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An Energy Efficient Power Allocation Method for NOMA-Based VLC systems 12

An Energy Efficient Power Allocation Method for NOMA-Based V...

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12th international conference on intelligent computing and Wireless Optical Communications (ICWOC)

作者： Wu, Yali Li, Xiaojuan Sun, Lei Lin, Xiaoran Hebei Univ Econ & Business Inst Informat Technol Shijiazhuang Hebei Peoples R China

ISBN: (纸本)9798350374377

We present an optimal power allocation method to improve the energy efficiency (EE) of visible light communications (VLC) based on non-orthogonal multiple access (NOMA). The EE optimization model is established under the constraints of minimum data rate, maximum transmission power, successive interference cancellation (SIC) and direct current (DC) bias of the multiplexing light-emitting diodes (LEDs). Then an iterative power allocation algorithm is proposed to exploit the solution of the EE optimization problem. The simulation results show that the proposed power allocation algorithm can significantly improve the system EE.

关键词： visible light communication non-orthogonal multiple access energy efficiency power control group strategy

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Privacy Preserving Attribute based Access Control with data Deduplication using RSA-BLAKE3-OCO for Secure Cloud Storage 1

Privacy Preserving Attribute based Access Control with Data ...

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1st international conference on intelligent systems and Computational Networks, ICISCN 2025

作者： Gayathri, G.N. Channakrishnaraju Sri Siddhartha Academy of Higher Education Department of Computer Science and Engineering Tumkur India

ISBN: (数字)9798331529246

ISBN: (纸本)9798331529246

Nowadays, cloud storage is one of the popular application models in various fields, where the security and access permission of storage data are widely considered. De-duplication algorithms are designed to mitigate redundant storage of data in the cloud. However, the main problem was data duplication which occupied the storage in many cloud storage systems that require an appropriate data security model. To overcome this problem, Rivest-Shamir-Adleman (RSA) - BLAKE3 based Optimal Cache Oblivious (OCO) demonstrates ensured access and privacy while removing the duplicates in cloud computing. The combination of RSA and BLAKE-3 is used to maintain efficient attribute exchange and prevent data leakage and privacy violations. In addition, the OCO technique is used to hide the access pattern in the cloud storage and copy the data by matching the random pattern. This process ensures data privacy and secure data sharing in cloud storage by avoiding data corruption. The result analysis clearly shows that the proposed RSA-BLAKE3-OCO attains a communication overhead of 11MB, a data integrity rate of 93% and a data confidentiality rate of 95% from 50 files which is better when compared with the existing methods. © 2025 ieee.

关键词： data integrity

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Distance Impact on Collaboration Quality in Smart Glasses Applications

Distance Impact on Collaboration Quality in Smart Glasses Ap...

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ieee international Workshop on intelligent data acquisition and advanced computing systems: Technology and Applications

作者： Amal Yassien Abdelkareem Tarek Slim Abdennadher German International University in Cairo Egypt German University in Cairo Cairo Egypt

This research investigates the effect of the distance between users within the virtual space on collaboration quality in social smart glasses based virtual environments. We developed a Vuzix smart glasses application to enable users to work together on assembling furniture models. Afterwards, we conducted a user study to assess the impact of distance between users on collaboration quality, and the results showed that distance significantly affects collaboration quality. Our prototype could be used as a remote aftersale service, and our findings could aid in designing low-cost Smart Glasses social solutions for productive teamwork.

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Research of Facial Recognition systems and Criteria for Identification

Research of Facial Recognition Systems and Criteria for Iden...

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ieee international Workshop on intelligent data acquisition and advanced computing systems: Technology and Applications

作者： Mariia Nazarkevych Agnieszka Kowalska-Styczeń Vasyl Lytvyn Lviv Polytechnic National University Lviv Ukraine Faculty of Organization and Management Silesian University of Technology Zabrze Poland

Biometric security systems are rapidly developing and becoming widespread. The purpose of the research is to develop a system for recognizing a person's face, since these are contactless identification systems and this topic is particularly relevant. Video surveillance systems have become widespread, where it is often necessary to identify a person. A face identification method that works in video surveillance systems is proposed. Experiments were conducted with selfies, portraits and documentary photography. The developed method captures a person's face, saves it, and then goes into recognition. A method for recognizing human eyes based on the method of Sherlock and Monroe has been developed.

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data-Driven Channel acquisition with Pilot Decontamination in IRS-Aided Communication systems 59

Data-Driven Channel Acquisition with Pilot Decontamination i...

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59th Annual ieee international conference on Communications (ieee ICC)

作者： Haider, Majumder Ahmed, Imtiaz Hassan, Md. Zoheb Matin, Mohammad Pu, Cong Howard Univ Dept Elect Engn & Comp Sci Washington DC 20059 USA Univ Laval Dept Elect & Comp Engn Quebec City PQ Canada Univ Denver Dept Elect & Comp Engn Denver CO USA Oklahoma State Univ Dept Comp Sci Stillwater OK USA

ISBN: (纸本)9798350304060;9798350304053

This paper aims to enhance the cascaded channel estimation process of intelligent reflecting surface (IRS)-aided communication systems while considering the detrimental effect of pilot signal contamination. When the transmitter is equipped with massive multiple-input multiple-output (mMIMO) antennas, and the IRS consists of a large number of reflecting elements, it is practically infeasible to allocate orthogonal pilots over each cascaded link, each consisting of a pair of antenna and reflecting elements. Reusing pilot signals over multiple parallel cascaded links causes interference, known as pilot contamination. Severe pilot contamination deteriorates the accuracy of the channel estimation process significantly. Accurate estimation of high-dimensional cascaded channels of IRS is crucial to distribute narrow beams in the desired direction, which becomes even more cumbersome in the presence of pilot contamination. To address this challenge, we propose deep learning-empowered two approaches to accurately estimate the channel gains of the cascaded links. Subsequently, learning from the correlation of the estimated cascaded links, we predict the cascaded links for other reflecting elements. Simulation results demonstrate the improved performance of the proposed techniques over the baseline schemes.

关键词： IRS cascaded channel estimation pilot contamination deep learning B5G

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Development of intelligent Fault Early Warning System for Substation Integrating Satellite Remote Sensing and Ground Monitoring 3

Development of Intelligent Fault Early Warning System for Su...

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3rd international conference on data Analytics, computing and Artificial Intelligence, ICDACAI 2024

作者： Tian, Yuewei Dai, Wenju Wu, Xiaoyao Shi, Lintao Zhao, Yongqiang Zou, Wenqiang Guiyang Power Supply Bureau of Guizhou Power Grid Co. Ltd. Guizhou Guiyang563000 China China Southern Power Grid Technology Co. Ltd. Guangdong Guangzhou510000 China

ISBN: (纸本)9798331519032

In this paper, an intelligent fault early warning system of substation integrating satellite remote sensing and ground monitoring technology is proposed and developed, aiming at improving the safety and stability of substation operation. The system architecture is designed as four layers, including data acquisition layer, data processing and fusion layer, fault early warning layer and user interaction layer. The data acquisition layer is responsible for collecting satellite remote sensing images and ground monitoring data;The data processing and fusion layer preprocesses, extracts and fuses the original data to improve the data quality. Fault early warning layer uses machine learning algorithm to build fault early warning model, and automatically identifies and predicts potential faults;The user interaction layer displays the early warning information in real time through the graphical interface, and provides visual fault analysis results. The fault early warning model based on ensemble learning adopts random forest algorithm and introduces weighted voting mechanism, which improves the accuracy and stability of prediction. Case analysis shows that the system has significantly improved the accuracy and timeliness of fault early warning in practical application, from 85.234% to 96.789%. The research results show that the intelligent fault early warning system of substation integrating satellite remote sensing and ground monitoring can overcome the limitations of traditional technology, realize comprehensive, real-time monitoring and efficient early warning of substation operation state, and provide strong support for the stable operation of power system. © 2024 ieee.

关键词： Random forests

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Economical Electricity Supplement for Mobile Collectors in Large-Scale Multitask WSNs 21

Economical Electricity Supplement for Mobile Collectors in L...

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21st ieee international Symposium on Parallel and Distributed Processing with Applications, 13th ieee international conference on Big data and Cloud computing, 16th ieee international conference on Social computing and Networking and 13th international conference on Sustainable computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Zhai, Xin Xu, Lijie Zhang, Jialei Wang, Kun Xu, Jia Xu, Bei Nanjing University of Posts and Telecommunications Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing210023 China

ISBN: (纸本)9798350329223

For large-scale multitask wireless sensor networks (LSM-WSNs), the traditional data collection mode could suffer low energy-efficiency on data transmission, since the large-scale multitask scenarios could result in much higher packet collision probability, especially for harsh environments. Mobile data collection is an efficient data acquisition way to prolong network lifetime for LSM-WSNs. However, the mobile collectors could suffer electricity shortage problem, since the limited battery capacity of any mobile collector could not afford the energy consumption of its long-distance movement and massive data collection in large-scale multitask scenarios. Deploying wireless chargers to supplement the energy of mobile collectors is a feasible solution to electricity shortage problem, but will incur extra charger deployment cost. In this paper, we focus on the problem that how to optimize such charger deployment cost, which is NP-hard. By transforming it into minimum-cost submodular cover problem, we devise an efficient approximation algorithm with a provable approximation ratio. The extensive simulation results reveal that our solution always outperforms the other solutions under whatever configurations. © 2023 ieee.

关键词： Wireless sensor networks

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Enhancing data Security in Cloud-Based Soil Carbon Sequestration Monitoring systems Using Random Forest Regression

Enhancing Data Security in Cloud-Based Soil Carbon Sequestra...

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2024 international conference on intelligent systems for Cybersecurity, ISCS 2024

作者： Chandrakala, D. Ranganathan, Chitra Sabapathy Swarnalatha, E. Karpagalakshmi, R.C. Meenakshi, B. Srinivasan, S. Easwari Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Mphasis Corporation Tamil Nadu Chennai India Guru Nanak Institute of Technology Department of Electronics and Communication Engineering Hyderabad Telangana Ibrahimpatnam India Alliance College of Engineering and Design Alliance University Karnataka Bengaluru India Sri Sairam Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Biomedical Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350375237

The evaluation of the protections of soil carbon sequestration monitoring technique using cloud computing and machine learning. The implementation of these systems is essential for development of agricultural industry that is friendly to the environment for reducing the effect on the environment. As a consequence of recent developments in technology, including cloud computing, these surveillance systems are now far more effective than they were before. However, the storing of data on the cloud creates worries over the security of the data. Using Random Forest Regression (RFR) it potential these difficulties. Through the use of this method, the potential to improve the safety of data collection is utilized. With the examination of patterns within the data that has been collected to identify possible security. The capabilities of ensemble learning are responsible for the improved consistency and precision with which it operates. According to the findings of the studies, this method makes the process of collecting and analyzing data on soil carbon more secure. For maintaining confidentiality this is beneficial for both environmentally responsible farming and sustainable agriculture. © 2024 ieee.

关键词： Intrusion detection

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Proceedings - 2024 ieee 20th international conference on intelligent Computer Communication and Processing conference, ICCP 2024

Proceedings - 2024 IEEE 20th International Conference on Int...

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20th ieee international conference on intelligent Computer Communication and Processing conference, ICCP 2024

ISBN: (纸本)9798331539979

The proceedings contain 58 papers. The topics discussed include: policy transfer with maximum entropy deep reinforcement learning for real cart-pole control;COR-MP: conservation of resources model for maneuver planning;improved grapes detection and tracking in drones imagery by integrating the coordinate attention mechanism;optimization methods of deep neural networks on automotive embedded computing systems;6D pose estimation of unseen objects for industrial augmented reality;self-sovereign identity system using blockchain and smart contracts;a novelty real-time gesture recognition model for air-hand piano playing using MediaPipe;classifying emotional states using data collected from wearable devices;and navigating the labyrinth: the mixed Chinese postman problem and its SLAM algorithm application.

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IoT based intelligent systems for Vehicle 2

IoT based Intelligent Systems for Vehicle

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2nd international conference on intelligent data Communication Technologies and Internet of Things, IDCIoT 2024

作者： Vishnu Kumar, P. Ali, Adnan Sha, Akula Zaheer Rajesh, Siddem G. Pullaiah College of Engineering and Technology Department of Internet of Things Andhra Pradesh Kurnool India

ISBN: (纸本)9798350327533

This paper introduces an intelligent vehicle system implemented through Internet of Things (IoT) technology, employing various sensors for comprehensive vehicle monitoring. The ESP32 microcontroller processes sensor data and manages the system's actuators. The system focuses on enhancing vehicle safety by detecting drunk driving, accidents, and driver fatigue. Recent techniques, including machine learning algorithms for improved detection accuracy and edge computing for real-time processing, are explored. Challenges faced by such systems, such as sensor calibration, data accuracy, and the integration of complex algorithms, are acknowledged. Despite these challenges, real-world evaluations confirm the system's effectiveness in identifying instances of drunk driving, accidents, and driver fatigue. The system consistently delivers real-time vehicle tracking information and antitheft alerts. The proposed intelligent vehicle system aims to address these challenges and significantly improve vehicle safety and convenience. It is designed to be innovative, cost-effective, and user-friendly, making it a valuable asset for any driver. © 2024 ieee.

关键词： Accident Alert Alcohol Detection Driver Fatigue Detection Internet of Things (IoT) Technology Post-crash Assistance Real-time Vehicle Tracking Safety Innovation Seat-Belt Alert Vehicle Safety Monitoring

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