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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

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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

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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

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An Efficient Approach for Transforming Unbalanced Transportation Problems into Balanced Problems in Order to Find Optimal Solutions

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American Journal of Operations Research（美国运筹学期刊） 2024年第1期

作者： Abdur Rashid md. Amirul islam

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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

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MOVPE Growth of In_xGa_(1-x)N(x～0.4) and Fabrication of Homo-junction Solar Cells

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Journal of Materials Science & Technology 2013年第2期29卷 128-136页

作者： md. Rafiqul islam md. Rejvi Kaysir md. Jahirul islam A. Hashimoto A. Yamamoto Department of Electrical and Electronic Engineering KUETKhulna 9203 Bangladesh Graduate School of Engineering University of Fukui 3-9-1 BunkyoFukui 910-8507 Japan

The metal organic vapor phase epitaxy （MOVPE） growth of indium gallium nitride （InGaN） has been discussed in detail towards the fabrication of solar cell. The InGaN film with In contents up to 0.4 are successfully grown by controlling the fundamental growth parameters such as the precursor gas flow rates, temperature etc. The formation of metallic In originates from the higher value （0.74） of trimethylindium/ （trimethylindium ＋ triethylgallium）（TMI/（TMI ＋ TEG）） molar ratio with low （4100） V/lll weight molar ratio while the lower value （0.2） of TMI/（TMI ＋ TEG） causes the phase separation. It is also necessary to control the growth rate and epitaxial film thickness to suppress the phase separation in the material. The crystalline quality of grown films is studied and it is found to be markedly deteriorated with increasing In content. The lattice parameters as well as the thermal expansion coefficient mismatch between GaN template and InGaN epi-layer are primarily considered as the reasons to deteriorate the film quality for higher In content. By using Ino.16Ga0.84N films, an n＋-p homo-junction structure is fabricated on 0.65 μm GaN template. For such a device, the response to the light illumination （AM 1.5） is observed with an open circuit voltage of 1.4 V and the short circuit current density of 0.25 mA/cm2. To improve the performance as well as increase solar photon capturing, the device is further fabricated on thick GaN template with higher In content. The In0.25Ga0.75N n＋-p junction solar cell is found better performance with an open circuit voltage of 1.5 V and the short circuit current density of 0.5 mA/cm2. This is the InGaN p-n homo-junction solar cell with the highest In content ever reported by MOVPE.

关键词： InGaN Metal organic vapor phase epitaxy (MOVPE) Growth Film quality Doping p-n junction

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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

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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

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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

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Fine-tuning electronic structure of N-doped graphitic carbon-supported Co-and Fe-incorporated Mo_(2)C to achieve ultrahigh electrochemical water oxidation activity

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Carbon Energy 2024年第7期6卷 134-149页

作者： md.Selim Arif Sher Shah Hyeonjung Jung Vinod K.Paidi Kug-Seung Lee Jeong Woo Han Jong Hyeok Park Department of Chemical and Biomolecular Engineering Yonsei UniversitySeoulRepublic of Korea Department of Chemistry University of North BengalRaja RammohunpurDarjeelingWest BengalIndia Department of Materials Science and Engineering Research Institute of Advanced MaterialsSeoul National UniversitySeoulRepublic of Korea Pohang Accelerator Laboratory Beamline DivisionPohangRepublic of Korea European Synchrotron Radiation Facility France

Mo_(2)C is an excellent electrocatalyst for hydrogen evolution reaction(HER).However,Mo_(2)C is a poor electrocatalyst for oxygen evolution reaction(OER).Herein,two different elements,namely Co and Fe,are incorporated in Mo_(2)C that,therefore,has a finely tuned electronic structure,which is not achievable by incorporation of any one of the ***,the resulting electrocatalyst Co_(0.8)Fe_(0.2)-Mo_(2)C-80 displayed excellent OER catalytic performance,which is evidenced by a low overpotential of 214.0(and 246.5)mV to attain a current density of 10(and 50)mA cm^(-2),an ultralow Tafel slope of 38.4 mV dec^(-1),and longterm stability in alkaline *** data demonstrates that Co_(0.8)Fe_(0.2)-Mo_(2)C-80 requires the lowest overpotential(1.00 V)for OER and Co centers to be the active *** ultrahigh catalytic performance of the electrocatalyst is attributed to the excellent intrinsic catalytic activity due to high Brunauer-Emmett-Teller specific surface area,large electrochemically active surface area,small Tafel slope,and low chargetransfer resistance.

关键词： fine-tuning electronic structures heteronanostructures Mo_(2)C multimetal(Co/Fe) oxygen evolution reaction

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