The impact of information technology to improve the level of performance of employees in the Ministry of Higher Education and Scientific Research of Jordan

The purpose of this study was to investigate the effect of the use of information technology in the Ministry of Higher Education of Jordan to improve the administrative performance of the staff where, researcher has used the descriptive analytical method to achieve the objectives of the study, may be a study population consisted of a random sample of employees in the Ministry of Higher Education of Jordan of (45) individuals, as was the use of statistical package program SPSS for data analysis and hypothesis testing, and was the most important statistical methods used is to test one way anova, it was the most important results of the study that there is a significant effect for statistical information technology used in the ministry of higher education to improve the administrative performance of the employees. As they were the most important recommendations that the Ministry of Higher Education is working to develop Electronic systems and existing programs even have help in the development of employee performance. Key words: information technology, development of employee performance, The Jordanian Ministry of Higher Education

Feature extraction techniques for abandoned object classification in video surveillance

We address the problem of abandoned object classification in video surveillance. Our aim is to determine (i) which feature extraction technique proves more useful for accurate object classification in a video surveillance context (scale invariant image transform (SIFT) keypoints vs. geometric primitive features), and (ii) how the resulting features affect classification accuracy and false positive rates for different classification schemes used. Objects are classified into four different categories: bag (s), person (s), trolley (s), and group (s) of people. Our experimental results show that the highest recognition accuracy and the lowest false alarm rate are achieved by building a classifier based on our proposed set of statistics of geometric primitives' features. Moreover, classification performance based on this set of features proves to be more invariant across different learning algorithms. © 2008 IEEE

The Impact of E-Business Elements in Improving the Quality of Management Performance in the Ministry of Higher Education and Scientific Research of Jordan

This study aimed to identify the elements of the electronic administration in the Ministry of Higher Education of Jordan, also aimed to determine the effect of the elements of electronic management applied in the ministry in improving the quality of management performance which has been a questionnaire consisting of (26) question, and distributed to a random sample of the staff at ministry by (100) subject to statistical analysis ,the most important results that there is the impact of the use of the elements of the electronic administration in improving the quality of management performance in the ministry, as they were the most important recommendations of the study work on activating the elements and other technology in the ministry through increased government support her so that the ministry can buy devices and technological to help the improve the quality of management performance in the ministry

Mixtures of Gaussian distributions under linear dimensionality reduction

High dimensional spaces pose a serious challenge to the learning process. It is a combination of limited number of samples and high dimensions that positions many problems under the "curse of dimensionality", which restricts severely the practical application of density estimation. Many techniques have been proposed in the past to discover embedded, locally-linear manifolds of lower dimensionality, including the mixture of Principal Component Analyzers, the mixture of Probabilistic Principal Component Analyzers and the mixture of Factor Analyzers. In this paper, we present a mixture model for reducing dimensionality based on a linear transformation which is not restricted to be orthogonal. Two methods are proposed for the learning of all the transformations and mixture parameters: the first method is based on an iterative maximum-likelihood approach and the second is based on random transformations and fixed (non iterative) probability functions. For experimental validation, we have used the proposed model for maximum-likelihood classification of five "hard" data sets including data sets from the UCI repository and the authors' own. Moreover, we compared the classification performance of the proposed method with that of other popular classifiers including the mixture of Probabilistic Principal Component Analyzers and the Gaussian mixture model. In all cases but one, the accuracy achieved by the proposed method proved the highest, with increases with respect to the runner-up ranging from 0.2% to 5.2%

Impact of Lack of Self-efficiency and Assets Evaluation on Resistance of IPSAS Implementation

This study examines factors influencing the international public sector accounting standards (IPSAS) implementation and presenting of accounting information related to the Jordanian public sector, also the information of reports is based on “Accounting principles and practices (No.39/1962) among government accountants. This study identified several important factors influencing the IPSAS implementation which are; lack of self-efficiency and assets evaluation. In addition, a quantitative approach was employed by distributed the questionnaires to 100 respondents enrolled at Jordanian General Budget Department using simple random sampling. The data were analyzed using SPSS to verify the relationships between the variables. The results found significant positive relationships between lack of self-efficiency and assets evaluation and IPSAS implementation resistance among government accountant in the public sector of Jordan. To sum up, this study contributes in expanding the literature concerning IPSAS implementation in Jordanian context, it’s also provides meaningful guideline to the government of Jordan for IPSAS implementation resistance. Finally, providing insights on the critical success factors to ensure successful implementation process

MLiT: Mixtures of Gaussians under linear transformations

The curse of dimensionality hinders the effectiveness of density estimation in high dimensional spaces. Many techniques have been proposed in the past to discover embedded, locally linear manifolds of lower dimensionality, including the mixture of principal component analyzers, the mixture of probabilistic principal component analyzers and the mixture of factor analyzers. In this paper, we propose a novel mixture model for reducing dimensionality based on a linear transformation which is not restricted to be orthogonal nor aligned along the principal directions. For experimental validation, we have used the proposed model for classification of five "hard" data sets and compared its accuracy with that of other popular classifiers. The performance of the proposed method has outperformed that of the mixture of probabilistic principal component analyzers on four out of the five compared data sets with improvements ranging from 0. 5 to 3.2%. Moreover, on all data sets, the accuracy achieved by the proposed method outperformed that of the Gaussian mixture model with improvements ranging from 0.2 to 3.4%. © 2011 Springer-Verlag London Limited

Bayes model for assessing the reading difficulty of English text for English education in Jordan

Predicting the reading difficulty level of English texts is a critical process for second language education and assessment. Reading difficulty level is concerned with the problem of matching a reader’s proficiency and the appropriate text. The reading difficulty level or readability assessment is the process for predicting the reading grade level required from an input text or document, which corresponds to the reader and to the materials. Students in Jordan at their academic levels find obstacles in finding relevant readable data for any subject at their levels. This paper is intended to introduce a model that foretells the reading difficulty level of a given text in terms of a student's ability to read and understand English as a non-native English speaker in Jordanian schools. In this paper, Jordanian students were classified into four categories according to their knowledge of English. The prediction of the reading difficulty level is achieved by using a modern statistical model that is situated on the Bayes model. The model compares the given text with some standard predefined text that strongly reflects the ability to read and understand English text. The accuracy of the proposed model was tested using the hold-out method. The overall prediction accuracy was 75.9%

Bridging the Gap: A Program to Enhance Medical Students\u27 Learning Experience in the Foundation Year

Objective: To evaluate students’ perceptions of the intervention program based on small group teaching, regular continuous assessment, science-based tailored study skills program and recorded attendance on students’ enhanced learning experience in the first year of study in an outcome-based medical course. Design: Descriptive study. Setting: RCSI Bahrain. Method: A Twenty-seven-item questionnaire was administered to foundation year students at the Royal College of Surgeons in Ireland – Medical University of Bahrain (RCSI Bahrain) after the completion of the first semester to explore whether these interventions enriched the students’ learning experience or not. Comparisons of pass rates in all modules over the four years were also included. Students’ perceptions of the academic study skills course were collected through a questionnaire activity (version 2007120102) via the Virtual Learning Environment (VLE). Result: The results suggest that local adaptations of undergraduate programs may lead to pedagogical expertise that contribute to enhanced learning experience of students and better integration of pre-university and third-level courses. The majority of questionnaire items were rated positively and the comparison of pass rates showed the highest results in the year the intervention was implemented. Conclusion: Making local adaptations to medical programs without changing the core curriculum can mark good academic practice. Considering specific socio-cultural frameworks of students may lead to improvements in the delivery of programs in universities