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Human Gait Recognition for Biometrics Application Based on Deep Learning Fusion Assisted Framework

Computers, Materials & Continua 2024年第1期78卷 357-374页

作者： Ch Avais Hanif Muhammad Ali Mughal Muhammad Attique Khan Nouf Abdullah Almujally Taerang Kim Jae-Hyuk cha Department of Electrical Engineering HITEC UniversityTaxila47080Pakistan Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon Department of Computer Science HITEC UniversityTaxila47080Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Hanyang UniversitySeoul04763Korea

The demand for a non-contact biometric approach for candidate identification has grown over the past ten *** on the most important biometric application,human gait analysis is a significant research topic in computer *** have paid a lot of attention to gait recognition,specifically the identification of people based on their walking patterns,due to its potential to correctly identify people far *** recognition systems have been used in a variety of applications,including security,medical examinations,identity management,and access *** systems require a complex combination of technical,operational,and definitional *** employment of gait recognition techniques and technologies has produced a number of beneficial and well-liked *** proposes a novel deep learning-based framework for human gait classification in video *** framework’smain challenge is improving the accuracy of accuracy gait classification under varying conditions,such as carrying a bag and changing *** proposed method’s first step is selecting two pre-trained deep learningmodels and training fromscratch using deep transfer ***,deepmodels have been trained using static hyperparameters;however,the learning rate is calculated using the particle swarmoptimization(PSO)***,the best features are selected from both trained models using the Harris Hawks controlled Sine-Cosine optimization *** algorithm chooses the best features,combined in a novel correlation-based fusion ***,the fused best features are categorized using medium,bi-layer,and tri-layered neural *** the publicly accessible dataset known as the CASIA-B dataset,the experimental process of the suggested technique was carried out,and an improved accuracy of 94.14% was *** achieved accuracy of the proposed method is improved by the recent state-of-the-art techniques that show the significance of this wor

关键词： Gait recognition covariant factors biometric deep learning fusion feature selection

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Deep Convolutional Neural Networks for Accurate Classification of Gastrointestinal Tract Syndromes

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Computers, Materials & Continua 2024年第1期78卷 1207-1225页

作者： Zahid Farooq Khan Muhammad Ramzan Mudassar Raza Muhammad Attique Khan Khalid Iqbal Taerang Kim Jae-Hyuk cha Department of Computer Science COMSATS University IslamabadWah CampusWah47040Pakistan Department of Computer Science and Mathematics Lebanese American UniversityBeirut13-5053Lebanon Department of Computer Science HITEC UniversityTaxila47080Pakistan Department of Computer Science COMSATS University IslamabadAttock CampusAttock43600Pakistan Department of Computer Science Hanyang UniversitySeoul04763Korea

Accurate detection and classification of artifacts within the gastrointestinal(GI)tract frames remain a significant challenge in medical image *** science combined with artificial intelligence is advancing to automate the diagnosis and treatment of numerous *** to this is the development of robust algorithms for image classification and detection,crucial in designing sophisticated systems for diagnosis and *** study makes a small contribution to endoscopic image *** proposed approach involves multiple operations,including extracting deep features from endoscopy images using pre-trained neural networks such as Darknet-53 and ***,feature optimization utilizes the binary dragonfly algorithm(BDA),with the fusion of the obtained feature *** fused feature set is input into the ensemble subspace k nearest neighbors(ESKNN)*** Kvasir-V2 benchmark dataset,and the COMSATS University Islamabad(CUI)Wah private dataset,featuring three classes of endoscopic stomach images were *** assessments considered various feature selection techniques,including genetic algorithm(GA),particle swarm optimization(PSO),salp swarm algorithm(SSA),sine cosine algorithm(SCA),and grey wolf optimizer(GWO).The proposed model excels,achieving an overall classification accuracy of 98.25% on the Kvasir-V2 benchmark and 99.90% on the CUI Wah private *** approach holds promise for developing an automated computer-aided system for classifying GI tract syndromes through endoscopy images.

关键词： Feature fusion Darknet-53 Xception binary dragonfly algorithm ensemble

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Enhancement of vertical phase separation in sequentially deposited organic photovoltaics through the independent processing of additives

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Journal of Energy Chemistry 2024年第7期94卷 768-777页

作者： Damin Lee changwoo Park Gayoung Ham Young Yong Kim Sung-Nam Kwon Junyeong Lee Sungjin Jo Seok-In Na Hyojung cha Department of Hydrogen and Renewable Energy Kyungpook National UniversityDaegu 41566Republic of Korea Department of Energy Convergence and Climate change Kyungpook National UniversityDaegu 41566Republic of Korea Pohang Accelerator Laboratory(PAL) Pohang University of Science and Technology(POSTECH)PohangGyeongbuk 37673Republic of Korea Department of Flexible and Printable Electronics Jeonbuk National UniversityJeonju-siJeollabuk-do 54896Republic of Korea School of Energy Engineering Kyungpook National UniversityDaegu 41566Republic of Korea

Herein,the impact of the independent control of processing additives on vertical phase separation in sequentially deposited (SD) organic photovoltaics (OPVs) and its subsequent effects on charge carrier kinetics at the electron donor-acceptor interface are *** film morphology exhibits notable variations,significantly depending on the layer to which 1,8-diiodooctane (DIO) was *** incidence wide-angle X-ray scattering analysis reveals distinctly separated donor/acceptor phases and vertical crystallinity details in SD ***-of-flight secondary ion mass spectrometry analysis is employed to obtain component distributions in diverse vertical phase structures of SD films depending on additive *** addition,nanosecond transient absorption spectroscopy shows that DIO control significantly affects the dynamics of separated charges in SD *** SD OPVs,DIO appears to act through distinct mechanisms with minimal restriction,depending on the applied *** study emphasizes the significance of morphological optimization in improving device performance and underscores the importance of independent additive control in the advancement of OPV technology.

关键词： Sequential deposition Vertical phase separation charge dynamics Organic photovoltaics Nonfullerene acceptors

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Solar Driven 15.7% Hydrogen Conversion by Harmony of Light Harvesting,Electron Transporting Bridge,and S-Defection in a Self-Assembled Microscale CuS/rGO/CP Photoanode

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Energy & Environmental Materials 2024年第3期7卷 190-201页

作者： Sujeong Kim Boseok Seo Hyerim Park Younghwan im Jeong Yeon Do Byung Sub Kwak Namgyu Son Minkyu Kim Misook Kang Department of Chemistry College of Natural SciencesYeungnam UniversityGyeongsan Gyeongbuk 38541Korea School of Chemical Engineering Yeungnam UniversityGyeongsan Gyeongbuk 38541Korea Department of Energy and Hydrocarbon Chemistry Graduate School of EngineeringKyoto UniversityKyoto 615-8510Japan Korea Evaluation Institute of Industrial Technology(Keit) Cheomdan-Ro 8-GilDong-GuDaegu 41069Korea Korea Electric Power Research Institute(KEPRI)105 Munji-ro Yooseong-guDaejeon 34056Korea

CuS is an encouraging photoelectrode candidate that meets the essential requirements for efficient solar-to-hydrogen production,but it has not been thoroughly studied.A CuS light absorber layer is grown by the self-assembly of copper and sulfur precursors on a carbon paper(CP)***,rGO is introduced as a buffer layer to control the optical and electrical properties of the *** well-ordered microstructural arrangement suppresses the recombination loss of electrons and holes owing to enhanced charge-carrier generation,separation,and *** potential reaching 10 mA cm^(-2)in 1.0 M KOH solution is significantly lowered to 0.87 V,and the photocurrent density at 1.23 V is 94.7 mA cm^(-2).The computational result reveals that the potential-determining step is sensitive to O^(*)stability;the lower stability of O^(*)in the thin layer of CuS/rGO decreases the free-energy gap between the initial and final states of the potential-determining step,resulting in a lowering of the onset *** faradaic efficiency for the photoelectrochemical oxygen evolution reaction in the optimized 2CuS/1rGO/CP photoanode is 98.60%,and the applied bias photon-to-current and the solar-to-hydrogen efficiencies are 11.2%and 15.7%,respectively,and its ultra-high performance is maintained for 250 *** record-breaking achievement indices may be a trigger for establishing a green hydrogen economy.

关键词： 15.7%-solar to hydrogen density functional theory lower photopotential p-CuS/rGO/CP photoanode photoelectrochemical oxygen evolution

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An Artificial Intelligence-Based Framework for Fruits Disease Recognition Using Deep Learning

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Computer Systems Science & Engineering 2024年第2期48卷 529-554页

作者： Irfan Haider Muhammad Attique Khan Muhammad Nazir Taerang Kim Jae-Hyuk cha Department of Computer Science HITEC UniversityTaxila47080Pakistan Department of Computer Science Hanyang UniversitySeoulKorea

Fruit infections have an impact on both the yield and the quality of the *** a result,an automated recognition system for fruit leaf diseases is *** artificial intelligence(AI)applications,especially in agriculture,deep learning shows promising disease detection and classification *** recent AI-based techniques have a few challenges for fruit disease recognition,such as low-resolution images,small datasets for learning models,and irrelevant feature *** work proposed a new fruit leaf leaf leaf disease recognition framework using deep learning features and improved pathfinder *** fruit types have been employed in this work for the validation process,such as apple,grape,and *** the first step,a noisy dataset is prepared by employing the original images to learn the designed framework *** EfficientNet-B0 deep model is fine-tuned on the next step and trained separately on the original and noisy *** that,features are fused using a serial concatenation approach that is later optimized in the next step using an improved Path Finder Algorithm(PFA).This algorithm aims to select the best features based on the fitness score and ignore redundant *** selected features are finally classified using machine learning classifiers such as Medium Neural Network,Wide Neural Network,and Support Vector *** experimental process was conducted on each fruit dataset separately and obtained an accuracy of 100%,99.7%,99.7%,and 93.4%for apple,grape,Citrus fruit,and citrus plant leaves,respectively.A detailed analysis is conducted and also compared with the recent techniques,and the proposed framework shows improved accuracy.

关键词： Fruit disease contrast enhancement augmentation deep learning fusion feature selection classification

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Network Traffic Synthesis and Simulation Framework for Cybersecurity Exercise Systems

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Computers, Materials & Continua 2024年第9期80卷 3637-3653页

作者： Dong-Wook Kim Gun-Yoon Sin Kwangsoo Kim Jaesik Kang Sun-Young im Myung-Mook Han Department of AI Software Gachon UniversitySeongnam-Si13120Republic of Korea School of Computer Engineering&Applied Mathematics Hankyong National UniversityPyeongtaek-Si17738Republic of Korea Cyber ElectronicWarfare Research and Development LIG Nex1Seongnam-Si13488Republic of Korea

In the rapidly evolving field of cybersecurity,the challenge of providing realistic exercise scenarios that accurately mimic real-world threats has become increasingly *** methods often fall short in capturing the dynamic and complex nature of modern cyber *** address this gap,we propose a comprehensive framework designed to create authentic network environments tailored for cybersecurity exercise *** framework leverages advanced simulation techniques to generate scenarios that mirror actual network conditions faced by professionals in the *** cornerstone of our approach is the use of a conditional tabular generative adversarial network(CTGAN),a sophisticated tool that synthesizes realistic synthetic network traffic by learning fromreal data *** technology allows us to handle technical components and sensitive information with high fidelity,ensuring that the synthetic data maintains statistical characteristics similar to those observed in real network *** meticulously analyzing the data collected from various network layers and translating these into structured tabular formats,our framework can generate network traffic that closely resembles that found in actual *** integral part of our process involves deploying this synthetic data within a simulated network environment,structured on software-defined networking(SDN)principles,to test and refine the traffic *** simulation not only facilitates a direct comparison between the synthetic and real traffic but also enables us to identify discrepancies and refine the accuracy of our *** initial findings indicate an error rate of approximately 29.28%between the synthetic and real traffic data,highlighting areas for further improvement and *** providing a diverse array of network scenarios through our framework,we aim to enhance the exercise systems used by cybersecurity *** not only improves their ability to r

关键词： Cybersecurity exercise synthetic network traffic generative adversarial network traffic generation software-defined networking

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Biomimetic Fe_(7)S_(8)/Carbon electrocatalyst from[FeFe]-Hydrogenase for improving pH-Universal electrocatalytic hydrogen production Special Collection:Aggregation-Induced Processes and Functions

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Aggregate 2024年第1期5卷 451-459页

作者： Dohun Kim Subramani Surendran Sejin im Jaehyoung Lim Kyoungsuk Jin Ki Tae Nam Uk Sim Department of Energy Science&Engineering Daegu Gyeongbuk Institute of Science&Technology(DGIST)DaeguRepublic of Korea Hydrogen Energy Technology Laboratory Korea Institute of Energy Technology(KENTECH)NajuRepublic of Korea Department of Chemistry Korea UniversitySeoulRepublic of Korea Department of Materials Science and Engineering Seoul National UniversitySeoulRepublic of Korea

Efficient and cost-effective electrocatalysts that can operate across a wide range of pH conditions are essential for green hydrogen *** by biological systems,Fe_(7)S_(8)nanoparticles incorporated on polydopamine matrix electrocatalyst were synthesized by co-precipitation and annealing *** resulting Fe_(7)S_(8)/C electrocatalyst possesses a three-dimensional structure and exhibits enhanced electrocatalytic performance for hydrogen production across various pH ***,the Fe_(7)S_(8)/C electrocatalyst demonstrates exceptional activity,achieving low overpotentials of 90.6,45.9,and 107.4 mV in acidic,neutral,and alkaline environments,*** impedance spectroscopy reveals that Fe_(7)S_(8)/C exhibits the lowest charge transfer resistance under neutral conditions,indicating an improved proton-coupled electron transfer ***-wave electron paramagnetic resonance results confirm a change in the valence state of Fe from 3+to 1+during the hydrogen evolution reaction(HER).These findings closely resemble the behavior of natural[FeFe]-hydrogenase,known for its superior hydrogen production in neutral *** remarkable performance of our Fe_(7)S_(8)/C electrocatalyst opens up new possibilities for utilizing bioinspired materials as catalysts for the HER.

关键词： biomimetic electrocatalyst hydrogen production renewable energy

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Two distinct subpopulations of marginal zone B cells exhibit differential antibody-producing capacities and radioresistance

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Cellular & Molecular immunology 2024年第4期21卷 393-408页

作者： Sujin Lee Yeunjung Ko Hyun Woo Lee Won Joon Oh Hun Gi Hong Dinuka Ariyaratne Se Jin im Tae Jin Kim Department of immunology Graduate School of Basic Medical ScienceSungkyunkwan University School of MedicineSuwon16419Republic of Korea Department of immunology and Molecular Medicine Faculty of Medical SciencesUniversity of Sri JayewardenepuraNugegodaSri Lanka Present address:immunology and Microbiology Graduate Program Baylor College of MedicineHoustonTX77030USA

Marginal zone(MZ)B cells,which are splenic innate-like B cells that rapidly secrete antibodies(Abs)against blood-borne pathogens,are composed of heterogeneous ***,we showed that MZ B cells can be divided into two distinct subpopulations according to their CD80 expression ***80^(high)MZ B cells exhibited greater Ab-producing,proliferative,and IL-10-secreting capacities than did CD80^(low)MZ B ***,CD80^(high)MZ B cells survived 2-Gy whole-body irradiation,whereas CD80^(low)MZ B cells were depleted by irradiation and then repleted with one month after *** of CD80^(low)MZ B cells led to accelerated development of type II collagen(CII)-induced arthritis upon immunization with bovine ***80^(high)MZ B cells exhibited higher expression of genes involved in proliferation,plasma cell differentiation,and the antioxidant ***80^(high)MZ B cells expressed more autoreactive B cell receptors(BCRs)that recognized double-stranded DNA or CII,expressed more immunoglobulin heavy chain sequences with shorter complementarity-determining region 3 sequences,and included more clonotypes with no N-nucleotides or with B-1a BCR sequences than CD80^(low)MZ B *** transfer experiments showed that CD21^(+)CD23^(+)transitional 2 MZ precursors preferentially generated CD80^(low)MZ B cells and that a proportion of CD80^(low)MZ B cells were converted into CD80^(high)MZ B cells;in contrast,CD80^(high)MZ B cells stably remained CD80^(high)MZ B *** summary,MZ B cells can be divided into two subpopulations according to their CD80 expression levels,Ab-producing capacity,radioresistance,and autoreactivity,and these findings may suggest a hierarchical composition of MZ B cells with differential stability and BCR specificity.

关键词： Marginal Zone B Cell CD80 Autoreactivity Radioresistance

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TRAIL and Celastrol Combinational Treatment Suppresses Proliferation, Migration, and Invasion of Human Glioblastoma Cells via Targeting Wnt/β-catenin Signaling Pathway

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Chinese Journal of Integrative Medicine 2024年第4期30卷 322-329页

作者： QIN Jing-jing NIU Meng-da cha Zhe GENG Qing-hua LI Yu-lin REN Chun-guang David P.Molloy YU Hua-rong Research Center of Neuroscience School of Basic Medical SciencesChongqing Medical UniversityChongqing(400016)China Laboratory of Developmental Biology Department of Cell Biology and GeneticsSchool of Basic Medical SciencesChongqing Medical UniversityChongqing(400016)China Department of Biochemistry and Molecular Biology School of Basic Medical SciencesChongqing Medical UniversityChongqing(400016)China

Objective To investigate the mechanistic basis for the anti-proliferation and anti-invasion effect of tumor necrosis factor-related apoptosis-induced ligand(TRAIL)and celastrol combination treatment(TCCT)in glioblastoma *** Cell counting kit-8 was used to detect the effects of different concentrations of celastrol(0-16µmol/L)and TRAIL(0-500 ng/mL)on the cell viability of glioblastoma cells.U87 cells were randomly divided into 4 groups,namely control,TRAIL(TRAIL 100 ng/mL),Cel(celastrol 0.5µmol/L)and TCCT(TRAIL 100 ng/mL+celastrol 0.5µmol/L).Cell proliferation,migration,and invasion were detected by colony formation,wound healing,and Transwell assays,*** reverse transcription polymerase chain reaction and Western blotting were performed to assess the levels of epithelial-mesenchymal transition(EMT)markers(zona occludens,N-cadherin,vimentin,zinc finger E-box-binding homeobox,Slug,and β-catenin).Wnt pathway was activated by lithium chloride(LiCl,20 mol/L)and the mechanism for action of TCCT was *** Celastrol and TRAIL synergistically inhibited the proliferation,migration,invasion,and EMT of U87 cells(Pchanism of action for TCCT as an effective therapy for glioblastoma.

关键词： celastrol Chinese medicine tumor necrosis factor-related apoptosis-induced ligand glioblastoma β-catenin Tripterygium wilfordii

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Des-Arg(9)bradykinin as a causal metabolite for autism spectrum disorder

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World Journal of Psychiatry 2024年第1期14卷 88-101页

作者： Zhong-Yu Huang Zi-Pan Lyu Hong-Gui Li Hua-Zhi You Xiang-Na Yang Cai-Hui cha Center for Medical Research on Innovation and Translation Institute of Clinical MedicineGuangzhou First People’s HospitalSchool of MedicineSouth China University of TechnologyGuangzhou 510000Guangdong ProvinceChina School of Biological Sciences Nanyang Technological UniversityNanyang Ave 639798Singapore Department of Pediatrics First Affiliated Hospital of Guangzhou University of Chinese MedicineGuangzhou 510405Guangdong ProvinceChina Department of Nutrition First Affiliated Hospital of Guangzhou University of Chinese MedicineGuangzhou 510405Guangdong ProvinceChina Department of Pediatric Traditional Chinese Medicine Clinic Guangzhou Women and Children's Medical CenterGuangzhou 510632Guangdong ProvinceChina Department of Psychology Guangzhou Women and Children's Medical CenterGuangzhou 510632Guangdong ProvinceChina

BACKGROUND Early diagnosis and therapeutic interventions can greatly enhance the developmental trajectory of children with autism spectrum disorder(ASD).However,the etiology of ASD is not completely *** presence of confounding factors from environment and genetics has increased the difficulty of the identification of diagnostic biomarkers for *** To estimate and interpret the causal relationship between ASD and metabolite profile,taking into consideration both genetic and environmental *** A two-sample Mendelian randomization(MR)analysis was conducted using summarized data from large-scale genome-wide association studies(GWAS)including a metabolite GWAS dataset covering 453 metabolites from 7824 European and an ASD GWAS dataset comprising 18381 ASD cases and 27969 healthy *** in plasma were set as exposures with ASD as the main *** causal relationships were estimated using the inverse variant weight(IVW)*** also performed leave-one-out sensitivity tests to validate the robustness of the *** on the drafted metabolites,enrichment analysis was conducted to interpret the association via constructing a protein-protein interaction network with multi-scale evidence from databases including Infinome,SwissTargetPrediction,STRING,and *** Des-Arg(9)-bradykinin was identified as a causal metabolite that increases the risk of ASD(β=0.262,SE=0.064,P_(IVW)=4.64×10^(-5)).The association was robust,with no significant heterogeneity among instrument variables(P_(MR Egger)=0.663,P_(IVW)=0.906)and no evidence of pleiotropy(P=0.949).Neuroinflammation and the response to stimulus were suggested as potential biological processes mediating the association between Des-Arg(9)bradykinin and *** Through the application of MR,this study provides practical insights into the potential causal association between plasma metabolites and *** findings offer perspectives for the discovery of diagnos

关键词： Des-Arg(9)bradykinin Autism spectrum disorder Mendelian randomization Metabolite Enrichment analysis

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