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Machinery Fault Diagnoses in High-Voltage Circuit Breakers Using Empirical Mode Decomposition-Support Vector Machine Model 3

Machinery Fault Diagnoses in High-Voltage Circuit Breakers U...

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3rd IEEE International Conference on Distributed Computing and Electrical Circuits and electronics, ICDCece 2024

作者： Al-Farouni, Mohammed Sudhakar, A.V.V. Divya, G. Bala Dhandayuthapani, V. Shivakanth, Gandla Department Of Computers Techniques Engineering College Of Technical Engineering The Islamic University Najaf Iraq Department Of Electrical And Electronics Engineering Sr University Warangal India Department Of Ece Nitte Meenakshi Institute Of Technology Bengaluru India Department Of It College Of Computing And Information Sciences University Of Technology And Applied Sciences Shinas campus Shinas Oman Department Of Computer Science And Engineering Koneru Lakshmaiah Education Foundation Telangana Hyderabad India

ISBN: (纸本)9798350318609

The circuit breakers have a flaw in their trip mechanism. Early mechanical faults like coil-plunger jam are hard to report using traditional fault diagnosis based on the coil current. However, users still have difficulty understanding and trusting the diagnosis results since the standard EMD is opaque in terms of interpretability. In this work, an Empirical Mode Decomposition with Support Vector Machine (EMP-SVM) proposed for machinery fault diagnosis. This work uses the vibration signal recovered from the trip process as an intrinsic time series of the data. At first, The Improved EMD is a data-adaptive multiresolution approach that breaks down signals into physically relevant components based on vibration and coil current signals. Lastly, utilizing the characteristics that were retrieved, the SVM is used to diagnose the defect. The implemented improved EMP-SVM model demonstrates superior performance, achieving Precision of (98.37%), recall of (91.03%) and F1-Score of (96.34%). When compared to previous models like Improved Dempster-Shafer Evidence Theory-Echo State Neural Network (IDSET-ESNN) and Phase Space Reconstruction with Support Vector Machine (PSR-SVM). © 2024 IEEE.

关键词： Empirical mode decomposition

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Designing an Intelligent Data Transmission Strategy Between Entities Using Wireless Communication Methodology

Designing an Intelligent Data Transmission Strategy Between ...

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2024 International Conference on Intelligent Systems for Cybersecurity, ISCS 2024

作者： Geetha, R. Jayakumar, D. Devi, S. Rukmani Senthurya, S. Akula, Akhila Karthiga, R. Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Electrical and Electronics Engineering Saveetha School of Engineering Tamil Nadu Chennai India R.M.D. Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Saveetha College of Liberal Arts and Sciences Simats Deemed to Be University Chennai Department of Computer Science Tamil Nadu India Mlr Institute of Technology Department of Ece Hyderabad India R.M.K Engineering College Department of It Tamil Nadu Chennai India

ISBN: (纸本)9798350375237

Data security is of the utmost importance in wireless sensor networks due to the massive amounts of data collected and sent between nodes. An improved security method for wireless sensor networks is presented in this paper. This mechanism takes into account the application, the security level, and the bit error rate simultaneously. In order to provide the user with the ability to select between unsecure and secure modes, we made use of reserved bits of the frame control field that are contained within the communication header. The Secured and Intelligent Data Transmission Protocol (SIDTP) is the name of the unified perceptual information transmission model that is established in this research. Its purpose is to compensate for the unequal distribution of cognitive radio users across different wireless LANs. For the purpose of determining whether or not the suggested scheme is effective, the proposed model will be cross-validated with the traditional data transmission model known as Wireless Data Transmission Protocol (WDTP). The approach has the potential to optimize the utilization of spectrum resources in an efficient manner. In addition, to help lessen the risks connected with wireless networks, this study lays out a technique for transmitting data using cyclic delay full diversity sensing information coding. In order to evaluate the performance of the system against a variety of correlation coefficients, we developed a system simulation model. The result of the study showed that cyclic delay diversity systems had overall interference intensity similar to frequency division duplex as well as time division duplex. As an added bonus, this enhances its anti-jamming attack capabilities. The proposed system has been planned and implemented, and significant trials have been carried out in an industrial setting. Additionally, a prototype of the system has been designed. Compared to conventional communication interfaces that are only equipped with a single wireless interf

关键词： Data transfer

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Exploring the concept of multi-modality using grounding dino with evaluation of its performance in the context of different types and complexity of input text prompts

Exploring the concept of multi-modality using grounding dino...

引用

2024 International Conference on Smart Devices, ICSD 2024

作者： Rahim, Abdul Singh, Amanjot Sharma, Ankur Garg, Rachit Ravisankar, Ch Yamsani, Nagendar Malla Reddy Engineering College for Women Department of ECE Hyderabad India Lovely Professional University School of Electronics and Electrical Engineering Punjab Phagwara India Institute of Technology and Science Mohan Nagar Ghaziabad India Lovely Professional University School of Computer Science and Engineering Punjab Phagwara India SR University School of Computer Science and Artificial Intelligence Warangal India

ISBN: (纸本)9798350394412

We have known artificial intelligence, deep learning models can be trained with a certain type of input format to perform a task e.g., OCR models takes input in the form of image to read the text characters from the image, a weather prediction model can take weather data like wind speed, moisture, etc. as an input which is in text format to predict future weather data. But the multi-modality concept which is comparatively newer in the market paves the way for models to be built which can take more than one type of inputs e.g., text and audio, text and image, etc. In the same concept one of the popular architectures is specially designed for detection of any hindrance, model grounding dino about which we will be discussing in this setting. It is a zero-shot object detection model which can perform inference just by taking a text prompt input from the user describing what they want the model to detect in the provided image. In this study, we will be discussing about its capabilities, architecture and also its performance. We will be testing and quantifying its performance using standard self-created input text prompts with variations including description of the object, complexity of the object, etc. on a standard image. © 2024 IEEE.

关键词： Zero-shot learning

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Automated Deep Learning with Wavelet Neural Network based Rice Plant Classification

Automated Deep Learning with Wavelet Neural Network based Ri...

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2023 International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2023

作者： Rekha, V. Reddy, L. Venkateswara Chaudhari, Sachin Vasant Gopi, Arepalli Nithiya, C. Ahamed, Shaik Khaleel Agurchand Manmull Jain College Tamil Nadu Chennai India Department of Computer Science and Engineering Kg Reddy College of Engineering and Technology Telangana Hyderabad India Department of Electronics and Computer Engineering Sanjivani College of Engineering Kopargaon India Department of Computer Science Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Guntur India Department of Ece R.M.K. College of Engineering and Technology Puduvoyal India Department of Cse Methodist College of Engineering and Technology Telangana Hyderabad India

ISBN: (纸本)9781665474511

In the agricultural sector, a disease that occurs in plants is primarily responsible for the decrease in production and results in massive financial loss. Rice is considered the crucial food crop in Asian nations and is affected by distinct types of diseases. Due to the arrival of deep learning (DL) and computer vision methods, rice plant ailments will be identified and diminish the problem of the agriculturalists to save the crops. Currently, computer aided diagnosis (CAD) methods become accessible to observe pests and crop diseases with the help of plant images. An automatic rice disease prognosis technique could present details regarding preventing and controlling rice ailments for decreasing the monetary loss, decline the insecticide residue, and increase the number and quality of yields. In order to attain this method, authors are advised to advance effective image processing methods for noticing plant diseases. Therefore, this paper presents an Automated Deep Learning with Wavelet Neural Network Based Rice Plant Classification model named ADLWNN model. The proposed ADLWNN model focuses on the effectual recognition and categorization of rice plant images. The proposed ADLWNN model primarily exploits convolutional neural network (CNN) model to extract features from the input rice plant images. Moreover, manta ray optimization algorithm (MRFO) algorithm is applied as a hyperparameter optimizer. Besides, the WNN model is employed for the robust recognition and categorization of rice plant images. The simulation analysis of the ADLWNN model is tested using a set of rice plant images and the results indicated as 98.17% better outcomes for the ADLWNN model over other techniques. © 2023 IEEE.

关键词： Image classification

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An Improved Hierarchical Control Strategy for Power Management in Islanded Hybrid Microgrids 2

An Improved Hierarchical Control Strategy for Power Manageme...

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2nd IEEE Global Conference on Communications and Information Technologies, GCCIT 2024

作者： Jeba Singh, O. Yamini, K. Anish Pon Rajesh Sharma, R. Mahapathra, Sheila Alliance University Centre for Academic Research Bengaluru India Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology Department of Ece Tamil Nadu Chennai India Alliance University Department of Computer Science and Engineering Bengaluru India Alliance University Department of Electrical and Electronics Engineering Bengaluru India

ISBN: (纸本)9798350388916

Power management and control through a hierarchical control strategy in a Hybrid Micro Grid (HMG) consisting of multiple AC and DC small Micro Grids (MG) with different voltage ratings are focussed of this research. The ultimate aim of the proposed power management strategy is to limit the continuous operation of Interlink (IL)in different load conditions. Hence, the power loss at the IL converters are reduced, orelse it may affect the operational stability of the HMG. The hierarchical control strategy for power management and coordination for islanded mode of HMG is implemented and analysed. The designed system consists of primary and secondary control levels, that provides an accurate power transfer among the small MGs. The new methodology ensure a continuous power flow within the small MGs with minimal operation of IL converter. © 2024 IEEE.

关键词： Hybrid power

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Memristor-Fet Hybrid Circuits for Real-Time Electronic Applications

Memristor-Fet Hybrid Circuits for Real-Time Electronic Appli...

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2025 IEEE International Students' Conference on Electrical, electronics and computer Science, SCEECS 2025

作者： Raj, P Michael Preetam Vittapu, Sravan K Chinnasamy, P. Gupta, Manu Priyanka, B.G. Gajbhiye, Pranjali Mlr Institute of Technology Department of Cse Hyderabad India Nalla Narasimha Reddy Education Society's Group of Institutions Department of Ece Hyderabad India Kalasalingam Academy of Research and Education Department of Cse Tamil Nadu India Sreenidhi Institute of Science and Technology Department of Electronics and Computer Engineering Hyderabad India Pes Institute of Technology and Management Department of Ece Shivamogga India Woxsen University Department of Ai Research Centre Hyderabad India

ISBN: (纸本)9798331529833

Circuits comprising of memristor paired with Field effective transistor (FET) were determined to be exceedingly significant as the output current modulated by the FET heightened memristive executions. In this paper, the memristor-FET pair is studied in terms of its electronic features. The duo exhibited the characteristics of negative resistance. Interestingly, the duo was capable of generating ramp and pulse signals with improved circuit complexity of ~93% when compared to conventional signal generators. Importantly, the linearity was improved by ~20.5%. © 2025 IEEE.

关键词： Memristors

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Path Planning for Autonomous Ground Vehicles by Applying Modified Harris Hawks Optimization Technique 12th

Path Planning for Autonomous Ground Vehicles by Applying Mod...

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12th International Conference on Soft Computing for Problem Solving, SocProS 2023

作者： Das, Subhranil Kumari, Rashmi Thakur, Abhishek Singh, Raghwendra Kishore Nigam, Akriti Faculty of Business and Leadership School of Business MIT World Peace University Pune India School of Computer Science and Engineering Bennett University Greater Noida India Department of Electrical and Electronics Engineering BIT Mesra Ranchi India Department of ECE NIT Jamedeshpur Jamedeshpur India Department of CSE BIT Mesra Ranchi India

ISBN: (纸本)9789819731794

Automated Guided Vehicles (AGVs) have found extensive use in industry, particularly in port shipping, logistics, and warehousing. Finding the shortest path is the most crucial problem with the AGV. In this proposed work, a new optimization algorithm, i.e., the Modified Harris Hawks Optimization (MHHO) technique, has been applied for path planning problems. Simulation results show the proposed technique performs much better when compared with four other state-of-the-art techniques. The efficacy of the proposed MHHO technique has been verified with two working environments. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Motion planning

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Artificial Intelligence assisted Electric Vehicles Fast Charging Station Design using Grid Distribution Network Model 4

Artificial Intelligence assisted Electric Vehicles Fast Char...

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4th International Conference on Intelligent Technologies, CONIT 2024

作者： Anitha, C. Chitra, K. Vijayalakshmi, G. Kumaran, G. Vijetha, T. Ormila, K. Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Cmr Institute of Technology Department of Electrical and Electronics Engineering Karnataka Bengaluru India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Cse Tamilnadu Chennai India Mlr Institute of Technology Department of Ece Hyderabad Dundigal India A.M.K. Technological Polytechnic College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350349900

The electric vehicle charging station is a game-changer that supplants the older kind of charging stations. Our futuristic electric vehicle charging station may be installed virtually anywhere, takes minimal space, and operates independently of the government's power source, in contrast to the current practice of reserving these stations for major urban areas. Among the many global industries that rely on fossil fuels, transportation ranks high. The development of electric vehicles (EVs) and other forms of transportation electrification are thus essential in the fight against carbon-dioxide emissions and the over-reliance on traditional energy sources that are harmful to the environment. At the same time, electricity distribution, use, and supply have been accompanied by massive amounts of data due to the fast digitization of electrical networks and EVs. These datasets may be used to inform choices and insights by using artificial intelligence (AI) algorithms. Despite a number of recent studies in this area, no one has explicitly examined the usefulness of AI for charge-demand profiling, data augmentation, demand forecasting, explainability of demand, and charge optimization of the EVI. For the purpose of efficiently delivering the fast charging function, this study suggested a novel logic called Grid Distributed Fast EV Charging (GDFEVC). To evaluate the proposed model's efficiency, it was cross-validated with the standard Fast EV Charging Model (FEVCM). This AI framework has been empirically tested on a real-world EVI case study, and the results show that it helps with the new problems with dispersed energy supplies that are coming up with EV adoption. © 2024 IEEE.

关键词： Charging stations

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Synergizing Collaborative Filtering and Popularity Scores in a Machine Learning Approach for Content Suggestions 7

Synergizing Collaborative Filtering and Popularity Scores in...

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7th International Conference on electronics, Communication and Aerospace Technology, ICECA 2023

作者： Chaturvedi, Abhay Mathews, Boban Kumar Patra, Sasi Anil Kumar, N. Kavitha, R. Kumar Lakineni, Prasanna GLA University Department of Electronics and Communication Engineering Uttar Pradesh Mathura India Brindavan College of Engineering Department of ECE Karnataka Bangalore India GIET Engineering College Department of Computer Science & Engineering Andhra Pradesh India School of Engineering Department of Electronics and Communication Engineering Mohan Babu University Tirupati India Velammal College of Engineering and Technology Department of Information Technology Tamilnadu Madurai India GITAM School of Technology Department of CSE GITAM University Visakhapatnam India

ISBN: (纸本)9798350340600

Today, it is common to rely on reviews from other people when making decisions on a variety of life decisions, including which movies to watch, which items to buy, and which books to read. Recommender systems are crucial in meeting this need. By projecting a user's expected rating for an item, these systems function as filtering algorithms. Recommender systems provide advice to consumers via a prioritized list of projected item ratings after filtering through large data repositories. Online book recommender systems focus primarily on book aficionados. People frequently take into account and put their faith in the comments and reviews written by previous readers when choosing which book to read. The following study proposes a cleverly combined hybrid recommender system that combines content-based and collaborative filtering techniques. The author uses clustering techniques to divide data points into various clusters in the context of collaborative techniques. For this, methods like K-means clustering and Gaussian mixture models are employed, with the best algorithm being selected through the use of the silhouette score. The clustering procedure is then guided by the selected algorithm. Additionally, to efficiently reduce the dimensions of a sparse dataset, the research applies the Matrix Factorization method, specifically using Truncated Singular Value Decomposition (Truncated-SVD). The system uses the TF-IDF vectorizer for Content-Based Filtering, which takes textual assertions as input and converts them into a matrix of related vectors. The Root Mean Square Error (RMSE), a metric that measures the difference between absolute and obtained values, is used in the study to assess the system's correctness. This measure sheds light on the recommender system's underlying accuracy. © 2023 IEEE.

关键词： Recommender systems

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Improving UHVDC Wall Bearings Electric Reliability: Grading Ring Optimization and Field Investigation 3

Improving UHVDC Wall Bearings Electric Reliability: Grading ...

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3rd International Conference on Advancement in electronics and Communication engineering, Aece 2023

作者： Kumar, Prashant Aandhasilambarasan, D. Kumar, Brijesh Karthigaikumar, P. Ingle, Anup Tmu Department of Ece India Karpagam Academy of Higher Education Department of Computer Science Engineering India School of Commerece and Management Iimt University Meerut India Karpagam College of Engineering Department of Electronics and Communication Engineering India Vishwakarma Institute of Information Technology E&tc India

ISBN: (纸本)9798350330724

The cause of the violent explosion of a standard 800 kV conversion generator component has been examined in this study. The electromotive force and possibility dispersion along HV bearing are calculated using the numerical simulation technique, and the construction of the scoring plates for the 800 kV bearing is optimized. Software is employed to build the two-half model of the 800kV gasket and control hall arrangement. The junction between the flange and indeed the enclosure and casing have a greater field strength, and the electromotive force is spread instead irregularly, in accordance with the computation of the magnetic charge and dissipation factor along the sleeve without any classification rings. The technique for attaching a classification ring to the hinge side to lessen its field strength from around top of the shed and scabbard is then presented in this article. In order to reduce the maximum electrical field strength all around component and the evaluation ring and to achieve the best evaluation ring construction, this technique also improves the position and setup factors of the assessment ring. The optimum layout is able to be used to the 800-kV power production project to minimize the likelihood of overloads of UHVDC stabilizer bar after the model. the model confirms that the maximum field density from around ground of the specimen, shed and holster, and the assessment ring is dominated within an appropriate limit. © 2023 IEEE.

关键词： Finite element method

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