Social-Media-based Lifelong Learning (SMLL) have come under the spotlight nowadays because they allow people to realise lifelong learning in their quotidian existence. However, the factors that determine SMLL have received little scholarly attention, hence our poor understanding in this regard. To remedy the deficiency, a research model was developed through Maslow’s need hierarchy theory to address the issue. The research findings show that (1) safety needs play an initial role that drives users gradually towards belongingness and love needs, self-esteem needs and self-actualisation needs; (2) self-actualisation needs serve as a sole pivotal role in users’ satisfaction with SMLL, which in turn affects their continuance intention towards SMLL. These findings reveal that social media not only allow people to safeguard their jobs by offering access to the latest knowledge but also help them fulfil their ambitions and realise their self-worth. This study also challenges the stereotypes about Maslow’s need hierarchy theory by showing that the levels of needs are not necessarily to be fulfilled in ascending order but can be satisfied simultaneously.

Artificial intelligence (AI)-based text-to-image technologies have recently gained considerable attention, but their specific applications for educational purposes remain relatively unexplored. This research aims to bridge this gap by developing a theoretical model that combines constructs from the Expectation Confirmation Model (ECM) with the Technology Acceptance Model (TAM) to understand the sustainable use of AI-driven visual synthesis in design ideation. Data was collected via a survey involving 106 vocational university students who were enrolled in a user interface (UI) design course to test the proposed model. The hypotheses analysis demonstrated that confirmation positively influenced perceived usefulness, perceived ease of use, and satisfaction. Furthermore, perceived usefulness had a positive impact on satisfaction. Students’ perceptions of the utility, usability, and satisfaction of AI-driven visual synthesis also positively affected their intention to continue using the technology. However, the hypothesis proposing a positive relationship between perceived ease of use and user satisfaction did not find support. A moderation analysis revealed that novice design students were susceptible to effort expectancy, negatively affecting their satisfaction with the technology. These findings offer valuable practical implications for developers, designers, and instructors interested in utilizing AI-driven visual synthesis for educational purposes in UI design.

Visualization influences the collaborative design process and design thinking (DT) education outcomes. Accordingly, digital visual collaborative learning (DVCL) technology has great potential to facilitate students’ remote collaborative design experiences. This study investigates the fitness of DVCL for DT learning activities and the factors influencing students’ continued use of the technology with a model integrating technology acceptance model (TAM) and design task-technology fit (DTTF). The research findings demonstrate that the perceived usefulness of the technology is the primary direct factor influencing the continuance intention toward the technology. In addition, the DTTF mediated by perceived usefulness and ease of use significantly affected the intention to continue using the technology. The visual characteristics of the technology influenced the DTTF in the collaborative design environment. This study highlights visualization as a critical feature of collaborative learning in DT education and provides implications from both theoretical and practical perspectives.

The affordance of immersive virtual reality (VR) holds great potential for education, supporting learning through simulation and visualization. However, the literature on STEM education indicates that VR learning is not necessarily more effective than traditional learning, because participants are immersed in learning environments with high visual loads, which increases cognitive load, resulting in poor learning outcomes. In addition, VR studies rarely evaluate learner performance in physical hands-on activities after participating in VR learning programs. Therefore, in this study, we seek to reduce cognitive load by incorporating feedback into the VR learning environment. This study conducts a quasi-experiment and proposes a VR learning environment for embedded electronic circuits and a practical hands-on task, to investigate learners’ learning performance on practical hands-on task skills and their cognitive load. Participants were randomly assigned to groups with and without feedback. The results show that feedback in the VR environment is effective in reducing participants’ extraneous cognitive load and increasing engagement, with fewer trial-and-error times in the learning units and better performance in the physical hands-on task.

Speech-to-text recognition (STR) usage in lectures in English as the medium of instruction (EMI) has been recognized as an assistive technology, but previously reported studies have neglected to investigate the benefits of speech-enabled language translation (SELT) for learning. This study used either STR or SELT to help students in EMI lectures, specifically to increase their attention and meditation and also to decrease their learning anxiety. In this study, we used a mixed research method and collected the data as perceptions and mental state. Sixty-three students attended the lectures and they were categorized into two groups. Students in the STR group (n = 30) were exposed to STR texts, whereas the students in the SELT group (n = 33) were exposed to SELT texts; the affective factors in their learnings were also compared. The results showed that on comparison the attention and meditation levels in the SELT group were higher than those in the STR group, the learning anxiety decreased in lectures with SELT support, and the SELT group positively perceived the usefulness of SELT for learning. Based on the findings of this study, implications were drawn and suggestions were provided.

The main objective of engineering education is to cultivate students to possess capabilities demanded by industries. Of capabilities, creative thinking is the most crucial one. Generally, art-related fields are classified with high creativity while science and engineering are classified as a field dealing with numbers, calculations and realistic phenomena. However, the real-world situation is that students majoring in science and engineering need the skill of creativity to face emerging complicated engineering problems. Our question is that: can art foster creativity of students majoring in science and engineering? This study is to explore link of art and creativity of mater students in science and engineering through the experience of interactive art and aesthetic sense to realize its effect on creativity by using the Processing Software and Leap Motion to create visual and music interactive art works. The total of 70 subjects are students in Colleges of Science and Engineering and College of Electronical Engineering and Computer Science from a university in Taiwan. The research measurement tools are Abbreviated Torrance Test for Adults (ATTA) for pretest-posttest research design and the Study Preference Questionnaire (SPQ) to differentiate the cognitive styles. Using descriptive statistics, One-Sample t test, Paired-samples t test, One-Way ANOVA and Pearson Correlation etc. for statistical analysis. Our findings indicate that students in science and technology fields, their creativity falls on average standard (Creative Index, CI), not particularly outperforming. Different genders, cognition styles and different institutes and colleges of master’s degree students in science and technology demonstrated also no significant differences in creativity. Nevertheless, after introducing the experience of visual and music interactive art works, it has significant effect on the creativity of students in science and technology. The study may provide a cross path of art, science and engineering in STEAM education if conducted further.

In this study, we compared the effects of speech-to-text recognition (STR) versus speech-enabled language translation (SELT) on comprehension of lecture content in a foreign language. When the instructor lectured in a foreign language, the STR system generated texts from the voice input and showed them to control students. During the SELT process, in addition to the STR function of receiving speech input from the instructor, CAT translated the STR output from a foreign language into native language of the students, and displayed it to experimental students. We compared post-test results of the control and experimental students. Our results showed that the experimental students outperformed the control students on the post-tests. Based on our results, some implications were made.

We applied a speech-to-text recognition (STR) and computer-aided translation (CAT) systems to support multi-lingual communications students participating in cross-cultural learning project. The participants were engaged in interactions and information exchanges in order to learn and understand cultures and traditions of their peers. Their communications were carried out in their native languages on social communication platforms. The participants spoke and STR system generated texts from their voice inputs. CAT system then simultaneously translated STR-texts into English. Finally, translated texts were posted on social communication platforms along with spoken content in the participants' native languages. We aimed to examine accuracy rates of processes associated with STR and CAT for different languages during multi-lingual communications in our cross-cultural learning project. In addition, the feasibility of our approach to support multi-lingual communications in cross-cultural learning project was investigated. Our results showed that the lowest accuracy rate was for Mongolian and Filipino and the highest was for Spanish, Russian, and French. Our results also demonstrated that cross-cultural learning took place, the participants understood and were able to explain foreign traditions to others as well as to compare foreign traditions with their own local. Based on our results, we made several suggestions and implications for the teaching and research community.

We provide texts generated by speech-to-text-recognition (STR) technology for non-native English speakers during lectures in English. We aim to test the feasibility of our approach. Our results show that participants who learned with STR-texts outperformed those who learned without them. Results also show no significant effect of STR-texts on post-test scores of the low and high ability participants after controlling for the effect of learning ability. Besides, there is no significant difference in cognitive load and anxiety of the low and high ability participants. Based on our findings several implications are made for the teaching and research communities.

This study aimed to explore the effectiveness of applying the speech-to-text recognition (STR) technology during lectures in English on learning performance of non-native English students. Furthermore, how useful texts generated by the STR for students of different English as foreign language (EFL) ability during different difficulty level lectures was explored. For this reason, one experiment was carried out in this study. Two lectures, one is intermediate difficulty level lecture and the other is advanced, were administered in a traditional classroom and the STR was adopted to aid students' learning. Results of this study showed that students who used STR-generated texts outperformed students who did not use them. According to students, STR-texts were useful to follow the instructor, clarify some words, confirm what the lecturer has said, make up missed information, and enhance understanding. It was found that STR-texts were beneficial for learning of low EFL ability students during both lectures while high EFL ability students only used STR-texts during the advanced level lecture. Based on these results, several suggestions and implications for teaching and research community are proposed in this study.

This study aimed to evaluate how differently co-located users perform and interact while solving problems by using existing and newly developed interaction mechanisms of a multi-touch tabletop system on a large-size tabletop display. Furthermore, this study aimed to investigate users’ perceived situation awareness due to the system. This study conducted one experiment and introduced three newly developed interaction mechanisms: two-way rubber band, drag-and-response, and centre collection area. Two-way rubber band enables users not only to send but also to request digital objects. Drag-and-response allows users to accept or to reject digital objects sent by others; therefore, it eliminates conflicting situations and interference. Centre collection area stores, organises, and manages shared digital resources on a surface of a tabletop display, so that users have an overall picture of available resources. This paper discusses results of an experiment, research findings, and implications along with conclusions and several suggestions for future development and research.

In this study, a multimedia e-book system is built and its use monitored in an empirical study investigating various factors which effect learners' reading preferences. 69 fifth-grade students participated in this experiment, one student with an attention deficit hyperactivity disorder was excluded. After three weeks of learning activities, we found that there are differences in browsing patterns, navigation facilities, and annotation patterns in terms of gender. In the cognitive style, holists use bookmarks (tags made by the learner) to navigate more than serialists. Also, regarding annotation patterns, there are statistically significant differences related to the degree of the user's prior knowledge. Parts of the results are similar to those found in previous research, as well as some interesting findings. The findings of this study contribute a deeper understanding of the relationship between human factors and the usage of e-books. This understanding can be applied to develop adaptive e-books that can accommodate learners' individual differences.

One major drawback of previous research on speech-to-text recognition (STR) is that most of their findings showing an effectiveness of STR for learning in traditional classroom were based on subjective evidences. Very few studies have used eye-tracking techniques to investigate visual attention of students on STR generated text. Furthermore, not much attention was paid to learning differences (i.e. Learning ability) to use STR-text. Therefore, this study carried out one experiment in which participants' visual attention on STR generated text during lectures was investigated by employing eye-tracking technique. Besides, how differently effective STR-text can be to influence participants' learning achievement was tested. Furthermore, this paper discusses results, research findings, and implications along with conclusions and several suggestions for future development and research.

With an experience in the development of web-based learning, mobile learning, and web 2.0-based learning, we have seen an emerging trend in the integration of web 2.0 technology into mobile learning, so called Mobile 2.0 Learning. By analyzing previous studies with the model of social cognitive theory, we reveal that their integration is not in conflict with each other; in contrast, Mobile 2.0 Learning may reframe the relationship between environments inside and outside of school. The social interactivity of Web 2.0 can improve students’ sense of community and collaboration in mobile learning. Mobility and context capturing facilities can support learners to exchange information in daily life and further develop context-specific competences in an informal social community. This study first introduces the components of Mobile 2.0 learning and its unique characteristics. Next, the key elements driving Mobile 2.0 were illustrated by an example to show their processing flow. Finally, further research issues of Mobile 2.0 learning were proposed. It is hoped to provide readers a potential research blueprint by this study.

Classroom observation is a way for teachers to better understand and thus improve what happens in their classes. Reading is a complex cognitive process, and one that is often difficult to observe. However, e-books present one way to overcome this problem, as they can be used to better understand students' reading strengths and weaknesses, thus making it possible to offer more effective reading guidance. Therefore, this study proposed an E-book Reading Behavior Monitoring System based on sensing technology and e-books, with the following three stages: the analysis of a real classroom situation, system design and implementation, and an evaluation of the functionality and usability of the proposed system. This system uses a webcam and touch screen with the artificial bee colony algorithm to record data of the students' reading fixation and reading rates, which can then be used as a reference by teachers to provide individual reading guidance. Finally, this study carried out a series of experiments to evaluate the usability and functionality of the proposed system through a case study, system simulation, expert evaluation and actual assessment. The results show that the proposed system has both good usability and functionality with regard to its aim.

Computer programming language is a fundamental skill for university students learning more advanced courses. However, programming courses have been regarded as difficulty courses by many students, leading to a high dropout rate. Therefore, how to enhance students learning attitude so as to improve their programming language skills becomes a challenging issue. The program of accredited courses has been promoted for over a decade and it tends to provide students achieving the purpose of self-learning. Those courses, containing videos of instructors and courseware, are digitalized on an e-learning system for facilitating learning anytime. This study tends to examine the effect of using an accredited course for programming language learning on an e-book platform which is regarded as a personalized learning device. Based on the personalization concept, a strategy of adapting the student's personalized programming language experiences has been adopted in this study. Our results reveals that with the personalized e-book device and the quality accredited programming course not only can enhance students' attitude but also promote their performance in learning the computer programming course.

This study aimed to investigate effects of unidirectional versus reciprocal teaching strategies on computer programming learning. Thus, this study conducted an experiment with participating novice programmers, who applied no strategies, unidirectional, and reciprocal teaching strategies for computer programming learning by using a web-based learning system (VPen). Yet, this study explored participants' perceptions toward the VPen system and the strategies. The paper reports results of this study as well as it provides useful suggestions on application of the strategies by using the VPen for teaching and research community of this field and for future studies.

The popularity of social networking has changed interactive relationships between people. The development of mobile devices has further provided diverse communication channels for social networking websites. The rich resources in virtual communities, instantaneous feedback, and sharing of information have led many studies to apply it in the instructional environment of collaborative learning. This study uses Google plus as the learning platform, Tablet PC as the learning device, and group investigation (GI) as the collaborative learning instructional strategy, introducing it in the public health nursing practice course in nursing school. The experiment shows that learners using the Google plus system to carry out GI collaborative learning have better learning effects than engaging in GI instruction with traditional paper books. Most learners and instructors hope that future courses can be conducted in this way for learning.

Contemporary E-learning research tends to se parately evaluate the effectiveness of mobile learning or web 2.0-based learning. Although the independent use of these technologies in the short term reveals substantial research value, in the long run, if we can integrate the various technologies according to their tool-specific features, this combination will be able to bring students greater learning benefits than their individual use. By means of reviewing and comparing both aspects of research articles published in six major SSCI journals from 2006 to 2010, this study primarily aimed to understand the individual current mobile and Web 2.0-based learning research. The results should be helpful for researchers in identifying interesting topics for further exploration. A comparative analysis of both literature tracts could then predict the potential benefits of integrated use of different technologies, suggest practical recommendations for implementation, guide the direction of educational applications, and provide effective instruments for evaluation.

In recent years, under the concern of energy crisis, the government has actively cooperated with research institutions in developing smart meters. As the Internet of Things (IoT) and home energy management system become popular topics, electronic appliance recognition technology can help users identifying the electronic appliances being used, and further improving power usage habits. However, according to the power usage habits of home users, it is possible to simultaneously switch on and off electronic appliances. Therefore, this study discusses electronic appliance recognition in a parallel state, i.e. recognition of electronic appliances switched on and off simultaneously. This study also proposes a non-invasive smart meter system that considers the power usage habits of users unfamiliar with electronic appliances, which only requires inserting a smart meter into the electronic loop. Meanwhile, this study solves the problem of large data volume of the current electronic appliance recognition system by building a database mechanism, electronic appliance recognition classification, and waveform recognition. In comparison to other electronic appliance recognition systems, this study uses a low order embedded system chip to provide low power consumption, which have high expandability and convenience. Differing from previous studies, the experiment of this study considers electronic appliance recognition and the power usage habits of general users. The experimental results showed that the total recognition rate of a single electronic appliance can reach 96.14%, thus proving the feasibility of the proposed system.

The Internet of Things (IoT) interconnects Internet and end device networks connected by identification information, which not only extends and explores the range of the Internet, but also constructs bridges of communication between realistic objects and the Internet. With increasing awareness about the energy crisis, the development of intelligent energy-saving systems has become a new trend in all circles. This work proposes an appliance-aware activity recognition mechanism for an IoT energy management system, and especially an intermediate management service layer for the conformability of current household appliances, which not only establishes communication services among various appliances, but also provides services for upper-layer application based on a service-oriented architecture. Further, the presented system has the capability to deduce human activities from appliances being used and the variation of their states, and provide energy management services. In other words, the system can identify home activities at present, and notify users what unused appliance is or turn them off automatically. According to experiment results, improving the usage behaviour of appliances by means of a remainder system improves the efficiency in saving household electricity.

Clustering has emerged as an important tool for discovering the structure of data. Among the clustering methods, fuzzy c-means (FCM) has increased its wide attention in recent years. Owing to the huge amount of data, the existence of uncertainty in the dataset, computational complexity and noise-corrupted data, the FCM algorithm finds it difficult to produce a good clustering result. This paper proposes effective objective functions of FCM with the combination of entropy function, tolerance and kernel distance functions in order to effectively cluster the more complicated data into appropriate groups. This paper provides an effective way of computing membership degrees and updating cluster centers by minimizing the proposed novel objective functions. To reduce the computational time of the proposed algorithm, we develop a prototype initialization algorithm for assigning the initial cluster centers instead of random initialization. To show the effectiveness of proposed methods, we implement the proposed methods on a two-dimensional artificial dataset and more complicated synthetic control chart time series dataset. We prove the superiority of the proposed methods through the clustering validity, number of iteration and the strength of the membership.

In this study, we developed a game-based learning system on a social network platform to instruct customs and cultures in the English speaking countries in order to investigate the increase of learning willingness and motivation by using the digital game-based learning(DBGL) model. To determine the learning behaviors and results of the learning design which combines game-based and social network theories, this study involved students from an elementary school to implement a multi-player, real-time quiz game, known as 'Challenger', on the Facebook platform. As players, the learners can "Call Out" for help or assistance; however, online friends hold the decision of "Replying" or "Not to Reply" the players' "Call Outs". This mechanism is so called "Peer Feedback". Results of this study showed that the DGBL incorporated into a social network website is a feasible and sound model for teaching. By the model, English learning will become more interesting which makes students more enjoyable in learning auxiliary materials after school if they cannot fully comprehend the course in the classroom. By the outcome, we found peer influence seems not only motivates learner's participation in the game but also catalyze learning effectiveness.

SUMMARY In two‐tier high‐performance networks (HPNs), some facilities are constructed to form a powerful supercomputing environment, and to alleviate server load. Then, the applications are provided by them in co‐operated, parallel and distributed manners. A proper way to select facilities is crucial to the performance of two‐tier HPNs The problem of selecting facilities can be regarded as a kind of the facility location problem, which is to determine an optimal subset of facilities that will be open to serve users. The traditional facility location problem aims to minimize the incurred costs between the users/servers and their assigned facilities. In two‐tier HPNs, the incurred costs can be regarded as the transmission costs, e.g. transmission latency, bandwidth overhead. We observe that most of the packets are transmitted among the facilities for application servicing and framework maintaining. In this paper, we address the problem of selecting facilities in two‐tier HPNs by minimizing the transmission costs from servers to users by passing through the selected facilities. Our problem is different from the traditional facility location problem, which only considers the transmission costs between the users/servers and their assigned facilities. In our problem, the transmission costs between the selected facilities are further considered. The problem is formulated as a 0/1 integer non‐linear programming (0/1 INLP) and 0/1 integer linear programming (0/1 ILP). Further, a simple heuristic algorithm is proposed for obtaining a feasible solution when the network sizes increase, since solving INLPs and ILPs for large‐scale problems takes long time. Copyright © 2010 John Wiley & Sons, Ltd.

In this study, we implemented a digital game-based learning (DGBL) system over Face book platform. For better understanding the impact of DGBL applied to social networking, the technology acceptance model (TAM) was employed for the evaluation. Results of this study showed that the DGBL incorporated into a social network website is a feasible and sound model for teaching. This study investigated the potential important design issues of the application over a social network website. It is believed that this study could bring teachers a better understanding how those characteristics of social networks can attribute to the success of users' learning.

For the recent years, the Taiwan government has been investing in National e-Learning and Digital Archives Program constructively, it makes Digital Content become rising and flourishing, and inject a new tidal current of medium into Taiwan's culture, especially in virtual reality (VR) is one of the key projects. The purpose of the study is to investigate and explore the Taiwan research work of academic VR fields in 2000s. This study used the "Taiwan Digital Library of Theses and Dissertations" as inspection tool, content analyses the papers that titled with "virtual reality". 274 papers were adapted from 2001 and 2010. Four findings were concluded, the result of this research will offer the trend of VR as the result for the reference of the further study.

Parallel structures may be used to increase a system processing speed in case of large amount of data or highly complex calculations. Dynamic Voltage and Frequency Scaling (DVFS) may be used for simpler calculations in order to decrease the system voltage or frequency and achieve lower power consumption. Combining these two mechanisms may lead to higher efficiency and lower power consumption. In this paper, we introduce a parallel decoding process with Digital Signal Processing (DSP) for power efficiency in a heterogeneous multi-core embedded system. We describe a parallel low-power design on the system level. Under the condition of preserving the original decoding process, we manage the size of the system's multimedia buffer by considering the spontaneous streaming transfer and tuning the decoding process scheduling time by using the DVFS system in order to decrease the multimedia data dependency and achieve a multi-core embedded system with accurate and low-power detection mechanism.

Multimedia video sharing has been developed rapidly over the past years. P2P multimedia sharing mechanisms for P2P network such as PPLive, PPStream, Joost, have been used popularly. However, if Content Server and Client in the home network have to transmit via P2P sharing, P2P network must be adopted, thus it is unable to increase the network transmission speed through this intranet connection. Although there are DLNA, HAVi, and Jini protocols in the home network to share multimedia files, it cannot access P2P network due to the limitation of home network framework. Therefore, this paper extends the DLNA-based multimedia sharing system to P2P network on OSGi frameworks, so that users can access multimedia resource on P2P Network via DLNA, and P2P network users can apply P2P network mechanism in OSGI bundle to access shared DLNA multimedia resource in the home network.

This paper presents a collaborative mobile learning system: Mobile Virtual Campus (MVC) powered by the loction-based dynamic grouping algorithm. The MVC system has been developed to provide an innovative and interactive platform for online mobile learners by utilizing the location awareness and other built-in sensory compoments in mobile devices. On the platform, the mobile learners can learn collaboratively and interactively either at a distance or face-to-face in the mobile learning environment.

Lack of overall ecological knowledge structure is a critical reason for learners' failure in keyword-based search. To address this issue, this paper firstly presents the dynamic location-aware and semantic hierarchy (DLASH) designed for the learners to browse images, which aims to identify learners' current interesting sights and provide adaptive assistance accordingly in ecological learning. The main idea is based on the observation that the species of plants and animals are discontinuously distributed around the planet, and hence their semantic hierarchy, besides its structural similarity with WordNet, is related to location information. This study then investigates how different cognitive styles of the learners influence the use of DLASH in their image browsing. The preliminary results show that the learners perform better when using DLASH based image browsing than using the Flickr one. In addition, cognitive styles have more effects on image browsing in the DLASH version than in the Flickr one.

This paper presents a case study of one teacher and 28 first-grade primary students utilizing the interactive whiteboard (IWB) and computer feedback system (CFS) to improve the group works in their language learning activities. The classroom observation and a content analysis method were conducted for investigating the teaching and learning interactions, and total 72 instructional events were considered to be the data in the coding procedure. The results indicated that 44.44% of instructional events embraced students’ learning interest, active participation, and peer cooperation behaviors, which reveal the students were very engaged in the cooperative group works. Consequently, the IWB plus CFS improved the teaching and learning interactions, especially on whole-class discussion and cooperative group work, in which student’s concept was constructed by those efficient dialogic interactions among teacher and students.

The booming of information technology has influenced the evolution of learning patterns and the integration of information technology into teaching has became one of the mainstream methods. The teaching and delivery of knowledge are no longer restricted to traditional lectures. As Learning Management System (LMS) at the present stage can accommodate a diversity of learning requirements and functions, there are many literatures to study on the application of the LMS. However, as the development of relevant industries and technologies, users’ requirements on the LMS may be influenced and changed. How will these changes affect the development of the LMS? What are the changes and developments of the LMS required for addressing the current and future requirements of the users? To address these questions this study aims to perform a comprehensive investigation on the technologies, applications, and analysis of the LMS to realize the developments of the LMS.

This study designs and implements a cross-platform, cross-domain P2P multimedia sharing system in the Taiwan Advance Research and Education Network. The system allows users to easily access the multimedia resources of the entire network from any network node, and all multimedia providers can share local multimedia resources from any location on the entire network. Moreover, this is a Peer-to-Peer based transmission architecture model, thus, users can easily maintain the network, and enhance the service quality and efficiency of the entire network through relevant mechanisms.

As wireless networks have been widely deployed for public mobile services, predicting the location of a mobile user in wireless networks became an interesting and challenging problem. If we can predict the next cell which the mobile users are going to correctly, the performance of wireless applications, such as call admission control, QoS and mobility management, can be improved as well. In this paper, we propose a mobility prediction algorithm based on dividing sensitive ranges. The division is in accordance with the cell transform probability. Then different prediction methods are applied according to the sensitivity of the range to gain high precision. Simulations are conducted to evaluate the performance of the proposed scheme. As it turns out, the simulation results show that the proposed scheme can accurately predict the location for mobile users even in the situation of lacking location history.

With large network coverage, high transmission rate, strong quality of service (QoS) assurance and inexpensive deployment cost, mobile WiMAX has emerged as one of the most promising broadband wireless access technologies. However, resource management is still a challenging issue between system capacity and user gratification, especially for multimedia transmission which ordinarily requires strict delay constraints. In this study, the authors propose an adaptive call admission control in order to efficiently increase system capacity. The control mechanism can admit an incoming video on demand (VOD) connection establishing even without sufficient idle slots/bandwidth to meet the QoS requirement. With consideration of the existing VOD user stream buffer (USB), our scheduling mechanism performs adaptive admission control and QoS provision feasible each time. Also employing adaptive modulation and coding (AMC) scheme, each connection keep its fluency of real-time video performance over dynamic wireless channel status. The authors evaluate the concurrent stream connection number and connection blocking probability with different resource management strategies.

Abstract CBR (constant bit rate) traffic is expected to be an important traffic source in wireless networks. Such sources usually have stringent jitter or delay requirements and in many cases they should be delivered exactly as they were generated. In this paper, we propose a strictly guaranteed QoS (quality‐of‐service) provisioning CAC (call admission control) scheme with a polling‐based scheduling policy for CBR traffic in IEEE 802.11e wireless LANs. Under such a scheme, the proposed transmit‐permission policy for HCCA (HCF controlled channel access) method can forecast the maximum suffered delay for each packet and derive sufficient conditions so that all the CBR sources satisfy their time constraints to provide deterministic QoS guarantees. A simple analytical model is carried out to estimate the average queueing delay of the proposed scheme. In addition to theoretical analysis, simulations are conducted to validate its promising performance. Our simulation results show that the proposed scheme maintains a high throughput with respect to the whole range of system load. Copyright © 2009 John Wiley & Sons, Ltd.

In this paper, we proposed a backoff mechanism to improve the performance of initial ranging for the IEEE 802.16 standard. In the proposed scheme, the size of contention window in the initial ranging is combined with exponential and linear backoff mechanisms, and it is adjusted based on the current network environments. In addition, a threshold in the proposed scheme is set to find out the current network situation. If the contention window size is smaller than the threshold, the contention window size is tuned exponentially in response to a light network traffic load. On the other hand, when the contention window size is larger than the threshold, the contention window size is tuned linearly in response to a congested scenario. The numerical simulation results show that the proposed scheme can achieve a better performance in terms of collision rate, average access delay, and system throughput in both light and congested environments.

In the vehicular environment, the transmissions of signals have to face the higher challenges then indoor wireless local area networks (WLAN). Multipath fading cause high bits error rate (BER), in such an unstable transmission environment. And high BER cause high dropping probability of packets. In order to reduce the dropping probability of handshaking packets without increase the capability of infrastructures, a mechanism is proposed in this paper. In our work, we altered the traditional cyclic prefix (CP) into a variable cyclic prefix (VCP) of request to send (RTS) frame and clear to send (CTS) frame, and reduce the handshaking packets error rate in vehicular wireless transmissions, hence we can improve the contending ability in Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) at vehicles to infrastructure (V2I) transmission., By analyzing environment parameters, we can predict the suitable VCP time slots and dynamic adjust VCPs. And we can competently eliminates the impacts of Intersymbol interference (ISI) caused by multipath fading in CSMA/CA.

In a traditional intercom system that only allows place-to-place communication in a house, it is necessary to dial the extension number of a specific family member, or dial each extension number individually via the intercom broadcasting, in order to reach the desired person. Additional master stations controlled the intercom system are required, and it is load to maintain the stations for general users. In order to solve these problems, we propose the digital living network alliance (DLNA) compatible family intercom system (DFIS): the architecture to support user mobility. This architecture makes it possible to quickly reach a family member without the knowledge of the extension number that caters to a fixed location. In other words, it will be not necessary to dial the extension number of the location of the desired person. We introduce call control and phone handling under the subject of DFIS architecture and demonstrate that the proposed DLNA family intercom device and DLNA family intercom adaptor can work well.

Identification of characters in films, although very intuitive to humans, still poses a significant challenge to computer methods. In this paper, we investigate the problem of identifying characters in feature-length films using video and film script. Different from the state-of-the-art methods on naming faces in the videos, most of which used the local matching between a visible face and one of the names extracted from the temporally local video transcript, we attempt to do a global matching between names and clustered face tracks under the circumstances that there are not enough local name cues that can be found. The contributions of our work include: 1) A graph matching method is utilized to build face-name association between a face affinity network and a name affinity network which are, respectively, derived from their own domains (video and script). 2) An effective measure of face track distance is presented for face track clustering. 3) As an application, the relationship between characters is mined using social network analysis. The proposed framework is able to create a new experience on character-centered film browsing. Experiments are conducted on ten feature-length films and give encouraging results.

Abstract IEEE 802.11 protocol supports adaptive rate mechanism, which selects the transmission rate according to the condition of the wireless channel, to enhance the system performance. Thus, research of multi‐rate IEEE 802.11 medium access control (MAC) performance has become one of the hot research topics. In this paper, we study the performance of multi‐rate IEEE 802.11 MAC over a Gaussian channel. An accurate analytical model is presented to compute the system saturation throughput. We validate our model in both single‐rate and multi‐rate networks through various simulations. The results show that our model is accurate and channel error has a significant impact on system performance. In addition, our numerical results show that the performance of single‐rate IEEE 802.11 DCF with basic access method is better than that with RTS/CTS mechanism in a high‐rate and high‐load network and vice versa. In a multi‐rate network, the performance of IEEE 802.11 DCF with RTS/CTS mechanism is better than that with basic access method in a congested and error‐prone wireless environment. Copyright © 2008 John Wiley & Sons, Ltd.

In recent years, 3D virtual reality technology has been growing fast. The user interface of the Internet is facing a new challenge. Many organizations have begun to propose various kinds of specifications and standards for Web3D. The specification draft of VRML1.0 was proposed in 1994. In 2000, Java3D, Extensible 3D (X3D) and MPEG-4 Binary Format for Scene (BIFS) were formally included as important components of Web3D development by the Web3D Consortium. Quickly developing information science and technology have been shortening the half-life of knowledge. The time and the cost have become important factors in developing programs and software. Among all kinds of platforms and compiling devices, the portable bytecode of Java can reduce the waste caused by different platforms. Java technology is growing up, and its compression and security technology have improved in recent years. All of these aspects serve in making Java extremely competitive in the future. This research uses Java and Java3D API to develop a Web3D virtual reality learning environment, and proposes the development of techniques and praxis from four aspects; the virtual scene construction, learning history record, file compression technology, and security. Designers will be able to use this particular VR as a reference for developing Web3D virtual reality in the future.

Web-based programming has become a popular and vital issue in recent years. The rapid growth of various applications not only demonstrates the importance of web-based programming, but also reveals the difficulty of training relevant skills. The difficulty is owing to the lack of facilities such as online coding, debugging and peer help to assist the students in promoting their cognitive development in web-based programming. To cope with these problems, in this paper, a web-based programming assisted system, “WPAS”, is proposed, which is able to support five programming activities with various difficulty levels of cognition based on Bloom’s cognitive taxonomy. WPAS provides online coding, debugging and annotation tools to conduct the training and peer assessment for web-based programming. Experimental results of 47 undergraduate students show that the innovative approach is helpful to the students in improving their cognitive development in Web-based programming. In addition, according to the results of the questionnaire, most of the participants perceived the ease of use and usefulness of the proposed system. Therefore, this study suggests that teachers could design Web-based programming activities supported by the WPAS system to improve students’ cognitive development in web-based programming.

This paper introduces a new space-time coding scheme, namely space-time complementary coding (STCC) scheme. With the help of pair-wise complementary codes, an STCC MIMO system can achieve both spatial diversity and multiplex transmission. The scheme requires neither bandwidth expansion nor feedback information from receiver, and it offers a nearly interference-free and multipath-resist performance due to a widely open interference-free window of the pair-wise complementary codes. The analytical results reveals that it provides a uniquely high diversity-multiplex gain product for its applications in flat or frequency-selective fading channel.

According to the latest version of the IEEE 802.11 standard, the backoff parameters of its collision avoidance mechanism are far from optimal, especially in a heavy load or error-prone WLAN environment. This strategy has a high collision probability and channel utilization is degraded in bursty arrivals or congested scenarios. Besides, the standard backoff mechanism may treat noise corruption as packet collisions. In this paper, we identify the relationship between backoff parameters, contention level, and channel BER in order to propose a simple, but yet well-performing distributed algorithm that allows a station to dynamically adjust its contention window size based on turn-around-time measurement of channel status. In addition to theoretical analysis, simulations are conducted to evaluate its performance. The proposed scheme works very well in providing a substantial performance improvement in heavy loaded and error-prone WLAN environments.

Multicast routing is an effective way to communicate among multiple hosts in a network. It outperforms the basic broadcast strategy by sharing resources along general links, while sending information to a set of predefined multiple destinations concurrently. However, it is vulnerable to component failure in ad hoc network due to the lack of redundancy, multiple paths and multicast tree structure. Tree graph optimization problems (GOP) are usually difficult and time consuming NP-hard or NP-complete problems. Genetic algorithms (GA) have been proven to be an efficient technique for solving the GOP, in which well-designed chromosomes and appropriate operators are key factors that determine the performance of the GAs. Limited link, path constraints, and mobility of network hosts make the multicast routing protocol design particularly challenging in wireless ad hoc networks. Encoding trees is a critical scheme in GAs for solving these problems because each code should represent a tree. Prufer number is the most representative method of vertex encoding, which is a string of n-2 integers and can be transformed to an n-node tree. However, genetic algorithm based on Prufer encoding (GAP) does not preserve locality, while changing one element of its vector causes dramatically change in its corresponding tree topology. In this paper, we propose a novel GA based on sequence and topology encoding (GAST) for multicast protocol is introduced for multicast routing in wireless ad hoc networks and generalizes the GOP of tree-based multicast protocol as well as three associated operators. It has revealed an efficient method of the reconstruction of multicast tree topology and the experimental results demonstrated the effectiveness of GAST compare to GAP technique.

Abstract In recent years, the wireless network has been attracting a lot of attentions, and due to these devices has enjoyed a tremendous rise in popularity. However, the broadcast storm becomes a very serious problem for ad hoc networks to migrate into the overlay networks for the applications of group communications. The main concept of virtual subnet technology is the capability to group users into broadcast domains, which divides a virtual subnet into logic, instead of physical, segments and reduces the traffic overhead. With this characteristic, we propose an interoperability network model integrating self‐organizing ad hoc networks and the Internet/a conventional network with the partition of physical/virtual subnets. Moreover, we describe a protocol to establish the virtual broadcast domains by using the IPv6 addressing concept in ad hoc networks and perform IP‐based network communications in a multi‐switch backbone. Since the virtual subnet technology functions by logically segmenting the network into different broadcast domains, packets can only be delivered between fixed/mobile nodes with the same virtual identity. Therefore we can prevent the broadcast storm problem in MANET. The hierarchical networks, physical/virtual subnets, addressing method, and mobility management are described, and some performance issues are evaluated. Copyright © 2006 John Wiley & Sons, Ltd.

Based on our previous work (Y. H. Kuo et al., 1999), learning patterns can be discovered and recommended to learners. This paper extends the proposed problem to handle the questionable mining results. According to the learning patterns discovered by using learning histories, it happened whenever the learners have ineffective learning behaviors, and we define them as questionable mining results. These ineffective behaviors may induce the bias suggestions. Therefore, we propose a candidate sequence set generation process to take care the stumble learning behavior.

Over the last years, we have witnessed an explosive growth of e-learning. More and more learning contents have been published and shared over the Internet. Therefore, how to progress an efficient learning process becomes a critical issue. This paper proposes a sequential mining algorithm to analyze learning behaviors for discovering frequent sequential patterns. By these patterns, we can provide suggestions for learners to select their interest learning contents. Different to other sequential mining algorithms, this study provides an incrementally method to analyze learning sequencing. More specifically, the mining algorithm in this paper can provide real-time analysis, and then report to learners for selecting learning contents more easily.

The broadcast storm becomes a very serious problem for ad hoc networks to migrate into the overlay networks for the application of group communications. The main concept of virtual subnet technology is the capability to group users into broadcast domains, which divides a virtual subnet into logic, instead of physical, segments and reduces the traffic overhead. With this characteristic, we propose a novel interoperability network model integrating a self-organizing ad hoc network and the Internet/a conventional network with the partition of physical/virtual subnets. Moreover, we describe a protocol to establish the virtual broadcast domains by using the IPv6 multicast-membership in ad hoc networks and perform IP-based network communications in a multi-switch backbone. Since the virtual subnet technology functions by logically segmenting the network into different broadcast domains, packets can only be delivered between fixed/mobile nodes with the same virtual identity. Therefore we can prevent the broadcast storm problem in MANET. The hierarchical networks, physical/virtual subnets, addressing method and mobility management are described, and some performance issues are evaluated.

Broadcasting is an elementary operation to support many applications in a mobile ad hoc network. However, naively broadcasting by flooding may cause serious redundancy, contention, and collision in the network, which we refer to as the broadcast storm problem. In this paper we propose a limited flooding scheme which takes the advantage of the cluster structure and which only requires clusterheads, initial nodes and selected gateways to forward the broadcast packets. Our approach reduces control overhead of ad hoc routing protocols significantly and introduces many benefits, including efficient flooding, density adaptation and mobility adaptation. As a result, our approach enables routing scheme in a dense and high mobility mobile ad hoc networks. Simulation shows that our approach outperforms conventional AODV in the dense network, and overmatches some existing cluster schemes such as lowest-ID or highest-connectivity cluster algorithm in the aspect of mobility adaptability.

In an ad hoc network, each mobile node plays the role of a router and relays packets to final destinations. The network topology of an ad hoc network changes frequently and unpredictable, so that the routing and multicast become extremely challenging. We describe the multicast routing representation using fuzzy Petri net model with the concept of immediately reachable set in wireless ad hoc networks which all nodes equipped with GPS unit. It allows structured representation of network topology, and has a fuzzy reasoning algorithm for finding multicast tree and improves the efficiency of the ad hoc network routing scheme. Therefore when a packet is to be multicast to a group by a multicast source, a heuristic algorithm is used to compute the multicast tree based on the local network topology with a multicast source. Finally, the simulation shows that the percentage of the improvement is more than 15% when compared the IRS method with the original method.

With the exponential growth of time to obtain an optimal solution, the job-shop scheduling problems have been categorized as NP-complete problems. The time complexity makes the exhaustive search for a global optimal schedule infeasible or even impossible. Recently, genetic algorithms have shown the feasibility to solve the job-shop scheduling problems. However, a pure GA-based approach tends to generate illegal schedules due to the crossover and the mutation operators. It is often the case that the gene expression or the genetic operators need to be specially tailored to fit the problem domain or some other schemes may be combined to solve the scheduling problems. This work presents a GA-based approach with a feasible energy function to generate good-quality schedules. This work concentrates mainly on dynamic real-time scheduling problems with constraint satisfaction. In our work, we design an easy-understood genotype to generate legal schedules and induce that the proposed approach can converge rapidly to address its applicability.

A novel diagnostic scheme to develop quantitative indexes of diabetes is introduced in this paper. The fractal dimension of the vascular distribution is estimated because we discovered that the fractal dimension of a severe diabetic patient's retinal vascular distribution appears greater than that of a normal human's. The issue of how to yield an accurate fractal dimension is to use high-quality images. To achieve a better image-processing result, an appropriate image-processing algorithm is adopted in this paper. Another important fractal feature introduced in this paper is the measure of lacunarity, which describes the characteristics of fractals that have the same fractal dimension but different appearances. For those vascular distributions in the same fractal dimension, further classification can be made using the degree of lacunarity. In addition to the image-processing technique, the resolution of original image is also discussed here. In this paper, the influence of the image resolution upon the fractal dimension is explored. We found that a low-resolution image cannot yield an accurate fractal dimension. Therefore, an approach for examining the lower bound of image resolution is also proposed in this paper. As for the classification of diagnosis results, four different approaches are compared to achieve higher accuracy. In this study, the fractal dimension and the measure of lacunarity have shown their significance in the classification of diabetes and are adequate for use as quantitative indexes.

Software standards are highly recommended because they promise faster and more efficient ways for software development with proven techniques and standard notations. Designers who adopt standards like UML and design patterns to construct models and designs in the processes of development suffer from a lack of communication and integration of various models and designs. Also, the problem of implicit inconsistency caused by making changes to components of the models and designs will significantly increase the cost and error for the process of maintenance. In this paper, an XML-based unified model is proposed to solve the problems and to improve both software development and maintenance through unification and integration.

Differentiation service (Diffserv) is regarded as one of the practical architectures to realize quality of service (QoS) on the Internet. Relative differentiated service, which achieves relative QoS differentiation between traffic classes, is a simple and easily-deployed service model. Based on the concept of relative differentiated service, Dovrolis et al. (ACM SIGMETRICS Performance Evaluation Review vol.27, no.1, pp.204-5, 1999; IEEE Network, September 1999; ACM SIGCOMM-99, September 1999) proposed a proportional differentiation service model which guarantees the ratios of service differences between classes. They claimed that weighted fair queuing (WFQ) is not suitable for implementing relative differentiation service and employed priority-based scheduling algorithms in their model. In this paper, we extend WFQ and apply it to proportional delay differentiation service. The extended WFQ algorithm adjusts the weighting of each class dynamically so that the delay differences between classes can be well controlled. Simulations show that the proposed methods can realize proportional delay differentiation service effectively and efficiently.

The Hopfield neural network is extensively applied to obtaining an optimal/feasible solution in many different applications such as the traveling salesman problem (TSP), a typical discrete combinatorial problem. Although providing rapid convergence to the solution, TSP frequently converges to a local minimum. Stochastic simulated annealing is a highly effective means of obtaining an optimal solution capable of preventing the local minimum. This important feature is embedded into a Hopfield neural network to derive a new technique, i.e., mean field annealing. This work applies the Hopfield neural network and the normalized mean field annealing technique, respectively, to resolve a multiprocessor problem (known to be a NP-hard problem) with no process migration, constrained times (execution time and deadline) and limited resources. Simulation results demonstrate that the derived energy function works effectively for this class of problems.

The traveling salesman problem (TSP), a typical combinatorial explosion problem, has been well studied in the AI area, and neural network applications to solve the problem are widely surveyed as well. The Hopfield neural network is commonly referred to in finding an optimal solution and a fast convergence to the result, however, it often traps to a local minimum. Stochastic simulated annealing has an advantage in finding the optimal solution; it provides a chance to escape from the local minimum. Both significant characteristics of the Hopfield neural network structure and stochastic simulated annealing algorithm are combined together to yield a so called mean field annealing technique. A complicated job scheduling problem of a multiprocessor with multiprocess instance under execution time limitation process migration inhibited and bounded available resource constraints is presented. An energy based equation is developed first whose structure depends on precise constraints and acceptable solutions using an extended 3D Hopfield neural network (HNN) and the normalized mean field annealing (MFA) technique; a variant of mean field annealing was conducted as well. A modified cooling procedure to accelerate a reaching equilibrium for normalized mean field annealing was applied to the study. The simulation results show that the derived energy function worked effectively, and good and valid solutions for sophisticated scheduling instance can be obtained using both schemes.

This paper presents an unsupervised segmentation approach applying the mean field annealing (MFA) heuristic with the modified cost function. The idea is to cast a clustering problem as a minimization problem where the criteria for the optimum segmentation is chosen as the minimization of the Euclidean distance between samples to cluster centers. To resolve the optimal problem using a Hopfield or simulated annealing neural network, the penalty terms are combined into a weighted sum using several coefficients determined by user. Using the MFA network to medical image segmentation, the need for finding weighting factors in the energy function can be eliminated and the rate of convergence is much faster than that of simulated annealing. The experimental results show that good and valid solutions can be obtained using the MFA neural network.

A framework for aiding the construction of simulation models in system design problems is presented. The framework employs concepts of artificial intelligence and simulation modeling. A knowledge representation scheme called system entity structure expresses information about the structure of the system to be designed and its corresponding models. More specifically, the entity structure represents objects and their attributes, decompositions, and taxonomies. A knowledge base of production rules is defined for a given design domain and is incorporated in an expert system shell which recommends a feasible configuration of design objects from the system entity structure, based on specific design objectives, constraints, and requirements. This configuration is a basis for constructing a model of the system. The methodology for constructing the system entity structure and its corresponding rule base is presented. A case study based on a high level robot design problem is discussed to illustrate the conceptual framework. INFORMS Journal on Computing, ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.