United Arab Emirates University
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ON FRACTIONAL DUNKL-TYPE LAPLACIAN
Get PDFThis thesis presents a comprehensive study of the fractional Dunkl-type Laplacian operator (−∥x∥ Δ)σ for 0\u3cσ\u3c1, through four equivalent key characterizations: the heat semigroup characterization, the pointwise characterization, the spherical mean characterization, and through an extension theorem. These characterizations offer different perspectives on the operator ∥x∥Δ, generalizing known results for the Euclidean Laplace operator by incorporating reflection symmetries, making it highly relevant in the harmonic analysis of root systems.By exploring these characterizations, the thesis highlights the deep connections between the fractional operator (−∥x∥Δ)σ and harmonic analysis, as well as its broader applicability in mathematical physics and partial differential equations
PERFORMANCE ANALYSIS OF UNDERGROUND-TO-ABOVEGROUND COMMUNICATION IN AGRICULTURAL IOT NETWORKS
Get PDFThis thesis investigates the potential of LoRa, a low-power, wide-area networking technology, for establishing reliable communication between underground sensors and aboveground infrastructure. We comprehensively analyze LoRa\u27s performance in both single-hop and multi-hop configurations, considering the impact of diverse environmental factors such as soil composition, moisture content, underground transmission distance, and path loss on signal propagation. We delve into the crucial role of the spreading factor (SF) within the LoRa communication system, analyzing its influence on network performance. Furthermore, we develop a comprehensive mathematical model for bit error rate (BER) under various channel conditions, including additive white Gaussian noise (AWGN) and Rayleigh fading, encompassing multi-hop networks with decode-and-forward relays. Through simulations employing realistic Rayleigh fading scenarios, we validate the accuracy of our theoretical models. Our key findings highlight the importance of optimizing network parameters, particularly the SF, to achieve superior bit error rate performance, ultimately enhancing the overall network reliability. We demonstrate that multi-hop LoRa networks offer a significant advantage over single-hop configurations, especially in challenging underground environments. This extended reach via multi-hop makes LoRa a compelling technology for large-scale, reliable communication networks in diverse agricultural applications
الرقابة القضائية على قرار إنهاء خدمة الموظف العام على ضوء القضاء الإماراتي
Get PDFJudicial Oversight of the Decision to Terminate A Public Employee\u27s Service Based on the UAE Judiciary
The examination dealt with judicial oversight of administrative decisions issued to terminate the staff member\u27s service as a safeguard established by the staff member against the abuse of his or her right. The supervision examined the legality of the administrative decision issued to terminate the staff member\u27s service formally and objectively, and the penalty for violation of the principle of lawfulness, namely, invalidity and judicial annulment. The research also dealt with the jurisprudence and the judiciary\u27s views on the limits of the judge and is in the process of adjudicating the annulment proceedings and the differences in them. Some argued that the judge could not direct orders to the administration. Others argued that the judge could direct the administration and that the judiciary\u27s position in the United Arab Emirates on that issue was different. The research also dealt with the legal implications of the judgements handed down in the termination action and enjoys absolute validity contrary to the general rule of relative validity of judicial decisions, The research also dealt with the mechanism for implementing the termination clause criminal liability of the executing officer , and the liability that may result from its failure to carry out the sentence against it, as well as civil liability, which may be incurred by the administration as a result of its failure to implement the annulment judgement, must be compensated. The main findings of the research include the lack of legislation in the United Arab Emirates governing the implementation of administrative judgements in general, the annulment of decisions to terminate an employee\u27s employment, and the disparity in the attitude of the UAE judiciary towards the judge\u27s power to direct orders to the administrator upon the annulment judgement.
One of the most important recommendations of the research was to present the divergence of opinions of the UAE\u27s Supreme Courts to the Unification of Federal and Local Judicial Principles, to enact legislation governing the implementation of administrative rulings in general, and to abolish in particular
PREDICTING THE CURRENT HABITAT DISTRIBUTION OF IMPORTANT HALOPHYTES AND THEIR POTENTIAL FUTURE SHIFTS UNDER CLIMATE CHANGE USING SPECIES DISTRIBUTION MODELING
No full textThis thesis is concerned with the current habitat distribution of important 15 halophyte species and the impact climate change on their distribution, probability of occurrence and presence for two future temporal points (2050, 2070). The main objective of this thesis is to define the current distribution of important halophytes and to assess the impacts of climate change on their distribution using future climate projections CMIP5 RCP 8.5. This study utilizes multidimensional available data to address the current and to predict the future distribution of Halophyte plant species. To perform this study, the object-oriented and reproducible R package known as SDM, and RStudio platform were used for the species distribution modeling. The Species Distribution Modeling techniques showed a high discriminatory ability with area under the ROC (receiver operating characteristic) curve (AUC) between 0.94 to 0.99 for the 15 species. At a global scale, results showed a clear distributional shift and expansion of halophytes towards the poles of the earth under climate change. Moreover, most of the important halophytes, like Aerva javanica (Burm. f.) Juss., Prosopis cineraria (L.) Druce, Rhizophora mucronata Lam, and Phragmites australis (Cav.) Trin. are expected to survive and massively expand within the harsh climatic conditions under climate change. In addition, the results showed different distributional behaviors of halophytes under climate change, but plants either showed an increase in presence like Amaranthus graecizans L, almost stable presence like Acacia tortilis (Forssk.) Hayne, or a decline in presence like Anastatica hierochuntica L within the Gulf and UAE scales in the future. Most of the selected halophytes should have an obvious presence within the hyper-arid regions currently and predictably in future under climate change. This study represents a guide and a holistic overview of 15 important halophyte species current and future distribution under climate change. It gives an enhanced understanding of climate change’s impacts on halophytes distribution and presence behaviors for environmental conservation sustainable planning and decision making
KINETICS, THERMODYNAMICS, AND BIOLOGICAL CHARACTERIZATIONS OF HYDROLYSATES ENZYMATICALLY PRODUCED FROM PROTEINS EXTRACTED FROM MICROALGAE
No full textThis thesis aims to explore the use of Zeolitic Imidazolate Framework-L (ZIF-L) as a support for immobilizing alcalase and its potency in producing protein hydrolysates. ZIF-L was synthesized at room temperature using an aqueous solution, and alcalase was immobilized through adsorption batch experiment. The successful immobilization of alcalase on ZIF-L was confirmed through Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and thermogravimetric analysis (TGA). The maximum adsorption capacity of alcalase on ZIF-L was determined to be 672.1 ± 5.5 mg g-1 at 40°C using an initial protein concentration of 5 mg mL-1. Adsorption equilibrium data suggested that alcalase physically adsorbed on ZIF-L, with the Freundlich model isotherm providing the best fit. The adsorption kinetics were well described by pseudo-first order model, indicating that both film and intraparticle diffusion were significant. The activity of the prepared immobilized alcalase on ZIF-L was tested using bovine serum albumin as a substrate. Impressively, the immobilized alcalase retained over 90% of the initial activity after being stored at 4°C for up to 70 days. A diffusion-reaction model was developed and numerically solved to describe the reaction dynamics, revealing the significance of mass transfer limitations during the early stages of hydrolysis. Furthermore, the immobilized alcalase was used to hydrolyze protein extracted from microalgae, and the bioactivity of the resulting peptides was assessed through total phenolic content and radical scavenging activity assays. The findings underscore the potential of alcalase-based biocatalysts immobilized on ZIF-L for applications in food industry, offering a sustainable and cost-effective approach to producing bioactive peptides with health-promoting properties. This research opens avenues for further exploration of MOF-based enzyme immobilization in various biotechnological applications
SATELLITE-BASED SPATIAL AND TEMPORAL CHARACTERIZATION OF RAINFALL OVER THE UAE
No full textStudies on rainfall characteristics have been of particular interest in the arid and semi-arid regions, including the United Arab Emirates (UAE), due to its impact on the built and natural environment. Rainfall represents a vital water source and a potential threat to the built environment, particularly during flash rainfall. This thesis evaluates spatial and temporal variation of rainfall in the UAE. The UAE is classified into four ecosystems with a distinct distribution of precipitation (East Coast, Mountains, the Gravel Plains, and Desert Foreland). Satellite data on daily rainfall for the years starting from 2001 up to 2020 was obtained from the Global Precipitation Measurement (GPM) mission. Several rainfall characterization metrics and their trends are evaluated; these include rainfall patterns, the probability of occurrence, the severity of precipitation, rainfall Intensity-Duration-Frequency relationships (IDFs), Standard Precipitation Index (SPI), and Probable Maximum Precipitation (PMPs). The data is analyzed using statistical techniques to outline anomalies that may indicate climate change in the UAE. The outcome of this thesis will serve as baseline data for several activities, including irrigation scheduling, rehabilitation projects, and hydrological studies such as the mitigation of possible flood hazards and the design of dams. Moreover, satellite data will be beneficial in the case of insufficient ground data, mainly where rain gauges are generally scarce. Regions characterized by low population densities and remote locations and have a diminishing need to deploy a network of rain gauges and automated weather stations will benefit the most from this study. The findings indicate distinct patterns in rainfall distribution among the UAE\u27s ecosystems. The desert region encounters fewer rainfall events, whereas the east coast has the highest rainfall frequency. Additionally, the thesis reveals similar rainfall patterns in the mountain and gravel plains regions. Notably, high-intensity rainfall events are more prevalent on the east coast compared to the mountain and gravel plains. Further examination of Probable Maximum Precipitation (PMP) unveils the east coast as having the highest PMP, compared with the gravel plains region\u27s minimum PMP. This thesis makes significant contributions to studying rainfall patterns in the UAE. Firstly, the open-source availability of our developed source code promotes collaboration and transparency, enabling fellow researchers to replicate and extend our analyses. Secondly, our meticulous two-decade spatial and temporal analysis enhances understanding of local climate dynamics, providing a comprehensive dataset for researchers and policymakers. Finally, the presentation of Intensity-Duration-Frequency (IDF) curves and spatial maps offers clear visual insights into rainfall characteristics, aiding decision-makers in water resource management and infrastructure planning. Together, these contributions advance our understanding of UAE\u27s rainfall and serve as a valuable resource for future research in similar climatic contexts
ON FRACTIONAL DUNKL-TYPE LAPLACIAN
Get PDFThis thesis provides a comprehensive study of the fractional Dunkl-type Laplacian operator (—llxllΔk) σ for 0 \u3c σ \u3c 1, focusing on four key equivalent characterizations: the heat semigroup approach, the pointwise formulation, the spherical mean representation, and through an extension theorem. A significant part of the thesis is devoted to the extension theorem, where, following the approach of Caffarelli and Silvestre for the Euclidean Laplacian, we prove that (—llxllΔk) σ can be characterized as an operator that maps a Dirichlet boundary condition to a Neumann-type condition via an extension PDE problem. Further, a Poisson formula for the extension was established. These four characterizations provide distinct perspectives on the operator llxllΔk, extending Euclidean Laplacian results to include reflection symmetries and revealing connections between the fractional operator (—llxllΔk) σ, harmonic analysis, and applications in mathematical physics and PDEs
FACTORS INFLUENCING UAE HIGH SCHOOL CHEMISTRY STUDENTS\u27 LEARNING OF ORGANIC QUALITATIVE ANALYSIS: A QUALITATIVE STUDY
Get PDFChemistry is one of the five science subfields typically covered in secondary schools in the United Arab Emirates. Chemistry is a branch of science that studies substances\u27 characteristics, components, and structures. Numerous subfields fall under the umbrella of chemistry, including inorganic, organic, analytical, and physical chemistry. One of the topics covered in chemistry classes is the analysis of chemical compounds, which is divided into two types: quantitative analysis and qualitative analysis. While qualitative analysis determines the kind of each element or group present in a given solution sample, quantitative analysis determines the quantity of each element or group present. Students\u27 low achievement and poor chemistry performance are significant issues plaguing education in the UAE. For example, in PISA 2018, the average performance in science of 15-year-old UAE students was 434 points, compared to an average of 489 points in OECD countries. Furthermore, the average performance in science of 8-Grade UAE students is 473 points, which is below the scale center- point of 500 points. In this context, this study aims to identify the factors influencing 12th grade UAE school students\u27 learning of an essential Chemistry concepts (OQA). A qualitative research approach was used to gain an in-depth understanding of the factors responsible for the difficulties UAE students in grade 12 encounter while studying OQA topics in Chemistry. Three qualitative data collection instruments were used; students\u27 observations, participants\u27 interviews, and document analysis of students\u27 study journals, notebooks, and worksheets. Thematic analysis was then utilized to examine the students\u27 conceptual understanding of the topic using the qualitative data gathered. The results highlighted challenges within teaching OQA in chemistry including resource constraints impacting practical instruction, curriculum content misalignments, instructional method deficiencies, and teacher motivation issues. Recommendations include overcoming these challenges through incorporation of practical based approaches, enhancing resource availability, aligning the chemistry curriculum with instructional practices and improving PD (professional development), with offering support to both instructors and 12th grade students to drive a more effective learning environments in chemistry education
QUANTUM MARKOV CHAINS RELATED TO CERTAIN LATTICE MODELS
Get PDFA central open problem in quantum probability is the establishment of a general theory of Markov fields. This thesis contributes to the general theory by introducing quantum probability and applies it via the construction of quantum Markov chains on different hierarchical lattices (Cayley trees). This thesis examines two types of trees one of which corresponds to the Ising-XY-Model on a Cayley tree of order two which then the existence of Markov chains can be utilized to detect phase transitions. The other discussed model is a (1,3) tree in which the XY-model is considered to determine the existence of a quantum Markov chain. The methods of which the construction of such chains is discussed along with its conditions. This thesis identifies the solutions associated with the conditions and if such solutions exist, assigns a quantum Markov chain to the model. The solutions of these conditions is non-trivial. The aim is to construct quantum Markov chains and detect phase transitions because phase transitions exhibit great importance and interest in many areas of physics such as condensed matter physics
UNVEILING THE ORIGINS OF SOURCE CODE THROUGH AUTHORSHIP ATTRIBUTION: A COMPARATIVE STUDY OF AI AND HUMAN CODING PATTERNS
Get PDFIn recent years, Artificial Intelligence (AI) techniques have been used for source code authorship attribution, which is the process of identifying the original author of a given piece of code. With the advancement of AI technologies like ChatGPT, which can generate code, there is a need to accurately identify whether a piece of code is written by a human or generated by a machine. This is crucial for intellectual property protection, cybersecurity, and software forensics. The main objective of this thesis is to review existing research on source code authorship attribution and conduct several experiments to determine the best AI models for identifying the authorship of source code. This includes distinguishing between human-written and ChatGPT-4-generated codes and providing insights into the gender and region. A dataset of 600 source codes was utilized, focusing on extracting lexical and layout features. The study applied several information retrieval and ranking techniques such as TF-IDF, MI, and IG to extract features and understand author characteristics. It also employed various machine learning models, such as SVM, logistic regression, MLP, XGBoost, and random forest. It also employed deep learning models like LSTM, RNN, and CNN to analyze the data. The research achieved up to 94.7% accuracy with the random forest model using TF-IDF in machine learning, and a 95% accuracy rate with the CNN model in deep learning. These results demonstrate the effectiveness of these models in authorship attribution of source code. This work contributes to the field by identifying effective AI models for source code authorship attribution. It provides a comprehensive analysis of how machine learning and deep learning can be used to attribute authorship, differentiating between human and AI-generated code, and identifying gender and region. By achieving high accuracy in identifying the authorship of source codes, this thesis fills a gap in the current understanding and methodologies in source code authorship attribution. It offers new insights and methods in distinguishing between human- and AI-generated code to address the ethical concerns