The Impact of the Formation and the Jurisdiction of the Constitutional Court (CC) on the Essential Rights and Freedoms in the Light of the 1952 Jordanian Constitution and its Amendments

Judicature, generally, and constitutional judicature, specifically, are considered a guardian over the freedoms of the public and the rights of individuals in all countries of the world. From that basis, the Jordanian constitutional legislator founded an independent constitutional court that coincides with the constitutional amendments applied in 01/10/2011 and it specified the method of forming this court and determined its competences and jurisdictions. The formation and the extent of the court's jurisdiction are known to affect the essential rights and freedoms in one way or the other, especially when the Executive Authority solely appoints members of this court, which does not coincide with the independence of the judicial system. This is further shown when we compare how the Constitutional Court is formed in Jordan as appose to other countries. The result is that the Jordanian constitutional legislator does not benefit in any way from other countries' experiences while specifying the formation method of the Constitutional Court. Regarding the jurisdictions of the court, the amended Jordanian constitution has specified the court with jurisdictions of overseeing and monitoring the constitutionality of applicable laws and regulations as well as interpreting constitutional provisions while oversight. Oversight takes place in two methods; the first is the direct approach, which is exclusive to the House of Representatives, the House of Senates and the Cabinet. The second is the indirect approach, where one part of litigation demands the court not to enforce a regulation that is in breach of the constitution (defence of non constitutionality) in the pending case before the court. The court then, refers the defence to the court of Cassation which then considers its referral to the Constitutional Court (CC) to determine the constitutionality of the regulation. Giving ordinary courts the authority to accept or overrule a defence, based on the validity of the defence takes away from the exclusivity of the CC to oversee constitutionality, therefore, jeopardizing essential rights and freedoms of individuals.

A stage-structured delayed advection reaction-diffusion model for single species

In this paper, we derived a delay advection reaction-diffusion equation with linear advection term from a stage-structured model, then the derived equation is used under the homogeneous Dirichlet boundary conditions u_m (0,t)=0, u_m (L,t)=0, and the initial condition u_m (x,0)=u_m^0 (x)>0,x∈[-τ,0] with u_m^0 (0)>0 in order to find the minimum value of domain L that prevents extinction of the species under the effect of advection reaction diffusion equation. Finally, for the measurement the time lengths from birth to the development of the species population, time delays are integrated

Improvement Of Landslide Prediction System Based On Hybrid Neural Networks (Penang Island, Malaysia)

Landslides are one of the most aggressive natural disasters that cause loss of lives and of billions dollars in damages annually worldwide. They pose a threat to the safety of human lives, the environment, resources and property. It is one of the natural disasters that occur quite often in Malaysia and particularly in Penang Island during heavy rainy seasons. Numerous researches on landslides studies have been done based on Penang Island. However, many issues seriously related to landslides have not been solved yet. These issues include the extraction of new factors which cause landslides, investigation on the optimum factors which cause landslides and the generation of an accurate landslide hazard map for Penang island. In addition to that, the landslide hazard prediction intelligent system, either for Penang Island or for the entire world is still being investigated up to this date. For that reason, an intelligent landslide hazard mapping system is proposed. It consists of three stages: factor extraction, factor selection and Artificial Neural Network (ANNs) as an analysis tool. Twenty one factors are used in this study where nine factors were collected from different governmental agents. The rest of the factors (twelve) were extracted from the Digital Elevation Models (DEM), seven of these factors were extracted and used for the first time on Penang Island. In the factor selection phase. six factor selection techniques are employed to select the most important factors in the landslide prediction

Solving delay differential equations by Runge-Kutta method using different types of interpolation

Introduction to delay differential equations (DDEs) and the areas where they arise are given. Analysis of specific numerical methods for solving delay differential equation is considered. A brief discussion on Runge-Kutta method when adapted to delay differential equation is introduced. Embedded Singly Diagonally Implicit Runge-Kutta (SDIRK) method of third order four-stage in fourth order five-stage which is more attractive from the practical point of view is used to solve delay differential equations. The delay term is approximated using three types of interpolation that is the divided difference interpolation, Hermite interpolation and In't Hout interpolation. Numerical results based on these three interpolations are tabulated and compared. Finally, the stability properties of SDIRK method when applied to DDEs using Lagrange interpolation and In't Hout interpolation are investigated and their regions of stability are presented

Runge-Kutta Methods for Solving Ordinary and Delay Differential Equations

An introduction to Runge-Kutta methods for the solution of ordinary differential equations (ODEs) is introduced. The technique of using Singly Diagonally Implicit Runge-Kutta (SDIRK) method for the integration of stiff and non-stiff ODEs has been widely accepted, this is because SDIRK method is computationally efficient and stiffly stable. Consequently embedded SDIRK method of fourth-order six stage in fifth-order seven stage which has the property that the first row of the coefficient matrix is equal to zero and the last row of the coefficient matrix is equal to the vector output value is constructed. The stability region of the method when applied to linear ODE is given. Numerical results when stiff and non-stiff first order ODEs are solved using the method are tabulated and compared with the method in current use. Introduction to delay differential equations (DDEs) and the areas where they arise are given. A brief discussion on Runge-Kutta method when adapted to delay differential equation is introduced. SDIRK method which has been derived previously is used to solve delay differential equations; the delay term is approximated using divided difference interpolation. Numerical results are tabulated and compared with the existing methods. The stability aspects of SDIRK method when applied to DDEs using Lagrange interpolation are investigated and the region of stability is presented. Runge-Kutta-Nystróm (RKN) method for the solution of special second-order ordinary differential equations of the form ),(yxfy=′′ is discussed. Consequently, Singly Diagonally Implicit Runge-Kutta Nystróm (SDIRKN) method of third-order three stage embedded in fourth-order four stage with small error coefficients is constructed. The stability region of the new method is presented. The method is then used to solve both stiff and non-stiff special second order ODEs and the numerical results suggest that the new method is more efficient compared to the current methods in use. Finally, introduction to general Runge-Kutta-Nystrom (RKNG) method for the solution of second-order ordinary differential equations of the form ),,(yyxfy′=′′ is given. A new embedded Singly Diagonally Implicit Runge-Kutta-Nystróm General (SDIRKNG) method of third-order four stage embedded in fourth-order five stage is derived. Analysis on the stability aspects of the new method is given and numerical results when the method is used to solve both stiff and non-stiff second order ODEs are presented. The results indicate the superiority of the new method compared to the existing method

Evaluation of the Professional Diploma in Teaching Program by Students in Universities. A Case Study of UAE

The researcher assessed the professional diploma in the teaching program at one of the institutions in the United Arab Emirates from the students’ perspectives in this study. To reach the desired results, the researcher utilized the descriptive-analytical approach. The data was gathered using a questionnaire with 39 items divided into four sections: program objectives, program contents, program outputs, and the teaching and learning process. The questionnaire was distributed to 271 male and female students in the 2018/2019 academic year program. According to research findings, students rated the curriculum highly in all areas. There have been no significant disparities between the four components assessments. Gender, specialization, years of experience, and educational level are unaffected. The outcomes of this study will add to the body of information, allowing for a better understanding of the features and behaviors of diplomas in teaching program execution in various nations

Developing a Hybrid Model to Predict Student First Year Retention and Academic Success in STEM Disciplines Using Neural Networks

Understanding the reasoning behind the low enrollment and retention rates of Underrepresented Minority (URM) students (African Americans, Hispanic Americans, and Native Americans) in the disciplines of science, technology, engineering, and mathematics (STEM) has concerned many researchers for decades. Numerous studies have used traditional statistical methods to identify factors that affect and predict student retention. Recently, researchers have relied on using data mining techniques for modeling student retention in higher education [1]. This research has used neural networks for performance modeling in order to obtain an adequate understanding of factors related to first year academic success and retention of URM at Virginia Commonwealth University. This research used feed forward back-propagation architecture for modeling. The student retention model was developed based on fall to fall retention in STEM majors. The overall freshman year GPA was used to model student academic success. Each model was built in two different ways: the first was built using all available student inputs, and the second using an optimized subset of student inputs. The optimized subset of the most relevant features that comes with the student, such as demographic attributes, high school rank, and SAT test scores was formed using genetic algorithms. A further step towards understanding the retention of URM groups in STEM fields was taken by conducting a series of focus groups with participants of an intervention program at VCU. Focus groups were designed to elicit responses from participants for identifying factors that affect their retention the most and provide more knowledge about their first year experiences, academically and socially. Results of the genetic algorithm and focus groups were incorporated into building a hybrid model using the most relevant student inputs. The developed hybrid model is shown to be a valuable tool in analyzing and predicting student academic success and retention. In particular, we have shown that identifying the most relevant student inputs from the student’s perspective can be incorporated with quantitative methodologies to build a tool that can be used and interpreted effectively by people who are related to the field of STEM retention and education. Further, the hybrid model performed comparable to the model developed using the optimized set of inputs that resulted from the genetic algorithm. The GPA prediction hybrid model was tested to determine how well it would predict the GPA for all students, majority students and URM students. The root mean squared error (RMSE) on a 4.0 scale was 0.45 for all students, 0.47 for majority students, and 0.45 for URM students. The hybrid retention model was able to predict student retention correctly for 74% of all students, 79% of majority students and 60% of URM students. The hybrid model’s accuracy was increased 3% compared to the model which used the optimized set of inputs

Self-Esteem and its Relationship to some Demographic Variables among Students with Learning Disabilities

This study aimed at identifying self-esteem and its relationship to some demographic variables among students with learning disabilities in Irbid, Jordan. The study used the descriptive methodology and used a scale to measure the levels of self-esteem among 2000 male and female students from the third and fourth grades in primary schools in Irbid city. The results revealed that the level of self-esteem was average. There were apparent significant differences in the levels of self- esteem due to the effect of gender, and the differences came in favor of males. The results also showed no statistically significant differences due to the effect of the school grade. In light of the results of the study, the researcher recommends raising the level of the students’ self-esteem through cooperation between school administrations, teachers, and students’ parents, and researchers conducting developmental studies, comparing levels of shyness and self-esteem among students at different ages and environments

The difficulty and implementation of online assessment in higher education

The study goal is to look into the difficulties of online assessment in higher education and how it could be implemented. In order to achieve this goal, this study must evaluate the strengths and weaknesses of e-assessment activities based on a review of university experience. Cheating, technology, integrating learning goals, and student adherence to deliver evaluations were all recognized as major concerns in online examinations. The most efficient approach for reducing cheating was shown to be developing different responses for each student. It was also discovered that regulating academic integrity violations through an online presentation was a viable option. Integrating various assessment procedures, such as report submission with an online platform, aids in the reduction of cheating by allowing the examiner to confirm that the submitted work is the student's work