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11th International Conference on Computer, Control, Informatics and its Applications, IC3INA 2024

作者： Setiawan, Foni Agus Rohmah, Zakiah Aulia Laxmi, Gibtha Fitri Research Center for Data and Information Science National Research and Innovation Agency Bandung Indonesia Informatics Engineering Universitas Ibn Khaldun Bogor Indonesia

ISBN: (纸本)9798331542313

People with disabilities have increased over the past few years in Indonesia. data from the Central Bureau of Statistics, Republic of Indonesia shows that the number of people with disabilities reached 212,240 in 2022 and specifically deaf people reached 19,392. This shows the need for attention to people with disabilities, especially the deaf and hard of hearing. This research aims to develop an Indonesian Sign Language (BISINDO) alphabet detection model using the You Only Look Once (YOLO) v8 algorithm. The resulting model is expected to help people in understanding sign language, thus expanding accessibility for people with disabilities. The model was trained using 2.759 images and 30 videos. The results show that the model can identify 26 letters in BISINDO alphabet including letters with motion (G, J and R) with an accuracy rate of 99%, a precision value of 99.4%, recall 98.4% and F1-score reached 98.9%. These values indicated that the model works well in predicting the BISINDO alphabet. The model built using this YOLOv8 produces sign language gesture conversion output into text, which can then be assembled into words, thus facilitating communication with deaf and hard of hearing people. © 2024 IEEE.

关键词： Disabled persons

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Universal machine learning potential accelerates atomistic modeling of materials

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Journal of Energy Chemistry 2023年第8期83卷 1-2,I0002页

作者： Zhongheng Fu Dawei Zhang Beijing Advanced Innovation Center for Materials Genome Engineering Institute for Advanced Materials and TechnologyUniversity of Science and Technology Beijing.Beijing 100083China National Materials Corrosion and Protection Data Center University of Science and Technology BeijingBeijing 100083China

With the rapid development of computer techniques,atomistic modeling is playing an increasingly important role in understanding the structure-activity relationship of *** dynamics (MD) is a computational simulation approach to predicting the structural evolution of an atomic system over time,widely used to understand physical and chemical phenomena including phase transition,diffusion,crystallization,and reaction [1].

关键词： Machinelearning Atomisticmodeling Neural networkpotential Solid-statematerials

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Using analytic hierarchy process to evaluate deep learning for infrared target recognition

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Multimedia Tools and Applications 2024年第38期83卷 86229-86245页

作者： Xu, Laixiang Cao, Bingxu Wei, Xinhong Li, Bei Su, Jingfeng Ning, Shiyuan Zhao, Junmin School of Computer and Data Science Henan University of Urban Construction Pingdingshan467036 China School of Information Engineering Luohe Vocational Technology College Henan University of Technology Luohe Institute of Technology Luohe462000 China School of Computer and Data Science Innovation Laboratory of Smart Traffic and Big Data Development of Hainan Province Pingdingshan467036 China School of Computer and Data Science Research Center of Smart City and Big Data Engineering of Henan Province Henan University of Urban Construction Pingdingshan467036 China Department of Software Information China Electronics Technology Group Corporation 36-th Research Institute Jiaxing314033 China School of Computer and Data Science Research Center of Smart City and Big Data Engineering of Henan Province Research Center of Intelligent Campus Application Engineering of Henan Province Innovation Laboratory of Smart Traffic and Big Data Development of Hainan Province Henan University of Urban Construction Pingdingshan467036 China

In order to promote the evaluation performance of deep learning infrared automatic target recognition (ATR) algorithms in the complex environment of air-to-air missile research, we proposed an analytic hierarchy process (AHP) evaluation system consisting of the target recognition ability, the generalization recognition ability, the anti-interference ability, the background suppression ability, and the cost metrics ability. According to detailed quantitative analysis and experimental results, we establish probability evaluation models and get their probability values. Compared with traditional evaluation systems, our proposed method implementation is showing high reliability. Similar superior performances are also achieved, such as quick, comprehensive, and scientific. Through the above research, the key technology of deep learning performance evaluation in automatic target recognition has been broken through, which provides some basis and guidance for the analysis of infrared imaging-guided weapon systems. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Infrared imaging

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Local and Global Feature-Aware Dual-Branch Networks for Plant Disease Recognition

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植物表型组学（英文） 2024年第4期6卷 828-840页

作者： Jianwu Lin Xin Zhang Yongbin Qin Shengxian Yang Xingtian Wen Tomislav Cernava Quirico Migheli Xiaoyulong Chen Text Computing & Cognitive Intelligence Engineering Research Center of National Education Ministry College of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China College of Big Data and Information Engineering Guizhou UniversityGuiyang 550025China Guizhou-Europe Environmental Biotechnology and Agricultural Informatics Oversea Innovation Center in Guizhou University Guizhou Provincial Science and Technology DepartmentGuiyang 550025China Text Computing & Cognitive Intelligence Engineering Research Center of National Education Ministry College of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China College of Big Data and Information Engineering Guizhou UniversityGuiyang 550025China Guizhou-Europe Environmental Biotechnology and Agricultural Informatics Oversea Innovation Center in Guizhou University Guizhou Provincial Science and Technology DepartmentGuiyang 550025China College of Big Data and Information Engineering Guizhou UniversityGuiyang 550025China School of Biological Sciences Faculty of Environmental and Life SciencesUniversity of SouthamptonSouthampton S017 1BJUK Dipartimento di Agraria and NRD-Nucleo di Ricerca sulla Desertificazione Università degli Studi di SassariSassariItaly Guizhou-Europe Environmental Biotechnology and Agricultural Informatics Oversea Innovation Center in Guizhou University Guizhou Provincial Science and Technology DepartmentGuiyang 550025China College of Life Sciences Guizhou UniversityGuiyang 550025China

Accurate identification of plant diseases is important for ensuring the safety of agricultural *** neural networks(CNNs)and visual transformers(VTs)can extract effective representations of images and have been widely used for the intelligent recognition of plant disease ***,CNNs have excellent local perception with poor global perception,and VTs have excellent global perception with poor local *** makes it difficult to further improve the performance of both CNNs and VTs on plant disease recognition *** this paper,we propose a local and global feature-aware dual-branch network,named LGNet,for the identification of plant *** specifically,we first design a dual-branch structure based on CNNs and VTs to extract the local and global ***,an adaptive feature fusion(AFF)module is designed to fuse the local and global features,thus driving the model to dynamically perceive the weights of different ***,we design a hierarchical mixed-scale unit-guided feature fusion(HMUFF)module to mine the key information in the features at different levels and fuse the differentiated information among them,thereby enhancing the model's multiscale perception ***,extensive experiments were conducted on the Al Challenger 2018 dataset and the self-collected corn disease(SCD)*** experimental results demonstrate that our proposed LGNet achieves state-of-the-art recognition performance on both the Al Challenger 2018 dataset and the SCD dataset,with accuracies of 88.74％and 99.08％,respectively.

关键词： global plant disease dual-branch feature-aware local networks recognition

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Distributed Truss Computation in Dynamic Graphs

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Tsinghua science and Technology 2023年第5期28卷 873-887页

作者： Ziwei Mo Qi Luo Dongxiao Yu Hao Sheng Jiguo Yu Xiuzhen Cheng School of Computer Science and Technology Shandong UniversityQingdao 266200China State Key Laboratory of Software Development Environment School of Computer Science and Engineering and the Beijing Advanced Innovation Center for Big Data and Brain ComputingBeihang UniversityBeijing 100191China Big Data Institute Qilu University of Technology(Shandong Academy of Sciences)Jinan 250353China

Large-scale graphs usually exhibit global sparsity with local cohesiveness,and mining the representative cohesive subgraphs is a fundamental problem in graph *** k-truss is one of the most commonly studied cohesive subgraphs,in which each edge is formed in at least k 2 triangles.A critical issue in mining a k-truss lies in the computation of the trussness of each edge,which is the maximum value of k that an edge can be in a *** works mostly focus on truss computation in static graphs by sequential ***,the graphs are constantly changing dynamically in the real *** study distributed truss computation in dynamic graphs in this *** particular,we compute the trussness of edges based on the local nature of the k-truss in a synchronized node-centric distributed *** decomposing the trussness of edges by relying only on local topological information is possible with the proposed distributed decomposition ***,the distributed maintenance algorithm only needs to update a small amount of dynamic information to complete the *** experiments have been conducted to show the scalability and efficiency of the proposed algorithm.

关键词： distributed algorithm dynamic graph graph mining cohesive subgraph k-truss

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Stability of connected and automated vehicles platoon considering communications failures

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Chinese Physics B 2023年第7期32卷 598-609页

作者：刘润坤于海洋任毅龙崔志勇 School of Transportation Science and Engineering Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety ControlBeihang UniversityBeijing 100191China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang UniversityBeijing 100191China

As a form of a future traffic system,a connected and automated vehicle(CAV)platoon is a typical nonlinear physical *** can communicate with each other and exchange ***,communication failures can change the platoon system *** characterize this change,a dynamic topology-based car-following model and its generalized form are proposed in this ***,a stability analysis method is ***,taking the dynamic cooperative intelligent driver model(DC-IDM)for example,a series of numerical simulations is conducted to analyze the platoon stability in different communication topology *** results show that the communication failures reduce the stability,but information from vehicles that are farther ahead and the use of a larger desired time headway can improve ***,the critical ratio of communication failures required to ensure stability for different driving parameters is studied in this work.

关键词： connected and automated vehicle car-following model communication failures string stability

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Pan-media liquid metal 3D printing

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The innovation 2025年第4期6卷 7-8页

作者： Xiaohui Shan Weichen Feng Minghui Guo Xuelin Wang Jing Liu School of Biomedical Engineering Tsinghua UniversityBeijing 100084China Key Laboratory of Cryogenic Science and Technology Technical Institute of Physics and ChemistryChinese Academy of SciencesBeijing 100190China Beijing Advanced Innovation Center for Biomedical Engineering Beijing Advanced Innovation Center for Big Data-Based Precision MedicineSchool of Engineering MedicineBeihang UniversityBeijing 100191China

INTRODUCTION The manufacturing industry has evolved from traditional forging and cutting to three-dimensional(3D)printing,a revolutionary technology that expands human imagination by creating everything of complex shapes and intricate structures,making it a cornerstone of smart manufacturing.1 However,conventional fabrications may encounter bottlenecks that seriously restrict their printing across different inks,ambient,and *** existing 3D printing methods to produce target functional components on diverse working media,therefore,requires significant *** highly adaptable 3D printing inks,liquid metals(LMs)open large spaces to address such challenges due to their versatile capabilities,such as fluidities,conductivities,easy solid-liquid transitions,and *** continuous efforts are being increasingly made in LM printing in different media,2 there is still no generalized methodology or concept proposed to unite all LM 3D printing techniques,inks,and media *** achieve this intriguing target,here we present a unified 3D printing concept,termed pan-media liquid metal 3D printing,to manufacture customized end-user devices as ***-media 3D printing means that it is able to administrate printing with any ink and any working ambient,from gases and liquids to soft matters,bio-tissues,and rigid media,transcending the boundaries of traditional printing ***,with intentionally introduced physical or chemical processing between LM inks and ambient,pan-media LM 3D printing could achieve a much wider variety of 3D object and targeted functions over existing *** synthesizing the pan-media theory of LM 3D printing,we prospect a pan-media manufacturing center equipped with functional ink storage,media library,printing head system,and control units,all integrated to fully address the desired printing tasks.

关键词： expands human imagination Liquid metals creating everything complex shapes intricate forging cutting smart manufacturing d printing produce target functional com D printing

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Model Based Quadriceps Activation Strategy in Squat Training with Exhaustion Method Under Different Loads 8

Model Based Quadriceps Activation Strategy in Squat Training...

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8th International Symposium on Computer science and Intelligent Control, ISCSIC 2024

作者： Xie, Cong Guo, Xin Qie, Botao Hebei University of Technology Control Engineering Technology Innovation Center of Hebei Province Hebei University of Technology School of Artificial Intelligence and Data Science Tianjin China

ISBN: (纸本)9798350380286

The aim of this study is to explore the muscle activation strategy of quadriceps muscle training in untrained sedentary people under different resistance training to exhaustion to provide control target for body state-based intelligence exercise equipment. Ten daily sedentary men with no training experience performed three sets of heavy load squats (single leg bench squat) in exhaustion mode (4RM) and one set of lower resistance squats (double leg squat with 10 KG garment) in exhaustion mode (18-26RM) to explore which and when the muscle fibers will be recruited as much as more. EMG signals from the dominant side of the vastus medialis), rectus femoris, and vastus lateralis in both squats were recorded, and the maximum RMS of 500 MS length in each movement was normalized to the maximum voluntary isometric contraction. Reliability analysis of the normalized EMG signal for each muscle between the three groups of heavy-load squats was as follows: Alpha (vastus medialis)= 0.885, Alpha (rectus femoris)=0.903, Alpha (vastus lateralis) = 0.925. Paired samples t-test of the three muscles under different resistance:p (vastus medialis) © 2024 IEEE.

关键词： Exercise equipment

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Asymmetric scattering behaviors of spin wave dependent on magnetic vortex chirality

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Chinese Physics B 2023年第10期32卷 635-640页

作者：张雪枫沈帝虎马晓萍宋成于海明朴红光 Hubei Engineering Research Center of Weak Magnetic-Field Detection China Three Gorges UniversityYichang 443002China Department of Physics College of ScienceYanbian UniversityYanji 133002China Key Laboratory of Advanced Materials(MOE) School of Materials Science and EngineeringTsinghua UniversityBeijing 100084China Fert Beijing Institute School of Integrated Circuit Science and EngineeringBeijing Advanced Innovation Center for Big Data and Brain ComputingBeihang UniversityBeijing 100191China

We investigate asymmetric spin wave scattering behaviors caused by vortex chirality in a cross-shaped ferromagnetic system by using the micromagnetic *** the system,four scattering behaviors are found:(i)asymmetric skew scattering,depending on the polarity of vortex core,(ii)back scattering(reflection),depending on the vortex core stiffness,(iii)side deflection scattering,depending on structural symmetry of the vortex circulation,and(iv)geometrical scattering,depending on waveguide *** first and second scattering behaviors are attributed to nonlinear topological magnon spin Hall effect related to magnon spin-transfer torque effect,which has value for magnonic exploration and application.

关键词： magnonics magnetic vortex spin wave magnetic chirality

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The Digital Twin City in Enhancing Flood Evacuation Systems: Future Opportunities and Challenges

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IEEE Access 2025年 13卷 32371-32383页

作者： Setijadi Prihatmanto, Ary Prasetyadi, Abdurrakhman Yoganingrum, Ambar Sutriadi, Ridwan Hadiana, Ana Bandung Institute of Technology School of Electrical and Informatics Engineering Bandung40132 Indonesia National Research and Innovation Agency Research Center for Data and Information Science Bandung40231 Indonesia Bandung Institute of Technology School of Architecture Planning and Policy Development Bandung40132 Indonesia

In recent decades, the increasing frequency and severity of natural disasters have necessitated the development of more effective disaster management systems. This paper explores the potential of digital twin technology to enhance flood evacuation systems. A digital twin-city model can simulate urban environments, predict flood inundation, and identify optimal evacuation routes in real-time. The study conducts a systematic literature review to assess current advancements, evaluating the integration of 3D city models, artificial intelligence, and Internet of things sensors in flood evacuation planning. Results indicate that digital twin technology significantly improves predictive capabilities and evacuation efficiency, although data integration, model accuracy, and computational demands remain. Future research should focus on enhancing data integration, refining simulation models, improving predictive analytics, developing advanced visualization tools, and validating models across diverse environments to ensure reliability and effectiveness. © 2025 The Authors.

关键词： Digital elevation model

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