Multimedia and Ubiquitous Engineering

In this paper the definition of a multiwedgelet is introduced. The multiwedgelet is defined as a vector of wedgelets. In order to use a multiwedgelet in image approximation its visualization and computation methods are also proposed. The application of multiwedgelets in image denoising is presented, as well. As follows from the experiments performed multiwedgelets assure better denoising results than the other known state-of-the-art methods.

If a piece of picture could contain a sequence of video frames, it is amazing. This paper develops a new video compression approach based on underdetermined blind source separation. Underdetermined blind source separation, which can be used to efficiently enhance the video compression ratio, is combined with various off-the-shelf codecs in this paper. Combining with MPEG-2, video compression ratio could be improved slightly more than 33 %. As for combing with H.264, twice compression ratio could be achieved with acceptable PSNR, according to different kinds of video sequences.

Little prior communication between supplier and demander makes recognition of grid service ability helpful to make full use of some rich resources, such as software, hardware, information and others. Description and matching process about grid service based on ontology semantic were proposed, and its relative advantages comparing with the existing grid discovery mechanisms were also proved.

In beacon-enabled LR-WPANs, the high reliability of beacon frame transmission is required because all transmissions are controlled by the information in the beacon frame. However, the process for the beacon-loss scenario is not carefully considered in the standard. The method proposed in this paper allows a node not receiving a beacon frame to keep transmit its pending frames only within the minimum period of CAP based on the previously received beacon frame while the standard prevents the node from sending any pending frame during a whole superframe. The method is extensively simulated and proven the enhancements on the performances.

In this paper, we present monitoring the distribution environmental factors for exporting agricultural products in real time based on sensor networks and packaging technologies, and how the distribution environmental factors would influence the quality of agricultural products has been studied by measuring the actual quality of agricultural products when this distribution process has been completed. For this, sensor nodes and communication system, optimized to a monitoring process for the distribution environmental factors of agricultural products, have been designed and implemented. With the paprika exported to overseas, information on temperature/humidity/path (distribution environmental factors) has been monitored in real time. The possibility of utilization of sensor networks based distribution environmental factors monitoring technology could be verified through such case studies.

The increasing number of accidents is attributed to several factors, among which is the lack of concentration caused by fatigue. The driver drowsiness state can be detected with several ways. Among these methods, we can quote those which analyze the driver eyes or head by video or studying the EEG signal. We present, in this paper an approach which makes it possible to determine the orientation of the driver head to capture the drowsiness state. This approach is based on the estimation of head rotation angles in the three directions yaw, pitch and roll by exploiting only three points face features.

Hadoop has good features for storing data, task distribution, and locality-aware scheduler. These features make Hadoop suitable to handle Big data. And GPGPU has the powerful computation performance comparable to supercomputer. Hadoop tasks running on GPGPU will enhance the throughput and performance dramatically. However the interaction way between Hadoop and GPGPU is required. In this paper, we use JNI to interact between them, and write the experimental Hadoop program with JNI. From the experimental results, we show the potentiality GPGPU-enabled Hadoop via JNI.

This study aims to provide personalized contents recommendation services depending on a learner’s learning stage and learning level in the learning management system using open courses. The intelligent recommendation system proposed in this study selects similar neighboring groups by performing user-based collaborative filtering process and recommends phased learning contents by using prior knowledge information between contents and considering the relevance and levels of learning contents. The proposed learning contents recommendation is applied flexibly according to a user’s learning situation and situation-specific contents recommendation link is created by performing the intelligent learning process of recommendation system. This service allows a variety of industrial classification learners using open course to effectively choose more accurate curriculum.

Service engineering is quickly moving forward to social services. Social service engineering is one of the most promising arenas of service engineering in the 2010s. The term social experience represents the analogy of user experience in a social service context. The author proposes an evolutionary path model of social experience design in order to highlight the design principles of social experience design.

This paper proposes a method to improve the performance of DRAM-SSD in Linux systems by modifying the block device driver. Currently, it processes requests in a segment-by-segment way. However it involves overheads because it needs to perform overlapped works repetitively when finishing one segment and starting next one. It prevents DRAM-SSD from running in full speed. The proposed method reduces the overheads by grouping multiple segments into one request, removing unnecessary duplicated steps. But, the grouping also involves overhead. Thus we propose to determine adaptively whether to do grouping or not according to the number of segments contained in requests. From the evaluation results, the throughput of the proposed method improved compared with the segment-by-segment way.

The paper proposed the Closed Plant Factory System (CPFS) applied the crop growth model. The CPFS monitors climate data in a closed building or room and the actuator’s status for control devices, and provides optimized operations for controlling growth environments. The CPFS monitors environmental data, plant growth data and the control devices’ status data. This system can analyse the optimal growth environment and the correct control environment. We implemented the system and applied it to a testbed, also confirmed that the CPFS operated real-time monitoring service and controlling service correctly.

Leveraging on the Web-of-Things (WoT) allows standardizing the access of things from an application level point of view. The protocols of the Web and especially HTTP are offering new ways to build mashups of things consisting of sensors and actuators. Two communication protocols are now emerging in the WoT domain for event-based data exchang, namely WebSockets and RESTful APIs. In this work, we motivate and demonstrate the use of a hybrid layer able to choose dynamically the most energy efficient protocol.

Recently, femtocell received a signification interest to improve the indoor coverage and provide better voice and data services. Lots of work has been done to improve the femtocell security, but still there are some issues which need to be addressed. Our contribution to the femtocell security is to protect secure zone (femtocell coverage area within macrocell) from unauthorized (non-CSG) users. In this paper, we propose a secure registration scheme for femtocell embedded network. In this scheme, only Closed Subscriber Group (CSG) users are allowed to access both the femtocell and macrocell services within the secure zone. By prioritizing the femtocell over macrocell within the secure zone, every user will try to camp on femtocell and invoke location registration to the femtocell as the user enters to the femtocell coverage area. If the user is within the allowed users list, the femtocell will allow the user otherwise femtocell will send a reject message to the user and also send the user information to the core network.

Keyphrase extraction is to select the most representative phrases within a given text. While supervised methods require a large amount of training data, unsupervised methods can perform without prior knowledge such as language. In this paper, we propose a ranking algorithm based on unsupervised keyphrase extraction and develop a framework for retrieving opinion articles. Since the proposed algorithm uses an unsupervised method, it can be employed to multi-language systems. Moreover, our proposed ranking algorithm measures the importance in three aspects, the amount of information within articles, representativeness of sentences, and frequency of words. Our framework shows better performance than previous algorithms in terms of precision and NDCG.

In this paper, we propose a frequent pattern mining technique for ranking webpages based on topics. This technique shows search results according to selected topics in order to give users exact and meaningful information, where we use an indexer with the frequent pattern mining technique to comprehend webpages’ topics. After mining frequent patterns related to topics (i.e. frequent topics) in collected webpages, the indexer compares new webpages with the generated patterns and calculates degree of topic proximity to rank the new ones, where we also propose a special tree structure, named RP-tree, to compare the new webpages to the frequent patterns. Since our technique reflects topic proximity scores to ranking scores, it can preferentially show webpages which users want.

We propose a new probabilistic model for constructing efficient prototypes of handwritten digit images. We assume that all digit images are of the same size and obtain one color histogram for each pixel by counting the number of occurrences of each color over multiple images. For example, when we conduct the counting over the images of digit “5”, we obtain a set of histograms as a

prototype

of digit “5”. After normalizing each histogram to a probability distribution, we can classify an unknown digit image by multiplying probabilities of the colors appearing at each pixel of the unknown image. We regard this method as the baseline and compare it with a method using our probabilistic model called Multinomialized Subset Infinite Relational Model (MSIRM), which gives a prototype, where color histograms are clustered column- and row-wise. The number of clusters is adjusted flexibly with Chinese restaurant process. Further, MSIRM can detect

irrelevant

columns and rows. An experiment, comparing our method with the baseline and also with a method using Dirichlet process mixture, revealed that MSIRM could neatly detect irrelevant columns and rows at peripheral part of digit images. That is, MSIRM could “trim” irrelevant part. By utilizing this trimming, we could speed up classification of unknown images.

As the number of people who buy books online increases, it is becoming a way of life for people. Recently, algorithms to retrieve book reviews have been proposed for searching meaningful information since ranking algorithms for general purpose are not suitable. Although the previous algorithms consider features of book review, they calculate ranking scores without reflecting user influence. In this paper, thus, we propose a novel algorithm for ranking book reviews based on user influence. To apply user influence, the proposed algorithm uses recommendations by other users. For performance evaluation, we perform precision and recall tests. The experimental results show that the proposed algorithm outperforms previous algorithms for searching book reviews.

Support Vector Machine (SVM) has been shown powerful in pattern recognition problems. SVM-based speaker verification has also been developed to use the concept of sequence kernel that is able to deal with variable-length patterns such as speech. In this paper, we propose a new kernel function, named the Log-Likelihood Ratio (LLR)-based composite sequence kernel. This kernel not only can be jointly optimized with the SVM training via the Multiple Kernel Learning (MKL) algorithm, but also can calculate the speech utterances in the kernel function intuitively by embedding an LLR in the sequence kernel. Our experimental results show that the proposed method outperforms the conventional speaker verification approaches.

A new possible confidence measure for automatic speech recognition is presented along with results of tests where they were applied. A classical method based on comparing the strongest hypotheses with an average of a few next hypotheses was used as a ground truth. Details of our own method based on comparison of edit distances are depicted with results of tests. It was found useful for spoken dialogue system as a module asking to repeat a phrase or declaring that it was not recognised. The method was designed for Polish language, which is morphologically rich.

Recently, codebook-based object recognition methods have achieved the state-of-the-art performances for many public object databases. Based on the codebook-based object recognition method, we propose a novel method which uses the saliency information in the stage of pooling code vectors. By controlling each code response using the saliency value that represents the visual importance of each local area in an image, the proposed method can effectively reduce the adverse influence of low visual saliency regions, such as the background. On the basis of experiments on the public Flower102 database and Caltech object database, we confirm that the proposed method can improve the conventional codebook-based methods.

For the ovarian cancer diagnosis with biomarkers in urine samples, various calibration functions are selected and investigated to compensate the variability of their concentrations. The 15 biomarkers tested in this paper were extracted and measured for the urine samples of 178 patients. Three types of functions were employed to calibrate the biomarkers, including the existing one that divides the biomarker concentration by that of the creatinine. The AUC of the ROC of the calibrated biomarker with each function was chosen to evaluate the performance. Experimental results show that the best performance could be obtained by dividing the concentration of the biomarker by that of the creatinine raised to the power of the optimal exponent that was determined for the maximum AUC of the calibrated biomarker.

Giving a certain training sample set, the learning efficiency almost depends on the kernel function in kernel methods. This inspires us to learn the kernel and the parameters. In the paper, a selecting parameter algorithm is proposed to improve the calculation efficiency. The normalized inner product matrix is the approximation target. And utilize the iterative method to calculate the optimal bandwidth. The defect detection efficiency can be greatly improved adopting the learned bandwidth. We applied the algorithm to detect the defects on tickets’ surface. The experimental results indicate that our sampling algorithm not only reduces the mistake rate but also shortens the detection time.

This paper presents a fast version of the self-organizing map (SOM) algorithm, which simplifies the weight distance calculation, the learning rate function and the neighborhood function by removing complex computations. Simplification accelerates the training process in software simulation and is applied in the field of handwritten digit recognition. According to the evaluation results of the software prototype, a 15–20 % speed-up in the runtime is obtained compared with the conventional SOM. Furthermore, the fast SOM accelerator can recognize over 81 % of handwritten digit test samples correctly, which is slightly worse than the conventional SOM, but much better than other simplified SOM methods.

To process data which increasingly become larger and more complicated, frequent graph mining was proposed, and numerous methods for this has been suggested with various approaches and applications. However, these methods do not consider characteristics of sub-graphs for each length in detail since they generally use a constant minimum support threshold for mining frequent sub-graphs. Small sub-graphs with a few vertices and edges tend to be interesting if their supports are high, while large ones with lots of the elements can be interesting even if their support are low. Motivated by this issue, we propose a novel frequent graph mining algorithm, Frequent Graph Mining with Length-Decreasing Support Constraints (FGM-LDSC). The algorithm applies various support constraints depending on lengths of sub-graphs, and thereby we can obtain more useful results.

A meta-search engine transmits the user’s query simultaneously to several individual search engines and aggregate results into a single list. In this paper we conduct comparisons on several existing rank aggregation methods. Then based on those comparisons, an improved ranking aggregation method is proposed for meta-search engine. This method combines merits of the Borda’s method and scaled footrule method. Extensive experiments show that this improved method outperforms the alternatives in most cases.

The digitization of patient health information has brought many benefits and challenges for both the patient and doctor. But security and privacy preservation have remained important challenges for wireless health monitoring systems. Such concerns may result in reluctance and skepticism towards health systems by patients. The reason for this skepticism is mainly attributed to the lack of assurances about the way patient health information is handled and the implications that may result from it on patients’ privacy. This paper proposes an identity-based privacy preservation framework over u-healthcare systems. Our framework is based on the concepts of identity-based cryptography and non-interactive key agreement scheme using bilinear pairing. The proposed framework achieves authentication, patient anonymity, un-traceability, patient data privacy and session key secrecy, and resistance against impersonation and replay attacks.

Retrieving the content of webmail from physical memory is one key issue for investigators because it may provide with useful information. This paper proposes a webmail evidence reconstructing method from memory dumps on Windows XP platform. The proposed method uses mail header format defined in RFC2822 and HTML frame based on specific webmail server to locate header and body respectively. Then webmail is reconstructed based on matching degree between FROM, TO(CC/BCC), DATE and SUBJECT fields of header and corresponding content extracted from body. The experiment results show that this method could reconstruct the webmail from memory dumps.

Bucketization techniques allow for effective organization of encrypted data at untrusted servers and for querying by clients. This paper presents a new metric for estimating the risk of data exposure over a set of bucketized data. The metric accounts for the importance of bucket distinctness relative to bucket access. Additionally, we review a method of controlled diffusion which improves bucket security by maximizing entropy and variance. In conjunction with our metric we use this method to show that the advantages of bucketization may be offset due to a loss of bucket security.

The latest boom in the prevalence of smartphones has been encouraging various personal services to store and utilize important data such as photos and banking information. Thus, the importance of user authentication has also been growing rapidly. Nevertheless, many problems have arisen as a result of the common method of using a four-digit personal identification number (PIN) because of its potential for being breached by a brute force attack or shoulder-surfing attack. Various authentication schemes have been developed to overcome these problems. In this paper, we also propose a new password-based user authentication scheme that utilizes the well-known Minesweeper game, providing better usability as well as greater security. The proposed scheme provides its users a simple method for memorizing their passwords and usable security by allowing them to enter calculated values rather than the password itself.

In recent years, the opportunity to deal with classified information in a computer has increased, so the cases of classified information leakage have also increased. We have developed a function called “diffusion tracing function for classified information” (tracing function), which has the ability to trace the diffusion of classified information in a computer and to manage which resources might contain classified information. The classified information exchanged among the processes in multiple computers should be traced. This paper proposes a method which traces the diffusion for classified information among multiple computers. Evaluation results show the effectiveness of the proposed methods.

An app in Android can collaborate with other apps and control personal information by using the Intent or user’s allowing of permission. However, users cannot detect when they communicate. Therefore, users might not be aware information leakage if app is malware. This paper proposes DroidTrack, a method for tracking the diffusion of personal information and preventing its leakage on an Android device. DroidTrack alerts the user of the possibility of information leakage when an app uses APIs to communicate with outside. These alerts are triggered only if the app has already called APIs to collect personal information. Users are given the option to refuse the execution of the API if it is not appropriate. Further, by illustrating how their personal data is diffused, users can have the necessary information to help them decide whether the API use is appropriate.

Secure authentication mechanism is a pre-requisite to remote access of server’s resources particularly when done over the Internet. This paper presents a three factor authentication protocol which is based on verification of user’s: biometrics, knowledge proof of a password and possession of token to pass authentication. The proposed protocol utilizes bilinear mapping for session key establishment and elliptic curve discrete logarithm problem for security.

Copy-move is the most common tampering manipulations, which copies one part of the image and pastes into another part in the same image. Most existing techniques for detecting tampering are sensitive to rotation and reflection. This paper proposed an approach to detect Copy-Move forgery with rotation. Firstly the suspicious image is divided into overlapping blocks, and then LBP operator are used to produce a descriptor invariant to the rotation for similar blocks matching. It is effective to solve the mismatch problem caused by the geometric changes in duplicated regions. In order to make the algorithm more effective, some parameters are proposed to remove the wrong matching blocks. Experiment results show that the proposed method is not only robust to rotation, but also to blurring or noise adding.

At CDCIEM 2012, Yang et al. proposed a new construction of somewhat homomorphic encryption scheme over integers, which is quite efficient in the perspective of the key size. In this paper, we present an effective lattice reduction attack on Yang et al.’s scheme, where it is easy to recover the plaintext by applying LLL algorithm.

Since wireless sensor networks (WSNs) are resources-constrained, it is very essential to gather data efficiently from the WSNs so that their life can be prolonged. Data aggregation can conserve a significant amount of energy by minimizing transmission cost in terms of the number of data packets. Many applications require privacy and integrity protection of the sampled data while they travel from the source sensor nodes to a data collecting device, say a query server. However, the existing schemes suffer from high communication cost, high computation cost and data propagation delay. To resolve the problems, in this paper, we propose a new and efficient integrity protecting sensitive data aggregation scheme for WSNs. Our scheme makes use of the additive property of complex numbers to achieve sensitive data aggregation with protecting data integrity. With simulation results, we show that our scheme is much more efficient in terms of both communication and computation overheads, integrity checking and data propagation delay than the existing schemes for protecting integrity and privacy preserving data aggregation in WSNs.

Reversible watermarking can recover the original cover after watermark extraction, which is an important technique in the applications requiring high image quality. In this paper, a novel image reversible watermarking is proposed based on neural network and parity property. The retesting strategy utilizing the parity detection increases the capacity of the algorithm. Furthermore, the neural network is considered to calculate the prediction errors. Experimental results show that this algorithm can obtain higher capacity and preserve good visual quality.

An image protection apparatus includes an information collecting unit for collecting personally identifiable information to be embedded in images captured by an image capturing instrument; and an information processing unit for extracting personal information from the collected personally identifiable information. Further, the image protection apparatus includes an information embedding unit for embedding the extracted personal information into a captured image; and an image signature unit for writing a signature on the captured image by using the extracted personal information.

Six Thinking Hats which is designed by Edward de Bono enhances the excellence of the thinking and has an effect on cultivating divergent thinking. In particular, it is effective in seeking a reasonable solution by analyzing some problems from a variety of views in debate-learning. In this paper, we developed a system sharing voice and images based on Six Thinking Hats, using sensors of android device. We analyzed tools and guidelines by making design structural model for designing the system. We developed debate-learning system, verified its utility and analyzed improvements through a demonstration and a practice for educational experts.

With the advent of smart devices, educational apps for smart learning are actively being developed, but the existing native apps run only on specific devices and are not compatible with other devices. Webapp, a new app development method, which is written using HTML5, supports a cross-platform. In this study, a Webapp for learning about levers as mentioned in elementary school textbooks was developed using HTML5. The proposed Webapp was tested by a group of incumbent expert elementary school teachers, revealing that the proposed contents and Webapp offer high educational value.

This paper demonstrates and evaluates the classification performance of the optimal biomarker combinations that can diagnose ovarian cancer under Luminex exposed environment. The optimal combinations were determined by T Test, Genetic Algorithm, and Random Forest. Each selected combinations’ sensitivity, specificity, and accuracy were compared by Linear Discriminant Analysis (LDA) and k-Nearest Neighbor (k-NN). The 8 biomarker data used in this experiment was obtained through Luminex-PRA from the serum of 297 patients (cancer 81, benign 216) of two hospitals. In this study, the results showed that selecting 2–3 markers with Genetic Algorithm and categorizing them with LDA shows the closest sensitivity, specificity, and accuracy to those of the results obtained through complete enumerations of the combination of 2–4 markers.

The remote control and media sharing of consumer devices are key services for smart living. The involving of mobile devices into these services has become a technology trend. Existing solutions to these services restrict these devices to be located in the same local network. In this paper, we design and implement an integrated architecture that supports the outdoor remote control to home devices and the sharing of digital media among indoor and outdoor devices. By following the digital home related standards, we show our system design with the details of hardware and software components.

To manage the frequent updates of moving objects’ locations on road networks in an efficient way, we propose a new distributed grid scheme which utilizes node-based pre-computation technique to minimize the update cost of the moving objects’ locations. Because our distributed grid scheme manages spatial network data separately from the POIs (Point of Interests) and moving objects, it can minimize the update cost of the POIs and moving objects. To process k-nearest neighbor (k-NN) query in our distributed grid scheme, we propose a k-NN query processing algorithm based on Incremental cell expansion which minimize the number of accesses to adjacent cells during POIs retrieval in a parallel way. Finally, we show from our performance analysis that our algorithm is better on retrieval performance than the k-NN algorithm of the existing work.

Recent development in wireless communication technology and mobile equipment is making location-based services (LBSs) more popular day by day. However, because users continuously send queries to a server by using their exact locations in the LBSs, private information can be in danger. Therefore, a mechanism for users’ privacy protection is required for the safe and comfortable use of LBSs. For this, we, in this paper, propose a grid-based cloaking area creation scheme in order to support continuous queries in LBSs. Our scheme creates a cloaking area rapidly by using grid-based cell expansion to efficiently support the continuous LBSs. In addition, to generate a cloaking area which lowers the exposure probability of a mobile user to a minimum level, our scheme computes a privacy protection degree by granting weights to the mobile users. Finally, we show from our performance analysis that our cloaking scheme shows better performance than the existing cloaking scheme.

This paper considers a relational data system to store XML document efficiently. Also this paper proposes a data model to rewrite XML documents from data storage by representing data view and structure view at the same time and introduce a mapping schema to relational data base system from the data for electronic commerce.

This paper suggests a location-based reservation management service model that can manage various reservation services and provide related information to users through their smart phones in real-time. The proposed service model is based on a smart phone to relieve inconvenience of existing reservation systems that have limited access effectiveness in space and time or long waiting time. To improve service satisfaction, the proposed service model includes a service server to manage highly qualified and reliable reservation schedules with user’s location information from smart phones, and a client to support users to make their application plans through intuitive user interfaces. Therefore, the proposed model can help users to save a long waiting time in various service places, for example food stores, banks, and government office customer service centers.

The detection of moving objects is a basic and necessary preprocessing step in many applications such as object recognition, context awareness, and intelligent visual surveillance. Among these applications, object detection for context awareness impacts the efficiency of the entire system and it requires rapid detection of accurate shape information, a challenge specially when a complicated background or a background change occurs. In this paper, we propose a method for detecting a moving object rapidly and accurately in real time when changes in the background and lighting occur. First, training data collected from a background image are linearly transformed using principal component analysis (PCA). Second, an eigen-background is organized from selected principal components with excellent ability to discriminate between object and background. Finally, an object is detected by convoluting the eigenvector organized in the previous step with an input image, the result of which is the input value used on an EM algorithm. An image sequence that includes various moving objects at the same time is organized and used as training data to realize a system that can adapt to changes in lighting and background. Test results show that the proposed method is robust to these changes, as well as to the partial movement of objects.

Trajectory modeling is basic work for 4D-Route modeling, conflict detection and air traffic flow management. This paper proposes a novel algorithm based on coordinate prediction for trajectory calculation. We demonstrated through simulations with flight position and ground speed, and experimental results show that our-trajectory calculation exhibits much better performance in accuracy.

Edutainment lies at the intersection of games and learning and includes the benefits of both. To increase students’ interest in mathematics and improve their problem-solving abilities, we have designed and implemented a geometric origami edutainment application. This application is based on three heuristic axioms and simple data structures. Students can create any angle or polygon by folding/unfolding the 2D paper displayed on the screen of the Android based system. This application has the benefit of an intuitive interface, and requires a higher level of thinking from the students than that required by traditional origami. We created the application to entertain the students, but also to assist in improving their mathematical problem-solving abilities.

Gamification is a collection of game-design-origin know-how that facilitates service engagement. It is used in a wide range of applications, marketing, enterprise management, and education. The positive side of gamification provides useful tools for improving engagement. At the same time, there are negative sides of gamification when it is used excessively or maliciously. The author proposes the concept of gamification literacy.

This paper presents a real time algorithm for solving foot skating problem of a character whose motions are controlled in on-line puppetry manner through motion depth sensor such as Kinect. The IR (Infrared Light) projection-based motion sensor is very sensitive to occlusion and light condition. One significant artifact from these characteristics is foot skating, which means that feet are floating over the ground even when the character is standing still. Our algorithm is working as a post processing that applies the orientation data from sensors to a character first, and then keeps monitoring the current character status and applying foot skating solver next whenever the problem occurs. For this, we propose an adaptive threshold method that make positional and velocity threshold change automatically. Inter-frame smoothing is then followed to make sure there is no discontinuity on the motions.

Students meet with many problems during programming education in computer education. Programming education have been several research that are published that helps develop students’ creativity in the process of exploring solutions through flexible. Especially in elementary school students, receive training in programming for the first time feel constraint to lean programming language. But the use of EPL reduces difficulties. So Students can focus on the thinking. Therefore, in this paper, a draft was produced and applied to observe the creative elements increasing of elementary school students. And modify and supplement the draft through improvements to a draft obtained by applying.

This study was conducted to create a more tangible educational environment by allowing learners to directly control three-dimensional learning contents through the touch interface of smart devices. Furthermore, because there are limitations to the acquisition and provision of three-dimensional learning contents due to difficulties in producing them, the proposed framework was designed to allow teachers and learners to directly produce and share contents. The proposed framework is based on intuitive XML language and the application was built to enable playback and authoring in Android-installed devices. In addition, a server environment was constructed for contents sharing. The feasibility of the proposed framework was verified through expert evaluation and its potential for utilization of new learning contents was positively evaluated.

Currently used electronic books (hereafter referred as “e-book”) do not reflect people’s memo-taking behavior patterns, as an intuitive Graphic User Interface (hereafter referred as “GUI”) is not used in e-books. A study was carried out to suggest a GUI prototype that applies users’ memo-taking behavior patterns to the memo function of iBooks to enable greater usability. The prototype herein suggested is a memo GUI prototype that can apply people’s real-life memo-taking behavior to the memo function based on the iBooks interface. For the next step, a usability test was conducted on the suggested prototype and the iBook’s memo interface through four environmental factors and eighteen evaluation factors. Five research subjects participated in the usability test on two types of interface, and a questionnaire was analyzed using a paired t-test (T-test). Analysis of the questionnaire showed that users were highly satisfied with the usability of the newly suggested prototype, compared to iBooks.

The requirement for quickly solving complicated problems poses a fundamental challenge to the modern organization. In order to cope with this challenge, an organization needs to tune its management methodology to reduce time and costs and to increase its organizational efficiency. The author proposes a theory called a Relaxed Stability Organization (RSO) framework from implications learned from Relaxed Stability Technology (RST) in Configured-Control Vehicle (CCV) technology. The author discusses the overall organizational challenges in general. Then, the author discusses how the viewpoint of RST technology can be applied to organizational management. The author presents the framework of RSO Theory.

Stream processors, with the stream programming model, have demonstrated significant performance advantages in the domains signal processing, multimedia and graphics applications, and are covering scientific applications. In this paper we examine the applicability of a stream processor to 2-D stencil scientific applications, an important and widely used class of scientific applications, which compute values using neighboring array elements in a fixed stencil pattern. We first map 2-D stencil scientific applications in FORTRAN version to the stream processor in a straightforward way. In a stream processor system, the management of system resources is the programmers’ responsibility. We then present several optimizations, which avail the stream program for 2-D stencil scientific applications, of various aspects of the stream processor architecture. Finally, we analyze the performance of optimized 2-D stencil scientific stream applications, with the presented optimizations. The final stream scientific programs gain from 2.56 to 7.62 times faster than the corresponding FORTRAN programs on a Xeon processor, with the optimizations playing an important role in realizing the performance improvement.

In this study, an application to support field learning was developed to apply to education Location Based Service (LBS) which is expanding with the spread of smartphones. To select functions in tune with the purpose, a requirements survey was conducted for current elementary school teachers, and the application was developed by reflecting the requirements based on an analysis of the survey results. Through the developed application, teachers can provide information to students and students can acquire information (location, pictures, description) required for field learning and carry out autonomous activities. The developed application was explained and demonstrated to current elementary school teachers who were given an experience of using it. A survey to verify its effectiveness was conducted and it was found that the application had a high potential for being utilized in field learning.

Among the variety of vehicle technology trend issues, the biggest one is focus on automotive network system. Especially, optical network system is preferred. The aim in optical network system including vehicular environment information is that realization of media streaming service beyond the current car audio system. This paper is introduced the implementation of media streaming service which is consist of optical network as called MOST (Media Oriented System Transport) and realization of car audio system adapted to vehicular environment information collected from (On-Board Diagnosis) OBD via (Controller Area Network) CAN.

In order to realize energy-aware information systems, it is critical to discuss how to reduce the total electric power consumption of information systems. We consider applications of a communication type where a server transmits a large volume of data to clients. A client first selects a server in a cluster of servers and issues a file transmission request to the server. In this paper, we newly propose the transmission power consumption laxity-based (TPCLB) algorithm to select a server for a cluster of servers so that the total power consumption in a cluster of servers can be reduced. We evaluate the TPCLB algorithm in terms of the total power consumption and elapse time compared with the round-robin (RR) algorithm.

In this paper, we considered that SCADA system has few authorized users and access control is one of the most important values for cyber security. We propose the method which reducing the success probability of attacker’s penetration using ordered countermeasures. We assume that any system has two or more safety countermeasures for authentication. It follows that setting multiple countermeasures in chain and making a causal relationship before and after action. And then, we making an access procedure matrix for it and sharing them among authorized users. As doing so, we can prevent attacker’s penetration and reduce risk level by hacking.

For this study, we reviewed theoretical background of STEAM education and domestic and international case studies in STEAM education. By doing so, we developed and applied the STEAM Education Program through the use of Scratch. This program is designed for the 3rd (“Energy and Tools”) and 4th (“Combustion and Extinguishing”) lessons of 6th graders’ science in elementary school. As a result, the creativity index and positive attitude about science of the students who went through the researched program increased with meaningful difference compared to that of the sample population. The result of this study shows that ‘The STEAM Education Program,’ using Scratch, can improve creativity. And it is sure that it brings positive changes for the Science Related Affective Domains.

Smart Grid is a convergent system of the existing power grid and Information Technology (IT). In Smart Grid system, AMI (Advanced Metering Infrastructure) is a system with various sensors to evaluate data related with the usage of various utility resources such as electricity, gas, and water. In this paper, IEEE 802.15.4 MAC protocol for the AMI sensor networks is analyzed. Based on the analysis, OPNET simulator was implemented for the performance evaluation. Particularly, this paper focuses on the effect of protocol parameters to the performance. For these parameters, the simulation results are presented to achieve the most efficient usage of network under different traffic loads. Based on the performance evaluation results, it is revealed that real-time data transmission is possible if the total offered load is restricted under 50 % with 100 nodes and the offered load period from 20 to 50 % makes the best trade-off in terms of network throughput, average delay, etc.

We propose Peer-to-Peer-based (P2P-based) home monitoring system architecture to exploit a vacuum robot with an IP camera, a movable IP camera, without requiring a number of cameras for the whole monitoring at home. The key implementation issues for the proposed home monitoring system are (1) the easy configuration of a vacuum robot to connect to Wi-Fi networks, (2) the session management between a vacuum robot and a home monitoring server, and (3) the support of the Network Address Translator (NAT) traversal between a vacuum robot and a user terminal. In order to solve these issues, we use and extend the Wi-Fi Protected Setup (WPS), the Session Initiation Protocol (SIP), and the UDP hole punching. For easy configuration of a vacuum robot, we also propose the GENERATE method which is an extension to the SIP that allows for the generation of a SIP URI. In order to verify the feasibility of the proposed system, we have implemented the prototype and conducted the performance test using the authoritative call generator.

With the development of mobile communications and Internet technologies, smart phones have become a necessity of life. To have better connection status, power consumption, and faster transmission speed, the most of mobile users want to access 802.11 wireless networks that are well known as a Wi-Fi. When entering a new area, a mobile host (MH) decides to use one of access routers (ARs) on available networks. However, since previous works are focused on layer 2 handoff for faster connection at 802.11, only the subsystem identification (SSID) and signal strength are considered to choose its new connection. This can fail to provide the MH with a suitable AR. Therefore, more information needs to be used to determine the suitable AR and seamless connectivity. In this paper, we extend a prefix information option in the router advertisement message to include the status information of an AR, such as status of the MH, capacity of the router, current load of the router, and depth of the network hierarchy. Also, we propose a decision engine by which the MH can analyze the status information of ARs and determine a suitable AR automatically based on the information. By analyzing our simulation results, we found that our AR discovery process has several advantages. For the MH, the packet loss can be reduced with the increase of wireless connection period. Additionally, load balancing was achieved for the AR and router, and the network topology was also able to become more efficient.

For years, computer scientists have been dreaming of innovating Internet in terms of performance, reliability, energy efficiency, security, and so on. However, it is nearly impossible to carry out practical large-scale experiments and verification, since new software and programs are hardly evaluated on the current Internet environment where routers and switches are totally closed. In this context, Software Defined Networking (SDN) concept has been introduced to deploy software-oriented and open programmable network coupled tightly with traditional Internet (non-SDN) environment. This tight integration results in easy and efficient deployment of SDN domains into non-SDN infrastructure, but it is also required that integrated management methods for SDN and non-SDN be developed. This paper proposes how SDN and non-SDN can be managed in an integrated manner in terms of two aspects: (1) non-SDN driven management approach and (2) SDN oriented management approach, in order to achieve reliable Future Internet environment.

This paper proposes a new half hypercube interconnection network that has the same number of nodes as a hypercube but reduces the degree by approximately half. To evaluate the effectiveness of the proposed half hypercube, its connectivity, routing, and diameter properties were analyzed. The analysis results demonstrate that the proposed half hypercube is an appropriate interconnection network for implementation in large-scale systems.

Wearable computing has been proposed as an alternative to the best computing interfaces and devices for the ubiquitous computing. A digital wear can be a main element of wearable computers. This study shall apply digital yarn as a material of data communications for the purpose to take advantage a digital garment. Wearable P2P application communications are consisted of periodic or aperiodic methods. This paper proposes an aperiodic event process for wearable P2P computing. It shows the transmission process that collects from a digital garment at random time. Specially, the process supports the recovery transfer process when the aperiodic event messages are failed.

The half hypercube interconnection network, has been proposed as a new variation of the hypercube, reducing its degree by approximately half with the same number of nodes as an

n

-dimensional hypercube,

Q

n

. This paper proposes an algorithm for one-to-many broadcasting in an

n

-dimensional half hypercube,

HH

n

, and examines the embedding between hypercube and half hypercube graphs. The results show that the one-to-many broadcasting time of the

HH

n

can be accomplished in

n

+ 1 when

n

is an even number and in

$$ 2 \times \lceil n/ 2\rceil $$

2

×

⌈

n

/

2

⌉

when

n

is an odd number. The embedding of

HH

n

into

Q

n

can be simulated in constant time

O

(

n

) and the embedding of

Q

n

into

HH

n

in constant time

O

(1).

A method to locate an obstacle and calculate the distance to it is proposed. The proposed method utilizes multiple ultrasound emitters that generate signals of identical frequencies and intensities. Corresponding sensors detect the reflected ultrasound signals, and the position of the obstacle is calculated based on the time of flight (TOF) of the ultrasound wave. This method is suitable for autonomous wheelchairs as it facilitates detection of the nearest obstacle, and yields more accurate estimation of the position.

In recent years, with a fast spread of smart phones, the number of users is rapidly increasing, causing the saturation of various kinds of traffic in mobile networks and access networks. This implies that although not only conventional Internet traffic but also many smart phone applications create much traffic, the development of network analysis technologies has yet to be furthered. As a method to analyze and monitor the traffic types of smart devices, the method of using signature and classifying traffic is used, and the speed measurement agent is used to measure the Internet speeds in smart devices. This paper aims to classify the smart device traffic and Internet traffic, analyze the traffic use amount, measure Internet speeds in smart phones amid traffic being created, and thus propose a platform designed to measure user service quality.

RFID tag failure analysis test involves analysis of general devices and interpretation of analysis results, which suggests failure mechanism. Hence, it can only be performed by failure analysis experts with rich expertise and experience. Interpretation of causal relationship between a failure phenomenon and explainable causes of the failure has to rely on failure analyzers’ knowledge and experience. Analyzers have the capability to figure out the precise failure mechanism because they know which type of a failure is associated with which failure mechanism. Failure mechanism by major failure type frequently observed in RFID tag and analysis method should be fully recognized by analyzers.

With the development of information and communication technology, the social infrastructure is secured in order to pass and use anytime, anywhere the information we want. Smart phone application occupies an important place in Ubiquitous Environments. More efficient and sensible way are needed across the medical field taking and getting the prescribed medications according to the disease. This paper present the smart phone application based medication management system using the QR code. We can prevent the duplication prescription and reduce the side effects such as exasperating the disease from cases of overdose or under-taking due to the failure of recognizing the times or time of taking the medication or augmenting immunity to the drug schedule through this model. Also, More efficient and sensible research are needed such as connection problems between the most basic home diagnostic equipment and smart phone application, the algorithm about avoiding drug duplication, time management algorithm of taking the medication and medication delivery algorithm base on this model.

Robot-posture with genetic algorithm is presented in this paper. As a robot platform walking biped robot is used. To cope with the difficulties and explain unknown empirical laws in the robot, practical robot walking on a descending sloped floor is modeled by genetic architecture. These results from the modeling strategy is analyzed and compared.

These days wide variety of platforms and frameworks were researched for network based robot (NBR) but it is difficult to apply those platforms and frameworks to the NBR, because the NBR and its service components keep developed. In other works, the interfaces and execution environments of the NBR and the service components are changed and upgraded very often, and at times, the service components are totally reconstructed. Consequently, a new flexible and reliable network framework that adapts to various service components is necessary. To handle these problems, a solution is suggested in this paper.

Since the modern age, China’s major historical events have always been related to culture and it has been centered to discussions on the national development. Since adopting the reform and openness policy, China has been emerging as a new power and enlarging influence in international politics, economics, and military. However, China recognizes that its cultural influence is still light. Thus, the Chinese government exercises cultural policy which enables China to expand Chinese cultural clout and soft power externally and, at the same time, integrate society by establishing a clear national identity internally. China’s cultural heritage, which once was target to be overthrown, is now inherited and developed. China is changing its cultural awareness.

In the globalized world, the cultural industry has emerged as a new promising field. Countries are accelerating their competition to become a culture power nation. In the past, China used culture in the purpose of electing ideology. Since China’s entry into the World Trade Organization (WTO), China started to foster the cultural industry. Since 2001, China started to carry out the cultural industry policy. In 2009, after ‘Cultural Industry Promoting Plan’, China propelled cultural industry to promote policy in earnest. In 2011, the Chinese government claimed it would nurture the cultural industry as a national strategic industry. In China, cultural industry has been stressed as a part of its soft power strategy. The culture has been emerged as a mean for spreading ideology and a new growth engines for industry.

This research is to suggest a mobile game program for rehabilitation of the hearing impaired. The suggested program is based on the characteristics of hearing-impaired children and the classification of hearing loss. The voice recognition technology is the most intimate way of delivery of information. The suggested program does not require any additional learning or training course, but enables the hearing impaired to do vocal exercises through games and helps them to enjoy rehabilitation training.

Traffic accidents are one of the big problems of modern society. The social damage caused by the traffic accidents are increasing. So, there have been a variety of research analyses to predict the traffic accidents. But there are few studies to predict the frequency of traffic accidents. In this paper, the modeling proposes applying the Markov chain modeling to predict the traffic accidents. In this paper, it is expected that the proposed traffic accident prediction modeling to predict the number of traffic accidents.

The social network has been a very popular research area in the recent years. Lot of people at least have one or more social network account and use it keep in touch with other people on the internet and build own small social network. Thus, the effect and the strength of social network is a very deep and worth to figure out the information delivery path and apply to digital learning area. In this age of web 2.0, sharing knowledge is the main stream of the internet activity, everyone on the internet share and exchanges the information and knowledge every day, and starts to collaborate with other users to build specific knowledge domain in the knowledge database website like Wikipedia. This learning behavior also called co-writing or collaborative learning. This learning strategy brings the new way of the future distance learning. But it is hard to evaluate the performance in the co-writing learning activity, researchers still continue to find out more accurate method which can measure and normalize the learner’s performance, provide the result to the teacher, assess the student learning performance in social dimension. As our Lab’s previous research, there are several technologies proposed in distance learning area. Based on these background generation, we build a wiki-based website, provide past exam question to examinees, help them to collect all of the target college or license exam resource, moreover, examinees can deploy the question on the own social network, discuss with friends, co-resolve the questions and this system will collect the path of these discussions and analyze the information, improve the collaborative learning assessment efficiency research in social learning field.

With the population of social platform, such as Facebook, Twitter and Plurk, there are lots of users interest in playing game on social platform. It’s not only the game style they want to play, but also high interaction with other users on social platform. Hence, the development of social network makes social games as a teaching tool becomes an emerging field, but in order to use the social network games for teaching, it needs to understand the game flow as an appropriate reference to be judged. In this paper, we use simulation games and social utility games of Facebook as examples. Using the flowcharts and the triangulation methods theory to analyze the characteristics of the flows by finding verbs and goals, and obtaining the differences by comparing social behavior, accumulate of experience, items collection system and tasks.

In recent years, ubiquitous learning becomes more and more popular. Geography learning can be adapted into smart phone platform to be very useful learning system. Junior high school students can assess the smartphone to study geography in Taiwan. With simple test items, the system will generate individual learning profile and test analysis report for students.

Nowadays E-learning is widely used in teaching and training purposes, and it also facilitates conventional classroom-based learning activities with advanced information technologies. On the other hand, such advanced information technologies also make digital learning content easily applied to some acknowledged learning theories, such as Behaviorism, Cognitivism, Constructivism, and make e-learning being more practical and diverse in many pedagogical purposes.

The resources and applications about ebook have been changing people’s way of reading due to the popularization of ebook readers. It also has significantly changed the traditional rules and concepts of publication. Therefore, an important issue we have to face consequentially is how to create qualified digital publications for readers. In fact, there are a lot of excellent e-learning contents have been produced and stored in repositories or management systems. But unlike the convenience of enjoying ebooks with ebook readers, these excellent learning contents have much more complicated design issues and have to be put on specific learning management systems (LMS) due to the conformance of learning strategies and management requirements. Moreover, many excellent learning contents and courses are produced by the teachers who spent a lot of time and energy. They also have the expectation of converting these learning contents to their own private publications. As the result, we propose a file converter which is able to convert the SCORM compliant courses into EPUB publications. The system consist of four modules; Presentation Transforming Module, Metadata Transforming Module, Sequencing and Navigation Transforming Module and Packaging Transforming Module. We look forward to seeing these excellent SCORM learning contents can be wildly distributed and enjoyed with the EPUB format and publications.

People like to attend exhibition activities, but hard to enter into the information effectively. We build new system with wireless internet and mobile device to guide visitor into the core information initiatively and effectively. The mobile guide system could classify visitor base on exhibition information and personal information that provide more suitable for users. Our system combined with semantic web technology to connect items data which users’ markup the type or property information in our system to created human portfolio. Our system is in compliance with human portfolio and metadata method to provide user information automatically and appropriately.

This paper deals with modal frequencies of rotating flexible beam. To investigate effects on the modal frequencies from rotation, the mathematical models are derived by using three descriptions on deformation: the conventional approach, the quadratic approach, and a synthetical approach. The theoretical solutions of modal frequencies based on the three methods are used to compare and draw some summaries.

Different piezoelectric harvester interface circuits are demonstrated and compared through SPICE simulation. The simulations of the effect of switch triggering offset and switch on time duration on SSHI’s power are performed. The inductor’s quality factors in synchronized switch harvesting on inductor interface have important effect on the harvested power. Parallel SSHI shows the optimal output voltage to harvest the maximum power varies according to the Q severely. It is concluded that switch triggering offset has more impact on the s-SSHI than p-SSHI and the switch on-time duration is more important in case of the p-SSHI. p-SSHI shows when the on-time duration becomes more than 1.3 times or less than 0.7 times of exact duration time, the harvested power gets negligible. s-SSHI reveals the characteristics that when less than 1.5 times exact on-time duration, the harvested power varies significantly with the on-time duration.

Typically, most of the agricultural works have to consider not only fixed data related with a cultivated crop, but also various environmental factors which are dynamically changed. Therefore, a farmer has to consider readjust the fixed data according to the environmental conditions in order to cultivate a crop in optimized growth environments. However, because the readjustment is delicate and complicated, it is difficult for user to by hand on a case by case. To solve the limitations, this paper introduces an approach for self-growing agricultural knowledge cloud in smart agriculture. The self-growing agricultural knowledge cloud can offer a user or a smart agricultural service system the optimized growth information customized for a specific crop with not only the knowledge and the experience of skillful agricultural experts, but also useful analysis data, and accumulated statistics. Therefore, by using the self-growing agricultural knowledge cloud, a user can easily cultivate any crop without a lot of the crop growth information and expert knowledge.

The paper presents the main specifications for a monitoring of metalworking fluids and cleaners for mass industries. The implementation of fluid outsourcing in these industries. There is presented method o flaboratory determination and diagnostic in industry of water-miscible fluids.

Die casting represents the highest technological level of metal mould casting. This technology enables production of almost all final products without necessity of further processing. The important aspect of efficiency and production is a proper casting parameters setting. In the submitted paper following die casting parameters are analyzed: casting machine plunger speed and increase pressure. The studied parameters most significantly affect a qualitative castings dimension and they influence the most a gained porosity level

f

as well as basic mechanical properties represented by tensile strength

R

m

and ductility

A

5

.

In this paper, we propose a ring array of active structured light image-based ranging sensors for a mobile robot. Since the ring array of ranging sensors can obtain omnidirectional distances to surrounding objects, it is useful for building a local distance map. By matching the local omnidirectional distance map with a given global object map, it is also possible to obtain the position and heading angle of a mobile robot in global coordinates. Experiments for omnidirectional distance measurement, matching, and localization were performed to verify the usefulness of the proposed ring array of active ranging sensors.

Composite-order bilinear pairing has been applied in many cryptographic constructions, such as identity based encryption, attribute based encryption, and leakage resilient cryptography. However, the computation of such pairing is relatively slow since the composite order should be at least 1024 bits. Thus the elliptic curve group order

n

and the base field are large. The efficiency of these pairings becomes the bottleneck of the schemes. Existing solutions, such as converting composite-order pairings to prime-order ones or computing many pairings in parallel cannot solve the problem. The former is only valid for certain constructions and the latter is only helpful when many pairings are needed. In this paper, we make use of the huge number of threads available on Graphics Processing Units (GPUs) to speed up composite-order computation, both between pairings and within a single pairing. The experimental result shows that our method can speed up paring computation. Our method can also be ported to other platforms such as cloud systems.

This paper introduces an agent application service and shows its application through the implementation of a multimedia data distribution service. This service is broadly comprised of agents, agent systems, an agent master and agent manager components. A software component of relaying multimedia date traffic is developed as an agent application, and is created dynamically with the distribution of the content client in the network. By using this service, it is possible to deploy a new multimedia data distribution with greater speed, efficiency and convenience.

This paper focuses on configuration design optimization of the assembly supply chain network. It is intended to use this approach to select an optimal assembly process structure in early stages of manufacturing/assembly process design. For the purpose of optimization, structural complexity measures as optimality criteria are considered. In order to compare alternatives in terms of their complexity, a method for creating comparable process structures is outlined. Subsequently, relevant comparable process structures are assessed to determine their structural complexity.

A ball-shaped mobile robot, called a ballbot, has a single point of contact with the ground. Thus, it has low energy consumption for motion because of the reduced friction. This paper presents the systematic kinematics modelling for a type of ballbot with omnidirectional motion capability. This kinematics modelling describes the velocity relationship between the driving motors and the robot body for the motion control of the robot.

Nowadays people connected to the Internet are using more than six mobile connected personal devices, such as smartphones, smart pads, and laptops. To provide a simple way to share multiple devices owned by themselves or by their family and friends without configuration, this research aims at building and managing social relationships of personal devices by using human relationships obtained by social networking services. This paper proposes the design of device sociality database on the basis of ER diagrams, which is a critical step to store and manage data and information required for zero-configured device interaction. The database design is made up of the resource specification of personal devices and device sociality including device ownership, human relationships, and access permission of device resources.

This paper presents the image processing algorithm for wireless charging between each mobile robot. The image processing algorithm converts Red Green Blue (RGB) format of inputted image to detect edge. It calculates a specific area using Hough Transformation (HT) in detected edge and judges correct charging antenna using Speeded-Up Robust Features (SURF). Accordingly, the image processing algorithm can control position and direction of mobile robot and antenna for wireless charging. The image processing algorithm is implemented wireless charging systems, which are set up on each two mobile robot and it is verified with experiment.

This paper presents a new configuration for in-vehicle networks to increase the reliability of the communication between electronic control units (ECU) and to improve the safety level of a vehicle. Basically, the CAN (Controller Area Network) protocol is assumed for the data communication in vehicles but more reliable communication can be guaranteed by adding the ZigBee communication function to each ECU. To show the validity and the performance of the presented network configuration for some network faults, the Electronic Stability Control (ESC) operation is analyzed by using an ECU-In-the-Loop Simulation (EILS). The experimental set-up for EILS of ESC system consists of two 32-bit microcontroller boards which can be communicated with the CAN or the ZigBee protocol. A 7-DOF (Degrees Of Freedom) vehicle model and ESC algorithm is implemented on each microcontroller. It is shown by the experimental results that ESC using the high reliability CAN system can achieve the same performance as using only CAN protocol without disconnected CAN bus.

With advent of satellite positioning system and availability of wireless communication network, it is possible for an end user to navigate even in the scarce location where there are fewer inhabitants. With affordable cost and vast coverage, millions of users can access location co-ordinates from any part of the world due to wireless positioning techniques. In this study, we highlight different positioning methods, location-based services and vast variety of applications benefited from these methods and services. This paper covers brief mathematical models used among all the wireless positioning systems along with their comparison. In today’s fast pace information era, location-based services are not only used for hotspot navigation but, also used for marketing strategy and so on. In addition, this article includes location-based services that access mobile network, and utilized the current location of the mobile device appropriately. Finally we classify the location-based solutions that have been used in variety of models such health services, marketing, tourism, entertainment and advertisement, and so forth. The study concludes that with evolution of technological advancement, wireless positioning system will be more improved and will be used in every part of our daily life in an effective manner.

In this paper, we design and analyze a digital retrodirective array antenna (RDA) system based on bandpass sampling for wireless communication. The proposed system has low power consumption thanks to increased signal to interference noise ratio (SINR) because digital RDA can automatically make beam toward source with no information about the direction of incoming signal. Also, this paper presents a robust communications system to frequency offset due to digital PLL. Digital PLL can automatically compensate for frequency offset which occurs because of different frequency between transceivers. Simulation results show that the proposed scheme has better BER performance about 5 dB than that of without phase conjugation when the array elements are three.

A low profile antenna, using coupled-fed, meandered, and folded Planar Inverted–F antenna (PIFA), is proposed to cover multi-band Wireless Wide Area Network (WWAN) operations. The proposed antenna, which is suitable for modern 4G mobile phones, requires only a small foot print of 44 × 20 mm

2

. The antenna covers band 14 of LTE-700, GSM-850, GSM-900, DCS-1800, PCS-1900, WCDMA-2100, and band 41 of LTE-2500. In addition to the common WWAN frequencies for mobile communication, the antenna also covers the IEEE802.11b band. The proposed antenna has three simple structures comprising a coupled-fed strip, a meandered shorted-patch, and a folded-patch. These elements are capacitively coupled to each other to form resonant regions in the low bands and the high bands. Modifications to the ground plane are added to achieve a good operation in LTE low band. In the scope of this paper, simulation results, using CST software, are presented to show the effectiveness of the proposed antenna.

In this paper, we propose two new signature schemes and a novel short signature scheme from two hard problems. The proposed schemes have two prominent advantages. Firstly, they are developed from some signature schemes where the security and efficiency have been proven. Therefore, they inherit these properties from the previous schemes. Secondly, the security of the proposed schemes is based on two hard problems. Therefore, they are still safe even when cryptanalysis has an effective algorithm to solve one of these problems, but not both. Moreover, we also propose a method for reducing signatures and this is the first attempt to reduce signatures based on two hard problems. Therefore, our proposed schemes are suitable for the applications requiring long-term security in resource limited systems.

Deterministic Adaptable Priority Net Access Delay, one of the channel access methods defined in MIL-STD-188-220 standard, is designed focusing on the reliable transmissions of the highest priority packets. Therefore, it degrades the performances of the low priority traffics. This paper proposes a method to improve the performances of the low priority traffics while maintaining the performances of the highest priority traffics. The method upgrades intentionally the priority of the traffics that stays in a queue for a certain time period, so that it gives an opportunity for even lower priority traffic to be transmitted. The proposed method is simulated and the results show it improves the network performances.

Satellite communication system does not use training sequence because the satellite communication channel is similar to the additive white gaussian noise (AWGN). But, in the mobile satellite communication environment, inter-symbol-interference (ISI) seriously occurs due to movement of receiver. We must use the blind equalization for remove the ISI in mobile satellite communication. Blind equalization techniques such as MCMA and SAG-MCMA is suitable for channel equalization in the mobile satellite environment. But equalization performance of blind equalizer were not as satisfactory as expected. In this paper, we propose a blind equalization technique based on coordinate change and beamforming method in order to improve the BER performance of receiver in mobile satellite communication. The simulation results show that the proposed scheme with coordinate change need to less SNR about 1 dB to satisfy BER performance (10-5).

In order to meet the growing demand of large-scale wind power farms (WPF), integration of high reliability, high speed, cost effectiveness and secure communication networks are needed. This paper proposes the Ethernet passive optical network (EPON) as one of promising candidates for next generation WPF. Critical communication network characteristics such as reliability, mean downtime, optical power budget, path loss and network cost are evaluated and compared with conventional switched-based architectures. The results show that our proposed EPON-based network architectures are superior to conventional switched-based architectures.

The conventional Interleave Division Multiple Access (IDMA) employs interleavers to separate users, while the conventional Code Division Multiple Access (CDMA) uses user specific spreading sequences for user separation. In this paper, we propose a User-Data Division Multiple Access (UDMA) scheme that employs user data as the spreading sequence for user separation with chip-by-chip iterative multiuser detection strategy. As such, this spreading sequence is not only as random as user data and independent of current symbols, but also dynamically changes from one symbol to another according to the user data. Therefore, this spreading sequence makes unwanted detection of the data by unintended receivers practically impossible. Also, in UDMA, identical interleavers are used and thus do not require to store all interleaving patterns. The simulation results show that the proposed scheme is superior to the bit error rate (BER) performance of the system in flat fading channel.

For the high end-to-end channel capacity, the amplify-and-forward (AF) scheme multiple-hop MIMO relays system is considered. The distance between each transceiver and the transmit power of each relay node are optimized to prevent some relays from being the bottleneck and guarantee the high end-to-end channel capacity. However, when the system has no control on Mac layer, the interference signal should be taken in account and then the performance of system is deteriorated. Therefore, the specific access control on MAC layer is proposed to obtain the higher end-to-end channel capacity. The optimum number of relays for the highest channel capacity is obtained for each access method. However, there is the trade-off of channel capacity and delay time.

In this paper, a single-feed wideband circularly polarized antenna has been proposed for UHF RFID reader. This antenna is designed to cover the frequency range from 860 to 960 MHz. In this antenna, the main patch is a modified form of the conventional E-shaped patch to obtain a circular polarization. A parasite patch is placed at the same layer of main patch to enhance axial ratio bandwidth. A short-circuited cylinder is also added in main patch to broaden the impedance bandwidth. The 3 dB axial ratio bandwidth is over 11 %, from 850 to 960 MHz. The impedance bandwidth is of 17 % (850–1000 MHz). Thus, The impedance bandwidth and 3 dB axial ratio bandwidth totally covers the universal UHF RFID band (860–960 MHz). The simulated and measured results indicate that the proposed antenna will be a good candidate for UHF RFID reader system.

Wireless communication systems have become important in daily life such as wireless body area network (WBAN). An ultra-wideband (UWB) technology is chosen to be used for short-range communication scenarios, low-power and high data rate technology which accommodates appropriate technology in WBAN. In this paper, we design a printed circular monopole with coplanar waveguide (CPW) fed for WBAN with common frequency band following FCC common band (7.25–8.5 GHz). The antenna structure is simple, using FR4 circuit board (PCB) with overall size of 18 × 20 × 1.6 mm

3

. The simulation and experiment results show that the proposed antenna achieves good impedance matching and stable radiation patterns over operating bandwidth of 6.8–12.34 GHz. Moreover, the authors evaluate UWB antenna in two scenarios are free-space and with human-body to consider the antenna performance in time domain.

An ultra wideband impulse radio (UWB-IR) are developing to use in communication system and medical application because it has been an increase interest in using on body for health monitoring and body area networks (BAN). This research want to improving UWB channel propagation on body by using CLEAN algorithm for eliminate noise in channel propagation. In addition to, we use result from previous work for easier to compare performance before system. Moreover, in this paper us analysis performance of system when using CLEAN algorithm and compare without use CLEAN Algorithm by us will show BER in each position on body for analysis performance of CLEAN algorithm can be reduce noise or effect on body when without CLEAN Algorithm.

In last couple of years many research have been done to develop the technology for minimizing the energy consumption, security and maintaining a comfortable living environment in smart buildings. In this paper, we propose comparison simulator to analyze algorithms such as averaging method, moving averaging, Low-pass filter, Kalman filter and Gray model for predicting energy consumption in indoor space. Additionally, we evaluate energy prediction algorithms in order to facilitate the testing. Our propose comparison simulator support to verify the performance of the prediction algorithms and effective estimation of energy usage in indoor environment.

In recent years, flooding in Ho Chi Minh city, Vietnam has become more and more serious, it affects much the lives and economics of the citizens. There are some reasons which caused this situation; among them the unfavorable natural conditions like rainfall, tide, are the crucial one. It is the reason why to build an intelligent network which is suitable for data collection precisely, rapidly and timely for water environment monitoring is essential. While traditional networks spend much money and effort to ensure continuous information in specific regions, Wireless Sensor Network is best known its advantages such as low cost, reliable and accurate over long term and required no real maintenance. Our contribution is that to build a network topology with suitable hardware and Low Energy Adaptive Clustering Hierarchy (LEACH) routing protocol in order to reduce energy consumption of whole network and prolong network life time. Fact has shown that LEACH protocol achieves a factor of 8–15 % energy improvement compared to direct transmissions.

Wireless sensor network has been evolving to wireless sensor actuator networks (WSAN), which is supposed to provide more dynamic services based on events from sensor nodes. WSANs require event reliability to support more accurate services. The optimum number of event notification messages from sensor nodes is the prerequisite for the further service reliability in WSANs. In this paper, we provide the analysis about how the number of event notification affects the energy consumption of actuator node in wireless sensor actuator networks.

Based on work in wireless ad hoc network for Marine Search and Rescue Sys-tem (MSnR) system, this paper presents an improving GPS-based wireless ad hoc network capable of providing location and emergency service to small fishing boats by improving the weak sea-to-land wireless radio link from small fishing boats to the central in-land stations. The proposed approach provides continuous report and monitoring of all boats and its locations for searching and rescuing process during emergencies. The message priority assignment allows the system to operate more efficient and reliable when one or several boats boat in distress. System model, communication mechanism and network simulation results are presented.

In this paper, we propose two relay selection algorithms based on the signal-to-noise ratio (SNR) and the eigenvalue which achieve improved bit error rate (BER) performance compared with the previous one based on the mean square error (MSE) at the same complexity order.

Recently, Guo et al. proposed an efficient and non-interactive hierarchical key agreement protocol applicable to mobile ad-hoc networks, which is a try to solve the open question: How can secrets be established if an adversary can eavesdrop on every message exchange? However, their protocol does not support freshness of the established session key that key agreement protocols should have. Thereby, we propose a freshness preserving hierarchical key agreement protocol over the hierarchical MANETs. Compared with other existing protocols, the proposed protocol offers much better performance on the bandwidth consumption, the computational cost, and the storage cost.

Widespread adoption of Radio Frequency Identification System (RFID) has been widely used to develop and improve the Supply chain management. The Logistic control system has been focused in this work. In details, the system emphasizes at packaging, inventory and warehouse utilization that actually holds a good impact to final packing process and shipping process. The RFID hardware’s specification are UHF frequency at 860–930 MHz on ISO/IEC 18000-6C Class 1 Gen 2 which well known to utilize in supply chain management. Data stored in the tag are the compressed version of all pieces inside the box. No indexing is further needed as required by the conventional barcode system. For the analysis of business deployment, an economic analysis tool is employed. The Net Present Value (NPV) of 5 year-period has been carried out for the purpose of medium-term to long-term investment.

Nowadays, real time video becomes popular in a lot of multimedia equipment, video cameras, tablets, camcorders. The more hardware improved the more application is used. Requesting a faster and cost-effective systems there are triggers a shift to Field Programmable Gate Arrays (FPGAs), where the inherent parallelism results in better performance. The implementation is based on efficient utilization of embedded multipliers and look up table (LUT) of target device to improve speed but also saves the general purpose resources of the target device. This paper proposes new hardware architecture for capture NTSC/PAL video stream. The whole system is implemented on a single low cost FPAG chip, capable of real time procession at frequency 60 MHz. In addition, to increase real-time performance, hardware architecture with streamlined data flow are developed.

Iterative hard thresholding (IHT) algorithm is one of the representative compressive sensing (CS) reconstruction algorithms. For applying to images, however, it has a problem of lacking in addressing human visual system (HVS) characteristics—its hard thresholding process treats all of coefficients in transform domain equally. To overcome the problem, this paper addresses an adaptive hard thresholding method accounting for the HVS characteristics. For this purpose, a suitable threshold level is adaptively selected for each coefficient in transform domain by utilizing the standard weighting matrix table used in JPEG together with the threshold value which is estimated over the noisy version of image. Experimental results show that the performance of the block compressive sensing with smooth projected Landweber (BCS-SPL) with the proposed adaptive hard thresholding algorithm remarkably outperforms that of the conventional BCS-SPL algorithm.

This paper deals with a fundamental problem for 3D model acquisition after camera calibration [

1

]. We present an approach to estimate a robust fundamental matrix for camera calibration [

2

,

3

]. Single axis motion can be described in terms of its fixed entities, those geometric objects in space or in the image that remain invariant throughout the sequence. In particular, corresponding epipolar lines between two images intersect at the image of the rotation axis. This constraint is then used to remove the outliers and provides new algorithms for the computing the fundamental matrix. In the simulation results, our method can be used to compute the fundamental matrix for camera calibration more efficiently.

Recently, research into computer, vision-based methods to recognize gestures are widely conducted as means to communicate the volition of humans to a computer. The most important problem of gesture recognition is a reduction in the simplification treatment time for algorithms by means of real-time treatment. In order to resolve this problem, this research applies mathematical morphology, which is based on geometric set theory. The orientations for the primitive shape elements of hand signal shapes acquired from the application of morphological shape analysis include important information on hand signals. Utilizing such a characteristic, this research is aimed at suggesting a feature vector-based, morphological gesture recognition algorithm from a straight line which connects central dots of major primitive shape elements and minor primitive shape elements. It will also demonstrate the usefulness of the algorithm by means of experimentation.

This paper presents a novel paradigm of a global localization method motivated. The proposed localization paradigm consists of three parts: panoramic image acquisition, multiple object recognition, and grid-based localization. Multiple object recognition information from panoramic images is utilized in the localization part. High level object information is useful not only for global localization but also robot-object interaction. The metric global localization (position, viewing direction) is conducted based on the bearing information of recognized objects from just one panoramic image. The experimental results validate the feasibility of the novel localization paradigm.

Gender classification is one of the challenging problems in computer vision. Many interactive applications need to exactly recognize human genders. In this paper, we are carrying out some experiments to classify the human gender in conditions of low captured video resolution. We use Local Binary Pattern, Gray Level Co-occurrence Matrix to extract the features from faces and Gait Energy Motion, Gait Energy Image for gaits. We propose to combine face and gait features with the combination classifier to enhance gender classification performance.

Traditionally, sub-pixel interpolation in stereo-vision systems has been used for the block-matching algorithm. In this paper, Census transform algorithm which has been on area-based matching algorithm is improved and it’s compared with existing census transform algorithm. Two algorithms are compared using Tsukuba stereo images provided by Middlebury web site. As a result, disparity map error rate is decreased from 16.3 to 11.8 %.

Compressed sensing has been widely researched since the beginning of 2000s. Although there are several well-known signal recovery algorithms, its reconstruction noise cannot be avoided completely, thus requiring good filters to remove the noise in the reconstructing process. Since each different filter has its own advantages and disadvantages depending on specific reconstruction algorithm, the reconstruction performance can be varied according to the choice of filter. This paper proposes an inner filter selection method according to the sampling rate and the property of image to be sensed.

This paper presents extended local binary patterns (LBP) for facial expression analysis from 3D depth map images. Recognition of facial expressions is important to understand human emotion and develop affective human computer interaction. LBP and its extensions are frequently used for texture classification and face identification and detection. In the 3D surface analysis, curvature is very important characteristics. This paper presents an extension of LBP for modeling curvature from 3D depth map images. The extended curvature LBP (CLBP) is used for facial expression recognition. Experimental results using Bosphorus facial expression database show better performance by 3D curvature and the combination of 3D curvature and 2D images than by conventional 2D or 2D + 3D approaches.

The paper focuses on brief presenting again the 3D, 4D GIS data models that have been proposed in the past. The paper uses the tables to compare models based on various criteria in the applications of 3D, 4D GIS. In 3D data models, there were some special models because they can represent the spatial objects by multiple levels of detail. The paper also compares the differences of these models in tables. These tables are the foundation for the developers to build the GIS applications.

In this paper, we describe an approach of modeling and simulation based on multi-agent theory to build the model of traffic system. Our model presents a traffic system including traffic light system at a ‘+’ junction. This paper controls duration of red-light/green-light to release traffic congestion on roads. In addition, we establish six Vietnamese traffic rules in our model. The simulation model represents real traffic system in GAMA platform with GAML language. All systems are visualization in GUI to show the participant of vehicles and traffic light on roads.

The point kinetic equations in nuclear dynamics, various analytical methods have been used. In this paper, a numerical approach of point kinetic equations using an inherently large sampling interval and multiple inputs is developed and analyzed. To implement this method, Taylor-Lie Series under the Zero Order Hold (ZOH) is used to approximate the neutron density and precursor concentrations at each corresponding time step. Afterwards, an additional technique, the Adomian Decomposition Method, is used based on its merit of algorithmic and computational advantages in carrying out the discretization.

To protect the members of the vehicular networks from malicious users and malfunctioning equipments, certificate revocation list (CRL) should be distributed as quickly and efficiently as possible without over-burdening the network. The common theme among existing methods in the literature to reduce distribution time is to reduce the size of the CRL, since smaller files can be distributed more quickly. Our proposal has been concerned with the problem of how to reduce the size of CRL effectively. We propose a regional CRL distribution method that introduces partitioned CRLs corresponding to certificate authority (CA) administrative regions. A regional CRL includes only neighbouring vehicle’s revoked certificates and distributed to vehicles within one CA region. Consequently, since there is no need to process full CRLs by all vehicles, the method can reduce computational overhead, long authentication delay, message signature and verification delay, and processing complexity imposed by full CRL distribution methods.

A traffic signal control mechanism is proposed to improve the dynamic response performance of a traffic flow control system in an urban area. The necessary sensor networks are installed in the roads and on the roadside upon which reinforcement learning is adopted as the core algorithm for this mechanism. A traffic policy can be planned online according to the updated situations on the roads based on all the information from the vehicles and the roads. The optimum intersection signals can be learned automatically online. An intersection control system is studied as an example of the mechanism using Q-learning based algorithm and simulation results showed that the proposed mechanism can improve traffic efficiently more than a traditional signaling system.

AUTOSAR (Automotive Open System Architecture) is a de factor standard for automotive software development. It addresses crucial topics such as software architecture, application interfaces and development methodology, thereby providing a basic infrastructure for software development. However, the current AUTOSAR standard is too complex to learn and has significant dependence upon tool chains. As a result, it is very difficult to implement custom functionality in BSW (Basic Software) without special support from tool vendors. In this paper, we present how custom functionality can be implemented within AUTOSAR BSW obviating the need for tool vendor’s support. We first examine the internal structure and function of AUTOSAR software stack with an emphasis on the interfaces and execution of BSW modules. We then describe how a new BSW functionality can be incorporated into AUTOSAR BSW. Our approach is illustrated through a simple BSW module implementation with EB tresos AutoCore and Infineon TriCore TC1797.

This paper presents a hybrid adaptive neuro-fuzzy algorithm in application of battery management system. The proposed system employed the Cuk converter as equalizing circuit, and utilized a hybrid adaptive neuro-fuzzy as control method for the equalizing current. The proposed system has ability for tracking dynamic reactions on battery packs, due to taking advantages of adaptability and learning ability of adaptive neuro-fuzzy algorithm. The current output generated from learning process drives Pulse-Width-Modulation (PWM) signals. This current output is observed and collected for next coming learning process. The feedback line is provided for current output observation. The results demonstrate the proposed scheme has the ability to learn previous stages. Therefore, the proposed system has adaptability to deal with changing of working conditions.

It is very important to understand the brain’s biological cognition data processing mechanism for human cognitive ability and concentration enhancement. Based on biological data processing area and information flow, concentration indicators were defined to interpret the brain data processing mechanism in concentration by engineering, and cognitive concentration model based on this was proposed. The cognitive concentration model is the change of concentration patterns shown by EEG signal. The value of cognitive concentration model was verified with the EEG signals acquired from Subjects solving mathematical questions with different difficulties.

As for studies on autonomic nerve reactions, many researchers have published study results for long time, but in the standpoint of reproducibility and usefulness, no satisfactory outcomes have been obtained so far. As a new way to measure the change in autonomic nerve system, the method of using pulse signal the oriental medicine diagnosis measure is proposed. Specifically the autonomic nerve reaction measuring device to verify the usefulness of the proposed method is designed directly, and new method to process the measured pulse signals is proposed.

In this paper, we developed the semiconductor monitoring system for the etching process. Process monitoring techniques has an important role to give an equivalent quality and productivity to produce semiconductor. The proposed monitoring system is mainly focused on the dry etching process using plasma and it provides the detailed observation, analysis and feedback to managers.

Fault diagnosis and fault tolerant control are increasingly importance in robotic systems. A number of researchers have proposed the generalized observer scheme for fault isolation when a fault happened. One of the key issues in this scheme is based on the sensitive of the residual with the corresponding adaptive threshold. In this paper, we present a new method to derive the adaptive threshold in order to enhance the robustness of fault isolation estimator and reduce the fault isolation time. Mathematical proof and computer simulation are performed to show the effectiveness of the proposed method.

Cyber-physical systems demand higher levels of reliability for several reasons. First, unlike traditional computer-based systems, cyber-physical systems are more vulnerable to various faults since they operate under harsh working conditions. For instance, sensors and actuator may not always obey their specification due to wear-out or radiation. Second, even a minor fault in cyber-physical systems may lead to serious consequences since they operate under minimal supervision of human operators. In this paper we propose a software framework of fault detection and recovery for cyber-physical systems, called Fault Detection and Recovery for CPS (FDR-CPS). FDR-CPS focuses on specific types of faults related to sensors and actuators, which seem to be the likely cause of critical system failures such as system hangs and crashes. We divide such critical failures into four classes and then present the design and implementation of FDR-CPS that can successfully handle the four classes of critical failures. We also describe a case study with quadrotor to demonstrate how FDR-CPS can be applied in a real world application.

We propose a parallelization method for SAO, in-loop filter of HEVC. SAO filtering proceeds along CTB lines and there exists data dependency between inside and outside of CTB boundaries. Data dependency makes data-level parallelization hard. In this paper, we equally divided an entire frame into sub regions. With a little amount of memory, proposed method shows 1.9 times of performance enhancement in terms of processing time.

Recently, applying the novel data mining techniques for anomaly detection-an element in Intrusion Detection System has received much research alternation. Support Vector Machine (SVM) and Back Propagation Neural (BPN) network has been applied successfully in many areas with excellent generalization results, such as rule extraction, classification and evaluation. In this paper, we use an approach that is entropy based analysis method to characterize some common types of attack like scanning attack. A model based on SVM with Gaussian RBF kernel is also proposed here for building anomaly detection system. BPN network is considered one of the simplest and most general methods used for supervised training of multilayered neural network. The comparative results show that with attack scenarios that we create and through the differences between the performance measures, we found that SVM gives higher precision and lower error rate than BPN method.

Intrusion Detection by automated means is gaining widespread interest due to the serious impact of Intrusions on computer system or network. Several techniques have been introduced in an effort to minimize up to some extent the risk associated with Intrusion attack. In this paper, we have used two novel Machine Learning techniques including Multinomial Logistic Regression and Naïve Bayesian in building Anomaly-based Intrusion Detection System (IDS). Also, we create our own dataset based on four attack scenarios including TCP flood, ICMP flood, UDP flood and Scan port. Then, we will test the system’s ability of detecting anomaly-based intrusion activities using these two methods. Furthermore we will make the comparison of classification performance between the Multinomial Logistic Regression and Naïve Bayesian.

Among the variety of vehicle technology trend issues, the biggest one is focus on automotive network system. Especially, optical network system is mentioned. The outstanding point in optical network system for vehicular environment is that realization of automotive media platform. This paper is introduced the implementation of media platform which is consist of optical network as called Media Oriented System Transport (MOST) and engraftment of vehicle data processing module collected from On-Board Diagnosis (OBD) via Controller Area Network (CAN) transformed into Extensible Marked Language (XML) schema structure. Also, for the reliability of the development, it is executed the MOST compliance test of designed platform.

In this paper, a receiver and an analyzer system of Digital Video Broadcasting_2nd Generation Terrestrial (DVB-T2) were designed using Digital Video Broadcasting_2nd Generation Satellite (DVB-S2), and Digital Video Broadcasting_2nd Generation Cable (DVB-C2). This software-based receiver and analyzer system were implemented by memory sharing techniques for minimization of system overloads.

This paper proposes a TV viewer age-group classification method for family members based on TV watching history. User profiling based on watching history is very complex and difficult to achieve. To overcome these difficulties, we propose a probabilistic approach that models TV watching history with a Gaussian mixture model (GMM) and implements a feature-selection method that identifies useful features for classifying the appropriate age-group class. Then, to improve the accuracy of age-group classification, a multi-layered Bayesian classifier is applied for demographic analysis. Extensive experiments showed that our multi-layered classifier with GMM is valid. The accuracy of classification was improved when certain features were singled out and demographic properties were applied.

Supporting floating point operations on coarse-grained reconfigruable architecture (CGRA) becomes essential as the increase of demands on various floating point inclusive applications such as multimedia processing, 3D graphics, augmented reality, or object recognition. However, efficient support for floating point operations on CGRA has not been sufficiently studied yet. This paper proposes a novel technique to enhance utilization of integer units for high-throughput floating point operations on CGRA with experimental results.

Multipath is one of main error sources in code tracking in global navigation satellite system. One of the first approaches to mitigate multipath is called Double Delta Correlator (DDC). This technique originally applied to Global Positioning System signals (C/A signals) which are Binary Phase ShiftKeying ones and have a single–peak autocorrelation function. Latter, it also applied to new GNSS signals which are binary offset carrier (BOC) modulated ones. It shows a good code multipath performance for mid-delayed and long-delayed multipath in both cases. For short-delayed multipath, there is still remaining error. This paper presents an Improved DDC that could reduce the error for short-delayed multipath signals. This improved DDC method is proposed for BOC signals. The simulation results show a better performance of proposed method than conventional DDC.

The global action began to resolve the problem of global warming. Thus, the wind power has been emerged as an alternative energy of existing fossil fuel energy. The existing wind power has limitation of location requirements and noise problems. In case of Korea, the existing wind power has difficulties on limitation of location requirements and the noise problems. The wind power turbine requires bigger capacity to ensure affordability in the market. Therefore, expansion into sea is necessary. But due to the constrained access environment by locating sea, the additional costs are occurred by secondary damage. In this paper, we suggest automatic fault diagnosis system based on CMS (Condition Monitoring System) using neural network and wavelet transform to ensure reliability. In this experiment, the stator current of induction motor was used as the input signal. Because there was constraint about signal analysis of large wind turbine. And failure of the wind turbine is determined through signal analysis based wavelet transform. Also, we propose improved automatic monitoring system through neural network of classified normal and error signal.

Direction-of-arrival estimates are required in many applications such as automatic video camera steering and multiparty teleconferencing for beam forming and steering to suppress noise and reverberation and improve speech intelligibility. Ambient noise and multiple reflections of the acoustic source signal significantly degrade the performance of time-difference-of-arrival (TDOA) methods to localize the sound source using only two microphones. In this work, we investigate the performance of a multichannel cross-correlation coefficient (MCCC) algorithm for the estimation of the direction-of-arrival (DOA) of an acoustic source in the presence of significant levels of both noise and reverberation. Simulations and initial experimental results confirm that the DOA estimation robustness and complexity is suitable for a practical micro-phone array using miniature MEMS microphones and an FPGA implementation of the MCCC algorithm.

This paper presents the design of a System on Programmable Chip (SoPC) based on Field Programmable Gate Array (FPGA) for speech recognition in which Mel-Frequency Cepstral Coefficients (MFCC) for speech feature extraction and Vector Quantization (VQ) for recognition are used. The execution speed of the blocks in the speech recognition system is surveyed by calculating the number of clock cycles while executing each block.