This paper introduces a novel unsupervised domain adaptation (UDA) method, MeTa Discriminative Class-Wise MMD (MCWMMD), which combines meta-learning with a Class-Wise Maximum Mean Discrepancy (MMD) approach to enhance domain adaptation. Traditional MMD methods align overall distributions but struggle with class-wise alignment, reducing feature distinguishability. MCWMMD incorporates a meta-module to dynamically learn a deep kernel for MMD, improving alignment accuracy and model adaptability. This meta-learning technique enhances the model’s ability to generalize across tasks by ensuring domain-invariant and class-discriminative feature representations. Despite the complexity of the method, including the need for meta-module training, it presents a significant advancement in UDA. Future work will explore scalability in diverse real-world scenarios and further optimize the meta-learning framework. MCWMMD offers a promising solution to the persistent challenge of domain adaptation, paving the way for more adaptable and generalizable deep learning models.

A style transfer aims to produce synthesized images that retain the content of one image while adopting the artistic style of another. Traditional style transfer methods often require training separate transformation networks for each new style, limiting their adaptability and scalability. To address this challenge, we propose a flow-based image style transfer framework that integrates Randomized Hierarchy Flow (RH Flow) and a meta network for adaptive parameter generation. The meta network dynamically produces the RH Flow parameters conditioned on the style image, enabling efficient and flexible style adaptation without retraining for new styles. RH Flow enhances feature interaction by introducing a random permutation of the feature sub-blocks before hierarchical coupling, promoting diverse and expressive stylization while preserving the content structure. Our experimental results demonstrate that Meta FIST achieves superior content retention, style fidelity, and adaptability compared to existing approaches.

Advanced Distance Education Technologies focused on the advanced techniques to provide practical solutions for distance education. Including Communication Technologies, Intelligent Technologies and Educational Technologies, advanced techniques construct a friendly and innovating learning environment for learners with different learning space and various learning style. For examples, Human-Computer Interaction, Agent-Based Software Systems, Internet and Information Systems Development, Web-Based Tools, Internet and Information Systems Development, Data Mining, Mobile and Ubiquitous Computing. Though pedagogies are less emphasize, this special issue praise those proposed technologies and applications based on educational theory, such as Computer-Supported Cooperative Work, intelligent tutoring, individualized distance learning. In this special issue, we invited some papers from ICWL (International Conference on Web-based Learning) 2008, WBL (Workshop of Blended Learning) 2008 and ADET (Advanced Distance Learning Technologies) 2008. All of these papers have been reviewed with second round and were recommended to contain 30% more new material to be accepted and published in this Special Issue. The first paper “A Chinese Handwriting Education System with Automatic Error Detection” demonstrates a distance education application of a Chinese handwriting education system. This system can automatically check the handwriting errors, such as the stroke production errors, stroke sequence error and stroke relationship error. Zhi-Hui Hu, Yun Xu, Liu-Sheng Huang and Howard Leung shows the experiment results to proof the system can handle more handwriting error cases than existing methods with a higher accuracy. The handwriting teaching in traditional classroom can be extended anywhere with this system, and allows students to practice homework at anytime for Master Learning. Next paper, “eLearning 2.0 – Technologies for Knowledge Transfer in European-Wide Network of Schools” mentions a concept that experiences and knowledge are sharing through word-wide social communities. Kawa Nazemi, Maja Ćukušić and Andrina Granić apply the concept to the EU- project UNITE and set a European network of fourteen schools. In addition, this system presents an iterative fourstage- process, covering scenario planning and implementation, validation in addition to platform and process improvement. With the rapidly development of Web 2.0 technologies, this paper shows another toward way of traditional classroom teaching paradigm. To deserve to be mentioned, collaborative learning is an important feature in the traditional classroom teaching paradigm. Thus, Jagadeesh Chandra A.P and R.D Sudhaker Samuel presents “Web-Based Collaborative Learning Architecture for Remote Experiment on Control of Bioreactor’s Environment” to provide collaborative learning and remote experiment on control of bioreactor’s environment. To translate traditional collaborative characteristics into an Internet based on-line collaborative learning environment, this paper proposes a system structure and functionalities by establishing communication between the process control computer and remote users through the Internet. With such revolutionary changes nowadays, collaborative working in an on-line environment can be more accessibility. Moreover, Ubiquitous Learning becomes more and more popular due to the success of ubiquitous computing technique. A ubiquitous computing system involves some integration between computing nodes and the real world. That is why ubiquitous learning environments can attract learner easier and started to attract considerable attention in various disciplines. Next paper, Hai Zhang and Takanori Maesako present “A Framework of Learner Development Ecosystem for Designing a Ubiquitous Educational Informational Infrastructure”. In this paper, ubiquitous learning environment is built on the theory of social constructivism proposed by Vygotsky, the theory of ecology of human development by Bronfenbrenner and the knowledge spiral theory by Nonaka. Based on those theories supported, the authors propose a new framework of a learner development ecosystem to design ubiquitous learning environment. With advanced computer and network technologies nowadays, learners could benefit from well- developed distance learning systems for obtaining vast learning content, as well as performing learning exercises at anytime, anywhere. One possible solution is to include some motivator factors in the online learning activities. Jui-Hung Chen, Te-Hua Wang, Wen-Chih Chang, Louis R. Chao and Timothy K. Shih present “Developing an Interactive Video Game-Based Learning Environment” which combines the video-based course materials and game elements with an integrated learning platform called “V-GBL” environment. Multimedia integrating e-learning environment motivates learners’ study motivation, lecture recording and organizing of visual information through user’s interaction at different technologies. Yi- Chun Liao and Chun-Hong Huang propose “Automatic Video Segmentation and Story-Based Authoring in E-Learning” which depicted a story-based editing and browsing system with the automatic video segmentation. The authors use a video classification technology can be further integrated to enhance the tool by using visual and audio information. The story-based editing is similar to hypervideo. Hypervideo is used as a hyperlink in a web. An instructor constructs an instructional material by hypervideo links. Combing the traditional collaborative learning and Web 2.0 Blog together, Chun-Chia Wang depicts “The Development of Collaborative Learning Environment with Learning Blogs”. Current researches on collaborative learning paid little attention to the functionalities of group members. In order to solve this problem,...