Data Mining - Concepts and Techniques.

National Institute of Standards and Technology における超伝導研究及び生活

本文对国际科学计量学杂志《Ｓｃｉｅｎｔｏｍｅｔｒｉｃｓ》１９７９－１９９１年的研究论文内容、栏目、作者及国别和编委及国别作了计量分析，揭示出科学计量学研究的重点、活动的中心及发展趋势，说明了学科带头人在发展科学计量学这门新兴学科中的作用。

国际刊物《Scientometrics》文献计量研究

There has been little research on assessment of learning management systems (LMS) within educational organizations as both a web-based learning system for e-learning and as a supportive tool for blended learning environments. This study proposes a conceptual e-learning assessment model, hexagonal e-learning assessment model (HELAM) suggesting a multi-dimensional approach for LMS evaluation via six dimensions: (1) system quality, (2) service quality, (3) content quality, (4) learner perspective, (5) instructor attitudes, and (6) supportive issues. A survey instrument based on HELAM has been developed and applied to 84 learners. This sample consists of students at both undergraduate and graduate levels who are users of a web-based learning management system, U-Link, at Brunel University, UK. The survey instrument has been tested for content validity, reliability, and criterion-based predictive validity. The analytical results strongly support the appropriateness of the proposed model in evaluating LMSs through learners' satisfaction. The explanatory factor analysis showed that each of the six dimensions of the proposed model had a significant effect on the learners' perceived satisfaction. Findings of this research will be valuable for both academics and practitioners of e-learning systems.

Multi-dimensional students' evaluation of e-learning systems in the higher education context: An empirical investigation

Secure attribute-based data sharing for resource-limited users in cloud computing

Purpose – The purpose of this paper is to demonstrate the importance of undertaking a systemic view of learning management systems (LMSs) evaluation addressing the conceptualization and measurement of e‐learning systems success in higher education.Design/methodology/approach – The paper adopts a quantitative case perspective and derives a conceptual model for e‐learning assessment (Hexagonal e‐learning assessment model – HELAM). The model is empirically tested for validity and reliability in the university setting.Findings – Qualitative and quantitative findings have been presented, which will be valuable for academics and practitioners doing research in e‐learning evaluation. The findings support the flexibility and relevance of HELAM as an e‐learning assessment model. It highlights a number of success measures which are grouped under six dimensions.Research limitations/implications – Further research efforts should explore new dimensions or test the causal relationships among proposed dimensions within ...

Evaluating learning management systems

MedicoPort: A medical search engine for all

Android mobile devices have reached a widespread use since the past decade, thus leading to an increase in the number and variety of applications on the market. However, from the perspective of information security, the user control of sensitive information has been shadowed by the fast development and rich variety of the applications. In the recent state of the art, users are subject to responding numerous requests for permission about using their private data to be able run an application. The awareness of the user about data protection and its relationship to permission requests is crucial for protecting the user against malicious software. Nevertheless, the slow adaptation of users to novel technologies suggests the need for developing automatic tools for detecting malicious software. In the present study, we analyze two major aspects of permission-based malware detection in Android applications: Feature selection methods and classification algorithms. Within the framework of the assumptions specified for the analysis and the data used for the analysis, our findings reveal a higher performance for the Random Forest and J48 decision tree classification algorithms for most of the selected feature selection methods.

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The analysis of feature selection methods and classification algorithms in permission based Android malware detection

Hash chains are used extensively in various cryptography applications such as one-time passwords, server-supported signatures and micropayments. In this paper, we present a method, called infinite length hash chains to improve the flexibility of this chaining idea by using public-key techniques. One of its distinguishing features is that communication and computation overhead of restarting of the system is avoided For the owner of the chain it is possible to go in either way in the chain at any time without any restriction in the chain length, but others see no difference as the functionality it provides with respect to traditional hash chains. On the other hand the drawback here is the increased computation cost due to public-key operations. Part of our work would be considered as one additional step after traditional one-time passwords in the natural progression from fixed password schemes to challenge-response identification protocols.

Infinite length hash chains and their applications

In this study we extracted websites' URL features and analyzed subset based feature selection methods and classification algorithms for phishing websites detection.

Nazife Baykal

Papers

Evaluating learning management systems

MedicoPort: A medical search engine for all

The analysis of feature selection methods and classification algorithms in permission based Android malware detection

Infinite length hash chains and their applications

Feature extraction and classification phishing websites based on URL