Shyan-Ming Yuan

Web-based peer assessment : feedback for students with various thinking-styles

Abstract This study used aptitude treatment interaction design to examine how feedback formats (specific vs. holistic) and executive thinking styles (high vs. low) affect web-based peer assessment. An Internet-based (anonymous) peer-assessment system was developed and used by 58 computer science students who submitted assignments for peer review. The results indicated that while students with high executive thinking styles significantly improved over two rounds of peer assessment, low executive students did not improve through the cycles. In addition, high executive students contributed substantially better feedback than their low executive counterparts. In the second round of peer assessment, thinking style and feedback format interactively affected student learning. Low executive students receiving specific feedback significantly outperformed those receiving holistic feedback. In receiving holistic feedback, high executive thinkers outperformed their low executive counterparts. This study suggests that future web-based peer assessment adopts a specific feedback format for all students.

A relaxable service selection algorithm for QoS-based web service composition

Context: Web Services are emerging technologies that enable application to application communication and reuse of autonomous services over Web. Composition of web services is a concept of integrating individual web services to conduct complex business transactions based on functionality and performance constraints Objective: To satisfy user requirements, technologies of Quality of service (QoS)-based web service composition (QWSC) are widely used to build complex applications by discovering the best-fit web services in term of QoS. Method: In this paper, a QoS-based service selection (RQSS) algorithm is proposed to help composite web application development by discovering feasible web services based on functionalities and QoS criteria of user requirements. The RQSS recommends prospective service candidates to users by relaxing QoS constraints if no suitable or available web service could exactly fulfill user requirements. Results: A generic framework is implemented to demonstrate the feasibility and performance of RQSS by adapting WS-BPEL standards, and can be reused for QoS-based web composition applications. Conclusion: The experimental results show that the RQSS algorithm indeed performs well and increases the system availability and reliability.

A Networked Peer Assessment System Based on a Vee Heuristic

This study implements a networked peer assessment system based on the use of a Vee heuristic. Using this system, students submit their homework (relating to designing science activities)via the underlying network facility. They then assess each others homework by offering suggestions – again, through the network. Students then modify their original designs based on the suggestions that they receive. This procedure is repeated for two or three consecutive rounds. In this process, each student functions as an author, a reviewer, and an adapter. This learning model allows students to further develop their critical thinking skills. Preliminary peer assessment results revealed that the networked peer-assessment model and Vee heuristic facilitated pre-service science teachers to continuously progress when designing science activities.

Use of peer feedback to enhance elementary students' writing through blogging.

Addressforcorrespondence:Mr.YuLiangChen,Departmentof ComputerScience,NationalChiaoTungUniversity,1001 University Road, Hsinchu 300, Taiwan. Email: imklchen@gmail.com; Dr. Eric Zhi Feng Liu, GraduateInstitute of Learning & Instruction, National Central University, no. 300 Jung-da Road, Chung-Li City, Taoyuan320, Taiwan. Email: totem@cc.ncu.edu.tw

Synchronous navigation control for distance learning on the Web

Abstract Most of the research on “distance learning on the Web” is learner-centric. That is, learners play an active role in their learning process, while instructors are passive or even invisible. Unable to treat the instructor/learner relationship as a whole causes some problems. Therefore, we introduce a new concept of instructor-oriented navigation control on the Web, and then propose and implement a protocol for it. In this model, an instructor (technically, master) can setup a learning group, and those who wish to be guided distantly (technically, slaves) during the study may have their navigation activities controlled synchronously by joining the group. We believe that instructors will become more active and positive with the help of our proposed model in a WWW-based educational environment.

A fault-tolerant object service on CORBA

Abstract The Common Object Request Broker Architecture (CORBA), is a major industrial standard for distributed object-based applications. Todays large-scale CORBA applications have to deal with object crashes, node failures, networks partitioning and unpredictable communication delays. Existing efforts to enhance the CORBA reliability can be roughly categorized into three approaches: integration approach, interception approach and service approach. Each approach has its own merits and prices. In this paper, we propose a service approach solution called Object Fault–tolerance Service (OFS). Solutions that adopt the service approach usually specify their service in terms of CORBA IDL interfaces. The implementations of such solutions in general do not modify the ORB infrastructure or IDL language mappings, and thus applications developed with those systems appear to be more portable. OFS differs from other service approach solutions in that OFS does not assume underlying support of reliable group communication. Applications with advance registration can rely on OFS for detection of object and node crashes, and for customized recovery. In this paper, we first present the service specification of OFS. We then give the system architecture of an OFS implementation. This OFS implementation is developed on the Solaris 2.5 platform and with IONAs Orbix 2.0. The performance evaluation of the OFS implementation is also presented. The preliminary experiments indicate that OFS overhead is minimal and client objects experience little response delay when a service object is under OFS surveillance.

Mobile cloud-based depression diagnosis using an ontology and a Bayesian network

Recently, depression has becomes a widespread disease throughout the world. However, most people are not aware of the possibility of becoming depressed during their daily lives. Therefore, obtaining an accurate diagnosis of depression is an important issue in healthcare. In this study, we built an inference model based on an ontology and a Bayesian network to infer the possibility of becoming depressed, and we implemented a prototype using a mobile agent platform as a proof-of-concept in the mobile cloud. We developed an ontology model based on the terminology used to describe depression and we utilized a Bayesian network to infer the probability of becoming depressed. We also implemented the system using multi-agents to run on the Android platform, thereby demonstrating the feasibility of this method, and we addressed various implementation issues. The results showed that our method may be useful for inferring a diagnosis of depression. Integrating Ontology with Bayesian Network to predict getting depressed or not.Using mobile agent and cloud environment to implement the diagnosis environment.Evaluation result shown the system is feasibility for doing the prediction.

A Framework for Scalable Cloud Video Recorder System in Surveillance Environment

In recent years, video surveillance industry has encountered huge evolution. First, the IP based video cameras are gradually replacing the market share of Closed-circuit television (CCTV). Second, hardware and software based network video record come to market to support more amounts of camera sources. However, pure NVR hardware or software which is installed on single physical machine may reach maximum storage or throughput limitation due to predefined resource limitation. In this paper, we proposed a prototype of cloud based video recorder system under Infrastructure as a Service (IaaS) abstraction layer in cloud computing domain. This system provides scalable video recording, backup and monitoring features. Furthermore, this system was implemented using Hadoop distributed file system to store video streaming. In this way, Map / Reduce mechanism could be used to support intelligent video analysis tasks. The paper shares a good experience while design unlimited resource video recording system.

Reversible data hiding for VQ-compressed images based on search-order coding and state-codebook mapping

Abstract In the field of digital multimedia, numerous researchers have exploited data hiding for providing secure communications. Because most multimedia is compressed in advance to save storage space and transmission time, this paper presents a reversible data-hiding scheme for vector quantization (VQ)-compressed images. In the proposed scheme, search-order coding (SOC) is first employed to reduce the size of the VQ index table. For image blocks that cannot be processed by SOC, a technique called state-codebook mapping (SCM) is used to map the blocks to the corresponding indices in their state-codebooks, which are generated by a set of neighborhood indices. After SOC and SCM, the size of the output code stream is reduced, and a large amount of space is available for embedding sensitive data. Performance comparisons with similar recent studies are presented for demonstrating the superiority of the proposed scheme. The experimental results indicated that the proposed scheme can achieve a high embedding capacity and a high compression bit rate.

A parallel Bees Algorithm implementation on GPU

Bees Algorithm is a population-based method that is a computational bound algorithm whose inspired by the natural behavior of honey bees to finds a near-optimal solution for the search problem. Recently, many parallel swarm based algorithms have been developed for running on GPU (Graphic Processing Unit). Since nowadays developing a parallel Bee Algorithm running on the GPU becomes very important. In this paper, we extend the Bees Algorithm (CUBA (i.e. CUDA based Bees Algorithm)) in order to be run on the CUDA (Compute Unified Device Architecture). CUBA (CUDA based Bees Algorithm). We evaluate the performance of CUBA by conducting some experiments based on numerous famous optimization problems. Results show that CUBA significantly outperforms standard Bees Algorithm in numerous different optimization problems.