This paper presents a new approach to a recommendation of learning activities adapted to the spatial and temporal context of each mobile learner. Indeed, the path traveled by the user during a field trip can be guided using the technique of passive collaborative filtering. This recommendation is based on the ACO (Ant Colony Optimization) algorithm, which represents a good model for swarm intelligence. For this reason, the structure of our mobile scenario is described as a graph where POIs (Point Of Interest) are represented by nodes and the arcs indicate the probability of moving between them. This recommendation system allows the orchestration of mobile learning according to the geographical location of learners and the historical of their activities. Our contribution is devised in three parts: (1) the creation of a mobile learning scenario based on POIs, (2) the adaptation of the ACO algorithm for the orchestration of paths taken by learners, and (3) the development of a recommender system that helps learners to better choose their paths during the field trip.

In the era of Information and Communication Technology (ICT), virtual laboratories in the field of engineering and sciences have gained popularity, as a smart way of imparting practical and theoretical education. This paper discusses the realization of web-enabled simulated and remote control virtual laboratory of transducer based on one of the modular transducer kit/trainer commonly used in conducting experiments in Instrumentation and Control Engineering curriculum or related fields. Using component-based modeling methods, apparatus/devices used in a particular transducer experiment been have accurately modeled and assembled virtually. The virtual experiment panel mimics the functionality and physical appearance of the actual experimental set up. It provides various options to study and simulate the experiment by varying the input signal or device parameters. The remote control lab facility is also provided that enables the user to remotely perform the experiment on the kit. The experiment is interfaced to PC using suitable data acquisition system. Interactive virtual panel with web-cam connectivity is implemented and published on the web. It allows the user to control the set up and perform the experiment interactively; acquire and analyze real-time data and capture online view of the physical experimental setup remotely. The outcome of this work is the virtualization of transducer based experiments and development of integrated educational tool with high level of pedagogical effectiveness and technical support.

We live in a world where we are exposed to everyday changes that information and communication technologies (ICT) give us impose. These changes are largely related to education, and so the introduction of ICT in universities as institutions of higher education, clearly changing the way it is implemented. The policy of “Goce Delcev” University (UGD) is to fully implement ICT in all segments of management, administration and teaching. For this purpose, several projects for e-learning implementation at UGD have been conducted. But, as much as important introduction is, the more important is the acceptance of new technologies in education. Therefore, we shall use a modified Unified Theory of Acceptance and Use of Technology (UTAUT) as the research methodology. The purpose of this paper is understanding teaching staff acceptance and use e-Learning system (ELC) and investigating the influence of seven determinants (four UTAUT determinants, 2 additional determinants and one personal "self-confidence" determinant). A survey was administered to 92 respondents (teaching staff) to capture their perceptions of e-learning. The findings of this research show that among the seven UTAUT factors, the effort expectancy and facilitating conditions have the strongest effect of intention to use new technology. Also according to the survey, social influence and facilitating conditions are in strongest correlation with the behavioral intention and thereby the most influence on the behavior of participants for acceptance and use of the e – learning system.

In large data sets data pre-processing always has been the most essential data processing stages. Sampling and using small volumes of data has been an integrated part of data pre-processing to decrease training errors and increase speed of learning. In this study, instead of sampling from all data and using small parts of them, a method has been proposed to not only benefit from sampling but all data be used during training process. In this way, outliers would be detected and even used in completely different way. Using artificial neural networks, new features for instances will be built and the problem of intrusion detection will be mapped as a 10- feature problem. In fact, such a classification is for feature creation and as features in new problem only have discrete values, in final classification decision tree will be used. The results of proposed method on KDDCUP’99 datasets and Cambridge datasets show that this has improved classification in many classes dramatically.

Learning styles vary according to the individual and this diversity is fundamental in terms of teaching as curricula must respond adaptively to the various learning styles of pupils. This study conducts an analysis of an Arabic form of the Index of Learning Styles (ILS), a 44-item questionnaire designed to determine learning styles using the Felder-Silverman learning style model. This study focuses on the interpretation of data derived from the Arabic form of the Index of Learning Styles (ILS) to establish correlations between the learning styles of 1024 female students drawn from two specific departments at the King Abdul-Aziz University in Saudi Arabia. The findings, generated by Multiple Correspondence Analysis and cross-validated by correlation analysis, demonstrate a definite link between certain learning styles from opposing dimensions that are considered to be contradictory within the same dimension of learning. The validity and reliability of the Arabic scale was established and compared to the examples reported in the literature. Findings show comparable reliability and factor analysis supports the interdependencies between dimensions and perhaps the constructs they intend to assess. The results of this paper have implications for the design of e-learning tools, materials and sessions in order to adapt to the relationships between learning styles and have a positive impact on the learners themselves and their learning experience

The introduction and application of computer as a resource in teaching and learning process in education has contributed to the achievement of educational objectives. Students at all levels of education use computers for specified purpose. Do computers really help students to achieve academic excellence? The study investigated the perception of students on computer utilization and academic performance. It is a descriptive research with emphasis on survey design. The population comprised all Colleges of Education in North Central geopolitical zone of Nigeria: made up of six states and FCT-Abuja; out of which six colleges were selected as sample. A 20-item questionnaire (CUSAPQ) was designed and validated through expert judgment and reliability co-efficient of 0.86 was obtained. The null hypotheses were tested using Chi-square and ANOVA statistical analysis at 0.05 level of significance. Findings revealed that there was positive perception of computer utilization on students’ academic performance in the selected zone. Based on the findings, recommendations were made; seminar and workshops on computer utilization should be organised for the lecturers and the students to facilitate active and effective learning.

Cloud computing environments have introduced a new model of computing by shifting the location of computing infrastructure to the Internet network to reduce the cost associated with the management of hardware and software resources. The Cloud model uses virtualization technology to effectively consolidate virtual machines (VMs) into physical machines (PMs) to improve the utilization of PMs. Studies however have shown that the average utilization of PMs in many Cloud data centers is still lower than expected. The Cloud model is expected to improve the existing level of utilization by employing new approaches of consolidation mechanisms. In this paper we propose a new approach for dynamic consolidation of VMs in order to maximize the utilization of PMs. This is achieved by a dynamic programing algorithm that selects the best VMs for migration from an overloaded PM, considering the migration overhead of a VM. Evaluation results demonstrate that our algorithms achieve good performance.

Biometrics is being commonly used nowadays for the identification and verification of humans everywhere in the world. In biometrics humans unique characteristics like palm, fingerprints, iris etc. are being used. Pattern Recognition and image processing are the major areas where research on signature verification is carried out. Hand written Signature of an individual is also unique and for identification of humans are being used and accepted specially in the banking and other financial transactions. The hand written signatures due to its importance are at target of fraudulence. In this paper we have surveyed different papers on techniques that are currently used for the identification and verification of Offline signatures.