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检索条件"任意字段=2023 International Conference on Computer Science and Automation Technology, CSAT 2023"

共 68658 条记录，以下是4891-4900 订阅

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Proxy-based Super Twisting Control Algorithm for Aerial Manipulators 13

Proxy-based Super Twisting Control Algorithm for Aerial Mani...

引用

13th IEEE international conference on CYBER technology in automation, Control, and Intelligent Systems, CYBER 2023

作者： Hua, Zhengyu Xu, Bowen Xing, Li Quan, Fengyu Xiong, Xiaogang Chen, Haoyao School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China

ISBN: (纸本)9798350315196

Aerial manipulators are composed of an aerial multi-rotor that is equipped with a 6-DOF servo robot arm. To achieve precise position and attitude control during the arm's motion, it is critical for the system to have high performance control capabilities. However, the coupling effect between the multi-rotor UAVs' movement poses a challenge to the entire system's control capability. We have proposed a new proxy-based super twisting control approach for quadrotor UAVs that mitigates the disturbance caused by moving manipulators. This approach helps improve the stability of the aerial manipulation system when carrying out hovering or trajectory tracking tasks. The controller's effectiveness has been validated through numerical simulation and further tested in the Gazebo simulation environment. © 2023 IEEE.

关键词： Manipulators

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Ship Intrusion Detection technology Based on Bayesian Optimization Algorithm and XGBoost 3

Ship Intrusion Detection Technology Based on Bayesian Optimi...

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3rd international conference on Electrical Engineering and Control science, IC2ECS 2023

作者： Zhou, Aobo Zhu, Qi Zhang, Jundong Meng, Ke School of Marine Engineering Dalian Maritime University Liaoning Dalian China

ISBN: (纸本)9798350382426

Cybersecurity is a prerequisite for maritime safety. This study focuses on intelligent ship integrated automation system, analyzing the principles and shortcomings of these system. We propose a machine learning-based intrusion detection solution that utilizes Recursive Feature Elimination (RFE) as a feature selection algorithm and XGBoost as a classification algorithm. The Bayesian optimization algorithm is applied to optimize the hyperparameters of the XGBoost model for detecting anomalous network data. Results indicate that, compared to decision trees, logistic regression, random forests, KNN, and recent research findings, the proposed method exhibits smaller estimation errors with an overall accuracy of 99.8%. It effectively reduces vulnerabilities in ship networks, achieving a F1-score of 96.37% and a recall rate of 96.33% under sufficient dataset conditions. This approach enhances network security performance and elevates the cybersecurity level of intelligent ships. © 2023 IEEE.

关键词： Anomaly detection intelligent ship integrated automation system shipboard network security XGBoost algorithm

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AI-Driven Farming: CNN-Based Rice Leaf Disease Identification and Classification

AI-Driven Farming: CNN-Based Rice Leaf Disease Identificatio...

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2023 international conference on Advanced Mechatronics, Intelligent Manufacture and Industrial automation, ICAMIMIA 2023

作者： Alianto, Tegar Erik Fauzi Abdulloh, Ferian Aminuddin, Afrig Rahardi, Majid Universitas Amikom Yogyakarta Faculty of Computer Science Sleman Indonesia

ISBN: (纸本)9798350309225

This research investigates the performance of three distinct neural network models, including the Convolutional Neural Network (CNN) architecture, InceptionV3, and Xception, for classifying rice plant diseases. Evaluation metrics encompassing accuracy, precision, recall, and F1 score were employed to assess the models' efficacy in classifying diseases (Blast, Blight, and Tungro). The findings reveal that the Xception Transfer Learning Model outperformed the other models, achieving an average accuracy of 0.97. InceptionV3 also exhibited strong performance, with an average accuracy of 0.95. Meanwhile, the CNN Architecture model presented lower performance, with an average accuracy of 0.94. Confusion matrices were analyzed for each model, offering comprehensive insights into classification performance. These results facilitate the selection of the most suitable model for disease classification in rice plants, with the Xception Transfer Learning Model emerging as the preferred choice. © 2023 IEEE.

关键词： Neural network models

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Employee Recruitment Analysis Using the MOORA Method

Employee Recruitment Analysis Using the MOORA Method

引用

2023 international conference on Informatics Engineering, science and technology, INCITEST 2023

作者： Mardiani, G.T. Susanto, R. Harihayati, T. Universitas Komputer Indonesia Informatics Engineering Engineering and Computer Science Bandung Indonesia

ISBN: (纸本)9798350317862

A company definitely needs employees to help in its business processes. These employees are generated from the recruitment process. Errors in the recruitment process will have an impact on the company's productivity and reputation. Therefore, when a division or part of a company that handles employee recruitment requires a technique or method that can provide recommendations for employees to be recruited as needed. One method that can be used to support the decision of which employee to accept or hire is the Multi Objective Optimization by Ratio Analysis (MOORA) method. The results of calculations using MOORA based on the criteria set by the company with prospective employees applying for administrative positions state that alternative 1 (A1) gets a preference value (Yi) of 0.40 (the highest score obtained compared to the alternatives), this shows if this method can be applied to provide recommendations on which employees should be recruited according to company needs with simple and easy-to-understand calculations. © 2023 IEEE.

关键词： Personnel

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Study on a NiTiHfTa shape memory alloy with high-pressure torsion and subsequent annealing 9

Study on a NiTiHfTa shape memory alloy with high-pressure to...

引用

9th international conference on Mechanical Engineering, Materials, and automation technology, MMEAT 2023

作者： Zhang, Jintao Hu, Peng Wang, Shibo Zhang, Yu Huang, Yi Ding, Hua School of Materials Science and Engineering Northeastern University Shenyang110819 China Key Laboratory of Light Structural Materials of Liaoning Province Northeastern University Shenyang110819 China Department of Design and Engineering Faculty of Science and Technology Bournemouth University Dorset PooleBH12 5BB United Kingdom Materials Research Group Department of Mechanical Engineering University of Southampton SouthamptonSO17 1BJ United Kingdom

ISBN: (纸本)9781510668584

An alloy with the composition of 49.6Ni-35.4Ti-9Hf-6Ta (at%) was processed by high-pressure torsion (HPT) and post-HPT annealing treatment. The microhardness of HPT-processed samples increased obviously, and amorphous feature appeared in 2 turns sample. The microhardness further increased and amorhozation was enhanced in 16 turns sample. After annealing at 750 ℃ for 3h, almost full crystallization occurs in 16 turns sample. In-situ high temperature X-ray diffraction experiment reveals that martensite to austenite transformation took place, indicating the alloy would exhibit SMA effect. © 2023 SPIE.

关键词： Annealing

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Transformation of Network Flow Data into Images for Intrusion Detection Using Convolutional Neural Networks

Transformation of Network Flow Data into Images for Intrusio...

引用

2023 international Russian automation conference, RusAutoCon 2023

作者： Golubev, Sergey Novikova, Evgenia St. Petersburg Federal Research Center of Russian Academy of Sciences Laboratory of Computer Security Problems St. Petersburg Russia

ISBN: (纸本)9798350345551

One of the most challenging problems in intrusion detection is the development of techniques that are able to detect novel and unseen attacks. Currently, the researchers are investigating applicability of the deep learning techniques to solve this task, as the deep learning models are known for their ability to reveal spatial as well as temporal patterns in data flows. However, their usage often requires converting tabular data to matrix-based structures. This paper presents an approach to constructing images from the raw sequence of bytes representing network flow, discusses several options to generate them, and evaluates their impact on the performance of intrusion detection model. The experiments are conducted using the CICIDS2017 dataset. The obtained results show that the proposed data preprocessing technique allows one to achieve high accuracy in attack detection, and as this approach does not require knowledge of protocol structure, it could serve as a basis for development of protocol-independent preprocessing techniques in intrusion detection tasks. © 2023 IEEE.

关键词： Intrusion detection

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An approach to interval-valued possibility intuitionistic fuzzy soft sets for treating drug addict patients based on decision making 2

An approach to interval-valued possibility intuitionistic fu...

引用

2nd international conference on Advancements in Electrical, Electronics, Communication, Computing and automation, ICAECA 2023

作者： Aruna, Devi.S. Jayanthi, D. Research Scholar Avinashilingam Institute of Home Science and Higher Education for Women Kumaraguru College of Technology Tamil Nadu Coimbatore India Avinashilingam Institute of Home Science and Higher Education for Women Tamil Nadu Coimbatore India

ISBN: (纸本)9798350306811

A decision maker has to choose a optimized solution among the many possible solutions available under a uncertain circumstance. To find one such optimal solution in a uncertain circumstance is not a easy task for anyone. A decision making in a uncertain circumstance is very important for every individual. In our research article, we propose a new Interval-valued possibility intuitionistic fuzzy soft set (IVPIFSS) based approach to the decision makers. The reduction algorithms are suggested for the future approaches are on choice basis and score values. We also applied the new approach on a real application as an example to demonstrate their effectiveness by solving them using MATLAB *** results are compared and discussed with the existing algorithms. © 2023 IEEE.

关键词： Decision making

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Applied Research on Attribute-Based Encryption Scheme with Two-level Encryption 3

Applied Research on Attribute-Based Encryption Scheme with T...

引用

2023 IEEE 3rd international conference on Data science and computer Application, ICDSCA 2023

作者： Ma, Zhuangjun Zhou, Shuaiyu Yu, Bohua Harbin Institute of Technology School of Marine Science and Technology Weihai China Yunnan University School of Software Kunming China Anhui University School of Internet Hefei China

ISBN: (纸本)9798350341546

This study addresses the issue of sensitive data protection in cloud computing environments and proposes a solution that combines Attribute-Based Encryption with the Rivest-Shamir-Adleman encryption algorithm to safeguard the data. The proposed solution enables efficient two-way encrypted communication using this two-level encryption approach. The advantages of this solution include enhanced access control, ensuring that only users with appropriate attributes can access the data, and strong security achieved through the combination of Attribute-Based Encryption (ABE) and Rivest-Shamir-Adleman (RSA) algorithms, effectively defending against man-in-the-middle (MITM) attacks and data leakage risks. © 2023 IEEE.

关键词： Attribute-Based Encryption cloud computing encrypted communication man-in-the-middle attacks Rivest-Shamir-Adleman

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The Role of ERNIE Model in Analyzing Hotel Reviews using Chinese Sentiment Analysis

The Role of ERNIE Model in Analyzing Hotel Reviews using Chi...

引用

2023 international conference on computer Communication and Informatics, ICCCI 2023

作者： Jie, Lee Hao Ayyasamy, Ramesh Kumar Sangodiah, Anbuselvan Jalil, Norazira Binti A Krishnan, Kesavan Chinnasamy, P. University Tunku Abdul RahmanKampar Faculty of Information and Communication Technology Malaysia Faculty of Computing and Engineering Quest International University Ipoh Malaysia Universiti Malaya Faculty of Computer Science and Information Technology Kuala Lumpur Malaysia MLR Institute of Technology Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350348217

This research aims to find the best deep learning model to do Chinese sentimental analysis. BERT's model may work well in the English language but not work in the Chinese language. English is easier to encode in embedding space, and words are separated by space characters, unlike Chinese words, which do not exist separate by the area. BERT Chinese model work on character level encoding is not enough to make the BERT model adapt to Chinese NLP tasks. The BERT Model and ERNIE models are the current state of art pre-training language models. Word level embeddings and input is needed to improve the BERT model to perform in Chinese Sentiment Analysis. With the motivation to improve the Chinese Sentiment Analysis, this study will explore the role of different models to propose a better version of the ERNIE model. This study will limit the scope to improve Chinese sentiment analysis among different NLP tasks. © 2023 IEEE.

关键词： Sentiment analysis

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Artificial Intelligence Techniques for Early Prediction of Neonatal Jaundice 4

Artificial Intelligence Techniques for Early Prediction of N...

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4th international conference on Computation, automation and Knowledge Management, ICCAKM 2023

作者： Remya, K. Ramya, R. Sadim, Mohd Kalpana, B. Amirthayogam, G. Hindustan Institute of Technology and Science India Psna College of Engineering and Technology India Ies Institute of Technology and Management Ies University Bhopal India Prince Shri Venkateshwara Padmavathy Engineering College S&h Chennai India Department of Information Technology Kelambakkam India

ISBN: (纸本)9798350393248

The potential of artificial intelligence (AI) methods for the early detection of neonatal jaundice is examined in this study, a common condition affecting newborns. Through comprehensive research, we discover that AI models, notably deep learning algorithms, exhibit remarkable accuracy in identifying neonates at risk of jaundice well before visible symptoms manifest or bilirubin levels become critically high. Early prediction is of paramount importance in neonatal jaundice, as it allows for timely interventions, reducing the risk of complications, minimizing invasive treatments, and easing emotional and financial burdens on families. The implications of this research extend to a brighter and healthier future for newborns, with AI technologies at the forefront of safeguarding their well-being from the outset of life. We also discuss potential future research directions, emphasizing the importance of data quality, generalizability across diverse populations, and ethical considerations for responsible AI implementation in neonatal care. © 2023 IEEE.

关键词： Diagnosis

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