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Security Challenges and Future Privacy Perspectives in Cloud computing for Smart City Environments

Security Challenges and Future Privacy Perspectives in Cloud...

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2023 international conference on Power Energy, Environment and Intelligent control, PEEIC 2023

作者： Tayal, Ankit Bhatia, Gaurav Singh, Jay Bansal, Mohit Anitha, G. Gl Bajaj Institute of Technology & Management Electrical Engineering Department Gr. Noida India Gl Bajaj Institute of Technology & Management Computer Application Department Gr. Noida India Institute of Aeronautical 5Engineering Department of Computer Science and Information Technology Hyderabad India

ISBN: (纸本)9798350357769

The context of smart cities and cloud computing is essential to understanding the broader landscape in which security challenges and privacy perspectives play pivotal roles in enhancing the quality of life for the residents in smart cities. Smart cities use information and communication technologies (ICT) to optimize resource efficiency. They leverage data, sensors, and connectivity to improve various aspects of urban living, including transportation, energy usage, public services, and sustainability. Cloud computing is an integral part of the infrastructure of smart cities that enables the collection, storage, analysis, and sharing of data and services. This research paper indicates many factors and challenges in the development of cloud-enabled smart city areas and provides potential recommendations. A guideline for future studies on this research topic has also been provided to serve the comparative analysis of the various findings and results. © 2023 IEEE.

关键词： Cloud computing Cyber Security Data computing Internet of Things (IoT) Smart City

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Robust control of Linear Systems: A Min-Max Reinforcement Learning Formulation

Robust Control of Linear Systems: A Min-Max Reinforcement Le...

引用

international conference on electrical engineering, computing science and automatic control (CCE)

作者： Juan Alejandro Flores-Campos Adolfo Perrusquía UPIITA-IPN Instituto Politécnico Nacional Mexico City Mexico School of Aerospace Transport and Manufacturing Cranfield University Bedford UK

In this paper, an online robust controller based on a min-max reinforcement learning approach for linear systems is discussed. Disturbances are represented by external signals coupled with the control input which are assumed to be bounded within a set of admissible disturbances. The proposed controller implements a min-max approach which realizes a smooth transition between optimal and robust controllers. Lyapunov stability theory is used to assess the stability and boundedness of the min-max robust formulation. A neural reinforcement learning architecture is used to obtain an approximation of the parameters associated to the optimal cost. Simulations are carried out to validate the proposed approach.

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A Sustainable Privacy-Preserving Aggregation Authentication Protocol for Smart Grid 1

引用

2nd international conference on Smart Grid Energy Systems and control, SGESC 2023

作者： Chaudhary, Dharminder Soni, Tanmay Singh, Soumyendra Durgarao, M.S.P. Gupta, Surisetty Mahesh Chandra Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India

ISBN: (数字)9789819976300

ISBN: (纸本)9789819976294

Smart grid (SG) is an advanced framework for controlling computers, automation, new technologies, and smart equipment that is more efficient and dependable. Smart grid possesses advanced self-healing capabilities and enables electricity customers to become active participants. Both security and privacy are two very important attributes of SG communication. The proposed model is efficient for communication between smart grids which uses a privacy-preserving aggregation mechanism. The model structure uses super increasing sequences to organize data and then encrypts it using the homomorphic Paillier approach. Data aggregation is done directly on cipher at local gateways without following any decryption for data transfers from users to smart grid operation center. The aggregate outcome of the source data may be accessed at the operation center that saves time. Finally, our findings demonstrate that the proposed method supports batch verification that makes it cost-effective in terms of computing and communication as compared to existing architectures. The proposed design is fast symmetric encryption, and it is suitable for massive user groups, and it can be adopted to support the flexible and rapid growth of residential scales in smart grids. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Smart power grids

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Urological Condition Simulator for Accurate Uroflowmeter Calibration and Testing

Urological Condition Simulator for Accurate Uroflowmeter Cal...

引用

international conference on electrical engineering, computing science and automatic control (CCE)

作者： Maria Lesvia Escobar-Hernández Jesús Fausto Córdova-Manzo Daniel Acosta-Mares Jesús Fausto Córdova-Escobedo Arturo Vera-Hernández Lorenzo Leija-Salas Josefina Gutiérrez-Martínez Electrical Engineering Department Bioelectronics Section CINVESTAV-IPN Mexico City Mexico Electrical Faculty Universidad Veracruzana Campus Coatzacoalcos Coatzacoalcos Veracruz Mexico Division for Medical Engineering Research Instituto Nacional de Rehabilitación LGII Mexico City Mexico

ISBN: (数字)9798350377545

ISBN: (纸本)9798350377552

This project describes the development of a urological condition simulator designed to test uroflowmeters. The simulator reproduces various urological conditions by programming voltage sequences to control a pump, thus mimicking specific urinary flow patterns. The main conditions simulated are benign prostatic obstruction (BPO), overactive detrusor, urethral stricture and underactive detrusor. Each condition is modeled using parameters such as maximum flow velocity, mean flow velocity and flow duration. Using an ESP32 microcontroller, the system generates tailored voltage sequences that produce accurate and reproducible urinary flow patterns. The results demonstrate the successful generation of voltage sequences corresponding to each urological condition, allowing for consistent simulation of the flow characteristics. This method provides a reliable tool for the standardized testing and calibration of uroflowmeters, ensuring their accuracy in clinical diagnostics and monitoring of urological conditions.

关键词： Accuracy Microcontrollers Programming electrical engineering computing Reliability engineering Calibration Voltage control Monitoring Testing

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Research on ceramic battery core defect detection device based on PLC

Research on ceramic battery core defect detection device bas...

引用

2024 international conference on Automation control, Algorithm, and Intelligent Bionics, ACAIB 2024

作者： Zhang, Jinxing Zhang, Jianfeng Feng, Hailin Wu, Jian College of Mathematics and Computer Science Zhejiang Agricultural and Forestry University 311300 China College of Optical Mechanical and Electrical Engineering Zhejiang Agricultural and Forestry University Hangzhou311300 China Zhejiang Zhen Tai Energy Technology Company Limited Lishui321400 China

ISBN: (纸本)9781510682597

To address the issues of high labor intensity and high misjudgment rate in manual inspection of surface defects on ceramic cores in high-temperature fuel cells, this study has designed a PLC-based automatic defect detection device. Central to the device is the recognition algorithm that employs Visual C++ and Halcon machine vision library, with PLC as the main controller and DOP-107BV touch screen as the interactive interface. Therefore, it achieves flexible control of software and hardware through the allocation of I/O addresses. Experimental results demonstrate that the system boasts fast response speed and high efficiency, with a surface defect detection accuracy exceeding 93%, significantly improving detection accuracy and efficiency. Compared to manual inspection, the overall accuracy has increased by more than 2.43%, with significant improvements in all aspects of performance. This research is of great significance for the progression of intelligent inspection methodologies, thereby enhancing overall quality control and indicating extensive potential for real-world applications. © 2024 SPIE.

关键词： Touch screens

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Pitch Angle Centralized Optimization Strategy for Wind Farm considering Fluctuation Range of Wind Speed of Nonpitch Regulation 4

Pitch Angle Centralized Optimization Strategy for Wind Farm ...

引用

4th international conference on electrical engineering and control science, IC2ECS 2024

作者： Wang, Siyuan Xu, Chang Zhao, Dawei Wang, Xiaoya Nanjing University of Science and Technology School of Automation Nan Jing China

ISBN: (纸本)9798331510107

With the increasing proportion of wind power integrated into the grid, wind turbines need to accurately respond to power commands issued by the grid and actively participate in the automatic generation control. To reduce the drastic pitch angle change triggered by frequent touching of the rotor speed boundary in the process of wind turbines responding to power commands, the existing researches have proposed the fluctuation range of wind speed of nonpitch regulation, which makes the rotor speed within the variable speed range as much as possible by proactively setting the reference of pitch angle to match the predict wind speed fluctuation. However, the above studies are limited to the independent optimization at the turbine aspect, and when they are applied to wind farm, the additional pitch angle action will still occur in some turbines due to the wake effect. To address this problem, this paper firstly analyses the mismatch between the corresponding fluctuation range of wind speed of nonpitch regulation and the actual wind speed when each turbine is optimized independently due to neglecting the wake effect between the upstream and downstream turbines. And this is the key reason why the existing methods still have large pitch angle action when applied to wind farm. On this basis, this paper proposes a pitch angle centralized optimization strategy based on the improved sparrow search algorithm to determine the pitch angle set of all wind turbines that minimize the amount of pitch angle action of the wind farm. The effectiveness and superiority of centralized optimization are illustrated by the Matlab/Simulink case. © 2024 IEEE.

关键词： Wind turbines

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Research on Lane Changing Strategy for Automated Vehicles Basing on Vehicle-in-the-Loop System 6

Research on Lane Changing Strategy for Automated Vehicles Ba...

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6th IEEE international conference on Automation, Electronics and electrical engineering, AUTEEE 2023

作者： Wang, Qiang Wang, Yindong Hou, Quanshan Wu, Xiaomeng Meng, Jiaxu Shan, Yingjie Sun, Bohua Catarc Intelligent and Connected Technology Co. Ltd. China Automotive Technology & Research Center Co. Ltd. Tianjin China Jilin University State Key Laboratory of Automotive Simulation and Control Changchun China

ISBN: (纸本)9798350305623

As one of the core technologies of automatic driving, the decision-making module plays a crucial role in the safety of automatic driving. In this paper, a fuzzy logic based automatic driving lane changing strategy is proposed to fuzzy the time to collision and distance coefficients by introducing a safe distance model. Fuzzy rules are established based on expert experience to get the fuzzy output of lane changing willingness, which in turn forms the lane changing decision of the self-driving vehicle. The strategy has strong adaptability and practicality, effectively handles various complex traffic scenarios, and improves the safety and comfort of self-driving vehicles. In this study, a lane-changing scenario is designed in the virtual simulation software, and the vehicle-in-the-loop test platform is utilized for experimental verification. The test results prove that the automatic driving lane changing strategy enables the vehicle to make reasonable lane changing decisions in different traffic scenarios, avoids collision risks, and improves driving comfort. © 2023 IEEE.

关键词： Automated Vehicle Lane Changing Strategy Vehicle-in-the-Loop

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A Review on Environmental Sustainability Using Machine Learning Applications 5

A Review on Environmental Sustainability Using Machine Learn...

引用

5th international conference on IoT Based control Networks and Intelligent Systems, ICICNIS 2024

作者： Nirmala, E. Yadav, Manish Naveen, Palanichamy Maragatharajan, M. Suresh, M. Bhargava, Pranjal School of Computing Science and Engineering VIT Bhopal University Madhya Pradesh Kothri Kalan India School of Computing Science Engineering and Artificial Intelligence VIT Bhopal University Madhya Pradesh Kothri Kalan India KPR Institute of Engineering and Technology Department of Electrical and Electronics Engineering Tamil Nadu Coimbatore India

ISBN: (纸本)9798331518097

Environmental sustainability reduces the destruction of natural resources in the hands of mother earth for next generation. Due to the development of cities and its social and economic factors leads the major role of any such destruction. It affects huge volume of biological system in terms of environmental pollution, change in climate and respective population growth. Henceforth, the general population is severely affected with their quality of life in the present scenario. This research study discusses about various resources that are affected severely due to the environmental factors have stated with the proven evident. Along with this various prediction technology using machine learning procedures are discussed in detail to prevent any such destruction by improving the present style of work. The prediction of any such destruction exploiting resources like land, water, mineral and planetaries creates its impact in the form of climatic changes, as a result of this we are facing drought, earthquakes and landslide. Apart from preventing techniques over plantation of greeneries, it is necessary to implement techniques towards efficient use of resources Monitoring is essential features. All these things are now essentially managed with the help of computer aided technology. Further the effective usage of environmental factors results into safe future for the next generation. This can be achieved by using AI with SUV to increase the prediction accuracy. Further this article is directed towards future direction to prevent and use the natural resources is discussed for the benefit of population around the world. © 2024 IEEE.

关键词： Climate change

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Double Replay Buffer Mechanism for Deep Reinforcement Learning Algorithm 4

Double Replay Buffer Mechanism for Deep Reinforcement Learni...

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4th international conference on Electronic Information engineering and Computer science, EIECS 2024

作者： Ji, Yiwei Le, Weixuan Tian, Xiumei Liu, Guangming Han, Longzhe Cui, Tao Nanchang Institute of Technology Nanchang Key Laboratory of IoT Perception and Collaborative Computing for Smart City Nanchang China School of Electrical and Electronic Engineering Changchun University of Technology Changchun China

ISBN: (纸本)9798331531409

Deep Reinforcement Learning (DRL) has emerged as a highly promising area of research within the fields of artificial intelligence and machine learning. However, the conventional experience replay mechanism employed in DRL typically utilizes a uniform sampling method, which fails to account for the varying importance of different samples. This oversight can result in suboptimal sample utilization and low learning efficiency. To address these limitations, this paper proposes a double experience replay buffer mechanism. The proposed approach adaptively adjusts the experience pool ratio through the Q-learning algorithm and leverages the Upper Confidence Bound (UCB) method to calculate sample priorities. Furthermore, we design a hybrid sampling strategy to increase the selection rate of high-value samples, and enhance overall learning performance. To validate the effectiveness of this approach, comprehensive experiments were conducted across several Gym control tasks. The experimental results demonstrate the improvements in learning efficiency and performance. © 2024 IEEE.

关键词： Deep reinforcement learning

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Big Data Graph Node Importance Using Page Rank 1

Big Data Graph Node Importance Using Page Rank

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1st international conference on Innovations in Communications, electrical and Computer engineering, ICICEC 2024

作者： Roseline, R. Vasudevan, B. Clementking, A. Rani, S. Sivakumar, T. Srinivasan, C. PG Department of Computer Applications Cuddalore India SRM Institute of Science and Technology Department of Electronics and Communication Engineering Kattankulathur India Karnataka Bengaluru India Department of BCA/IT Tamil Nadu Chennai India Sri Eshwar College of Engineering Department of Computer Science and Engineering Tamil Nadu Coimbatore India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350376517

Improving the efficiency and accuracy of finding important nodes in large networks is the goal of enhancing Big Data graph node significance analysis using PageRank. To deal with the massive and complicated data sets seen in big data settings, it is necessary to modify and enhance the PageRank algorithm. The objective is to provide a more efficient framework that can speed up computation and improve the accuracy of significance ranking in large-scale networks. To control the algorithm's scalability, it is necessary to use state-of-the-art computational methods, such as parallel processing and effective data structures. The expected result is a scalable and reliable system that can quickly and correctly analyze large networks, yielding useful insights for applications like recommendation systems, online search, and social network analysis. The focus is on making PageRank more feasible for use in large data settings while also increasing its computing efficiency and scalability. The Adjacency Matrix of the Graph in a sample of 5 nodes has a value ranging from 15 to 55 in numbers, according to results from synthetic graph data. In another instance of the same dataset, the Initial PageRank Scores range from 0.2-0.15 in numbers, and in yet another instance, the final PageRank Scores for nodes range from 0.177 to 0.242 in numbers. © 2024 IEEE.

关键词： Data accuracy

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