Abstract: In this paper, we propose an energy-aware routing protocol for wireless sensor networks. Our design is based on the ladder diffusion algorithm and cat swarm optimization algorithm. With the properties of ladder diffusion algorithm, our protocol can avoid the generation of circle routes and provide the backup routes. Besides, integrating cat swarm optimization can effectively provide better efficiency than previous works. Experimental results demonstrate that our design reduces the execution time for finding the routing path by 57.88 % compared with a very recent research named LD.

Abstract: Recently, Social Network Service (SNS) users are rapidly increasing, and Social Network Analysis (SNA) methods are used to analyze the structure of user relationship or messages in many fields. However, the SNA methods based on the shortest distance among nodes is time-consuming in measuring computation time. In order to solve this problem, we present a heuristic method for the shortest path search using SNS user graphs. Our proposed method consists of three steps. First, it sets a start node and a goal node in the Social Network (SN), which is represented by trees. Second, the goal node sets a temporary node starting from a skewed tree, if there is a goal node on a leaf node of the skewed tree. Finally, the betweenness and closeness centralities are computed with the heuristic shortest path search. For verification of the proposed method, we demonstrate an experimental analysis of betweenness centrality and closeness centrality, with 164,910 real data in an SNS. In the experimental results, the method shows that the computation time of betweenness centrality and closeness centrality is faster than the traditional method. This heuristic method can be used to analyze social phenomena and trends in many fields.

Abstract: In order to solve some problems associated with network security situation forecast, this study proposed a new forecast method based on fuzzy Markov chain. In this work, we focus on forecasting the threat value of network combines historical data of safe behavior with the level of threat. We establish unified information database based on multi-source log data mining techniques. By using text categorization and the threat level division, it is capable of calculating the threat value of a period of time. Due to the discrete nature of the threat values of each time and its unfollow-up effect property, considering the fuzziness of safety state, we use fuzzy Markov chain to predict the threat value in next period of time.

Abstract: Recently, cyber-physical systems (CPS) have emerged as a promising direction to enrich the interactions between physical and virtual worlds. Because of the large-scale features of CPS, mobile agents (MA) technology can promote the performance of CPS. In this article, we first introduce the concept and characteristics of CPS, MA, and intelligent transportation system (ITS). Then, we propose the structure of intelligent transportation CPS (ITCPS). On this basis, giving the case of mobile agents for ITCPS, we exploit a mobile agent by three levels (node level, task level, and combined task level) to reduce the information redundancy and communication overhead. Finally, we in brief outline the technical challenges for ITCPS.

Abstract: In recent years, with the rapid development of information technology, educational technologies have been used successfully in enriching learning content and improve learning efficiency. This study attempts to develop an assisted learning system for increasing students’ motivation by creating flexible learning path. The purpose of the designed system is to bridging the gap between formal and informal learning on natural science subject. Augmented reality and indoor positioning technologies have been implemented in the system to guide learners to construct their knowledge in the informal learning environment, National Museum of Natural Science. Learners can not only receive virtual information left by other learners in such space, but also leave their own learning experience and share with others. Additionally, the system also analyzes individualized learning subject. By doing so, other learners who have the same interests could find an efficient way to learn.

Abstract: For portable communication systems, the delegation-based authentication protocol provides efficient subsequent login authentication, data confidentiality, User privacy protection, and non-repudiation. However, in all proposed protocols, the non-repudiation of mobile users is based on an impractical assumption that home location registers are trusted. To reduce the HLR’s trust assumption and enhance the non-repudiation of the mobile users, our new delegation-based authentication protocol is proposed. Our protocol also removes the exhaustive search problem in the subsequent login authentication to improve the subsequent login authentication performance. Moreover, the user unlinkability in the subsequent login authentication is also provided in our protocol to enhance the user identity privacy.

Abstract: High speed image processing is becoming increasingly important in medical imaging. Using the state-of-the-art ZYNQ-7000 system on chip (SoC) has made it possible to design powerful vision systems running software on an ARM processor and accelerating it from hardware resources on a single chip. In this paper, we take the advantage of accelerating an embedded system design on a single SoC, which offers the required features for real-time processing of skin cancer images. Different edge detection approaches such as Sobel, Kirsch, Canny and LoG have been implemented on ZYNQ-7000 for border detection of skin lesions, which can be used in early diagnosis of melanoma. The results show that the extended 5 × 5 canny edge detection implemented on the proposed embedded platform has better performance in compare with other reported methods. The performance evaluation of this approach has shown good processing time of 60 fps for real time applications.

Abstract: This paper presents an interactive web-based anatomy navigation system based on the high-resolution Chinese Visible Human (CVH) dataset Compared with previous anatomy learning software, there are three new features in our navigation system First, we directly exploit the capabilities of graphics hardware to achieve real-time computation of large medical dataset on the web In addition, various visualization effects are supplied to enhance the visual perception of human model Second, to facilitate user interaction, we design a set of user-friendly interface by incorporating the Microsoft Kinect into the system, and the users can navigate the Visible Human with their hand gestures Third, in order to eliminate the unreliable bottleneck: network transmission, we employ a progressive strategy to transmit the data between the server and the client Experimental results validate the advantages of the proposed navigation system for learning human anatomy, indicating its great potential in clinical applications

Abstract: The aim of this study is to protect an electronic mail (email) server system based on an integrated Entropy calculation via detecting flooding attacks. Lots of approaches have been proposed by many researchers to detect packets accessing email whether are belonging to the normal or abnormal packets. Entropy is an approach of the mathematical theory of Communication; it can be used to measure the uncertainty or randomness in a random variable. A normal email server usually supports the four protocols consists of Simple Mail Transfer Protocol (SMTP), Post Office Protocol version 3 (POP3), Internet Message Access Protocol version 4 (IMAP4), and HTTPS being used by remote web-based email. However, in Internet, there are many flooding attacks will try to paralyze email server system. Therefore, we propose a new approach for detecting flooding attack based on Integrated Entropy Measurement in email server. Our approach can reduce the misjudge rate compared to conventional approaches.

Abstract: As the network communications technology developing, a new type of networks has appeared in the daily life which is named underwater sensor networks (UWSNs). Routing protocols in UWSNs should ensure the reliability of message transmission, not just decrease the delay. In this paper, we propose a novel routing protocol named Location-Aware Routing Protocol (LARP) for UWSNs, where the location information of nodes are used to help the transmission of the message. Simulation results show that the proposed LARP outperforms the existing routing protocols in terms of packet delivery ratio and normalized routing overhead.

Abstract: Studies on the measurement of happiness have been utilized in a variety of areas; in particular, it has played an important role in the measurement of society stability. As the number of users of Social Network Services (SNSs) increase, efforts are being made to measure human well-being by analyzing user messages in SNSs. Most previous works mainly counted positive and negative words; they did not consider the grammar and emotion. In this paper, we reorganize the mechanism to harness the advantages of (a) Part-Of-Speech (POS) tagging for grammatical analysis, and (b) the SentiWordNet lexicon for the assignment of sentiment scores for emotion degree. We suggest a modified formula for calculating the Gross National Happiness (GNH). To verify the method, we gather a real-world dataset from 405,700 Twitter users, measure the GNH, and compare it with the Gallup well-being release. We demonstrate that the method has more precise computation ability for GNH.

Abstract: The intra-body communication uses the human body as a conducting wire, providing the simplicity and the security. Although the communication distance is limited within a body-area, it is useful on the construction of personal area network. In this paper, we introduce our prototype intra-body communication module using the FPGA. The proposed system has the FSK modulator and the demodulator. These modulation methods are chosen after body-channel analysis. The experimental results demonstrate the feasibility of our intra-body communication module for establishing the PAN (Personal Area Network).

Abstract: Recently, more and more wireless networks have been deployed and start provide varies services to customers. Such as smart-phones integrate heterogeneous wireless devices, it may cause unintended interactions between multiple radios using difference radio access technologies. Thus, heterogeneous wireless network will be the trend of future network. The Co-channel interference problem in heterogeneous wireless networks is more and more important. This paper focus on the coexistence problem between IEEE 802.11b/g/n and IEEE 802.15.4 protocols in the ISM 2.4 GHz band. The performance impact on IEEE 802.15.4 network under IEEE 802.11 wireless network has been analysis, and results show that IEEE 802.15.4 has serious collision problem if there has no appropriate scheduling mechanisms among two wireless protocols. A CIFS (Coexistence Inter-Frame Space) has been proposed in this paper to effectively enhance the IEEE 802.15.4 transmission probability which is implemented in IEEE 802.11 nodes to observe the transmission opportunity for IEEE 802.15.4 under wireless coexistence environment.

Abstract: In this paper, we propose a glove based equipment (mrGlove) for a user interface that controls a device through hand motion recognition. The mrGlove provides more user experience compared to conventional devices such as a keyboard and a touchscreen. Our mrGlove is able to control a heterogeneous device (Windows or Android) that offers more convenience and user experience. Experimental results prove the feasibility of our proposal for enhancing convenience and user experience by obtaining control of an object through motion recognition in the PC and the smartphone.

Abstract: With the rapid growth of user-created contents and wide use of community-based websites, content recommendation systems have attracted the attention of users. However, most recommendation systems have limitations in properly reflecting each user’s characteristics, and difficulty in recommending appropriate contents to users. Therefore, we propose a content recommendation method using Friend-Of-A-Friend (FOAF) and Social Network Analysis (SNA). First, we extract user tags and characteristics using FOAF, and generate graphs with the collected data, with the method. Next, we extract common characteristics from the contents, and hot tags using SNA, and recommend the appropriate contents for users. For verification of the method, we analyzed an experimental social network with the method. From the experiments, we verified that the more users that are added into the social network, the higher the quality of recommendation increases, with comparison to an item-based method. Additionally, we can provide users with more relevant recommendation of contents.

Abstract: In the past, an incremental algorithm for mining high utility itemsets was proposed to derive high utility itemsets in an incrementally inserted way. In real-world applications, transactions are not only inserted into but also deleted from a database. In this paper, a maintenance algorithm is thus proposed for reducing the execution time of maintaining high utility itemsets due to transaction deletion. Experimental results also show that the proposed maintenance algorithm runs much faster than the batch approach.

Abstract: Community analysis of social networks is a widely used technique in many fields. There have been many studies on community detection where the detected communities are attached to a single topic. However, an overall topical analysis for a community is required since community members are often concerned with multiple topics. In this paper, we propose a semantic method to analyze the topical community “fingerprint” in a social network. We represent the social network data as an ontology, and integrate with two other ontologies, creating a Social Semantic Network (SSN) context. Then, we take advantage of previous topological algorithms to detect the communities and retrieve the topical “fingerprint” using SPARQL. We extract about 210,000 Twitter profiles, detect the communities, and demonstrate the topical “fingerprint”. It shows human-friendly as well as machine-readable results, which can benefit us when retrieving and analyzing communities according to their interest degrees in various domains.

Abstract: MapReduce is a kind of distributed computing system, and also many people use it nowadays. In this paper, the Green Master based on MapReduce is proposed to solve the problem between load balance and power saving. There are three mechanism proposed by this paper to improve the MapReduce system efficiency. First, a brand new architecture called Green Master is designed in the system. Second, Benchmark Score is added to each services in the cluster. In the last, an algorithm about how to distinguish the high score service and the low score service, and how to use them effectively.

Abstract: To predict the tendency of Micro-blog information dissemination, provide the early warning of the Internet emergencies, and contribute to the content security of micro-blog, the paper offers a platform for Micro-blog information perceiving and mining. This platform is an integration of Micro-blog data collection and processing module, topic detection and tracking module, user behavior analysis module, trend prediction module, etc. It could access and analyze micro-blog information automatically, leading a positive significance to grasp the emergencies on micro-blog. This paper puts forward methods based on the Latent Dirichlet Allocation (LDA) document clustering and hot topics prediction, which could analysis and predict the micro-blog data effectively, avoiding the problems in the traditional algorithm. Also, these methods have a higher accuracy for clustering and prediction.

Abstract: The software radio has the advantages of flexibility, low cost and multimode ability, but the major disadvantage is the slower speed. To increase the speed of PC-based software DVB-T receiver, we need implement the baseband signal processing algorithms much faster. In this thesis, we discuss faster implementation of (1) 16QAM de-mapper to bits, (2) expanding_channel coefficient value in Viterbi decoder, and (3) inner de-interleaver and depuncturer. The speed of these three blocks is 6.64x, 0.57x and 0.88x faster.

Abstract: Situation-aware service is recognized as an emerging research issue in ubiquitous computing. It becomes more important and significant with the recent progress in IoT (Internet of Things), since the situations considered in IoT are more complex, become global, and cause more conflict. In this paper, a middleware for management conflict situations was designed, to prompt the development of context-aware services. It is characterized by its ability of situation-oriented, paying attention to relations among users (and situations as well) and smart objects around. Eventually, following issues were solved: (a) a method for detecting (i.e., being aware of) a specific situation, and triggering corresponding service; and (b) an algorithm for conflict situations/contexts management. A diagram of situation state transition (DSST) was proposed to specify states of a situation. A set of situation-oriented ECA rules are presented to reason the situations’ states based on sensed data. Policies based on DSST for resolving conflicts were also given. The experiment results demonstrate the feasibility of proposed method, and the performance of proposed situation-oriented policies.

Abstract: Due to advances in communications technology in recent years, prompting more extensive application of wireless sensor networks. Such sensors are limited in battery energy supply and produce the energy hole problem, this even causes paralysis of part of the system. In the cluster architecture, burden of the cluster head is bound to become the energy consumption of the maximum point, so our method is focused on reducing energy consumption of the cluster head. To this end, we propose a new scheduling mechanism based on cluster architecture. In this mechanism, we use the “polling” method to make the cluster head have an absolutely effective data receiving. In addition, we also introduced the “sleeping” mechanism to ensure that the cluster head can achieve power saving under the premise of the most effective data receiving.

Abstract: The paper describes the structure and functions of a digital multimedia environment as a means of teaching and studying foreign languages. The authors suggest an LMS-centered environment consisting of language labs, interactive whiteboard rooms, multimedia rooms, a videoconferencing hall, a webinar platform, and multimedia repositories, with all the components being linked together by an e-learning platform. The article is intended for experts in information technology and second language teaching methodology, as well as for all those interested in the problems of computer-assisted language learning.

Abstract: Railway cyber physical systems involve interactions between software controllers, communication networks, and physical devices. These systems are among the most complex cyber physical systems being designed by humans, but the complexities of railway cyber physical systems make their development a significant technical challenge. Various development technologies are now indispensable for quickly developing safe and reliable transportation systems. In this paper, we apply AADL to specify railway cyber physical systems and give a detailed analysis and design of the CBTC system. The CBTC system is split into four subsystems and makes friendly communication between the other three subsystems connecting to the data communication subsystem. We apply AADL to model each subsystem and give a detailed analysis and modeling, and make an effective integration of all subsystems together to form a complete CBTC system finally.

Abstract: Low-rate Denial of Service (LDoS) attack is a new type of Denial of Service attack, which is difficult for the router and victim site to detect because the attack packets are as many as the valid packets. In consideration of the fact that the features in time domain between attack traffic and valid traffic are different, we present a method to identify such kind of attack and try to trace the potential location of the attacker. We also carry out a simulation to illustrate the usability of this method.

Abstract: In this paper, we propose a hardware architecture for in-time transaction accelerator that reduces the bottlenecks between the DB server and the DB storage in margin FX trading system’s RDBMS (Relational Database Management System). In-time transaction accelerator located between the DB server and the DB storage analyzes and processes the queries used for margin FX trading system by co-processing of the CPU and the FPGA. The accelerator analyzes the patterns and the consistency of the queries to reduce the total database access in order to increase the RDBMS’s throughput.

Abstract: This study presents a novel summarization method, which utilizes attentive motion analysis, mutual information, and segmental spectro-temporal subtraction, for generating sports video abstracts. The proposed attentive motion entropy and mutual information are both based on an attentive model. To capture and detect significant segments among a video, this work uses color contrast, intensity contrast, and orientation contrast of frames to calculate saliency maps. Regional histograms of oriented gradients based on human shapes are also adopted at the preliminary stage. In the next step, a new algorithm based on mutual information is proposed to improve the smoothness problem when the system selects the boundaries of motion segments. Meanwhile, differential salient motions and oriented gradients are merged to mutual information analysis, subsequently generating an attentive curve. Furthermore, to remove non-motion boundaries, a smoothing technique based on segmental spectro-temporal subtraction is also used for selecting favorable event boundaries. The experiment results show that our proposed algorithm can detect highlights effectively and generate smooth playable clips. Compared with existing systems, the precision and recall rates of our system outperform their results by 8.6 and 11.1 %, respectively. Besides, smoothness is enhanced by 0.7 on average, which also verified feasibility of our system.

Abstract: Cloud computing has been widely introduced because of its ability to increase resource utilization. Furthermore, cloud computing offers resources as services that taken part as one of the next generation computing technologies. Before delivery application to cloud computing environment, the first step is the migration of the data. Migrating data from relational database management system (RDBMS) to Google App Engine is time-consuming problem. Hence, Google App Engine (GAE) Datastore provides NoSQL data storage with configuration file that contains table schema and CSV or XML file. This study presents the method for simplifying data migration from RDBMS to GAE including blob data migration. The proposed method leverages AppCfg to provide convenience way for data migration. As a result, user has eliminated at least 75 % task effort for data migration.

Abstract: A differential relay that is very sensitive relay operating even at its limits may be used for protecting a power transformer. However, this characteristic may lead to unnecessary tripping due to transient currents. In order to avoid this unnecessary tripping, estimated harmonics of these currents may be required which need great computation efforts. In this paper, a new frame work is proposed using PC interfaced with a data acquisition card AD622, which acquires real-time signals of the currents, process them numerically in the computer and outputs tripping signal to the circuit breaker. All algorithms of differential protection function and blocking techniques have been implemented using the Simulink/Matlab. To validate the present work, the performance of developed relay is tested by signals generated by Simulink/MATLAB simulator under different conditions. The test results show that this proposed scheme provides good discrimination between the transient currents and the internal fault currents.