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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) IAES International Journal of Artificial Intelligence (IJ-AI) Journal of Information Systems and Informatics Narra J
Md. Rabiul Islam
Rajshahi University of Engineering & Technology
Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Health Professions Immunology & microbiology Medicine & Pharmacology Public Health

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Performance analysis of 2D optical code division multiple access through underwater wireless optical medium Islam, Md. Rabiul; Islam, Md. Jahedul; Mitra, Bithi; Hossain, Md. Amzad; Islam, Jahedul; Dev, Shuvo
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i2.pp1665-1673

Abstract

The performance of a two-dimensional optical code division multiple access (2D-OCDMA) system using an underwater wireless optical (UWO) medium is assessed in this work. The optical source is an LED with a working wavelength of 532 nm, and the optical detector is a p–i–n photodiode. When calculating the bit error rate (BER), the phase-induced intensity noise (PIIN), thermal noises, and shot sounds are taken into account. The user code address is set using 2D perfect difference (2D-PD) codes. Link distance, inclination angle, beam divergence angle, transmitter power, and the number of concurrent users are all taken into account when determining the BER performance. For various water media, such as pure sea water (PSW), clear ocean water (CLOW), and coastal ocean water (CSOW), the performance of the suggested system is examined.
Titer disparity of anti-Spike receptor binding domain SARS-CoV-2 antibody between vaccinated and naturally infected individuals Surawan, Dewa P.; Sumohadi, Duwi; Budhitresna, Anak AG.; Lestari, Putri P.; Dewi, Kartika; Wikananda, Wasudewa; Suwari, Retenra P.; Islam, Md. Rabiul; Te, Haypheng; Rabaan, Ali A.; Masyeni, Sri
Narra J Vol. 2 No. 1 (2022): April 2022
Publisher : Narra Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52225/narra.v2i1.71

Abstract

In conjunction with other health promotion strategies, vaccination of coronavirus disease 2019 (COVID-19) is a strategy to alleviate the burden of infection. The aim of this study was to determine the differences in antibody response strength between individuals who received COVID-19 vaccination and those who had a natural infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A cross-sectional study was conducted among post-natural confirmed COVID-19 infection and immunized people in Bali, Indonesia. The vaccination was using Sinovac-CoronaVac with two-weeks interval between the two vaccine doses. To measure the level of anti-Spike receptor binding domain (SRBD) of SARS-CoV-2 antibody, we used Roche electro-chemiluminescence immunoassay (ECLIA) platform. Blood samples were obtained before and 28 days after first immunization in the vaccinated group, as well as two weeks after hospital discharge in the confirmed COVID-19 patients based on real-time reverse transcription polymerase chain reaction (RT-PCR). A total of 58 confirmed COVID-19 patients and 60 vaccinated individuals were included. On the 28th day after the initial vaccination, the seroconversion rate among vaccinated individuals was 91.67%. The mean titer of anti-SRBD SARS-CoV-2 antibody among vaccinated participants was 63.62±82.57 IU/mL (ranged between 0 IU/mL and 250 IU/mL). The mean titer among naturally infected group was 188.47±94.57 IU/mL (ranged between 4.25 IU/mL to 250 IU/mL) regardless the severity of COVID-19. Our data suggested that the titer of anti-SRBD SARS-CoV-2 antibody was significantly higher in naturally infected individuals compared to those who received COVID-19 vaccination (p<0.001). These data suggest that not all individuals vaccinated with Sinovac COVID-19 had protective level of anti-SRBD SARS-CoV-2 antibody and booster dose of heterologous vaccine maybe required.
Pharmaceutical quality evaluation of marketed vildagliptin tablets in Bangladesh based on the United States Pharmacopeia specifications Islam, Md. Rabiul; Daria, Sohel; Ankhi, Arjina A.; Sultana, Sharmin; Rahman, Md. Ashrafur
Narra J Vol. 2 No. 2 (2022): August 2022
Publisher : Narra Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52225/narra.v2i2.84

Abstract

Continuous monitoring of pharmaceutical products is vital because it matters to human health. Here we aimed to assess the quality parameters of commercially available vildagliptin tablets in Bangladesh. We tested the tablets for the content uniformity, hardness, friability, disintegration, dissolution, and potency. Then, we fitted the dissolution data with kinetic models to investigate the release pattern of the studied brands. Moreover, we applied a mathematical model-independent approach to compare the dissolution profiles of the brands. The interchangeability was determined using difference and similarity factors. Weight variation, friability, and hardness were between 150.35±1.26 to 230.8±1.98 mg, 0 to 0.88%, and 47.3±5.09 to 108.1±1.92 N, respectively. All tablets disintegrated within 0.54±2.85 to 7.69±2.14 min in distilled water. The potency of tablets in 0.1 N HCl and PBS (pH 6.8) were between 97.67±2.58 to 105±0.95% and 99±4.63 to 105±1.65%, respectively. The drug release (%) in 0.1 N HCl and phosphate-buffered saline (PBS) (pH 6.8) after 60 min were between 99.37±1.80 to 111.09±0.64% and 96.59±3.52 to 109.57±0.53%, respectively. All the brands complied with the United States Pharmacopeia (USP) specification for physicochemical properties. Also, we observed the drug release patterns of vildagliptin tablets matched with different kinetic models. We found only one substitutable brand with the standard product regardless of the dissolution medium. In-vitro chemical equivalence is not always consistent with bioequivalence. Therefore, continuous evaluation of marketed products is essential to ensure the desired quality.
Impedance network-based ultra sparse matrix converter with enhanced voltage gain Hassan, Zahid; Khan, M. A.; Islam, Md. Rabiul
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i4.pp2262-2274

Abstract

The matrix converter is devised to achieve sinusoidal input current and output voltage, and high power density. The typical matrix converter gives voltage gain less than unity using a significantly large number of switches. To reduce the number of switches an ultra sparse matrix converter (USMC) is introduced whose voltage gain is still less than unity. Researchers also introduced many modified versions of these matrix converters including quasi-Z-source, series Zsource, switched inductor, and switched capacitor USMCs. Although all of these matrix converters have their relative advantages and disadvantages in terms of the number of switches and passive elements, the voltage gain is still marginal. This paper focused on achieving higher voltage gain using minimal switches and passive elements. We proposed a doubler boost impedance network based ultra sparse matrix converter (DB-USMC). The doubler boost impedance network consists of a boost stage and doubler stage where the boost stage enhances the voltage and the doubler stage makes it double. The voltage gain of the proposed DB-USMC converter is 4.00 at a 50% duty cycle. The obtained results of the proposed DB-USMC converter show a path to get superior voltage gain using minimal switches and passive elements in a cost-effective manner.
From Traditional Marketplace to Online Shop: Shifting Shopping Patterns among University Students in Bangladesh Balaly, Md. Habibullah; Islam, Md. Rabiul; Makhdum, Niaz; Shah, A.M.M. Mubassher; Banna, Hasanul
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i2.1137

Abstract

The explosive rise of e-commerce has largely changed shopping habits around the world, and university students are one of the biggest groups to have changed their ways of shopping. In Bangladesh, the change from conventional to digital shopping has been visible with the help of mobile technology, the impact of social media, and also due to the ease of online shopping. The study identifies the drivers of online shopping acceptance among university students in Bangladesh through the lens of theoretical framework based on TAM, UTAUT and TPB. Quantitative method was employed, and the data were collected using simple random sampling from 384 students, determined based on 95% confidence level and 5% margin of error, from three different universities in Bangladesh. The results suggest that the convenience, quickness, and the assortment of the product are the key motivations that drive students to online shopping. Besides, social media networks, mainly Facebook and Instagram, play an incredibly significant role in deciding to buy the students. However, issues like the delay in delivery, high delivery charges, and the question of products' authenticity have proven to be the barriers to the online shopping experience. The research advocates that a reduction in delivery fees, better logistics operations, and providing student discounts will lead to an increase in adoption of e-commerce in Bangladesh. Besides, it is essential to instill customer trust in e-commerce platforms by using secure payment systems and trustworthy products and delivery services.
Ensemble model-based arrhythmia classification with local interpretable model-agnostic explanations Islam, Md. Rabiul; Kumar Godder, Tapan; Ul-Ambia, Ahsan; Al-Islam, Ferdib; Nag, Anindya; Ahamed, Bulbul; Tanzim, Nujhut; Ahmed, Md. Estiak
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i3.pp2012-2025

Abstract

Arrhythmia can lead to heart failure, stroke, and sudden cardiac arrest. Prompt diagnosis of arrhythmia is crucial for appropriate treatment. This analysis utilized four databases. We utilized seven machine learning (ML) algorithms in our work. These algorithms include logistic regression (LR), decision tree (DT), extreme gradient boosting (XGB), K-nearest neighbors (KNN), naïve Bayes (NB), multilayer perceptron (MLP), AdaBoost, and a bagging ensemble of these approaches. In addition, we conducted an analysis on a stacking ensemble consisting of XGB and bagging XGB. This study examines various arrhythmia detection techniques using both a single base dataset and a composite dataset. The objective is to identify the optimal model for the combined dataset. This study aims to evaluate the efficacy of these models in accurately categorizing normal (N) and abnormal (A) heartbeats as binary classes. The empirical findings demonstrated that the stacking ensemble approach exhibited superior accuracy when used with the combined dataset. Arrhythmia classification models rely on this as a crucial component. The binary classification achieved an accuracy of 98.61%, a recall of 97.66%, and a precision of 97.77%. Subsequently, the local interpretable model-agnostic explanations (LIME) technique is employed to assess the prediction capability of the model.
Co-Authors Ahamed, Bulbul Ahmed, Md. Estiak Al-Islam, Ferdib Ankhi, Arjina A. Balaly, Md. Habibullah Banna, Hasanul Budhitresna, Anak AG. Daria, Sohel Dev, Shuvo Hossain, Md. Amzad Islam, Jahedul Islam, Md. Jahedul Kartika Dewi Khan, M. A. Kumar Godder, Tapan Lestari, Putri P. Makhdum, Niaz Masyeni, Sri Mitra, Bithi Nag, Anindya Rabaan, Ali A. Rahman, Md. Ashrafur Shah, A.M.M. Mubassher Sultana, Sharmin Sumohadi, Duwi Surawan, Dewa P. Suwari, Retenra P. Tanzim, Nujhut Te, Haypheng Ul-Ambia, Ahsan Wikananda, Wasudewa Zahid Hassan