International Journal of Research and Reviews in Applied Sciences
ISSN: 2076-734X, EISSN: 2076-7366

Volume 40 (July-September 2019)

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1. FACTORS AFFECTING THE ACADEMIC PERFORMANCE OF STUDENTS AT ACADEMIC INSTITUTION
by Abdelnaser Omran and Mohamed Saad Hamad Saleh
Abstract

Measuring of academic performance of students is challenging since students’ performance are the product of socio-economic, psychological and environmental factors. This study investigates the factors affecting academic performance of students at College of Business of University Utara Malaysia located in Kedah State, Malaysia. A quantitative approach was used to collect the data in the selected area of study. Where, out of 135 sets of a questionnaire distributed, only 117 sets were completely returned and analyzed, yielding a response rate of 87.7%.  This study revealed that teaching style, English language and communication, language assessment, students’ academic stress, students’ self-concept are all playing a significant role on the students’ academic performance at College of Business, Universiti Utara Malaysia. As the students’ academic stress, the study has concluded that pressure from parents and parents’ involvement were significantly the most associated factors with students’ academic performance.

Source: International Journal of Research and Reviews in Applied Sciences
July - September (Vol. 40, Issue 1) - 2019

2. EXAMINING THE FACTORS AFFECTING THE PRODUCTIVITY IN THE LIBYAN CONSTRUCTION COMPANIES
by Mohamed Saad Hamad Saleh
Abstract

This study aims to examine the productivity constraints in the construction companies in the city of Ajdabiya, which is located in the central northern area of Libya. Moreover, it aims to propose any strategies that can improve productivity in construction companies. A questionnaire survey was used to collect data from project managers, executives, and managers who are working in construction companies. Of the 203 questionnaires dispatched to the selected respondents, only 149 were completed and returned, yielding a response rate of 73.4%. Almost all companies used the 36 factors used in the survey. Drawings and specification alteration during execution, lack of labor experience, material shortage, rework, and supervisors’ absenteeism are the factors which strongly affect productivity in the construction companies. If these factors are taken seriously, then the performance and productivity level will definitely show positive results and encourage progress in these companies. Strategies to improve productivity in the construction companies in Ajdabiya are proposed in this research. Several recommendations to help increase the productivity level in the Libyan construction industry are provided. These recommendations include encouraging more organizational training for lower-level supervisors who are directly responsible for the people who are handling the tools, providing training, mentoring front-line supervisors, and improving the project planning phase, including organization, clear division of responsibilities, and identifying the scope of work for all parties involved. Other recommendations are managing construction activities with proper sequencing, e.g., timely equipment arrival and material and proper planning, and providing sufficient resources on-site to coordinate contractors.

Source: International Journal of Research and Reviews in Applied Sciences
July - September (Vol. 40, Issue 1) - 2019

3. ANALYSIS OF A SINGULAR PARABOLIC PARTIAL DIFFERENTIAL EQUATION BY USING ALGEBRAIC APPROACHES
by Alfred Huber
Abstract

In this paper we suggest different algebraic approaches to analyze the solution structure (or solution manifold) of a nonlinear singular parabolic partial differential equation (nPDE) importantly in applications of theoretical economics. The crucial step is the fact that the solution manifold of a general nPDE under consideration can be expressed in terms of special functions which are solutions of a specific (nonlinear) first-order ordinary differential equation (nODE), e.g. the Riccati equation. By using algebraic methods derived by the author we further show how one can augment the solution manifold in order to get different classes of solutions. Then we analyze and interpret (if possible) the meaning of these solutions.

Source: International Journal of Research and Reviews in Applied Sciences
July - September (Vol. 40, Issue 1) - 2019
4. SIMPSON'S RULE AND ROMBERG INTEGRATION FOR SOLVING NON-LINEAR FREDHOLM INTEGRAL EQUATION
by A.M. Al-Bugami
Abstract

When we talk about Fredholm integral equations we are talking about equations of paramount importance for solving the problems of applied sciences and study of natural phenomena: physics, engineering and biological, whether these equations linear or nonlinear, homogeneous or nonhomogeneous, with the continuous kernel or singular kernel. There are many different numerical methods to solve these equations. Many of the references discussed many numerical methods to solve linear Fredholm integral equations of which (Kress [1], Kanwal [2], Atkinson [3], and Mirzaee [4] ). In [5], Guoqiang and Jiong discussed the extrapolation of Nystrom solution for two dimensional nonlinear Fredholm integral equations. In [6], Emamzadeh and Kajani studied the nonlinear Fredholm integral equation of the second kind with quadrature methods. Allahviranloo and Ghanbari in [7], discussed the Discrete homotopy analysis method for the nonlinear Fredholm integral equations. In [8], Shahsavaran solved the nonlinear integral equations of the second kind using Lagrange Functions. Matoog in [9], discussed the numerical treatment for solving nonlinear integral equation. In [10], AL-Bayati and others, used Romberg Algorithm to solve a system of nonlinear Fredholm integral equations of the second kind.

Source: International Journal of Research and Reviews in Applied Sciences
July - September (Vol. 40, Issue 1) - 2019
5. SOME TECHNIQUES FOR SOLVING FREDHOLM-VOLTERRA INTEGRAL EQUATION OF THE SECOND KIND
by A.M. Al-Bugami
Abstract

In this paper, the existence and uniqueness of solution of the linear Fredholm- Volterra integral equation (LF-VIE) of the second kind with continuous kernel is discussed and proved, then we use a numerical method to reduce this type of equations to a system of Volterra integral equations.RungeKutta method (R.KM)and Block by block method (Bby BM) are used to solve a system of linear Volterra integral equations (SLVIEs)of the second kind with continuous kernel. Numerical examples are considered to illustrate the effectiveness of the proposed methods and the error is estimated.

Source: International Journal of Research and Reviews in Applied Sciences
July - September (Vol. 40, Issue 1) - 2019
6. FACTORS CONTRIBUTING TO POOR PROJECT DELIVERY IN MALAYSIA
by Abdelnaser Omran and Mohamed Saad Hamad Saleh
Abstract

ABSTRACT Delay is a common issue in the construction industry around the world, and it is also happening in Malaysia. There are many factors that can influence the project delivery in a construction project. Many problems will be arising during the implementation of the construction project. The common problems of the project such as exceed the time and cost estimate and not within the standard required of quality. These are the condition that contributes to poor project delivery when the project that not delivered within the requirement of the client, out of construction budget and not completed within the time and schedule. It can lead to even worse like project failure. It is important to find out the major causes of poor project delivery in order to propose ways to prevent and mitigate these issues. Thus, this study was aimed at identifying the factors that cause a poor project delivery in Malaysia. To achieve the aim of the study, a questionnaire sent out 320 targeted respondents included clients, project managers, contractors and consultants basically in Penang and Kedah states, of these, 264 sets of questionnaires were returned and analyzed with a response rate of 82.8%. As results, it was found that the F-statistics for construct 3 was significant at 5% level, defining enough evidence to accept that values of all the coefficients are different from zero or finally Construct 3 is Statistically Good Fit for the decision making.

Source: International Journal of Research and Reviews in Applied Sciences
July - September (Vol. 40, Issue 1) - 2019