<P> Repository for Undergraduate Thesis/Projects</P> http://dspace.aiub.edu:8080/jspui/handle/123456789/76 2026-03-31T20:45:43Z 2026-03-31T20:45:43Z Debnath, JC Wang, Jianli Saha, Tusar Hossain, Md Sarowar Ahmed, Shams Forruque http://dspace.aiub.edu:8080/jspui/handle/123456789/2898 2025-10-13T04:22:07Z 2025-08-20T00:00:00Z

Title: Effect of interstitial boron and hydrogenation on the magnetocaloric properties of La0.8Ce0.2Fe11.4Si1.6 compound Authors: Debnath, JC; Wang, Jianli; Saha, Tusar; Hossain, Md Sarowar; Ahmed, Shams Forruque Abstract: This study explores how boron doping influences hydrogen absorption and magnetocaloric properties in the La0.8Ce0.2Fe11.4Si1.6 (LCFS) compound. While hydrogenation can adjust the Curie temperature (TC) in magnetocaloric materials, its influence on hysteresis loss remains a challenge. To address this, we synthesized a series of hydride La0.8Ce0.2Fe11.4Si1.6BxHy compounds by exposure to the La0.8Ce0.2Fe11.4Si1.6Bx (LCFSB) alloys and analyzed their structure. X-ray diffraction confirmed phase composition, revealing that boron and hydrogen co-doping tunes TC between 174 and 329 K. The addition of boron and hydrogen significantly diminished the itinerant electron metamagnetic (IEM) transition and increased the slope of the critical field, HC, while reducing magnetic hysteresis. This preserves a high maximum entropy change, ΔSM with maximum values of 21.8, 12.6, and 12.1 kg−1 K−1 under 0–5 T for different compositions. The corresponding effective refrigerant capacity, RCPeff values are 121.3, 154 and 81.2 J kg−1 respectively. It was found that the inclusion of boron in the LCFS compound enhanced the absorption of hydrogen. Further, the evaluation of dehydrogenation dynamics revealed that the B doping significantly enhanced the stability of hydrogen and the stable temperature was increased to 250 °C for B doped samples. Finally, these findings demonstrate that boron doping optimizes hydrogen absorption, improves thermal stability, and enhances magnetocaloric performance by mitigating hysteresis losses.

2025-08-20T00:00:00Z Islam, Md. Ariful Karmaker, Debajyoti Bhowmik, Abhijit Billah, Md Masum Mobin, Md Iftekharul Mohd Noor, Noorhuzaimi http://dspace.aiub.edu:8080/jspui/handle/123456789/2863 2025-07-17T05:55:54Z 2025-04-08T00:00:00Z

Title: Unlocking Educational Excellence: Leveraging Federated Learning for Enhanced Instructor Evaluation and Student Success Authors: Islam, Md. Ariful; Karmaker, Debajyoti; Bhowmik, Abhijit; Billah, Md Masum; Mobin, Md Iftekharul; Mohd Noor, Noorhuzaimi Abstract: Federated Learning (FL) is an emerging machine learning approach with promising applications. In this paper, FL is comprehensively examined in relation to teacher performance evaluation. Through FL, teachers can be evaluated based on data-driven metrics while preserving data privacy. There are several benefits, including data privacy preservation, collaborative learning, scalability, and privacy-preserving insights. Additionally, it faces problems related to communication efficiency, system heterogeneity, and statistical heterogeneity. To address these issues, we propose a novel clustering-based technique in federated learning. The technique aims to overcome the challenges of system heterogeneity and improve communication efficiency. We provide a comprehensive review of existing research on clustering techniques in the context of federated learning, offering insights into the state of the art in this field. In addition, we emphasize the need for advanced compression methods, enhanced privacy-preserving mechanisms, and robust aggregation algorithms for future federated learning research. To address these challenges, we present a clustering-based approach to address the merits and challenges of federated learning The clustering-based approach we propose in this research demonstrates promising results in terms of reducing communication overhead and improving model convergence in federated learning. These findings suggest that incorporating clustering techniques can significantly enhance the efficiency and effectiveness of federated learning algorithms, paving the way for more scalable and privacy-preserving distributed machine learning systems. The findings of this study suggest that clustering techniques can improve the efficiency and scalability of federated learning.

2025-04-08T00:00:00Z Saha, Tusar http://dspace.aiub.edu:8080/jspui/handle/123456789/2803 2025-07-01T03:00:51Z 2025-06-16T00:00:00Z

Title: Band degeneracy in W-doped BaTiO3: An insight from theoretical approach with experiment Authors: Saha, Tusar Abstract: The structural, dielectric, and conduction mechanisms have been studied for BaTiO3 (BTO) and BaTi0.85W0.15O3 (BTWO) ceramics synthesized through the double sintering approach. X-ray diffraction (XRD) analysis confirms that both materials adopt a tetragonal perovskite structure (P4mm space group). Calculations based on Density Functional Theory (DFT) instruct perceptions into the electronic band structure and geometric optimization of the tetragonal segment, revealing an indirect bandgap with 3.28 eV and 2.21 eV for BTO and BTWO respectively, and demonstrating a remarkable transformation of a general n-type semiconductor to a p-type degenerate semiconductor. The Fermi level in BTWO shifts downward (1.64-1.15 eV) relative to BTO, as evidenced by fermi energy, the Moss-Burstein shift ( ), and charge carrier concentration calculations. Dielectric studies across 300–450 K display a clear ferroelectric-to-paraelectric phase transition in both materials. Notably, BTO reveals behavior between a typical ferroelectric and optimal relaxor, while BTWO is assessed as a canonical relaxor. Frequency-dependent resistivity measurements in addition elucidate the conduction mechanisms, contributing valuable insights into the dielectric and electronic properties of W-doped BaTiO3 ceramics. Notably, this degenerate behavior will provide immense implications for the improvement of advanced substances for practical applications in electronics, thermoelectric devices, memory systems, and energy storage.

2025-06-16T00:00:00Z Islam, Md Rafiqul Islam, Md. Shahidul Boni, Pritam Khan Sarker, Aldrin Saurov Anam, Md. Asif http://dspace.aiub.edu:8080/jspui/handle/123456789/2603 2025-02-26T09:42:29Z 2024-12-30T00:00:00Z

Title: Solving the maximum cut problem using Harris Hawk Optimization algorithm Authors: Islam, Md Rafiqul; Islam, Md. Shahidul; Boni, Pritam Khan; Sarker, Aldrin Saurov; Anam, Md. Asif Abstract: The objective of the max-cut problem is to cut any graph in such a way that the total weight of the edges that are cut off is maximum in both subsets of vertices that are divided due to the cut of the edges. Although it is an elementary graph partitioning problem, it is one of the most challenging combinatorial optimization-based problems, and tons of application areas make this problem highly admissible. Due to its admissibility, the problem is solved using the Harris Hawk Optimization algorithm (HHO). Though HHO effectively solved some engineering optimization problems, is sensitive to parameter settings and may converge slowly, potentially getting trapped in local optima. Thus, HHO and some additional operators are used to solve the max-cut problem. Crossover and refinement operators are used to modify the fitness of the hawk in such a way that they can provide precise results. A mutation mechanism along with an adjustment operator has improvised the outcome obtained from the updated hawk. To accept the potential result, the acceptance criterion has been used, and then the repair operator is applied in the proposed approach. The proposed system provided comparatively better outcomes on the G-set dataset than other state-of-the-art algorithms. It obtained 533 cuts more than the discrete cuckoo search algorithm in 9 instances, 1036 cuts more than PSO-EDA in 14 instances, and 1021 cuts more than TSHEA in 9 instances. But for four instances, the cuts are lower than PSO-EDA and TSHEA. Besides, the statistical significance has also been tested using the Wilcoxon signed rank test to provide proof of the superior performance of the proposed method. In terms of solution quality, MC-HHO can produce outcomes that are quite competitive when compared to other related state-of-theart algorithms.

2024-12-30T00:00:00Z