Saudi Arabia Emergency and Disaster Response

Although the kingdom of Saudi Arabia has most recently drawn media and global attention for the escalation terrorism and Hajj incidents, very little attention is paid to the increasing frequency of natural disaster affecting the country. Unfortunately, despite the increase in the number of these natural disasters, the government remains slow to react. This project provides a comprehensive and conclusive discussion on the negative impacts of poor response to these calamities. While the government is concerned with climate change and its role in increasing the frequency of natural disasters, it is important to pay attention to other disasters including human-inclined dangers and technological risks. Each of these calamities has had an adverse effect on the lives of all the people living or visiting the kingdom. There has been a proposition for establishing a government agency in order to improve disaster response. It has further been noted that this agency could coordinate between different government departments to implement crisis and rapid management as well as disaster readiness training programs for each and every sector of the nation. The agency would also work to offer support in case of emergency. Though the success of a program cannot be founded on the use of systems engineering, the project recognizes its significance towards attaining success. In a nut- shell, the project compels the Saudi government to think widely so as to prepare for and respond to the occurrence of disasters

THE EFFECT OF THE SYRIAN CRISIS ON THE PROFITABILITY OF THE COUNTRY\u27S PRIVATE BANKING SECTOR

This research analyses the effect of the Syrian crisis on the profitability of local private banks during the period from 2011 to 2018 using fixed effects estimator on panel data. The research studies all of the 14 Syrian private banks and includes bank-specific variables calculated from the published quarterly and annual reports of all the banks, as well as a variable for the Syrian crisis measured by the following macro-economic factors: the number of crisis-related casualties, the number of Syrians who fled the country as refugees or asylum seekers, and the Syrian Pound exchange rate against U.S. Dollar during the studied period. Using return on average assets (ROAA) as the dependent variable, the research results found that bank capital, deposits, and loans to assets all have a statistically significant positive effect on profitability at 1%, while operating efficiency and asset quality have a statistically significant negative effect on profitability at 1% and 5% respectively. Furthermore, the macro-economic variable of the Syrian crisis has a statistically significant negative effect on profitability at 1%. The results of this paper enhance the understanding of profitability determinants during crisis times and provide supervisory authorities and banks with important indicators regarding profitability in economic distress periods

THE IMPACT OF DYNAMIC WRITTEN CORRECTIVE FEEDBACK ON ARAB EFL INTERMEDIATE STUDENTS’ WRITING ACCURACY

This thesis is concerned with finding the impact of applying dynamic written corrective feedback (DWCF) on Arab intermediate EFL learners’ writing accuracy. The current study focuses on the writing components of content, organization, grammar, vocabulary, and mechanics. The main objective of this thesis is to examine how DWCF can affect intermediate EFL learners’ writing accuracy. The research included 38 grade eight learners as participants of the study. Both quantitative and qualitative research methods were used. The quantitative data was collected via the use of pre-post test research instruments while the survey research instrument gathered the qualitative data. The study found that DWCF has a positive impact on these intermediate EFL learners’ writing accuracy. The research results showed that the significant difference in learners’ writing accuracy between control and experimental groups was on four components (organization, grammar, vocabulary, and mechanics). Also, the participating students expressed positive perceptions and attitudes toward the use of DWCF. The study demonstrated that DWCF helps teachers to scaffold students’ writing accuracy from an early age by providing students with frequent corrective feedback that helps them to improve their writing skills

Combined supervised and unsupervised learning to identify subclasses of disease for better prediction

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonDisease subtyping, which aids in the development of personalised treatments, remains a challenge in data analysis because of the many different ways to group patients based upon their data. However, if I can identify subclasses of disease, this will help to develop better models that are more specific to individuals and should therefore improve prediction and understanding of the underlying characteristics of the disease in question. In addition, patients might suffer from multiple disease complications. Models that are tailored to individuals could improve both prediction of multiple complications and understanding of underlying disease characteristics. However, AI models can become outdated over time due to either sudden changes in the underlying data, such as those caused by new measurement methods, or incremental changes, such as the ageing of the study population. This thesis proposes a new algorithm that integrates consensus clustering methods with classification in order to overcome issues with sample bias. The method was tested on a freely available dataset of real-world breast cancer cases and data from a London hospital on systemic sclerosis, a rare and potentially fatal condition. The results show that nearest consensus clustering classification improves accuracy and prediction significantly when this algorithm is compared with competitive similar methods. In addition, this thesis proposes a new algorithm that integrates latent class models with classification. The new algorithm uses latent class models to cluster patients within groups; this results in improved classification and aids in the understanding of the underlying differences of the discovered groups. The method was tested on data from patients with systemic sclerosis (SSc), a rare and potentially fatal condition, and coronary heart disease. Results show that the latent class multi-label classification (MLC) model improves accuracy when compared with competitive similar methods. Finally, this thesis implemented the updated concept drift method (DDM) to monitor AI models over time and detect drifts when they occur. The method was tested on data from patients with SSc and patients with coronavirus disease (COVID)

A study of cohesion in international postgraduate Business students’ multimodal written texts: an SF-MDA of a key topic in finance

Empirical research studies of finance students’ language use have investigated students’ performance in finance courses and the effect of class attendance on students’ performance.Similarly, research on accounting students’ texts has been directed at readability of accounting narratives and lexical choices. Systemic Functional Linguistics (SFL) based research in multimodal communication and representation has been confined to school and workplace contexts. Whereas multimodal communication investigations in tertiary contexts has been conducted across the fields of mathematics, science and computing, and nursing, business courses have not been explored. The purpose of this paper is to report on a case study designed to investigate the key multimodal academic literacy and numeracy practices of ten international Master of Commerce Accounting students enrolled at an Australian university. Specifically, it aims to provide an account of the salient textual and the logical patterns through the analysis of cohesive devices in a key topic in the Principles of Finance course, namely capital budgeting techniques and management reports. This study is pertinent as most international ESL/EFL students’ enrolments in Australia and elsewhere is in business programs. This study is underpinned by Halliday’s (1985) Systemic Functional Linguistics (SFL) approach to language and Halliday and Hasan’s (1976) cohesion analysis scheme. The study employs a Systemic Functional Multimodal Discourse Analysis (SF-MDA) for the analysis of cohesive devices in the participants’ multimodal texts. Lexical cohesion formed the largest percentage of use, and in particular repetition of the same lexical items, followed by reference.The findings contribute to the description of the meaning-making processes in these multimodal artefacts. They provide a potential research tool for similar investigations across a broad range of educational settings. Implications of the findings for finance students and educators are finally presented

English-Arabic Translator Education Through Systemic Functional Linguistics: Analysis of Cohesive Devices in Investopedia Business Texts

In translation courses, students are asked to practice translation skills by translating a source text (ST) in a specific field. While teachers usually select texts based on topic and language accuracy, some such texts do not provide rich textual features that help students practice and improve their translation skills. This study aimed to analyze the cohesive features in business texts collected from “Investopedia” to investigate their suitability for use as STs to practice translation skills in the field of finance and administration. It was framed by Halliday’s (1978) systemic functional linguistics (SFL) approach to language and Halliday and Hassan’s (1976) cohesion analysis scheme. The findings demonstrated that the most prominent type used was lexical cohesion, followed by reference and conjunctions. Ellipses and substitution were rarely used. The findings indicated that the intensive use of lexical cohesion and the various subcategories used in these texts can help enrich the background knowledge of financial terminology and provide a communicative understanding of the ST while practicing various elements of textual features. The study provided a demonstration of the significance of SFL in providing coherent and cohesive STs that facilitate the needs of translation instructors and students in the field of finance and administration. Other SFL tools can be employed to provide a better understanding of these texts

The Fatigue Behaviour of Tension Lap Spliced Reinforced Concrete Beams Strengthened with Fibre Reinforced Polymer Wrapping

Many reinforced concrete structures containing lap splices were constructed before modern bond and fatigue design codes came into existence and are subjected to fatigue loading, which may lead to a bond failure even when the applied load is far below the ultimate load for a bond failure under a monotonic loading. Fatigue loads result in a deterioration of the bond interaction between the steel and concrete and interrupt the force transfer mechanism resulting in an increased deflection, an increased number of cracks and their widths, and a decreased load carrying capacity of reinforced concrete elements of structures. Some of these structures require strengthening to enhance their bond strength at lap splices. This study was aimed at increasing our understanding of the behaviour of the bond between the steel bar and the concrete along the lap splice region for structures subjected to cyclic loading. An additional aim of the study was to investigate the effect of fatigue loading on the bond between concrete and steel, and the ability of the new high and low modulus fiber-reinforced polymer (FRP) sheets to enhance the fatigue performance of a tension lap splice. Fifty three beams were cast and tested under monotonic and fatigue loading. The beams dimensions were 2200 mm in length, 350 mm in height and 250 mm in width. Each beam was reinforced with two 20M bars lap spliced in the constant moment region of the tension zone and two 10M bars in the compression zone outside the constant moment region. The test variables were the concrete cover, the presence or absence of FRP wrapping, the type of the FRP wrapping glass or carbon fiber-reinforced polymer (GFRP or CFRP), the type of loading and the fatigue load range. The minimum load applied was 10% of the static bond capacity of the specimen. The maximum load was varied to obtain fatigue lives between 1,000 and 1,000,000 cycles. The test frequency for all cyclic tests was 1.3 Hz. The results of the tests under monotonic load showed that the GFRP wrapped beams had an increase in bond strength of approximately 25% compared to the unwrapped beams for each of the concrete covers. However, the CFRP wrapped beams had a percentage increase in bond strength that decreased as the concrete cover increased. The CFRP wrapped beams had increases in bond strength of 71%, 60% and 44% compared to the unwrapped beams for concrete covers of 20 mm, 30 mm and 50 mm, respectively. The results of the tests under fatigue load showed that all beams failed by a bond failure except for those beams that exceeded the fatigue life limits for a longitudinal bar. As expected, these beams failed by fatigue rupture of the longitudinal steel bars. The GFRP and CFRP sheets increased the fatigue strength (measured as the applied load range for a given fatigue life) of the wrapped beams for all concrete covers compared to that of the unwrapped beams. The longitudinal splitting cracks for the FRP wrapped beams were finer in width and larger in number compared to those cracks for the unwrapped beams. A crack growth model was developed to calculate the fatigue life of the bond specimens and to calculate the slip and the deflection due to stress changes in the steel and concrete due to cracking, and compare it to the measured slip and deflection. There is also a good agreement between the calculated number of cycles with the actual fatigue data for all different wrapping conditions and all different concrete cover thicknesses. Also, only a small amount of the inelastic slip and the inelastic deflection are due to the stress changes in the steel and concrete due to splitting cracking. The remaining inelastic slip and inelastic deflection which are due to deformation of the concrete in front of the steel rebar lugs is much larger