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检索条件"任意字段=2023 International Research Conference on Smart Computing and Systems Engineering, SCSE 2023"

共 8072 条记录，以下是91-100 订阅

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Deep Learning in Automated Tests for the Automotive Industry 15th

Deep Learning in Automated Tests for the Automotive Indus...

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15th international conference on Soft computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired computing, NaBIC 2023

作者： Branco, Beatriz C. Barbosa, Ramiro S. Department of Electrical Engineering Institute of Engineering - Polytechnic of Porto (ISEP/IPP) Porto Portugal GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development ISEP/IPP Porto Portugal

ISBN: (纸本)9783031810824

The automotive industry is one of the biggest industries nowadays, representing almost 80% of the projects in Capgemini engineering Portugal, where this work was developed. In this paper, a new approach for automated tests in this sector is presented, based on the application of Deep Learning (DL) algorithms. Experimental results show that the new solution reduces the frameworks needed for testing, as well as the human interaction, improving the efficiency in HMI testing for the company. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Automated tests Automotive industry Deep learning

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Artificial Intelligence Technology Promotes Sustainable Development of Agricultural Economy 14th

Artificial Intelligence Technology Promotes Sustainable Deve...

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14th international conference on Frontier computing, FC 2024

作者： Lu, Xinyong Li, Changgui School of Economics and Trade Zhongkai College of Agricultural Engineering Guangdong Guangzhou510225 China Business School Guilin University of Technology Guangxi Guilin541004 China

ISBN: (纸本)9789819623907

With the progress of the times, traditional research methods cannot well meet the urgent needs of sustainable development of agricultural economy. Therefore, this article aims to study the application of AI technology to promote sustainable development of agricultural economy. Firstly, this article utilizes support vector machines in machine learning techniques to establish a prediction model and optimize the planting optimization techniques in the R area;secondly, it uses deep reinforcement learning technology to construct an intelligent scheduling system for R area, optimizing the scheduling of intelligent agricultural machinery operations;next, this article constructs a long-term and short-term memory network model to make intelligent market predictions based on market data in the R region. Finally, this article takes the irrigation system in R area as an example to conduct experimental evaluation of sustainable development indicators for agricultural economy. The results showed that the irrigation efficiency and water resource utilization rate of irrigation systems using AI (Artificial Intelligence) technology were 24.05% and 25.64% higher than traditional irrigation systems, respectively. It can be seen that the application of AI technology can effectively promote the sustainable development of agricultural economy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： smart agriculture

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Comparative Analysis of Monopole and Dipole Antennas for CubeSats: A Review 5th

Comparative Analysis of Monopole and Dipole Antennas for Cub...

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5th international conference on computing, Communications, and Cyber Security, IC4S 2023

作者： Oubahsis, Nissrine Benhmimou, Boutaina Karim, Mohamed Hussain, Niamat Omari, Fouad Gupta, Nancy Khadiri, Khalid El Cengiz, Korhan Garg, Sangeeta Laamara, Rachid Ahl Guerrero, Josep M. Bakkali, Mohamed El LPHE-MS Faculty of Sciences University Mohammed V in Rabat Rabat Morocco LIMAS Faculty of Sciences Dhar El Mahraz Sidi Mohammed Ben Abdellah University Fez30000 Morocco Department of Smart Device Engineering Sejong University Seoul Korea Republic of ECE Department Lyallpur Khalsa College Technical Campus Punjab Jalandhar India Department of Physics Faculty of Sciences El Jadida University Chouaib Doukkali of El Jadida El Jadida Morocco Department of Electrical-Electronics Engineering Istinye University Istanbul34010 Turkey Mewar Institute of Management Uttar Pradesh Ghaziabad India CROM Aalborg University Aalborg Denmark

ISBN: (纸本)9789819773701

CubeSats provide new communications, navigation, remote sensing, and research capabilities for military and commercial applications. Their capabilities led the scientific community to rethink existing spacecraft technology to make it suitable for CubeSats. This research focuses on the development of monopole and dipole antennas and their application to CubeSats. There is a lot of ongoing research in the antenna design community to create monopole and dipole antennas for use in CubeSat communications, which we will discuss in this article. This study provides comprehensive information to review the current status of monopole and dipole antennas. This paper explores and examines the suitability of monopole and dipole antenna designs for CubeSats. We also provide a set of design-based analysis models that can support many interesting projects in the future. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Dipole antennas

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Kalman Filters in IoT: A Bibliometric Analysis

Kalman Filters in IoT: A Bibliometric Analysis

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international IoT, Electronics and Mechatronics conference, IEMTRONICS 2024

作者： Obaideen, Khaled AlShabi, Mohammad Gadsden, Stephen Andrew Bio-Sensing and Bio-Sensors Group Smart Automation and Communication Technologies RISE P.O. Box 27272 Sharjah United Arab Emirates Department of Mechanical and Nuclear Engineering University of Sharjah Sharjah27272 United Arab Emirates Department of Mechanical Engineering McMaster University HamiltonONL8S 4L8 Canada

ISBN: (纸本)9789819747832

This bibliometric analysis focuses on the evolution and trends of the Kalman Filters (KFs) studies in the Internet of Things (IoT) from the year 2009 to 2023. This being a data-intensive study, it uses the information from major academic databases, which it adapts to explore key terms, publication patterns, and the interdisciplinary nature of the research. The paper comes out with a sharp increase of the research in 2015, which corresponds to growing of the research interest to the application of KFs for IoT. Key points of the study accentuate the role of KFs in IoT, especially in respect of the betterment of the systems for indoor positioning, global positioning, and sensor data fusion. This software proves the KFs are in the spotlight in IoT by helping to improve localization accuracy and data processing. The research highlights progress in filtering methods, for example, extended and unscented Kalman filters, evidently to improve state estimation and predictive analytics in dynamic contexts. Furthermore, KFs research scope includes novel areas such as machine learning and deep learning, which indicates the possibility of using this technology as a tool for advancing IoT. The rapid growth of technology in this area also presents challenges, a part of those are the data privacy and security problems in complex IoT environments. The paper emphasizes the major part KFs are playing in driving IoT technology and also stresses the type of interdisciplinary studies that are needed to navigate the changing landscape of IoT applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Extended Kalman filters

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Prediction of Processing Parameters Based on Multi-objective Bayesian Optimization Combined with Machine Learning Model for High Frequency Heat Treatment of Metals 2nd

Prediction of Processing Parameters Based on Multi-objective...

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2nd international conference on Security and Information Technologies with AI, Internet computing and Big-data Applications, SITAIBA 2023

作者： Lin, Chih-Hsueh Tseng, Yu-Hsiang Hu, Kuo-Hsin Ho, Chia-Wei Department of Electronic Engineering National Kaohsiung University of Science and Technology Kaohsiung City Taiwan Knowledge Application Development Group Metal Industry Research and Development Center Taguig Philippines

ISBN: (纸本)9789819777853

In the process of metal processing, heat treatment is a common metal processing method, which is usually used to change the mechanical properties of metal alloys to control such as hardness, strength, toughness, ductility, and elasticity. The high-frequency heat treatment is to rapidly heat the surface of the steel with high frequency, stop the heating when it reaches the quenching temperature, and use an appropriate coolant to implement quenching. In the process of processing, it is often necessary to set processing parameters for the processed products, so as to ensure that each processed product meets the requirements. This manual setting method is not only inefficient but also needs to rely on the experience of field personnel to set parameters. Even so, the problem of artificially setting wrong parameters still occurs. Therefore, this paper applies machine learning technology to analyze the correlation between processing parameters and establishes a predictive evaluation model in combination with hyperparameter optimization, and then predicts the best processing parameters. In order to achieve the concept of intelligent production line, and can reduce the problems caused by human setting errors, thereby improving efficiency. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Quenching

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Development of Digital Capabilities for E-commerce Agribusiness: An Exploratory research 3rd

Development of Digital Capabilities for E-commerce Agribusin...

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3rd international conference on smart Technologies and Innovation Management, MTYMEX 2024

作者： Pham, Thi Tuan Linh Taherdoost, Hamed Le, Tuan-Vinh International School Thai Nguyen University Thai Nguyen Viet Nam University Canada West VancouverBC Canada GUS Institute Global University Systems London United Kingdom Fu Jen Catholic University New Taipei Taiwan

ISBN: (纸本)9783031649561

Digital transformation is considered as challenging yet imperative in Vietnam recently. In the agriculture sector, one of the directions to comprehensively promote digital transformation is to encourage and support farmers to promote their agribusiness on e-commerce platforms. This study aims to explanatorily develop a framework for farmers’ digital capabilities for e-commerce agribusiness. The research setting is Thai Nguyen city, a midland area in the North of Vietnam. A qualitative research design with literature review of recognized databases and focus group method is employed to develop such framework. The framework for farmers’ digital capabilities for e-commerce agribusiness is designed with four dimensions including (1) attitude toward e-commerce agribusiness, (2) basic ICT capabilities, (3) e-commerce digital marketing capabilities, and (4) digital learning capabilities, with various specific capabilities for each dimension. Future studies could further validate the reliability and applicability of the framework developed to propose insightful suggestions for agriculture managers and policymakers. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Agribusiness

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research on virtual-real coordination control system of litchi picking robot based on Unity3D

Research on virtual-real coordination control system of litc...

引用

2024 international conference on Optical and Photonic engineering, icOPEN 2024

作者： Xiong, Juntao Lu, Chang Yao, Zhaoshen South China Agricultural University 510642 China

ISBN: (数字)9781510688117

ISBN: (纸本)9781510688100

The purpose of this study is to explore the application of virtual and real simulation technology in the control system of litchi picking robot. With the rapid development of agricultural automation and intelligence, picking robots are important equipment in modern agriculture, and the design and optimization of their control systems have become the focus of research. At present, the litchi picking robot control system has high technical requirements for operators, and the development cost is high and the risk is high. Secondly, the litchi picking robot is highly dependent on the real environment in the experiment and can easily cause damage to the natural environment. In view of the special environment and operational requirements of litchi picking, virtual simulation technology is used, combined with the performance characteristics of physical robots, to build a simulated litchi orchard scene and simulated picking manipulator in the virtual environment. At the same time, a real-time communication platform was built in Unity3D, and the digital twin control framework of the picking robot was creatively designed to achieve coordinated control and coordinated movement of the real and virtual robotic arms. The accuracy of the virtual-real combination control system was verified through design accuracy experiments. After experimental verification, the error rate of virtual and real motion of the robotic arm reaches less than 0.03%, which can meet the precise operation requirements of the robotic arm. The system can simulate the operation process of the picking robot in a virtual environment in advance. Experiments can also be performed without the need for actual equipment, reducing the risk and cost of development. In addition, the virtual orchard environment can also be used for smart agriculture research and lay the foundation for smart agriculture. It can also reduces dependence on the real environment and protects the ecological environment. © 2025 SPIE.

关键词： Orchards

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One-Step Laser-Induced Dissolvable PVA Mask for 3D Soft Carbon Electrode Array 38

One-Step Laser-Induced Dissolvable PVA Mask for 3D Soft Carb...

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38th IEEE international conference on Micro Electro Mechanical systems, MEMS 2025

作者： Wang, Xuanqi Xue, Kai Bai, Ruiyu Huang, Ye Zhang, Zimo You, Xiaoli Wang, Minghao Chang, Honglong Ji, Bowen Northwestern Polytechnical University Unmanned System Research Institute China Northwestern Polytechnical University National Key Laboratory of Unmanned Aerial Vehicle Technology Integrated Research and Development Platform of Unmanned Aerial Vehicle Technology China Northwestern Polytechnical University Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace School of Mechanical Engineering China Northwestern Polytechnical University Sanhang Institute for Brain Science and Technology China Northwestern Polytechnical University Institute of Medical Research China Hangzhou Dianzi University Moe Engineering Research Center of Smart Microsensors and Microsystems College of Electronics and Information China

ISBN: (纸本)9798331508890

This paper introduces a 3D soft carbon electrode array, fabricated through a one-step laser-induced process integrating a water-dissolvable polyvinyl alcohol (PVA) mask. This approach achieves precise conical microstructures and robust conductive channels using hybrid MWCNT@PDMS conductive paste. The soft carbon electrode sites with a 3D conical microstructure are designed to enhance proximity to neural tissue, thereby enhancing electrocorticogram (ECoG) signal quality and enabling effective neural stimulation. The electrode array demonstrates remarkable stretchability (25% over 1,000 cycles without failure) and stability (equivalent to 66 days in vivo). Compared to conventional materials, our electrodes exhibit superior electrochemical properties, including lower impedance (9.7 kΩ at 1 kHz) and higher signal-to-noise ratio (SNR, 61.7 dB). Thus, this one-step process is a cost-effective, scalable solution for recording and modulating central or peripheral neural tissues. © 2025 IEEE.

关键词： Carbon electrodes

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Design and Study Performance of Vibration-Based Mechanical Energy Harvester and Reservoir 5th

Design and Study Performance of Vibration-Based Mechanical E...

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5th international conference on Vibration and Energy Harvesting Applications, VEH 2024

作者： Afsharfard, Aref Kim, Kyung Chun School of Mechanical Engineering Eco-Friendly Smart Ship Parts Technology Innovation Center Pusan National University Busan Korea Republic of

ISBN: (纸本)9789819611904

Nowadays, the worldwide scarcity of lithium-ion batteries is mainly due to the increased demand for electric vehicles, energy storage systems, and consumer electronics that rely on these batteries. While many experts in the industry anticipate a resolution to this shortfall shortly, it appears that the battery dilemma remains an ongoing obstacle for electrical systems, likely to reoccur. A novel system has been proposed for harnessing natural environmental kinetic energy, which can be utilized alongside all mechanical amplifiers employed as vibration-based energy harvesters. This mechanical system operates as both a rectifier and converter, capable of producing unidirectional rotary motion that can be stored as potential energy. A magnetic transducer will be employed to convert the stored potential energy into electrical energy. The system presented herein serves as a mechanical rectifier, energy converter, and energy reservoir, proficient not only in harvesting vibration-based energy but also in storing it. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Kinetic energy

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research on dynamic network security detection technology based on SDN 4

Research on dynamic network security detection technology ba...

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4th international conference on Network Communication and Information Security, ICNCIS 2024

作者： Zhao, Kai Beijing Polytechnic Beijing100176 China

ISBN: (数字)9781510688261

ISBN: (纸本)9781510688254

Traditional network architecture can no longer meet the development needs of technologies such as cloud computing and big data. SDN network architecture has the characteristics of high openness and programmability, which can quickly respond to changes in business requirements. SDN decouples the control management function of the network from the data forwarding function, simplifies network configuration work based on logic centralized controllers and open programming interfaces, thereby achieving a flat management mode and flexible data forwarding function. The centralized control and programmability of SDN networks also pose significant security threats to SDN. Based on the CSE-CIC-IDS2018 dataset, this article tests the performance of various intelligent learning algorithms, analyzes data flows, distinguishes normal data from abnormal data, improves detection accuracy, and has practical significance for the security defense of SDN networks. © 2025 SPIE.

关键词： Network security Computer security Network architectures Control systems Machine learning Data transmission Defense and security Detection and tracking algorithms Information security Security technologies

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