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intelligent Traffic Signal control System Based on Improved YOLOv8 and Deep Reinforcement Learning 6

Intelligent Traffic Signal Control System Based on Improved ...

引用

6th international conference on Frontier Technologies of Information and Computer, ICFTIC 2024

作者： Liu, Ziyuan Chen, Hongxiang Wang, Jiajie Deng, Tianqi Liu, Mingshuo Zhao, Guodong School of computer science and technology Harbin Engineering University Harbin150001 China

ISBN: (纸本)9798331541750

As urban traffic pressure continues to increase, existing traffic systems have achieved some success in improving vehicle throughput. However, they commonly face issues such as insufficient precision in visual recognition models, traffic signal control algorithms that neglect pedestrian needs, and excessive reliance on hardware infrastructure, leading to high deployment complexity. To address these challenges, an intelligent traffic system based on an improved YOLOv8 model and Deep Q-Network (DQN) algorithm is proposed. The system consists of a road dataization module and a traffic signal control module. In the road dataization module, the improved YOLOv8 model incorporates an attention mechanism to efficiently recognize vehicle information and uses OpenCV to process traffic images, enabling accurate data modeling. In the traffic signal control module, the enhanced DQN algorithm dynamically adjusts signal durations to balance the needs of pedestrians and vehicles, thereby improving traffic efficiency. Verified through the SUMO simulation platform, this approach demonstrates significant ad-vantages in optimizing traffic flow and throughput. Furthermore, by leveraging algorithmic data analysis of the environment, the system reduces dependency on hardware infrastructure, significantly lowering deployment complexity and showing strong potential for practical application. Additionally, the design of a visualized front-end interface and an embedded display system enhances the system's usability and integrity, validating its feasibility. © 2024 ieee.

关键词： Traffic signals

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Design of Distributed intelligent Waste Sorting and Dropping System Based on RS-485 19

Design of Distributed Intelligent Waste Sorting and Dropping...

引用

19th ieee international conference on Mechatronics and automation (ieee ICMA)

作者： Zhang, Fanyu Li, Jianwen Kang, Jun Zhang, Jinwei Tianjin Key Lab Control Theory & Applicat Complic Binshui Xidao 391 Tianjin 300384 Peoples R China Tianjin Univ Technol Binshui Xidao 391 Tianjin 300384 Peoples R China Tianjin Jinsheng Environm Technol Co Ltd Tianjin 300450 Tianjin Peoples R China

ISBN: (数字)9781665408530

ISBN: (纸本)9781665408530;9781665408523

In response to the problem of complicated structure and poor scalability of waste sorting and dropping systems in the market. Combined with distributed measurement and control technology, an intelligent garbage sorting and dropping system is designed. The system is based on RS-485 bus, and the framework adopts the data interaction method of one master station and multiple slave stations. The master station is mainly used for communication and data processing, and realizes humancomputer interaction with users through the touch screen;it connects to the cloud through the DTU to obtain user information and upload the points information to the cloud server after the garbage is put out, so as to fulfill the record of user's put-out information;The slave station is mainly used to control the movement of the bin door at the drop port and the acquisition of the waste weight. The experimental results show that the system operates stable and satisfies the needs of environmental protection enterprises. Compared with the traditional intelligent sorting and putting station, the system is more expandable and the free combination of the drop system is more convenient, which achieves the intelligent construction of waste separation and disposal.

关键词： Distributed measurement and control Data interaction RS-485 Embedded

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Detection and Mitigation of Attacks in MANETs: A Comprehensive Survey of Security Techniques 4

Detection and Mitigation of Attacks in MANETs: A Comprehensi...

引用

4th international conference on Ubiquitous Computing and intelligent Information systems, ICUIS 2024

作者： Mohandas, R. Sivapriya, N. Vaigandla, Karthik Kumar Kirubasankar, K. Chennai Institute of Technology Department of Electronics & Communication Engineering Tamil Nadu Chennai India Cauvery College for Women Department of Computer Applications Tamilnadu Trichy India Balaji Institute of Technology and Science Department of Electronics & Communication Engineering Telangana Warangal India

ISBN: (纸本)9798331529635

MANETs are decentralized and self-organizing networks with no fixed infrastructure. They are very flexible but, at the same time are vulnerable to the huge diversity of security threats. The dynamic topology and the lack of central control along with the reliance on wireless communication expose MANETs to several attacks, which are blackhole, wormhole, Sybil, and DoS attacks. This is a survey paper that covers the most common security threats towards MANETs and probes for different detection and prevention techniques proposed to mitigate those risks. Various methodology are examined, ranging from cryptographic methods and trust-based models to machine learning and intrusion detection systems, comparing the effectiveness, scalability, and adaptability of those approaches in different network environments. The paper further outlines some real strengths and weaknesses of the currently used solutions, indicates potential key challenges, and states the future directions that could form the way for strengthening the security capabilities of MANETs with respect to evolving emerging technologies such as 5G and beyond. The aim is to demonstrate the ongoing state of the attack detection and prevention in MANETs, thereby offering insights into promising research opportunities. © 2024 ieee.

关键词： Network intrusion

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Research on Database Construction and Assembly Path Planning Method for Key Components of Phased Array Antennas 8

Research on Database Construction and Assembly Path Planning...

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8th international conference on Electrical, Mechanical and Computer Engineering, ICEMCE 2024

作者： Chen, Minghui Jin, Chaoning Xi, Lei Han, Yong Zhou, Bo Nanchang Yanchang Electromechanical Technology Co. Ltd Jiangxi Nanchang330096 China The 39th Research Institute of China Electronics Technology Group Corporation Shaanxi Xi'an710065 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Liaoning Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Liaoning Shenyang110169 China

ISBN: (纸本)9798331506230

Compared with traditional antennas, phased array antennas with key structural components such as multi Vilvadi oscillators and grid plates have advantages such as high gain and high directional ability. Due to the need for a large number of structural components in phased array antennas, this will affect the performance and assembly accuracy of the assembled antenna. How to quickly and reasonably provide an assembly error distribution plan is the key to improving the performance of phased array antennas. This paper proposes a database based on geometric feature extraction of contact surfaces and finite element analysis of contact stress to obtain an optimized assembly plan for key components of phased array antennas, which requires the use of a large number of key components. Considering the real-time updated assembly data, a reasonable assembly path planning method was planned to avoid assembly interference. The simulation results show that this method can significantly improve assembly efficiency and provide a reasonable assembly error distribution scheme. © 2024 ieee.

关键词： Database systems

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Context-Conditional Navigation with a Learning-Based Terrain- and Robot-Aware Dynamics Model 11

Context-Conditional Navigation with a Learning-Based Terrain...

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11th European conference on Mobile Robots (ECMR)

作者： Guttikonda, Suresh Achterhold, Jan Li, Haolong Boedecker, Joschka Stueckler, Joerg Max Planck Inst Intelligent Syst Embodied Vision Grp Tubingen Germany Univ Freiburg Freiburg Germany

ISBN: (纸本)9798350307047

In autonomous navigation settings, several quantities can be subject to variations. Terrain properties such as friction coefficients may vary over time depending on the location of the robot. Also, the dynamics of the robot may change due to, e.g., different payloads, changing the system's mass, or wear and tear, changing actuator gains or joint friction. An autonomous agent should thus be able to adapt to such variations. In this paper, we develop a novel probabilistic, terrain- and robot-aware forward dynamics model, termed TRADYN, which is able to adapt to the above-mentioned variations. It builds on recent advances in meta-learning forward dynamics models based on Neural Processes. We evaluate our method in a simulated 2D navigation setting with a unicycle-like robot and different terrain layouts with spatially varying friction coefficients. In our experiments, the proposed model exhibits lower prediction error for the task of long-horizon trajectory prediction, compared to non-adaptive ablation models. We also evaluate our model on the downstream task of navigation planning, which demonstrates improved performance in planning control-efficient paths by taking robot and terrain properties into account.

关键词： Navigation

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AIEPU at ALQAC 2023: Deep Learning Methods for Legal Information Retrieval and Question Answering 15

AIEPU at ALQAC 2023: Deep Learning Methods for Legal Informa...

引用

15th international conference on Knowledge and systems Engineering, KSE 2023

作者： Hoang, Long Bui, Tung Nguyen, Chau Nguyen, Le-Minh Japan Advanced Institute of Science and Technology Ishikawa Japan Electric Power University Hanoi Viet Nam

ISBN: (纸本)9798350329742

Given the widespread integration of Artificial Intelligence across various domains, the exploration of its applications in the legal field remains understudied, emphasizing the critical need for the development of effective deep learning approaches. This paper describes on our approaches to legal information retrieval (Task 1) and legal question answering (Task 2) in the Automated Legal Question Answering Competition (ALQAC 2023). Specifically, we employed the Paraformer model for information retrieval and leveraged large language models for answering questions. In the competition, we achieved the 1st place for Task 2. In this task, our findings demonstrate that fine-tuning appropriate prompts helps the large language models to achieve better performance. Our prompts are available at https://***/DucLong06/Legal-Prompts © 2023 ieee.

关键词： Information retrieval

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Detection and Mitigation of DDoS Attack in SDN Using Feature Based SVM and Decision Tree Approach 5

Detection and Mitigation of DDoS Attack in SDN Using Feature...

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5th international conference on IoT Based control Networks and intelligent systems, ICICNIS 2024

作者： Ashwin, A. Santhosh, V. Thirupathi Venkatesh, R. Gowthami, N. Tamilselvi, S. National Engineering College Information Technology Kovilpatti India National Engineering College Electronics and Communucation Engineering Kovilpatti India

ISBN: (纸本)9798331518097

Software-Defined Networking (SDN) is an innovative network architecture that separates the control plane from the data plane, enabling centralized management and dynamic network resource configuration through software. However, the centralization of the SDN controller makes it a critical target for Distributed Denial of Service (DDoS) attacks. To effectively detect and mitigate these threats, deploying a robust machine learning-based solution is essential. This study utilized Particle Swarm Optimization (PSO) and Generalized Normal Distribution Optimization (GNDO) as feature selection techniques to extract the most relevant features from the SDN-DDoS-2020 dataset, which includes ICMP, TCP, and UDP traffic (Mendeley). The selected feature subsets were used to train and evaluate the performance of Support Vector Machine (SVM) and Decision Tree (DT) classifiers. Additionally, a dedicated mitigation framework was designed to counter flood traffic generated by TCP, UDP, and ICMP-based DDoS attacks. Among the models, the PSO-Decision Tree (PSO-DT) approach demonstrated superior performance, achieving an accuracy of 98.87% and a False Alarm Rate (FAR) of 0.7702, underscoring its effectiveness in reducing false positives and enhancing detection reliability. © 2024 ieee.

关键词： Particle swarm optimization (PSO)

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Cinnalyst: A Sales Meeting Analysis System 15

Cinnalyst: A Sales Meeting Analysis System

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15th international conference on Knowledge and systems Engineering, KSE 2023

作者： Nguyen, Hy Trinh, Phuoc Nguyen, Minh-Tien Chau, Duc Thanh Cinnamon Ai Hanoi Viet Nam Hung Yen University of Technology and Education Hung Yen Viet Nam Uninersity of Science VNU-HCM Ho Chi MinhChi Minh Viet Nam

ISBN: (纸本)9798350329742

Analysis of sales meetings is vital in many businesses to obtain insights about clients' needs and evaluate sales representatives' performance. This paper introduces a sales meeting analysis prototype, Cinnalyst, which helps sales managers observe how their employees perform in client meetings. By conducting statistics from meetings in the past, it can reveal many important factors to improve sales efficiency. To automatically analyze the sales meeting content, the proposed system includes three modules: speaking party detection, conversational topic classification, and dialogue act classification. We demonstrate the performance of Cinnalyst in practical cases where users can experience the analyses of conversational topics and dialogue acts in sales meetings. A demonstration video is attached with this paper at https://***/d7toaexlB0E. © 2023 ieee.

关键词： Sales

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Review of GPS-GSM Based intelligent Speed Assistance systems: Development and Research Opportunities 3

Review of GPS-GSM Based Intelligent Speed Assistance Systems...

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3rd international conference on intelligent Communication and Computational Techniques, ICCT 2023

作者： Ya'u Gital, Abdulsalam Abdulhamid, Mahmood Abdulhameed, Muhammed Zambuk, Fatima Umar Nehemiah, Musa Lawal, Mustapha Abdulrahman Yakubu, Zahraddeen Ismail Abubakar Tafawa Balewa University Department of Mathematical Sciences Bauchi Nigeria Abubakar Tafawa Balewa University Department of Electrical and Electronics Engineering Bauchi Nigeria Federal Polytechnic Department of Maths and Statistics Bauchi Nigeria Srm Institute of Science and Technology Chennai India

ISBN: (纸本)9781665453578

About two billion passenger cars travel the roads of the world and this is projected to double by the year 2050. This calls for the need to create real time surveillance systems to manage the impending dangers of on-road traffic and to meet the objective of intelligent transport systems (ITS). Nowadays, speed control and monitoring is mostly handled using speed law enforcement measures, such as speed bumps, speed limits, signs, speed guns, road designs, speed cameras and intelligent speed assistance (ISA). Previous surveys have not given enough attention to the application of Global Positioning System (GPS) combined with Global System for Mobile Communication (GSM) based ISA systems with respect to their types. To fill this gap, this review aims to study the different development and applications of GPS and GSM based ISA systems with the focus on their types, technology and analysis environment. Although, the development of ISA systems is not recent, the full potentials of using ISA systems are still a persistent pursuit. The study concludes by highlighting limitations and research opportunities mined from the reviewed papers to enable improvements and novel researches from the ITS research community and vehicle manufacturers' companies. © 2023 ieee.

关键词： Global positioning system

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State-of-Charge Estimation of Lithium Battery Based on Deep Residual Shrinkage Networks and a Variant Long Short Term Memory Neural Network 35

State-of-Charge Estimation of Lithium Battery Based on Deep ...

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35th Chinese control and Decision conference (CCDC)

作者： Li, Penghua Zhang, Yihui Chongqing Univ Posts & Telecommun Key Lab Intelligent Comp Big Data Coll Automat Chongqing 400065 Peoples R China

ISBN: (纸本)9798350334722

Accurate state-of-charge (SOC) estimation, which is critical to ensuring the safe and reliable operation of battery management systems in electric vehicles, is still a challenging task due to sophisticated battery dynamics and ever-changing ambient conditions. This paper proposes a method combining DRSN and ASTLSTM neural networks to estimate lithium batteries' state of charge (SOC). The proposed method can not only utilize the historical information of the data but also eliminate unimportant features by inserting soft thresholding into the deep architectures. To reveal the performance of the proposed method, the results are compared with several other methods from the literature. The comparative experimental results show that the proposed method achieves a lower root mean square error (RMSE) of 0.83% with normal data and RMSE of 0.98% with noisy data, respectively.

关键词： Lithium Battery State of Charge Recurrent Neural Network Deep Residual Shrinking Network

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