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2nd International Conference on Augmented Intelligence and Sustainable Systems, ICAISS 2023

作者： Dutta, Chiranjit Maheswari, M. Saravanan, K.G. Dhaliwal, Navdeep Pandey, Akhilesh Sophia, S. Srm Institute of Science and Technology Department of Computer Science and Engineering Uttar Pradesh Ghaziabad India Dmi College of Engineering Department of Information Technology Tamil Nadu Chennai India Sona College of Technology Department of Mechanical Engineering Tamil Nadu Salem India Lovely Professional University Division of Research and Development Punjab Phagwara India Uttaranchal University Division of Research and Innovation Uttarakhand Dehradun India Karunya Institute of Technology and Sciences Department of Computer Science and Engineering Tamil Nadu Coimbatore India

ISBN: (纸本)9798350325799

The Cyber Physical System (CPS) is referred as the amalgamation of physical system with control system mechanisms. CPS is largely used in versatile process from automation, controlling and monitoring process. This is the process of converting the physical system into a digital platform through sensing, data storage and monitoring process. Due to the advancement in the Internet of Things (IoT), the cyber security has become a complex parameter. Thus they need to be considered. To overcome the constraints, the machine learning is implemented to provide security concerns for the cyber physical systems. The machine learning provides a platform for the intrusion detection system. The machine learning helps in the classification and detection of the cyber-attacks. This is done through the optimization techniques, which helps to provide the solution for reducing the complexity. The internet of system paved way for the sensing, control, monitoring and communication of information. The attacks in the networking system are identified through the machine learning that enable smart applications in diverse fields. © 2023 IEEE.

关键词： Cyber Physical System

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Digital Twin of Cyber-Physical CNC for Smart Manufacturing

Digital Twin of Cyber-Physical CNC for Smart Manufacturing

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Bethanie Williams Gabriela Ciocarlie Kyle Saleeby Muhammad Ismail Clifton Mulkey Department of Computer Science Tennessee Technological University Tennessee USA Research Development and Engineering Cybersecurity Manufacturing Innovation Institute (CyManII) Texas USA Research and Development of Science and Engineering Sandia National Laboratories New Mexico USA

Due to the complexity of smart manufacturing systems, digital twins (DTs) can help manufacturers test and validate products as well as determine any process failures before production. Computer numerical control (CNC) machines are widely used and employed in several manufacturing industries because of their precision and efficiency. Despite the wide adoption of CNC machines, there is currently no CNC-based DT that simulates an entire production process. This paper demonstrates the implementation and validation of a DT that can 1) replicate the physical manufacturing operations of products on Tormach CNC machines by accurately generating the positional values of the machine’s tool path along the X, Y, and Z axes, 2) employ MTConnect’s communication protocol by utilizing an adapter and an agent that produces data such as timestamps, axis positions, and spindle speed into MTConnect’s standardized XML format, 3) deploy an MTConnect utility, dataminer, to collect data from the agent and properly store it into a JSON format for further analysis. For validation purposes, an example coin geometry was simulated on the DT and manufactured in aluminum on a real Tormach machine. A comparison between the simulated operations and real system was made to validate the accuracy of the DT. Dynamic time warping (DTW) was used to compare process data from the DT with data from the real machine. Our analysis shows that the DT and real system have a high correlation as the DTW warping path is closely aligned at a 45 degree angle line and has minimal time warping.

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An Innovative Method for Snatch Theft Detection Using Convolutional LSTM-Auto Encoder Approach

An Innovative Method for Snatch Theft Detection Using Convol...

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2023 International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023

作者： Konda Reddy, Gondi Reddy Esanakula, Jayakiran Prajna, K.B. Chandra Purohit, Kamlesh Kaliappan, S. Maranan, Ramya Sreenidhi Institute of Science and Technology Department of Mechanical Engineering Telangana Hyderabad India Nitte Meenakshi Institute of Technology Department of Electronics and Communication Karnataka Bengaluru India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun India Lovely Professional University Division of Research and Development Punjab Phagwara144411 India Saveetha School of Engineering Simats Department of Research and Innovation Tamil Nadu Chennai India

ISBN: (纸本)9798350300857

Urban areas frequently experience snatch stealing, a severe threat to public safety. It entails forcibly seizing a victim's personal items, including purses or cell phones, before scurrying away from the scene. Due to how quickly they happen, it is difficult to identify snatch theft instances in real-time. The systems now in use to identify the snatching occurrences mainly rely on human participation, which may result in lengthy delays and mistakes. Consequently, there is a need for an automated method that can quickly and effectively identify these situations. Preprocessing, segmentation, feature extraction, and model training are all used in the suggested method. Gaussian Model is utilized for preprocessing. Canny edge is utilized for segmentation. LSTM-AE is used to train the model. Two further models, LSTM and AE, are contrasted with the suggested method. When compared to two existing approaches, the proposed strategy performs exceptionally well. © 2023 IEEE.

关键词： Feature extraction

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Design of Highly Reliable Fault Backtracking Calculation for Space Applications 15

Design of Highly Reliable Fault Backtracking Calculation for...

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15th International Conference on Computer research and development, ICCRD 2023

作者： Yu, Jiyang Huang, Dan Li, Jinyang Li, Wenjie Wang, Xianjie Shi, Xiaolong China Academy of Space Technology Beijing Institute of Spacecraft System Engineering Beijing China China Research and Development Academy of Machinery Equipment Beijing Chongqing China Chongqing University of Technology Chongqing Beijing China Chongqing Feima Innovation Research Institute Intelligent Equipment Research Department Chongqing China College of Computer Science and Engineering Chongqing University of Technology Chongqing China

ISBN: (纸本)9781665487504

The design architecture of backtracking calculation control processing for space large manipulator control is proposed. SRAM-Type FPGA is used to build the hardware full three-mode computing core, and the processor architecture is designed based on FPGA. The register value and cache access value of the single instruction calculation process of the three computing processors are used to compare the three modes in the anti-fuse FPGA. At the same time, the results of three computing processors were compared by SPARC CPU. Fault backtracking calculation control, when a single computing module occurs an error, first detect the instruction execution position of the faulty module, and then carry out register-level data recovery for the faulty module, and restore to the instruction before the fault to accelerate the operation to complete the 'backtracking' process, until the other two modules complete the calculation synchronization. According to the theoretical derivation and analysis, it is clear that under the linear increasing detection window, the maximum time of fault recovery is only related to the three-mode ratio transmission rate. According to this conclusion, the hardware digital logic design of the key modules of fault detection and recovery is carried out. The overall structure is simple and easy to implement, digital logic only occupies less than 100,000 logic gates. Compared with traditional methods, the fault recovery efficiency is improved by at least 90%. © 2023 IEEE.

关键词： Field programmable gate arrays (FPGA)

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A Comprehensive Survey on Federated Learning Applications in Computational Mental Healthcare

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Computer Modeling in engineering & sciences 2025年第1期142卷 49-90页

作者： Vajratiya Vajrobol Geetika Jain Saxena Amit Pundir Sanjeev Singh Akshat Gaurav Savi Bansal Razaz Waheeb Attar Mosiur Rahman Brij B.Gupta Institute of Informatics and Communication University of DelhiDelhi110021India Maharaja Agrasen College University of DelhiDelhi110096India Computer Engineering Ronin InstituteMontclairNJ 07043USA Department of Research and Innovation Insights2TechinfoJaipur302001India University Centre for Research and Development(UCRD) Chandigarh UniversityChandigarh140413India Management Department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia CCRI&Department of Computer Science and Information Engineering Asia UniversityTaichung413Taiwan Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPune411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India

Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing *** aims to alleviate the workload on healthcare professionals and aid *** applications have been developed to support the challenges in intelligent healthcare ***,because mental health data is sensitive,privacy concerns have *** learning has gotten some *** research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare *** explores various dimensions of federated learning in mental health,such as datasets(their types and sources),applications categorized based on mental health symptoms,federated mental health frameworks,federated machine learning,federated deep learning,and the benefits of federated learning in mental health *** research conducts surveys to evaluate the current state of mental health applications,mainly focusing on the role of Federated Learning(FL)and related privacy and data security *** survey provides valuable insights into how these applications are emerging and evolving,specifically emphasizing FL’s impact.

关键词： Depression emotional recognition intelligent healthcare systems mental health federated learning stress detection sleep behaviour

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An adaptive representation model for geoscience knowledge graphs considering complex spatiotemporal features and relationships

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science China Earth sciences 2023年第11期66卷 2563-2578页

作者： Yunqiang ZHU Kai SUN Shu WANG Chenghu ZHOU Feng LU Hairong LV Qinjun QIU Xinbing WANG Yanmin QI State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing 210023China Department of Automation Tsinghua UniversityBeijing 100084China School of Computer Science China University of GeosciencesWuhan 430074China Department of Electronic Engineering Shanghai Jiao Tong UniversityShanghai 200240China School of Computer Science University of Nottingham Ningbo ChinaNingbo 315100China

Geoscience knowledge graph(GKG)can organize various geoscience knowledge into a machine understandable and computable semantic network and is an effective way to organize geoscience knowledge and provide knowledge-related *** a result,it has gained significant attention and become a frontier in *** knowledge is derived from many disciplines and has complex spatiotemporal features and relationships of multiple scales,granularities,and ***,establishing a GKG representation model conforming to the characteristics of geoscience knowledge is the basis and premise for the construction and application of ***,existing knowledge graph representation models leverage fixed tuples that are limited in fully representing complex spatiotemporal features and *** address this issue,this paper first systematically analyzes the categorization and spatiotemporal features and relationships of geoscience *** this basis,an adaptive representation model for GKG is proposed by considering the complex spatiotemporal features and *** the constraint of a unified spatiotemporal ontology,this model adopts different tuples to adaptively represent different types of geoscience knowledge according to their spatiotemporal *** model can efficiently represent geoscience knowledge,thereby avoiding the isolation of the spatiotemporal feature representation and improving the accuracy and efficiency of geoscience knowledge *** can further enable the alignment,transformation,computation,and reasoning of spatiotemporal information through a spatiotemporal ontology.

关键词： Geoscience Knowledge graph Representation model Spatiotemporal features Spatiotemporal relationships

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Wireless Technologies and Applications for Industrial Internet of Things: A Review 1st

Wireless Technologies and Applications for Industrial Intern...

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1st International Conference of Advanced Computing and Informatics, ICACIN 2020

作者： Bahri, Nisrine Saadaoui, Safa Tabaa, Mohamed Sadik, Mohamed Medromi, Hicham Foundation for Research Development and Innovation in Engineering Sciences Casablanca Morocco EMSI Casablanca Casablanca Morocco RTSE Research Team Laboratory of Research Engineering ENSEM Hassan II University Casablanca Morocco

ISBN: (纸本)9789811560477

Industrial automation has developed a lot thanks to the concept of IoT and this is the reason why many industries have been working on new emerging technologies to ensure the concept of connectivity, such as the most popular ones: Low-power wide-area networks (LPWANs) designed to solve many problems such as scalability and range encountered by traditional cellular networks and short-range communication technologies, in order to also address the application of IoTs in the industrial context. The objective of this document is to provide an overview in one of the main pillars of Industry 4.0, contextualizing the IoT in Industry 4.0, discussing the most relevant technologies in the IoT: wireless technologies highlighting the major differences between the two ecosystems IoT and IIoT based on their different criteria and applications, and then based on this projecting existing technologies to study the appropriate one, although these technologies have their own drawbacks in the external and industrial environment. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Internet of things

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Recognition of Hypertension Through Retinal Fundus Images by Segmentation of Blood Vasculature 2nd

Recognition of Hypertension Through Retinal Fundus Images by...

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Emergent Converging Technologies and Biomedical Systems Select Proceedings of the 2nd International Conference, ETBS 2022

作者： Kaur, Jaskirat Mittal, Deepti Singla, Parveen Kaur, Ramanpreet Tiwari, Sharad Kumar Sector 12 Chandigarh160012 India Electrical and Instrumentation Engineering Department Thapar Institute of Engineering and Technology Patiala147004 India Electronics and Communication Engineering Department Department of Research and Development Chandigarh Engineering College Mohali140307 India Electronics and Communication Engineering Department Chandigarh Engineering College Mohali140307 India Electronics and Communication Engineering Department Vignan Foundation for Science and Technology Vadlamudi India

ISBN: (纸本)9789819922703

Condition of high blood pressure is termed as hypertension. Hypertension also causes variations in the blood vessels of retina which forms as a base to identify hypertension at a very early stage. These variations occur as narrowing of arteries, bifurcation variations and may lead to torturous blood vessels. The present paper introduces an automated method of vessel segmentation based on top-hat filtering and slicing of bit-planes on which measurements like arteriovenular ratio (AVR), bifurcation points and tortuosity index are calculated. The performance of the designed retinal vasculature identification and detection of bifurcations are evaluated on two open-source datasets, namely: DRIVE and STARE. DRIVE dataset achieved the mean accuracy of 94.89% and STARE dataset achieved the mean accuracy of 94.56%. Arteriovenous ratio of the retinal vessels is computed on a standard dataset INSPIRE-AVR with the aid of two medical specialists. Specialist 1 reported the mean accuracy of 98.43 and specialist 2 reported the mean accuracy of 98.43%. Also, retinal vessels curve and tortuosity-based computations are made using the standard dataset, namely RETTORT dataset. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Blood vessels

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Electronegativity-assisted optimized electronic structure of functionalized-Pt catalysts for boosting oxygen reduction kinetics

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Rare Metals 2024年第5期43卷 1965-1976页

作者： Jin Long Kai-Wen Zhuang Wei Liao Yan An Bin Wang Chen-Zhong Wu Jian-Xin Cao Qing Wang Jun-Song Chen Qing-Mei Wang Guizhou University Key Laboratory of Green Chemical and Clean Energy Technology School of Chemistry and Chemical EngineeringGuizhou UniversityGuiyang 550025China Guizhou University Engineering Research Center of Effcient Utilization for Industrial Waste Guizhou UniversityGuiyang 550025China Institute of Dual-Carbon and New Energy Technology Innovation and Development of Guizhou Province Guiyang 550025China Department of Dermatology West China HospitalSichuan UniversityChengdu610041China Institute for Catalysis Hokkaido UniversitySapporo 001-0021Japan School of Materials and Energy University of Electronic Science and Technology of ChinaChengdu 611731China Interdisciplinary Materials Research Center Institute for Advanced StudyChengdu UniversityChengdu 610106China

Opportunity to harmonize aspects of oxygen reduction reaction(ORR)performance and structure,and morphology,as well as composition,is urgent for the commercialization of proton exchange membrane fuel ***,we demonstrate the design and synthesis of a functionalized-supported-Pt catalyst(Pt@HNC)featuring a hollow nitrogen-modified dodecahedral carbon substrate obtained by a stress-induced-shrink tailoring *** as-obtained Pt@HNC catalyst possesses enhanced ORR per-formance,in particular with half-wave potential,mass activity(MA)and specific activity,which greatly exceed the commercial Pt/*** density functional theory(DFT)calculations further confirmed that the charge redistribution induced by the electronegativity differences improved the electron interaction between Pt and HNC *** optimized electronic structure of Pt weakens the reaction energy barrier on the Pt@HNC surface and adsorption of^(*)OH species,thus cooperatively improving the intrinsic activity toward ***,our work indeed provides a guide for the future design of functional nanomaterials in the field of catalysts and clean energy.

关键词： Proton exchange membrane fuel cell(PEMFC) Oxygen reduction catalysis Supported Pt-based catalyst Stability

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Traffic Steering in Large-scale Public Cloud 8

Traffic Steering in Large-scale Public Cloud

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8th International Conference on Communication and Information Processing, ICCIP 2022

作者： Hu, Zhangfeng Sun, Siqing Yin, Ping Li, Yanjun Ren, Qiuzheng Li, Baozhu Li, Xiong Department of Cloud Platform Research and Development Inspur Cloud Beijing China Internet of Things and Smart City Innovation Platform Zhuhai Fudan Innovation Institute Zhuhai China School of Computer Science Fudan University Shanghai China School of Computer Science and Engineering University of Electronic Science and Technology Chengdu China

ISBN: (纸本)9781450397100

More and more complex services composed of a series of sequentially arranged middleboxes which are mainly used to meet the requirements of advanced services such as security services, auditing services, monitoring services, personalized enterprise services, and so forth, are increasingly deployed in cloud data centers of public cloud. SFC (Service Function Chaining) is a technique that facilitates the enforcement of complex services and differentiated traffic forwarding policies, dynamically steering the traffic through an ordered list of service functions. Flow table-based traffic steering scheme is commonly adopted in SDN-enabled scenarios, which consumes too many flow entries and is unsuitable for large-scale public clouds in steering traffic between VNFs (Virtual Network Function) inside of VPC (Virtual Private Cloud). Legacy PBR (Policy-based Routing) based schemes which are widely used in traditional physical networks cannot fulfill the requirements of fully distributed routing architectures of large-scale public clouds. In this paper, we present a PBR and unsymmetrical NAT (Network Address Translation) converged scheme to structure SFC in a fully distributed routing architecture. The scheme uses distributed PBR rules to steer traffic between an ordered list of VNFs located on different nodes while performing NAT on different nodes for ingress/egress traffic of a specific flow to avoid asymmetry of packet headers which may lead to failures of communication. The proposed scheme brings no overhead in data transmission, eliminates extra configurations on each middle box of the chain, and is scalable to support the scenarios of large-scale public cloud. © 2022 ACM.

关键词： Complex networks

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