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Gradient Optimizer Algorithm with Hybrid Deep Learning Based Failure Detection and Classification in the Industrial Environment

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1341-1364页

作者： Mohamed Zarouan Ibrahim M.Mehedi Shaikh Abdul Latif md.Masud Rana Department of Electrical and Computer Engineering(ECE) King Abdulaziz UniversityJeddah21589Saudi Arabia Center of Excellence in Intelligent Engineering Systems(CEIES) King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Nuclear Engineering King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical and Electronic Engineering Rajshahi University of Engineering and TechnologyRajshahiBangladesh

Failure detection is an essential task in industrial systems for preventing costly downtime and ensuring the seamlessoperation of the system. Current industrial processes are getting smarter with the emergence of Industry ***, various modernized industrial processes have been equipped with quite a few sensors to collectprocess-based data to find faults arising or prevailing in processes along with monitoring the status of *** diagnosis of rotating machines serves a main role in the engineering field and industrial production. Dueto the disadvantages of existing fault, diagnosis approaches, which greatly depend on professional experienceand human knowledge, intellectual fault diagnosis based on deep learning (DL) has attracted the researcher’sinterest. DL reaches the desired fault classification and automatic feature learning. Therefore, this article designs a Gradient Optimizer Algorithm with Hybrid Deep Learning-based Failure Detection and Classification (GOAHDLFDC)in the industrial environment. The presented GOAHDL-FDC technique initially applies continuous wavelettransform (CWT) for preprocessing the actual vibrational signals of the rotating machinery. Next, the residualnetwork (ResNet18) model was exploited for the extraction of features from the vibration signals which are thenfed into theHDLmodel for automated fault detection. Finally, theGOA-based hyperparameter tuning is performedtoadjust the parameter valuesof theHDLmodel *** experimental result analysis of the GOAHDL-FD Calgorithm takes place using a series of simulations and the experimentation outcomes highlight the better resultsof the GOAHDL-FDC technique under different aspects.

关键词： Fault detection Industry 4.0 gradient optimizer algorithm deep learning rotating machineries artificial intelligence

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

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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

Design and Analysis of Power and Transmission System of Downhole Pure Electric Command Vehicle

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Journal of Transportation Technologies 2024年第1期14卷 31-52页

作者： md Jahangir Alam md Shahriar Sujan md. Al Imran Tapu Joy Howlader College of Civil and Transportation Engineering Hohai University Nanjing China College of Harbor Coastal & Offshore Engineering Hohai University Nanjing China Department of Computer Science and Technology College of Computer and Information Hohai University Nanjing China

Electric vehicles use electric motors, which turn electrical energy into mechanical energy. As electric motors are conventionally used in all the industry, it is an established development site. It’s a mature technology with ideal power and torque curves for vehicular operation. Conventional vehicles use oil and gas as fuel or energy storage. Although they also have an excellent economic impact, the continuous use of oil and gas threatened the world’s reservation of total oil and gas. Also, they emit carbon dioxide and some toxic ingredients through the vehicle’s tailpipe, which causes the greenhouse effect and seriously impacts the environment. So, as an alternative, electric car refers to a green technology of decarbonization with zero emission of greenhouse gases through the tailpipe. So, they can remove the problem of greenhouse gas emissions and solve the world’s remaining non-renewable energy storage problem. Pure electric vehicles (PEV) can be applied in all spheres, but their special implementation can only be seen in downhole operations. They are used for low noise and less pollution in the downhole process. In this study, the basic structure of the pure electric command vehicle is studied, the main components of the command vehicle power system, namely the selection of the drive motor and the power battery, are analyzed, and the main parameters of the drive motor and the power battery are designed and calculated. The checking calculation results show that the power and transmission system developed in this paper meets the design requirements, and the design scheme is feasible and reasonable.

关键词： Pure Electric Vehicles Transmission Gears Electronic Differential Control Algorithms

A New Algorithm for a Condenser Design for Large-Scale Nuclear Power Plants in Tropical Region

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Journal of Thermal Science 2020年第5期29卷 1370-1389页

作者： KHAN Abid hossain ISLAM md.Shafiqul Department of Industrial and Production Engineering Jashore University of Science and TechnologyJashore 7408Bangladesh Department of Nuclear Engineering University of DhakaDhaka 1000Bangladesh

This work presents a new velocity search algorithm for designing a condenser of a 1200 MWe large-scale nuclear power plant situated in tropical *** this,the condenser pressure was considered in the range of 7.5-15 kPa while its tube inner diameter was taken as 28 mm with 1 mm tube wall *** longitudinal and transverse condensers with multiple shell tanks and varied shell tank lengths from 8-14 m have been considered in this *** different tertiary coolant temperature rises were chosen as 4°C,8°C and 12°C by considering tropical region average reservoir water temperature range of 28°C to 32°C during *** of tertiary coolant was kept within 0.75-1.5 m/s to ensure sufficient turbulence to avoid erosion-corrosion of the *** simulation has been employed to obtain tube-side pressure drop and convection heat transfer coefficient directly from tertiary coolant inlet velocity using κ-ω turbulent flow model.A new iterative“Velocity-search algorithm”has been developed that focuses on finding the correct tertiary coolant velocity instead of overall heat transfer *** revealed that velocity-search algorithm yielded very close to the important physical and thermal parameters of condenser compared to the existing design data in large scale nuclear power ***-search algorithm has given less number of condenser design physical parameters that meets the velocity acceptance criteria for longitudinal condenser compared to the transverse ***,velocity-search algorithm is found to be more reliable,robust,and consistent for condenser design compared to the conventional design algorithm used in Log-Mean Temperature Difference method.

关键词： nuclear power plant vacuum condenser velocity-search algorithm tropical region

Activation of cerebral Ras-related C3 botulinum toxin substrate(Rac) 1 promotes post-ischemic stroke functional recovery in aged mice

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Neural Regeneration Research 2024年第4期19卷 881-886页

作者： Fan Bu Jia-Wei Min md Abdur Razzaque Ahmad El Hamamy Anthony Patrizz Li Qi Akihiko Urayama Jun Li Department of Neurology University of Texas Health Science Center Department of Neurology&Psychology The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine

Brain functional impairment after stroke is common;however,the molecular mechanisms of post-stroke recovery remain *** is well-recognized that age is the most important independent predictor of poor outcomes after stroke as older patients show poorer functional outcomes following *** evidence suggests that axonal regeneration and angiogenesis,the major forms of brain plasticity responsible for post-stroke recovery,diminished with advanced *** studies suggest that Ras-related C3 botulinum toxin substrate(Rac)1 enhances stroke recovery as activation of Rac1 improved behavior recovery in a young mice stroke ***,we investigated the role of Rac1 signaling in long-term functional recovery and brain plasticity in an aged(male,18 to 22 months old C57BL/6J)brain after ischemic *** found that as mice aged,Rac1 expression declined in the *** overexpression of Rac1,using lentivirus encoding Rac1 injected day 1 after ischemic stroke,promoted cognitive(assessed using novel object recognition test)and sensorimotor(assessed using adhesive removal tests)recovery on days 14–*** was accompanied by the increase of neurite and proliferative endothelial cells in the periinfarct zone assessed by *** a reverse approach,pharmacological inhibition of Rac1 by intraperitoneal injection of Rac1 inhibitor NSC23766 for 14 successive days after ischemic stroke worsened the outcome with the reduction of neurite and proliferative endothelial ***,Rac1 inhibition reduced the activation of p21-activated kinase 1,the protein level of brain-derived neurotrophic factor,and increased the protein level of glial fibrillary acidic protein in the ischemic brain on day 28 after *** work provided insight into the mechanisms behind the diminished plasticity after cerebral ischemia in aged brains and identified Rac1 as a potential therapeutic target for improving functional recovery in the older adults after stroke.

关键词： aging angiogenesis brain-derived neurotrophic factor(BDNF) cerebral ischemia cognitive recovery neurite Pak1 Rac1 sensorimotor recovery

Insights into the physical properties and anisotropic nature of ErPdBi with an appearance of low minimum thermal conductivity

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Chinese Physics B 2021年第1期30卷 398-406页

作者： S K Mitro R Majumder K M hossain md Zahid Hasan md Emran hossain M A Hadi Bangamata Sheikh Fojilatunnesa Mujib Science and Technology University Jamalpur-2012Bangladesh Physics Discipline Khulna UniversityKhulna-9208Bangladesh Department of Materials Science and Engineering University of RajshahiRajshahi-6205Bangladesh Department of Electrical and Electronic Engineering International Islamic University ChittagongKumiraChittagong-4318Bangladesh Department of Physics University of RajshahiRajshahi6205Bangladesh

We theoretically study the structural, elastic and optical properties of Er Pd Bi together with its anisotropic behaviors using density functional theory. It is observed that Er Pd Bi satisfies the Born stability criteria nicely and possesses high quality of machinability. The anisotropic behavior of Er Pd Bi is reported with the help of theoretical anisotropy indices incorporating 3 D graphical presentation, which suggests that Er Pd Bi is highly anisotropic in nature. It is noticed that the minimum thermal conductivity is very low for Er Pd Bi compared to the several species. This low value of minimum thermal conductivity introduces the potentiality of Er Pd Bi in high-temperature applications such as thermal barrier *** addition, deep optical insights of Er Pd Bi reveal that our material can be used in different optoelectronic and electronic device applications ranging from organic light-emitting diodes, solar panel efficiency, waveguides etc. to integration of integrated circuits. Therefore, we believe that our results will provide a new insight into high-temperature applications and will benefit for the development of promising optoelectric devices as well.

关键词： Er Pd Bi minimum thermal conductivity anisotropy density functional theory(DFT)

YOLO-RLC:An Advanced Target-Detection Algorithm for Surface Defects of Printed Circuit Boards Based on YOLOv5

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Computers, Materials & Continua 2024年第9期80卷 4973-4995页

作者： Yuanyuan Wang Jialong Huang md Sharid Kayes Dipu Hu Zhao Shangbing Gao Haiyan Zhang Pinrong Lv School of Computer and Software Engineering Huaiyin Institute of TechnologyHuai’an223003China Huaiyin Institute of Technology Laboratory for Internet of Things and Mobile Internet Technology of Jiangsu ProvinceHuai’an223001China Jiangsu Kesheng Xuanyi Technology Co. Ltd.Huai’an223300China

Printed circuit boards(PCBs)provide stable connections between electronic ***,defective printed circuit boards may cause the entire equipment system to malfunction,resulting in incalculable ***,it is crucial to detect defective printed circuit boards during the generation *** detection methods have low accuracy in detecting subtle defects in complex background *** order to improve the detection accuracy of surface defects on industrial printed circuit boards,this paper proposes a residual large kernel network based on YOLOv5(You Only Look Once version 5)for PCBs surface defect detection,called YOLO-RLC(You Only Look Once-Residual Large Kernel).Build a deep large kernel backbone to expand the effective field of view,capture global informationmore efficiently,and use 1×1 convolutions to balance the depth of the model,improving feature extraction efficiency through reparameterization *** neck network introduces a bidirectional weighted feature fusion network,combined with a brand-new noise filter and feature enhancement extractor,to eliminate noise information generated by information fusion and recalibrate information from different channels to improve the quality of deep *** the aspect ratio of the bounding box to alleviate the issue of specificity *** training and testing on the PCB defect dataset,our method achieved an average accuracy of 97.3%(mAP50)after multiple experiments,which is 4.1%higher than YOLOv5-S,with an average accuracy of 97.6%and an Frames Per Second of *** comparative analysis also proves the superior performance and feasibility of YOLO-RLC in PCB defect detection.

关键词： Deep learning PCB defect detection large kernel noise filtering weighted fusion YOLO

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

Regeneration mechanisms and therapeutic strategies for neuromuscular junctions in aging and diseases

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Neural Regeneration Research 2025年第1期20卷 193-194页

作者： Masashi Fujitani Abu md Mamun Tarif Yoshinori Otani Department of Anatomy and Neuroscience Faculty of MedicineShimane UniversityShimaneJapan

The neuromuscular junction(NMJ)is an essential synaptic structure composed of motor neurons,skeletal muscles,and glial cells that orchestrate the critical process of muscle contraction(Li et al.,2018).The typical NMJ structure is classically described as having a“pretzel-like”shape in mice(Figure 1),whereas human NMJs have a smaller,fragmented structure throughout *** NMJs exhibit smaller or fragmented endplates,partial denervation,reduced numbers of synaptic vesicles,abnormal presynaptic mitochondria,and dysfunctional perisynaptic Schwann cells(Alhindi et al.,2022).

关键词： aging structure Figure