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检索条件"任意字段=2015 2nd International Conference on Engineering Technology and Application"

共 27583 条记录，以下是191-200 订阅

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Power Quality Challenges in Integrated Distribution Generation and Scope of Intelligent Control Techniques 2

Power Quality Challenges in Integrated Distribution Generati...

引用

2nd IEEE international conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2024

作者： Birje, Tushar Karchi, Nalini Kulkarni, D.B. Karchi, Nihal Kle Dr. M S. Sheshgiri College of Engineering & Technology Dept of Electrical & Electronics Belagavi India Kls Gogte Institute of Technology Department of Electrical and Electronics Belagavi India Kls Gogte Institute of Technology Department of Computer Science Engineering Belagavi India

ISBN: (纸本)9798350306415

This paper gives an overview of challenges introduced due to the interconnection of distributed generators into the grid. It also discusses the control technique and scope of AI applications in the mitigation of power quality issues. Exhaustive discussion is carried out on the interconnection of DGs to the grid and power quality issues. It also discusses the different controllers and algorithms that are used to control the parameters of the distributed generation system. A detailed comparison of conventional controllers studied by authors that are used in distribution generation is also discussed. Similarly, the application of artificial intelligence and adaptive algorithm in distribution generation is also presented as per the points, Different connection methods of DG's to the grid, the effect of distributed generation on power quality, the necessity of local voltage control of distribution generator, control methods and intelligent techniques. © 2024 IEEE.

关键词： Adaptive algorithms Control techniques Distribution generation FACTS Renewable energy sources

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Using AI and Blockchain in Case of Algorithm Regulation 2

Using AI and Blockchain in Case of Algorithm Regulation

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2nd international conference for Innovation in technology, INOCON 2023

作者： Tripathi, Neha Mishra, Amit Kumar Dept. of Computer Science & Engineering Uttarakhand Dehradun India Graphic Era Hill University Dept. of Computer Science & Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350320923

The implication of AI is determined by some basic applications where the important analysis is properly modulated as much as possible. All of the basic applications are determined by the growth of AI technologies for finding a better perspective appropriately. Fundamentally, there are different aspects based on the advantages of AI developed by the basic application on the organized basic application of the various variable perspective. In addition, all of the importance regarding the basic development basis is properly incremented on the functional approach. Examination of some basic applications to determine all of the appropriate resolutions has to be evaluated in this research article. © 2023 IEEE.

关键词： Machine learning

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Analysis and Research on Learning Behaviors Based on K-Means Algorithm in MOOC Platforms 2

Analysis and Research on Learning Behaviors Based on K-Means...

引用

2nd IEEE international conference on Sensors, Electronics and Computer engineering, ICSECE 2024

作者： Chen, Jianqiang Software Engineering Institute of Guangzhou Guangzhou510900 China

ISBN: (纸本)9798350373646

Massive Open Online Courses (MOOC) is a fruitful attempt for online education to target the whole society and achieve comprehensive educational equity, serving as a powerful supplement and enrichment to offline education. Learners can access courses and knowledge from all over the world through online access at any time and any place. Taking the Web log analysis of the MOOC platform as the project background, this paper utilizes the ELK technology stack (Elasticsearch + Logstash + Kibana) to complete the collection, storage, and organization of learning behavior data on the MOOC platform. Furthermore, an online learning behavior clustering analysis method based on the k-means clustering algorithm is employed, providing significant data analysis and application support for online learning platforms. This approach assists teachers and platform managers in adjusting teaching modes and strategies in a timely manner to enhance learners' online learning effectiveness. © 2024 IEEE.

关键词： Federated learning

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Fruit and Vegetable Detection With Calorie Estimation Built On Mobilenetv2 2

Fruit and Vegetable Detection With Calorie Estimation Built ...

引用

2nd IEEE international conference on Advances in Information technology, ICAIT 2024

作者： Sengottaiayn, N. Hamsanandhini, S. Rajesh Sharma, R. Sungheetha, Akey Monika, M. Adare, Ketema Alliance University Bengaluru India Department of Computer Technology Kongu Engineering College Erode India Kongu Engineering College Erode India Department of Computer Science and Engineering Adama Science and Technology University Adama Ethiopia

ISBN: (纸本)9798350383867

Fruit and Vegetable Recognition with Calorie Estimation based on Mobilenetv2 is a pioneering research endeavor aimed at leveraging deep learning techniques to enhance dietary monitoring and health management. Building upon the success of neural network models in various domains, this study explores the application of Mobilenetv2 and EfficientNet architecture for accurately identifying fruits and vegetables from images and estimating their respective caloric content. The research dataset comprises meticulously curated images of diverse fruits and vegetables, ensuring comprehensive coverage across different categories. Through rigorous experimentation and evaluation, the proposed model demonstrates remarkable accuracy in fruit and vegetable recognition, achieving an impressive accuracy rate of 97.6%. Moreover, the incorporation of calorie estimation adds a novel dimension to dietary analysis, enabling users to make informed decisions regarding their nutritional intake. The findings of this research not only contribute to the advancement of computer vision techniques but also hold significant implications for personalized nutrition tracking and health- conscious applications. © 2024 IEEE.

关键词： CNN Deep Learning EfficientNet Fruit and vegetable Recognition MobileNetV2

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Mind controlled Movements: Directing Action with left and right thoughts cooperating with EEG 2

Mind controlled Movements: Directing Action with left and ri...

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2nd IEEE international conference on Advances in Information technology, ICAIT 2024

作者： Sajitha, A.K. Srithilak, R. Karthic, Vikas K. Rathi, G. Department of Computer Science and Engineering Sri Ramakrishna Engineering College Coimbatore India

ISBN: (纸本)9798350383867

This study demonstrates the potential of Brain-Computer Interface (BCI) technology to enable individuals to control devices simply through thought, specifically focusing on actions such as moving left and right. Leveraging machine learning techniques, particularly linear regression analysis, on real-time datasets, the research endeavors to develop an application tailored for individuals with paralysis. The process involves the systematic collection of data through the placement of electrodes to capture brain signals associated with the intention to perform left and right movements. These collected datasets are then processed and prepared to train a machine learning model. Through iterative training, the model learns to accurately interpret the brain signals associated with the intended actions of moving left or right. The results of the study underscore the efficacy and precision of the real-time datasets collected, as demonstrated by their successful implementation within the machine learning model. By successfully splitting and discerning between the signals corresponding to left and right movements, the model showcases promising potential for practical application in assisting individuals with paralysis. Overall, this research represents a significant step towards harnessing the capabilities of BCI technology combined with machine learning to enhance the quality of life for individuals facing motor impairments, offering new avenues for intuitive and efficient control of assistive devices through the power of thought. © 2024 IEEE.

关键词： Fast Fourier transforms

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A Collection of Exploratory Data Analysis Techniques for Process Fault Detection in the Tennessee Eastman Dataset 2

A Collection of Exploratory Data Analysis Techniques for Pro...

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2nd international conference on Information and Communication technology, ICICT 2024

作者： Nasif, Sadman Tasnim, Anika Sanzida, Nahid Dept. of Chemical Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh

ISBN: (纸本)9798331508227

The Tennessee Eastman process (TEP) is a widely studied industrial benchmark for testing fault detection and diagnosis techniques, given its complexity and the need for reliable fault detection systems in chemical plants. This paper proposes a comprehensive application of exploratory data analysis (EDA) techniques to the TEP dataset to enhance process fault detection and improve understanding of the dataset’s features. The proposed methodology involves plotting time series data to capture temporal dynamics and applying Shewhart control charts to monitor process variability. Additionally, deviation atlases are used to detect anomalies across all features, dendrograms are employed to identify hierarchical clusters, and correlation heatmaps visualize interdependencies between process variables. By applying these EDA techniques, patterns and relationships that were less apparent in the raw dataset became identifiable, contributing to a more thorough fault diagnosis. The findings highlight the value of EDA in uncovering hidden insights, which could aid in the development of more robust fault detection algorithms for real-world industrial applications. ©2024 IEEE.

关键词： Chemical plants

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Voice Recognition based Energy Efficient Control and Monitoring of Home Appliances through Android Mobile App using IoT 2

Voice Recognition based Energy Efficient Control and Monitor...

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2nd IEEE international conference on Emerging Research in Computational Science, ICERCS 2024

作者： Sathish Kumar, D. Pazhanimuthu, C. Saravanan, G. Suresh, P.K. Chandran, G. Malukannan, M. Karpagam Academy of Higher Education Department of EEE Coimbatore India KPR Institute of Engineering and Technology Department of EEE Coimbatore India Sri Krishna College of Technology Department of EEE Coimbatore India DMI College of Engineering Department of EEE Chennai India Mahendra Engineering College Department of EEE Namakkal India

ISBN: (纸本)9798331534950

The suggested system aims to provide wireless control and monitoring of household equipment using a mobile application. Bluetooth-enabled home appliance monitoring and control is a reliable, low-cost, and simple technique;however, it is limited to a range of ten meters. The Internet of Things (IoT) provides an efficient home automation solution, allowing users to remotely manage household appliances and monitor sensor data via internet connectivity. The system is managed via an Android application created using MIT App Inventor 2, an open-source development tool. This app allows users to control home appliances like lights and fans by utilizing a Firebase web server. The implemented system can be operated via manual switches, the mobile app, or Google Assistant-based voice commands. Validation and verification of the system's functionality were tested using Proteus 8.9 software. The proposed system simplifies wiring structures, reduces implementation costs and security risks, and enhances energy efficiency. © 2024 IEEE.

关键词： Domestic appliances

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Optimizing Regulatory Compliance in Supply Chains with Blockchain and Gaussian Process Regression 2

Optimizing Regulatory Compliance in Supply Chains with Block...

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2nd IEEE international conference on IoT, Communication and Automation technology, ICICAT 2024

作者： Tulasiram, D. Jebaseeli, S. Kanmani Adnan, Myasar M. Madhavi, Arelli Varshney, Neeraj Nandhini, T.J. CMR College of Engineering & Technology Department of CSE India New Prince Shri Bhavani College of Engineering and Technology Department of IT Tamil Nadu Chennai600073 India The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq GRIET Bachupally Department of AI&ML Telangana Hyderabad India GLA University Department of Computer Engineering & Applications Mathura India Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350368109

Increased regulation of the supply chain is another important issue of concern to industries in distinct countries as they struggle to implement the regulation in a network setting. This paper aims to explore ways to improve regulatory compliance through the application of the blockchain and machine learning model, namely Gaussian process regression. Blockchain is an accurate and permanent record-keeping system that can be applied to track the flow of items and associated activities in the supply chain. Compliance can also be enforced, and through smart contracts, analyses of various parameters such as obligations can be monitored and adjusted automatically through GPR which involves the analysis of data from systems that use blockchain to model compliance risks and predict compliance issues. Thus, using the above-mentioned technologies, a company can prevent compliance failures, meet the necessary standards and set up a constant process of improvement in the supply chain area. This research specifically defines the theoretical foundations, application, and advantages of blockchain and GPR in enhancing the compliance of supply chains with the regulations in this work. In this approach, case-study and use of examples show how this approach works in handling compliance issues in several industries. © 2024 IEEE.

关键词： Smart contract

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Fall Detection and Alerts in Hearing Aids for Deaf using Generative AI 2

Fall Detection and Alerts in Hearing Aids for Deaf using Gen...

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2nd international conference on Computational Intelligence, Communication technology and Networking, CICTN 2025

作者： Tripathi, Bharat Lal Saini, Madan Jain, Manish Saxena, Apoorva Pal, Narendra Department of Computer Application Allenhouse Institute of Technology Kanpur India Department of Computer Science and Engineering Apex Institute of Technology Chandigarh University Punjab India Department of Computer Application Allenhouse Business School Kanpur India Department of Computer Science & Engineering Axis Institute of Technology & Management Kanpur India Department of Computer Science & Engineering Invertis University Bareilly India

ISBN: (纸本)9798331530389

Individuals with sensorineural hearing loss often experience difficulty comprehending speech when background noise is present. This paper investigates the extent of this problem in various listening scenarios and with different types of background sounds. Additionally, the section explores the contributing factors to this challenge such as reduced audibility, reduced frequency selectivity, loudness recruitment, and dead regions in the cochlea where there are no surviving inner hair cells and or neurons. The sections evaluate different techniques for compensating for the effects of these factors. While signal-processing methods using the output of a single microphone to compensate for reduced frequency selectivity have had limited success, techniques utilizing multiple microphones have proven effective. Amplitude compression has also been effective in compensating for the effects of loudness recruitment, enabling individuals to understand speech across a wide range of sound levels. Next, the paper delves into the technical aspects of implementing fall detection systems in hearing aids, learning algorithms are also investigated for their potential in enhancing fall detection accuracy and minimizing false alarms. Furthermore, the importance of user-friendly interfaces and customization features in ensuring the effectiveness and acceptance of fall detection alerts is also highlighted. The paper also addresses the ethical and privacy considerations associated with fall detection in hearing aids. It emphasizes the need for transparent data handling practices and user consent, while also addressing potential concerns related to user autonomy and intrusion. © 2025 IEEE.

关键词： Data privacy

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Design of fractal tree based open stub loaded filtering antenna suitable for wireless application 2

Design of fractal tree based open stub loaded filtering ante...

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2nd international conference on Microwave, Antenna and Communication, MAC 2024

作者： Kanimozhi, T. Sheeja, L.K. Vennila, A. Veer Surendra Sai University of Technology Electronics and Telecommunication Engineering Odisha India Kongu Engineering College Electronics and Communication Engineering Erode India

ISBN: (纸本)9798350350104

In this study, a compact microstrip filtering antenna designed by integrating a fractal binary tree-based band-pass filter with an antenna array of dimension (42 x 48) mounted on an FR4 substrate of thickness 1.545 is investigated to achieve wide pass-band with good selectivity. The acquired pass-band is achieved by modifying the fractal tree iterations without much change in the filter's physical parameter. The designed filtering antenna employs an 11.96 GHz -15.1 GHz band in its state of operation. The Filtenna's bandwidth is 3140MHz, and the extended stop-band measures up to 25GHz. The exhibiting fractional bandwidth is approximately equal to 24%. To establish the performance of the filtering, optimization and investigation of the proposed filtering array were done using the HFSS V15 simulator. © 2024 IEEE.

关键词： Microstrip antennas

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