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Journal of Forestry Research 2011年第4期22卷 577-582页

作者： Mahmood Hossain Mohammad Raqibul hasan Siddique md. Saidur Rahman md. Zaber Hossain md. mahedi hasan Forestry and Wood Technology Discipline Khulna University Khulna - 9208 Bangladesh Soil Science Discipline Khulna University Khulna-9208 Forestry and Wood Technology Discipline Khulna University Khulna- 9208

Azadirachta indica A. Juss, Dalbergia, sissoo Roxb., and Melia azedarach L. are little studied species in nutrient return capabilities from leaf litter decomposition to maintenance of the soil fertility despite their importance in agroforestry practices of Bangladesh. A leaf litter decomposition experiment was conducted using a litterbag teeh7 nique to assess the nutrient reaun efficiency of these species. The de- composition rate of leaf litter was highest for M. azedarach and lowest for D. sissoo. Rainfall and temperature of study sites showed a significant （p〈0.05） positive relationship with the rate of leaf litter decomposition. The highest decay constant was observed for M. azedarach （6.67）. Nitrogen and Phosphorus concentration in leaf litter showed a decreased trend sharply at the end of the first month, whereas rapid decrease of Potassium concentration was reported within 10 days. Conversely, higher concentration of nutrient was observed at the later stages of decomposition. All three species showed a similar pattern of nutrient release （K 〉 N 〉 P） during the decomposition process of leaf litter. Among the studied species, D. sissoo was best in terms of N and P return and A. indica was best in terms of K return.

关键词： agroforestry decay constant decomposition leaf litter andnutrient dynamics

Heat and Mass Transfer on Non-Newtonian Peristaltic Flow in a Channel in Presence of Magnetic Field: Analytical and Numerical Analysis

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Applied Mathematics 2024年第8期15卷 568-583页

作者： md. Maruf hasan md. Enamul Karim md. Abdus Samad Department of Mathematics Comilla University Comilla Bangladesh Department of Applied Mathematics University of Dhaka Dhaka Bangladesh

A study has been arranged to investigate the flow of non-Newtonian fluid in a vertical asymmetrical channel using peristalsis. The porous medium allows the electrically conductive fluid to flow in the channel, while a uniform magnetic field is applied perpendicular to the flow direction. The analysis takes into account the combined influence of heat and mass transfer, including the effects of Soret and Dufour. The flow’s non-Newtonian behavior is characterized using a Casson rheological model. The fluid flow equations are examined within a wave frame of reference that has a wave velocity. The analytic solution is examined using long wavelengths and a small Reynolds number assumption. The stream function, temperature, concentration and heat transfer coefficient expressions are derived. The bvp4c function from MATLAB has been used to numerically solve the transformed equations. The flow characteristics have been analyzed using graphs to demonstrate the impacts of different parameters.

关键词： Stream Function Mass Transfer Vertical Channel Casson Fluid

Insights into Manipulation: Unveiling Tampered Images Using Modified ELA, Deep Learning, and Explainable AI

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Journal of Computer and Communications 2024年第6期12卷 135-151页

作者： md. Mehedi hasan md. Masud Rana Abu Sayed md. Mostafizur Rahaman Department of Information and Communication Technology Bangladesh University of Professionals Dhaka Bangladesh Department of Computer Science and Engineering Jahangirnagar University Dhaka Bangladesh

Digital image forgery (DIF) is a prevalent issue in the modern age, where malicious actors manipulate images for various purposes, including deception and misinformation. Detecting such forgeries is a critical task for maintaining the integrity of digital content. This thesis explores the use of Modified Error Level Analysis (ELA) in combination with a Convolutional Neural Network (CNN), as well as, Feedforward Neural Network (FNN) model to detect digital image forgeries. Additionally, incorporation of Explainable Artificial Intelligence (XAI) to this research provided insights into the process of decision-making by the models. The study trains and tests the models on the CASIA2 dataset, emphasizing both authentic and forged images. The CNN model is trained and evaluated, and Explainable AI (SHapley Additive exPlanation— SHAP) is incorporated to explain the model’s predictions. Similarly, the FNN model is trained and evaluated, and XAI (SHAP) is incorporated to explain the model’s predictions. The results obtained from the analysis reveals that the proposed approach using CNN model is most effective in detecting image forgeries and provides valuable explanations for decision interpretability.

关键词： IFD DIF ELA CNN FNN XAI SHAP CASIA2.0

Finite Element Analysis of Tubular KK Joint under Compressive Loading

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American Journal of Computational Mathematics 2024年第3期14卷 291-304页

作者： Mohammad Tanzil hasan md. Jobayer Mia md. Syful Isalm Bipul Department of Mathematics Bangabandhu Sheikh Mujibur Rahman Maritime University Dhaka Bangladesh Department of Naval Architecture and Offshore Engineering Bangabandhu Sheikh Mujibur Rahman Maritime University Dhaka Bangladesh

KK tubular joints are used to build jacket-type offshore structures. These joints are mostly made up of structural steel. These joints can withstand yield, buckling, and lateral loads depending on the structure’s design and environment. In this study, the Finite Element Model of the KK-type tubular joint has been created, and analysis has been performed under static loading using the Static Structural analysis system of ANSYS 19.2 commercial software and structural mechanics module of COMSOL Multiphysics. The KK tubular model is analyzed under compressive load conditions, and the resulting stress, strain, and deformation values are tabulated in both graphical and tabular form. This study includes a comparison of the outcomes from both commercial software. The results highlight that maximum stress, strain, and deformation values decrease as joint thickness increases. This study holds significant relevance in advancing the understanding of tubular KK joints and their response to compressive loading. The insights derived from the analysis have the potential to contribute to the development of more robust and reliable tubular KK joints in various engineering and structural applications. .

关键词： KK Joint Brace Offshore Structures Chord Numerical Analysis Static Analysis

Adequate Closed Form Wave Solutions to the Generalized KdV Equation in Mathematical Physics

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Journal of Applied Mathematics and Physics 2024年第6期12卷 2069-2082页

作者： md. Munnu Miah md. Al Amin Meia md. Matiur Rahman Sarker Ahammodullah hasan Department of Mathematics Islamic University Kushtia Bangladesh Department of Mathematics Government Titumir College Dhaka Bangladesh Department of Pharmacy University of Asia Pacific Dhaka Bangladesh

In this paper, we consider the generalized Korteweg-de-Vries (KdV) equations which are remarkable models of the water waves mechanics, the shallow water waves, the quantum mechanics, the ion acoustic waves in plasma, the electro-hydro-dynamical model for local electric field, signal processing waves through optical fibers, etc. We determine the useful and further general exact traveling wave solutions of the above mentioned NLDEs by applying the exp(−τ(ξ))-expansion method by aid of traveling wave transformations. Furthermore, we explain the physical significance of the obtained solutions of its definite values of the involved parameters with graphic representations in order to know the physical phenomena. Finally, we show that the exp(−τ(ξ))-expansion method is convenient, powerful, straightforward and provide more general solutions and can be helping to examine vast amount of travelling wave solutions to the other different kinds of NLDEs.

关键词： The Generalized KdV Equation The exp(-τ(ξ)) -Expansion Method Travelling Wave Solitary Wave

Dynamic Hand Gesture-Based Person Identification Using Leap Motion and Machine Learning Approaches

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Computers, Materials & Continua 2024年第4期79卷 1205-1222页

作者： Jungpil Shin md.AlMehedi hasan md.Maniruzzaman Taiki Watanabe Issei Jozume School of Computer Science and Engineering The University of AizuAizuwakamatsuFukushima965-8580Japan Department of Computer Science&Engineering Rajshahi University of Engineering&TechnologyRajshahi6204Bangladesh

Person identification is one of the most vital tasks for network security. People are more concerned about theirsecurity due to traditional passwords becoming weaker or leaking in various attacks. In recent decades, fingerprintsand faces have been widely used for person identification, which has the risk of information leakage as a resultof reproducing fingers or faces by taking a snapshot. Recently, people have focused on creating an identifiablepattern, which will not be reproducible falsely by capturing psychological and behavioral information of a personusing vision and sensor-based techniques. In existing studies, most of the researchers used very complex patternsin this direction, which need special training and attention to remember the patterns and failed to capturethe psychological and behavioral information of a person properly. To overcome these problems, this researchdevised a novel dynamic hand gesture-based person identification system using a Leap Motion sensor. Thisstudy developed two hand gesture-based pattern datasets for performing the experiments, which contained morethan 500 samples, collected from 25 subjects. Various static and dynamic features were extracted from the handgeometry. Randomforest was used to measure feature importance using the Gini Index. Finally, the support vectormachinewas implemented for person identification and evaluate its performance using identification accuracy. Theexperimental results showed that the proposed system produced an identification accuracy of 99.8% for arbitraryhand gesture-based patterns and 99.6% for the same dynamic hand gesture-based patterns. This result indicatedthat the proposed system can be used for person identification in the field of security.

关键词： Person identification leap motion hand gesture random forest support vector machine

Post Thyroidectomy Assessment of Intact Parathyroid Hormone for Early Prediction of Hypocalcaemia

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International Journal of Otolaryngology and Head & Neck Surgery 2024年第2期13卷 71-84页

作者： md. Masum Billah Ripon Kumar Sarkar md. Yousuf Ali Saad Zaman md. Nazmul hasan md. Shehab Uddin md. Mosleh Uddin Kazi Shameemus Salam Farzana Binte Abedin Leera Department of Otolaryngology-Head & Neck Surgery Universal Medical College Hospital Dhaka Bangladesh Department of Otolaryngology-Head & Neck Surgery National Institute of Ear Nose and Throat Dhaka Bangladesh Shaheed Ahsan Ullah Master General Hospital Gazipur Bangladesh Department of Otolaryngology-Head & Neck Surgery Cumilla Medical College Cumilla Bangladesh Department of ENT Oncology National Institute of Cancer Research & Hospital Dhaka Bangladesh Department of ENT Outdoor Rajshahi Medical College Hospital Rajshahi Bangladesh Department of Otolaryngology-Head & Neck Surgery Bangabandhu Sheikh Mujib Medical University Dhaka Bangladesh Department of Biochemistry Delta Medical College Hospital Dhaka Bangladesh

Background: As the half-life of intact parathyroid hormone (iPTH) is very low, it reflects parathyroid insufficiency within minutes to hours after total thyroidectomy. Therefore, iPTH level assessment in the postoperative period can be used to predict the development of hypocalcaemia. The optimal time point to measure serum iPTH is important for the accurate prediction of hypocalcaemia. Aim: This paper aims to evaluate the ability of iPTH as an early predictive marker of hypocalcaemia and determine which time iPTH is more able to predict postoperative hypocalcaemia. Method: This prospective observational study was conducted in the Department of Otolaryngology-Head & Neck Surgery, BSMMU, Dhaka, from July 2020 to December 2021, with 67 patients who underwent total thyroidectomy. iPTH levels were measured on the day before the operation and at 1 hour, 4 hours, and 24 hours after the operation. *** levels were measured on the day before the operation and 1st postoperative day. All the data were compiled and sorted properly and were analyzed statistically. Results: Postoperative hypocalcaemia developed in 18 cases, with an incidence of 26.9%. Pearson correlation showed a significant correlation between postoperative iPTH at 1 hr, 4 h, and 24 hr with 1st postoperative calcium value. The Receiver operating characteristic (ROC) curve was processed for the postoperative iPTH at 1 hr, 4 h, and 24 hr. The sensitivity, specificity, cut-off value, and mean AUC found 93.9%, 94.4%, ≤14.0, 0.988;95.9%, 94.4%, ≤09.5, 0.993 and 91.8%, 94.4%, ≤11.0, 0.993 respectively. Conclusion: iPTH can be used as an early predictor of post-thy-roidectomy hypocalcaemia. 4 hr iPTH showed more sensitivity and specificity for a cut-off value near the laboratory reference range.

关键词： Total Thyroidectomy Hypocalcaemia Serum Intact Parathyroid Hormone Early Predictor of Hypocalcaemia

Genome-wide identification,characterization and functional prediction of the SRS gene family in sesame(Sesamum indicum L.)

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Oil Crop Science 2024年第2期9卷 69-80页

作者： Farjana Afroz Susmi Tasmina Islam Simi md.Nahid hasan md.Abdur Rahim Department of Genetics and Plant Breeding Sher-e-Bangla Agricultural UniversityDhaka1207Bangladesh

Sesame(Sesamum indicum L.)is an ancient oilseed crop of the Pedaliaceae family with high oil content and potential health *** RELATED SEQUENCE(SRS)proteins are the transcription factors(TFs)specific to plants that contain RING-like zinc finger domain and are associated with the regulation of several physiological and biochemical *** also play vital roles in plant growth and development such as root formation,leaf development,floral development,hormone biosynthesis,signal transduction,and biotic and abiotic stress ***,the SRS gene family was not reported in sesame *** this study,identification,molecular characterization,phylogenetic relationship,cis-acting regulatory elements,protein-protein interaction,syntenic relationship,duplication events and expression pattern of SRS genes were analyzed in *** identified total six SiSRS genes on seven different linkage groups in the *** genome by comparing with the other species,including the model plant Arabidopsis *** SiSRS genes showed variation in their structure like2–5 exons and 1–4 *** other species,SiSRS proteins also contained‘RING-like zinc finger'and‘LRP1'***,the SiSRS genes were clustered into subclasses via phylogenetic analysis with proteins of ***,***,and some other plant *** cis-acting regulatory elements analysis revealed that the promoter region of SiSRS4(SIN_1011561)showed the highest 13 and 16 elements for light-and phytohormone-responses whereas,SiSRS1(SIN_1015187)showed the highest 15 elements for *** ABREs,or ABA-responsive elements,were found in a maximum of 8 copies in the SiSRS3(SIN 1009100).Moreover,the available RNA-seq based expression of SiSRS genes revealed variation in expression patterns between stress-treated and non-treated samples,especially in drought and salinity conditions *** SiSRS genes like SiSRS1(SIN_1015187)and SiSRS5(SIN_1021065),also exhibited variabl

关键词： SiSRS gene family SHI Transcription factor Characterization Sesamum indicum

Multi-objective performance optimization&thermodynamic analysis of solar powered supercritical CO_(2)power cycles using machine learning methods&genetic algorithm

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Energy and AI 2024年第1期15卷 193-216页

作者： Asif Iqbal Turja md.Mahmudul hasan M.Monjurul Ehsan Yasin Khan Department of Mechanical and Production Engineering(MPE) Islamic University of Technology(IUT)Board BazarGazipur1704Bangladesh

The present study is focused on multi-objective performance optimization&thermodynamic analysis from the perspectives of energy and exergy for Recompression,Partial Cooling&Main Compression Intercooling supercritical CO_(2)(sCO_(2))Brayton cycles for concentrated solar power(CSP)applications using machine learning *** novelty of this work lies in the integration of artificial neural networks(ANN)and genetic algorithms(GA)for optimizing the performance of advanced sCO_(2)power cycles considering climatic variation,which has significant implications for both the scientific community and engineering applications in the renewable energy *** methodology employed includes thermodynamic analysis based on energy,exergy&environmental factors including system performance *** system is modelled for net power production of 15 MW thermal output utilizing equations for the energy and exergy balance for each ***,thermodynamic model extracted dataset used for prediction&evaluation of Random Forest,XGBoost,KNN,AdaBoost,ANN and LightGBM ***,considering climate conditions,multi-objective optimization is carried out for the CSP integrated sCO_(2)Power cycle for optimal power output,exergy destruction,thermal and exergetic *** algorithm and TOPSIS(technique for order of preference by similarity to ideal solution),multi-objective decision-making tool,were used to determine the optimum operating *** major findings of this work reveal significant improvements in the performance of the advanced sCO_(2)cycle by 1.68%and 7.87%compared to conventional recompression and partial cooling cycle,*** research could advance renewable energy technologies,particularly concentrated solar power,by improving power cycle designs to increase system efficiency and economic *** advanced supercritical CO_(2)power cycles in concentrated solar power plants might increase renewable energy use

关键词： Supercritical CO_(2) Concentrated solar power Thermodynamic analysis Machine learning Artificial neural network Multi-objective optimization

Japanese Sign Language Recognition by Combining Joint Skeleton-Based Handcrafted and Pixel-Based Deep Learning Features with Machine Learning Classification

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 2605-2625页

作者： Jungpil Shin md.Al Mehedi hasan Abu Saleh Musa Miah Kota Suzuki Koki Hirooka School of Computer Science and Engineering The University of AizuAizuwakamatsu965-8580Japan Department of Computer Science&Engineering Rajshahi University of Engineering&TechnologyRajshahi6204Bangladesh

Sign language recognition is vital for enhancing communication accessibility among the Deaf and hard-of-hearing *** Japan,approximately 360,000 individualswith hearing and speech disabilities rely on Japanese Sign Language(JSL)for ***,existing JSL recognition systems have faced significant performance limitations due to inherent *** response to these challenges,we present a novel JSL recognition system that employs a strategic fusion approach,combining joint skeleton-based handcrafted features and pixel-based deep learning *** system incorporates two distinct streams:the first stream extracts crucial handcrafted features,emphasizing the capture of hand and body movements within JSL ***,a deep learning-based transfer learning stream captures hierarchical representations of JSL gestures in the second ***,we concatenated the critical information of the first stream and the hierarchy of the second stream features to produce the multiple levels of the fusion features,aiming to create a comprehensive representation of the JSL *** reducing the dimensionality of the feature,a feature selection approach and a kernel-based support vector machine(SVM)were used for the *** assess the effectiveness of our approach,we conducted extensive experiments on our Lab JSL dataset and a publicly available Arabic sign language(ArSL)*** results unequivocally demonstrate that our fusion approach significantly enhances JSL recognition accuracy and robustness compared to individual feature sets or traditional recognition methods.

关键词： Japanese Sign Language(JSL) hand gesture recognition geometric feature distance feature angle feature GoogleNet