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Advancing PCB Quality Control: Harnessing YOLOv8 Deep Learning for real-Time Fault Detection

Computers, Materials and Continua 2024年第1期81卷 345-367页

作者： k.an r.u. Shah F. k.an A.A. Tahir H. Faculty of Cognitive Sciences and Human Development Universiti Malaysia Sarawak Kota Samarahan 94300 Malaysia School of Computer Science and Engineering Anhui University of Science and Technology Huainan 232001 China Department Electronic Quaid-i-Azam University Islamabad 45320 Pakistan

Printed Cir.u.t Boards (PCBs) are materials used to connect components to one another to form a working cir.u.t. PCBs play a crucial role in modern electronics by connecting various components. The trend of integrating more components onto PCBs is becoming increasingly common, which presents significant challenges for quality control processes. Given the potential impact that even minute defects can have on signal traces, the surface inspection of PCB remains pivotal in ensuring the overall system integrity. To address the limitations associated with manual inspection, this research endeavors to automate the inspection process using the YOLOv8 deep learning algorithm for real-time fault detection in PCBs. Specifically, we explore the effectiveness of two variants of the YOLOv8 architecture: YOLOv8 Small and YOLOv8 Nano. Thr.u.h rigor.u. experimentation and evaluation of our dataset which was acquired from Peking university’s Human-robot Interaction Lab, we aim to assess the suitability of these models for improving fault detection accuracy within the PCB manufacturing process. Our results reveal the remarkable capabilities of YOLOv8 Small models in accurately identifying and classifying PCB faults. The model achieved a precision of 98.7%, a recall of 99%, an accuracy of 98.6%, and an F1 score of 0.98. These findings highlight the potential of the YOLOv8 Small model to significantly improve the quality control processes in PCB manufacturing by providing a reliable and efficient solution for fault detection. © 2024 The Authors. Published by Tech Science Press.

关键词： deep learning object detection Printed cir.u.t boards (PCB) YOLOv8 YOLOv8 Nano YOLOv8 Small

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Fuzzy and IrLNC-based r.u.ing approach to improve data storage and system reliability in IoT

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Intelligent and Converged Networks 2024年第1期5卷 68-80页

作者： u.Indumathi A.r.Arunachalam the Department of Computer Science and Engineering Dr.M.G.R.Educational and Research InstituteChennai 600095India

Internet of Things(IoT)based sensor network is largely utilized in various field for transmitting huge amount of data due to their ease and cheaper *** performing this entire process,there is a high possibility for data cor.u.tion in the mid of *** the other hand,the network performance is also affected due to various *** address these issues,an efficient algorithm that jointly offers improved data storage and reliable r.u.ing is ***,after the deployment of sensor nodes,the election of the storage node is achieved based on a fuzzy expert *** random Linear Network Coding(IrLNC)is used to create an encoded *** encoded packet from the source and neighboring nodes is transmitted to the storage ***,to transmit the encoded packet from the storage node to the destination shortest path is found using the Destination Sequenced Distance Vector(DSDV)*** analysis of the proposed work is carried out by evaluating some of the statistical *** residual energy,packet delivery ratio,compression ratio and storage time achieved for the proposed work are 8.8%,0.92%,0.82%,and 69 *** on this analysis,it is revealed that better data storage system and system reliability is attained using this proposed work.

关键词： Internet of Things(IoT) data storage management fuzzy system improved random linear network coding energy utilization system reliability

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An Efficient Long Short-TermMemory and Gated recurrent unit Based Smart Vessel Trajectory Prediction using Automatic Identification System Data

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Computers, Materials and Continua 2024年第1期81卷 1789-1808页

作者： Zaman u. k.an J. Lee E. Hussain S. Balobaid A.S. Aburasain r.Y. kim k. Department of Computer Engineering Chungnam National University Daejeon 34134 South Korea Department of Environmental IT Engineering Chungnam National University Daejeon 34134 South Korea Autonomous Ship research Center Samsung Heavy Industries Daejeon 34051 South Korea ICArOS Center (PrISMA Lab) University of Naples Federico II Naples 80131 Italy Department of Computer Science College of Computer Science and Information Technology Jazan University Jazan 45142 Saudi Arabia

Maritime transportation, a cornerstone of global trade, faces increasing safety challenges due to growing sea traffic volumes. This study proposes a novel approach to vessel trajectory prediction utilizing Automatic Identification System (AIS) data and advanced deep learning models, including Long Short-Term Memory (LSTM), Gated recurrent unit (Gru), Bidirectional LSTM (DBLSTM), Simple recurrent Neural Network (SimplerNN), and kalman Filtering. The research implemented rigor.u. AIS data preprocessing, encompassing record deduplication, noise elimination, stationary simplification, and removal of insignificant trajectories. Models were trained using key navigational parameters: latitude, longitude, speed, and heading. Spatiotemporal aware processing thr.u.h trajectory segmentation and topological data analysis (TDA)was employed to capture dynamic *** using a three-month AIS dataset demonstrated significant improvements in prediction accuracy. The Gru model exhibited superior performance, achieving training losses of 0.0020 (Mean Squared Error, MSE) and 0.0334 (Mean Absolute Error, MAE), with validation losses of 0.0708 (MSE) and 0.1720 (MAE). The LSTM model showed comparable efficacy, with training losses of 0.0011 (MSE) and 0.0258 (MAE), and validation losses of 0.2290 (MSE) and 0.2652 (MAE). Both models demonstrated reductions in training and validation losses, measured by MAE, MSE, Average Displacement Error (ADE), and Final Displacement Error (FDE). This research underscores the potential of advanced deep learning models in enhancing maritime safety thr.u.h more accurate trajectory predictions, contributing significantly to the development of robust, intelligent navigation systems for the maritime industry. © 2024 The Authors. Published by Tech Science Press.

关键词： AIS data deep learning Gru LSTM smart vessel Trajectory prediction

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Bubble coalescence in interacting system of DNA molecules

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International Journal of Biomathematics 2024年第4期17卷 195-216页

作者： u.A.rozikov V.I.romanouskiy Institute of Mathematics 9 Universitet Street100174 Tashkent uzbekistan AkFA university National Park StreetBarkamol MFY Mirzo-Ulugbek District111221 Tashkent uzbekistan National university of uzbekistan 4Universitet Street 100174 TashkentUzbekistan

We consider two models of interacting DNA molecules:First is(four parametric)bubble coalescence model in interacting DNAs(shortly:BCI-DNA).Second is(three parametric)bubble coalescence model in a condensed DNA molecules(shortly BCC-DNA).To study bubble coalescence thermodynamics of BCI-DNA and BCC-DNA models we use methods of statistical ***,we define Hamiltonian of each model and give their translation-invariant Gibbs measures(TIGMs).For the first model,we find parameters such that corresponding Hamiltonian has up to three TIGMs(three phases of system)biologically meaning existence of three states:“No bubble coalescence”,“Dominated soft zone”,“Bubble coalescence”.For the second model,we show that for any(admissible)parameters,this model has unique *** is a state where“No bubble coalescence”phasedominates.

关键词： DNA bubble configuration Cayley tree Gibbs measure Potts model

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Hybrid-Vlasov simulation of soft X-ray emissions at the Earth’s dayside magnetospheric boundaries

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Earth and Planetary Physics 2024年第1期8卷 70-88页

作者： M.Grandin H.k.Connor S.Hoilijoki M.Battarbee Y.Pfau-kempf u.Ganse k.Papadakis M.Palmroth Department of Physics University of HelsinkiHelsinkiFinland NASA Goddard Space Flight Center GreenbeltMD20771USA Space and Earth Observation Centre Finnish Meteorological InstituteHelsinkiFinland

Solar wind charge exchange produces emissions in the soft X-ray energy range which can enable the study of near-Earth space regions such as the magnetopause,the magnetosheath and the polar cusps by remote sensing *** Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)and Lunar Environment heliospheric X-ray Imager(LEXI)missions aim to obtain soft Xray images of near-Earth space thanks to their Soft X-ray Imager(SXI)*** earlier modeling works have already simulated soft X-ray images as might be obtained by SMILE SXI during its mission,the numerical models used so far are all based on the magnetohydrodynamics description of the space *** investigate the possible signatures of ion-kinetic-scale processes in soft Xray images,we use for the first time a global hybrid-Vlasov simulation of the geospace from the Vlasiator *** simulation is driven by fast and tenuous solar wind conditions and purely southward interplanetary magnetic *** first produce global X-ray images of the dayside near-Earth space by placing a vir.u.l imaging satellite at two different locations,providing meridional and equatorial *** then analyze regional features present in the images and show that they correspond to signatures in soft X-ray emissions of mirrormode wave structures in the magnetosheath and flux transfer events(FTEs)at the *** results suggest that,although the time scales associated with the motion of those transient phenomena will likely be significantly smaller than the integration time of the SMILE and LEXI imagers,mirror-mode structures and FTEs can cumulatively produce detectable signatures in the soft X-ray *** instance,a local increase by 30%in the proton density at the dayside magnetopause resulting from the transit of multiple FTEs leads to a 12%enhancement in the line-of-sight-and time-integrated soft X-ray emissivity originating from this ***,a proton density increase by 14%in the magnetosheath

关键词： magnetosphere magnetosheath numerical simulation SMILE LEXI soft X-ray emissions hybrid-Vlasov model polar cusp flux transfer events mirror-mode waves

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Suppressive effects of exercise-conditioned serum on cancer cells:A narrative review of the influence of exercise mode,volume,and intensity

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Journal of Sport and Health Science 2024年第4期13卷 484-498,F0003页

作者： Francesco Bettariga Dennis r.Taaffe Daniel A.Galvao Chris Bishop Jin-Soo kim robert u.Newton Exercise Medicine research Institute Edith Cowan UniversityJoondalupWA 6027Australia School of Medical and Health Sciences Edith Cowan UniversityJoondalupWA 6027Australia London Sport Institute School of Science and TechnologyMiddlesex UniversityLondonNW44BTUK School of Human Movement and Nutrition Sciences University of QueenslandSt.LuciaQLD 4072Australia

Cancer is a major cause of morbidity and mortality worldwide,and the incidence is increasing,highlighting the need for effective strategies to treat this *** has emerged as fundamental therapeutic medicine in the management of cancer,associated with a lower risk of recur-rence and increased *** avenues of research demonstrate reduction in growth,proliferation,and increased apoptosis of cancer cells,including breast,prostate,colorectal,and lung cancer,when cultured by serum collected after exercise in vitro(i.e.,the cultivation of cancer cell lines in an experimental setting,which simpliﬁes the biological system and provides mechanistic insight into cell responses).The underlying mechanisms of exercise-induced cancer suppressive effects may be attributed to the alteration in cir.u.ating factors,such as skeletal muscle-induced cytokines(i.e.,myokines)and ***,exercise-induced tumor suppressive effects and detailed information about training interventions are not well investigated,constraining more precise application of exercise medicine within clinical *** date,it remains unclear what role different training modes(i.e.,resistance and aerobic training)as well as volume and intensity have on exercise-condi-tioned serum and its effects on cancer ***,the available evidence is that a single bout of aerobic training at moderate to vigor.u. intensity has cancer suppressive effects,while for chronic training interventions,exercise volume appears to be an inﬂuential candidate driving cancer inhibitory effects regardless of training *** for future research investigating training modes,volume and intensity are provided to further our.u.derstanding of the effects of exercise-conditioned serum on cancer cells.

关键词： Cancer cells High intensity interval training Moderate intensity continuous training resistance training Myokines

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unmixing detrital zircon u-Pb ages reveals tectonic and climatic depositional influences on the Carbonifer.u. Ansilta Formation,Calingasta-uspallata Basin,Western Argentina

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Geoscience Frontiers 2024年第4期15卷 61-77页

作者： J.r.Malone J.E.Malone J.L.Isbell D.H.Malone J.P.Craddock k.N.Pauls Department of Geological Sciences Jackson School of GeosciencesUniversity of Texas at AustinAustinTX 78712USA Iowa Geological Survey University of IowaIowa CityIA 52240USA Department of Geosciences University of Wisconsin-MilwaukeeMilwaukeeWI 53211USA Department of Geography Geology and the EnvironmentIllinois State UniversityNormalIL 61790-4400USA

The Late Paleozoic Ice Age(LPIA)was a principal control of sedimentation across Gondwana from the late Devonian thr.u.h early *** assess the hypothesis that glacial to interglacial transitions in western Argentina were the primary control influencing sediment r.u.ing patterns among the various Carbonifer.u.-Permian basins in western *** Carbonifer.u. Ansilta Formation consists of glaciomarine,nearshore,and fluvial systems deposited during the LPIA along the eastern margin of the Calingasta-uspallata Basin in *** lower,glacially influenced succession of the Ansilta Formation records at least five glacial advances;the upper succession of consists of progradational shallow marine,deltaic,and fluvial *** combine 1225 new u-Pb zircon ages from six samples of the Carbonifer.u. Ansilta Formation in the Calingasta-uspallata Basin with 5864 u-Pb ages from 147 pub-lished samples in the detrital Pymix forward mixture model to characterize provenance *** the glacially influenced lower Ansilta Formation,sediment was derived locally from the Protoprecordillera,which was a prominent highland with alpine glaciers flowing west and east into the Calingasta-uspallata and Paganzo basins,***,there was little or no connection between these two basins during Ser.u.hovian-Bashkirian *** fluvial/deltaic upper Ansilta had distal sediment sources in the Sierras ***,our results support the collapse of the Protoprecordillera topographic barrier,enabling drainage patterns connecting the Paganzo and Calingasta-uspallata basins by late Pennsylvanian-early Permian time.

关键词： Late Paleozoic Ice Age Argentina Calingasta-uspallata Basin Ansilta Formation Detrital zircon provenance

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Stakeholder Theory, Public Engagement, and Epistemic Injustice: The Case of Covid-19 Vaccine Hesitancy in Scotland's African, Caribbean, and Black Communities

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INTErNATIONAL JOurNAL OF DISASTEr rISk SCIENCE 2024年第4期15卷 552-564页

作者： Adekola, Josephine u. Chia, robert univ Glasgow Adam Smith Business Sch Glasgow G11 6EY Scotland

The adoption of a stakeholder approach to public engagement within the public sector has been extensive. However, there remain critical gaps in the understanding of stakeholder participation arising from hidden disparities that contribute to unequal access to communication channels, information, and hence ultimately knowledge and decision making. The term "epistemic injustice" has been used to describe such inequality of access and consequently, the outcome that ensues. Epistemic injustice is much overlooked in stakeholder theory. This article shows how epistemic injustice can act as a barrier to effective stakeholder engagement and hence to successful public policy for.u.ation and implementation. We use the case of vaccine hesitancy among Scotland's African, Caribbean, and Black (ACB) communities to illustrate this problem of unequal participation. The study drew on primary data involving 85 participants and secondary data sources from extant literature and explored salient factors shaping barriers to vaccine uptake during the recent pandemic. The findings demonstrate how the failure to grasp epistemic injustice undermines the effectiveness of the stakeholder approach, even with the most well-intentioned efforts. We ar.u. that epistemic injustice is a critical barrier to effective stakeholder approaches.

关键词： Covid-19 vaccine hesitancy Epistemic injustice Public engagement Scotland Stakeholder theory PArTICIPATION VIDEOGrAPHY MANAGEMENT POWEr

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Variational data encoding and correlations in quantum-enhanced machine learning

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Chinese Physics B 2024年第9期33卷 298-306页

作者： Ming-Hao Wang Hua L¨u School of Physics Hubei UniversityWuhan 430062China School of Science Hubei University of TechnologyWuhan 430068China

Leveraging the extraordinary phenomena of quantum superposition and quantum correlation,quantum computing offers unprecedented potential for addressing challenges beyond the reach of classical *** paper tackles two pivotal challenges in the realm of quantum computing:firstly,the development of an effective encoding protocol for translating classical data into quantum states,a critical step for any quantum *** encoding strategies can significantly influence quantum computer ***,we address the need to counteract the inevitable noise that can hinder quantum *** primary contribution is the introduction of a novel variational data encoding method,gr.u.ded in quantum regression algorithm *** adapting the learning concept from machine learning,we render data encoding a learnable *** allowed us to study the role of quantum correlation in data *** numerical simulations of various regression tasks,we demonstrate the efficacy of our variational data encoding,particularly post-learning from instructional ***,we delve into the role of quantum correlation in enhancing task performance,especially in noisy *** findings underscore the critical role of quantum correlation in not only bolstering performance but also in mitigating noise interference,thus advancing the frontier of quantum computing.

关键词： quantum machine learning variational data encoding quantum correlation

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Lump and travelling wave solutions of a(3+1)-dimensional nonlinear evolution equation

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Journal of Ocean Engineering and Science 2024年第2期9卷 164-172页

作者： kalim u.Tariq raja Nadir Tufail Department of Mathematics Mirpur University of Science and TechnologyMirpurAJK 10250Pakistan

In this paper,the(3+1)-dimensional nonlinear evolution equation is studied *** bilinear form of given model is achieved by using the Hirota bilinear *** a result,the lump waves and col-lisions between lumps and periodic waves,the collision among lump wave and single,double-kink soliton solutions as well as the collision between lump,periodic,and single,double-kink soliton solutions for the given model are ***,some new traveling wave solutions are developed by applying the exp(−φ(ξ))expansion *** 3D,2D and contours plots are drawn to demonstrate the nature of the nonlinear model for setting appropriate set of *** a result,a collection of bright,dark,periodic,rational function and elliptic function solutions are *** applied strategies appear to be more power.u. and efficient approaches to construct some new traveling wave structures for various contemporary models of recent era.

关键词： The Hirota bilinear method Lump wave solution Travelling wave solution Exp(−φ(ξ))expansion technique

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