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检索条件"任意字段=International Conference on Electrical Engineering Computing Science and Automatic Control"

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FPGA-based Real-Time High-resolution Image Processing for rocket on-board processing 17

FPGA-based Real-Time High-resolution Image Processing for ro...

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17th IEEE international conference on Computer Research and Development, ICCRD 2025

作者： Zhou, Hui Wang, Xiaofeng Xie, Yujia Cao, Yongxiang Tang, Yu Huo, Yongchun Wen, Huan Zhao, Xiongbo Li, Chaoran National Key Laboratory of Science and Technology on Aerospace Intelligent Control Beijing Aerospace Automatic Control Institute Beijing China Beihang University Computer Science and Engineering Beijing China Beihang University National Superior College for Engineers Beijing China

ISBN: (纸本)9798331531881

The structure of the rocket-borne model is inherently complex, with processed images exhibiting high resolution and generating substantial amounts of data and calculations. Achieving robust real-Time computing on an embedded platform poses significant challenges due to strictly limited resources, power consumption constraints, and size limitations. Our review of rocket-borne applications reveals considerable variability in the design resources of different devices, indicating a need for expanded design approaches. Upon evaluating existing methods, we identified two primary drawbacks. First, certain operators within the high-resolution target detection model are difficult to parallelize, resulting in significant inference delays that hinder the ability to meet task requirements. Although existing methods have been extended, there remains significant potential for performance enhancement in core scheduling for poor acceleration. This paper proposes an optimized architecture for the target detection algorithm accelerator designed for high-resolution images, along with a novel highly parallel data pre-processing and post-processing module implemented on FPGA to address these issues. Compared to the ARM implementation, this architecture demonstrates an improved performance of 24.64x. Furthermore, to ensure flexible application across various rocket launch scenarios, we introduce an optimization structure for convolution, pooling, and fusion operators and a multi-core expansion optimization method. This approach yields a 1.29x improvement in computing unit utilization compared to state-of-The-Art multi-core scaling efforts. Finally, we assessed the accelerator architecture across multiple FPGA platforms, achieving a peak processing element utilization rate of 99.71% for a single core and layer. The overall computing efficiency, excluding the first layer, exceeded 90%. The peak computing power for the four cores reached 1638.4 GOPS, and the end-To-end computation time for

关键词： Image enhancement

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Neural Network Modelling of Point-Defect Microcavities in One-Dimensional Photonic Crystals

Neural Network Modelling of Point-Defect Microcavities in On...

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Computer science and Blockchain (CCSB), international conference on

作者： Yuanxiu Liu School of Information and Electrical Engineering Hunan University of Science and Technology Xiangtan Hunan China

ISBN: (数字)9798350356502

ISBN: (纸本)9798350356519

In a pioneering study, researchers have explored the optical properties of one-dimensional photonic crystal microcavities with point defects, utilizing neural networks to enhance the prediction and optimization of these properties. Leveraging the distinct photonic bandgaps of these crystals, the study highlights how introducing point defects can modulate light through localized modes, pivotal for optical control. Employing the Massachusetts Institute of Technology's Photonic-Bands (MPB) software for preliminary band structure simulations, the research seamlessly integrates conventional simulation techniques with cutting-edge machine-learning strategies. A Multi-Layer Perceptron (MLP) model was meticulously trained across diverse photonic crystal configurations to accurately predict crucial characteristics such as bandgap positions and the intensities of localized modes. Subsequent validation through MATLAB affirmed the model's precision, substantially boosting the efficiency and accuracy of optical property predictions. These findings underscore the transformative impact of integrating deep learning with photonic crystal research, heralding a new era of advanced integrated photonic devices and optical sensors. This innovative methodology not only propels forward the field of optical device engineering but also establishes a solid foundation for ongoing advancements in photonic studies.

关键词： Photonic band gap Neural networks Optical computing Predictive models Optical fiber networks Mathematical models Microcavities Software Optical sensors Photonics

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MPA-Tuned Fractional Order PID controller for Frequency control of Interconnected Smart Grid Power System 3

MPA-Tuned Fractional Order PID Controller for Frequency Cont...

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3rd IEEE international Virtual conference on Innovations in Power and Advanced computing Technologies, i-PACT 2021

作者： Padhy, Sasmita Sahu, Preeti Ranjan Khadanga, Rajendra Kumar Prusty, B Rajanarayan Panda, Sidhartha National Institute of Science and Technology Department of Electrical and Electronics Engineering Odisha Berhampur India Centurion University of Technology and Management Department of Electrical Engineering Odisha Bhubaneswar India School of Electrical Engineering Vellore Institute of Technology Tamil Nadu Vellore India Veer Surendra Sai University of Technology Department of Electrical and Electronics Engineering Odisha Burla India

ISBN: (纸本)9781665426916

The paper aims at establishing a frequency control strategy with the coordination of fractional order PID (FOPID) controller and electric vehicles (EVs) in interconnected smart grid power systems to improve the dynamic response under the change in load conditions. The system under consideration is a two-area system, wherein in one area, a thermal power unit is present, and a PV plant is installed in the second area. FOPID controller is proposed to have the secondary frequency control in the interconnected system. It is compared with classical controllers PI and PID to prove the proposed FOPID controller's efficiency. The parameters of the controllers, employed to reduce the frequency deviation and improve the dynamic response, are tuned using a novel Marine Predator algorithm (MPA). MPA-based FOPID controller gives better results compared to the classical controller in enhancing the dynamic response of the considered systems. When EVs are incorporated into the system, the combination of controller and EVs eliminates oscillations, further improves the settling time of frequency and tie-line power fluctuations. © 2021 IEEE.

关键词： controllers

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Implementation of Neural Network controller for Grid Connected Wind-Solar PV Charging Station

Implementation of Neural Network Controller for Grid Connect...

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Sustainable computing and Smart Systems (ICSCSS), international conference on

作者： Koteswara Rao Gorla Vinoth Krishnamoorthy Ramesh. S Karunanithi. K School of Electrical & Electronics Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai India

ISBN: (数字)9798350379990

ISBN: (纸本)9798350391558

This work proposes a novel approach to enhance grid-connected wind-solar PV charging stations that face challenges like fluctuating energy supply, inefficient resource usage, and the necessity for adaptive real-time control. Traditional control methods like PI controllers, often fall short in optimizing the system performance under the dynamic conditions, resulting in inadequate power supply for EV charging. To tackle these challenges, this study proposes a novel approach by employing Neural Network (NN) controllers to enhance grid-connected wind-solar PV charging stations' operation. NN controllers dynamically adjust charging station operations based on real-time data inputs, offering superior adaptability and efficiency. By integrating wind and solar power generation with intelligent NN control mechanisms, the system adeptly responds to varying environmental conditions and grid demands, ensuring more effective utilization of renewable energy sources. The proposed NN controller-based system targets enhancing the reliability, sustainability, and economic feasibility of grid-connected charging stations. Simulations showcase the effectiveness and stability of this approach in integrating renewable energy into transportation infrastructure. Performance evaluation can be conducted using Matlab/Simulink Software.

关键词： Wind energy generation Renewable energy sources Artificial neural networks Charging stations Power system stability Wind power generation Real-time systems

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Optimizing Household Energy Consumption: A Web-Based Tool for Real-Time Carbon Footprint Calculation and Sustainable Benchmarking

Optimizing Household Energy Consumption: A Web-Based Tool fo...

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Advances in Computer science, electrical, Electronics, and Communication Technologies (CE2CT), international conference on

作者： Harsh Raja Jayaditya Kishore J. Kalaivani V. Angayarkanni P. Rama Department Of Computing Technologies Faculty Of Engineering And Technology Srm Institute Of Science And Technology Chengalpattu District Tamil Nadu India

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

This is an innovative project from an energy-saving perspective. This project ensures that users become in control of their energy consumption and able to take an actively reducing their carbon footprints. It provides users with an interface to input details about household appliances and usage patterns, through which a correct calculation of the carbon footprint could be done. Compared against standard norms, it would help the users identify certain areas where improvement is possible and adopt more sustainable use of energy. Apart from personalized energy assessments, it has now become the central source that connects users to local schemes and initiatives on sustainable energy, including information on resources and programs into waste energy and carbon emission reduction. This integration, therefore, promotes more engagement and involvement within the community as users are nudged to join in the efforts that are being made for the goal of energy conservation. The platform educates its users about energy consumption and aids them in making green choices in data; however, with a holistic approach in carbon footprint management and education pertaining to sustainable long-term behavior, the process takes place through integrated accurate energy tracking, fine recommendations, and community-driven action.

关键词： Energy consumption Energy conservation Green products Real-time systems Sustainable development Carbon footprint Standards Research and development Meteorology Resilience

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Interim Analysis Using Machine Learning

Interim Analysis Using Machine Learning

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Electronics, computing, Communication and control Technology (ICECCC), international conference on

作者： Vennila J V.S. Prakash Himani Kotian K. Chitra Liji Sebastian Keerthi Vijayan Basker P K. Esther Jenitha Manipal Academy of Higher Education (MAHE) Statistics - Manipal College of Health Profession (MCHP) Manipal Karnatka India Department of Computer Science Kristu Jayanti College Bengaluru Karnataka India Department of Community Medicine Kasturba Medical College Mangalore Manipal Academy of Higher Education (MAHE) Karnataka India Department of Electrical and Electronics Engineering CMR Institute Of Technology Bangalore Karnataka India Department of Statistics Periyar University Salem Karnataka India Department of Statistics Kristu Jayanti College Karnataka India Department of Statistics Kristu Jayanti College Bengaluru Karnataka India Chandigarh University Punjab India Department of Statistics Loyola College Chennai-34 Tamil Nadu India

ISBN: (数字)9798350371802

ISBN: (纸本)9798350371819

The purpose of this article is to recalculate sample size by adjusting the initial design about trial results and taking uncertainty in power estimations into consideration throughout study preparation. This article examines two primary methods: Pocock and O'Brien/Fleming using R programming. Interim data analysis must be done far in advance to provide enough power and minimize the risk of having Type I errors. These results suggest that robust performance indicators have enabled improved comprehension of the study's development, notably increased control, more efficient use of resources (e.g., monitoring time), quicker enrolment, shorter operational timelines, and less expensive costs.

关键词： Uncertainty Data analysis Costs Estimation Machine learning Programming Planning

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Formal Modelling of the Multiple Trains Following Operation in Uncertain Environments

Formal Modelling of the Multiple Trains Following Operation ...

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international conference on Intelligent System and Knowledge engineering, ISKE

作者： Xia Wang Yang Xu Jun Liu Guanfeng Wu Shuwei Chen School of Computing and Artificial Intelligence Southwest Jiaotong University National- Local Joint Engineering Laboratory of System Credibility Automatic Verification Chengdu China School of Mathematics Southwest Jiaotong University National- Local Joint Engineering Laboratory of System Credibility Automatic Verification Chengdu China School of Computing Ulster University Northern Ireland

Ensuring the safety of the following operation under moving block signal is very important for safe operation. Now that the Train control system under Moving Block Signal (TC-MBS) is a distributed, complex, dynamic, and highly interactive system, the proposed method uses the Multi-Agent System (MAS) technique to design, model, and analyse the TC-MBS system. This paper describes implementing formal methods for modelling the TC-MBS system that operates in an uncertain environment and its safety verification based on model checking techniques. First, the multi-mode following operation in an uncertain environment is analysed using the decision table technique. Second, we introduce a creative modelling approach for MAS called UML-MAS to build the semi-formal model of the TC-MBS system. UML-MAS acts as a standard interface for the system designers and infrastructure managers to increase their requirement comprehension, analysis, system design, and scheme planning at the conceptual level. Thirdly, a set of rules is suggested to convert UML-MAS model into Vector-based Interpreted Systems Programming Language (VISPL) model, which serves as the input for the model checker MCMAS- T. In order to demonstrate the practicality and effectiveness of the suggested approach, some case studies on modelling the TC-MBS systems while considering various scenarios in an uncertain environment and their verification employing MCMAS- Tare presented.

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Implementation of a Priority-Based Home Energy Management System

Implementation of a Priority-Based Home Energy Management Sy...

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2021 international Mobile, Intelligent, and Ubiquitous computing conference, MIUCC 2021

作者： Abdelwahed, Ahmed S. Zekry, Abdelhalim Amer, Ghada Mohamed Tawfeek, Radwa M. Benha University Department of Electrical Engineering Benha Egypt Ain Shams University Department of Electronics and Communications Cairo Egypt

ISBN: (纸本)9781665412438

The increasing number of home appliances and the variation of technologies between them (modern or smart and legacy or old) is the reason for homes energy problem. In addition, increasing the peak load of grids facilities often causes electricity cuts of homes' sectors to reduce the overloads due to peak load. All of these reasons lead to use the energy management systems to reduce energy consumption and automatic control of home appliances to reduce billing for consumers, as well as utilities and decrease peak and peak-topeak *** this paper, an energy management system to automatically control energy of home appliances will be presented, by using MATLAB software simulation and by hardware using a Microcontroller through prototype to analyze the Demand Response. The proposed algorithm will handle consumption to achieve minimum power cost, decrease peak load according to the consumer priority, and guarantees total home power consumption without a certain limit. The accuracy of the algorithm illustrated through cases of different home scenarios showed that this algorithm is able to reduce the peak load by up to 39.5% compared to that without using the proposed algorithm. © 2021 IEEE.

关键词： Energy efficiency

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GWO-PI controlled Re-Lift LUO Converter for Standalone Load System

GWO-PI Controlled Re-Lift LUO Converter for Standalone Load ...

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international conference on Circuit, Power and computing Technologies (ICCPCT)

作者： Suguna R M. Muthalakshmi Pradeep Katta Mohammed Ovaiz A Tamilarasan G K D Arunachalam M Electrical and Electronics Engineering Vel Tech High Tech Dr.Rangarajan Dr.Sakunthala Engineering College Chennai India Bio Medical Engineering Vel Tech. Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Avadi Chennai India Electronics and Communication Engineering Vel Tech High Tech Dr.Rangarajan Dr.Sakunthala Engineering College Chennai India

When renewable energy resources started, it opened a new horizon to transmission and distribution of electrical energy. Several distributed energy resources are linked to the utility network or microgrid with the aid of a power electronic interface. However, the power quality is deteriorated by different factors such as varying load demands, changing weather condition and nonlinear loads. Hence, the proposed system aims to achieve improved power quality under balanced and unbalanced conditions with high control capability. To raise the quality of power at Distribution side of utility grid, three-phase four-leg VSI is used. In this proposed system, Photovoltaic system is used to supply power to load. Therefore, a DC-DC Relift Luo converter is used, which efficiently boosts the voltage gain while reducing the effects of parasitic elements over a large duty ratio range. Output of DC-DC converter is stabilized using a Grey Wolf Optimization (GWO) tuned PI controller and the effective grid voltage synchronization is achieved by the technique of feedback line controller. To ascertain the working of the proposed design in terms of its efficiency and dynamic compensation capability, a MATLAB based simulation model along with a laboratory prototype are developed and analyzed.

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Performance Boosting of automatic Sun Following Panels Using Soft computing Technique

Performance Boosting of Automatic Sun Following Panels Using...

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international conference on Contemporary computing and Informatics (IC3I)

作者： Shubhashis Goswami Kaushal Kumar Santosh Kumar D. Anandhasilambarasan S. Kannimuthu V.K. Kolekar School of Engineering and Computer Dev Bhoomi Uttarakhand University Uttarakhand India Department of Mechanical Engineering School of Engineering & Technology K. R. Mangalam University Gurugram India Department of Computer Applications Invertis University Bareilly India Department of Computer Science Engineering Karpagam Academy of Higher Education Coimbatore India Department of Information Technology Karpagam College of Engineering Coimbatore India Computer Engineering Vishwakarma Institute of Information Technology Pune India

The optimizing for the sun committee's tilt position using soft computation is subject of research study. At particular inclination angles above a flat surface, distinct radiation types provide various amounts of exposure. Properly set, the degree of tilt additionally delivers greater electricity using the exact same screen. A research on optimizing the slant inclination was done. Initially a significant power improvement was made by using genetic codes to continuously modify the slant angle. Sunny tracking is crucial to improving overall gadget performance for many solar-powered generators, concentrators, and rectangular plates. Mechanism honor, a key component of process functioning, is basic scientific method to modeling the procedure that is controlled either to identify plant undiscovered characteristics. An Automated network based on artificial intelligence is presented in order to define and simulate a dual axis sunlight tracking system. Both alongside and despite the application of scaled variables, a clear proportionate integral then a liquid-based logical control mechanism was investigated and integrated within the photovoltaic function.

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