Pusat Pengajian Sains Matematik - Tesis

Browse

Now showing 1 - 5 of 482

Optimization Seaweed Drying Efficiency Using Hybrid Solar Dryers And Sparse Robust Regression Models
(2025-04)
Afouna, Nour Hamad Suleiman Abu
Data analytics in statistics is vital for extracting insights, identifying patterns, and guiding decisions. In precision farming, particularly post-harvest management, challenges arise from iot sensor dependency, system complexity, and variable interactions, leading to issues like variability, multicollinearity, and sensitivity to outliers. Addressing these challenges requires improved data inclusivity, robust data management, and cross-sector collaboration to unlock the full potential of analytics. Variability in agricultural systems impacts crop yield and post-harvest processes. Heterogeneity in sensors, data collection methods, and transmission protocols complicates agricultural drying. Multicollinearity, where independent variables are highly correlated, creates difficulties in post-harvest monitoring as overlapping environmental data from multiple sensors obscures the impact of individual variables. Fluctuations due to environmental changes, sensor errors, and human interventions further complicate modeling, requiring robust statistical methods capable of handling noise and outliers.
Analysis Of Nonlinear Dynamics Of Epidemiological Models With Local Dispersal, Reinfection And Limited Medical Resources
(2025-09)
Salman, Al Zaidi Amer Mohammed
Examining the dynamics of disease spread and its control measures remains a main challenge in epidemiology. Numerous studies have proposed various factors influencing disease transmission, including environmental conditions, population movement, and healthcare resources. While distinct models have been formulated to examine these factors, less attention has been given to understanding how the interplay of reinfection, medical resource limitations, and spatial dispersal processes determines epidemic outcomes. This thesis investigates the long-term dynamics of COVID-19 in Malaysia using a group of deterministic Susceptible-Infectious-Removed (SIR) kinetic models that incorporate temporary immunity, spatial heterogeneity, local dispersal, and control measures.
Magmas And The Twelve Local Moufang Identities
(2025-05)
Lee, Han Zhou
Quasigroup is a binary system in which the specification of any two of x,y and z in the equation x · y = z determines the third element uniquely. A loop is a quasigroup with a (two-sided) identity element. A magma is a generalization of loops that does not satisfy the quasigroup condition. The (four) moufang identities are identities which are equivalent to each other in the variety of loops, for which a direct and comprehensive proof is provided. Each moufang identity involves three variables. By transforming a variable into a constant in each identity, the four moufang identities can be localized into twelve local identities. However, these local moufang identities are not generally equivalent to each other in the variety of magmas. Hence, this thesis aims to introduce not-too-restrictive conditions to magmas such that relationships can be found between these local identities. The automated reasoning tool prover9 and the finite model builder mace4 are used to obtain some of the important results in this thesis.
Development Of Non-Standard Finite Difference Methods For Systems Of Fractional Differential Equations With Application To Mathematical Biology Problems
(2025-08)
Masoud, Al Kathiri Said Salim
Non-standard finite difference schemes (NSFDSs) have been proven highly effective in solving non-fractional differential equations. However, the applications of these schemes to physical phenomena, e.g., biological disease models, remain largely unexplored. Therefore, in this thesis, a mechanism has been developed to implement these schemes beyond the existing limitations of solving smaller fractional models.
Enhanced Optimal Homotopy Asymptotic Multiple Parameters Method For Solving Fuzzy Fractional Differential Equations
(2025-09)
Alshbeel, Abdallah Eshbeel Abdallah
This thesis addresses these challenges by applying and extending the Optimal Homotopy Asymptotic Method (OHAM) to solve both linear and nonlinear FFDEs. The main contribution is the development of a generalized OHAM framework that incorporates advanced forms of fractional derivatives, specifically the Caputo-Katugampola (CK) derivative with two parameters and theAtangana–Baleanu–Caputo (ABC) derivative with Mittag–Leffler (ML) kernels involving three parameters.

Browse

Recent Submissions