Browsing by Author "Rahim, Abdur"

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Intake and absorption of nutrients in children with cholera and rotavirus infection during acute diarrhea and after recovery
(1982) Molla, Ayesha; Molla, Abdul Majid; Rahim, Abdur; Sarker, Shafiqul Alam; Mozaffar, Zahid; Rahman, Mujibur
Possibility of Renewable and Sustainable Energy in Bangladesh
(Daffodil International University, 22-08-13) Rahim, Abdur; Ahmed, Mostak
The thesis titled "Possibility of renewable and sustainable Energy in Bangladesh" was completed under the supervision of Professor Dr. Md. Shahid Ullah (Professor), Co supervision Jahidul Islam (Lecturer) of Department of Electrical & Electronic Engineering, Daffodil International University in Dhaka, Bangladesh, approved it as partial fulfillment of the Bachelor of Science in Electrical & Electronic Engineering requirement. To the best of our knowledge and belief, the capstone contains no material previously published or authored by another individual, save when fair mention is given in the capstone itself.
Surface Engineered Mesoporous Silica Carriers for the Controlled Delivery of Anticancer Drug 5-Fluorouracil: Computational Approach for the Drug-Carrier Interactions Using Density Functional Theory
(Frontier Scientific Publishing, 2023-04-13) Rehman, Fozia; Khan, Asif Jamal; Sama, Zaib Us; Alobaid, Hussah M.; Gilani, Mazhar Amjad; Safi, Sher Zaman; Muhammad, Nawshad; Rahim, Abdur; Ali, Abid; Guo, Jiahua; Arshad, Muhammad; Emran, Talha Bin
"Introduction: Drug delivery systems are the topmost priority to increase drug safety and efficacy. In this study, hybrid porous silicates SBA-15 and its derivatives SBA@N and SBA@3N were synthesized and loaded with an anticancer drug, 5-fluorouracil. The drug release was studied in a simulated physiological environment. Method: These materials were characterized for their textural and physio-chemical properties by scanning electron microscopy (SEM), nuclear magnetic resonance (NMR), Fourier transform infrared spectroscopy (FTIR), small-angle X-ray diffraction (SAX), and nitrogen adsorption/desorption techniques. The surface electrostatics of the materials was measured by zeta potential. Results: The drug loading efficiency of the prepared hybrid materials was about 10%. In vitro drug release profiles were obtained in simulated fluids. Slow drug release kinetics was observed for SBA@3N, which released 7.5% of the entrapped drug in simulated intestinal fluid (SIF, pH 7.2) and 33% in simulated body fluid (SBF, pH 7.2) for 72 h. The material SBA@N presented an initial burst release of 13% in simulated intestinal fluid and 32.6% in simulated gastric fluid (SGF, pH 1.2), while about 70% of the drug was released within the next 72 h. Density functional theory (DFT) calculations have also supported the slow drug release from the SBA@3N material. The release mechanism of the drug from the prepared carriers was studied by first-order, second-order, Korsmeyer–Peppas, Hixson–Crowell, and Higuchi kinetic models. The drug release from these carriers follows Fickian diffusion and zero-order kinetics in SGF and SBF, whereas first-order, non-Fickian diffusion, and case-II transport were observed in SIF. Discussion: Based on these findings, the proposed synthesized hybrid materials may be suggested as a potential drug delivery system for anti-cancer drugs such as 5-fluorouracil."
Voice impersonation detection using LSTM based RNN and explainable AI
(BRAC University, 2021-10) Barua, Kawshik; Rahim, Abdur; Parizat, Prantozit Saha; Noor, Md.Asad Uzzaman; Jannah, Miftahul; Alam, Md.Golam Rabiul
The advancing eld of arti cial synthetic media introduced deepfakes which made it easier to synthesize a person's voice, identical to their original voice mechanically to use it for negative means. People's voices are exposed to public as it is a pro - cient and more convenient media of exchanging information over various mediums, entertainment, speech delivering, news reading and so on, making it easier to collect voice samples for creating fake yet almost identical voice samples to trick people. So it has become vital to prevent this crime which led us to do this research paper for saving the victims of voice impersonation attacks where we used LSTM based RNN model in order to distinguished between real and synthesize voice.Furthermore, to compare the results we got from the mentioned process, we build a SVM classi er and nally we've explained the predicted outputs(fake or real) of both LSTM and SVM model by using an Explainable AI method named LIME. Our research resulted in 98.33% accuracy rate through our proposed model and very low percentage of error in detecting fake/synthesized voices.