Mutasem Alsmadi

Performance Comparison of Multi-layer Perceptron (Back Propagation, Delta Rule and Perceptron) algorithms in Neural Networks

A multilayer perceptron is a feedforward artificial neural network model that maps sets of input data onto a set of appropriate output. It is a modification of the standard linear perceptron in that it uses three or more layers of neurons (nodes) with nonlinear activation functions, and is more powerful than the perceptron in that it can distinguish data that is not linearly separable, or separable by a hyper plane. MLP networks are general-purpose, flexible, nonlinear models consisting of a number of units organised into multiple layers. The complexity of the MLP network can be changed by varying the number of layers and the number of units in each layer. Given enough hidden units and enough data, it has been shown that MLPs can approximate virtually any function to any desired accuracy. This paper presents the performance comparison between Multi-layer Perceptron (Back Propagation, Delta Rule and Perceptron). Perceptron is a steepest descent type algorithm that normally has slow convergence rate and the search for the global minimum often becomes trapped at poor local minima. The current study investigates the performance of three algorithms to train MLP networks. Its was found that the Perceptron algorithm are much better than others algorithms.

Healthcare professionals’ acceptance Electronic Health Records system: Critical literature review (Jordan case study)

ABSTRACT The purpose of this paper, acceptance of Electronic Health Records (EHRs) system in the Jordan eHealth sector, is to contribute to develop the quality of hospitals, reduce medical error issues and reduce health costs. However, few researches have addressed the antecedent factors of healthcare professionals’ intentions to use an EHR system. Founded on trust factors integrated with the UTAUT2 model, a theoretical model is proposed to explain the exercise behaviour of healthcare professionals to use an EHR system.

Instructor's success measures of Learning Management System

Distance learning has been used widely as a helpful solution by many institutions to offer learning on demand opportunities to working adults. Educational technology evaluation model (ETM) have been tested in large sample size among students, and little research has been conducted to measure the success of distance learning technologies such as Learning Management System (LMS) from the point of view of instructors. Based on previous literature of critical success factors (CSF), this study validated a multidimensional model for assessing distance learning management systems success from the perspective of the instructors. To conceptualizing the ETM, measuring factors, collecting data procedure, reliability and validity testing are described. Structural Equation Modelling (SEM), which is a statistical technique, is used to estimate a series of interrelated dependence relationships of ETM factors simultaneously. This technique is applied to help in generating a model of relationships among variables. This paper presents results of the instrument reliability and constructs validity by analyzing data from a sample of 110 participants. Managerial and theoretical implications of the results are discussed. This empirical validation of the ETM will be useful to researchers in developing and measuring distance learning technologies, as well as to organizations in implementing successful distance learning technologies.

Looking Inside and Outside the System: Examining the Factors Influencing Distance Learners Satisfaction in Learning Management System

In the last few years, the use of educational technology, particularly the concept of Learning Management System (LMS), has increased rapidly. With this fast development, the question arises as how to manage the LMS to obtain success and efficiency in online courses. One of the important factors that have received many citations in literature studies (and has a special position in information system research) is the user satisfaction. It is a crucial factor that can predict the success or failure of any LMS. In relation, this research examined the success factors that affect the user satisfaction and outcomes of LMS. This paper discusses the conceptual User Satisfaction Evaluation Model (USEM) employed to measures LMS success. In particular, it seeks to examine “the relationship between: Service quality, system quality, ease of use, perceived usefulness, information quality and students satisfaction, as well as to measure the outcomes of the LMS.” Results from the data analysis indicate that all proposed factors have a positive effect on student satisfaction. The result also concludes that a higher rate of user satisfaction will lead to greater benefits for the students.

SERVER FAILURES ENABLED JAVASPACES SERVICE

JavaSpaces service is a Distributed Shared Memory (DSM) implementation. It has been introduced by Sun Microsystems as a service of the Jini system. Currently, JavaSpaces support client side fault tolerance. It enables both transaction and mobile coordination mechanisms for such purpose. The application failures could be detected and recovered. However, server side failures may occur during the application runtime. Therefore, it is important to supply JavaSpaces with a mechanism that handles such type of failures dynamically. On the other hand, An example of a system that supports both server and client fault tolerance over DSM is TRIPS system. TRIPS protocols are suitable to be integrated in JavaSpaces to supply it with server fault tolerance capabilities. In this study, a server Failures Enabled Javaspaces Service (FTJS) is introduced. FTJS is based on the dynamic failure detection and recovery mechanisms implemented by TRIPS. However, FTJS is able to handle both client and server side failures. The analysis, design and implementation issues of FTJS are introduced.