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Computational, Communication and Information technology (ICCCIT), International Conference on

作者： Bhavesh Suthar Syed Ibad Ali Aritificial Intelligence& Data science Parul University Faculty of Engineering & Technology Vadodara Gujarat

ISBN: (数字)9798331512965

ISBN: (纸本)9798331512972

This study examined the research on the project investigates the integration of sign language into a hand gesture recognition system that relies on vision. the review's findings indicate that the field of The study of hand gesture recognition using eyesight is dynamic, with several investigations carried out and dozens of articles published yearly in journals and conference proceedings. Three crucial elements of the vision-based hand gesture recognition system, notably hand gesture representation, were the focus of the majority of these *** learning methods with an Arduino Leonardo for hand gesture recognition. An accelerometer sensor on the Arduino Leonardo records dynamic hand movement data. After being sent to a computer, this sensor data is processed by a deep learning model that has been trained to identify particular motions. I practice word-by-word modeling rather than two-word, two-line training.

关键词： Hands Training Surveys Learning systems Deep learning Sign language Computational modeling Dynamics Nearest neighbor methods Information and communication technology

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Smart Farming: Intelligent Animal Detection Framework in Agriculture using IoT Sensors 2

Smart Farming: Intelligent Animal Detection Framework in Agr...

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2nd International Conference on Edge Computing and Applications, ICECAA 2023

作者： Priyanka, S. Suje, S.A. Selvapandian, D. Narasimharaj, V. Sns College of Engineering Department of Information Technology Coimbatore India Sns College of Engineering Department of Artificial Intelligence and Data Science Coimbatore India Karpagam Academy of Higher Education Department of Computer Science and Engineering Coimbatore India Sri Krishna College of Engineering and Technology Department of Mechatronics Engineering Coimbatore India

ISBN: (纸本)9798350347579

Agriculture, the study and practice of plant cultivation, is crucial to the development of a subsistence farming economy. In India, farming supports more than half of the population. The agricultural sector's expansion has been severely hampered by obstacles. Ineffective crop management and crop raiding by external sources, notably human-wildlife conflict, provide the greatest challenge to farmers. Intricately highlighted by means of integrated systems is a cumulative strategy that employs Internet-of-Things (IoT) and conventional farming practices, as well as barriers to prevent crop destruction. A device that can detect the occurrence of a little alive object using a PIR Sensor or an Ultrasonic Sensor, particularly creatures, fenced terrestrial to be cultivated, this module aims to make agriculture smart. This module also proposes smart irrigation control and real-time data analysis. The GSM Module can send this information as text messages, or the Blynk software can be used to visualize it. The suggested system includes animal identification and a laser security system to minimize noise pollution from animals. Multiple issues have been addressed to aid the farmer in fixing them all at once. © 2023 IEEE.

关键词： Internet of things

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Hybrid Security Enhancement of ECC with Side Channel And Sign Fault Attack Countermeasures

Hybrid Security Enhancement of ECC with Side Channel And Sig...

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2022 International Telecommunications Conference, ITC-Egypt 2022

作者： Souror, Walid W. Fouad, Mohamed Takieldeen, Ali E. Electronics and Communication Department Engineering Zagazig Egypt IEEE Faculty of Artificial Intelligence Delta University for Science and Technology Egypt

ISBN: (数字)9781665488082

ISBN: (纸本)9781665488082

The research presents the elliptic curve algorithm in addition to measures and countermeasures for Sign Change Fault attacks (SCF) and side-channel attacks (SCA) on the elliptic curve algorithm (ECC). The attack and countermeasures are studied in the ambience of exact projective coordinates and ECC on the main fields. The combination between countermeasures both SCF Attacks and SCA on ECC is envisioned to potency the device to discharge objects on a curve that is coded weakly. The research presents the enhancement of security of hybrid-ECC for defending against types of attacks. In elliptic curve cryptography, side-channel attacks take place when data is unintentionally leaked while being processed. Calculating n∗P, where n is a positive integer and P is a point on the elliptic curve E, is a crucial operation. The binary algorithm's implementations may show whether P + Q is calculated for P=6∗Q or P=Q, depending on the circumstances. There are many solutions that have been proposed for this issue. Here, we outline a generic method for creating a variety of representations of the points on E with characteristic p ≥ 5, each with a consistent application of P+Q. For each n∗P computation, the parametrization can be modified effectively for free. It works with all elliptic curves. Hence, all others ECC included in the current and future standards for p ≥ 5 may be used with them. In characteristic p ≥ 5. © 2022 IEEE.

关键词： Side channel attack

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Discounted Iterative Adaptive Critic Designs With Novel Stability Analysis for Tracking Control

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1262-1272页

作者： Mingming Ha Ding Wang Derong Liu School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing 100083China Faculty of Information Technology the Beijing Key Laboratory of Computational Intelligence and Intelligent Systemthe Beijing Laboratory of Smart Environmental Protectionand the Beijing Institute of Artificial IntelligenceBeijing University of TechnologyBeijing 100124China Department of Electrical and Computer Engineering University of Illinois at ChicagoChicago IL 60607 USA IEEE

The core task of tracking control is to make the controlled plant track a desired *** traditional performance index used in previous studies cannot eliminate completely the tracking error as the number of time steps *** this paper,a new cost function is introduced to develop the value-iteration-based adaptive critic framework to solve the tracking control *** the regulator problem,the iterative value function of tracking control problem cannot be regarded as a Lyapunov function.A novel stability analysis method is developed to guarantee that the tracking error converges to *** discounted iterative scheme under the new cost function for the special case of linear systems is ***,the tracking performance of the present scheme is demonstrated by numerical results and compared with those of the traditional approaches.

关键词： Adaptive critic design adaptive dynamic programming(ADP) approximate dynamic programming discrete-time nonlinear systems reinforcement learning stability analysis tracking control value iteration(VI)

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Rooted Tree Optimization for Wind Turbine Optimum Control Based on Energy Storage System

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Computers, Materials & Continua 2023年第2期74卷 3977-3996页

作者： Billel Meghni Afaf Benamor Oussama Hachana Ahmad Taher Azar Amira Boulmaiz Salah Saad El-Sayed M.El-kenawy Nashwa Ahmad Kamal Suliman Mohamed Fati Naglaa K.Bahgaat Department of Electrical Engineering Badji Mokhtar UniversityLSEM LaboratoryAnnaba23000Algeria Department of Electrical Engineering Biskra UniversityLGEB LaboratoryBiskra07000Algeria Department of Drilling and Rig Mechanics Ksadi Merbah UniversityOuargla30000Algeria College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Faculty of Computers and Artificial Intelligence Benha UniversityBenha13518Egypt Department of Electronics University of Badji MokhtarLERICA LaboratoryAnnaba23000Algeria Delta Higher Institute for Engineering&Technology(DHIET) Mansoura35511Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Faculty of Engineering Cairo UniversityGiza12613Egypt Department of Communications and Electronics Engineering Faculty of EngineeringCanadian International College(CIC)ElShiekh ZayedEgypt

The integration of wind turbines(WTs)in variable speed drive systems belongs to the main factors causing lowstability in electrical ***,in order to avoid this issue,WTs hybridization with a storage system is a *** paper investigates WT system operating at variable *** system contains of a permanent magnet synchronous generator(PMSG)supported by a battery storage system(BSS).To enhance the quality of active and reactive power injected into the network,direct power control(DPC)scheme utilizing space-vector modulation(SVM)technique based on proportional-integral(PI)control is ***,to improve the rendition of this method(DPC-SVM-PI),the rooted tree optimization technique(RTO)algorithm-based controller parameter identification is used to achieve PI optimal *** compare the performance ofRTO-based controllers,they were implemented and tested along with some other popular controllers under different working *** obtained results have shown the supremacy of the suggested PIRTO algorithm compared to competing controllers regarding total harmonic distortion(THD),overshoot percentage,settling time,rise time,average active power value,overall efficiency,and active power steadystate error.

关键词： Rooted tree optimization(RTO)method direct power control(DPC) wind turbine(WT) proportional integral(PI) PMSG

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An Evaluation of the Impact of AI on data Access Optimization Performance 3

An Evaluation of the Impact of AI on Data Access Optimizatio...

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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Ghule, Vijaykumar R. Agrawal, Ankur Kumar Kumar, Jambi Ratna Raja Mondal, Dipannita Hemelatha, S. Preetha, M. Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Mangalayatan University Department of Management Aligarh India Genba Sopanrao Moze College of Engineering Balewadi Department of Computer Engineering Maharashtra Pune India Dr. D.Y. Patil College of Engineering and Innovation Artificial Intelligence and Data Science Department Talegaon India Karpagam Academy of Higher Education Department of Computer Science Engineering Coimbatore India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350319125

The emergence of synthetic intelligence (AI) has substantially revolutionized the way records is accessed and optimized. With AI-powered equipment and algorithms, groups are capable of efficiently method and manipulate large amounts of data, main to upgrades in overall performance and decision-making. This paper pursuits to evaluate the impact of AI on statistics get entry to optimization performance, discussing both the potential blessings and challenges that include its integration. One of the major blessings of using AI for information get entry to optimization is its capability to automate and streamline obligations. AI-powered structures can analyze and categorize massive datasets at a quicker and extra correct rate than human beings, liberating up time and assets for different obligations. This results in stronger efficiency and productivity in statistics control methods. Further, AI also can enhance the accuracy and best of facts access. thru system learning and predictive analytics, AI structures can identify styles and correlations in information, providing treasured insights for decision-making. This now not simplest improves the speed at which records is accessed, however also the reliability and relevance of the data. However, there are also demanding situations associated with the combination of AI in facts get admission to optimization. one of the fundamental worries is the potential bias in algorithms, which can result in erroneous or discriminatory selection-making. it's far vital for groups to carefully display and review the algorithms utilized by AI structures. © 2023 IEEE.

关键词： accuracy discriminatory predictive structures treasured

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Enhanced Route Optimization: Incorporating Road Safety Factors for Optimal Path Selection 4

Enhanced Route Optimization: Incorporating Road Safety Facto...

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4th International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2024

作者： Subash, R. Prathaban, Banu Priya Ganeshkumar, N. Gopinathan, S. Srm Institute of Science and Technology School of Computing Department of Computing Technologies Chennai India Srm Institute of Science and Technology School of Computing Department of Networking and Communications Chennai India Gitam School of Technology Gandhi Institute of Technology and Management Department of Computer Science and Engineering Karnataka Bengaluru562163 India Sri Sai Ram Institute of Technology Department of Artificial Intelligence and Data Science Chennai India

ISBN: (纸本)9798331508845

Efficient route optimization is a crucial concern in modern transportation systems, influencing travel time, resource consumption, and user satisfaction. By empowering users to select their priority parameters, such as safety or efficiency, this project enables travellers to make eco-conscious choices and select routes that minimize their environmental footprint. Real-time data integration ensures users can bypass traffic jams and accidents, reducing emissions and fuel consumption. Furthermore, the focus on safety factors helps prevent accidents, thereby fostering safer road environments. Existing systems often fall short, providing limited customization and overlooking safety and sustainability priorities. To bridge these gaps, this project introduces an advanced route planning system that empowers users to select their priority parameters, integrates real-time data for up-to- the-minute updates, and prioritizes road safety. It introduces a pioneering approach that enhances the Dijkstra Algorithm by integrating real-time accident rate and travel time data into the route optimization process. By considering these additional factors, the algorithm produces routes that not only minimize distance but also prioritize safety and time efficiency in dynamic real-world conditions. The algorithm's multi-factor optimization considers distance, accident rates, and travel times, enabling the creation of routes that balance these criteria and offer improved decision-making for users through a user- friendly interface. The algorithm's dynamic adaptability, multi- factor optimization, and practical implementation showcase its potential to revolutionize how routes are planned, leading to safer, faster, and more informed travel experiences. © 2024 IEEE.

关键词： Travel time

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Fetal Brain Component Segmentation Using 2-Way Ensemble U-Net 7th

Fetal Brain Component Segmentation Using 2-Way Ensemble U-Ne...

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7th International Conference on data Management, Analytics and Innovation, ICDMAI 2023

作者： Halder, Shinjini Gangopadhyay, Tuhinangshu Dasgupta, Paramik Chatterjee, Kingshuk Ganguly, Debayan Sarkar, Surjadeep Roy, Sudipta Government College of Engineering and Leather Technology Kolkata700106 India Asian Institute of Technology Khlong Nueng Thailand Government College of Engineering and Ceramic Technology Kolkata700010 India Artificial Intelligence and Data Science Jio Institute Navi Mumbai410206 India

ISBN: (纸本)9789819914135

Fetal brain segmentation has been a field of interest since a long time. However, it is a challenging task as well for reasons, like blurred images due to fetal motion. Recently, deep learning has been successful in performing this task with good accuracy. In this paper, we developed 2-way Ensemble U-Net model, a convolutional neural network architecture for performing segmentation on the fetal brain image to divide it into its seven components: intracranial space and extra-axial cerebrospinal fluid spaces, gray matter, white matter, ventricles, cerebellum, deep gray matter, and brainstem and spinal cord. The fetal brain image can be obtained by segmenting it from the fetal magnetic resonance images using any of the previous works on fetal brain segmentation, which presents our work as an extension of the already existing segmentation works. The Jaccard similarity and Dice score for this task are 83% and 88%, respectively. This is higher than that returned by any of the previous models, when trained for the same task, thus showing the potential of our model in segmentation related tasks. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Cerebrospinal fluid

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Industry 5.0: Enhancing Human-Robot Collaboration through Collaborative Robots – A Review

Industry 5.0: Enhancing Human-Robot Collaboration through Co...

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Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA), International Conference on

作者： Raffik R Rithish Ramamoorthy Sathya Vaishali V Balavedhaa S Jyothi Lakshmi N Mechatronics Engineering Kumaraguru College of Technology Coimbatore India Artificial Intelligence and Data Science Kumaraguru College of Technology Coimbatore India Artificial Intelligence and Data Science Engineering Kumaraguru College of Technology Coimbatore India

Modern production systems are currently changing, moving from mass production to mass customization logic, as described in Industry 5.0. The aim of Industry 5.0 is to outperform conventional manufacturing techniques by creating interconnected systems that include everything from machinery, robots, and workers to goods and consumers. This is accomplished by fully integrating the physical and virtual worlds. It focuses on building intelligent hybrid workspaces where robots share labour-intensive duties to increase productivity and safety in a range of industrial sectors. Cobots, or collaborative robots, are introduced in this. Cobots are becoming more prevalent in modern industrial systems because they combine the adaptability and competence of manual labour with the efficiency of automated systems. To maintain consistent human safety and effective collaborative productivity, communication between a human operator and the robot in these collaborative contexts must be precise and seamless. In more specific words, the framework can be used to operate an industrial robot securely and remotely in real-time while still protecting the safety of the technician. The objective of this article is to offer a clear overview of Industry 5.0's major ideas and prospective applications. It focuses on the supporting technologies of Industry 5.0 such as the Internet of Things (IoT), 6G systems, Blockchain technology (BT), Digital Twin (DT), artificial intelligence (AI), Cyber-physical systems, and Extended Reality (XR) technologies, for seamless connectivity and data exchange. Furthermore, it also elaborates on the application of Cobots in various industrial fields.

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Medical Imaging Analysis Using Machine Learning By Design Thinking Approach 4

Medical Imaging Analysis Using Machine Learning By Design Th...

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4th IEEE International Conference on Smart Technologies in Computing, Electrical and Electronics, ICSTCEE 2023

作者： Devi, N. Ramya Revathi, K. Lekhaa, T.R. Aravindhan, K. Kavinkumar, K. Sarumathi, U. Sns College Of Engineering Department Of Information Technology Tamil Nadu Coimbatore India Reva University Department Of Computing And Information Technology Bangalore India Sns College Of Engineering Department Of Artificial Intelligence And Data Science Tamil Nadu Coimbatore India

ISBN: (纸本)9798350384628

Breast cancer is a significant global health concern and a leading cause of cancer-related morbidity and mortality among women. Early detection and accurate prediction of breast cancer are crucial for improving outcomes and reducing the impact of this disease. The development of predictive models and risk assessment tools has become an important area of research, as they can help healthcare professionals identify individuals at a higher risk of developing breast cancer and tailor screening and prevention strategies accordingly. This introduction provides an overview of breast cancer prediction, highlighting the importance of the topic and the motivation behind predictive models. It sets the stage for a more comprehensive exploration of the subject and the various methods, technologies, and factors involved in breast cancer prediction. © 2023 IEEE.

关键词： Machine learning

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