Saudi EFL High School Learners’ Attitude Toward Learning English

Attitude is an important factor that influences evolving English language learning and determines whether the learner will embrace learning or not. This study aimed at investigating the attitudes of high school learners in Saudi Arabia toward English learning. To achieve this, the descriptive method was used. To collect the data, a 24-item attitude questionnaire was administered to measure learners’ attitudes. Participants consisted of 118 randomly chosen learners in their third year of high school. The results showed that Saudi English language learners had a positive attitude toward learning English. The findings suggested that teachers should create a pleasant classroom atmosphere and design experiences that match the learners’ interests. The study also recommended that other studies should examine the attitude of learners toward learning specific skills, such as writing or reading stories, as well as determine the challenges faced during English learning. Keywords: Attitude, English as a foreign language (EFL) learners, Language learning. DOI: 10.7176/JEP/11-20-10 Publication date:July 31st 202

Regulating Fiduciary Duties of Directors Towards Company Property in England and Saudi Arabia: a Comparative Analysis

This thesis investigates the regulation of fiduciary duties of directors towards company property in England and Saudi Arabia. The analysis concentrates on the statutory law of both countries as the main legal instrument to prevent exploitation of company property by company directors. The study follows a functionalist approach to compare the legal systems of England and Saudi Arabia, taking into account the socio-cultural ramifications for the application of law to regulate the fiduciary duties of company directors towards company property. The study argues that despite belonging to different law families and having developed in different socio-cultural environments, the legal systems of both countries face a similar issue of effective prevention of company property exploitation by company directors. Further, it is noted that the statutory provisions aimed at regulating the fiduciary duties of company directors towards company property are not completely effective. The main contribution to knowledge provided by the thesis consists in making suggestions for statutory amendments in England and Saudi Arabia for a more effective regulation of directors’ fiduciary duties towards company property. A further original contribution of the study is in exploring the different features in each legal system that can be effectively transferred and applied to the other system in order to improve the regulation of directors’ fiduciary duties towards company property.Saudi Cultural Burea

Challenges and opportunities of e-fulfilment operations in the Gulf Cooperation Council

Electronic commerce (EC) in scholarship and practice has been richly discussed. Consumers’ fulfilment is considered a potential factor for firms. EC involves different processes, from inbound to outbound, which have to maintain consistency of flow within the booming e-commerce market. As a result, the variety of tools employed has increased, such as omnichannel marketing and the use of smart phones. Logistics is considered one of the major stages that can support the process of EC and achieve consumers’ fulfilment. This thesis explores the issues of electronic commerce fulfilment (ECF) in the five Gulf Cooperation Council (GCC) countries.The extent of ECF in the GCC online market is little known, as is how logistics activities operate, how ECF models are assembled and why. Whether or not logistics activity is considered in a firm’s strategy also remains a question for research. Therefore, this thesis investigates pure-player (PP) and multichannel (MC) firms and involves logistics service providers (LSPs) in the five GCC countries. A wide range of consumers from small and large cities across the five countries also contributed to obtaining information required to achieve the study’s objective and contribute to knowledge. This study adopted a qualitative and inductive approach in using semi-structured interviews to collect data. Fifty-three participants (owners, managers, logistics managers, and consumers) were interviewed to provide an objective study aimed at making e-commerce better and more efficient.This study finds logistics models are not considered a priority in a firm’s strategy plan and cultural factors greatly affect e-fulfilment, such as when using another language during communication and delivery processes. Communication between firms and providers is also considered to be unclear. Furthermore, the business-to-consumer (B2C) segment is still not a target for most LSPs. Hence, policy plays an essential role, such as in banning the entry of lorries to a city or applying employment conditions when hiring citizen drivers, and has an effect on ECF. Mistrust emerged as a factor in the limited options for payment. For example, the cash on delivery (COD) method is strongly preferred by most consumers. Innovative solutions have not been provided as required by global LSPs, particularly in the cultural context, although some provision has been made, such as in the case of women not being allowed to drive in Saudi Arabia with imprecise postal system and delivery needs to be pre-arranged. Telephone numbers and shipment tracking are still not clear for firms and consumers, as telephone numbers are often incorrect, telephones are not answered and tracking is not available or is imprecise. As a result, the findings reveal eight themes grouped into three categories: logistics activity, purchasing methods and cultural effects and also proposes new models for ECF

Modeling of Renewable Resources in Distribution System Planning and Operation

In recent decades, interest in placing renewable resources in conventional power systems has increased because of their ability to reduce fossil fuel consumption, which leads to the preservation of the environment. The rapid increase in employing these renewable resource-based DGs drives the system to be more dynamic, and causes many obstacles that need to be overcome. Power system planners and operators should look at the distribution system from another angle, taking into consideration the intermittent behavior of most renewable resources. Furthermore, solid models that are able to handle the uncertainty in generation levels are required. This thesis presents a comprehensive probabilistic model for representing renewable energy resources in long term planning problems. This model utilized large historical data sets, grouping technique, and statistical analysis in order to handle the fluctuations that are caused by the variations in wind speed or solar irradiance. In this research, renewable resources (wind and PV based DGs) ae well as dispatchable units are optimally allocated and sized using a probabilistic optimization model. This model incorporates the intermittent nature of wind speed and solar radiation into the deterministic optimal power flow equations. The variability from the load side and the uncertainty from the feeding side are considered. Genetic algorithm is used in order to minimize the annual energy losses of a distribution system. This thesis proposes a new iterative-based optimization algorithm is proposed in order to determine the minimum number of states that can precisely describe or represent the behavior of wind speed and solar irradiance in operational planning problems. This algorithm is evaluated using a power system planning problem. The proposed algorithm takes into account the annual energy losses and the total DG penetration level and considers them as an indication of how far the proposed method's outcomes are from the actual results. Three di fferent data groupings are applied (hourly, seasonally, and yearly) to investigate the variety of weather and electricity demands on the proposed method. The obtained results should be maintained within an acceptable limit of error which is in this thesis, 2:5%, and any violation of this limit will interrupt the algorithm sequences. The importance of this method actually lies in its ability to reduce the complexity in reliability analysis such that the number of overall system states will be minimized when the analytical evaluation methods are utilized

Incentive-Based Expansion Planning and Reliability Enhancement Models for Smart Distribution Systems

Due to the rapid progress toward the implementation of smart grid technologies, electric power distribution systems are undergoing profound structural and operational changes. Climate concerns, a reduction in dependency on fossil fuel as a primary generation source, and the enhancement of existing networks constitute the key factors in the shift toward smart grid application, a shift that has, in fact, already led power industry stakeholders to promote more efficient network technologies and regulation. The results of these advances are encouraging with regard to the deployment and integration of small-scale power generation units, known as distributed generation units (DGs), within distribution networks. DGs are capable of contributing to the powering of the grid from distribution or even sub-distribution systems, providing both a positive effect on network performance and the least adverse impact on the environment. Smart grid deployment has also facilitated the integration of a variety of investor assets into power distribution systems, with a consequent necessity for positive and active interaction between those investors and local distribution companies (LDCs). This thesis proposes a novel incentive-based distribution system planning (IDSP) model that enables an LDC and DG investors to work collaboratively for their mutual benefit. Using the proposed model, the LDC would establish a bus-wise incentive program (BWIP) based on long-term contracts, which would encourage DG investors to integrate their projects at the specific system buses that would benefit both parties. The model guarantees that the LDC will incur minimum expansion and operation costs while concurrently ensuring the feasibility of DG investors’ projects. The proposed model also provides the LDC with the opportunity to identify the least-cost solution among a combination of the proposed BWIP and traditional expansion options (i.e., upgrading or constructing new substations, upgrading or constructing new lines, and/or reconfiguring the system). In this way, the model facilitates the effective coordination of future LDC expansion projects with DG investors. To derive appropriate incentives for each project, the model enforces a number of economic metrics, including the internal rate of return, the profit-investment ratio, and the discounted payback period. All investment plans committed to by the LDC and the DG investors for the full extent of the planning period are then coordinated accordingly. The intermittent nature of both system demand and wind- and PV-based DG output power is handled probabilistically, and a number of DG technologies are taken into account. Several linearization approaches are applied in order to convert the proposed model into a mixed integer linear programming (MILP) model, which is solved using a CPLEX solver. Reliability of service in a deregulated power environment is considered a major factor in the evaluation of the performance of service providers by consumers and system regulators. Adhering to imposed obligations related to the enhancement of overall system reliability places a substantial burden on the planning engineer with respect to investigating multiple alternatives and evaluating each option from both a technical and an economical perspective. This thesis also proposes a value-based reinforcement planning model for improving system reliability while maintaining reliability metrics within allowable limits. The optimal allocation of tie lines and normally open switches is determined by this planning model, along with required capacity upgrades for substations and lines. Two hierarchical levels for system operation under contingencies, namely, the restoration process and islanding-based modes, are applied in the model. A probabilistic analytical model is proposed for computing distribution system reliability indices based on consideration of these two hierarchical operating levels and taking into account variations in system demand, DG output power, and the uncertainty associated with system components. Due to the nature and complexity of these kinds of problems, a metaheuristic technique based on a genetic algorithm (GA) is implemented for solving this model. This thesis also proposes a new iterative planning model for smart distribution systems in which system reliability is considered a primary component in the setting of incentive prices for DG owners. A new concept, called generation sufficiency for dynamic virtual zones, is introduced in the model as a means of enhancing reliability in areas that are subject to reliability issues. To avoid any contravention of operational security boundaries, DG capacity is represented by two components: normal DG operating capacity and reserve DG capacity. The MILP planning model is constructed in a GAMS environment and solved with the use of a CPLEX solver

Krylov subspace split Bregman methods

Split Bregman methods are popular iterative methods for the solution of large-scale minimization problems that arise in image restoration and basis pursuit. This paper investigates the possibility of projecting large-scale problems into a Krylov subspace of fairly small dimension and solving the minimization problem in the latter subspace by a split Bregman algorithm. We are concerned with the restoration of images that have been contaminated by blur and Gaussian or impulse noise. Computed examples illustrate that the projected split Bregman methods described are fast and give computed solutions of high quality