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检索条件"任意字段=8th IEEE International Conference on Software Engineering and Computer Systems, ICSECS 2023"

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Iterative Achievable Rate Adaptive Beam Alignment for thz Communication systems 8

Iterative Achievable Rate Adaptive Beam Alignment for THz Co...

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8th international conference on Communication, Image and Signal Processing, CCISP 2023

作者： Huang, Weibin Zhang, Wenjie Wang, Chuyuan Chicese Flight Test Eatablishment Xi'an China Changsha University of Science & Technology School of Computer and Communication Engineering Changsha China

ISBN: (纸本)9798350305838

Beam alignment is a key technology to ensure reliable initial access and data transmission in thz communication systems. this paper proposes an iterative achievable rate adaptive beam alignment method which iteratively searches for the optimal codebook layers of initial training and termination training based on the achievable rate criterion. Besides, in beam training at each codebook layer, the pilot sequence length of each training codeword is adaptively adjusted based on the preset detection probability as well as false alarm probability, which significantly improves the success rate of beam alignment. In order to demonstrate the superior performance of the proposed method, comparative simulations were performed. the results show that a higher success rate has been achieved in the proposed method compared with the exist methods although the pilot cost was slightly reduced, resulting in more reliable access and higher transmission rate for the systems. © 2023 ieee.

关键词： Iterative methods

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Incorporating Multiple Relations into Multi-task Learning for Session-Based Recommendation 8

Incorporating Multiple Relations into Multi-task Learning fo...

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8th international conference on computer and Communication systems, ICCCS 2023

作者： Zeng, Yaohai Yang, Bo Gu, Jie School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9781665456128

Session-based recommendation aims to recommend the next item based on the information of sessions. there are multiple relations between items in sessions, e.g., the similar and sequential relation. How to learn these relations to effectively represent items and sessions is a major technical challenge of session-based recommendation. However, most of the existing session-based recommendation models do not distinguish the relations between items, thus difficult to learn the difference and relevance among relations. In this paper, we propose a model named MML-SR, which incorporates multiple relations into multi-task learning for session-based recommendation. In particular, we divide a session-based recommendation task into a similar relation recommendation task and a sequential relation recommendation task. the expert network layer and gate network layer are proposed to capture the representation of similar relations and sequential relations, then two proposed task towers are used to compute two recommendation results based on the similar relations and sequential relations of items in sessions respectively. We combine both recommendations results to get the final result. Experiments are conducted on three widely-used real-world datasets to evaluate the proposed MML-SR. the results demonstrate that MML-SR outperforms the state-of-the-art session-based recommendation models. © 2023 ieee.

关键词： Recommender systems

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VR-Game for Kids with Paraplegia using AI Agent Trained with PQR-DQN Techinique as Opponent 8

VR-Game for Kids with Paraplegia using AI Agent Trained with...

引用

8th international conference on Communication and Electronics systems, ICCES 2023

作者： Joypriyanka, M. Surendran, R. Saveetha Institite of Medical and Techinical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350396638

the application of artificial intelligence (AI) and virtual reality (VR) in the medical field has demonstrated encouraging potential for enhancing the quality of life of patients who suffer from physical impairments. this comprises the creation of an artificial intelligence agent that is trained in a virtual reality game using a deep reinforcement learning (DQN) algorithm. this will be used as a form of game therapy for children who have been diagnosed with paraplegia. the virtual reality game's artificial intelligence can give the child individualized feedback based on their specific skills and how far they've come in the game. As it observes visible growth over time, this can help the child build confidence and self-esteem, which is a win-win situation. this to the enhancement of the child's confidence as well as their general well-being. Multiple studies have shown that artificial intelligence-assisted game therapy is beneficial in enhancing the ability of thinking and overall quality of life of children who have been diagnosed with paraplegia. Children who took part in a virtual reality (VR) game treatment programmed using an artificial intelligence (AI) avatar exhibited significant gains in mental ability to think and their confidence level when compared to others. the usage of a virtual reality (VR) game that incorporates an AI agent that has been trained using the DQN algorithm as a form of game therapy for children who suffer from paraplegia has the potential to significantly improve the children's overall quality of life. Researchers should anticipate seeing even more creative uses of virtual reality (VR) and Artificial Intelligence (AI) in the medical and rehabilitation fields as the technology continues to advance. © 2023 ieee.

关键词： Reinforcement learning

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GAN-IVDS: An Intrusion Detection System for Intelligent Connected Vehicles Based on Generative Adversarial Networks 8

GAN-IVDS: An Intrusion Detection System for Intelligent Conn...

引用

8th international conference on Data Science in Cyberspace, DSC 2023

作者： Chen, Xiansen Xiao, Kun Luo, Lei Li, Yun Chen, Lirong School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Guangdong Weichen Information Technology Co. Ltd Dongguan China

ISBN: (纸本)9798350331035

this paper proposes an anomaly detection algorithm based on Generative Adversarial Networks (GANs) for intrusion detection in Intelligent Connected Vehicles (ICVs). To address the imbalance between normal network traffic and attack traffic in vehicular networks, as well as the difficulty in collecting attack data, we train the neural network solely with normal traffic. We employ the Gini index to perform data dimensionality reduction, selecting 34 features with the highest purity of information and enhancing model training speed via normalization functions. Our algorithm combines the generative capabilities of GANs and the reconstructive power of autoencoders, detecting abnormal network data by learning the distribution of normal network data, thus eliminating the need to analyze packet payloads and safeguarding user privacy. We also develop a vehicular network traffic data collection scheme to collect network traffic data from ICVs. Experimental results indicate that our algorithm demonstrates high accuracy in detecting anomalous network traffic in ICVs, with an accuracy rate of 94.9%. © 2023 ieee.

关键词： Anomaly Detection Algorithm Generative Adversarial Networks Intelligent Connected Vehicles Intrusion Detection Network Security

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Research on helmet detection algorithm based on android system 8

Research on helmet detection algorithm based on android syst...

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8th international conference on Information systems engineering, ICISE 2023

作者： Xie, Zheng Su, Lantao Zhang, Zhenhuan Hong, Biao Wuhan Donghu University Department of Computer Science Wuhan430200 China Meiga Polytechnic Institute Hubei Department of Information Technology Xiaogan432011 China Jilin Agricultural University College of Information Technology Changchun130118 China

ISBN: (纸本)9798350307009

Aiming at the demand of real-time detection of site helmet wearing, an artificial intelligence application based on android embedded system is designed to promote the accurate management of smart site safety. the dataset is obtained by Internet crawlers and construction site videos. Samples are divided into training set, validation set and test set in the ratio of 8:1:2. the yolov5s is used as the objective detection algorithm, and the network to be modified. After training the model is quantified, and then the model calls the interface and the lightly quantified model to improve the inference speed of the model. the accuracy of the trained model inference is 92%, the mAp is 80.4%, and the detection speed is 38s. After quantization and deployment to android system, the accuracy is 89.2 and the mAp is 87.6%. the detection speed is 19.2ms, which maximizes the detection speed under the premise of ensuring accuracy. the design helps to detect the safety helmet worn by site personnel automatically and promote the safety management of personnel at smart sites. © 2023 ieee.

关键词： Object detection

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Streamlining Attendance with Fast Face Recognition Model 8

Streamlining Attendance with Fast Face Recognition Model

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8th international conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Sundar, Koushik Ravikumar, S. Jeyalakshmi, J. Eugene Berna, I. Samuel, Prithi Citibank Na Jersey CityNJ United States Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science & Engineering Chennai India Amrita School of Computing Amrita Vishwa Vidhyapeetham Department of Computer Science and Engineering Chennai India Bannari Amman Institute of Technology Department of Artificial Intelligence and Machine Learning Erode India School of Computing Srm Institute of Science and Technology Department of Computational Intelligence Kattankulathur Campus Chennai India

ISBN: (纸本)9798350376425

Facial recognition technology has become increasingly prevalent in today's world, with applications ranging from mobile phones to banking and workplace security. this research proposes a facial recognition-based solution to replace the manual attendance tracking process, streamlining the process and reducing human error. the proposed system integrates facial recognition, registration forms, and a Redis database to automate attendance tracking. By leveraging the ML search algorithm (similarity approach) and the Insight face Python module, the system can accurately identify individuals within a database. the system's implementation involves two phases: the initial phase focuses on integrating facial recognition, registration forms, and database access. the second phase involves utilizing software such as Streamlit and Dashboard to enhance user experience and visualization. this innovative solution offers a more efficient and accurate alternative to traditional manual attendance tracking methods, improving overall efficiency and reducing administrative burdens. By automating the process, the system contributes to a more streamlined and secure environment. © 2024 ieee.

关键词： Database systems

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Research on Fusion Detection of FDI Attacks in WSNs with Privacy Preservation Under Communication Constraints 1

引用

8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Liu, Jinming Liu, Li Hu, Xin Zhang, He Leng, Kun Wang, Zengfeng School of Information and Electrical Engineering Ludong University Yantai264025 China School of Mathematics and Statistics Ludong University Yantai264025 China

ISBN: (数字)9789819603138

ISBN: (纸本)9789819603121

this paper investigates the issue of data security and false data injection (FDI) attack detection and warning speed in wireless sensor networks under bandwidth constraints. Firstly, for non-malicious and FDI attacks, a system model with privacy protection is established to ensure data security and integrity while reducing the covertness of FDI attacks for detection. Secondly, a privacy-protected residual generator is designed to capture the actual trajectory of FDI attacks, effectively identifying and distinguishing between genuine and false data. Introduce multiple quantizers with limited levels to meet communication bandwidth requirements, a convex optimization problem is formulated to design a privacy-protected FDI distributed fusion detection criterion. Subsequently, enhancing the resilience of residual signals to interference and obtain more accurate thresholds, thereby improving detection warning speed. Finally, the effectiveness of the proposed method is validated through simulation results of unmanned surface vessel (USV) navigation at maritime. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Differential privacy

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Resource Allocation Mechanism for Broadband Industrial Wireless Networks 8

Resource Allocation Mechanism for Broadband Industrial Wirel...

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8th international conference on computer and Communication systems, ICCCS 2023

作者： Chen, Yiying Wang, Hongchao Chen, Rongjun Xiang, Yuhong School of Electronic and Information Engineering National Engineering Research Center of Advanced Network Technologies Beijing Jiaotong University Beijing China

ISBN: (纸本)9781665456128

In recent years, wireless technology continues to evolve rapidly, as well as industrial wireless network. Traditional network architecture no longer meets the needs of emerging industrial scenarios. In order to meet the application requirements for high-bandwidth data transmission, a broadband industrial mesh network is proposed. It uses a mesh network structure and Orthogonal Frequency Division Multiple Access (OFDMA) as the multiple access scheme. As the industrial wireless network places high demands on network load balancing, effective resource allocation is required to meet the ever-increasing application demands and load balancing. It is still an open issue on how to balance the network load and maximize the throughput through proper resource scheduling. In this paper, a resource allocation model based on an industrial broadband wireless network is established with the goal of maximizing throughput. Based on this model, a two-stage design scheme for the resource allocation algorithm is proposed. By taking the link load ratio as a constraint, the network load balance is ensured and the throughput is maximized. Experimental results show that the performance of this algorithm is better than other throughput maximization algorithms that do not consider load balancing. © 2023 ieee.

关键词： Resource allocation

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Innovative Deep Learning Model-based Stock Price Prediction using a Hybrid Approach of CNN and Gradient Recurrent Unit 8

Innovative Deep Learning Model-based Stock Price Prediction ...

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8th international conference on Communication and Electronics systems, ICCES 2023

作者： Rao, B. Srinivasa Bhattacharya, Rajib Tiwari, Manoj Kumar Kumari, K. Aruna Devmane, Mahavir A. Singh, Kamlesh Gokaraju Rangaraju Institute of Engineering and Technology Department of Computer Science and Engineering Telangana Hyderabad India Globsyn Business School Department of Pgdm Bishnupur JL No. 101 South 24 Paganas West Bengal Chandipur India Jecrc University Department of Computer Application Rajasthan Jaipur India University Mathematics Gss Visakhapatnam India Vppcoe & Va Department of Computer Engineering Maharashtra Mumbai India Graphic Era Hill University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350396638

the fluctuation in stock prices from industry to industry are a major source of concern in the market. As the market attracts more participants and stock prices play a larger role in more transactions, the ability to accurately predict stock price movements becomes more valuable. When making an investment, many people first look at the share price and then try to anticipate whether or not that price will go up or down in the future. the traditional problem of forecasting the stock market using Machine Learning tools and methodologies has been thoroughly studied. Time dependence, volatility, and similar complicated dependencies are interesting aspects that make this modeling non-trivial. To overcome this the proposed method in this work is a deep learning-based hybrid strategy for predicting stock prices. Preprocessing is performed after input is delivered to increase precision. Selecting MPSOA features is the next step. In the end, it's put to use in MC-GRU model training. the proposed method achieves better results than both the CNN and GRU models. © 2023 ieee.

关键词： Investments

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Smart Food Box Design with IoT Based Android Monitoring System 8

Smart Food Box Design with IoT Based Android Monitoring Syst...

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8th international conference on Informatics and Computing, ICIC 2023

作者： Widiarto, Hendro Koswara, Iwan Nasution, Darmeli Wahyuni, Sri Sulistianingsih, Indri Airport Electrical Engineering Politeknik Penerbangan Indonesia Curug Tangerang Indonesia University of Pembangunan Panca Budi Department of Computer System Medan Indonesia University of Pembangunan Panca Budi Department of Computer Engineering Medan Indonesia

ISBN: (纸本)9798350342604

this research focuses on the development of a Smart Food Box with an IoT-based Android monitoring system. the system necessitates the establishment of an environmental control chamber (plant) to facilitate the operation of the Peltier controller, which comprises hardware components such as the Arduino Board, Relay, LM35 Temperature Sensor, DS1307 Real-Time Clock, $16\times 2$ Display, and a Buzzer. the software design encompasses temperature readings to determine Peltier functionality as either a heating or cooling element, while also providing time-based references for breakfast, lunch, and dinner. Based on the research findings, consumers can monitor real-time food conditions, including temperature and humidity, using an Android application that is connected to an IoT-enabled smart eating city. this innovative system enhances food preservation and access through the integration of IoT and mobile technology, offering a convenient and efficient solution for modern lifestyle demands. © 2023 ieee.

关键词： Android (operating system)

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