing the order in which the request of the user ID as the user ID on immediately before in the smart key system for vehicles that use many of the FOB key. In order to evaluate the performance of the system the improved anti-collision algorithm is applied, we show the behavior of the algorithm implemented in the state actually mounted on the vehicle and verify that communication response time required for many of the FOB key was reduced by about 33 % compared to existing algorithms.

Characteristically, 3D graphic algorithms have to perform complex calculations on massive amount of stream data. The vertex and pixel shaders have enabled efficient execution of graphic algorithms by hardware, and these graphic processors may seem to have achieved the aim of “hardwarization of software shaders.” However, the hardware shaders have hitherto been evolving within the limits of Z-buffer based algorithms. We predict that the ultimate model for future graphic processors will be an algorithm-independent integrated shader which combines the functions of both vertex and pixel shaders. We design the register file model that supports 3-dimensional computer graphic on the programmable unified shader processor. We have verified the accurate calculated value using FPGA Virtex-4(xcvlx200) made by Xilinx for operating binary files made by the implementation progress based on synthesis results.

Model-based development is useful method in engineering. AUTOSAR is a kind of model-based development method for automotive E/E system which is developed by automotive industry. AUTOSAR provides several models for model-based system development, e.g. software component model, platform model and system model. Basic benefit of AUTOSAR is relocation of the software components regardless of hardware, however limitation for design exploration still exist. This paper describes constraints and requirements of software component mapping and proposes simple algorithm for design space exploration. Two kinds of constraints, software component mapping and data element mapping, are in AUTOSAR but this paper considers software component mapping only for simple algorithm. Fast design space exploration is basis of design decision and acts as input to next phase of development.

As quality of life is improving, a number of people pay attention to their health. Though the demand for medical services has been increased steadily, the number of doctors per capita increased only 2 % per year on average. In order to solve lack of caregiver, manufacturer of medical devices has tried to develop automatic medical systems. This system is called “Medical Cyber Physical Systems (MCPS)”. It is necessary to ensure interoperability between medical devices and closed loop system in order to automatic control. We consider IEEE 11073 to support interoperability between medical devices. We also introduce prototype platform that is based closed loop system in MCPS. This platform is our preliminary work to support interoperability between medical devices and compose a closed loop system which makes possible to control devices each other.

Recently, steel industry including the ubiquitous logistics cost savings with IT skills and enhance their competitiveness in terms of traceability and logistics management through efficient management and utilization of real-time information about the importance of awareness and with increased require of needs logistics management services based on ubiquitous IT environment, focusing on the core of the many services that can be said to belong to the service area. Thus, the introduction of ubiquitous technology in the field of logistics in the steel industry, with some merits at minor degree and although some advantage is very small level. In this paper, presents the feasibility of deploying RFID for the steel industry as a tool to reduce the production costs. Steel industry that is applicable to RFID-based tracking management system is proposed. The results of this paper proved that the recognition of 100 % came from the material input and output and the location, the location indicated 99 % detection rate. Therefore, the proposed RFID-based tracking management system was found superior to the existing system in terms of productivity.

Because of its convenience and environmental benefits, public transportation like railway is getting more attention. With the growth of data traffic generated by smartphones, laptop computers and multimedia devices, in railway, there has been increasing demand for data services such as passengers’ Internet access and surveillance video data transmission. In order to meet such increasing demand for data communications, International Electro-Technical Commission (IEC) has been standardizing new Ethernet-based Train Communication Network (TCN) standards. Since Ethernet is not able to guarantee fixed and sustained data rate for a certain service class due to the opportunistic nature of random access, communication schemes in the new Ethernet-based TCN standards are required to be carefully designed in order to support time-critical control applications such as propulsion and braking controls. In this paper, extensive study on the train propulsion control performance over Ethernet networks is provided. Since control system and network system need to be studied jointly in this study, co-simulation is implemented using TrueTime. Through extensive co-simulations, the train propulsion control performance on Ethernet is evaluated with the variety of interfering background data traffics.

Accident protection system at railway level crossing usually informs vehicle drivers and pedestrian that train is approaching, and eventually prevents them from passing the level crossing. This paper proposes a new level crossing safety system to solve the problem of existing system and to deal with the changing traffic condition at level crossing. The objective of the proposed system is to detect stopped vehicles at a level crossing with the state-of-the-art intelligent technology (sensor, computer, data processing, communication) and to transmit information to train allowing train drivers to stop their trains automatically and to display information of approaching train to vehicle drivers in real-time and to develop technology for accident prevention and damage reduction in connection with road traffic signal system. To evaluate the function and operation, we have demonstrated the proposed system at real railway level crossing of Young-dong line of Korail with Sea Train.

Eco cancellation algorithm should not only promptly adapt itself to changing environment but also minimize effects of a speech signal. However, since the color noise does not feature a consistent signal, it certainly has a significant influence on the speech signal. In this paper, the echo cancellation algorithm with a moving average LMS filter applied has been proposed. For the color noise cancellation method, an average estimator was measured by LMS adaptation filter techniques while a LMS filter step size was controlled. In addition, as it was designed to converge on a non-noise signal, the echo signal was cancelled which would, in return, lead it to the improvement of a performance. For the color noise environment, the echo cancellation Algorithm with the Average Estimator LMS filter used was applied and, a result to prove a convergence performance and stability to be improved by 10 dB comparing to the current method was gained.

There are many limits like as shadowing occlusion and no lights in the video image detector systems. In order to make accurate detector system, we need to get rid of these problems specially accident detection system by using vehicle trace. In this paper, we introduce a method of overcoming shadow. And we propose the accurate accident detection system. We find the flow of vehicle trace is like as level spacing distribution as Wigner distribution. It is in the level statistics when we represent this vehicle trace avoidable. From this distribution we can derive a probability induced by different of position for each lane. Using this equation we can find abrupt state of vehicle flow comparing with normal flow. We shall show statistical results from some experiments for this system evaluation

In this paper, Improved Digital Predistortion (DPD) Algorithm using an active filter and approximation Hessian technique is suggested. The algorithm optimized the performance of the DPD based on Quasi-Newton family method. In modeling power amplifier, the memory polynomial model which can model the memory effect of the power amplifier is used. And we compared with Least Mean-Squares (LMS) and Recursive Least squares (RLS) algorithm.

In this paper a high efficient dual path power amplifier (PA) for the code division multiple access (CDMA) handset applications is proposed. A dual path PA consists of two different size Pas combined parallel with single input/output matching circuits. The dual path PA is fabricated in the InGaP/GaAs heterojunction bipolar transistor (HBT) monolithic micro-wave integrated circuit (MMIC) in the CDMA cellular, 824–849 MHz and operates at a supply voltage of 3.4 V. The dual path PA exhibits an output power of 31 dBm, a 36 % power added efficiency (PAE) at an output power, and a −46 dBc adjacent channel power ratio (ACPR) at an 885 kHz offset frequency in the high power mode and an output power of 21 dBm, a 14.2 % PAE at a 16 dBm output level, and a −49 dBc ACPR at a 885 kHz offset frequency in the low power mode. This concept is also available for the other CDMA/OFDM specifications.

The Ubiquitous Health, or u-Health, service is an IT health care service using the ubiquitous computing environment. u-Health provides customized medical services. As it is a service that has developed from the current hospital visiting medical system, the u-Health service provides a patient with healthcare anywhere and anytime. In this paper, we propose a health management service model using home health gateway based on the u-Health platform. Using home health gateway, u-Health can provide health monitoring, diet, and exercise services using the Healthcare Decision Support Module (HDSM) in the ubiquitous environment. This approach would offer specialized services using an external content provider of DB. In addition, a doctor can provide advice to patients using the monitoring service. The proposed u-Health platform provides effective services using home health gateway in ubiquitous environments to customers, which will improve the health of chronic patients.

The human constitution can be classified into four possible constitutions according to an individual’s temperament and nature: Tae-Yang (太陽), So-Yang (少陽), Tae-Eum (太陰), and So-Eum (少陰). This classification is known as the Sasang constitution. In this study, we classified the four types of Sasang constitutions by measuring twelve sets of meridian energy signals with a Ryodoraku device (良導絡). We then developed a Sasang constitution classification method based on a fuzzy neural network (FNN) and a two-dimensional (2-D) visual model. We obtained meridian energy signals from 35 subjects for the So-Yang, Tae-Eum, and So-Eum constitutions. A FNN was used to obtain defuzzification values for the 2-D visual model, which was then applied to the classification of these three Sasang constitutions. Finally, we achieved a Sasang constitution recognition rate of 89.4 %.

This paper presents graph coloring algorithms and their applications to the channel assignment problems. Two application problems of frequency assignment of low power FM broadcasting and reader collision problem of RFID system are modeled as graph coloring problems. Instead of performing an exhaustive search for the optimal result, we provide both search space reduction and variable ordering heuristics to obtain good approximate solutions. Constraint optimization modeling and variable ordering enforce the backtracking process in graph coloring algorithms, so the search space is greatly reduced and the approximate solution is found quickly. A great deal of outstanding work on graph coloring algorithms is described and applied to the simulation results.

Korean Traditional house made of natural resources with low level thermal properties shows high performance in temperature and humidify control comportable for human. The present investigation is to examine the thermal behaviors of air flows inside the traditional house. The transient numerical experiments are performed along with the different external conditions. Thermal properties of building units have been obtained by the parallel measurements and utilized in the numerical works. Consequently, the details of flows and temperature of air in the houses illustrate the thermal design of the traditional Korean house satisfy the requirements of human living.

A designers try to design traditional wooden house, HANOK, are suffering from drawing roof frame, especially. Because that a roof frame appears in curved surface made of a number of architectural components with repetitious work. For the same reason, modification is difficult job, also. Constituent components become a part of curved roof shape and elegant line of eaves is one of the outstanding features in the Korean traditional wooden architecture. Roof shape has architectural functionalities such as passive solar system and preventing the walls from rain water etc. Moreover, the curved roof surface makes a gorgeous figure of the Korean traditional buildings in the visual viewpoint. This study suggests an efficient and systematic method to create many constituent components automatically for making curved roof surface in the Korean traditional architecture design. For verifying its validity, suggested method is implemented and applied into a commercial architectural CAD system.

Distributed Virtual Environment Systems are widely used in massively multiplayer online games. With an efficient distributed architecture and load balancing algorithm, they can support tens of thousands of players interacting with each other. An existing prevalent mechanism is to divide the virtual world into several regions and microcells and use the graph-based partitioning algorithm. But they generally limit the assignment beginning with border nodes and can’t adapt to the situation when players are crowded around the center of the entire map. Furthermore, many algorithms simply focus on reducing the intra-server communication cost in a connected graph. In this paper, we propose an adaptive load balancing algorithm to solve the problem of the center-crowdedness in the DVE systems, while reducing the intra-server communication and client migration cost simultaneously.

Currently, research is actively being conducted on applying games to education. However, existing game-based learning systems mainly focus on how to increase learning motivation and enhance engagement, while achieving less success on how to make further improvements on the effectiveness of learning. To improve on these points, this paper proposes a game-based learning system using graduated-interval recall method to organize game contents and learning courses with appropriate review intervals according to learners’ status. The proposed system has been verified through comparative learning effectiveness tests between two learning groups, in which one group engaged in learning with the proposed system and the other with an existing system.

The new memory technologies having the characteristic of non-volatile such as Phase-change RAM (PRAM), Ferroelectric RAM (FRAM), Magnetic RAM (MRAM) and Resistive RAM (RRAM) that can be replaced the DRAM as main memory have been emerged. Among these memories, PRAM is especially the most promising alternative for DRAM as main memory because of its high density and low power consumption. On the other hand, the slower latency by comparison with DRAM and endurance are caused to reduce performance. In order to exploit these degradations of performance, we propose a hybrid memory system consisting of PRAM and DRAM as a converter. The DRAM converter is comprised of an aggressive streaming buffer to assure better use of spatial locality and an adaptive filtering buffer for better use of temporal locality. Our architecture is designed to enhance the long latency as well as low endurance of PRAM. The proposed structure is implemented by a trace-driven simulator and experimented by using SPEC 2006 traces. Our experimental results indicate that it is able to achieve reducing access count by about 65 %, compared with only PRAM-based main memory system. According to this result, our proposed memory architecture can be used to substitute for the current DRAM main memory system.

The Intelligent Transportation System (ITS) can be considered the most representative example of Machine-to-Machine (M2M) applications in a standardization and commercial market. To support the applications, utilizing multiple network interfaces and providing appropriate network connectivity to them are the key issues in order to meet different network requirements of M2M applications on ITS devices. Moreover, different from applications which are controlled by a human operator, the ITS device with M2M application is required to decide the appropriate air interface and network for each application by itself according to the predefined policy and network status. In this paper, we therefore propose a novel multiple network interface management framework for ITS devices with M2M applications having their different requirements and constraints based on the CALM architecture. This can provide the M2M applications with extensible and flexible system environments based on the CALM architecture.

In present era of railways transportation the presence of the railway signal system in railway networks makes the train control system much easier & safer. Today the all railway signal systems are based on electrical devices. In this paper we propose a new signal system for railway network which will be based on wireless sensor devices. Proposed frame work helps the train control mechanism to control the train even in low visibility weather condition like dust, haze, snow, heavy rain, fogginess conditions. In this paper we proposed the idea and the framework for the new wireless sensor device based signal system which can be implemented in modification in existing current signal systems.

The range of ubiquitous computing technology available for use in healthcare continues to evolve, allowing for an increasing variety of wireless sensors, devices, and actuators to be deployed in changing environments. This paper presents a robust distributed architecture for adaptive and intelligent bio-interaction systems, called Evolutionary Bio-inspired Knowledge Accumulation. This system is designed to its capability to increase knowledge enhancement even in dynamic and uneven environments. Our proposed system adopts the concepts of biological context-awareness with evolutionary computations where the working environments are modeled and identified as bio-environmental contexts. We have used an unsupervised learning algorithm for bio-context modeling, and a supervised learning algorithm for context identification. A genetic algorithm, for its adaptive criteria, is used to explore action configuration for each identified bio context to implement our concept. This framework has been used to reduce noise in ECG signals that have been gathered in routine remote healthcare monitoring. Experimental results showed that the proposed algorithm effectively removes baseline wander noise and muscle noise, and feature extraction results showed a significant improvement of T duration extraction values.

The new trends of memory semi-conductor technology are changing and developing. Phase-Change RAM (PRAM), Ferroelectric RAM (FeRAM), Magnetic RAM (MRAM) and Resistive RAM (RRAM) are going to take center stage of main memory material of new computer systems in next decade. PRAM also has higher dense, it can keep data about four times more than DRAM. But some problems caused when PRAM uses as a main memory directly. So we suggest Pre-load cache and Assistant buffer. It reduces main memory access and overcome low read speed of PRAM consequently. To reduce write operation also, we propose Assistant buffer. Assistant buffer keeps evicted data and impedes write operation, and facilitates more rapid response about required data when cache misses. As a result of our experimentation, overall performance is decrement of main memory accesses approximately 50 %.

The location awareness technology is a core technology to be expanded to include objects from human-oriented informatization, and active support actions have been performed in developed countries such as the United States and Japan to implement the location awareness technology and Real Time Location System (RTLS) tag and antenna technology for real-time location tracking through a variety of projects for years. However, problems have been posed by Global Positioning System (GPS) based on the location awareness technology and active bat system using sound waves in terms of the space and construction costs. In this regard, this study attempted to suggest passive RFIF-based Indoor Positioning System (IPS) for tracking the location of the moving objects (humans and assets) in real time.

This paper proposes a user customizable UI mechanism (SmartKeyboard) for people with disabilities in smartwork environment. In which, a user can utilize customized input UI through network assistance (such as network server, cloud service) anywhere, anytime. Currently we have developed user customizable input UI as a keyboard form, but our research result can be evolved into various types such as ATM, kiosk, even TV remote controllers.

Load-balancing is of major significance for large-scale decentralized networks such as Peer-to-Peer (P2P networks in terms of enhanced scalability and performance. P2P networks are considered to be the most important development for content distribution and sharing infrastructures. Load balancing among peers in P2P networks is critical and a key challenge. This paper addresses the out-of-date problem as a result of node’s state changes during loads movement among nodes. Consequently, this work proposes a load balancing algorithm that is based on extensive stochastic analysis and virtual server concept in P2P System. Finally, this work is complemented with extensive simulations and experiments.

A contents authoring software with device management for interactive shows and performances is proposed. The proposed system allows user to register and to manage various stage-related devices such as lighting system, fog generator, robots or multimedia players. In this paper, we describe software architecture, XML specification for unified protocol description, and user interface of the proposed system. The system can control multiple devices of heterogeneous protocols in timely manner. Once devices are registered, user can browse commands of each device and can organize commands to step-based list according to the performance scenario. Unlike current commercialized products, the system allows to manipulate authored list of commands during the show instantly. The proposed system also supports to control playback of authored commands by sensor inputs so that a player can trigger devices to execute according to events. The contributions of this paper can be summarized to three points; (1) define unified protocol description with XML structures for simplicity (2) give sensor triggering capability to control devices, and (3) implement fast and instant manipulation user interface during the show.

In this paper, we implemented discriminating system for various surround illuminants using photo sensor. To discriminate surround illuminants of display device we implemented discriminating system using photo sensor which has output Ye and Cy. Experimental results shows that we could discriminate surround illuminants effectively by using the output voltage ratio (Ye/Cy) of photo sensor in the varying luminous intensity of surround illuminants.

The purpose of the study was to develop a computer access assessment system for improving computer access of individuals with physical disabilities for the first time in South Korea. Korea-Computer Access Assessment (K-CAAS) presented in this article tests three user skills in aim, drag, and menu. Skill levels of the three test areas could be set as primary, intermediate, proficient, and individualized according to individual’s needs and conditions. All tests have their default set in each level, and the skill levels can be selected and changed by the abilities and goals of a user. Tests could be selected for users’ training and, their results could be traced and shown. Therefore, the K-CAAS is a training program to improve computer access skills as well as an assessment program. It would help users with physical disabilities operate a computer by themselves as improving their computer access skills.

As the smartphone market grows, tracking a person’s own positions become easier and popular. Especially for the bicycling, file based GPS data make it easier to manage and access personal trajectories. In this paper, we propose an effective color coding method for massive bicycle trajectories visualization. The motivation of the method is based on characteristics of the bicycle trajectories which have different spatial aspects compare to the automobiles. The proposed method modifies the color of the line segments based on the direction and flow, and provides visually enhanced trajectories. GPS data collected from Han riverside bicycle tracks were applied to the proposed visualization methods, and shown the potential possibilities for trajectory analysis.

MMORPGs (Massively Multi-player Online Role-Playing Games) follows a client–server model that has the numerous gaming users with many interactions at the same virtual world, massive loading that result in delays, resource shortages, and other such problems occur. To solve this, many developers devote research to load-balancing servers, yet due to steady and dynamic map divisions, such research is unreliable. Many developers propose algorithms to distribute the load on the server nodes, but the load is usually defined as the number of players on each server, what is not an ideal results. So, we propose a gaming user-oriented load balancing scheme for the load balancing of MMORPG servers in this paper. This scheme shows effectiveness at dealing with hot-spots and other gatherings of gaming users at specific servers compared to previous methods.

File sharing is the practice of distributing or providing access to digitally stored information. The advantages of the existing file sharing repositories are limited by the factors of the cost and usage of multiple repositories for different purposes. This paper presents the development of an intelligent web-enabled facilitation system called Smart Desk which provides a single file sharing interface to the users, with the capability of virtually unlimited space. Smart Desk uses the services of other repositories by storing the data on other networks, and thus providing virtually unlimited space to the users for storing data. The drag & drop based single interface allows the users to easily view, edit, delete, upload, and copy data. A usability study has been performed to evaluate the efficacy of the system. The evaluation shows that Smart Desk is a useful interface for sharing files which is time effective and user friendly.

Speeded up Robust Features (SURF) is an interest point detector and descriptor which has been popularly used for object recognition. However, in real time object recognition applications, SURF framework can not be used because of its expensive nature. In this paper, a feature reduction process is proposed by using only the most repeatable features for matching. The feature reduction step results in a remarkable computational speed up with little loss of accuracy. A noise-reduction process allows a further increase in matching speed and also reduces the false positive rates. A modified definition of the second-neighbor in the nearest neighbor ratio matching strategy allows matching with increased reliability. The comparative analysis with SURF framework shows that the proposed framework can be useful in applications where the accuracy can be sacrificed to save computational cost.

Magnetic resonance imaging (MRI) is the most clinically used and gifted modality to identify brain abnormalities in individuals who might be at risk for brain cancer. To date, automated brain tumor segmentation from MRI modalities remains a sensitive, computationally expensive, and a demanding task. This paper presents an automated and robust segmentation method to enable investigators to make successful diagnosis and planning of radiosurgery by reducing the risk factor and study duration. The proposed system consists of following steps: (1) remove the non-brain part from MRI, (2) estimate saliency map of MRI, (3) use the salient region (tumor) as an identification marker and segment the salient object by finding the “optimal” closed contour around the tumor. The system has been tested on real patient images with excellent results. The qualitative and quantitative evaluations by comparing with ground truths and with other existing approaches demonstrate the effectiveness of the proposed method.

This paper presents a simple and cost effective approach for digital image magnification (DIM). DIM is used in various applications and is an enthusiastic area of research at present. The proposed technique uses Gaussian edge directed interpolation to determine the precise weights of the neighboring pixels. The standard deviation of the interpolation window determines the value of ‘σ’ for generating Gaussian kernels. Gaussian kernels preserve the original detail of the low-resolution image to produce high-resolution image of high visual quality. The experimental results show that the proposed technique is superior to other techniques qualitatively as well as quantitatively.

To examine drivers’ perceptions of and attitudes toward car navigation systems, the present study integrated perceived satisfaction and perceived locational accuracy into a modified technology acceptance model, and investigated hypothesized causal paths proposed by the research model with data collected from an online survey (N = 1,204). Results from the structural equation modeling indicated that perceived satisfaction and locational accuracy played crucial roles in determining perceived ease of use and perceived usefulness of the navigation systems. Implications and limitations are discussed.

Since the core functionality of cellular network mobility management is handover and handover latency directly impacts service continuity and the end-user experience, handover has the most stringent latency requirement on service interruption time compared to other mobility related operations such as reentry from Idle mode. This paper presents the state-of-the-art handover schemes designed for IEEE 802.16m based 4G mobile networks (next generation WiMAX), approved by ITU as an IMT-Advanced technology and handover performance of 4G mobile networks is evaluated in terms of latency. A system-architectural view on handover is provided to analyze the causes of handover latency and methods to optimize them for latency reduction. Through handover latency analysis an insight on how well 4G handover scheme is designed can be provided.

On a highway, it has high potential of ‘chain-reaction collision’ to occur, since vehicle has high velocity. As a preventive method for chain-reaction collision, native broadcasting and intelligent broadcasting that sends emergency messages to rear vehicles were proposed. However, these methods were ineffective when vehicles were concentrated in one area. This paper offers you a broadcasting method that considers stopping distance and improved back-off algorithm based on the number of neighbor nodes, which solves previous problems. As a result, the frame reception success rate comparing two different methods, broadcasting methods considering dangerous factors, was 7 % improved than native and intelligent broadcasting.

One of the most severe threats to revenue and quality of service in telecom providers is fraud. The advent of new technologies has provided fraudsters new techniques to commit fraud. SIM box fraud is one of such fraud that has emerged with the use of VOIP technologies. In this work, a total of nine features found to be useful in identifying SIM box fraud subscriber are derived from the attributes of the Customer Database Record (CDR). Artificial Neural Networks (ANN) has shown promising solutions in classification problems due to their generalization capabilities. Therefore, supervised learning method was applied using Multi layer perceptron (MLP) as a classifier. Dataset obtained from real mobile communication company was used for the experiments. ANN had shown classification accuracy of 98.71 %.

In this paper, we propose Overlapping-node Removal Algorithm that utilizes the backup node to the detection of the nodes in the WSN sensing coverage overlapping node. Overlapping sensing coverage of the node that has a data network, energy efficiency is very low. In the proposed algorithm, the initial network connection each node to know the location information of neighbor nodes within their communication coverage, because according to the radius of the sensing coverage overlapping node may be able to identify. Overlapping node that occurs during the network tasks is changed to the standby-node until a specific event occurs, replace the fault node can improve the network lifetime.

Personal healthcare devices are mode for elderly people and chronic illness that needs a health monitoring continuously. There are several standard specifications for personal healthcare devices to interact each other safely and compatibly. Depending on evolution of technology, the elderly and the chronic disease can have their own personal healthcare devices and they can monitor themselves easily. But some kind of limitation is still remaining in their life even if they have powerful smart devices. They need to drive and go to medical office and drug store but automotive system does not support standard for personal healthcare device. We discuss about several standards of the personal healthcare device and propose several implementations of personal healthcare services to support standard of personal healthcare devices on automotive system.

Wireless sensor networks (WSNs) differ from traditional networks in several ways: sensor nodes have severe energy constraints, redundant low-rate data, and many-to-many flows. This paper deals with a data-centric merging and by-passing routing schemes based on our own network model. This model permits to gather data at a tuple-centroid node for merging the same type of data. The data-centric merging mechanism is an efficient approach which reduces the number of hops per source and to by-pass the different types of data. It is competent to reduce the unnecessary processing cost of an intermediate node. Our network model shows offers significant performance gains across the high routing cost environment.

Caching scheme is important to improve data access performance and decrease bandwidth in MANET which consists of only MN. Many study like to solve cache consistency problem in this caching technique is achieved, but most of scheme is exposed to various security attacks. In particular, malicious node causes error from receiver through insertion and modification of stale data. In this paper, we proposed the technique which removes threat factor for cache consistency through authentication process using trust check about node. Cache table management scheme based cluster is applied to decrease overhead and manage efficient cache as MN discovers cache. We identified that proposed scheme in experiment result showed improved performance in average query latency and cache hit ratio.

Efforts to downsize antennas were mostly made in microstrip antenna with great success and progress in a wide variety of fields. Using dielectric substance is one way to downsize antennas but it hinders such antenna characteristics as antenna bandwidth and radiation efficiency. Because of such limitations, there is an ongoing research to modify antenna structure. Radiation pattern of small antennas becomes nearly non-directional and antenna gain becomes lower. Furthermore, bandwidth gets narrower because of weakened input resistance and extremely high reactance. Developing a small-sized antenna that is free of such shortcomings is not easy and the major job is to downsize antennas while matching impedance to protect its characteristic. In this paper, we proposed novel particle swarm optimization method based on IE3D is used to design a mobile communication Microstrip Patch Antenna. The aim of the thesis is to Design and fabricate an inset fed rectangular Microstrip Antenna and study the effect of antenna dimensions Length (L), Width (W) and substrate parameters relative Dielectric constant (εr), substrate thickness on Radiation parameters of Band width. When the antenna was designed, a dual-band, dual-polarized antenna was used to secure the bandwidth and improve performance, and a coaxial probe feeding method so that the phased array of antenna is easy.

The tag antenna has been particularly influential in the performance of RFID system. Many applications require tag antennas to be of low profile mounted on electrically metallic objects. Several designs have been developed for RFID patch-type antennas or planar inverted-F antennas (PIFAs) mountable on metallic objects. Although most of these reported antennas can give the required reading-range performance, they may suffer from inconvenient mounting on metallic object because of their high profile. However, it is inherent for a patch-type antenna that lowering the antenna profile would degrade its radiation efficiency and antenna gain. Hence, an effort is being made to further improve the antenna gain of the low-profile patch antenna needed to provide the applicable reading range in a RFID application. In this paper, we designed meander-type microstrip patch antenna which displays the best performance at the frequency of 910 MHz, the RFID standard available in metal environment. Square-shaped power feeder, connected to the body for coordination with common-use tag chip attached to the antenna, is located in the body, while the patch device is designed in the form of multiple meanders to efficiently scale back the size of body of antenna. Then the characteristics of bandwidth, efficiency, and recognition distance are compared and analyzed by the size of proposed antenna and the number of being folded. It was found that the efficiency and gain characteristics changes by the size of antenna and the number of being folded in the form of meander have a significant influence over recognition distance of antenna.

In this paper, we proposed research to boost reception performance in link-down transmission method of LTE system, which is the next-generation mobile communication technology standard underway in 3GPP. At the moment, in LTE downlink system, OFDM which is suitable for high speed data transmission and multipath has been used. However, OFDM method has a weakness displaying the relatively greater PAPR at the terminal because it basically uses multi-carrier. To this end, SC-FDMA has been used in LTE uplink system in order to compensate this big defect related to a great PAPR of OFDM in such an important terminal where power efficiency really matters. However, when signals are deteriorated by the channels in the frequency domain, SC-FDMA reveals a defect in that the impact of deteriorated parts is spreading and causes performance degradation. To this end, it proposed installing relay (RS) in between station(BS) and terminal(MS), set the distance between BS and RS at 500 and 1,000 m, each, and chose OFDMA and SC-FDMA as transmission method of RS. The paper found SC-FDMA to be better choice in RS when it is closer to BS and OFDMA to be a better choice in RS when the distance between BS and RS is farther. The system’s reception performance improved when the most appropriate transmission method fitting the circumstances was used in the middle between BS and MS.

In this paper, we proposed to install a relay between base station and terminal (or user equipment) in order to improve receiving performance of the downlink transfer mode of the Long Term Evolution (LTE) system, which is the next-generation mobile communication technology standard that has been proceeding in the 3rd General Partnership Project (3GPP). In 3GPP LTE-advanced, hybrid OFDMA/SC-FDMA is recommended for its technological capability to make up for the performance gap between OFDMA and SC-FDMA and to make PAPR more efficient. OFDMA is used in LTE downlink in order to make frequency more efficient and raise cell capacity but OFDM struggles with a high PAPR owing to its use of multi carrier wave. LTE uplink, on the other hand, employs SC-FDMA, which is similar to OFDMA, but makes up for OFDM’s big PAPR in mobile stations where electricity efficiency is critical. We conduct a paper to improve receiving performance having selected OFDMA and SC-FDMA, as the transfer mode of base station and relay based on the distance of the relay that has been installed and location of base station. The paper found SC-FDMA to be better choice in RS when it is closer to BS and OFDMA to be a better choice in RS when the distance between BS and RS is farther. The system’s reception performance improved when the most appropriate transmission method fitting the circumstances was used in the middle between BS and MS.

In this paper, an efficient traffic control scheme for real-time multimedia services is proposed with the use of the IEEE 802.11 WLAN for wireless access part in wireless networks, which is based on both the traffic estimation of the mean rate and header compression. The network model consists of the core RTP/IP network as well as the wireless access parts with lots of mobile hosts. This model is designed to include the means of provisioning Quality of Service (QoS) strategy according to the requirements of each particular traffic flow as well as the header compression method for real-time multimedia applications. Performance evaluation is carried out for showing the effectiveness of the proposed traffic control scheme.

In the high-speed railway communication networks, interference is quite complicated and serious interference can even ruin the security of trains. So how to evaluate the effect is becoming more and more important. Both grey clustering evaluations and analytic hierarchy process are an effective comprehensive evaluation theory. In this paper, we apply the theory of grey clustering evaluations and analytic hierarchy process to assess the interference of the circuit domain in GSM-R networks and make a comprehensive evaluation on interference. Based on the theory of grey clustering evaluations, the interference is sorted into rough groups. Then further classification of the interference can be obtained. The results show that grey clustering evaluations combined with analytic hierarchy process can provide the reliable interference evaluation in the railway services.

This paper presents a simple design and implementation of a transducer interface agent. The agent communicates with a middleware for wireless sensor networks, and can be installed on the PC or any small gateway devices. The agent’s chief end is to replace the network capable application processor (NCAP) and wireless transducer interface module (WTIM) with the agent itself in the IEEE 1451 family of standards. In order to support various non-standardized transducers, we propose to use a variety of configuration template files instead of modifying the agent itself. While a wrapper of the transducer interface agent manages various types of sensors, the controller deals with many actuators. In order to justify the usefulness of the proposed agent and its protocol, we carried out health monitoring experiments in a mock-up railway system and verified the efficiency.

Mobile cloud computing is growing rapidly because its device (i.e., smart phone) is becoming one of the main processing devices for users nowadays. Due to the limitation of resources such as battery life time, CPU and memory capacity, etc., a mobile device cannot satisfy some applications which usually demand more resources than it can afford. To alleviate this, the mobile device should collaborate with external resources to increase its capacity. In order to address these problems, we introduce a collaboration of thin-thick clients which enhances thin client capacities. We further propose a strategy to optimize the data distribution, especially big data in cloud computing. Moreover, we present an algorithm to allocate resources to meet service level agreement (SLA) and conduct simulations to evaluate our approach. Our results evaluation shows that our approach can improve resource allocation efficiency and has better performance than existing approaches.

The mutual exclusion (MX) paradigm can be used as a building block in many practical problems such as group communication, atomic commitment and replicated data management where the exclusive use of an object might be useful. The problem has been widely studied in the research community since one reason for this wide interest is that many distributed protocols need a mutual exclusion protocol. However, despite its usefulness, to our knowledge there is no work that has been devoted to this problem in a mobile computing environment. In this paper, we describe a solution to the mutual exclusion problem from mobile computing systems. This solution is based on the token-based mutual exclusion algorithm.

In a ubiquitous computing environment, one basic parameter is whether all the components in any specific environment are able to connect with each other and users can utilize them at anytime, anywhere. To address above issues, we introduce an efficient resource management scheme based on polymorphism. In this paper, resource objects are presented in the unified form to cooperate each other based on a common interface defined in it. The unified form of resource objects are called as Virtual Object (VO). With the VO, we propose a mechanism to provide services to users. The proposed mechanism is based on the profiles, which represents the situational information of any certain user. In this paper, services will be transformed based on the varying profile and it is called polymorphic services.

As mass storage media is recently becoming more common due to spread of smart phones in which new technologies have been applied, data collected from digital crime has been increased a lot. At the time, if the investigator did not conduct the initial response properly, we may lose the value as the evidence. Thus, the collection of digital evidence in a short time is required. Therefore, this paper proposes the methods to collect data rapidly at the scene of the crime based on table related to criminal charges. Implemented application can collect data with a consideration of each feature of software and provide the rapid results through a pattern search.

Recently Internet users can access data to share information in distributed environment by way of FTP, Telnet, Web browser etc. Consequently, the importance of these transfer programs is increasing. This paper proposes new remote transfer methods that can remotely upload or download the searched information into one more computers on the other side in Internet. This is a remote-to-remote transfer protocol (R

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TP) for transferring the shared data from a third located computer or to other third located computer in Internet. In addition, this work proposes as well a simple user interface method easy to use as the selective or adaptive scenarios to transfer effectively the large volume of data.

Garbage collection is one of major reason for performance degradation on Android OS. Escape analysis can be one of techniques to prevent performance degradation and Google has tried to implement scalar replacement through the escape analysis. But it does not become Android default functionality. This paper took it and compared with our proposed stack allocation method. The experimental result shows scalar replacement has no effect at all but stack allocation produce effective results. The CaffeinMark benchmark also shows no performance degradation in spite of additional instructions.

As IPTV services advance, an increasing user demand and tremendous content volume of multimedia content cause some difficulties in network resource management. In this paper, we propose an improved load balancing algorithm for VoD service. Unlike existing algorithms, the proposed algorithm considers users’ behaviors for VoD service, and determines the most efficient allocation of VoD requests by estimating expected server load and expected user waiting time. In order to evaluate our algorithm, we conduct a simulation of an IPTV network and verify the effectiveness of our system by comparing it with two baselines (Least Load and Nearest methods). As experimental results, the proposed system performs significantly better than the baselines. Consequently, the system can manage limited network resources efficiently and enhance QoE.

The centralized mobility management protocols such as mobile IPv6 (MIPv6) and proxy mobile IPv6 (PMIPv6) may result in significant amount of data and control traffic being pushed into the central mobility anchor of core network. Moreover, the use of such a central mobility anchor may be vulnerable to a single point of failure and degrade overall system performance. Therefore, in order to overcome the limitations of centralized IPv6 mobility management protocols, signal-driven PMIPv6 (S-PMIP) [

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] was proposed. However, it cannot solve the problems of the potential bottleneck at local mobility anchor (LMA) and long handover delay. Therefore, FS-PMIP, which is our previous work in [

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], was proposed to alleviate the problems of S-PMIP. By exploiting a user’s movement locality, FS-PMIP effectively reduces both the access to LMA and the handover latency. However, even if FS-PMIP is an efficient PMIPv6-based distributed mobility management scheme, it still requires the access to LMA whenever the correspondent node (CN) sends the data packets to the mobile node (MN). Therefore, in this paper, we propose an Enhanced FS-PMIP (EFS-PMIP) to enhance FS-PMIP by exploiting a user’s traffic locality as well as movement locality, which adopt both the pointer-forwarding concept and the working set concept in communications. The proposed EFS-PMIP is expected to have apparent potential to effectively reduce the access to LMA and distribute the binding and routing functionalities at mobile access gateways (MAGs).

This paper proposes a multihoming-based vertical handover scheme. Mobile nodes must have several radio interfaces to support vertical handover in heterogeneous wireless networks. In this paper, we consider each interface of a mobile node has its own protocol stack with physical, data link, and network layer. When a mobile node moves to a different type of access network, the proposed scheme can provide a mobile node with fast and seamless handover by performing layer-3 handover using its new interface while the other interface is still communicating in the old access network. This scheme uses a newly defined Proxy binding update to minimize handover delay and packet loss while a mobile node moves to a different type of access network. The proposed Proxy binding update is different from the Mobile IP binding update in that it includes home address (HoA) of the old interface instead of the new interface. The performance analysis shows that the proposed scheme can efficiently reduce vertical handover delay and packet loss.

The recent development on semiconductor process and design technologies enables multi-core processors to become a dominant market trend in mobile devices. The parallel programming enabled by multi-core CPU can provide a great opportunity to increase the processing performance. This paper explores a performance prediction model of parallel DCT on heterogeneous mobile systems by measuring power dissipation. For our simulation, we implemented the fast DCT algorithm on various computing environments and the simulation results show the feasibility of the proposed method to estimate the performance gain in terms of power consumption on heterogeneous embedded systems.

This paper introduces a system that can effectively save home energy by applying a small embedded system through remote control. We used a wireless router based on OpenWrt for the platform to develop an embedded system and a smart phone for the remote LED light control. The system was implemented by connecting a wireless router with an OS of OpenWrt installed and an interface board with an LED attached. The smart phone, which was the remote control device, was implemented by TCP/IP programming. The operation of the remote control system was verified by socket communication between the smart phone and the wireless router, and by USB communication between the wireless router and the interface board.

We are proposing the multimedia presentation authoring and virtual collaboration system that produces multimedia contents and enables multiple users who are dispersed in locally and timely to collaborate by the Internet. The proposed system consists of two parts—multimedia presentation authoring and recordable virtual collaboration tools. The authoring tool makes it possible to create and edit multimedia presentations that integrate diverse media types including images, video, sound, and texts for e-learning. Media objects are synchronized with the temporal and spatial information using SMIL defined by W3C. The collaboration tool categorizes users by the interested conference and any users can create new topics or join the existing topics by validating user’s access right freely in a conference they belong. Users can participate in more than one topic simultaneously, so they can inquire and get a valuable knowledge on-line in one topic and participate in the other topic more informed and intelligent. The produced multimedia presentation may be provided to the users through the conference before the discussion begins. Users can use text along with associated symbols such as arrows and polygons over the presented images during the discussion. Users’ opinions along with symbols are recorded to XML database.

This paper addresses a real-time immersive ski game that allows a game player not only to naturally interact with graphic environment but also to sense motion-haptic feedback according to his/her interaction. The proposed system measures a player’s motion and then re-creates motion-haptic feedback according to the measured input. To re-create the motion-haptic information in response to a player’s interaction with virtual objects, we develop a motion generation platform which consists of a control part, a slope generation part and a horizontal acceleration part. To measure a player’s motion input, inertia measurement units (IMUs) are used. We conduct an experiment in order to verify the effectiveness and the feasibility of the proposed game. The experiment clearly shows that the proposed system creates realistic sensation as if a user enjoys a real ski on the snow.

In this study, a hybrid scheme that combines Gaussian mixture model (GMM) and the k-means approach, called GMM-kmeans, is proposed for automatic audio segmentation (AAS) of popular music. Generally, the structure of a popular music is composed of verse, chorus and non-repetitive (such as intro, bridge and outro) segments. The combined GMM-kmeans scheme including mainly two developed algorithms, GMMAAS and SFS, will efficiently divide a song into these three parts. In GMM-kmeans, the GMM classifier is to recognize the vocal segments and then calculate the section boundary between them and non-repetitive sections first. The song with vocal segments extracted by GMM, containing only the remaining verse and chorus sections, is then analyzed by the k-means clustering algorithm where the verse section is further discriminated from the chorus section. In classification of verse and chorus by k-means, the developed switching frame search (SFS) algorithm with the devise of verse group-of-frames (Verse-GoF) and Chorus-GoF will accurately estimate the separation boundary of verse and chorus sections. Experimental results obtained from a musical data set of numerous Chinese popular songs show the superiority of both proposed GMMAAS and SFS.

This paper suggests an algorithm to classify human actions for the intelligent surveillance system. In order to classify actions, the proposed method calculates the difference image between input images and modeled background, uses motion information histogram and traces of center points of objects. Human actions are categorized into four types: they are the most frequently three actions people take walking, sitting, standing up and unusual action like as sudden falling down. We examine the proposed method on eight people with a sequence captured by using a web camera and the result shows that the proposed method classifies human actions well and recognitions of the unusual action.

The complexity of generic pin control blocks of multimedia system-on-a-chip (SoC) which implements input/output (I/O) paths for off-chip communication has been increased significantly. Accordingly, the possibility of making human errors in designing this block has been magnified as a new controversy. Generic pin control blocks posses several productivity issues since special register for an additional function and multi-I/O paths are usually fixed at relatively late stage of design activities. Also, generic pin control blocks may have different types of design according to the designer. This feature results in various human errors when we use the traditional RTL description. Thus, this paper presents an approach to reduce human errors based on design automation. In our case study, we succeeded on auto-generating a configurable pin control block in a multimedia SoC platform which has more than 300 generic pins including whether it is an input and output and 900 PAD pins. Ultimately, we reduced the amount of manual description for generating configurable pin control block by 97 %.

Recent research has indicated a significant association between depression and fatigue. To analyze depression and fatigue, an experiment was conducted that provided the subjects with affective content to induce a variety of emotions and heart rate variability (HRV). This paper presents a mental–physical model that describes the relationship between depression and fatigue by using a neuro-fuzzy network with a weighted fuzzy membership function using two time-domain and four frequency-domain features of HRV. HRV data were collected from 24 patients. At the end of the experiment, we determined the relationship between depression and fatigue with the mental–physical model, and our analysis results had an accuracy of 95.8 %.

As mobile devices have been rapidly spread up throughout the world, various services have been provided through mobile devices recently. Many services of them have been developed by using built-in sensors mounted on the mobile devices. Non-photorealistic rendering techniques have been also applied to mobile devices for the purpose of user friendliness or attractions. This paper proposes non-photorealistic rendering method using built-in orientation sensor of mobile devices. The method makes changes of non-photorealistic rendering effects in real time by adjustment of vector fields according as coordinate values from orientation sensor get changed on a mobile device. The proposed method renders pen sketch for a given photo image with direction and strength of line strokes which are applied by vector fields. The method executes rendering based on enhanced LIC filter to make pen sketch on a mobile device. Finally, this paper proves efficiency through the experimental results and shows usefulness of the proposed method.

With the drop in the price of Brain-Computer Interface (BCI) devices, which have been widely used in the medical sector, the development of serious BCI-based games has been accelerated. However, developers involved with the development of these games have found it difficult to acquire brain- and brain-wave-related knowledge. This paper defines templates that are necessary for developing BCI contents and proposes a method for developing BCI contents; the definition of the knowledge is based on templates. We present an example of a BCI-based game that has been developed using the proposed method. Since technical knowledge required for the development of serious games has been defined on the basis of templates, a developer can concentrate on the task of developing games.

This investigation proposes a non-photo realistic rendering to reflect enough to emphasize the delicate pen touch of Korea traditional building images. The earlier studies for pen-ink sketch technologies produce good results for the general images but they should not make successful results for the images of traditional architectures. It because that the image comprises a large proportion of repetitive patterns of exquisite lines and curves in its roof and latticed door. For featuring out the distinguishable characteristics of the traditional building images, the important thing is to decide the direction and length of strokes. We suggest a method to extract stroke’s information using Tensor Subspace Analysis (TSA) technique and to draw pen-ink strokes according to the information. Therefore, the proposed method generates pen-ink sketches reflecting the texture property for the traditional building images and emphasizing the characteristics of light and shade for each area.

This paper proposes a statistical ontology approach for adaptive object recognition in a situation-variant environment. In this paper, we introduce a new concept, statistical ontology, for context sensitivity, as we found that many developed systems work in a context-invariant environment. Due to the effects of illumination on a supreme obstinate designing context-sensitive recognition system, we have focused on designing such a context-variant system using statistical ontology. Ontology can be defined as an explicit specification of conceptualization of a domain typically captured in an abstract model of how people think about things in the domain. People produce ontologies to understand and explain underlying principles and environmental factors. In this research, we have proposed context ontology, context modeling, context adaptation, and context categorization to design ontology based on illumination criteria. After selecting the proper ontology domain, we benefit from selecting a set of actions that produces better performance on that domain. We have carried out extensive experiments on these concepts in the area of object recognition in a dynamic changing environment, and we have achieved enormous success, which will enable us to proceed on our basic concepts.

This paper is related to an adaptive skinny smudge tool deciding a radius of the master adaptively as well as using an arbitrary master shape. The smudge tool should seem familiar to finger paintings in kindergarten. We can use the smudge tool by selecting its icon on the toolbox of Adobe Photoshop CS6 and dragging in the direction you want to smudge while holding the mouse button down on the image. As the smudge tool blends all the pixels within a fixed radius of the master to generate the result image, its disadvantages are to smudge even the pixels in the undesired region, and to often vary the radius of the master manually. In this paper to reduce the disadvantages, an adaptive skinny smudge tool is proposed. The proposed adaptive skinny smudge tool not only uses the arbitrary master shape adhered closely to the contour shape, but also is able to decide adaptively the radius of the master according to the characteristics of the pixel distribution. Thus, the proposed skinny smudge tool has the advantage of automatically varying the radius of the master and applying the smudge effect to the desired region regardless of the background.

In this work, we propose a model of students’ examination data which can contain timestamp and handwriting information using a tablet computer. Stored data is consumed by students’ achievement recording software so that both teachers and students can trace their records at any time. The handwriting data in this work can be expressed as XML description so that other applications can use the data easily. The scope of this work is limited to store students’ examination information so that it is recommended to be combined with students’ profile or other valuable data. Inside the data, this work treats the examination information, question information, students’ response time of each question, and moreover, students’ behavioral factors including page navigation, removal and writing activities. With the students’ behavioral data, a visualization software can give user to suppose the student’s activity easily and vividly. In this work, we describes an example of visualization software which allows user to review recorded secondary students’ mathematics examination. Not only score-based assessment, our work may contribute to improve student’s assessment and feedback with various educational insights.

IPTV is a system where a digital television service is delivered by using Internet protocol over a network infrastructure, which may include delivery by a broadband connection. This paper proposes advanced FR-based measuring methods between original and processed media while transport streams are delivery from headend system. The proposed measuring scheme uses the brightness and edge of digitized contents blocks per each frame of MPEG-2 transport stream to evaluate contents in realtime. The proposed algorithm is effective video measuring as evidenced in the experimental matching results. The method in this paper performed in a high precision degree.

The media sharing technique in the signal for multimedia communication is one of the necessary research issues to provide the quality-guaranteed services over IP-based NGN (Next Generation Network). This paper proposes noisy signal reduction method with considering packet loss for multi-user connected multimedia communication. In order to reduce noisy signal without packet distortion efficiently for applying to All-IP based convergence environment, we provide a shared signal reduction and recovery scheme which use an optimized Wiener filtering technique based on input-SNR estimation with adaptive both-side information utilization according to the average magnitude variation across the frames. Also, this paper presents the policy-based service overlay IPTV framework for user experiences in the Open IPTV. We suggest the EPG ought to be selectable in the Open IPTV framework for requirements. The framework is proposed with the basis of the ITU-T IPTV NGN framework with IMS (IP Multimedia Subsystem).

In this paper, we propose realtime sport analysis method to extract target scenes in mobile environment considering heterogeneous devices. The proposed method extracts a specific context and displays the context of the target scene from the whole scenes with considering optimal viewer visual sight on devices. We use color-based classification with satisfying viewer visual perception in terms of the number of fast frames within the sport video streaming.

3D trajectory data have progressively become common since more devices which are possible to acquire motion data were produced. These technology advancements promote studies of motion analysis based on the 3D trajectory data. Even though similarity measurement of trajectories is one of the most important tasks in 3D motion analysis, existing methods are still limited. Recent researches focus on the full length 3D trajectory data set. However, it is not true that every point on the trajectory plays the same role and has the same meaning. In this situation, we developed a new cost effective method that uses the feature ‘

signature

’ which is a flexible descriptor computed only from the region of ‘

elbow points

’. Therefore, our proposed method runs faster than other methods which use the full length trajectory information. The similarity of trajectories is measured based on the signature using an alignment method such as dynamic time warping (DTW), continuous dynamic time warping (CDTW) or longest common subsequence (LCSS) method. In the experimental studies, we compared our method with two other methods using Australian sign word dataset to demonstrate the effectiveness of our algorithm.

Context-awareness has empowered advanced multimedia computing technology to provide user-oriented services and environment. This research aims at achieving a seamless video delivery service concentrating on the user’s mobility patterns during a multimedia streaming service session. Mobility supporting technology providing seamless services are categorized into host mobility and user mobility. The former corresponds to host-level handoff while the latter refers to user-level handoff. In host-level handoff, the influential parameters affecting the quality of video consumption are the total distance between the hosts, the distance for streaming to resume while user is in mobility mode and the screen size of the end host. The interdependency amongst the parameters is evaluated by a user subjective assessment and a befitting video quality model is developed, accordingly. Additionally, the optimal video delivery switching point to enable user mobility based video service is studied based on a quality analysis of host mobility services at varying distances among hosts. This quality model supporting a complete mobilization has a high correlation with the assessed quality and enables an adequate seamless mobility for multimedia service delivery.

The rapid increase of mobile internet and digital technologies has shown an increased interest in demand for stereoscopic 3D to provide 3D digital contents on mobile. Furthermore, the fast growing LCD technology has already allowed 3D viewings even in Smartphone. As a result, the issues related with stereo imaging have been spotlighted greatly. This paper presents a brief overview of rapid developments in stereoscopic technologies for mobile devices to gain some perspective on the changes and progress with special emphasis on mobile 3D TV services.

The general object recognition method is based on the various area segmentation algorithms. However, there might be difficulties with segmenting the adjacent objects when their boundaries are not clear. In order to solve this problem, we propose an efficient method of dividing adjacent circular-shape objects into single object through three steps: detection of the region of interest (ROI), determination of the candidate segmentation points, and creation of a segmentation boundary. The simulation shows robust results of 6.5 % average difference ratio compared to the existing methods, even when SNR was severe.

In order to minimize the query processing time, a data warehouse maintains materialized views of aggregate data derived from a fact table. However, due to the expensive computing and space costs materializing the whole relations instead of part of the relations results in much worse performance. Consequently, proper selection of appropriate views to be materialized is very important to get a precise and fast response in the data warehouse. However, this view selection problem is NP-hard problem, and there have been many research works on the selection of materialized views. In this paper we propose an improved algorithm to overcome problems of existing view selection algorithms. In the presented algorithm, we first construct the reduced tables in the data warehouse using clustering method among data mining techniques, and then we consider the combination of reduced tables as the materialized views instead of combination of the original base relations. For the justification of the suggested idea, we show the experimental results in which time as well as space costs are about 1.7 times better than the conventional approaches which considered all the tuples in a relation to materialize.

Many of recent computer applications generate data as a form of data streams, so a study on mining data streams can give valuable results being widely used in the applications. In this paper, a novel weighting technique for mining interesting sequential patterns over a sequence data stream is proposed. Assuming that a sequence with small time-intervals between its data elements is more valuable than others with large time-intervals, the novel interesting sequential pattern is defined and found by analyzing the time-intervals of data elements in a sequence as well as their orders.

Frequent pattern mining has been playing an important role for analyzing data in various fields such as medical treatment, biology, finance, networks, and so on. Since Apriori algorithm was proposed, frequent pattern mining has rapidly developed due to active research activities, and numerous mining algorithms have been proposed, such as FP-growth, FP-growth*, LCM, AFORT, and MAFIA. In this paper, we analyze and compare a variety of frequent pattern mining approaches, and discuss advantages and disadvantages of their algorithms. For the comparison, we evaluate mining performance for each algorithm using real datasets. In addition, we also experiment scalability for the algorithms to analyze their characteristics exactly. In the experimental results, we can know that LCM guarantees the fastest runtime performance, and FP-growth* and AFOPT show the most efficient memory usage. Using the characteristics analyzed from this paper, we can select and utilize the most appropriate algorithm with respect to numerous databases in the real world.

Graph mining means a series of processes for finding frequent sub-graphs in graph databases with complex structures. To obtain useful sub-graphs, isomorphic decision is needed since one graph data can contain lots of duplicated patterns. Therefore, we need to consider only patterns without duplications. However, these operations can cause enormous overheads due to knotty characteristics of graphs, which is called NP-hard problem. In addition, there also exists a problem that exponentially increases the number of unnecessary operations whenever any pattern size grows. In this paper, we propose a method that enhances efficiency of isomorphic decision in cyclic graphs based on a state-of-the-art algorithm, Gaston, which is called Egaston-CS (Efficient gaston for Cyclic-edge and Spanning-tree). In experiments, we compare our algorithm with previous algorithms, and thereby we demonstrate that Egaston-CS outperforms the others in terms of isomorphic decision.

Approximate frequent pattern mining is to find approximate patterns, not exact frequent patterns with tolerable variations for more efficiency. As the size of database increases, much faster mining techniques are needed to deal with huge databases. Moreover, it is more difficult to discover exact results of mining patterns due to inherent noise or data diversity. In these cases, by mining approximate frequent patterns, more efficient mining can be performed in terms of runtime, memory usage and scalability. In this paper, we benchmark efficient algorithms of mining approximate frequent patterns based on statistical and probabilistic methods. We study the characteristics of approximate mining algorithms, and perform performance evaluations of the state of the art approximate mining algorithms. Finally, we analyze the test results for more improvement.

Recently, due to the rapid increase in the elderly population, the interest in u-healthcare for personal and social needs is increasing. In addition, extensive medical information through various media services is one of the causes for the interest. However, the general public often doesn’t have the time to visit a medical authority for u-healthcare in many cases. The absence of a system that can be easily and quickly accessible anytime or anywhere to monitor health is a sad reality, especially in light of the rapid development of IT convergence technology. In this study, we proposed an interactive self-diagnostic system that monitors the human body for u-healthcare. First of all, this study separates the human body of an adult male and female into skin, muscles, and skeleton. And these three categories are then modeled using 3DS MAX. The 3D human body structures are able to be viewed with a 3D viewer of the system. One of the key features of this system is using the picking technique. If you select certain part of the human body in the 3D viewer, the system provides a variety of detailed medical information about the diseases associated with the selected part. The 3D viewer has the advantage of being able to view the structure of the human body realistically and intuitively. Medical information about diseases is comprised of simple and clearly organized data about the causes, symptoms, treatment, prevention, recommended food, and related medical institutions (such as hospitals) that can deal with the disease. If you use our system anytime or anywhere for u-healthcare, it can prevent diseases in advance and provide answers to many questions about disease-related symptoms.

The recommendation of u-Health personalized service in a semantic environment should be done only after evaluating individual physical health conditions and illnesses. The existing recommendation method of u-Health personalized service in a semantic environment had low user satisfaction because its recommendation was dependent on ontology for analyzing significance. Thus, this article suggests a personalized service recommendation method based on Naive Bayesian Classifier for u-Health service in a semantic environment. In accordance with the suggested method, the condition data are inferred by using ontology, and the transaction is saved. By applying a Naive Bayesian Classifier that uses preference information, the service is provided based on user preference information and transactions formed from ontology. The service based on the Naive Bayesian Classifier shows a higher accuracy and recall ratio of the contents recommendation than the existing method.

This paper introduces a decision support system architecture for continuous activity recognition and actigraphy, which are important for mental health evaluation; the architecture is based on triaxial accelerometer data. Recent developments in acceleration sensor device technologies have made it possible to precisely measure the acceleration of motor activity with a triaxial accelerometer for a lengthy period of time. We propose an AMD (Actigraphy based Mental health Decision support system) architecture for objectively measuring daily activity, recognizing continuous activities, and analyzing the behavior pattern of people with mental disorders, as well as the correlation between change in mood symptoms and mental disorders.

A large number of Internet users are currently using social networking services (SNS) such as Twitter and Facebook. However, the SNS users are exposed to threats of malicious messages and spams from unwanted sources. It would be useful to have an effective method for detecting spammers or content polluters on social networks. In this paper, we present an efficient method for detecting content polluters on Twitter. Our approach needs only a few feature values for each Twitter user and hence requires a lot less time in the overall mining process. We demonstrate that our approach performs better than the previous approach in terms of the classification accuracy and the mining time.

The

k

-Nearest Neighbor (KNN) algorithm is widely used as a simple and effective classification algorithm. While its main advantage is its simplicity, its main shortcoming is its computational complexity for large training sets. A Prototype Selection (PS) method is used to optimize the efficiency of the algorithm so that the disadvantages can be overcome. This paper presents a new PS algorithm, namely Fuzzy

k

-Important Nearest Neighbor (FKINN) algorithm. In this algorithm, an important nearest neighbor selection rule is introduced. When classifying a data set with the FKINN algorithm, the most repeated selection sample is defined as an important nearest neighbor. To verify the performance of the algorithm, five UCI benchmarking databases are considered. Experiments show that the algorithm effectively deletes redundant or irrelevant prototypes while maintaining the same level of classification accuracy as that of the KNN algorithm.

In this paper, we propose a method to reduce the learning time of Q-learning by combining the method of updating even to Q-values of unexecuted actions with the method of adding a terminal reward to unvisited Q-values. To verify the method, its performance was compared to that of conventional Q-learning. The proposed approach showed the same performance as conventional Q-learning, with only 27 % of the learning episodes required for conventional Q-learning. Accordingly, we verified that the proposed method reduced learning time by updating more Q-values in the early stage of learning and distributing a terminal reward to more Q-values.

The technical development of service robots has enhanced the variety of services provided by them to human beings. Service robots need to interact with human beings; hence, they require considerable learning time. The learning time can be reduced by adopting a learning approach in a virtual environment. To this end, it is necessary to describe a human being’s movements in the virtual environment. In this paper, we propose a method to generate an action model of a virtual character by calculating the probability of human movements using Bayesian probability. The virtual character selects actions based on the action model, and it executes these actions. Using the proposed method, the path of a virtual character was decreased by around 74 %, as compared to related methods based on Bayesian probability.

Heart disease has the highest rates of death in non-communicable disease and there have been much research on heart disease. Even though there is recognition for importance of heart disease prediction, related studies are insufficient. Therefore, to develop heart disease prediction model for Korean, we suggest data mining driven rule induction for heart disease prediction in this paper. Proposed method suggest heart disease prediction model by applying decision tree driven rule induction based on data set from Korean National Health and Nutrition Examinations Survey V-1 (KNHANES V-1). The prediction model is expected contribute to Korea’s heart disease prediction.

We present Clinical Decision Support System (CDSS) architecture to implement extensible and interoperable clinical decision support service in perspective of heart study using data mining. In our architecture, intelligence agent engine is critical component for implementing intelligent service using data mining. In this paper, we suggested Fuzzy logic driven Heart risk factor Prediction Model (FHPM) architecture in CDSS. In this CDSS architecture, components for intelligent service with missing value processing logic, Fuzzy linguistic and rule induction method are consisted. FHPM can create chronic heart disease guideline using Korean Data set. FHPM can provide clinical decision support services for the heart disease prediction for Korean.

In this study, we figured out what relationship the elements (weather, temperature, precipitation, wind speed, humidity) of meteorological changes have with the incidence of the five violent crimes through data mining. For the data used in this study, the number of meteorological occurrences from January 1, 2011 to March 30, 2012 through portal sites and the elements of meteorological changes of the day recorded in the Korea Meteorological Administration were used as materials. In this study, an analysis was made using the C4.5 algorithm of decision tree to verify what crimes occur according to the elements of the climate change. As a result of such an analysis, most of the crimes were high in the incidence in the following meteorological conditions: when the weather is cloudy; when the temperature is more than 9 °C; when the precipitation is less than 10 mm; when the wind speed is less than 4 m/s; and the humidity is more than 50 %. Given these meteorological conditions, cloudy weather showed the highest rate of crime incidence.

In the recent, due to explosion of Digital Universe, the performance of computer and storage system is reducing. Therefore, the upgrade and capacity expansion needs is growing. Countermeasure for this problem is required fundamental and long-term solutions rather than piecemeal expansion. In this paper, we establish a data management policy for an enterprise through the operational status of storage system and the analysis of data value of it, and implement ILM-based tiered storage system on the basis of these. The results of this study shows the overall throughput was improved about 21 % compared to the existing system, it is very effective to maintain continuous quality and reduce operating costs in the long term aspect.

The purpose of this paper is to assist in measuring all costs associated with product warranties including the environmental problems and in estimating the potential warranty cost savings. The concept of the green warranty is emphasized in this paper because of its effect on increasing the scope of warranty cost savings. This paper suggests a new concept for the design of warranty system that combines some of neural network approaches in green IT’s point of view. In particular, Gompertz function is used as the transfer functions in the model. The academic importance of this study is that Gompertz can be a type of mathematical model for green warranty claims, where warranty growth is slowest at the start and end of warranty lifetime period. To apply the model to warranty data, the practitioners need not identify parametric distributions for the failure attributes. To demonstrate the model, this paper develops a neural network mixture model for the automotive warranty data.

It is feasible to collect individual user interests from social networking services. However, there have been few studies of the interests of domain users. In this paper, we propose an approach for ontology generating the interests of SNS domain users by employing semantic web technology and ID3 algorithm.In our approach, domain ontology is generated by a decision tree, which classifies the domain web pages and the domain users. Experimental test shows ontology of the interests of domains users regarding USA presidential candidates. We expect that our results will be beneficial in the field of computer science, such as recommendations, as well as other fields including education, politics, and commerce. Proposed approach overcomes the problem of domain user classification and lack of semantics by composing decision tree and semantic web technology.

IIR (Internet Information Retrieval) system searches important documents on the internet by measuring the importance of these documents. For this purpose, various ranking techniques are proposed and adopted. In this paper, we propose ReviewRank, a ranking technique for finding book reviews. With an increasing number of people buying books online, reviews of books written by other people have become more important. General ranking techniques measure the importance of documents based on references or quotations between documents through hyperlinks. However, they are not suitable for book reviews. In this paper, we analyze characteristics of the importance of book reviews based on voluntary participation or evaluation of people called as collective intelligence, and proposes measures for considering the importance. We also suggest a ranking algorithm which adopts ReviewRank for finding book reviews. Experimental results show that ReviewRank outperforms previous ranking techniques for both general IIR system and searching book reviews.

In general,when users try to search information, they can have difficulties to express the information as exact queries. Therefore, users consume many times to find useful webpages. Previous techniques could not solve the problem effectively. In this paper, we propose an algorithm, RCW (Ranking technique for finding Correlated Webpages) for improving previous ranking techniques. Our method makes it possible to retrieve not only basic webpages but also correlated webpages. Therefore, RCW algorithm in this paper can help users easily look for meaningful information without using exact queries. To find correlated webpages, the algorithm applies a novel technique for computing correlations among webpages. In performance evaluation, we test precision, recall, and NDCG of our RCW compared with the other popular system. In this result, RCW guarantees that itfinds the number of correlated webpages greater than the other method, and shows high ratios in terms of precision, recall, and NDCG.

While developing software products, performance regressions are always big issues in enterprise software projects. To detect possible performance regressions earlier, many performance tests are executed during development phase for thousands or ten thousands of performance metrics. In the previous researches, we introduced an automated performance anomaly detection and management framework, and showed Statistical Process Control (SPC) charts can be successfully applied to anomaly detection. In this paper, we address the special performance trends in which the existing performance anomaly detection system hardly detects the performance change especially when a performance regression is introduced and recovered again. Generally the issue comes from that the fluctuation gets aggravated and the lower and upper control limits get relaxed with the fixed sampling window size while applying SPC charts. To resolve the issue, we propose to apply automatically tuned sampling size, and to build the optimized Fuzzy detection system. ANFIS is adopted as a Fuzzy inference system to determine the appropriate sampling window size. Using the randomly generated data sets, we tune fuzzy rules and fuzzy input/output membership functions of ANFIS by learning. Finally we show simulation results of the proposed anomaly detection system.

The increasing availability of usage data for e-journals and the global standard project for usage statistics report has lead increasing interest on collecting and utilizing usage statistic information. However, collecting and integrating large-scale usage reports generated and transferred in a various way by publishers hinders librarians to utilize the usage statistics. Thus we have implemented an automatic collection and visualization system of e-journal usage statistics in this work. By using the suggested system, librarians can focus on more specific and concrete usage data of their institution. In addition, visualized statistics information can be utilized in the composition of various reports on budget or operation of the libraries.

Software failure time have been proposed in the literature exhibit either constant, monotonic increasing or monotonic decreasing. For data analysis of software reliability model trend analysis was developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offers information of outline content. In this paper, we discuss failure time case of failure time censoring, and predict the future failure time using nonlinear regression models (growth, Logistic and weighted type) which error terms for each other are different. The proposed prediction method used the failure time for the prediction using nonlinear regression model. Model selection, using the coefficient of determination and the mean square error, were presented for effective comparison.

As there is an increasing reliance on information systems in most organizations, there is also an increased risk of security accidents of information systems. Therefore, in order to verify the potential security risks and their results, it is necessary to have a security threat assessment process called threat modeling. However, research in security threat modeling has yet to mature as there is paucity of established techniques and tools to aid the threat modeling and formal analysis process. This study provides a method to design and analyze threats that occur in the bio-information processing system using the visual Goal-oriented threat modeling. In addition, it determines each threat based on the Goal-Threat model and defends itself through measuring repetitive assessment, vulnerability the degree of risk. Then, by designing each organization to perform security checks on its own, it supports to make it possible to easily find vulnerabilities in terms of administration and presents a recommendation to be performed in order to ensure stability.

Retaining wall using steel frame and fill material is a kind of the cellular structure. The cellular structure using a fill material has a number of advantages such as excellent constructability in the short term, permeability, and decrease in effects of groundwater fluctuations after the end of construction. Because this structure is discontinuity, it is quite difficult to apply analysis in finite element methods. In addition, there are no evaluation techniques to establish its shear resistance clearly. In order to solve the issue, this paper presents that shear resistance analysis is performed by introducing displacement incremental analysis into the distinct element method. It enables not only to model continuous and discontinuous structure, but also to perform static and dynamic analysis. The results of analysis are compared with experimental results of the retaining wall with a steel frame and fill materials.

This study performs the test with full-scaled models for each diameter to evaluate the behavior of the reinforced concrete columns using the spiral wire rope as a lateral reinforcement of the circular columns. This study performs the quasi-static test which induced binding shear destruction to review circular concrete columns bound with high strength wire rope. Three specimens of concrete columns with 700 and 800 mm diameter each were manufactured to evaluate the movement of reinforced circular columns with the wire rope. A hoop reinforced column and 2 spiral reinforced columns were manufactured to compare the bending history and the ductility reinforced with the wire rope to existing reinforced concrete columns. The peak strain of the longitudinal reinforcements is occurred at approximately 0.75 D from the bottom of the column. The spirally confined concrete columns with high-strength wire ropes showed that improve 2.5 % of the shear strength.

This article presents a new type of stress assessment method for double-layered pressure vessel. Due to its robust strength, a steel–concrete composite pipe is generally installed in poor burial conditions. However, it is difficult to directly define the stress state on pipe sections. For the convenient stress estimation of pipes encased in non-circular concrete, this article suggests a Stress Index (SI), a function of the interface pressure and changed diameter, based on the interface pressure. The ovalization characteristics of plain pipes and of pipes encased by circular and rectangular concrete are examined. The resultant stresses are replaced by the non-dimensional ratio of diameter change; thus, the stress index has the advantage of application for stress assessment irrespective of pipe characteristics.

It has become general common sense through numerous researches that exercise provides positive impacts on physical and mental health. And it has been reported that regular exercise adjusts obesity by reducing body fat and lipid levels found in the blood and ultimately, it improves human quality of life. In this study, indices for managing swimming exercise therapy were induced through prior researches and weighted value was measured by modelling correlations between indices by using fuzzy Analytic Network Process (ANP) technique. And patient management system was intended to be realized so that tailor-made management per patient can be established on real-time through mobile equipments such as portable phone, smart phone, notebook and etc.

This study proposed a method of developing an intelligent recommendation system for automotive parts assembly. The proposed system will display the detailed information and the list components which make up the relevant part that an user wants through the database using the ontology when selecting an automotive part that an user intends to learn or to be guided of. The intelligent recommendation system for parts is offered to users through determining the automatic recommendation order between parts using the weights. This study has experimented the principles of the recommendation system and the method of setting the weights by setting two scenarios.

Regarding the software development, MDA (Model Driven Architecture) of OMG can be regarded as the concept of making an independently-designed model according to the development environment and language and reusing it according to the desired development environment and language by expanding the reusable unit into the software model when developing software. The problem with these traditional research methods, but the first model, design model for checking the information with the model by defining a formal representation in the form of an abstract syntax tree, as you have shown how to perform validation of UML design model. Additional steps need to define more complex due to a software problem that is not the way to the model suitable for model transformation verification. In this paper, as defined in the verification based meta model for input and target model. And we also suggest how to perform model transformation verification using property matching based transformation similarity and mapping patterns.

This paper proposed a hierarchical architecture of steel house materials. The proposed architecture will include the detailed information of the components. For this, we made description about steel house design method and material change task ontology. Especially AFM is composited with total four steps. Using the method, the solution process of possible problems occurred in a steel house can be converted to an otology. Also we made category about composite patterns of steel house materials.

In this paper, we explained multi-faces recognition process. To construct a security framework of a CCTV-based face detection and recognition system, we suggested modeling method applied as 4 steps. For CCTV image recognition, we explained image recognition system composition, image recognition core module and face recognition system process. Especially, Face Recognition System is a system that extracts face from input images, and recognizes who is whom through similarity assessment process and characteristic data registered by extracting characteristic data for recognition in extracted face.

In this paper, we propose a method on software performance test automation by using the virtualization. In general, most test engineers use the public performance testwares such as Load Runner and Silk Performer to validate the performance efficiency of their own systems. In case that they cannot use the performance testwares due to some technical limitations in the testwares, the testers should perform the testing in manually. As waste of computer and human resources is resulted from the situation, we need to propose the test automation scheme by using the virtualization technology to prevent the dissipation in the test environment which has limited resources. The system architecture considered efficient usage of computer resources and test automation to reduce human acts are addressed mainly in this paper. Finally, a number of experiments show that the proposed schemes allow offering the possibility for automated software performance testing by using the virtualization.

Recently the software system is becoming little by little complexity termination. Aspect-oriented Programming is support a crosscutting concern. Crosscutting concerns are responsible for producing scattered and tangled representations those are difficult to maintain and evolve. Aspect-Oriented Software Development aims at providing means to identify, modularize, specify and compose crosscutting concerns. Requirements engineering techniques that explicitly recognize the importance of clearly identifying and treating crosscutting concerns are called Aspect-oriented Requirements Engineering Approaches. Aspect-oriented requirements engineering approaches improve existing requirements engineering approaches through an explicit representation and modularization of concerns that were otherwise spread throughout other requirements. Aspect-oriented requirements engineering approaches adopt the principle of separation of concerns at the analysis phase. This approach provides a representation of crosscutting concerns in requirements artifacts.

In software engineering, Unified Modeling Language (UML) is considered as the de-facto standard for modeling Object Oriented Systems. On the other hand when it comes to system engineering, then UML is believed to be not as good. More precisely, UML is not effective when modeling system’s (Non-functional) requirements, linking these non-functional requirements with other artifacts of the system and defining constraints on the system, in an effective manner to define the system architecture. OMG (Object Management Group) released SysML (a UML-profile) to overcome such limitations of UML, when applied to system engineering. This paper is an effort to show how system’s structure, its constraints and (non-functional) requirements can be effectively modeled and linked with each other in SysML with help of a case study.

In the design of 4G cellular mobile networks, also known as, IMT-Advanced systems, new air interface enhancements such as multi-carrier support and interference mitigation further require handover protocol to be scalable and flexible to support various 4G deployments. This paper presents the state-of-the-art handover schemes designed for IEEE 802.16m based 4G mobile networks (next generation WiMAX), approved by ITU as an IMT-Advanced technology and provides discussion on technical challenges of railroad communications for high speed trains. Based on the discussion, handover latency reduction scheme for railroad communications is proposed. Various advanced handover procedures accepted in IEEE 802.16m specification are explained in details in order to derive technical challenges and handover reduction scheme of railroad communications.

A REDOX flow battery as a large energy storage technology was reviewed in the paper. REDOX flow battery is a promising technology for the large scale of energy storage and can be expected as a new technology for energy storage device which can replace former secondary batteries. The recent research data and results concerning the REDOX flow battery technologies were summarized in the paper. Among many kinds of REDOX flow batteries the vanadium REDOX flow battery was mainly reviewed in this paper. The REDOX flow battery can be combined with the renewable energy systems, such as solar cell and wind power.

An interfacing adapter is required between cache layer and PRAM based main memory to cover the shortcomings of PRAM. Thus this research is to design a flexible DRAM buffer (FDB) structure, which can improves performance by prefetch candidate data into FDB to reduce the miss penalty, and extends PRAM lifetime by filtering a large portion of write back data upon eviction from last level cache. Our results show that FDB can effectively minimize the access latency to achieve similar performance to the case of DRAM main memory and reduce a certain degree of write count to PRAM, thus limited endurance can get some respite thereby, typically extend their life expectancy.