Modeling and Simulation of TCSC- Operated Single-Phase Induction Motor

As single-phase induction motor (SPIM) is not a self-starting motor, it has been a common practice to add an auxiliary component to the motor circuit to establish a starting torque. Traditionally, two capacitors are used in SPIM to establish and improve its starting torque and to enhance its running performance. As the Thyristor-Controlled Series Compensator (TCSC) is a control device that considerably alters impedance of the circuit in which it is inserted to be capacitive or inductive, it can be utilized for starting and running purposes in SPIM. This paper explores the representation of the TCSC as a variable impedance and investigates its valuable impacts, when it is operated in its capacitive mode, on the transient behavior of SPIM. It presents a state-space model of the TCSC-inserted SPIM and shows that inserting the TCSC in the auxiliary winding of the SPIM introduces more benefits compared to the traditionally used methods of starting and running the SPIM. The simulation results of the test cases presented in the paper, which include comparisons between the presented approach and the traditional approaches, emphasize that incorporating TCSC with the SPIM brings advantageous features to start and run the motor. The paper will show that controlling the firing angle of the TCSC may attain the desired electromagnetic torque and speed characteristics. The simulation results presented in the paper indicate that the TCSC can effectively replace the traditional auxiliary component and the accompanying mechanical centrifugal switch, which in turn may reduce the size and cost of the SPIM

The Effectiveness of Professional Training Programs in Developing the Digital Skills of Arabic Language Teachers from the Perspective of Principals and Academic Supervisors

The researcher of the present study aimed to explore the effectiveness of professional training programs in developing the digital skills of Arabic language teachers in the public schools in Zarqa. The sample consists from 108 female and male principals and academic supervisors. She used a questionnaire that consists from 41 items. This questionnaire sheds a light on 4 digital skills-related areas. It was found that the digital skill level of Arabic language teachers in the four areas jointly is moderate. It was found that there are differences between the respondents’ attitudes towards the effectiveness of the aforementioned program in developing (intermediate and advanced skills). Keywords:Digital skills, professional training, Arabic language teachers. DOI: 10.7176/JEP/11-36-07 Publication date: December 31st 2020

Gravitational-Search Algorithm for Optimal Controllers Design of Doubly-fed Induction Generator

Recently, the Gravitational-Search Algorithm (GSA) has been presented as a promising physics-inspired stochastic global optimization technique. It takes its derivation and features from laws of gravitation. This paper applies the GSA to design optimal controllers of a nonlinear system consisting of a doubly-fed induction generator (DFIG) driven by a wind turbine. Both the active and the reactive power are controlled and processed through a back-to-back converter. The active power control loop consists of two cascaded proportional integral (PI) controllers. Another PI controller is used to set the q-component of the rotor voltage by compensating the generated reactive power. The GSA is used to simultaneously tune the parameters of the three PI controllers. A time-weighted absolute error (ITAE) is used in the objective function to stabilize the system and increase its damping when subjected to different disturbances. Simulation results will demonstrate that the optimal GSA-based coordinated controllers can efficiently damp system oscillations under severe disturbances. Moreover, simulation results will show that the designed optimal controllers obtained using the GSA perform better than the optimal controllers obtained using two commonly used global optimization techniques, which are the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO)

Multilingualism in the linguistic landscape of urban Jordan

The main purpose of this study is to investigate language practices in the linguistic landscape (LL) of Jordanian cities. There have been few research studies that examine the LL of Jordanian cities, and none has investigated multilingualism. This study is intended to fill this gap in LL research. By means of qualitative and quantitative methods, it aims to discover the extent to which multilingualism is reflected in the LL. The main fieldwork was conducted in November and December 2012 in urban Jordan. Ten streets were selected in each of six major Jordanian cities, including Irbid, Salt, Zarqa, Amman, Karak and Aqaba, sixty streets in total. A LL item represents ‘any piece of text within a spatially definable frame’ (Backhaus, 2007). 4070 signs were recorded as multilingual (c. 51%), whereas 3967 signs were categorised as monolingual (c. 49%). To discover correlations between types of signs and existing languages and scripts, and to measure these against conflicting language policies, signs are categorised as ‘top-down’ or ‘bottom-up’. The notions of ‘code preference’ (Scollon & Scollon, 2003) and dynamics of language contact are employed to understand the semiotics of writing in the LL of Jordanian cities. The main data findings indicate that minority languages are almost absent, so a questionnaire was introduced as an additional supportive source to the analysis of the findings, providing a qualitative dimension to the study. The study was conducted in July 2013, during which period the researcher interviewed 32 participants. The primary objective of this secondary study is to reflect on plausible reasons explaining the limited presence of minority languages in the visual public space. The main data indicate a dominance of both Modern Standard Arabic (MSA) and English on signs, because they are closely related to Arab nationalism and globalization respectively. Jordanian Arabic is deleted from the top-down LL, because it is closely linked to informal domains. Classical Arabic (CA) is mainly used to convey religious functions in the LL. Mixed codes, Romanised Arabic (RA) and Arabacised English (AE), are commonly used in the LL to reflect ‘glocalisation’. French, German, Italian, Spanish, Turkish and Russian are found mainly to be used on brand name and business name signs for reasons of European linguistic fetishes and tourism. The data indicate that minority languages are significantly marginalised on both top-down and bottom-up signs. Several reasons lie behind the limited visibility of established minority languages in the LL. Spatial distribution of migrant communities, the small size of minority communities, lack of (sufficient) institutional and parental support, migration and absence of close ties with families and linguistic peers are behind different stages of language maintenance and shift among older migrant groups. Linguistic russification, hostility, instrumentality of both Arabic and English and top-down language policies enacted by the Jordanian government contribute to the limited visibility of minority languages in the LL. Although foreign workers’ minority languages tend to be maintained, the instrumental functions of both Arabic and English, Islam, and the small sizes of economic minority groups have each played a key role in the limited visibility or invisibility of minority languages in the LL

Reconstruction a protein 3D structure from it contact map: Tools comparison

Reconstruction a protein 3D structure using its contact map is not less than revolutionizes molecular biology.Recently, there are many research efforts that provide guidelines for protein contact map prediction; these efforts used machine learning approaches such as neural network and distance geometric.One of the approaches to help biologists is applying a software technique. As the consequence there are many categories of tools that have been developed to incorporate this technique.This paper analyses several predicting protein 3D structure tools. These tools are built to help to understand and predict a protein 3D structure.The paper briefly discusses the advantages of these tools; it also, gives the disadvantages of the existing tools, and, finally, talks about the proposed reconstructing a protein 3D tool

Hybrid harmony search algorithm for continuous optimization problems

Harmony Search (HS) algorithm has been extensively adopted in the literature to address optimization problems in many different fields, such as industrial design, civil engineering, electrical and mechanical engineering problems. In order to ensure its search performance, HS requires extensive tuning of its four parameters control namely harmony memory size (HMS), harmony memory consideration rate (HMCR), pitch adjustment rate (PAR), and bandwidth (BW). However, tuning process is often cumbersome and is problem dependent. Furthermore, there is no one size fits all problems. Additionally, despite many useful works, HS and its variant still suffer from weak exploitation which can lead to poor convergence problem. Addressing these aforementioned issues, this thesis proposes to augment HS with adaptive tuning using Grey Wolf Optimizer (GWO). Meanwhile, to enhance its exploitation, this thesis also proposes to adopt a new variant of the opposition-based learning technique (OBL). Taken together, the proposed hybrid algorithm, called IHS-GWO, aims to address continuous optimization problems. The IHS-GWO is evaluated using two standard benchmarking sets and two real-world optimization problems. The first benchmarking set consists of 24 classical benchmark unimodal and multimodal functions whilst the second benchmark set contains 30 state-of-the-art benchmark functions from the Congress on Evolutionary Computation (CEC). The two real-world optimization problems involved the three-bar truss and spring design. Statistical analysis using Wilcoxon rank-sum and Friedman of IHS-GWO’s results with recent HS variants and other metaheuristic demonstrate superior performance

The Impact of the Analogue Thinking Strategy on Developing the Listening Comprehension Skills of Fourth-Grade Female Students in the Arabic Language Subject

The study aimed to identify the impact of the analogue thinking strategy on developing the listening comprehension skills of fourth-grade female students in the Arabic language subject. The researcher has identified a list of listening comprehension skills, consisting of four major skills, which divides into 24 branch skills and built the study tool of listening comprehension skills test. The study sample consisted of 69 female students of the primary fourth grade from two governmental schools subject of Directorate of Education in Zarqa governorate. The sample was comprised two groups, experimental which contains 35 female students who are taught according to the analogue thinking strategy, and the other is a control group which is composed of 34 female students who are taught by using the traditional way of learning. The results of the study showed statistically significant differences (α= 0.05) in the listening comprehension skills, which refers to the analogue thinking strategy and in favor of the experimental group obtaining an overall average of 60.59 while the controlled group obtained 50.47. In light of the results of the study, the researcher recommends including the teacher’s guide for the Arabic Language subject for the primary stage the listening comprehension skills and focusing on higher skills. Keywords: Listening Comprehension Skills, Analogue Thinking Strategy, Arabic Languag

Enhancing three variants of harmony search algorithm for continuous optimization problems

Meta-heuristic algorithms are well-known optimization methods, for solving real-world optimization problems. Harmony search (HS) is a recognized meta-heuristic algorithm with an efficient exploration process. But the HS has a slow convergence rate, which causes the algorithm to have a weak exploitation process in finding the global optima. Different variants of HS introduced in the literature to enhance the algorithm and fix its problems, but in most cases, the algorithm still has a slow convergence rate. Meanwhile, opposition-based learning (OBL), is an effective technique used to improve the performance of different optimization algorithms, including HS. In this work, we adopted a new improved version of OBL, to improve three variants of Harmony Search, by increasing the convergence rate speed of these variants and improving overall performance. The new OBL version named improved opposition-based learning (IOBL), and it is different from the original OBL by adopting randomness to increase the solution's diversity. To evaluate the hybrid algorithms, we run it on benchmark functions to compare the obtained results with its original versions. The obtained results show that the new hybrid algorithms more efficient compared to the original versions of HS. A convergence rate graph is also used to show the overall performance of the new algorithms