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Journal of Geoscience and Environment Protection 2017年第6期5卷 147-171页

作者： md. Yousuf Gazi S. M. Mainul Kabir md. badrul imam Aminur Rahman md. Ashraful Islam Department of Geology University of Dhaka Dhaka Bangladesh Institute of Mining Mineralogy and Metallurgy Joypurhat Bangladesh

Geochemical analysis of Neogene mudrocks from Sitakund anticline, Chittagong Tripura Fold Belt (CTFB), Bengal Basin, Bangladesh, was deployed to delineate the provenance, tectonics and depositional environments. Representative samples went through mineralogical and geochemical analysis concerning major, trace and rare earth element analysis. Rigaku ZSX Primus and NITON XL3t 800 XRF instruments were utilized for the determination of major and trace elements. The experiment results reveal that the Neogene mudrocks are rich in silica having concentration of 58.10% to 62.60% with an average of 59.90%. Therefore, the geochemical response from the experiments apparently proved the existence of the active continental margin setting for the Neogene mudrocks. Different concentrations and ratios of major oxides satisfy that the mudrocks were derived from felsic source rocks. In addition, chemical index of alteration (CIA) values for the Neogene mudrocks vary from 67.81 to 77.57 with an average 74.41 indicating significant weathering at the source areas. Moreover, U/Th, Cu/Zn, Ni/Co and V/Cr ratios designate that the mudrocks were deposited in oxidizing depositional environment.

关键词： Geochemistry Neogene mudrocks Tectonic setting Provenance Weathering Depositional Environment Sitakund Anticline and Bengal Basin

Comparison of the Effect of Vermicompost and Inorganic Fertilizers on Vegetative Growth and Fruit Production of Tomato (Solanum lycopersicumL.)

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Open Journal of Soil Science 2015年第2期5卷 53-58页

作者： md. Abul Kashem Ashoka Sarker imam Hossain md. Shoffikul Islam Department of Soil Science University of Chittagong Chittagong Bangladesh

This study attempted to compare the effect of cow manure vermicompost and inorganic fertilizers on the vegetative growth and fruits of tomato plant (Solanum lycopersicum L.). An air dried sandy loam soil was mixed with five rates of vermicompost equivalent to 0 (control), 5, 10, 15 and 20 t ha-1 and three rates of NPK fertilizer equivalent to 50% (N-P-K = 69-16-35 kg ha-1), 100% (N-P-K = 137-32-70 kg ha-1) and 200% (N-P-K = 274-64-140 kg ha-1). The treatments were replicated three times. The data revealed that shoot length, number of leaves, dry matter weight of shoots and roots, fruit number and fruit weight were influenced significantly (P < 0.05) by the application of vermicompost and NPK fertilizer in the growth media. The highest dose of vermicompost of 20 t ha-1 increased dry weight of shoot of 52 folds and root of 115 folds, number of fruit(s)/plant of 6 folds and mean fruit weight of 29 folds while the highest rate of NPK fertilizer of 200% increased dry weight of shoot of 35 folds and root of 80 folds, number of fruit(s)/plant of 4 folds and mean fruit weight of 18 folds over the control treatment. The growth performance of tomato was better in the vermicompost amended soil pots than the plants grown in the inorganic fertilizer amended soil pots. This study suggested that the vermicompost served as a potential source of nutrients for plant growth.

关键词： Vermicompost NPK Fertilizer Tomato Growth Yield

Heart Disease Detection by Using Machine Learning Algorithms and a Real-Time Cardiovascular Health Monitoring System

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World Journal of Engineering and Technology 2018年第4期6卷 854-873页

作者： Shadman Nashif md. Rakib Raihan md. Rasedul Islam Mohammad Hasan imam Department of Computer Science & Engineering Rajshahi University of Engineering & Technology (RUET) Rajshahi Bangladesh Department of Electrical & Electronic Engineering American International University-Bangladesh (AIUB) Dhaka Bangla-desh

Cardiovascular diseases are the most common cause of death worldwide over the last few decades in the developed as well as underdeveloped and developing countries. Early detection of cardiac diseases and continuous supervision of clinicians can reduce the mortality rate. However, accurate detection of heart diseases in all cases and consultation of a patient for 24 hours by a doctor is not available since it requires more sapience, time and expertise. In this?study, a tentative design of a cloud-based heart disease prediction system had been proposed to detect impending heart disease using Machine learning techniques. For the accurate detection of the heart disease, an efficient machine learning technique should be used which had been derived from a distinctive analysis among several machine learning algorithms in a Java Based Open Access Data Mining Platform, WEKA. The proposed algorithm was validated using two widely used open-access database, where 10-fold cross-validation is applied in order to analyze the performance of heart disease detection. An accuracy level of 97.53% accuracy was found from the SVM algorithm along with sensitivity and specificity of 97.50% and 94.94%respectively. Moreover, to monitor the heart disease patient round-the-clock by his/her caretaker/doctor, a real-time patient monitoring system was developed and presented using Arduino, capable of sensing some real-time parameters such as body temperature, blood pressure, humidity, heartbeat. The developed system can transmit the recorded data to a central server which are updated every 10 seconds. As a result, the doctors can visualize the patient’s real-time sensor data by using the application and start live video streaming if instant medication is required. Another important feature of the proposed system was that as soon as any real-time parameter of the patient exceeds the threshold, the prescribed doctor is notified at once through GSM technology.

关键词： Data Mining Machine Learning IoT (Internet of Things) Patient Monitoring System Heart Disease Detection and Prediction

Simulation and Modelling of Water Injection for Reservoir Pressure Maintenance

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Computers, Materials & Continua 2022年第9期72卷 5761-5776页

作者： Rishi Dewan Adarsh Kumar Mohammad Khalid imam Rahmani Surbhi Bhatia md.Ezaz Ahmed Department of Physics University of Petroleum&Energy StudiesDehradun 248007UttarakhandIndia Department of Computer Science University of Petroleum&Energy StudiesDehradun 248007UttarakhandIndia College of Computing and Informatics Saudi Electronic UniversityRiyadh 11673Saudi Arabia Department of Information Systems College of Computer Science and Information TechnologyKing Faisal UniversityAl Hasa 36362Saudi Arabia

Water injection has shown to be one of the most successful,efficient,and cost-effective reservoir management *** re-injecting treated and filtered water into reservoirs,this approach can help maintain reservoir pressure,increase hydrocarbon output,and reduce the environmental *** goal of this project is to create a water injection model utilizing Eclipse reservoir simulation software to better understand water injection methods for reservoir pressure maintenance.A basic reservoir model is utilized in this *** simulation designs,the reservoir length,breadth,and thickness may be changed to different *** water-oil contact was discovered at 7000 feet,and the reservoir pressure was recorded at 3000 pounds per square inch at a depth of 6900 *** aquifer chosen was of the Fetkovich type and was linked to the reservoir in the j+*** porosity was estimated to be varied,ranging from 9%to 16%.The residual oil saturation was set to 25%and the irreducible water saturation was set at 20%.The vertical permeability was set at 50 md.as a *** Volume Temperature(PVT)data was used to estimate the gas and water characteristics.

关键词： Eclipse water injection reservoir modeling simulation oil saturation

Automatic Real-Time Medical Mask Detection Using Deep Learning to Fight COVID-19

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Computer Systems Science & Engineering 2022年第9期42卷 1181-1198页

作者： Mohammad Khalid imam Rahmani Fahmina Taranum Reshma Nikhat md.Rashid Farooqi Mohammed Arshad Khan College of Computing and Informatics Saudi Electronic UniversityRiyadhSaudi Arabia Computer Science and Engineering Department Muffakham Jah College of Engineering and TechnologyOsmania UniversityHyderabadTelanganaIndia Department of Commerce and Business Management Maulana Azad National Urdu UniversityHyderabadTelanganaIndia Department of Accountancy College of Administrative and Financial SciencesSaudi Electronic UniversityRiyadSaudi Arabia

The COVID-19 pandemic is a virus that has disastrous effects onhuman lives globally;still spreading like wildfire causing huge losses to humanityand economies. There is a need to follow few constraints like social distancingnorms, personal hygiene, and masking up to effectively control the virus *** proposal is to detect the face frame and confirm the faces are properly covered with masks. By applying the concepts of Deep learning, the results obtainedfor mask detection are found to be effective. The system is trained using4500 images to accurately judge and justify its accuracy. The aim is to developan algorithm to automatically detect a mask, but the approach does not facilitatethe percentage of improper usage. Accuracy levels are as low as 50% if the maskis improperly covered and an alert is raised for improper placement. It can be usedat traffic places and social gatherings for the prevention of virus transmission. Itworks by first locating the region of interest by creating a frame boundary, thenfacial points are picked up to detect and concentrate on specific features. Thetraining on the input images is performed using different epochs until the artificialface mask detection dataset is created. The system is implemented using TensorFlow with OpenCV and Python using a Jupyter Notebook simulation environment. The training dataset used is collected from a set of diverse open-sourcedatasets with filtered images available at Kaggle Medical Mask Dataset by Mikolaj Witkowski, Kera, and Prajna Bhandary. To simulate MobilNetV2 classifier isused to load and pre-process the image dataset for building a fully connectedhead. The objective is to assess the accuracy of the identification, measuringthe efficiency and effectiveness of algorithms for precision, recall, and F1 score.

关键词： COVID-19 pandemic convolution neural network deep learning face detection facemask detection global health machine learning

Nipah Virus Unveiled: A Review Article

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Advances in Bioscience and Biotechnology 2024年第3期15卷 161-173页

作者： Munama Magdum md. Abir Tazim Chowdhury Mahmuda Khandaker Razdip Datta md. Naheed Rayhan md. Siffat Uddin md. Junayed imam Bhuiyan md. Ahaduzzaman md. Abdullah Al-Mahammud Kabir Mohammad Zishan Uddin md. Estiak Ullah Sahid Subrata Saha Department of Community Medicine Shaheed Monsur Ali Medical College Dhaka Bangladesh Department of Cardiothoracic and Vascular Surgery Evercare Hospital Dhaka Bangladesh Department of Microbiology Shaheed Monsur Ali Medical College Dhaka Bangladesh Department of Anesthesia Dhaka Dental College & Hospital Dhaka Bangladesh Department of Cardiothoracic Anesthesia Evercare Hospital Dhaka Bangladesh Department of Medicine Times Multicare Hospital Ltd. Dhaka Bangladesh Barking Havering and Redbridge University Hospitals NHS Trust Romford UK

Nipah virus (NiV) is a highly infectious zoonotic pathogen that poses a significant threat to human and animal health. First identified in Malaysia in 1998, NiV has since caused several outbreaks in Southeast Asia, with sporadic cases reported in Bangladesh and India. The virus is primarily transmitted to humans through direct contact with infected animals, primarily fruit bats, or through the consumption of contaminated fruits and their juices. NiV infection presents a wide spectrum of clinical features, ranging from mild respiratory illness to severe encephalitis, with a high case fatality rate. The incubation period typically ranges from 4 to 14 days, during which patients develop fever, headache, myalgia, and respiratory symptoms such as cough and sore throat. As the disease progresses, neurological signs become prominent, including altered consciousness, seizures, and focal deficits. Severe cases may exhibit acute respiratory distress syndrome and multi organ failure. Laboratory findings often include lymphocytopenia, thrombocytopenia, and elevated liver enzymes. Diagnosis of NiV infection requires specialized laboratory testing, including reverse transcription-polymerase chain reaction (RT-PCR) and serological assays. Currently, no specific antiviral treatment exists for NiV infection, and management primarily focuses on supportive care. Prevention and control strategies encompass public health interventions, surveillance, and raising awareness among healthcare providers and the general population. The emergence and re-emergence of NiV highlight the urgent need for continued research, improved diagnostic capabilities, and the development of effective vaccines and therapeutics to mitigate the impact of this deadly virus.

关键词： Nipah Virus Zoonotic Pathogen Outbreaks Surveillance

Physiological Mechanism of Thermotolerance in Wheat (Triticum aestivumLin.) Seedlings

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American Journal of Plant Sciences 2018年第13期9卷 2719-2727页

作者： Soyema Khatun Jalal Uddin Ahmed md. Mahi imam Mollah Kim Taewan Crop Physiology Division Bangladesh Institute of Nuclear Agriculture Mymensing Bangladesh Department of Crop Botany Bangabandhu Sheikh Mujibur Rahman Agricultural University Gazipur Bangladesh Department of Entomology Patuakhali Science and Technology University Patuakhali Bangladesh Department of Food Science and Biotechnology Andong National University Andong South Korea

A research work was performed under sub-tropical condition (24°8'N, 90°0'E) at Bangabandhu Sheikh Mujibur Rahman Agricultural University with three wheat genotypes (BARI Gom 25, BARI Gom 26 and Pavon 76) to observe the mobilization of seed reserve and seedling growth under normal (15°C/25°C) and elevated (25°C/35°C) temperature in growth chamber. The effect of high temperature on wheat seedling was observed in terms of mobilized seed reserve, respiration and transpiration efficiency and seedling growth. At 35°C temperature, maximum mobilization of seed reserve was observed in BARI Gom varieties (BARI Gom 25 and 26) but the respiration efficiency was higher in Pavon 76 in comparison to other genotypes. Maximum loss of respiration and transpiration at 35°C temperature was found to produce low seedling growth in Pavon 76. It appeared from the result that at high temperature the maximum mobilized seed reserve and subsequently minimum loss of respiration and transpiration collectively contributed a positive role for better seedling growth in BARI Gom 25 and BARI Gom 26. Therefore the better mobilized seed reserve and subsequently minimum loss of respiration and transpiration during seedling development are indicators of the thermo tolerance in growing wheat seedling.

关键词： Thermo Tolerance Mobilized Seed Reserve Heat Stress Wheat

Machine Learning-Enabled Power Scheduling in IoT-Based Smart Cities

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Computers, Materials & Continua 2021年第5期67卷 2449-2462页

作者： Nabeela Awan Salman Khan Mohammad Khalid imam Rahmani Muhammad Tahir Nur Alam md.Ryan Alturki Ihsan Ullah Department of Computer Science Government Girls Degree College MardanKPK23200Pakistan Department of Electrical Energy System UETPeshawar25000Pakistan Department of Computer Science College of Computing and InformaticsSaudi Electronic UniversityKSA Department of Smart Computing Kyungdong UniversityGlobal CampusGosung24764South Korea Department of Information Sciences College of Computer and Information SystemsUmm Al-Qura UniversityMakkahSaudi Arabia Robotics Engineering Daegu Gyeongbuk Institute of Science and TechnologySouth Korea

Recent advancements in hardware and communication technologies have enabled worldwide interconnection using the internet of things(IoT).The IoT is the backbone of smart city applications such as smart grids and green energy *** smart cities,the IoT devices are used for linking power,price,energy,and demand information for smart homes and home energy management(HEM)in the smart *** complex smart gridconnected systems,power scheduling and secure dispatch of information are the main research *** challenges can be resolved through various machine learning techniques and data *** this paper,we have proposed a particle swarm optimization based machine learning algorithm known as a collaborative execute-before-after dependency-based requirement,for the smart *** proposed collaborative execute-before-after dependencybased requirement algorithm works in two phases,analysis and assessment of the requirements of end-users and power distribution *** the rst phases,a xed load is adjusted over a period of 24 h,and in the second phase,a randomly produced population load for 90 days is evaluated using particle swarm *** simulation results demonstrate that the proposed algorithm performed better in terms of percentage cost reduction,peak to average ratio,and power variance mean ratio than particle swarm optimization and inclined block rate.

关键词： PSO IBR machine learning IoT smart cities CDBR

Surgical Management for a Broken Delivery Shaft in Vivoduring PCI Following Acute Myocardial Infarction in a Complex LAD Artery Lesion: A Case Report and Literature Review

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World Journal of Cardiovascular Surgery 2021年第11期11卷 104-113页

作者： md. Abir Tazim Chowdhury md. Zulfiqur Haider Sohail Ahmed S. M. A. Zulker Nine md. Kamrul Hasan Arup Khan md. Junayed imam Bhuiyan Mohammad Zishan Uddin Niaz Ahmed Department of Cardiothoracic and Vascular Surgery Evercare Hospital Dhaka Bangladesh Department of Cardiothoracic Anesthesia Evercare Hospital Dhaka Bangladesh

Stuck up and fracture of coronary angioplasty hardware are unwonted complications of percutaneous coronary interventions (PCI) for which surgical retrieval and management is once in a while required. We present one case of a 59-year-old diabetic, a hypertensive gentleman who attended the emergency room (ER) with central chest pain for 2 hours. After evaluation of the patient by physical and noninvasive diagnostic tests, he was diagnosed as a case of acute myocardial infarction (AMI) with stable hemodynamic. For the aforementioned findings, the patient was treated first with a thrombolytic agent in ER and then shifted to Cardiology Department for monitoring and further coronary evaluation by coronary angiography (CAG). CAG revealed essentially single vessel disease (SVD) with complex left anterior descending (LAD) artery lesion, so PCI was attempted but failed with an unfortunate incidence of the broken delivery shaft and left in vivo. Immediate decision making and surgical management for retrieval of lost angioplasty device and correction coronary lesion with revascularization save the patient from grave complication. All the series of events and management approaches of this very complex coronary artery lesion are discussed in this article.

关键词： Percutaneous Coronary Intervention (PCI) Acute Myocardial Infarction (AMI) Angioplasty Hardware Broken Delivery Shaft Complex Coronary Lesion Surgical Revascularization

Improvement of Dissolution Rate of Gliclazide Using Solid Dispersions with Aerosil 380 and Its Effect on Alloxan Induced Diabetic Rats

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Pharmacology & Pharmacy 2019年第8期10卷 365-385页

作者： Subrata Paul md. Nur Islam md. Ashraf Ali Ranjan Kumar Barman Mir imam Ibne Wahed Bytul M. Rahman Department of Pharmacy Faculty of Science Rajshahi University Rajshahi Bangladesh Department of Pharmacy Faculty of Life Science Mawlana Bhashani Science and Technology University Tangail Bangladesh

The main objective of this research is to conduct a comprehensive study for enhancing the aqueous solubility of poorly water soluble gliclazide using hydrophilic fumed silica particles (Aerosil®380) and evaluating the influence of silica on drug release profile and pharmacological activity on alloxan induced diabetic rats. Solid dispersions (SD’s) of gliclazide were prepared using solvent evaporation method. The dissolution profiles and solid state characterization of the SD’s prepared were all evaluated. The dissolution rate of gliclazide in the SD’s with fumed silica (weight ratio, 1:1) was approximately 38%, which is about 10 fold higher than that of the pure drug after 30 min. After forming the SD’s, gliclazide changed into an amorphous state, which can infer from differential scanning calorimetry (DSC) and powder X-ray diffraction (PXRD). Fourier transform infrared spectroscopy (FTIR) also revealed the formation of weak hydrogen bonding through the interactions between the secondary amine groups of gliclazide and silanol groups of silica particles in the SD’s. The rapid dissolution rate from the SD’s might be attributed to the amorphization of drug, improved specific surface area and wettability than the original drug crystals. Further, we investigated the antidiabetic effects of SD’s of gliclazide in alloxan induced diabetic rats. The SD’s of gliclazide decrease the blood glucose level 64% whereas the conventional gliclazide decreases only 37% in diabetic rats. Lipid profiles, kidney and liver functions are remarkably improved in diabetic rat treated with SD’s of gliclazide than that of conventional gliclazide. These results suggest that SD’s of gliclazide have much more bioavailability and hence are more pharmacologically active than that of conventional gliclazide form.

关键词： In-Vitro Dissolution Fumed Silica Solid Dispersions Gliclazide Alloxan Diabetes