Ubiquitous Computing Application and Wireless Sensor

One of the famous space decomposition algorithm known as Voronoi diagram is applied to express metal’s microstructure for the first time by fortuitous discovery of superficial analogy of Voronoi cell and metal’s crystal grain. Areas of Voronoi cells are controlled by locations and the number of seed points. And it can be correlated to grain size of microstructure and nuclei numbers. Therefore grain coarsening and refinement of microstructure can be described by Voronoi tessellation for simple case. In addition to this, columnar crystal caused by rapid cooling rate in one direction is also described by anisotropic locations of seed points which can be observed in typical weldment in easy. Although it needs more profound research about correlation between crystal grain growth and Voronoi diagram control variables, it shows fairly reasonable feasibility of adopting Voronoi tesselation as metal’s microstructure description and prediction tool.

In this paper, we present high signal-to-noise ratio (SNR) approximate closed-form formulas for the average error probabilities of several

M

-ary signals, particularly in Nakagami-

q

(i.e., Hoyt) fading channels. The derived formulas are much more concise than the existing exact closed-form expressions, however, showing the very tightness to error performance obtained from the exact formulas in the high SNR regime. The validity of our derivations and analyses is verified though the rigorous numerical results.

In order to satisfy the heterogeneous service requirements from different applications and the complex channel characters owing to body motions, IEEE 802.15.6 standard was established as a new solution for Wireless Body Area Networks (WBANs). In this paper, we evaluate the effect of user priorities (UPs) on the performance of IEEE 802.15.6 CSMA/CA channel access mechanism in narrow band. Simulation metrics mainly focus on the normalized throughput and average packet delay in which the traffic arrival rate and traffic distribution vary. In addition, we make a performance comparison with the non-priority CSMA/CA which concludes that the IEEE 802.15.6 with user priorities performs better in specific situation.

In many Internet of Things (IoT) scenarios, the applications need to identify the location of sensors/actuators and interact with them. Thus, a basic, common and primary mechanism is needed to identify the location of things. Everybody knows that Global Positioning System (GPS) is widely accepted as a reliable, available and accurate source of positioning, able to operate across the globe. But it is unavailable for indoors, it is due to the absence of line of sight to satellites. For indoor positioning, there are many wireless technologies have been developed, includes WiFi, RFID, Bluetooth, etc. But the sensors and actuators of IoT will be deployed in anywhere and they maybe move between indoor and outdoor environment. So ubiquitous positioning systems is expected that can work in both environments. In this paper, we proposed a hybrid positioning algorithm, which combined the Complementary Extended Kalman Filter, Dead Reckoning, GPS and WiFi Fingerprinting technologies for ubiquitous positioning. Based on the algorithm, the mobile things can report its geographic coordinate no matter where they are.

In recent years, multi-core processor technology and next generation non-volatile memory technology have developed dramatically to boost performance while minimizing power consumption. In this paper, we study a hybrid memory-aware multi-core scheduling scheme for wireless sensor nodes which use DRAM/NVRAM hybrid main memory. The proposed HAMC (Hybrid memory-Aware Multi-Core) scheduling scheme considers different access latency of hybrid memory medium and tries to reduce total execution time of tasks. We showed through simulation that proposed scheme outperforms legacy scheduling scheme.

Long Term Evolution (LTE) is a fourth-generation mobile communication technology implemented throughout the world. There is still, however, an exposed vulnerability with regard to the identification parameters such as IMSI and RNTI, as they are transmitted in plain text during the initial attach procedure in the access to the LTE network. The vulnerability has existed since the initial release of the LTE Standards, and is still present in Release 12. To prevent a leak of the identification parameters during the initial attach process and a possible third party attack, the relevant parameters should be encrypted. This paper proposes a security scheme to safely transmit identification parameters in different cases of the initial attach. The proposed security scheme solves the exposed vulnerability by encrypting the parameters in transmission. Using an OPNET simulator, it is shown that the average rate of delay and processing ratio are efficient in comparison to the existing process.

Entropy coding becomes a performance bottle neck in video codecs because it requires a large amount of bitwise computation. Many video systems accelerate the coding process by implementing it as a hardwired accelerator or by executing it on an extra general-purpose processor to meet performance requirement. However, the variety of video formats causes a high degree of complication to a hardwired accelerator, which increases implementation cost and complexity. When an extra processor is used for the coding process, the property of using variable-length operands in the coding process significantly causes computation inefficiency. This paper presents a novel processor architecture which provides an instruction set suitable for efficient execution of entropy coding process as well as supports for multiple video formats.

Cognitive radio (CR) is a technology that enables the solution of the spectrum scarcity problem in wireless communication and is based on the concept of opportunistic spectrum access. Spectrum sensing is an essential functionality that enables CRs to detect spectral holes and opportunistically use under-utilized frequency bands without harmfully interfering to licensed users (LU). Spectrum sensing is highly affected by fading and shadowing. To overcome this, cooperative spectrum sensing was introduced. The decision of cooperative users can be combined using centralized or decentralized method. In this paper, we propose a new rule of combining evidences of users when they are highly conflicting, because in this situation the conventional Dempster-Shafer (D-S) combination rule produces illogical results. With our proposed system, we show that the reliability of the system increases as compared to the conventional D-S theory of combination rule. The simulation results show that our proposed system outperform the conventional D-S theory of combination.

Trajectory prediction is basic work for 4D-trajectory modeling, conflict detection and air traffic flow management. This paper proposes a novel algorithm based distance calculation formula (vincenty formula) for trajectory prediction. We demonstrated through simulations with real flight plan and real meteorological data and experimental results show that our trajectory prediction exhibits good performance in real air traffic management environment.

ADS-B data is an important data to effectively utilize limited airspace as it contains main flight information including the location, altitude, speed, and others of plane but it is very vulnerable to hacking attack such as Ground Station Flood Denial, Ground Station Target Ghost Injection, etc. Therefore, the purpose of this study lies in proposing ground-to-ground security framework using SPKI certificate to protect ADS-B data received from the plane. In security framework proposed in this study, each ADS-B sensor connected to ATC is authenticated using SPKI certificate and creates encrypted ADS-B data using the authenticated data. Also, the verification on validity of transmission delayed ADS-B is conducted using timer information.

In this paper, a system that draws drawings on a real-time camera input image is proposed. First, a background subtraction operation is performed on the camera input image. A skin area detection algorithm is applied to the image that has undergone a background subtraction operation. After applying a labeling algorithm to the detected skin region image, a pen is augmented on the position of the hand. In addition, based on the obtained coordinates, a hand gesture-dependent drawing is drawn simultaneously on the camera image, in real-time.

A number of cooperative spectrum sensing techniques have been purposed in cognitive radio networks. However, collaboration between multiple cognitive radio (CR) users also raises a number of security issues. It has been shown that the cooperative gain can be severely affected by malfunctioning or malicious CR users in cooperative sensing. One of them is spectrum sensing data falsification (SSDF) attack, where malicious users transmit false information instead of real detection results and thereby affecting the final decision. In this paper, we study the detection and suppressing the malicious users using different outlier detection methods based on Grubb’s test, Boxplot method and Dixon’s test. We have compared their performance through simulation and receiver operating characteristics (ROC) curve shows that Boxplot method outperforms both Grubb’s and Dixon’s test for the case where multiple malicious users are present.

Recently, NFC (Near Field Communication) and its related technologies are being loaded into smartphones. Consequently, payment and data exchange are easily made through NFC. However, smartphone can be permitted an attack such as a user impersonation by exposure to information in the communication process. Therefore, the communication between mobile devices in NFC environments must be made safely with leaving any information at the other party. Moreover, it should be light-weight for wireless communication. In this paper, we propose an authentication method and a scheme of key agreement that can reduce the weight by using a hash function and XOR operation algorithms for mobile payment systems. We confirm that the proposal method leaves no information at the other party.

Responsiveness and energy saving are key issues on the Smartphones due to its limited battery capacity. For gaining of execution delay and energy saving, the Android OS manage the main memory by LRU-based algorithm to maintain some terminated applications which expected to be re-execution soon. However, this LRU-based history does not correspond with the user’s behavior because most applications may be invoked by the user’s periodic habits. In this paper, we propose a novel memory management policy to improve such mismatch. The proposed policy based on user behavior outperforms about 10–30 % compare to the LRU-based policy.

Health Information Exchange (HIE) is regarded as an important requirement which can enhance the quality of healthcare services in many countries. In Korea, Care Record Summary (CRS) has been developed as a clinical document guideline for national HIE service since 2013, which includes medical information like laboratory, medication, diagnosis, and plan of care etc. And, in 2014, CRS almost reached the final standardized step of Korean Industrial Standard (KS) for exchanging health information among healthcare providers. Before CRS documents being widely populated, it has to be guaranteed that only validated CRS documents are exchanged. As a result, we develop CRS Validation Tool (VT) which can contribute to the improvement of the level of conformance to CRS KS. Furthermore, in order to help the healthcare professionals like physicians, nurses, and healthcare software developers to obtain knowledge about CRS KS as well as VT, we combine CRS VT with Social Network Service (SNS).

In this paper, an adaptive Trickle scheme is proposed for RPL-based networks. When the network conditions are changed and/or the minimal residual energy on the sensor node gets less than a pre-determined threshold, the Trickle-related parameters are dynamically adjusted to save more battery power on the nodes in the WSN (Wireless Sensor Network). The simulation results show that the proposed scheme improves the routing performance and effectively prolongs the network lifetime of the WSN.

Because moving objects usually move on spatial networks in location-based service applications, their locations are updated frequently, leading to the degradation of retrieval performance. To manage the frequent updates of moving objects’ locations 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 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. Using our grid scheme, we propose a new k-nearest neighbor (k-NN) query processing algorithm which minimizes the number of accesses to adjacent cells during POIs retrieval in a parallel way. Finally, we show from our performance analysis that our k-NN query processing algorithm is better on retrieval performance than that of the existing S-GRID.

This paper proposes a centroid global positioning system (GPS) model to improve the positioning accuracy of low-cost GPS receivers of a sensitive location-based system. The proposed model estimates the precise movement position by a centroid sum of the individual improved positions of three GPS receivers. Each GPS receiver’s position is improved by using a direction and velocity averaging technique based on combining the vehicle movement direction, velocity averaging, and distance between the waypoints of each GPS receiver using coordinate data (latitude, longitude, time, and velocity). Finally, the precise position is estimated by calculating a triangular centroid sum with distance threshold of the improved positions of three GPS receivers. In order to evaluate the performance of the proposed approach, we used three GARMIN GPS 19x HVS receivers attached to a car and plotted the processed data in Google map. The proposed approach resulted in an improved accuracy of about 2–12 m compared to the original GPS receivers. In addition, we compared the proposed approach to two other state-of-the-art methods. The experimental results show that the proposed approach outperforms the conventional methods in terms of positioning accuracy.

This paper aims to introduce some key parameters for the tracking application in wireless sensor networks. This paper has compared three different routing protocols which have been implemented in J-Sim simulation platform, and proposed several evaluation models. Based on these evaluation models, simulations are not necessary for the users to deploy sensors.

In this paper, we propose a secure framework for mobile based RFID services using personal policy-based access control for personalized ultra-high frequency (UHF) tags employing the Electronic Product Code (EPC). The framework provides a means for safe use of mobile phone-based RFID services by providing security to personalized wellness service. This new technology aims to provide absolute condentiality with only basic tags.

This paper proposes an SOM clustering method using user’s features to classify profitable customer for recommender service in e-Commerce. In this paper, it is necessary for us to classify profitable customer with RFM (Recency, Frequency, and Monetary) score, to use the purchase data to join the customers using SOM with input vectors of different features, RFM factors in order to do the recommending services in u-commerce, to reduce customers’ search effort for finding items, and to improve the rate of accuracy. To verify improved performance of proposing system, we make experiments with dataset collected in a cosmetic internet shopping mall.

Radio Frequency Identification (RFID) tags have been widely used for identifying objects on a global scale. Discovery service (DS) acting as a broker between objects and their information sources needs to handle a huge amount of query requests from the user. So the performance of the node of DS must be powerful enough to handle lots of query requests sent to it. However, no performance improvement schemes for the node of DS have been proposed until now. Therefore this paper proposes a novel performance improvement scheme for the node of DS based on anycast and Distributed Hash Table (DHT) network. By analysis, the performance improvement scheme proposed in this paper can not only significantly improve the performance of the node of DS but also has the advantages of shortening its response time, avoiding the adverse influence of ISP-unfriendly policies and being transparent to the user, which satisfies the actual requirements pretty well.

Because of the popularity of the internet, a variety of communications devices that make people live more convenient. The people generate information faster than before. The need of server rises gave birth to cloud computing. In recent years, the mobile device manufacturers launched aboard Near Field Communication, NFC chip device, and get large number of development the NFC application, such as Electronic Wallet, Electronic Ticket, Authentication function and so on. In North America has google wallet service, in England has mobile payment service, in Taiwan, we have prepare to work up NFC authentication center. So that our research plan to combine NFC device with RBAC authorization let users uses cloud service through internet any time. In this research we consider the widespread of mobile device and cross cloud application, we plan to use NFC technology combine RBAC mechanism to simulation the cross cloud authorization management.

Because of the more and more services wireless communication technology can offer nowadays, the quality of wireless communication became an important key. In this research, 3G/UMTS and WLAN, which are two major wireless communication techniques will be mentioned mainly. The former offers a wide-range, high-movability, complete and safe record of accounting; the latter offers a narrow-range, low-movability, high-speed-transmission access on the Internet. The complementary between these two techniques can not only enhance the quality of wireless communication but offer more services for customers to choose, and customers can use wireless application services regardless of any environmental limit. This research will focus on the problem of fast-handover when 3G/UMTS and WLAN is interworking, such as authentication and authorization. About the two formers, we will use W-SKE to accomplish authentication procedure, and achieve safer Mutual Full Authentication and Fast-Authentication.

In 2011, Yeh et al. proposed a PAACP: A portable privacy-preserving authentication and access control protocol in vehicular ad hoc networks. However, PAACP in the authorization phase is breakable and cannot maintain privacy in VANETs. In this paper, we present a cryptanalysis of an attachable blind signature and demonstrate that the PAACP’s Authorized Credential (AC) is not secure and private even if the AC is secretly stored in a tamper-proof device. An eavesdropper can construct an AC from an intercepted blind document. Any eavesdropper can determine who has which access privileges to access which service. For this reason, this paper copes with these challenges and proposes an efficient scheme. We conclude that a simple authentication scheme and access control protocol for VANETs not only resolves the problems that have appeared, but also is more secure and efficient.

The purposes of this research is using the Data Mining techniques, and explore the potential information from the National Health Insurance Research Database, analysis lung cancer patients which has the highest mortality in Taiwan, as a reference of the analysis of Bureau of National Health Insurance files and the clinical index of hospitals. By using statistical software, “SPSS Clementine 12.0”, this research merged “The detail file of hospital medical expenses inventory” and “The basic data file of medical institution” between 06’ and 09’ as the study data, then hospitalized lung cancer patients screened for the study sample, and using Two-Step clustering technique to produce the results that are effective. The hospitalized patients that with lung cancer and death patients, males have a higher percentage than females, lung cancer people are usually accompanied with comorbidities, especially for pneumonia; most lung cancer patients go to the center of medical, and most patients make booking as out-patient. The treatment of lung cancer patients should notice the factor that lead to pneumonia, and this research shows that most patients make booking as out-patient, therefore, taking drug treatment for patients can regarded as the main dependence for curing.

In this study, data mining is applied to the use of an Enterprise Resource Planning (ERP) database to explore the core value of business operations by revising the RFM model into an RFGP model through “customer value analysis”. This model is used as a tool by enterprises to make proper adjustment to business strategies in a timely manner. By using an RFM model to “analyze dependence on suppliers”, enterprises can properly plan to reduce internal procurement costs and suppliers can properly manage their risks. With this two-prong focus on “profit maximization” and “cost reduction”, enterprises can maximize their profits. The findings of this study indicate that high-value customers are stable customers and accounted for 31 % of total customers. The statistics also show that customers of LED backlight modules constituted 18 % of the total and were the primary source of profit for the enterprises. However, there remains much uncertainty in the LED lighting market and the rate of return was low. With limited operational resources, enterprises should explore technologies related to backlight products, purchase automation equipment, train professionals in related disciplines and seek to enhance their overall competitive power. Suppliers of key materials are suppliers of high dependence, accounting for 11 % of the total and including suppliers of heavy reliance and exclusive suppliers. Enterprises are strongly advised to establish new sources of supplies to ensure a proper procurement balance and reduce materials supply related risks. In addition, enterprises should take the top 10 key materials suppliers as targets for price reductions in order to cut costs and maximize profits. Enterprises are also strongly advised to invest in the suppliers of key materials. The recycled use of enterprise resources could feedback to the enterprises themselves and helps to maximize enterprise profits.

Feature selection is a search process to find the optimal feature subset to describe the characteristics of dataset exactly. Artificial Fish Swarm Algorithm is a novel meta-heuristic search algorithm, which can solve the problem of optimization by simulate the behaviors of fish swarm. This study proposes a modified version of Artificial Fish Swarm Algorithm to select the optimal feature subset to improve the classification accuracy for Support Vector Machines. The empirical results showed that the performance of the proposed method was superior to that of basic version of Artificial Fish Swarm Algorithm.

As the mobile device industry grows rapidly, smart phones and tablet computers have become the indispensable devices in our daily lives. Even more, one could have owned many devices at the same time. Although, the traditional personal computers or laptops has more powerful computing performance than mobile devices, but, compared with convenience and portability, the mobile device would be a better choice. Eventually, this leads to the increase of the variety of devices in our living; however, each of these devices has its own functions, which is not always replaceable from other devices, and how will these devices interact has become one of the most important discussion in the field of computer science. In this paper, we will focus on the integration of personal computer, which has better computing capacity, and mobile device, so it allows the user to control the mobile device through their personal computer via Wi-Fi or 3G. This allows the user to work with their personal computer and mobile device at the same time. The integration of both devices will improve the usage of the resources provided by these devices, such as phone call communications, GPS and G-sensor, so that we will be able to use our PC sufficiently, and contribute to computer technology in the future.

Conventional fluorescent light source, as well as incandescent light source is gradually being replaced to LED for reducing power consumption in image display area for multimedia application. LED light source requires the controller with a low-power operation. In this paper, a low-power technique using adiabatic operation is applied for the implementation of LED controller with a stable constant-current, a low-power and low-heat function. From the simulation result, the power consumption of the proposed LED controller using adiabatic operation was reduced to about 87 [%] in comparison with conventional operation with a constant V

DD

. The proposed circuit is expected to be an alternative LED controller which is sensitive to external conditions such as heat.

This paper proposes a hand gesture recognition technique that allows users to enjoy uninterrupted interaction with a variety of multimedia applications. Hand gestures are recognized using joint information acquired from a Kinect sensor, and the recognized gestures are applied to multimedia content. To this end, hand gestures are quantized in the grid space, expressed using an 8-directional vector chain, and finally recognized on the basis of a hidden Markov model. To assess the proposed approach, we define the hand gestures used in the “Smart Interior” multimedia application, and collect a dataset of gestures using the Kinect. Our experiments demonstrate a high recognition ratio of between 90 and 100 %. Furthermore, the experiments identify the possibility of applying this approach to a variety of multimedia content by verifying its superior operation in actual applications.

The network video surveillance system is the latest trend in surveillance technology and has been rapidly surpassing the older analogue cameras used in most surveillance systems nowadays. The network surveillance system is mostly similar to contemporary computer systems such as personal computer, server system, and embedded system. In means, acquiring or recovering video evidence in network surveillance are quite similar to traditional evidence collection techniques in digital forensics and these operations are needed to be considered proving the integrity of evidence. However, a lack of research on evidential video management in network surveillance system is able to damage reliability and admissibility in a court of law. In this paper, we defines forensic artifacts for performing video evidence retrieval in network surveillance systems. The purpose of this work is to provide reliable video evidence collection from each network surveillance systems with admissibility and integrity of evidence.

Energy efficient and lifetime aware wireless sensor network design is still a challenging issue in sensor network research community. Cluster based wireless sensor network is a proven approach of power aware routing. A new the challenge of cluster based approach is handling dynamic clusters, selection of cluster heads, balancing of energy consumptions of member nodes of a cluster. In this paper, we propose an energy efficient routing method for dynamic hierarchical clustering architecture WSNs with additional intra-cluster management additional subordinate cluster head (SCH) are selected in a cluster for working as data relay nodes. In our proposal, SCH nodes are selected using multilevel cluster algorithms for energy efficiency and load balancing. The proposed routing approach combines the facilities of proactive and reactive sensing, routing and data transmission and thus suitable for both time-sensitive and time-insensitive applications.

To meet the demand for seamless real-time services with limited resources of ubiquitous computing environments, this paper suggests a new virtualization-based server cluster system introducing three schemes:

simplified rotation process

to reduce system overhead,

exposure time adjustment

to prevent the degradation of system performance, and

spare server insertion

to cope with heavy incoming packets. It is verified for ubiquitous computing systems which should satisfy strict operational constraints with limited resources that the proposed schemes enable the systems to achieve higher levels of service quality as well as to stand up to distributed denial of service (DDoS) attacks.

Shiftwork schedule is required to provide uninterrupted service for the hospital emergency department. There are many limitations with the manual shiftwork scheduling applied at the University of Malaya Medical Centre Emergency Department (UMMC-ED). We propose an alternative shiftwork scheduling strategy to solve these limitations which consists of three modes; Initialization, Sufficient and Insufficient mode. These modes detect the imbalance between workforce and workload which enable the appropriate distribution according to the demands of individual staff. We developed a tool, Trauma Hospital Online Roster (THOR) that implements the above strategy.

Academic researchers argued that the use of pen-gesture commands in a pen-based environment could contribute to the improvement of task efficiency. However, previous research on pen-gesture commands tended to be focused on PDAs. A graphics tablet is also a pen-based input device. Therefore, it is possible to get better task efficiency while applying pen-gesture commands on a graphics tablet for a digital painting environment. The effects of pen-based input devices and command operations on subjects’ task efficiency and the System Usability Scale (SUS) were explored in this paper. The results indicated that pen-gesture commands provided better task efficiency in file editing, layer control and integrated applications. The result from the SUS showed that pen gestures with a rubber grip pen got better usability.

This paper proposes an efficient recommending method for computerized treatment plan of cancer patients in Korea using electronic discharge summary of EMR in HL7. In this paper, it is necessary for us to classify disease patterns in the medical historical record to join the electronic discharge summaries data in EMR to analyze the disease pattern with input vectors of different features, disease code, to build the medical treatment plan of cancer patients in Korea using recommending service in medical data sets, to reduce inpatients’ search effort to get the information of curing procedure, the diagnosis for recovering their health and to improve the rate of accuracy of recommending service. To verify improved performance, we make experiments with dataset collected in medical center.

This paper analyzes the situation of the college physics experiment teaching and discusses the necessity of the research on a network assisted teaching system, which is used in college physics experiments. Combining with our university’s condition, the design scheme of a network assisted teaching system is presented. The system includes administration module, teacher module, student module and resource module. All the modules build upon each other to provide students with more efficient guidance, rich content and more autonomy. In addition, students can make full use of the openness and interactions of the system to learn better.

With the development of vertical replenishment technology, to create a vertical replenishment schedule has become an important way to increase the efficiency of vertical replenishment. In this paper, the vertical replenishment (VERTREP) scheduling model is established. Base on the model, two algorithms are proposed to generate the VERTREP schedules. The Simple Scheduling (SS) algorithm is used to generate the schedule for the VERTREP mission that contains light cargos. The Cargo Capacity Hierarchy Scheduling (CCHS) algorithm can process heavier cargos and increase the cargo weight limit. Empirical results show that the vertical replenishment efficiency of schedules obtained by algorithm CCHS is higher than the vertical replenishment efficiency of schedules obtained by algorithm SS.

This paper describes the control modules for assist-control lung ventilation devices and introduces an embedded system application considered in the broader context of human centered computing. We highlight aspects of our current understanding of computer-assisted health care with special attention paid to patient/workstation interaction. The paper explores the possibility of using the technical project as a starting point for creating computer models which can be useful not only to verify technical solutions before they are embedded into the end devices but which can also be used for academic needs, thereby bridging the gap between classroom and enterprise scale projects. We involve students in an end-to-end project, from primary specifications and mathematical models up to the implementation of the end device. This is not usually easy to realize within the context of an academic course, but in so doing we aim to reduce the distance between the learning environment and real life projects of embedded systems and their applications.

To solve the problem of single sign-on and to realize the destination of fast access, an improved single sign-on system is presented, which is based on the combination between biometric key technology and elliptic curve cryptography. The system analyses the mechanism of status register and verification, which is based on the platform of cloud sign-on. The system needs dual authentication of both fingerprint and password. What’s more, it adopts a two-way authentication. So it has strong security, and it can resist replay attack and decimal attack effectively.

To enhance the overall safety of cloud service and ensure the data integrity and to ease the burden of monitoring system, cluster analysis is introduced into the paper to divide users into different trust domain. The monitoring system’s objects only include special users and users whose trust domain is minimal. The system has function of SMS alarm, and it permits users to recover the data by means of smart mobile phone. The system takes both special users and general users into consideration and ensures the reliability of the service and enhances the experience of users.

Specific dynamic action (SDA), the metabolic phenomenon resulting from the digestion and assimilation of a meal, is generally influenced by body mass. The effects of ration level on SDA of taimen (

Hucho taimen

, Pallas) was evaluated, by measuring the temporal pattern of the oxygen consumption rates of taimen with meal size, 1/3 satiation, 2/3 satiation and satiation, after feeding, at 17.5 °C. With the approximate body mass but different meal size, both Peak VO

2

and SDA had a tendency to increase with increased meal size. Factorial scope of peak Vo

2

and Duration had a tendency to increase with increased meal size.

In this publication authors present the most important aspects of semantic inference dedicated for description and analysis of financial data in cognitive management information systems. Analysis of financial data may be implemented not only to improve the results of the analysis process, i.e. insight analysis, the effectiveness of the proposed solutions, increase the use of analysis, but also to rationalization of data management processes of financial data in enterprises or organizations. The financial information management systems which semantically analyse the economic conditions, may execute their tasks using semantic information available to them. The foundation for the operation of financial and economic cognitive systems, consists in both the semantic analysis of the situation of the enterprise. This situation are described by various economic ratios and the assessment of the future situation of this enterprise.

In the chapter will be shortly presented some advances in the area of computer methods used for encryption and division of confidential data, as well as modern approaches for management of shared information. Cryptographic techniques for secret information distribution allow to secure strategic data against disclosure to unauthorized persons. The chapter will shortly describe algorithms for information sharing on the basis of personal biometric features. The development of computer techniques for classified information sharing should also be useful in the process of shared information distribution and management.

To solve the data security problem based on the Attribute Based Access Control (ABAC) mechanism, an improved CP-ABE algorithm which is applicable to ABAC environment is proposed. The research is done from two aspects of access system structure and formal definition to study the ABAC mechanism. Then the formal definition of improved algorithm is given. The simulation and performance analysis is also finished. The algorithm has less storage consumption and higher efficiency under ABAC environment through the comparison with traditional CP-ABE algorithm.

With rapid development of internet, the expansion of information restricts the effect of learning. This paper designs an education video personalized recommendation system based on collaborative filtering recommendation technology. We design this system mainly based on collaborative technology and content analysis technology. This system can increase the effect of teaching, also can increase the learning autonomy of students and make students studying high-efficiency. This system has been applied to Shanghai Lifelong Learning Network and achieves significant influence.

The study incorporates the semantic web to achieve the synchronization for medical rules. Web Ontology Language (OWL) is first used as the knowledge model and a medical rule is viewed as a class of medical statuses representing knowledge of medical rules. A classification is then applied to decide the legality of medical usage. The characteristics of the proposed solution are manifold. OWL supports the syntax of class inherences, so it can develop a cognitive economy and shorten the encoding length of medical rules. OWL syntax can represent the styles of most medical rules, so the automatic synchronization system only need one document and one inference engine to handle all medical rules. OWL simplifies the design of the medical rules of National Health Insurance automatically, and synchronizes the design to hospital information systems. Therefore, doctors’ ordering systems rapidly reflects the changes of medical rules.

In this paper, an approach to presenting the learning resources, especially those existing user-generated contents associated with learners’ activities, as the recommendation to satisfy their current requirements in a social media enhanced learning system, is proposed. Users’ attentions are caught and analyzed from the browsing behaviors of learners on a webpage through an eye-tracking device.

This paper demonstrates a method for colonies recognition and classification in super resolution images. According to the features of the colony images, we propose a novel strategy for colonies recognition and classification using image processing, binarization partitioning curved surface (BPCS), adhesion segmentation and support vector machines (SVM). The experimental results show that the new colonies algorithm is better than usual algorithm in reducing recognition classification time, and it also can display all colonies in different conditions, such as max length, sphericity, color feature, etc.

Course scheduling is a challenge task in the teaching process, which highly related with the quality of university. Given the number of the class rooms and time range, the aim of the algorithm is to arrange proper time and place to make sure there is no conflict. Usually, this kind of algorithms is NP-complete problem, and takes a lot of time to find the exact solution. To improve the speed and the quality, we propose a time searching algorithm consisting of three steps: initial, bottom-up and up- bottom. In order to speed the nearest capacity classroom searching, we also incorporate an equivalence class division algorithm. Besides, we provide a well-designed interactive interface to make the course scheduling more simple and flexible.

Taking the network marketing of sports products in China as the research object, through statistics to the application situation and effects of the Internet in the marketing of Chinese sports equipment, combined with the history of the Internet application in domestic and international sports events and some actual cases, using a variety of research methods of documents literature searching, comparative study, logic analysis and case study, this paper put forward a relatively complete theoretical reference to strategies and technique of the present sports network marketing in our country.

As one of the main tasks in colleges and universities, enrollment has a vital role in higher education. Visualization of enrollment data serves as an auxiliary to analyze and extract the potential and value of it. Due to the limitations of spatial imagination ability on multivariate data set, people can’t gain an intuitive sense of it. What is more, it’s difficult to display the variables and characteristics globally and simply using the common methods such as histogram, line chart and so on. It’s proposed that interactive visualization on multivariate enrollment data using parallel coordinates should be a simple and flexible approach. The comprehensive utilization of data modelling, data analysis and parallel coordinates aid to interpretation or mining on model, characteristics and rules hidden in the interior of enrollment data. Results of the application on the multivariate enrollment data set prove that, the method of parallel coordinates can implement visual analysis to multivariate Enrollment data flexibly and effectively.

Electronic learning (e-Learning) is the next generation of learning. It provides comprehensive supports to students and can overcome geographical and time limitations compared to traditional classroom learning. There is a dramatic difference between traditional classroom learning and e-Learning. One of the significant discrepancy is the nature of the social context, which is a main research issue in this study. The lack of in-person contacts in e-Learning does not isolate students from the social thoroughly, yet with the assistance of technology, there is still room for much more creative learning activities that facilitates interactivity between students. Therefore, in this study, social presence theory and social facilitation theory were reviewed and designed to examine the influence of information about peers’ progress on students’ learning effect. Forty-four students of an elective course in a senior high school at Tainan City, Tainan participated in the experiment. The result shows that students’ learning effect is affected by information about peers’ progress, and results were discussed with social presence theory and social facilitates theory. Displaying of information about peers on e-Learning system can have influence on students. Consequently, students’ learning can more or less be influenced by controlling the display of peer information.

Clinical Decision Support (CDS) applications have been widely recognized for improving health care quality and medical knowledge translation. However, its adoption and utilization in a real clinical environment is still subject to many factors, an important one of which is the lack of mechanism to easily integrate these applications to clinical workflow. This paper designs and develops an extensible CDS application integration and management system framework. This framework achieves interoperability between Clinical Information System (CIS) and CDS applications at two levels under predefined integration protocols; and through a mechanism of registration, management and delivery, various CDS applications can be delivered to targeted scenarios and executed in a context-aware way. This framework was validated in real clinical environment, and proved to be effective in both integration and interoperability. Meanwhile, targeted CDS application delivery further facilitates CDS in clinical promotion.

To achieve the realistic simulation of intelligent group animation, a method of generating intelligent group animation by fusing intelligent algorithms and motion capture data is proposed. This method mainly proposed a novel algorithm that can effectively fuse the animation path extracted from experiments about group simulation with particles based on the Artificial Fish-Swarm Algorithm (AFSA) and the original motion capture data, so as to synthesize one new motion data. As a result, we can achieve multi-roles path animation with reality through binding the synthesized motion data to specific roles. Depending on the experimental results, it demonstrates that the method of generating intelligent group animation by fusing motion capture data and intelligent group path planning can generate group animation with higher reality.

The number of eye disease cases, especially those that will result to blindness, is increasing. Retinal fundus images are usually used for disease detection and monitoring, which are essential for proper treatment and care. Image processing algorithms can be used to help increase the speed of analyzing these images. Since analyses require more computational effort and time, operations should be focused only on the object pixels. This paper will present a new technique that can identify the object pixels in a simple and fast manner. Unlike existing methods, this uses only a few assumptions and computations. Its performance is tested by experiments that used various publicly available datasets. Results will show the accuracy, effectiveness, and robustness of the proposed method.

Small group discussion is a part of the medical program for second and third year medical students at the Faculty of Medicine, Chiang Mai University. In the past, the students were scored manually by facilitators. The scores were checked and transferred to a spread sheet by at least three administrative assistants. This massive workload delayed the process of finalizing scores in each study block which meant students with low scores were not identified promptly. Consequently some of these students did not pass their study. An electronic scoring system was implemented to improve the scoring process. The system facilitates the administrative assistant to create a scoring form, manage scenario details, store data, perform backups, and export data. One year analysis showed the major effect of the new system was that it significantly reduced the time taken for the scoring process. Finally, the improvement of the scoring system decreased the number of repeat student from 10 (on average between 2008 and 2011) to 2 students in 2012.

In order to prevent corruption in Indonesia, the use of anti-corruption e-learning needs to be optimized and to reach young generation whose life nowadays mostly inseparable from the internet connections. The aim of this research is to identify predictor variables of perceived risk of anti-corruption e-learning. When risk perception is low, attitude toward e-learning is expected to be more positive. This psychotechnological research employs predictive correlational design, with the predictors (1) email phishing literacy and (2) anomia. The participants of this research were 71 students of faculty of psychology at a private university in Jakarta, Indonesia (20 males, 51 females; Mean of age = 19.93 years old; Standard Deviation of age = 1.397 years old). The data were analyzed by using simple linear regression analyses. Results of this research show that both variables are able to predict perceived risk of anti-corruption e-learning, consecutively in negative and positive ways.

Usually the purpose with business intelligence is to increase the profit, through capturing, storing, sharing, and utilizing knowledge in an innovative way. Are the concepts of business intelligence applicable to schools? If that is the case, then the primary and secondary education sectors should be replete with examples of institutions that leverage business intelligence to achieve operational excellence. This paper discusses the need for business intelligence from the perspectives of teachers in academic services, perceptions of application and benefits. However, although some examples exist, they are the exception rather than the rule. We believe there is tremendous value to school institutions that develop initiatives to achieve business objectives. The business intelligence can be classified as support for teaching staff decision making. The conclusion is that business intelligence could be used in schools, facilitating the business intelligence within the organization for academic services.

Antimicrobial abuse is very serious and is increasing threat China. It is important to make antimicrobials’ better service for patients through the information technology. The surveillance platform which provides the public health authorities the patterns of consumption of antimicrobial drugs is necessary for a constructive approach to many problems that arise from the multiplicity of antibiotics now available, their high cost and the ecological sequelae of their use. In this study, DDD (Defined Daily Dose) which is an international general concept to investigate the drug consumption is used to build such a surveillance platform in a Chinese 3A hospital. First, we will explain how to classify and grade each antimicrobial drug and obtain their corresponding DDD. Then the surveillance platform was described. In the end, this paper shows how we analyzed the consumption pattern of antimicrobial drugs through this platform.

Drug is an effective measure of alleviating pain and treating diseases. Whereas medication-related harms due to both adverse drug effects and drug errors have become the leading iatrogenic injury. However, such medication-related harms often remain unrecognized and unreported. The purpose of this study is to automatically identify adverse drug events (ADEs) in routine clinical documents. Firstly, ADE related Chinese lexical resource was collected and maintained. Then, a natural language processing (NLP) application which could automatically extract ADE symptom from drug manuals was developed and applied for building an ADE knowledge base for 3,733 drugs. Finally, based on these resources, an ADE detection algorithm was proposed to identify ADEs in the clinical free-text. Results revealed that the precision of the ADE detection algorithm was 80.8 %.

The paper involved a control system and control method for automatically adjusting the outdoor LED display screen brightness. The control system includes outdoor LED Display, test module, the optical system which was collect emitted light and reflect Light, a light sensor, a signal amplifier, analog to digital conversion control, LED display brightness automatic control system. The outdoor LED display controlled by LED display; the optical system which was collect emitted light includes a hood and fixed focus lens, fixed focus lens; the test modules controlled, scanned and drived by LED display; the hood is used to shield unwanted ambient light, fixed focus lens video test module emit light to the light sensor, the light sensor convert an optical signal into an electrical signal and amplified by the signal amplifier and the analog signal which amplified by the signal amplifier was sent to the digital converter and turned into the corresponding digital signals and was sent to the LED display brightness automatically control system and then achieves automatic brightness adjustment.

This paper presents a novel quantitative metric for comparison of 3D mesh segmentations, Ultimate Measurement Accuracy, basing on the screening data sets, to support our quantitative comparisons of seven recently published mesh segmentation algorithms; and the experiment results suggest that, our metrics is robust to degenerative segmentation and hierarchical refinement, stable to the imprecision of cut boundaries.

Objective: To probe the applicability conditions of Chinese Virtues Questionnaire (CVQ-96) in medical postgraduates, and to provide theoretical guidance for the establishment of corresponding policies. Method: Carrying out CVQ-96 on-site testing in elective class, using SPSS17.0 for the data analysis of the questionnaire. Results: According to the principal component analysis (PCA) results, four dimensions that gregariousness, flexibility, adaptability and principle are extracted in this paper, the scale and its dimensions presented good internal consistency reliability and construct validity during the validation among medical postgraduate. There is only gender difference of medical postgraduates in the adaptation dimension but little demographic difference in other dimensions. And there is no obvious difference in other demographic aspects. In addition, the strengths that have demographic differences among medical postgraduates are also not much. Conclusion: The results of the questionnaire can be used to analyze the distribution of character strengths among the medical postgraduates, but it still need to be revised. The relevant guidance of the aspects that have difference should be carried out to make the medical graduate students receive better education.

All-in-English teaching (AET) is a pedagogical reform performed by many universities of China. In this paper, we explore all-in-English teaching of compiler principles, which is a disciplinary basic course of the computer science curriculum. Teaching goals of compiler principles are analyzed and an action learning approach to all-in-English teaching of compiler principles is explored. We analyze the effect of all-in-English teaching of compiler principles through our 3 years of teaching experience.

In this study, an Ant Colony Optimization (ACO) clustering approach is proposed for medical diagnosis to assign patients into different primary headache groups with Visual C++ program. By experiments, 375 patients were classified into Migraine, Tension-Type Headache (TTH) and Trigeminal Autonomic Cephalalgias (TACs). Results show that the clustering algorithm with ant colony can be important supportive for the medical experts in diagnostic.

With the huge advancement in shape scanning and acquisition technology, 3D shape matching becomes one of hotspots in machine vision. This paper introduces the classical ICP together with Sparse ICP, EM-ICP and ICNP algorithms, which respectively refined ICP with weighted factor, closest normal vector as well as sparsity inducing norms, discusses their improvements and insufficient, and gives the direction of future research.

Distance education for judicial examination training is different from face-to-face teaching. The difference is mainly reflected in the authority and the pertinence of the teaching content. In addition, distance education can save the cost of hiring well-known experts as it in the field of face to face. However the actual effect of distance teaching method has achieved in the judicial examination training is poor. The main reason lies in the lack of teaching process among many reasons. Some measures must be taken to improve the teaching effect of distance judicial examination training: firstly we must solve the problem of short-term behavior of educational institutions, also should we strengthen the communication and interaction between teachers and students in the teaching process.

The notion of using a meta-heuristic approach to solve the Knapsack Problem has been intensively studied in recent years. By comparing and analyzing the research of Ant Colony Algorithm (AVA) for 0/1 Knapsack Problem the authors propose an improved ACA based on greedy strategy and normal distribution. Experimental results show that the proposed approach performs better than the basic ACA.

Non-Chinese students in Xiangya medical School had their reflection on the learning difficulty of sectional and clinical anatomy. Their suggestions of these two disciplines in various aspects may be helpful to the improvement of teaching.

In this paper, we have presented the three ways of search functions in Ichpedia, the web-based intangible cultural heritage encyclopedia database and archives system. The search system consists of simple search, semantic search and map search. All functions can promote dynamism and efficiency in the achievement of best results from the user’s point of view. First, the simple search provides not only exact results associated with keywords but also providing two statistical graphs. The graphs show the ratios of the search results according to classification and regional distribution of an individual ICH element. Second, map search provides graphical interface so that users are easy to follow the search result. It is constructed extensively by interconnecting two other searches, simple and semantic search functions. Third, semantic search is the most difficult and meaningful function but not perfect yet. However, it already shows some important implications in terms of that an ICH element is associated with other elements and its characteristics can be understood within the wider networks of ICH resources. The proficiency of our search system highlights in finding the connected elements and by doing so, in expanding users’ knowledge and safeguarding awareness of intangible cultural heritage.

Massive multiple-input multiple-output (MIMO) using a large number of antennas at both transmitter and receiver sides based on quasi-orthogonal space time block code (QOSTBC) is presented. Space-time block code (STBC) is a MIMO transmit strategy that applies transmit diversity and high reliability. QOSTBC is attractive because it achieves higher code rate than orthogonal STBC and lower decoding complexity than non-orthogonal STBC. We present the performance of massive MIMO systems using the QOSTBC with multiple antennas up to the 16 × 16 configuration. The performances of 2 × 2, 4 × 4, 8 × 8 and 16 × 16 massive MIMO systems have been presented. Simulation results show that the massive MIMO systems with QOSTBC give significant performance improvement with full rate and full diversity, compared with previously considered massive MIMO systems.

Cloud computing has been spotlighted as a new paradigm of database management system. However, privacy needs to be preserved for databases that are valuable and sensitive against unauthorized accesses. For this, two issues of data security, including data confidentiality and query result integrity, become major concerns for users. Existing bucket-based data authentication methods have problems of data disclosure and transmission overhead, due to the unsophisticated data grouping strategy. In this paper, we propose a privacy-aware query authentication index which guarantees data confidentiality and query result integrity for users. We privately partition a spatial database into small groups by using periodic function and generate a signature of each group. The group signature is used to check the correctness and completeness of outsourced data when answering a range query to users. Through performance evaluation, it is shown that proposed method outperforms the existing method in terms of range query processing time up to 3 times.

In order to improve the performance of text classification and information retrieval in big data of electric power domain, we propose a novel Chinese language classification algorithm—De-word classification algorithm. Focusing on the key role played by the De-word in modern Chinese language, this algorithm examines Chinese text classification method from a unique angle. Besides, on the basis of traditional weighted algorithm, it designs a novel relevance weighting model—De-TFIDF, and achieves a higher correlation in text information retrieval. Experiments show that, De-word classification algorithm significantly improves the efficiency of text classification, significantly improved information retrieval performance.