United Arab Emirates University
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EXPLORING EARLY YEARS PRACTITIONERS’ PERSPECTIVES ABOUT THE PROSPECTS OF A NATURE-BASED EARLY CHILDHOOD LEARNING APPROACH IN THE UNITED ARAB EMIRATES (UAE)
Get PDFThis thesis is concerned with exploring early years practitioners’ perspectives on the benefits, challenges, and feasibility of incorporating a nature-based learning approach in the UAE’s early childhood education sector. A mixed-methods approach was employed, utilizing a structured questionnaire that gathered both quantitative and qualitative data from early years practitioners across the UAE. The quantitative analysis conducted using SPSS while thematic analysis was employed for qualitative analysis. The findings revealed a strong belief in the benefits of nature-based education, including enhanced creativity, problem-solving skills, emotional well-being, and environmental awareness among children. While challenges such as extreme weather conditions, lack of training, and limited access to green spaces were acknowledged, practitioners suggested adaptive strategies like scheduling outdoor activities during cooler hours, utilizing shaded areas, incorporating indoor nature-based elements, and leveraging virtual nature exploration tools. This study highlights the potential for nature-based education to be integrated into early childhood settings in the UAE with appropriate modifications
EXPLORING THE ROLE OF PERSONALITY TRAITS IN PREDICTING FINANCIAL VULNERABILITY: MODERATING EFFECTS OF DIGITAL LITERACY AND FINANCIAL LITERACY WITHIN THE FRAMEWORK OF THE THEORY OF PLANNED BEHAVIOR
Get PDFThe growing integration of digital financial services in the UAE has introduced new challenges in mitigating financial fraud, particularly in understanding individual susceptibility to such risks. This study explores the role of personality traits and shaping financial fraud vulnerability, employing the theory of planned behavior (TPB) to examine how extraversion, agreeableness, consciousness, neuroticism, and openness to experience influence this vulnerability. The study further assesses the mediating roles of subjective norms, attitude towards financial fraud, and perceived behavioral control in these relationships, as well as the moderating effects of digital and financial literacy.Results from a cross-sectional survey of 406 UAE residents was collected and data was analyzed using structural equation modeling (SEM) to evaluate the proposed hypotheses. The results reveal that neuroticism has a significant positive effect on financial fraud vulnerability, underscoring that emotionally unstable individuals are more susceptible to becoming fraud victims. On the contrary, conscientiousness exhibited a negative correlation with fraud vulnerability, indicating that diligent and systematic individuals are less likely to be targeted. Extraversion also shows a positive relationship with fraud susceptibility, indicating that sociable, confident, and assertive individuals may be more prone to fraud given their impetuous decision-making, high expectations and ease of trust in social relationships. On the other hand, openness to experience and agreeableness were not found to impact fraud vulnerability, indicating that these factors do not directly play a significant role in susceptibility to financial fraud.Moreover, attitude towards financial fraud were found to significantly mediate the relationship between personality traits and fraud vulnerability, while subjective norms and perceived behavioral control did not exhibit strong mediating effects. The study found no significant moderating influence of digital and financial literacy on these relationships. These findings offer important theoretical and practical insights. Theoretically, the study advances understanding of how personality traits contribute to financial fraud vulnerability. Practically, it suggests that fraud prevention strategies should focus on fostering positive attitude towards financial fraud towards risk management, alongside enhancing consumer education on personality-driven vulnerabilities. This research contributes to developing more personalized approaches to financial fraud within the UAE\u27s digital economy.This research aligns with the UAE objectives of financial inclusion and digitization, which are imperative in building an inclusive digital economy. This research puts forth actionable strategies that can be adopted to build customized fraud prevention strategies by addressing the risks associated with personality-driven weaknesses, protecting individuals. Moreover, the results further the UAE’s efforts to enhance financial literacy and build a resilient digital infrastructure
How Long-Term Rents Are Being Impacted by The Emerging of Short-Term Rents in Riyadh
Get PDFالملخص
شهدت الرياض مؤخراً نمواً سريعاً ومتسارعاً للإيجارات قصيرة المدة مما أربك سوق الإسكان بالمدينة بسبب التأثيرات التي أحدثتها على المخزون السكني طويل الأجل وأسعار إيجاراته. فظهور الأنشطة والمهرجانات الترفيهية على شاكلة موسم الرياض وموسم الدرعية والفعاليات المصاحبة بالإضافة إلى انتشار تطبيقات منصات الاستئجار اليومي للسكنات مثل Airbnb، أدى لخلق سوق جديدة للإيجارات قصيرة المدة ساهمت في تغيير رغبات الكثير من زوار المدينة من التوجه للفنادق إلى استئجار الوحدات السكنية لفترات قصيرة. اعتمدت الدراسة على تحليل بيانات أعداد الوحدات الموجهة للإيجارات اليومية ومتوسطات عائداتها من منصة Airbnb ومقارنتها ببيانات الوحدات الموجهة للإيجارات طويلة المدة وعائداتها والتي تم استخلاصها من منصة إيجارejar، وذلك على مستوى القطاعات الخمسة لمدينة الرياض وعينة من أحياء كل قطاع. تبين النتائج أن هناك انتعاش كبير لهذا السوق الإيجاري قصير المدة بعد ركود أصابه بسبب الإجراءات الاحترازية خلال جائحة كورونا، وهو ما أثر سلباً على سوق الإيجارات طويلة المدة وساهم في تجفيف مخزونها ورفع إيجاراتها وبالتالي تفاقم مشكلة الإسكان أكثر في المدينة. تخلص الدراسة إلى التوصية بالضرورة الملحة لتنظيم وتقنين هذا السوق الإيجاري الجديد حفاظاً على توازن السوق السكني بالرياض
IMPLEMENTING MAINTENANCE 4.0 METHODS IN VENTILATION SYSTEMS: A CASE STUDY IN UAEU LABORATORIES
Get PDFThis study introduces an advanced Maintenance 4.0 framework aimed at systematically evaluating and mitigating air quality risks within laboratory environments, specifically applied to the context of the United Arab Emirates University (UAEU). Employing real-time monitoring through sophisticated IQ-Air sensors, this research continuously captures key indoor environmental parameters, such as particulate matter concentrations (PM₁, PM₂.₅, PM₁₀), carbon dioxide (CO₂) levels, ambient temperature, and humidity. State-of-the-art machine learning algorithms are developed and operationalized to enhance ventilation system efficiencies and proactively forecast maintenance requirements, thereby transitioning from reactive to predictive maintenance strategies. Empirical results indicate that Maintenance 4.0 applications significantly enhance the capacity to detect periods of compromised air quality and facilitate timely, data-driven maintenance actions. Additionally, integrating Industry 4.0 technological innovations, including the Internet of Things (IoT) and advanced big data analytics, demonstrably improves overall system efficacy, occupant health, and environmental sustainability. The proposed methodological framework is robust, scalable, and aligns effectively with internationally recognized standards and guidelines, specifically ASHRAE 62.1, the World Health Organization (WHO), and the Environmental Protection Agency (EPA). Consequently, this research offers substantial contribution
SCHOOL LEADERSHIP INSIGHTS AND PRACTICES: UNDERSTANDING BULLYING PREVENTION STRATEGIES AMONG EDUCATIONAL TEACHERS IN PRIVATE AND PUBLIC SCHOOLS ACROSS THE UAE
Get PDFThis thesis investigates the detrimental effects of bullying on students, including impacts on their mental health, academic performance, and overall well-being. Addressing this issue necessitates a proactive strategy involving school leaders, teachers, and parents. Data were collected through a questionnaire, with selected items employing a 5-point Likert scale and others utilizing a multiple-choice format. Analysis was conducted using SPSS software, encompassing statistical tests such as descriptive statistics, one-way ANOVA, t tests, and logistic binary regression. The t test indicated that leadership practices implemented to prevent bullying in both public and private schools were highly effective and statistically significant (p \u3c .05). This research contributes to understanding how school leadership and teacher involvement influence the efficacy of bullying prevention strategies. By incorporating quantitative methodologies, the study provides a comprehensive examination of school policies, bullying awareness initiatives, and reporting systems. Findings highlight the importance of adopting context-specific approaches to bolster bullying prevention efforts within schools. Future research combining qualitative and quantitative analyses may yield deeper insights into real-world challenges encountered in bullying intervention strategies, thereby bridging the gap between policy formulation and practical implementation to ensure anti-bullying programs are effective and culturally relevant
DYNAMIC ANALYSIS AND CONTROL OF A QUADRUPED ROBOTIC SYSTEM BASED ON NEWTON-EULER FORMULATION
Get PDFDespite advancements in legged robotics, comprehensive dynamic analyses remain limited in the literature. This research presents kinematic and dynamic modeling of a quadruped robot using the Newton-Euler approach to improve computational efficiency in high degree of freedom systems. The formulation leverages system over-constraints with assumed ground reaction forces and focuses on simulating two primary gait patterns: static walking and dynamic trotting. The research explores reaction wheel-based roll stabilization for a quadruped with 8 actuators, omitting the conventional Hip Abduction/Adduction (HAA) joints. This approach addresses roll control limitations by compensating for the reduced actuation. This research presents a brief overview of representative gaits for legged rovers, followed by a review of kinematic, dynamic, and control strategies for quadruped systems. The initial focus is on kinematic analysis of static walking gait using a planar model, with trajectories and gaits developed and simulated in MATLAB. Inverse kinematics and trajectory planning were performed and simulated in MATLAB to model the walking gait. Results matched expected outcomes and were experimentally validated on an 8-actuator quadruped, with all actuators mounted on the torso and Knee Flexion/Extension (KFE) motion transmitted via two four-bar linkage mechanisms. The main research models a 12-actuator quadruped with three actuators per leg, conducting full kinematic and dynamic analyses for staticwalking and dynamic trotting gaits. A flexible algorithm is developed to simulate the complete system dynamicsacross various gait patterns. The dynamic model is solved using the Newton-Euler recursive approach, computinglink forces and moments. Twelve generalized coordinates are used for static walking, with an additionalcoordinate for dynamic trotting. The framework employs programming strategies to solve six linear equations todetermine the unknown reaction forces at the legs. This approach effectively reduces the number of unknowns,thereby simplifying the computational complexity of the model. The robot’s body attitude is estimated from jointtrajectories, with velocity and acceleration derived from joint space variables. Forward dynamics is computedusing inverse dynamics to solve for joint accelerations via the mass matrix Coriolis, centrifugal and gravitationaltorque vectors. A reaction wheel, aligned with the primary axis, is integrated to generate compensatory torquesfor roll stabilization during dynamic trotting gait. The integrated approach, combining forward and inversedynamics with real-time roll stabilization via a reaction wheel, demonstrated effective, adaptive locomotion forquadruped systems. Experimental validation during static walking showed strong agreement between measuredand simulated torque profiles, with Hip Flexion/Extension (HFE) and Knee Flexion/Extension (KFE) joint torquesclosely matching trajectory predictions, confirming the model’s accuracy. These studies advance rigid-bodydynamic modeling by reducing system complexity through an efficient minimization of generalized coordinates.The proposed framework, incorporating both inverse and forward dynamics with reduced coordinates andsimplified ground constraints, significantly streamlines the overall dynamic formulation. The developedframework successfully implements gait-switching algorithms based on the robot’s current attitude. Thisresearch addresses key gaps in dynamic modeling, including computational efficiency, utilization of system over-constraints, and gait transition dynamics
UTILIZATION OF IMIDAZOLIUM IONIC LIQUIDS FOR ENHANCED OIL RECOVERY IN HARSH EMIRATI TIGHT CARBONATE OIL RESERVOIRS
Get PDFIn response to the increasing global demand for energy and the limitations of traditional chemical oil recovery methods. This study explores the potential of imidazolium-based ionic liquids (ILs) as enhanced oil recovery (EOR) agents for Emirati tight oil reservoirs. Four ILs—C10mimCl, C12mimCl, C12mimBF4, and C16mimBr—were evaluated for their effects on interfacial tension (IFT), wettability, emulsification, and rheological properties under reservoir conditions. Experiments conducted at varying temperatures (up to 110°C), IL concentrations (100–3000 ppm), and salinities demonstrated that longer alkyl chain ILs, particularly C16mimBr, effectively reduced IFT by \u3e99% and improved wettability by lowering contact angles up to 15.37°. Statistical modeling and optimization using Design of Experiments (DoE) confirmed that IL type and concentration are key factors in maximizing EOR efficiency. Rheological analysis confirmed shear-thinning behavior and enhanced emulsion stability, especially with FB-C16mimBr achieving the lowest viscosities of 1.73 mPa·s and 0.71 mPa·s at 25°C and 80°C, respectively. Reservoir-scale assessments, including spontaneous imbibition, secondary, and tertiary flooding, indicated that ILs significantly improved oil recovery. Spontaneous imbibition with ILs increased recovery to 58.15% of OOIP compared to 16.72% of OOIP with formation brine alone. In comparison, tertiary flooding with C12mimCl and C16mimBr yielded additional recoveries of 21.39% and 26.15% of OOIP, resulting in a final recovery of 93.51% and 96.39% respectively. X-ray Diffraction (XRD) and pressure monitoring revealed that IL viscosity, core permeability, and calcite stabilization were critical in optimizing oil displacement. The formation of Winsor Type III microemulsions facilitated capillary force reduction and mobilized trapped oil. These findings demonstrate that ILs offer an environmentally benign alternative to conventional surfactants, improving oil recovery through wettability alteration, viscosity reduction, and emulsion stabilization, thereby contributing to sustainable high-efficiency energy solutions
نظام الرجوع عن القرارات والأحكام الباتّة في دولة الإمارات العربية المتحدة دراسة تحليلية
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This study examines the conditions for accepting the retraction of irrevocable decisions and judgments issued by the Courts of Cassation in the United Arab Emirates. As a rule, Courts of Cassation represent the final stage of adjudicating a case, and their judgments are considered final, meaning they cannot be annulled, as they are deemed the embodiment of truth, whether issued correctly or erroneously. However, since judges are human and prone to error, the Emirati legislator saw fit to ease the rigidity of the principle of the finality of judgments and to prioritize justice. Thus, a reversal system was introduced in the Federal Civil Procedure Law, allowing the Courts of Cassation and the litigants to reverse final decisions and judgments in specific, limited cases.
However, the reversal system did not receive its due course of research given that it was recently introduced pursuant to Decree-Law No. 15 of 2021 and then amended in 2022. As such, this research, following an analytical approach, aims to shed light on the conditions for its acceptance by studying the grounds for reversal, as well as the procedures for submitting such requests, including the timeframes for reversal, who has the right to initiate it, and the methods of submission.
The research reached several findings, the most important of which is that although the grounds for reversal are explicitly listed in Article (190), cases involving a judge’s lack of competency can also be included. Reversal may be initiated either by the court itself or by the party against whom the final decision or judgment was issued, with the necessary differences in submission procedures accordingly.
ملخص البحث
يعنى هذا البحث بدراسة شروط قبول الرجوع عن القرارات والأحكام الباتة التي تصدر عن محاكم النقض في دولة الإمارات العربية المتحدة. فالقاعدة أنّ محاكم النقض تعتبر آخر مرحلة لنظر الدعوى وأحكامها باتّة، بحيث لا يجوز إلغاؤها؛ إذ تعتبر عنواناً للحقيقة سواء صدرت صحيحة أم خطأ. ولكن لكون القضاة بشراً يخطؤون؛ ارتأى المشرّع الإماراتي أن يخفّف من صرامة مبدأ بيتوتة الأحكام، ويرجّح كفّة العدالة، فاستحدث نظام الرجوع في قانون الإجراءات المدنية الاتحادي، الذي يخوّل محاكم النقض والخصوم أن يرجعوا عن القرارات والأحكام الباتّة في حالات محدّدة.
وحيث إنّ نظام الرجوع المذكور لم يأخذ حقّه من البحث؛ لكونه صدر بموجب المرسوم بقانون رقم 15 لسنة 2021، ثمّ عدّل في 2022، فإنّ هذا البحث سيسلط الضوء على شروط قبوله من خلال دراسة حالات الرجوع، وكذلك إجراءات تقديم طلباته، كميعاد الرجوع، ومن له الحقّ بمباشرته، وطرق تقديمه، متّبعاً في ذلك المنهج التحليلي. وقد توصّل البحث إلى عدّة نتائج من أهمّها أنّ حالات الرجوع وإن وردت حصراً في المادة (190) إلا أنّه يمكن ضمّ حالات عدم صلاحية القاضي إليها، وأنّ الرجوع يكون إمّا من تلقاء المحكمة نفسها أو من الخصم الصادر ضده القرار أو الحكم الباتّ، مع ما يستتبع ذلك من ضرورة اختلاف إجراءات تقديمه
MEASUREMENT AND IMPROVEMENT OF PHOTON IDENTIFICATION EFFICIENCIES USING MACHINE LEARNING TECHNIQUES IN THE ATLAS DETECTOR AT THE LHC
Get PDFPhotons play a crucial role in numerous analyses at the Large Hadron Collider (LHC), particularly in studies like the Higgs boson decay to two photons. Precise photon identification is essential for enhancing the sensitivity and accuracy of such measurements. This thesis focuses on the development of a machine learning (ML)-based photon identification algorithm to improve the photon identification efficiency within the ATLAS detector, using a Deep Neural Network (DNN) approach. The primary goal is to boost photon identification efficiency by using advanced neural network techniques. Traditional photon identification relies on cuts applied to shower shape variables, which can limit the effectiveness of separating prompt photons from background signals. To overcome this, a new ML-based identification algorithm using a DNN is proposed, building on previous research that demonstrates improvements in photon identification through neural networks. This work investigates the optimization of photon identification efficiency by training a DNN with shower shape variables to differentiate between prompt and background photons. The performance of the ML-based algorithm is benchmarked against the traditional cut-based approach. The data comes from Monte Carlo Simulations
CONTINUOUS PROFESSIONAL DEVELOPMENT (CPD) FOR INCLUSIVE EDUCATION IN UAE SCHOOLS: CURRENT PRACTICES AND IN-SERVICE TEACHERS’ PREFERENCES
Get PDFProfessional development serves as a driving force in empowering teachers within inclusive education settings. The purpose of this study was to investigate the perspectives of both general and special education teachers about the effectiveness of currently implemented professional development practices. Data were collected using explanatory mixed-methods design, which included a questionnaire and semi-structured interviews. This method was utilized to improve the depth of research through the integration of quantitative and qualitative data. The combination of these two methods strengthens validity, reduces bias, and increases reliability. Non-probabilistic purposive sampling method was employed to collect the data as a total of 115 teachers from the UAE completed the questionnaire, which was designed to capture their experiences with existing professional development programs. Furthermore, 15 teachers from both general and special education backgrounds were chosen for semi-structured interviews. The findings revealed no statistically significant relationship across most demographic variables and professional development efficacy (p \u3e .05). The only exception was education level, which showed a small but statistically significant correlation (ρ = .21, p = .03). However, the findings demonstrated that educators had moderate satisfaction with the effectiveness of current professional development approaches, as indicated by statistically significant spearman’s correlations ranging from ρ = .66 to .75, p \u3c .001, as well as important hurdles that must be addressed. These barriers included a disconnect between theoretical knowledge and practical application, misalignment between training content and actual classroom challenges, and cultural differences, as reported in the interviews. These challenges affect student outcomes and teacher competencies in managing diverse classrooms, which will be reflected in students\u27 progress and social aspect. The recommendations emphasized the need for differentiated and personalized professional development that reflects classroom realities. Despite fostering improvements to professional development, research on its efficacy in the United Arab Emirates remains limited