<span>This paper presents a learning media repository and delivery system (LMRD) for a smart classroom using IoT and mobile technologies. It was designed to support active learning pedagogy. Teachers are able to broadcast learning media or course materials directly to the student mobile devices, after that the students can interact to the media by drawing, editing, or adding comments using their mobile device then broadcast it back to present or reflect their thinking. The system includes 1) a server using a Raspberry Pi 3B+ and 2) mobile devices. The system supports full features involving two approaches in the form of an Internet model and a non-Internet model. The mobile applications were implemented using cross-platform approach to support major mobile platforms including iOS and Android. </span><span>The evaluation had three dimensions in terms of usability, functionality and security. The results revealed that all dimensions were evaluated highly. The teacher and students were highly satisfied with the system.</span>

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<p class="0abstract">The digital competence is necessary for 21^st century living, but from several countries survey, a large number of people still have insufficient digital competence. Moreover, from literature study found three problems of today cooperative education information system, (1) lack of information sharing among university community, (2) lack of connect information to public, and (3) lack of enhancing 21^st century learning skill. This paper proposes a process design of cooperative education management system by using the integration of cooperative education, E-Portfolio, digital competence framework 2.0, cloud computing technology, and blockchain technology. These processes make result of digital competence assessment credible and share to open digital labor market finally.</p>

Mobile technologies play an increasingly important role in education. Devices such as smart phones and tablets are becoming powerful tools in the hands for e-Learning, m-Learning and ubiquitous learning. In this paper, the authors propose analysis and design software architecture of a mobile augmented book for in-class and out-class learning. The aim is to improve the quality and usefulness of mobile learning by utilizing a physical book and a mobile device. Requirements, roles, and system architecture are discussed in terms of adaptive learning. The system architecture is based on a three-tier model; presentation tier, application logic tier and data tier. The application logic tier is comprised of four main components including 1) Profile/Registration, 2) Content/ Administration, 3) Communication 4) Quiz and 5) Report. The data tier consists of 1) Cloud Service, 2) Media Server and 3) Database. The presentation tier is designed to support all mobile devices--smart phones and tablets and all popular platforms including Android, iOS, Windows phone, Tizen, Ubuntu, Firefox and BlackBerry. JSON and Streaming media are used for the communications between the presentation tier (client devices) and the application logic tier. The data tier consists of 1) repository using cloud service and media server for storing and retrieving digital contents and 2) database for credentials, content descriptions and meta-data.

Spam mails distributed from botnets have been one of the critical problems for the Internet. Spamming is growing at a rapid rate since sending a flood of mails is easy and very cheap. Spam mails waste user time and consume resources e.g., space and network bandwidth, so fighting against spam is an interesting issue in computer security. We have spent for more than 3 years collecting and analyzing over 161,230 emails from several mailboxes. We found that some users received up to 235 emails per day, only 1 to 3 emails were legitimate and the rest appeared to be spam mails. This paper presents a fast effective spam filter by analyzing the mail header. It works well with both text-base spam and all kinds of image spam. Our experiments and results showed that spam was filtered out at least 96.23% with no false positive.