Recently, as mobile multimedia devices are used more and more, the needs for high-performance and low-energy multimedia processors are increasing. Application-specific integrated circuits (ASIC) can meet the needed high performance for mobile multimedia, but they provide limited, if any, generality needed for various application requirements. DSP based systems can used for various types of applications due to their generality, but they require higher cost and energy consumption as well as less performance than ASICs. To solve this problem, this paper proposes a single instruction multiple data (SIMD) based many-core processor which supports high-performance and low-power image data processing while keeping generality. The proposed SIMD based many-core processor composed of 16 processing elements (PEs) exploits large data parallelism inherent in image data processing. Experimental results indicate that the proposed SIMD-based many-core processor higher performance (22 times better), energy efficiency (7 times better), and area efficiency (3 times better) than conversional commercial high-performance processors.
This study developed a digital security device which power is on/off by the RFID card. This device is based on the wireless data transmit/receive circuits, built in RS-232C chip and applied to computer and other digital devices. We can check whether this device is operated or not by connecting the LED. In this system, 13.56MHz frequency circuit supplies power with ID card, and DC inputs check the proximity operating distance of the card field for verifying the existence of a card. The security level of this system is much stronger than that of a compared system. Anyone cannot use the system without RFID card. All illegal access is prevented except for authorized path.
As people have heightened attention to blogs that are individual media, a variety rank algorithms was proposed for the blog search. These algorithms was modified for structural features of blogs that differ from typical web sites, and measured blogs' reputations or popularities based on the interaction results like links, comments or trackbacks and reflected in the search system. But actual blog search systems use not only blog-ranks but also search words, a time factor and so on. Nevertheless, those might not produce desirable results. In this paper, we suggest a topic-rank technique, which can find blogs that have significant degrees of association with topics. This technique is a method which ranks the relations between blogs and indexed words of blog posts as well as the topics representing blog posts. The blog rankings of correlations with search words are can be effectively computed in the blog retrieval by the proposed technique. After comparing precisions and coverage ratios of our blog retrieval system which applis our proposed topic-rank technique, we know that the performance of the blog retrieval system using topic-rank technique is more effective than others.
A RAM-based Neural Net is a weightless neural network based on binary neural network. 3-D neural network using this paper is binary neural network with multiful information bits and store counts of training. Recognition method by MRD technique is based on the supervised learning. Therefore neural network by itself can not distinguish between the categories and well-separated categories of training data can achieve only through the performance. In this paper, unsupervised learning algorithm is proposed which is trained existing 3-D neural network without distinction of data, to distinguish between categories depending on the only input training patterns. The training data for proposed unsupervised learning provided by the NIST handwritten digits of MNIST which is consist of 0 to 9 multi-pattern, a randomly materials are used as training patterns. Through experiments, neural network is to determine the number of discriminator which each have an idea of the handwritten digits that can be interpreted.
Clustering is one of the well-known unsupervised learning methods, in which a data set is grouped into some number of homogeneous clusters. There are numerous clustering algorithms available and they have been used in various applications. Fuzzy c-means (FCM), the most well-known partitional clustering algorithm, was established in 1970's and still in use. However, there are some unsolved problems in FCM and variants of FCM are still under development. In this paper, the problems in FCM are first explained and the available solutions are investigated, which is aimed to give researchers some possible ways of future research. Most of the FCM variants try to solve the problems using domain knowledge specific to a given problem. However, in this paper, we try to give general solutions without using any domain knowledge. Although there are more things left than discovered, this paper may be a good starting point for researchers newly entered into a clustering area.
This paper collect sleep environment data of bedroom to sleeping, and analyzing the relationship between conditions with obtained data and sleep. We provide the optimal sleep environment of individual by extracting the simulation model based on it. The experiments was using temperature/humidity sensor(SHT11) and ambient light sensors(GL5507). For extraction of tossing and turning, we use difference image method in motion extraction from video. In addition, the information of weight can affect to sleep, it was entered such as ratio of fatigue, drinking, empty stomach. As a result, we are able to extract the optimal sleep environment. The future, we will try to improve to help to lead more pleasant daily life providing proper indoor environment changes depending on the situation even a partial of organic ubiquitous living environments such as eating, work ete. as well as certain sleep circumstances.
In many face recognition applications such as security systems, it is assumed that upright faces are given to the system. In order for the system to be used in more general environments, the system should be able to deal with the rotated faces properly. It is a generally used approach to rotate the face detection window and apply face detector repeatedly to detect a rotated face in the given image. But such an approach requires a lot of computation time. In this paper, a method of extracting the axis of symmetry for a given set of points is proposed. The axis of symmetry for the edge points in the face detection window is extracted in a way that is fast and accurate, and the face detector is applied only for that direction. It is shown that the mean and standard deviation of the symmetry detection error is and respectively, for the database used.
This paper proposes a new algorithm that improve color component of compensated image using Retinex method for back-light image. A back-light image has two regions, one of the region is too bright and the other one is too dark. If an back-light image is improved contrast using Retinex method, it loses color information in the part of brightness of the image. In order to make up loss information, proposed algorithm adds color components from original image. The histogram can be divided three parts that brightness, darkness, midway using K-mean (k=3) algorithm. For the brightness, it is used color information of the original image. For the darkness, it is converted using by Retinex method. The midway region is mixed between original image and Retinex result image in the ratio of histogram. The ratio is determined by distance from dark area. The proposed algorithm was tested on nature back-light images to evaluate performance, and the experimental result shows that proposed algorithm is more robust than original Retinex algorithm.
This paper provides a novel approach for developers to use face detection techniques for their applications easily without special knowledge by selecting optimal face detection algorithms based on fuzzy inference. The purpose of this paper is to come up with a high-level system for face detection based on fuzzy inference with which users can develop systems easily and even without specific knowledge on face detection theories and algorithms. Important conditions are firstly considered to categorize the large problem space of face detection. The conditions identified here are then represented as expressions so that developers can use them to express various problems. The expressed conditions and available face detection algorithms constitute the fuzzy inference rules and the Fuzzy Interpreter is constructed based on the rules. Once the conditions are expressed by developers, the Fuzzy Interpreter proposed take the role to inference the conditions and find and organize the optimal algorithms to solve the represented problem with corresponding conditions. A proof-of-concept is implemented and tested compared to conventional algorithms to show the performance of the proposed approach.
This Serious Game is on the issue for its positive role recently. A Serious Game helps the learners to recognize the problems effectively, grasp and classify important information needed to solve the problems and convey the contents of what they have learned. The Serious Game can be usefully applied to education and training in the areas of scientific technology and industrial technology. This Paper described trend and classification of Serious Game, and proposed design consideration element for disabled person, and proved the result through question investigation.
In this paper, we propose an routing algorithm for ultra low power and high reliable transmission in WBAN environment. This algorithm is to minimize energy consumption and to maximize the life and reliability for medical devices. Also, this algorithm is not only medical devices but also non-medical devices is to minimize energy consumption and to maximize the life of device. The combination of the distance from the previous node and residual energy calculates weight. The calculated weight is used to calculate the weight of full path by cumulative weights. The full path to the smallest of the weights are set to the path. Also this algorithm is able to select another path to avoid the error path by determining the link status between nodes, when occurs link error and congestion. In this paper, we show that WSN routing algorithm based on shortest hop count routing algorithm and EAR routing algorithm compared to ensure high reliability and low power characteristic of WBAN to be verified through simulations.
PECOLE (Peer-to-Peer Collaborative Environment) is a P2P-based multimedia distributed collaborative environment supporting a collaborative workspace which is composed of a variety of collaborative applications such as multi-chat, video conferencing, screen sharing and etc. Unfortunately, due to the PECOLE's simple group management, it is impossible to perform collaboration activities while joining multiple groups. In this paper, we present the design and implementation of PECOLE+ which is an extension of PECOLE. PECOLE+ resolves the drawback of PECOLE by providing the Group Management Service and the Workspace Management Service. The Group Management Service provides functionalities such as creating groups, joining multiple groups, and searching groups, and etc. The Workspace Management Service provides each group with an associated workspace, supporting the execution of collaborative applications over the workspace. In addition, any collaborative applications with the provided plug-in interfaces can be executed over the workspace as a PECOLE+ collaborative application.
This study was realized the home network system for home care by bio-physical sensor system, to convey for the remote physical signal. The composition condition has four functions of displacement point for a Vision, Somatosensory, Vestibular and CNS that the basic measurement used to a Heart Rate, Temperature, Weight. Physical signal are decided to search a max and min point with adjustment of 0.01 unit in the reference level. There were checked physical condition of body balance to compounded a physical neuroceptor of sensory organ for the measurement such as a Vision, Somatosensory, Vestibular, CNS, BMI. There are to check a health care condition through a combination of physical organ with a posturography of a exercise. The service of home network system can be used to support health care management system through health assistants in health care center and central health care system. It was expected to monitor a physical parameter for the remote control health management system.
When TCP operates in multi-hop wireless networks, it suffers from severe performance degradation due to the different characteristics of wireless networks and wired networks. This is because TCP reacts to wireless packet losses by unnecessarily decreasing its sending rate assuming the losses as congestion losses. Although several loss differentiation algorithms (LDAs) have been proposed to avoid such performance degradation, their detection accuracies are not high as much as we expect. In addition the schemes have a tendency to sacrifice the detection accuracy of congestion losses while they improve the detection accuracy of wireless losses. In this paper, we suggest a new sender-based loss differentiation scheme which enhances the detection accuracy of wireless losses while minimizing the sacrifice of the detection accuracy of congestion losses. Our scheme estimates the rate of queue usage which is highly correlated with the congestion in the network path between a TCP sender and a receiver, and it distinguishes congestion losses from wireless losses by comparing the estimated queue usage with a certain threshold. In the extensive experiments based on a network simulator, QualNet, we measure and compare each detection accuracy of wireless losses and congestion losses, and evaluate the performance enhancement in each scheme. The results show that our scheme has the highest accuracy among the LDAs and it improves the most highly TCP performance in multi-hop wireless networks.
Plaintext and key are independent in the existing block cipher. Also, encryption/decryption is performed by using structural features. Therefore, the external environment of suggested mixed cryptographic algorithm is identical with the existing ones, but internally, features of the existing block cipher were meant to be removed by making plaintext and key into dependent functions. Also, to decrease the loads on the authentication process, authentication add-on with dependent characteristic was included to increase the use of symmetric cryptographic algorithm. Through the simulation where the proposed cryptosystem was implemented in the chip level, we show that our system using the shorter key length than the length of the plaintext is two times faster than the existing systems.
Focusing upon the post-adoption stage of IS, this study reasoned that IS users' personality is one of major influencing factors of continuous IS usage intention and empirically examined how the degree of continuous IS usage intention is variable according to the IS users' personality types classified based on MBTI(Myers Briggs Type Indicator). In order to validate the research model and hypotheses, this study made a field survey of 330 IS users and statistically analysed response data. The results of empirical analyses showed that the intent of continuous IS usage was affected by self-efficacy of IS; and self-efficacy by self-leadership of IS; and self-leadership by IS user' personality type and expectation confirmation. That is, it was found that IS users' personality type and three intervening variables(expectation confirmation, self-leadership and self-efficacy) were significant predictors of the intent of continuous IS usage. This study is thought to be contributive to providing the theoretical basis of finding IS success factors in the post-adoption stage and the practical guideline for effective personnel management relevant to IS implementation.
In this paper, we propose a new paradigm of augmented reality board game environment and a portable game assistant(PGA) which can help gamers with strategy information. Previous AR board games consist of a private and public space. The public space provides rules of the game and shows the scene of game. And the gamers control game pieces in the public space. The previous games use the RFIDs for recognizing positions of the pieces, and the VR/AR environment for providing the scene of the game. However the RFIDs are expansive, and the VR/AR environment is inconvenient because it uses additional devices: the DataGlove, the digital pen, and the HMD. The proposed system recognizes positions of real pieces using the computer vision technique, and uses a monitor to provide dynamic effects. In the private space, previous systems provide entire screen of game and position of specific pieces, but cannot be controled the pieces by gamers. Therefore, in this system, we provide PGA that helps the user to plan of the strategy individually using universally mobile. The PGA helps to plan the strategy in the individual area, and to play easily in the side of the user’s convenience.
This study proposes CAOPI(Computer Aided Organ Prediction Index) system based on APACHE Ⅱ(Acute Physiology And Chronic Health Evaluation) for classifying disease severity and predicting the conditions of patients' major organs. The existing ICU disease severity evaluation is mostly about calculating risk scores using patients' data at certain points, which has limitations on making precise treatments. CAOPI system is designed to provide personalized treatments by classifying accurate severity degrees of emergency patients, predicting patients' mortality rate and scoring the conditions of certain organs.
This paper suggests a user based OST(Open Street Traffic) system that solves TPEG's one-way communication problem, UTIS's limited usage and DSRC's small traffic bandwidth. In current commercial TPEG service, only some service providers collect traffic information. Thus, it can't cover traffic status in local lanes And UTIS ,which local governments and police supports, requires additional equipments. Currently, only taxi and official vehicles use this system. Therefore, new traffic service by mobile device and user's participation can provide very detail traffic information coupling with previous traffic systems. But in this new system, real-time high volume data can be a problem. So, in this paper, new data storage manager design(TDSM :Traffic Data Storage Manager) is suggested and its performance is measured against commercial DBMS.
Under the influence of a paradigm shift for administrative service of public institutions in around the world, the 'Government Affairs Assessment Act' has been enacted in Korea in March 2006. By the law, each local governments have been obligating to conduct self-assessment and resident's satisfaction survey for improving administrative service. Thus, the purpose of this study is to evaluate the administrative service quality of district offices(in seoul) in order to meet the government's efforts, and to derive improvement point of administrative service quality in district office. Consequently, this study shows administrative service quality factors affecting resident's overall satisfaction degree, service value maturity and positive image maturity of district office and then, will explore improvement ways of each district office through attribute analysis of administrative service quality.
Each area of society has changed because of the development of information technology. Especially, the advent of NCW based on the technology of network has become a new paradigm for executing warfare. Effectiveness of NCW can be maximized by building the C4I system which is a core system of NCW. However, if we don't consider the influence in term of human dimension, we can't expect the effect of C4I system, since the key factor in C4I is human. In this paper, we propose an algorithm for evaluating Combat Power Effectiveness by considering the Influence of Human Factors that wasn't reflected in the past. Based on experimental validation our algorithm is more substantial than baseline algorithms. In addition, we proved that the Influence of Human Factors(e.g. collaboration) is the most important in battlefield. Therefore, proposed algorithm can be used for enhancing not only mission effectiveness in terms of military field but also work performance by effective Human Resource Management in terms of an enterprise.
Customer relationship management (CRM) comprises a set of processes and nabbing systems supporting a business strategy to build long term, profitable relationships with specific customers. Customer data and information technology(IT) tools form the foundation upon which any successful CRM strategy is built. Recently, the Internet rectifying this life, IT technology and the rapid development taking place over the Internet, customer relationship management, e-CRM has emerged. The purpose of this research is to investigate the important elements of e-CRM which in fluence the customer satisfaction and the brand loyalty in e-shopping mall. And this study is to investigate the relationship between customer satisfaction and repurchase intention and word of mouth intention.