Browsing by Author "Rahman, M.M."

Filter results by typing the first few letters
Now showing 1 - 20 of 99
  • No Thumbnail Available
    Item
    A Brief Phytochemical Investigation and Pharmacological Uses of Citrus Seed – A Review
    (Scopus, 2020) Rahman, M.M.; Jahan, F.I.; Mim, S.A.
    Citrus fruits are more important in all over the world. They are well known as nutritional and medicinal property. Lemon is one of the most common citrus fruit. Lemons are typically grown from seeds, which are planted and developed as trees. Trees of citrus fruit can stand from 10 feet to 20 feet tall, and can produce fruit for more than 30 years. Citrus seeds contain certain compounds with various level of bitterness. These compounds have been tested against insects and proved to be effective. Oil is extracted from citrus seeds to use in skin lotions and shower gels. The hexane-extracted oil content of citrus seeds ranged from 27.0 to 36.5%. The protein, fiber and ash contents were found to be 3.9-9.6%, 5.0-8.5%, and 4.6-5.6%, respectively. The extracted oils exhibited an iodine value of 99.9-110.0; refractive index (40 C), 1.4639-1.4670; density (24 C), 0.920-0.941 mg/mL; saponification value, 180.9-198.9; unsaponifiable matter, 0.3-0.5%; acid value (mg KOH/g of oil), 0.5-2.2 and color (1-in. cell) 1.4-3.0R + 15.0-30.0Y. Consuming citrus seeds can kill parasites like threadworms. Plump, bright and flavorful, lemons serve as the stars in many beverages and meals. But the tiny seeds are eventually responsible for all of those flavorful tarts, cold summer drinks and seafood toppers. The main characteristic of citrus seed is thorny branches, white flowers with purple edges. Medicinal property of lemon seed contains antioxidant activity, antifertility activity, hepato protective activity and others. Extracts from citrus seed were investigated for the radical scavenging activity and apoptotic effects in human breast adenocarcinoma (MCF-7) cells and non-malignant breast (MCF-12F) cells for the first time. This review presents update information gathered on scientifically screened plant parts used for different activity.
  • No Thumbnail Available
    Item
    A Hidden Markov Model-based Approach for Weather Prediction in Bangladesh
    (Institute of Electrical and Electronics Engineers Inc., 2023-12-15) Chowdhury, M.R.Z.; Rahman, M.M.; Tanny, N.T.; Bushra, T.A.
    In the context of Bangladesh, a country prone to diverse and often unpredictable weather patterns, reliable weather forecasts are critical for making informed decisions and mitigating the impact of extreme weather events. In this research, we present an innovative approach to predict the average temperature and rainfall of Bangladesh using Hidden Markov Models (HMM). Our HMM-based approach leverages the past weather data as the observation in order to predict future weather patterns. For this study, we used the Bangladesh Weather dataset from Kaggle which contains monthly average temperature and rainfall data from 1901 to 2015. Experimental results show that the proposed HMM model was able to successfully capture the trends of the weather pattern with an MAE of 0.74 and 77.01 for the temperature and rainfall prediction respectively. © 2023 IEEE.
  • No Thumbnail Available
    Item
    Absorption of macronutrients and nitrogen balance in children with dysentery fed an amylase-treated energy-dense porridge
    (1997-12) Rahman, M.M.; Mahalanabis, D.; Ali, M.; Mazumder, R.N.; Wahed, M.A.; Fuchs, G.J.
  • No Thumbnail Available
    Item
    Adeqate vitamin A status early in infancy interferences with the polio vaccine[abstract]
    (1997) Alvarez, J.O.; Rahman, M.M.; Unicomb, L.; Habte, D.
  • No Thumbnail Available
    Item
    An animal model of haemolytic--uraemic syndrome in shigellosis: lipopolysaccharides of Shigella dysenteriae I and S. flexneri produce leucocyte-mediated renal cortical necrosis in rabbits
    (1985-02) Butler, Thomas; Rahman, Hamidur; Al-Mahmud, K.A.; Islam, Moyenul; Bardhan, Pradip; Kabir, Iqbal; Rahman, M.M.
  • No Thumbnail Available
    Item
    Anti-inflammatory and analgesic activities of ethanolic extract of glochidion thomsonii (bark)
    (PharmacologyOnLine, 2018-12-30) Rahman, M.H.; Oliullah, A.B. Md.; Rahman, M.M.; Alam, M.J.
    The present communication attempts to evaluate the Anti-inflammatory and Analgesic activities of ethanolic extract of Glochidion Thomsonii (Bark) belongs to the family: Euphorbiaceae, which is widely distributed in Bangladesh and India. Methods: Ethanolic extract of Glochidion Thomsonii at doses of 250mg/kg and 500mg/kg were tested for their anti-inflammatory activity against Carrageenan induced paw edema & Xylene-Induced Ear Edema test in rats and analgesic activity was tested against Formalin-induced Paw licking test & acetic acid induced writhing (in mice) models and the two phases of formalin induced paw licking models of pain. Results: The results indicate that the ethanolic extracts at the doses of 250 and 500mg/kg body weight significantly inhibited, the carrageenan induced paw edema and Xylene-induced ear edema models of inflammation, similarly the extract at the doses of 250 and 500mg/kg significantly inhibited the acetic acid induced writhing (in mice) models and the two phases of formalin induced paw licking models of pain.
  • Thumbnail Image
    Item
  • Thumbnail Image
    Item
    Apparel supply chain optimization by developing e-commerce: An impact analysis
    (IEOM Society, 2019-10-25) Ahmad, S.,; Kamruzzaman, M.,; Hossain, M.S.; Rahman, M.M.
    Supply-chain optimization is the application of processes and tools to ensure the optimal operation of a manufacturing organization. The SCM is the spine of E-commerce, a very critical component of E-commerce. Supply chain efficiency means having the right product at the right place at the right time, can save money or reduce costs, and can enhance cash utilization. E-commerce plays a vital role on inventory management to keep the record electronically to avoid any information breach. In this paper, we have developed a database management system which would be centrally visualized by the partners of the apparel supply chain. Buyer can be able to place orders through this developed database system electronically which might save at least ordering cost, visit cost and 15 %-time savings of the total lead time. Furthermore, we have developed a system by which customer can buy surplus goods which remain after shipment has done with the cheapest cost and factory will not face any wastage of goods.
  • Thumbnail Image
    Item
    Automated Detection of Harmful Insects in Agriculture: A Smart Framework Leveraging IoT, Machine Learning, and Blockchain
    (Institute of Electrical and Electronics Engineers Inc., 2024-05-08) Rahman, W.; Hossain, M.M.,; Iqbal, M.S.; Rahman, M.M.; Fida Hasan, K.; Moni, M.A.
    Paddy cultivation is a significant global economic sector, with rice production playing a crucial role in influencing worldwide economies. However, insects in paddy farms predominantly impact the growth rate and ecological equilibrium of the agricultural field. Hence, the precise and timely identification of insects in agricultural settings presents a potential strategy for addressing this issue. This study aims to implement an automated system for paddy farming by employing a real-time framework that incorporates the Internet of Things (IoT), blockchain technology, and Deep Learning (DL) algorithms. The primary emphasis of the DL-based system is on the timely identification of pests. In contrast, integrating the IoT and blockchain technologies facilitates stablishing a fully automated system with security within the agricultural domain. The DL-based system includes a secondary dataset of paddy insects, and then preprocessing, feature extraction, and identification have been performed. Besides, an IoT-based system is embodied with a camera module and microprocessor, accompanied by some apparatus required to automate the whole system. In addition, the research also includes the blockchain to secure each individual data transmission among the several IoT components and the cloud server. While examining the proposed solution, various experimental data have been systematically documented and analyzed. The proposed framework attained a peak accuracy of 98.91% using the VGG19 model and ensemble classifiers to detect the pest with a specificity of 99.14% and a precision of 98.21%. The study additionally quantifies the mean duration of the cloud response when integrated with IoT, yielding an average time of 1.71 s after pest identification. Nevertheless, the system has exhibited a high level of efficacy in the context of real-time monitoring and automation of paddy farms.
  • Thumbnail Image
    Item
    BDWaste: A comprehensive image dataset of digestible and indigestible waste in Bangladesh
    (Elsevier Inc., 2024-02-07) Rahman, W. ,; Akter, M.; Sultana, N.; Farjana, M.; Uddin, A.; Mazrur, M.B.; Rahman, M.M.
    The “BDWaste” dataset contains two significant categories of waste, namely digestible and indigestible, in Bangladesh. Each category represents 10 distinct species of waste. The digestible categories are sugarcane husk, fish ash, potato peel, paper, mango peel, rice, shell of malta, lemon peel, banana peel, and egg shell. On the other hand, the indigestible species are polythene, cans, plastic, glass, wire, gloves, empty medicine packets, chip packets, bottles, and masks. The research uploaded the primarily collected dataset on Mendeley, and the dataset contains a total of 2497 raw images, of which 1234 were digestible and 1263 belonged to indigestible species. Each species is stored in a fixed file based on its name and categories. Also, each species contains an indoor (with a visible surface) and an outdoor (with a surface that can be seen generally) image. The dataset is free from any blurry, dark, noisy, or invisible images. The research also performed waste classification with pre-trained convolutional neural network models such as MobileNetV2 and InceptionV3. The research found the highest accuracy of 96.70% in the indigestible waste classification and 99.70% in the digestible waste classification. The researchers presume that this data can be used in the future in different types of research, such as sustainable development, sustainable environments, agricultural development, recycling processes, and other computer vision-based applications.
  • Thumbnail Image
    Item
    BDWaste: A comprehensive image dataset of digestible and indigestible waste in Bangladesh
    (Elsevier Inc., 2024-04-24) Rahman, W.; Akter, M.; Sultana, N.; Farjana, M.; Uddin, A.; Mazrur, M.B.,; Rahman, M.M.
    The “BDWaste” dataset contains two significant categories of waste, namely digestible and indigestible, in Bangladesh. Each category represents 10 distinct species of waste. The digestible categories are sugarcane husk, fish ash, potato peel, paper, mango peel, rice, shell of malta, lemon peel, banana peel, and egg shell. On the other hand, the indigestible species are polythene, cans, plastic, glass, wire, gloves, empty medicine packets, chip packets, bottles, and masks. The research uploaded the primarily collected dataset on Mendeley, and the dataset contains a total of 2497 raw images, of which 1234 were digestible and 1263 belonged to indigestible species. Each species is stored in a fixed file based on its name and categories. Also, each species contains an indoor (with a visible surface) and an outdoor (with a surface that can be seen generally) image. The dataset is free from any blurry, dark, noisy, or invisible images. The research also performed waste classification with pre-trained convolutional neural network models such as MobileNetV2 and InceptionV3. The research found the highest accuracy of 96.70% in the indigestible waste classification and 99.70% in the digestible waste classification. The researchers presume that this data can be used in the future in different types of research, such as sustainable development, sustainable environments, agricultural development, recycling processes, and other computer vision-based applications
  • Thumbnail Image
    Item
    Behavioral aspects in determining nutritional status of children
    (1982-08-21) Rizvi, Najma; Rahman, M.M.
  • Thumbnail Image
    Item
    Beliefs, attitudes and practices towards measles in rural Bangladesh
    (1981-07-29) Shahid, Nigar; Faruque, A.S.G.; Aziz, K.M.A.; Rahman, A.S.M. Mizanur; Rahman, M.M.
  • Thumbnail Image
    Item
    Bifurcation analysis, modulation instability and optical soliton solutions and their wave propagation insights to the variable coefficient nonlinear Schrödinger equation with Kerr law nonlinearity
    (Springer Science and Business Media B.V., 2024-07-02) Roshid, M.M.; Rahman, M.M.
    The present paper aims to explore bifurcation analysis, modulation instability, and optical soliton solutions in nonlinear media with third-order dispersion terms. A variable coefficient third-order nonlinear Schrödinger’s equation (PNLSE) with truncated M-fractional derivative is considered. We also discuss a few assets that the derivative satisfies. Initially, a novel evaluation method known as bifurcation analysis is employed to look at the complex model's dynamic behavior. Figure 1 provides an analytical and graphical study of the observed mechanism of static soliton through a saddle-node bifurcation in the nonlinear Schrödinger problem using a matching technique. Secondly, By implementing novel two analytic techniques such as unified solver and generalized unified techniques to offer insights into wave propagation and optical soliton conduct in nonlinear optics, optical communications, quantum mechanics, plasma physics, and engineering. The underlying idea of these two approaches is to transform the equation with partial derivatives into a version of the equation with ordinary derivatives, which are first required to incorporate a new wave definition. These techniques permit us to generate innovative soliton solutions that can be formulated in terms of rational, hyperbolic, and trigonometrical functions. The collected outcomes have the potential to facilitate an understanding and elucidation of the physical characteristics of waves moving within a dispersive substance. We additionally estimated conservative values related to solitons, such as energy, momentum, and power. By selecting appropriate parameter values, the graphical shapes in 3D, density, and 2D are generated using relevant parameter values to visually present the obtained results, including periodic wave soliton, interaction of kink and bell shape soliton, periodic breather wave soliton, double periodic soliton through unified solver method and interaction of kink and periodic lump wave soliton and also with the periodic soliton, double periodic wave soliton, periodic wave soliton with lump soliton, multi periodic wave with kink shape soliton, periodic wave soliton, periodic breather wave soliton, periodic wave soliton, multi periodic wave soliton, periodic lump wave soliton, breather wave soliton multi periodic wave through generalized unified technique, providing an insightful visualization of the discovered solutions. In a two-dimensional graph, we show the effect of truncated M-fractional parameters for [g=0.1,0.5,0.9]. Additionally, the modulation instability spectrum can be expressed utilizing a linear analysis technique, and the modulation instability bands are shown to be influenced by the third-order and group velocity dispersion. The findings indicate that the modulation instability disappears for negative values of the fourth order in a typical dispersion regime. Consequently, it was shown that the techniques mentioned previously could be an effective tool to generate unique, precise soliton solutions for numerous uses, which are crucial to nonlinear optics, optical communications, and engineering
  • Thumbnail Image
    Item
    Bioailability of iron from Bangladesh meals
    (1985-07-24) Alam, A.N.; Wahed, M.A.; Rashid, M.A.; Rahman, M.M.; Cook, J.D.
  • Thumbnail Image
    Item
    Biochemical basis of a hypoglycemic syndrome with high mortality
    (1984-10) Akbar, M.S.; Alam, A.N.; Zulfiquar, Dr.; Samsuzzoha, Dr.; Khan, Waker; Rahman, M.M.; Huq, Sayeedul; Islam, Moinul; Ahmed, Tofayel; Rubbi, S.F.; Greenough III, W.B.
  • No Thumbnail Available
    Item
  • Thumbnail Image
    Item
    Cardiovascular Disease Prediction Utilizing Machine Learning and Feature Selection with Clonal Selection Algorithm
    (Institute of Electrical and Electronics Engineers Inc., 2023-09-12) Rahman, W.,, ,; Aneek, R.H.; Moinuddin, M.; Sakib, M.S.,; Iqbal, M.S.; Rahman, M.M.
    A substantial and rising number of patients suffer from cardiovascular diseases, including heart attacks, heart failure, and other related illnesses. This case surge places increasing pressure on healthcare professionals and administrators while patients grapple with growing medical costs. To address these challenges, an automated system is necessary within the healthcare sector. In this paper, we present a cardiovascular health monitoring system that incorporates Machine Learning techniques. The study employed feature selection techniques on a secondary dataset. The study has used a nature-inspired technique, namely the Clonal Selection Algorithm (CSA) and Maximum Relevance Minimum Redundancy (mRMR) technique, to identify the most prominent feature in the detection of cardio-vascular illness. This approach was combined with a collection of Machine Learning classifiers. A group of experimental data has been listed to assess the suggested model's effectiveness. The research findings indicated a maximum accuracy rate of 100% when employing the proposed algorithms and orientations. The study also discusses the performance analysis for CSA and mRMR using a set of performance evaluation matrices. Based on the obtained results, it can be inferred that the suggested model will likely exhibit a high level of effectiveness in identifying cardiovascular diseases.
  • No Thumbnail Available
    Item
  • No Thumbnail Available
    Item
    Characterisation of humoral antibody in shiga dysentry(abstract)
    (1978-01) Ahmed, Ansaruddin; Gilman, R.; Aziz, K.M.S.; Rahman, M.M.