检索结果-南通市图书馆

Materials Sciences and Applications 2024年第6期15卷 137-154页

作者： Fatema Najrin Rabeya Bakar Sarna md. alamin sarker Budrun Neher md. Mahbubur Rahman Bhuiyan Farid Ahmed Department of Physics Jahangirnagar University Dhaka Bangladesh Department of Electrical and Electronics Engineering Green University of Bangladesh Purbachal American City Kanchan Rupganj Narayanganj-1461 Dhaka Bangladesh

In the present study, the effect of the exchange-correlation functional on the structural, mechanical, and optoelectronic properties of orthorhombic RbSrBr3 perovskite has been investigated using various functionals in Density Functional Theory (DFT) with the CASTEP code. The optimized lattice parameters are quite similar for all the functionals. The electronic properties have shown that RbSrBr3 perovskite is a wide direct band gap compound with a band gap energy ranging from 4.296 eV to 4.494 eV for all the functionals. The mechanical parameters like elastic constants, Young’s modulus, Shear modulus, Poisson’s ratio, Pugh’s ratio, and an anisotropic factor reveal that the RbSrBr3 perovskite has ductile behavior and an anisotropic nature which signifies the mechanical stability of the compound. The Debye temperature might withstand lattice vibration heat. High absorption coefficient (>104 cm−1), high optical conductivity, and very low reflectivity have been found in the RbSrBr3 perovskite for all functions. The computed findings on the RbSrBr3 perovskite suggested that the presented studied material is potentially applicable for photodetector and optoelectronic devices.

关键词： Density Functional Theory Mechanical Properties Photodetector Ductility Anisotropic Factor

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

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

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

Credit Card Fraud Detection Using Machine Learning Techniques

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Computer and Communications 2024年第6期12卷 1-11页

作者： Ananya sarker Must. Asma Yasmin md. Atikur Rahman md. Harun Or Rashid Bristi Rani Roy Department of Computer Science and Engineering Bangladesh Army University of Engineering & Technology (BAUET) Natore Bangladesh

Credit card companies must be able to identify fraudulent credit card transactions so that clients are not charged for items they did not purchase. Previously, many machine learning approaches and classifiers were used to detect fraudulent transactions. However, because fraud patterns are always changing, it is becoming increasingly vital to investigate new frauds and develop the model based on the new patterns. The purpose of this research is to create a machine learning classifier that not only detects fraud but also detects legitimate transactions. As a result, the model should have excellent accuracy, precision, recall, and f1-score. As a result, we began with a large dataset in this study and used four machine learning classifiers: Support Vector Machine (SVM), Decision Tree, Naïve Bayes, and Random Forest. The random forest classifier scored 99.96% overall accuracy with the best precision, recall, f1-score, and Matthews correlation coefficient in the experiments.

关键词： Support Vector Machine Decision Tree Nave Bayes Random Forest Matthews Correlation

Repercussion of salinity on hematological parameters and tissue morphology of gill and kidney at early life of tilapia

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Aquaculture and Fisheries 2024年第2期9卷 256-264页

作者： Azhar Ali md.Golam Azom Bhakta Supratim sarker Hasu Rani md.Samsul Alam m.sadiqul islam*department of fisheries biology and genetics bangladesh agricultural universitymymensingh2202bangladesh

This study was attempted to reveal the changes in three hematological parameters such as blood hemoglobin,number of white blood cells(WBCs)and number of red blood cells(RBCs)and one biochemical(e.g.,glucose)parameter along with the changes in histomorphological structures of gills and kidney of Nile tilapia fry reared in saline *** experimental set up were used for two different age groups-5 days-after-hatch(5DAH)and 15 days-after-hatch(15DAH)-to test a novel hypothesis:if a little difference in the age during the first exposure to saline water could produce any variation in the *** were placed into 6 plastic drums having six different salinity levels:0,5,10,15,20 and *** 60 days,at least 5 individuals were taken out from each drum to observe the above-hematological and histomorphological parameters.A two-way-ANOVA revealed that,except for hemoglobin,all the observed parameters have been affected the effect of age×salinity interaction(P<0.05).Between the two age groups,only the overall average glucose value and RBC count were significantly *** various salinity levels,only RBC and WBC counts differed ***,the mean glucose value,RBC counts and WBC count at different salinities differed significantly from the base mean value of each *** regard to the histomorphological structure of the gills and kidney,various malformations were *** hypertrophy,epithelial uplifting and epithelial necrosis were present as gill degenerations,hyperplasia was prevalent across almost all salinity *** the other hand,glomerular necrosis,pyknotic nucleus,hyaline droplets degeneration,shrinking of the glomeruli,*** observed in kidney *** assisting to understand the effects of salinity stress,all these data on tilapia fry will help to determine the prospects and scope of culturing the species in high-salinity water.

关键词： Nile tilapia Salinity Blood parameters Histomorphology Age groups

Vision Intelligence for Smart Sheep Farming: Applying Ensemble Learning to Detect Sheep Breeds

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

ARTIFICIAL INTELLIGENCE IN AGRICULTURE 2024年第1期11卷 1-12页

作者： Himel, Galib Muhammad Shahriar Islam, md. Masudul Rahaman, Mijanur Bangladesh Univ Business & Technol Dhaka Bangladesh

The ability to automatically recognize sheep breeds holds significant value for the sheep industry. Sheep farmers often require breed identification to assess the commercial worth of their flocks. However, many farmers specifically the novice one encounter difficulties in accurately identifying sheep breeds without experts in the field. Therefore, there is a need for autonomous approaches that can effectively and precisely replicate the breed identification skills of a sheep breed expert while functioning within a farm environment, thus providing considerable benefits the industry-specific to the novice farmers in the industry. To achieve this objective, we suggest utilizing a model based on convolutional neural networks (CNNs) which can rapidly and efficiently identify the type of sheep based on their facial features. This approach offers a cost-effective solution. To conduct our experiment, we utilized a dataset consisting of 1680 facial images which represented four distinct sheep breeds. This paper proposes an ensemble method that combines Xception, VGG16, InceptionV3, InceptionResNetV2, and DenseNet121 models. During the transfer learning using this pre-trained model, we applied several optimizers and loss functions and chose the best combinations out of them. This classification model has the potential to aid sheep farmers in precisely and efficiently distinguishing between various breeds, enabling more precise assessments of sector-specific classification for different businesses. (c) 2023 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co., Ltd. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： Computer vision Sheep breed classification Image processing Transfer learning Ensemble learning Meta learner

Privacy-Preserving Information Fusion Technique for Device to Server-Enabled Communication in the Internet of Things:A Hybrid Approach

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第7期80卷 1305-1323页

作者： Amal Al-Rasheed Rahim Khan Tahani Alsaed Mahwish Kundi Mohamad Hanif md.Saad Mahidur R.sarker Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science AbdulWali Khan University MardanMardan23200Pakistan Faculty of Computing and Informatics University Malaysia SabahKota KinabaluSabah88400Malaysia Applied College Taibah UniversityMadinah41477Saudi Arabia Maynooth International Engineering College Maynooth UniversityCo KildareW23 X021Irland Department of Mechanical Engineering Faculty of Engineering and Built EnvironmentUniversiti Kebangsaan MalaysiaBangiSelangor43600Malaysia Institute of Visual Informatics Universiti Kebangsaan MalaysiaBangiSelangor43600Malaysia University of Design Innovation and Technology(UDIT)Av.Alfonso XIII97Madrid28016Spain

Due to the overwhelming characteristics of the Internet of Things(IoT)and its adoption in approximately every aspect of our lives,the concept of individual devices’privacy has gained prominent attention from both customers,i.e.,people,and industries as wearable devices collect sensitive information about patients(both admitted and outdoor)in smart healthcare *** addition to privacy,outliers or noise are among the crucial issues,which are directly correlated with IoT infrastructures,as most member devices are resource-limited and could generate or transmit false data that is required to be refined before processing,i.e.,***,the development of privacy-preserving information fusion techniques is highly encouraged,especially those designed for smart IoT-enabled *** this paper,we are going to present an effective hybrid approach that can refine raw data values captured by the respectivemember device before transmission while preserving its privacy through the utilization of the differential privacy technique in IoT *** window,i.e.,δi based dynamic programming methodology,is implemented at the device level to ensure precise and accurate detection of outliers or noisy data,and refine it prior to activation of the respective transmission ***,an appropriate privacy budget has been selected,which is enough to ensure the privacy of every individualmodule,i.e.,a wearable device such as a smartwatch attached to the patient’s *** contrast,the end module,i.e.,the server in this case,can extract important information with approximately the maximum level of ***,refined data has been processed by adding an appropriate nose through the Laplace mechanism to make it useless or meaningless for the adversary modules in the *** proposed hybrid approach is trusted from both the device’s privacy and the integrity of the transmitted information *** and analytical results ha

关键词： Internet of things information fusion differential privacy dynamic programming Laplace function

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

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

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

A Comparative Study of 3D Virtual Pattern and Traditional Pattern Making

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Textile Science and Technology 2024年第1期10卷 1-24页

作者： md. Ahshan Habib md. Shamsul Alam Department of Fashion Design & Technology Sonargaon University Dhaka Bangladesh Department of Apparel Manufacture & Technology Sonargaon University Dhaka Bangladesh

Pattern making plays a key role in the aspect of fashion design and garment production, as it serves as the transformative process that turns a simple drawing into a consistent accumulation of garments. The process of creating conventional or manual patterns requires a significant amount of time and a specialized skill set in various areas such as grading, marker planning, and fabric utilization. This study examines the potential of 3D technology and virtual fashion designing software in optimizing the efficiency and cost-effectiveness of pattern production processes. The proposed methodology is characterized by a higher level of comprehensiveness and reliability, resulting in time efficiency and providing a diverse range of design options. The user is not expected to possess comprehensive knowledge of traditional pattern creation procedures prior to engaging in the task. The software offers a range of capabilities including draping, 3D-to-2D and 2D-to-3D unfolding, fabric drivability analysis, ease allowance calculation, add-fullness manipulation, style development, grading, and virtual garment try-on. The strategy will cause a shift in the viewpoints and methodologies of business professionals when it comes to the use of 3D fashion design software. Upon recognizing the potential time, financial, and resource-saving benefits associated with the integration of 3D technology into their design development process, individuals will be motivated to select for its utilization over conventional pattern making methods. Individuals will possess the capacity to transfer their cognitive processes and engage in introspection regarding their professional endeavors and current activities through the utilization of 3D virtual pattern-making and fashion design technologies. To enhance the efficacy and ecological sustainability of designs, designers have the potential to integrate 3D technology with virtual fashion software, thereby compliant advantages for both commercial enterpri

关键词： Pattern-Making 3D Pattern Making Virtual Fashion 3D-to-2D Unfolding Sustainable Designs

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

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

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

Antinociceptive Effect of Ethanolic Extract of Codiaeum variegatum Leaves in Mice

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Pharmacology & Pharmacy 2024年第9期15卷 285-302页

作者： md. Asrafuzzaman Ambia Khatun md. Abdul Mannan Department of Pharmacy Stamford University Bangladesh Dhaka Bangladesh

Background: Codiaeum variegatum, sometimes called garden croton, is a tropical plant in the Euphorbiaceae family. Historically used to cure various conditions, including intestinal infections, fever, ulcers, wounds, and gonorrhea. This work aimed to investigate the antinociceptive effects of ethanolic extract of Codiaeum variegatum leaves (EECV) in animal models. Methods: Five different pain models—the hot plate, tail immersion, acetic acid-induced writhing, formalin, and glutamate-induced nociception tests—were utilized to assess the antinociceptive activity in mice. The traditional drugs such as diclofenac sodium (10 mg/kg, i.p.) and morphine sulphate (5 mg/kg). EECV was administered orally at varying doses of 100, 200, and 300 mg/kg (0.1 mL/mouse), while the control group was given deionized water. Results: The current study found that all mouse models of heat- and chemical-induced pain had robust EECV reflections of their antinociceptive properties (*p Conclusions: The current finding offers a fresh perspective on the ethanolic extract of Codiaeum variegatum leaves’ antinociceptive properties in mice. This plant’s phytochemical analysis revealed the presence of triterpenoids, sterols, alkaloids, flavonoids, and general glycosides, all of which may have antinociceptive properties. More research on the mechanism of action and associated pharmacological studies, such as in vivo analysis, medication formulation, and clinical trials, is strongly advised.

关键词： Codiaeum variegatum Extract Phytochemistry Antinociceptive