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Location awareness and navigation are becoming one of the most important features in mobile phones and smartphones. Personal navigation and location based services are enlarging the scope of mobile applications. GPS is the most efficient positioning technology. Thanks to the reduction in the size of the GPS receivers and the integration of GPS with mobile phones, GPS is one of the most important service providers in LBS. By the way, since mobile phones and smartphones usually have relatively low cost GPS chips, the performance of locating accuracy is highly dependent on environmental factors. In addition, the accuracy of GPS varies depending on the number of GPS satellites and is reduced in GPS interfering spots such as in a forest or around buildings. This paper proposes a localization improvement algorithm in GPS interfering spots by integrating information of multiple sensors in smartphones. The proposed algorithm is implemented in a smartphone and the performance is evaluated on a campus. The proposed algorithm has better performance than only the GPS location information in GPS interfering spots and maintains reasonable performance in open spaces where the GPS receiver is accurate.

The evolution of mobile devices arising from the explosive dissemination of Smart phones is widely changing life as we know it. In particular, mobile advertising is facing great changes in dealing with Smart devices. However, the basic outline of mobile advertising still mostly resembles advertising strategies centered on feature phones. Despite the fact that Smart device-based mobile advertising has several strategic differences from the existing advertising method, currently there is insufficient research dealing with the appropriate advertising strategy and effectiveness in a Smart environment. The purpose of this study is to develop an effective mobile advertising strategy framework in a Smart environment by analyzing mobile advertising effects based on Smart devices and by deducing the characteristics of smart device-based adverting. To do so, a new combined advertising model suitable for the Smart generation was developed through the existing representative advertising effect theories, Davis’ TAM (1986) and DuCoffe’s web advertising effect model (1996). In conclusion, this study suggests a new advertising effect model by combining the DuCoffe model and TAM model, and on this basis contributes to the establishment of a suitable advertising strategy for a Smart environment.

Recently people do not only use mobile phone to call, but also use it to send a SMS. However, it is difficult to express own complicated emotion with text and emoticon of exited SMS service. We pay attention to express user’s emotion interesting and correct, we use character animation. This paper suggests emotion based gesture animation generation system that uses character's facial expression and gesture to delivery emotion excitably and clearly. Michael[1] investigated interview of two people who has stylized gesture. They suggested gesture generation graph for stylized gesture animation. In this paper, we focus to analyze and extract emotional gestures of Disney animation characters and create 3D models of extracted emotional gestures. To express emotion of person, we use emotion gesture generation graph that import the emotion flow graph that expresses emotion flow for probability. We investigated user reaction for research proprieties of suggested system and the alternation propriety.

Due to Thai government policy give tablets to first grade students for use in learning and teaching. Mobile-augmented reality is used to help teach a powerful one. However, the most application programs are applied in English when used with the Thai alphabet is a decrease in performance. Therefore, we are developing template matching base-on ARToolKit used for Thai alphabet learning on mobile augmented reality. Especially, we are focusing on improvement character recognition for Thai alphabet learning, which enables extract character image as marker from mobile camera. To increasing the recognition rate of Thai alphabet base on ARToolKit by group similar shape for identifying each group of character. To dissimilarity, we propose a structured template matching technique for recognizing features such as knot of character. In this paper, we describe an abstract of our proposed method and present its experimental results.

To date, most e-learning systems have not reflected emotion of users effectively as against off-line learning (system) that has sufficiently considered it. They might cause several prob-lems hindering e-learning from effectiveness. Overcoming this weakness, we introduce a methodology that measures user’s brain wave and recommends learning content to user based on it. In this paper, we assume that a person would have similar tendency with some-one whose brain wave patterns are like his, and use it for recommendation of learning con-tent type. As a technique for our experiment, we use kNN-Recommendation, learning content type recommendation system, based on brain wave data that appears in studying. Our system can solve cold-start problem that occurs in typical recommendation system and we addition-ally propose harmony value for better accuracy of recommendation that is calculated with recommended values from preceding our profile based recommendation system. We check advanced performance using several experiments.

With the development of social networking sites, the need to manage privacy levels has been demanded by many users and discussed by many researchers. Due to the fact that a large number of users of these sites are children, this need is becoming even more pressing. Protecting online privacy is crucial, especially for children who do not have the knowledge, ability and awareness to avoid risks caused by privacy breaches. This paper presents and evaluates a tool called PrivacyDoc that will help parents control their children's privacy level and recommend a suitable level of privacy. This tool has been implemented and its usability has been tested based on the user's point of view.

In this paper, we propose a new hybrid intelligent modeling using context clustering and Extreme Learning Machine (ELM) mechanism. It has been a sensitive issue that the ELM mechanism assigns initial parameters randomly, despite of its superior performance. The proposed approach focuses on initial parameters determination of the modeling to improve the accuracy of the ELM mechanism, through removing randomness of assignment. To accomplish it, a context clustering based on Gaussian Mixture Model (GMM), considering a relationship between input-output spaces will be adopted to a Radial Basis Function Network (RBFN) of the ELM. In addition, the proposed approach will reduce the randomness of results from the original ELM. Simulations and the results show usefulness of the proposed approach with improved performance accuracy.

Cardiac telemedicine systems facilitate treatment of patients by sending blood pressure and cardiac performance information to hospitals and medical emergency care units. Location-based services can be used in mobile cardiac telemedicine systems to improve efficiency, robustness and accuracy. This paper proposes a combination of mobile telemedicine systems and location-based services that will enable hospitals and emergency departments to do continuous monitoring of a patient’s heart activity; such a system would decrease the probability of critical condition patients in emergency cases and increase the chance of saving lives. In order to evaluate whether this kind of health care system might work, we explore the success factors for such a system by adapting the DeLone & McLean IS success model to the context of location-based mobile system in cardiac healthcare. After reviewing previous works, we identify fourteen factors which can affect the success of a location-based mobile cardiac telemedicine system: Realization of user expectations, Portability, Accessibility, Extent of data processing, Time response, Urgency, Currency, Sufficiency, Understandability, Reliability, Extent of Mobility (spatial, temporal, contextual), System support, Responsiveness, and Assurance. We apply these factors to propose a success model for our location-based mobile cardiac telemedicine system.

Since information systems for providing only Boolean search do not provide prioritized search result, users have to carry out time-consuming checking for lots of results one by one. The method proposed in this study is to provide search result prioritized by using coupling information between tags instead of index weight information in Boolean search. Since document queries are used instead of general user queries, key tags to be used as queries in a relevant document are extracted. A variety of groups of Boolean queries depending on tag couplings are created in the process of creating queries, and prioritization is processed by means of differentiation information between relevant query groups, and tag significance information in the process of matching. The proposed method was applied to the process of finding related trend analysis information for the emerging technology information consisting of 1500 technologies to prove the usability of the proposed method.

For the personalized learning, a good testing method, which can effectively estimate a learner’s proficiency, is required. In this paper, we propose a novel testing method, Bayesian network-based approach to Computerized Adaptive Testing (CAT). Our novel approach can estimate proficiency of the examinee effectively and efficiently because it reflects complicated relationships between all items and their categories, and can estimate detailed proficiency about each specific category. In experimental results, we show that our approach can improve accuracy and speed of estimating examinee’s proficiency as compared with classical testing methods like paper-based test and conventional IRT-based CAT.

An e-mentoring system is an online tool that enables interactive mentoring between a mentor and a mentee, regardless of place and time differences. This paper discusses the system design of an e-mentoring system for Malaysian orphans, called MyMentorMentee.com. The design of MyMentorMentee.com is an adaptation of Keller's ARCS Motivational model and uses its motivational elements to provide an effective mentoring experience for each session. A (attention), R (relevance), C (confidence) and S (satisfaction) are the four components of the ARCS motivational model. Keller’s model provides techniques for solving the motivational problems faced by a learner during the learning process. The purpose of MyMentorMentee.com is to study how an e-mentoring system can overcome the motivational challenges faced by orphans which were identified during the preliminary study. Among these are personal issues and learning issues. The system was developed to help mentor and mentee to carry out the mentoring session using alternative (web-based) way at anytime and anywhere. The system that we have designed has 4 modules: personal profile, text messaging, mentoring schedule, and personal video chat. All modules were evaluated using quantitative and qualitative techniques.

Many people from various sectors are now talking about the “Smart” things such as devices for work, home, education, and so on. Smart is another word for intelligence. Smart learning can be defined as a quite innovative way of getting the knowledge, especially in advanced science and technologies. Smart learning environments are always connected with WiFi, 3G and 4G and provide a learners' paradise where they can learn anywhere and anytime whatever they want to learn. In this paper, we have developed a computer simulation-based smart learning system called EDISON (EDucation-research Integration through Simulation On the Net) for supporting the area of CFD (Computational Fluid Dynamics). The EDISON system could be used by the curious learner, much like Thomas Alva Edison who lived in the 19th century and liked to do all kinds of experiments to verify or discover answers to his curiosities or to solve problems. We who are living in the 21st smart century can do many experiments like those done by Edison through computer simulations in a smart learning environment using EDISON. In addition, we explain in detail how we have been motivated to develop the EDISON system, what kind of functionalities and architecture it has, how the system is serviced, and how we plan to expand our system in the future.

Unicode 6.1 (2012) had encoded more than 74,000 Han characters. This great repertory could solve the problem of unencoded Han characters to a significant extent. However, most information systems today still only support input and display of the first 20,902 encoded Han characters in Unicode 1.0 (1991). Even in latest systems, designed to support 32-bit Unicode and with suitable fonts installed, it is not easy to use these newly encoded Han characters. We note that many of these newly encoded Han characters are rarely used in users’ everyday life. An ordinary user may have confusions of their glyph shapes, pronunciations, meanings, and usages. IMEs (input method editors) for Han characters usually require users to have good knowledge of wanted Han characters. It is not unusual users try but fail to input unfamiliar Han characters. In this paper, we present an auxiliary Unicode Han character lookup service by radicals. One can use any Han character IME to key in one or more radicals to look up a wanted Han character. Every Unicode Han character is decomposed as a glyph expression of radicals. The similarity between the glyph expression and user input is estimated by a derived edit distance algorithm. The most similar Unicode Han characters are returned. As a result, the system provides users a convenient way to look up unfamiliar Unicode Han characters.