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检索条件"任意字段=2023 3rd International Conference on Detection Technology and Intelligence System, DTIS 2023"

共 2097 条记录，以下是71-80 订阅

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Modeling of Electrochemical Treatment for Early detection of Tumor Cells 3

Modeling of Electrochemical Treatment for Early Detection of...

引用

3rd international conference on Artificial intelligence and Signal Processing, AISP 2023

作者： Lapakshi, Asad Hussain Chintalapalli, Ankitha Geetha, P. Sree Vidyanikethan Engineering College Department of Electronics and Communication Engineering Tirupati India Mohan Babu University School of Engineering and Technology Department of Electronics and Communication Engineering Tirupati India

ISBN: (纸本)9798350320749

By applying a constant uninterrupted current via more than two electrodes put inside alternatively close to the tumour, tumours can be treated electrochemically (EChT). To develop a reliable dose-planning system, it is essential to understand the underlying mechanism of destruction of EChT. One method for doing this is mathematical modelling. Through modelling of the anode processes, the importance of chlorine in the underlying EChT degradation mechanism has been made clear. It has been found that the production of hydrogen ions depends significantly on tissue and chlorine activities. The amount of these processes that contribute to the tissue's acidity near to the anode and the applied current density are highly connected. Throughout the course of the treatment, early deduction time is utilised. © 2023 IEEE.

关键词： Tumors

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Research on the Application of Deep Learning Object detection in Rust Defect detection of Power Equipment 3

Research on the Application of Deep Learning Object Detectio...

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3rd international conference on Electrical Engineering and Mechatronics technology, ICEEMT 2023

作者： Xu, Bo Ding, Yuan Super High Voltage Branch of State Grid Jiangxi Electric Power Co. Ltd 330000 China

ISBN: (纸本)9798350303698

In order to improve the intelligence level of power grid operation and enhance the credibility of rust defect detection in power equipment, this paper addresses the significant differences in image quality in actual situations of unmanned aerial vehicle (UAV) inspection. A rust detection method incorporating an attention mechanism into the Faster R-CNN model and considering background brightness and gamma transformation is proposed. This method can adaptively normalize the images and effectively identify rust areas in complex backgrounds, large brightness differences, and noise-contaminated conditions. By introducing three assessment indicators: rust rate, rust confidence, and rust heat map, comprehensive rust defect information is provided to maintenance personnel, ensuring the safe and stable operation of power equipment. © 2023 IEEE.

关键词： Object detection

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Design and Implementation Realization of Gas detection system Based on ZigBee 3

Design and Implementation Realization of Gas Detection Syste...

引用

3rd international conference on Electronic Information Engineering and Computer Science, EIECS 2023

作者： Su, Zhihua Yan, Lihong Yang, Tianqi Huan, Jiayu Xi 'An Eurasia University School of Information Engineering Shaanxi Xi'an China

ISBN: (纸本)9798350316674

ZigBee technology as a mature short-range communications technology, has been widely used in all walks of life. In this paper, a gas detection system with the network structure is designed and implemented based on ZigBee technology. The system mainly realizes the real-time monitoring and alarming of the household gas safety. The system includes wireless local area network, server and detection terminal. The system uses MFC and development technology for mobile devices to carry out application development of system, the server carries on the real-time data acquisition, the analysis and the early warning to the detected terminal contained in the system. After running the test and application, the system meets the function of safety detection for gas. © 2023 IEEE.

关键词： detection terminal gas detection system real-time data processing ZigBee technology

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Application of Artificial intelligence (AI) technology in Intelligent Recommendation of English Personalized Learning system 3

Application of Artificial Intelligence (AI) Technology in In...

引用

3rd international conference on Artificial intelligence and Autonomous Robot systems, AIARS 2024

作者： Jing, Yanhui Jia, Guifu Lanzhou Resources & Environment VOC-TECH University Gansu Province Lanzhou730000 China

ISBN: (纸本)9798350376173

The application of artificial intelligence in the field of English teaching is built on the basis of computer and network technology, through the construction of intelligent learning environment, to provide students with more convenient and efficient online personalized learning system. This paper aims to analyze and study the combination of artificial intelligence and traditional distance education, and design a learning system according to the intelligent recommendation technology of English personalized learning. In terms of implementation methods, this paper adopts the classification of intelligent algorithms. After testing the system, the test results show that the accuracy of grammar and reading in the intelligent recommendation system is quite close, about 85% and 90%. Writing was slightly more accurate than grammar and reading, at 92%. The accuracy of different learning content also varies. The accuracy of vocabulary learning was the lowest, only 80%, while the accuracy of spoken language learning was the highest, up to 95%. This suggests that oral learning may perform better in intelligent recommendation systems, while vocabulary learning is relatively poor. Through the use of artificial intelligence technology, English teaching can better meet the needs of students' personalized learning. Intelligent learning environment can provide targeted learning resources and personalized guidance according to students' learning characteristics and progress, so as to better promote the improvement of English language ability. © 2024 IEEE.

关键词： Contrastive Learning

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detection of Early Fault in Power Electronic Converters through Machine Learning and Data Mining Techniques 3

Detection of Early Fault in Power Electronic Converters thro...

引用

3rd international conference on Artificial intelligence and Smart Energy, ICAIS 2023

作者： Pradeep, K.V. Gowrishankar, K. Sivanantham, E. Rao, Katta Subba Kiran, Nagulapati Vimal, A. Vellore Institute of Technology School of Computer Science and Engineering Tamil Nadu Chennai India Amet University Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Rajalakshmi Institute of Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India B v Raju Institute of Technology Department of Computer Science and Engineering Telangana Medak India Anil Neerukonda Institute of Technology and Sciences Department of Electrical and Electronics Engineering Andhra Pradesh Visakhapatnam India Sri Eshwar College of Engineering Department of Mechanical Engineering Tamil Nadu Coimbatore India

ISBN: (纸本)9781665462167

The Power electronic system plays a significant role in versatile applications. The power electronic converters are largely used in energy conversion mechanisms. A fault is defined as the abnormal condition of the system that results in various consequences. The important constraints in the modelling of power electronic systems involve losses, Electromagnetic Interference (EMI) and harmonics. This includes the fault detection in the power electronic converters that includes three phase rectifier, d-dc converter and single-phase inverter. These parameter affects the overall efficiency and quality of the system. To overcome the fault in the power electronic converters, the machine learning with data mining techniques is adopted. This helps to predict the early fault and helps to increase the efficiency of the system. © 2023 IEEE.

关键词： Signal interference

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2023 3rd international conference on Artificial intelligence and Industrial technology Applications, AIITA 2023

2023 3rd International Conference on Artificial Intelligence...

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2023 3rd international conference on Artificial intelligence and Industrial technology Applications, AIITA 2023

The proceedings contain 90 papers. The topics discussed include: registration method of single-line point clouds and images based on depth learning;research on landslide detection in SAR images based on multi-channel change detection fusion;support vector regression based on improved Harris Hawk optimization algorithm for power load forecasting;epileptic seizure detection based on semi-supervised generative adversarial network;image recognition of peach pests based on improved convnext;optimization of BP neural network for wind power output prediction based on particle swarm optimization algorithm;application of improved genetic algorithm and ant colony algorithm in multi-objective path planning;automatic bridge detection of SAR images based on interpretable deep learning algorithm;image stitching method based on feature optimization and circular function weighted fusion;natural scene text detection algorithm based on the regional proposal;and research and development of machine vision algorithm performance evaluation system in complex scenes.

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2023 3rd international conference on Robotics, Automation and Artificial intelligence, RAAI 2023

2023 3rd International Conference on Robotics, Automation an...

引用

3rd international conference on Robotics, Automation and Artificial intelligence, RAAI 2023

ISBN: (纸本)9798350307566

The proceedings contain 53 papers. The topics discussed include: three-dimensional trajectory planning for multi-robot collaboration in complex components with heterogeneous materials;innovative approaches to tourism demand prediction: a genetic algorithm perspective;a fuzzy inference system-based hybrid assignment method for cobot assignment problem;cylinder-wheel coupled robot with buttocks-support mechanism for lower-limb rehabilitation training;area coverage maximization of multi UAVs using multi-agent reinforcement learning;design of a drone that applies multisensor information for the early detection of forest fires;and research on dataset generation in the development of large language models for digital textbooks.

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Hotspot detection of Solar Photovoltaic system: A Perspective from Image Processing 3

Hotspot Detection of Solar Photovoltaic System: A Perspectiv...

引用

IEEE 3rd international conference on Power Engineering Applications (ICPEA) - Shaping Sustainability Through Power Engineering Innovation

作者： Ishak, Nurul Huda Binti Isa, Iza Sazanita Binti bin Osman, Muhammad Khusairi Daud, Kamarulazhar bin Jadin, Mohd Shawal Univ Teknol MARA Ctr Elect Engn Studies Permatang Pauh 13500 Pulau Pinang Malaysia Univ Malaysia Pahang Fac Elect & Elect Engn Technol Pekan 26600 Pahang Malaysia

ISBN: (纸本)9781665475013

Research in solar energy has rapidly grown since its significant and contributes to the advancement in clean renewable energy technology. Effective energy management such as fault detection impacts the early-stage monitoring for the efficiency, reliability, and safety of solar photovoltaic (PV) systems. The formation of a hotspot is one of the issues commonly occurred in a PV system. However, the main limitation of hotspot detection is the difficulty to interpret specific components with erratic temperatures in the thermographic images for attributes in the intelligence detection model. In this study, a review of hotspot detection in solar PV panels using the image processing method is established based on the image processing field. The integration of image processing approach can further assist in developing automated fault detection in solar PV farms for effective preventive monitoring methods. Therefore, several aspects need to be categorized and considered accordingly for achieving accurate prediction. Several ways were discussed, and future research is suggested in this study.

关键词： hotspot solar PV system image processing

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Cybersecurity Threats, detection Methods, and Prevention Strategies in Smart Grid: Review 3

Cybersecurity Threats, Detection Methods, and Prevention Str...

引用

3rd international conference on Artificial intelligence and Smart Energy, ICAIS 2023

作者： Kumar, K. Dinesh Jawale, Madhuri A Sujith, M. Pardeshi, D.B. Sanjivani College of Engineering Department of Information Technology Maharashtra Kopargaon423 603 India Sanjivani College of Engineering Department of Electrical Engineering Maharashtra Kopargaon423603 India

ISBN: (纸本)9781665462167

Rapid progress is being made toward replacing the current global power system with a smart one. As with every new technology, a smart grid has its drawbacks. Cybersecurity is a serious concern for the smart grid. Managing such a massive network is difficult since millions of sensors are constantly transmitting and receiving data packets throughout the network. The smart grid's vital components - its privacy, security, and accessibility - are all vulnerable to hacking. In a smart grid system, cyberattacks can happen on any of three different levels: the consumers who use the system, the communication network of the smart devices and sensors, and the people who manage the system. In this article, numerous ways with which cyber security in smart grid network may be compromised, and then security measures that are taken on three separate levels to prevent cyber-attacks are discussed. This work also suggests a technique to decrease the severity of any possible cyberattack. © 2023 IEEE.

关键词： Cybersecurity

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Ship Target detection Method Based on Berthing Scenarios 3

Ship Target Detection Method Based on Berthing Scenarios

引用

3rd international conference on Electronic Information Engineering and Computer Communication, EIECC 2023

作者： Mu, Keke Chen, Xianqiao Xie, Kai Chen, Jianfeng School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan China

ISBN: (纸本)9798350359961

In port operations, berthing procedures play a crucial role, with ship detection serving as the cornerstone for automation in berthing scenarios. Existing ship detection methods suffer from issues such as low accuracy and slow detection speed. This paper proposes a ship detection method based on the SSD algorithm. The approach leverages dilated convolution to enhance features, utilizes the lightweight MobileV2 network to optimize the model, and ultimately employs the K-means++ method to refine the design of default box ratios. This method achieves high accuracy, rapid detection speed, and a lightweight profile, providing robust technical support for efficient ship target recognition in berthing operations. © 2023 IEEE.

关键词： Dilated convolution MobileV2 Ship detection SSD

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