Norjihan Abdul Ghani

Owner-Controlled Towards Personal Information Stored in Hippocratic Database

Privacy protection has become one of the important requirement in web-based information system that deal with personal information. There are an issues arise that personal information collected should be privacy-protected. Owner should know to what extent information about them has been collected, how it’ll used and able to control their own information. Hippocratic Database (HDB) introduced by Agrawal, et al. (2002) is a relational database system that has been proposed in order to protect the privacy at database level. Hippocratic Database used the purpose as a central concept in the database development. But, currently with the notion of purpose, owner is unable to control his/her PI stored in HDB regardless they are able to. This paper discussed and introduced an initial architecture of owner-controlled Hippocratic Database

Mobile Learning for English Language Acquisition: Taxonomy, Challenges, and Recommendations

Mobile learning (m-learning) is increasingly becoming a popular global trend, especially among English language learners. However, despite the growing interest in mobile English language learning, there have been no reviews of research conducted on this subject. This paper represents the first attempt to provide a comprehensive analysis of the existing literature (2010–2015) to identify the taxonomy and distribution of research as well as to identify the advantages and challenges and provide some recommendations to facilitate the effective use of mobile English language learning and its applications. Following a review protocol, articles on mobile English language learning from six major databases (IEEE Xplore, ScienceDirect, Web of Science, ERIC, SpringerLink, and Wiley Online Library) were reviewed. Applying inclusion and exclusion criteria, 133 related articles were identified. The results show that the majority of studies were conducted on application m-learning technologies. Pure mobile applications were the most widely-used applications in the English m-learning context. Meanwhile, concerns regarding quality, usability, integration, financial costs, security and privacy, pedagogical practice, and safety were found to be the main challenges of mobile English language learning. Finally, some recommendations are provided for users, developers/providers, and researchers. The results of this paper can assist users, researchers, policymakers, and practitioners in the education sector to allocate the necessary resources and make plans to mitigate the challenges and facilitate the effective use of mobile English language learning in educational practices.

Privacy-preserving in web services using hippocratic database

Nowadays, the growth of internet has been accompanied by the growth of web services (e.g e-government, e-health, e-commerce). Web services collect data, especially individuals, from users and use them for various purposes. Sometimes, web services need to release the data they own to third parties. Because privacy is an important concern in web services, there are several research efforts have been devoted to address issues related to the development of privacy-preserving data management techniques. In [3], Agrawal et. al. has introduced Hippocratic Database incorporating privacy protection in relational database systems. In this paper, we’ll proposed the use of Hippocratic Database to ensure the privacy in web services. We use a scenario for driving license renewal by Road Transport Department in order to illustrate this.

A novel association rule mining approach using TID intermediate itemset

Designing an efficient association rule mining (ARM) algorithm for multilevel knowledge-based transactional databases that is appropriate for real-world deployments is of paramount concern. However, dynamic decision making that needs to modify the threshold either to minimize or maximize the output knowledge certainly necessitates the extant state-of-the-art algorithms to rescan the entire database. Subsequently, the process incurs heavy computation cost and is not feasible for real-time applications. The paper addresses efficiently the problem of threshold dynamic updation for a given purpose. The paper contributes by presenting a novel ARM approach that creates an intermediate itemset and applies a threshold to extract categorical frequent itemsets with diverse threshold values. Thus, improving the overall efficiency as we no longer needs to scan the whole database. After the entire itemset is built, we are able to obtain real support without the need of rebuilding the itemset (e.g. Itemset list is intersected to obtain the actual support). Moreover, the algorithm supports to extract many frequent itemsets according to a pre-determined minimum support with an independent purpose. Additionally, the experimental results of our proposed approach demonstrate the capability to be deployed in any mining system in a fully parallel mode; consequently, increasing the efficiency of the real-time association rules discovery process. The proposed approach outperforms the extant state-of-the-art and shows promising results that reduce computation cost, increase accuracy, and produce all possible itemsets.

Mobile English Language Learning (MELL): a literature review

Abstract English has increasingly become an essential second language as well as a language for international communication. However, there is little research that examines the dimensions of mobile learning for both researchers and instructional designers and focuses on effective uses of the latest mobile learning technologies for education. There have been no reviews of research on mobile English learning. This paper aims to provide a comprehensive analysis of the research on Mobile English Language Learning (MELL) material to initiate an evidence-based discussion on the usage of mobile learning in English language education. Findings from existing literature show that studying and reviewing mobile learning leads to a deeper understanding of its effect and possibilities with respect to learning the English language. Additionally, findings also indicate that when it comes to English language skills, vocabulary is the most-used skill, and the most common problem that studies mention is that of motivation. Further studies need to investigate other terms and keywords that reflect on the use of mobile learning.

Game Framework to Improve English Language Learners’ Motivation and Performance

The dominance of English as the global language of entertainment, education and business creates a strong need to learn and teach it. Learning a second language is often difficult and educators continue to seek innovative ways to improve language learning and increase learners’ motivation especially for second language learners. A number of technologies exist to assist in language learning, ranging from basic tools of distance, electronic, and mobile learning, to the use of games on mobile platforms to teach language skills. Developing games for educational purposes, however, is not a straightforward task even for professional developers. As this technology is a recent trend, the available frameworks and guidelines to help developers as well as educators are still not adequate. In this paper, we explore an educational mobile game framework that is designed to improve students’ motivation and enhance English language learning. Through a review of existing mobile learning frameworks, plus refining and validation process with experts, the paper identifies necessary components and their holistic structure. The key components include inputs from the domain of persuasive technology, Bloom’s taxonomy and educational content. At the core of the framework, it is a set of guidelines to develop mobile language learning mobile games. We present an evaluation of the proposed framework using expert input, which returned a positive and supportive feedback. In a subsequent phase, the proposed framework will be used to build a mobile game application to enhance language learning, and an experimental evaluation will be set on a target sample of Arabic-speaking primary school students.

Correction: A novel association rule mining approach using TID intermediate itemset

[This corrects the article DOI: 10.1371/journal.pone.0179703.].