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Electrical, automation and Computer engineering (ICEACE), International Conference on

作者： Yu Peng Yuhang Liu Ruishi Lin Gang Xiang Shenhang Wang Zhiming Yang Department of System Engineering Beijing Aerospace Automatic Control Institute Beijing China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9798350368208

ISBN: (纸本)9798350368215

The paper introduces an intermittent fault diagnosis method for analog circuits using EMD and CNN. The proposed method obtains the circuit output characteristics under different intermittent fault type using SPICE simulation. Then, EMD is used to extract the features and finally, the CNN model for fault detection and localization is built. The effectiveness of the method is validated through experiments in a three-phase SVPWM circuit.

关键词： Fault diagnosis Space vector pulse width modulation Training Neural networks Analog circuits Feature extraction SPICE Software Convolutional neural networks Testing

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Optimizing Machine Learning Algorithms to Enhance Blood Donation for Liver Patients: A Case Study 7

Optimizing Machine Learning Algorithms to Enhance Blood Dona...

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7th IET Smart Cities Symposium, SCS 2023

作者： Mijwil, Maad M. El-Kenawy, El-Sayed M. Bala, Indu Aljanabi, Mohammad Abotaleb, Mostafa Ibrahim, Abdelhameed Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt School of Electrical and Electronics Engineering Lovely Professional University Punjab India Department of Computer Aliraqia University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

Blood is vital for transporting oxygen, nutrients, and hormones to all body parts as it circulates through arteries and veins. It removes carbon dioxide, regulates body temperature, and maintains the body's immune system. Individuals constantly need blood and its derivatives to save their lives and improve their health through medical treatments and surgical operations. Liver diseases are one of the diseases that affects the health of individuals and requires blood to continue living. These diseases cause significant damage to people's health, and early diagnosis plays a crucial role in saving lives. In this paper, machine learning algorithms (support vector machine and random forest) are involved in detecting liver diseases and determining whether donors are suitable to donate blood from blood values. This paper is applied research that found that the performance measures of the random forest algorithm achieved excellent performance in identifying suitable people to donate blood. © The Institution of engineering & Technology 2023.

关键词： Support vector machines

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基于改进分形方法的齿面磨损故障直齿轮啮合特性分析

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Journal of Central South University 2024年第5期31卷 1619-1636页

作者：刘子濛常成胡昊东马辉张顺豪赵松涛张晓旭彭志科 School of Mechanical Engineering and Automation Northeastern UniversityShenyang 110819China Key Laboratory of Vibration and Control of Aero-Propulsion System Northeastern UniversityShenyang 110819China Harbin Marine Boiler and Turbine Research Institute Harbin 150078China School of Mechanical Engineering Tongji UniversityShanghai 201804China Institute of Vibration Shock&Noise State Key Laboratory of Mechanical System and VibrationShanghai Jiao Tong UniversityShanghai 200240China

考虑实际的轮齿表面微观形貌,建立了轮齿间相互作用的三维分形接触模型。结合轮齿承载接触分析方法,考虑轮齿间摩擦力的影响,建立了直齿轮副的时变啮合刚度模型,并通过有限元方法进行了验证。结合Archard磨损模型,考虑齿面粗糙度和摩擦... 详细信息

考虑实际的轮齿表面微观形貌,建立了轮齿间相互作用的三维分形接触模型。结合轮齿承载接触分析方法,考虑轮齿间摩擦力的影响,建立了直齿轮副的时变啮合刚度模型,并通过有限元方法进行了验证。结合Archard磨损模型,考虑齿面粗糙度和摩擦力的影响,分析了齿面磨损故障状态下直齿轮副的啮合特性和磨损深度,同时分析了摩擦力和分形参数对时变啮合刚度和磨损深度的影响。摩擦力导致节线处的时变啮合刚度发生突变。当直齿轮副处于双齿啮合时,摩擦因数的增加和分形维数的降低导致磨损深度的增加和时变啮合刚度的降低。时变啮合刚度随分形维数的变化呈线性变化。分形维数对时变啮合刚度和磨损深度的影响随着磨损周期的增加更为明显,超过了摩擦因数对其的影响。

关键词：直齿轮啮合特性分型接触齿面摩擦力磨损故障

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Adaptive Anomaly Detection in Industrial systems: An EVT-DTS Approach with LSTM Autoencoders

Adaptive Anomaly Detection in Industrial Systems: An EVT-DTS...

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IEEE Instrumentation and Measurement Technology Conference

作者： Bing Yu Jiakai Xu Gang Xiang RuiShi Lin LiGuo Zhao Yang Yu School of Electronics and Information Engineering Harbin Institute of Technology Harbin China Department of System Engineering Beijing Aerospace Automatic Control Institute Beijing China

ISBN: (数字)9798350380903

ISBN: (纸本)9798350380910

The reliability of modern industrial systems is rigid; therefore, it is mandatory to monitor the system status and detect anomalies accurately. A long short-term memory (LSTM) network can be used to predict the trend of single-dimensional system test data and implement anomaly detection based on the prediction result. However, the structure of the modern system is complex, and strong dependencies may exist between different variables. The LSTM-based detection method cannot capture this dependency, and some anomalies can be ignored. Therefore, an anomaly detection framework based on the LSTM autoencoder is proposed in this paper. The auto encoder is applied to find the hidden dependency among variables by minimizing the reconstruction error of normal data, while the LSTM is used to capture the temporal dependencies in the time series. Moreover, a new dynamic error threshold selection strategy based on extreme value theory (EVT-DTS) is presented, which can avoid estimating the error distribution beforehand. The EVT-DTS method can dynamically adjust the error threshold according to the current input data error so that the overall optimal detection result can be obtained. Finally, we implement experiment on two industrial applications using the proposed method, which demonstrate its effectiveness in finding complex anomaly states in the system.

关键词： Adaptive systems Time series analysis Market research Reliability Long short term memory Anomaly detection Monitoring

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When Does Sora Show:The Beginning of TAO to Imaginative Intelligence and Scenarios engineering

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 809-815页

作者： Fei-Yue Wang Qinghai Miao Lingxi Li Qinghua Ni Xuan Li Juanjuan Li Lili Fan Yonglin Tian Qing-Long Han School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Department of Electrical and Computer Engineering Indiana University-Purdue University IndianapolisIndianapolisIN 46202USA Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Virtual Reality Fundamental Research Laboratory Department of Mathematics and TheoriesPeng Cheng LaboratoryShenzhen 518000China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia

DURING our discussion at workshops for writing“What Does ChatGPT Say:The DAO from Algorithmic Intelligence to Linguistic Intelligence”[1],we had expected the next milestone for Artificial Intelligence(AI)would be in the direction of Imaginative Intelligence(II),i.e.,something similar to automatic wordsto-videos generation or intelligent digital movies/theater technology that could be used for conducting new“Artificiofactual Experiments”[2]to replace conventional“Counterfactual Experiments”in scientific research and technical development for both natural and social studies[2]-[6].Now we have OpenAI’s Sora,so soon,but this is not the final,actually far away,and it is just the beginning.

关键词： something Intelligence replace

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Resource Allocation for Coupled Slices in Edge-Assisted Industrial IoT systems

Resource Allocation for Coupled Slices in Edge-Assisted Indu...

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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Wen, Xiaojing Chen, Cailian Ren, Cheng Lyu, Ling Guan, Xinping Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai200240 China Dalian Maritime University School of Information Science and Technology Dalian116026 China

ISBN: (纸本)9798350345384

Multiple types of sensors are utilized for remote monitoring of single industrial process to compensate for the limited accuracy of a single type of sensor. Network slicing technology is considered promising for collecting data from heterogeneous sensors and meeting diverse Quality of Service (QoS) requirements. However, existing research on network slicing optimization mainly focuses on inter-slice resource constraints based on slice heterogeneity, neglecting slice coupling feature. In this regard, this paper proposes a novel network slicing framework for edge-assisted industrial IoT systems. The framework includes a slice coupling model and network resource allocation (transmission and computing) to address the problem of improving estimation performance while ensuring system convergence. The slice coupling model is primarily composed of the estimation error covariance of two slices, calculated using the Age of Task (AoT) as a bridge, which reflects the accuracy and freshness of the estimation. To reduce the complexity of the direct solution, the optimization problem is scaled down and decoupled. The iterative Particle Swarm Optimization (PSO) algorithm is proposed to determine the allocation rates of inter-slice transmission and computing resources. Simulation results demonstrate that the proposed algorithm achieves a flexible balance under heterogeneous estimation weights and exhibits near-optimal performance. © 2023 IEEE.

关键词： Resource allocation

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3D bioprinting of in vitro porous hepatoma models:establishment,evaluation,and anticancer drug testing

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Bio-Design and Manufacturing 2024年第2期7卷 137-152页

作者： Xiaoyuan Wang Zixian Liu Qianqian Duan Boye Zhang Yanyan Cao Zhizhong Shen Meng Li Yanfeng Xi Jianming Wang Shengbo Sang Shanxi Key Laboratory of Micro Nano Sensors and Artificial Intelligence Perception College of Electronic Information and Optical EngineeringTaiyuan University of TechnologyTaiyuan 030024China Key Lab of Advanced Transducers and Intelligent Control System of the Ministry of Education Taiyuan University of TechnologyTaiyuan 030024China Shanxi Institute of 6D Artificial Intelligence Biomedical Science Taiyuan 030031China Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering Taiyuan 030024China Department of Pathology Shanxi Provincial Cancer HospitalTaiyuan 030024China General Hospital of Taiyuan Iron and Steel Company Taiyuan 030809China

Traditional tumor models do not tend to accurately simulate tumor growth in vitro or enable personalized treatment and are particularly unable to discover more beneficial targeted *** address this,this study describes the use of threedimensional(3D)bioprinting technology to construct a 3D model with human hepatocarcinoma SMMC-7721 cells(3DP-7721)by combining gelatin methacrylate(GelMA)and poly(ethylene oxide)(PEO)as two immiscible aqueous phases to form a bioink and innovatively applying fluorescent carbon quantum dots for long-term tracking of *** GelMA(10%,mass fraction)and PEO(1.6%,mass fraction)hydrogel with 3:1 volume ratio offered distinct pore-forming characteristics,satisfactorymechanical properties,and biocompatibility for the creation of the 3DP-7721 *** analysis and quantitative real-time fluorescence polymerase chain reaction(PCR)were used to evaluate the biological properties of the *** with the two-dimensional culture cell model(2D-7721)and the 3D mixed culture cell model(3DM-7721),3DP-7721 significantly improved the proliferation of cells and expression of tumor-related proteins and ***,we evaluated the differences between the three culture models and the effectiveness of antitumor drugs in the three models and discovered that the efficacy of antitumor drugs varied because of significant differences in resistance proteins and genes between the three *** addition,the comparison of tumor formation in the three models found that the cells cultured by the 3DP-7721 model had strong tumorigenicity in nude *** evaluation of the levels of biochemical indicators related to the formation of solid tumors showed that the 3DP-7721 model group exhibited pathological characteristics of malignant tumors,the generated solid tumors were similar to actual tumors,and the deterioration was *** research therefore acts as a foundation for the application of 3DP-7721 models in drug devel

关键词： 3D bioprinting Hepatoma tumor models Drug screening Antitumor drug development

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Federated Intelligence for Intelligent Vehicles

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年第5期9卷 1-5页

作者： Zhang, Weishan Zhang, Baoyu Jia, Xiaofeng Qi, Hongwei Qin, Rui Li, Juanjuan Tian, Yonglin Liang, Xiaolong Wang, Fei-Yue School of China University of Petroleum Qingdao China Department of Data Management Big Data Centre Beijing Beijing China Technology Company Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China Faculty of Innovation Engineering Macau University of Science and Technology Macao China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

This letter is a brief summary of a series of IEEE TIV's decentralized and hybrid workshops (DHWs) on Federated Intelligence for Intelligent Vehicles. The discussed results are: 1) Different scales of large models (LMs) can be federated and deployed on IVs, and three types of federated collaboration between large and small models can be adopted for IVs. 2) Federated fine-tuning of LMs is beneficial for IVs data security. 3) The sustainability of IVs can be improved through optimizing existing models and continuous learning using federated intelligence. 4) LM-enhanced knowledge can make IVs smarter. IEEE

关键词： Intelligent vehicle highway systems

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Underwater SLAM Implementation for a Bionic Robotic Dolphin

Underwater SLAM Implementation for a Bionic Robotic Dolphin

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2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023

作者： Ma, Shaoxuan Wang, Jian Yan, Shuaizheng Wu, Zhengxing Yu, Junzhi Chinese Academy of Sciences Laboratory of Cognitive and Decision Intelligence for Complex System Institute of Automation Beijing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China Peking University State Key Laboratory for Turbulence and Complex System Department of Mechanics and Engineering Science BIC-ESAT College of Engineering China

ISBN: (纸本)9798350327182

This paper aims to implement a simultaneous localization and mapping (SLAM) algorithm for a bionic robotic dolphin in underwater simulation environment. Through combining UWSim with ROS, an underwater simulation environment is constructed through importing various environmental models including coral, tropical fish, gullies, and so on. Thereafter, as an autonomous platform for underwater SLAM, a bionic robotic dolphin with its dynamic model is particularly built in the environment to perform dolphin-like swimming. Based on the sensor information from an onboard camera and an inertial measurement unit, the VINS-Mono algorithm is employed and implemented by the robotic dolphin to position itself underwater. Extensive simulations are conducted to validate the effectiveness of the employed SLAM algorithm in various dolphin-like motions of the robotic dolphin, such as linear, circular, and spiral motions. The obtained results provide valuable guidance for the underwater SLAM research. © 2023 IEEE.

关键词： Robotics

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An Experimental Research on Temperature Accuracy Algorithm in Fan Coil Thermostat 6

An Experimental Research on Temperature Accuracy Algorithm i...

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6th IEEE International Electrical and Energy Conference, CIEEC 2023

作者： Ari, Yunus Cücük, Ergün Karateke, Seda Institute of Graduate Studies Istanbul University - Cerrahpaşa Electric and Electronic Engineering Istanbul34320 Turkey Control and Automation Systems Industry and Trade Inc. Department of Research and Development Ges Teknik Air Conditioning Istanbul34852 Turkey Istanbul Topkapi University Faculty of Engineering Department of Computer Engineering Istanbul34087 Turkey

ISBN: (纸本)9798350346671

The efficient operation of HVAC&R systems are based on keeping indoor temperature and air quality at an optimum level without disturbing comfort. Starting from this point, in this experimental research, the factors affecting the measurement accuracy during the room temperature detection of a wall mount fan coil thermostat were examined. Among the external effects, the effect of the device components on the measurement was focused and the solution of the measurement deviations occurred in this extent was investigated. Based on the experiments, the algorithm that must be applied to reach the optimum temperature measurement of a room thermostat developed for Fan Coil systems was proposed. © 2023 IEEE.

关键词： Thermostats

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