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A New Three-phase Multi-mode AC/DC LLC Converter with Output-controlled Active Rectifier (with V2G and G2V functions) For Fast DC Charging Application

A New Three-phase Multi-mode AC/DC LLC Converter with Output...

引用

Annual IEEE Conference on Applied Power Electronics Conference and Exposition (APEC)

作者： Xiaoyi Xia John Lam Dept. of Electrical Engineering and Computer Science York University Toronto Canada

ISBN: (数字)9798331516116

ISBN: (纸本)9798331516123

This paper proposes a new three-phase multi-mode AC/DC LLC resonant converter with an output-controlled active rectifier for electric vehicle (EV) fast DC charging applications. In the proposed approach, two low-frequency bidirectional switches at the primary side in each phase of the converter allow vehicle-to-grid (V2G, i.e. DC/AC mode) and grid-to-vehicle (G2V, i.e. AC/DC mode) modes. When the proposed converter operates in AC/DC mode, each phase consists of an integrated bridgeless boost power factor corrector and an LLC resonant converter at the primary side. Output voltage regulation is managed by switches on the high frequency transformer's secondary side output rectifier in each phase, with soft-switching operation achieved in all the switches. When the proposed three-phase converter operates in DC/AC mode, each phase consists of a half-bridge DC/DC resonant converter cascaded with a half-bridge grid-side inverter. The operation of the proposed converter is explained in this paper. Results from a 20kW, 480V LLrms /350Vdc, 130kHz design, and a hardware test on a 130kHz, 250V-output proof-of-concept prototype are presented to validate the functionality of the proposed converter.

关键词： Vehicle-to-grid Reactive power Rectifiers Prototypes Resonant converters Zero voltage switching Transformers Hardware Fast charging Voltage control

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Survey of AI and Optimization Methods for DoS Attack Detection in WSNs

Survey of AI and Optimization Methods for DoS Attack Detecti...

引用

Trends in Material science and Inventive Materials (ICTMIM), International Conference on

作者： Kamparapu V V Satya Trinadh Naidu S. Lakshmana Pandian Dept. of Computer Science and Engineering Puducherry Technological University Puducherry India

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

The use of Wireless Sensor Networks (WSNs) in modern IoT applications is very important, as they can monitor and transmit data in different environments. Although their open communication nature, limited energy, and computational capacity render them highly vulnerable to Denial-of-Service (DoS) attacks that will deteriorate network performance and reliability significantly. This survey covers all aspects of recent developments using artificial intelligence (AI) based techniques for the detection and prevention of DoS attacks in wireless sensor networks (WSNs). It gives particular attention to the integration of deep learning models and metaheuristic optimization strategies in terms of making their detection accuracy better, minimizing predication of false positives, and improving the model’s adaptability in the way of constraints of resource limits. Real time DoS detection has been studied under the perspective of different ensemble learning strategies, hybrid deep learning frameworks, and feature selection methods. The paper also examines the efficiency of the dimensionality reduction and heuristic tuning techniques in improving model performance. It also discusses future research directions, challenges and open issues that are meant for guiding future innovation in this domain.

关键词： Deep learning Surveys Wireless sensor networks Adaptation models Accuracy Metaheuristics Intrusion detection Denial-of-service attack Real-time systems Artificial intelligence

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Pedestrian Group Detection with K-Means and DBSCAN Clustering Methods

Pedestrian Group Detection with K-Means and DBSCAN Clusterin...

引用

2022 IEEE International Conference on Electro Information Technology, eIT 2022

作者： Chen, Mingzuoyang Banitaan, Shadi Maleki, Mina Li, Yichun University of Detroit Mercy Dept. of Electrical & Computer Engineering & Computer Science DetroitMI United States

ISBN: (纸本)9781665480093

The development of autonomous vehicles has made real-time pedestrian detection and tracking an important research area for protecting human lives and improving society. A key challenge in this area is to improve pedestrian detection accuracy while reducing the processing time for tracking. This challenge can be addressed by detecting and tracking pedestrian groups since pedestrians move in groups. This paper proposes a method of detecting pedestrian groups using unsupervised machine learning methods. After detecting the pedestrians, K-Means and DBSCAN clustering methods were used to detect pedestrian groups based on the coordinates of pedestrians' bounding boxes. Simulation results of the MOT17 dataset indicate that both clustering techniques could reduce detection and tracking processing times. However, K-Means clustering is more effective than DBSCAN clustering in detecting pedestrian groups as measured by the Silhouette Coefficient score and Adjusted Rand Index (ARI). © 2022 IEEE.

关键词： Object detection

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Streamline Pro Next-Gen Recruitment Solution

Streamline Pro Next-Gen Recruitment Solution

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Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), International Conference on

作者： Vinod Kumar Sangeetha G Gopal K Kumar P Dept. of Computer Science and Engineering Rajalakshmi Engineering College Chennai India

ISBN: (数字)9798331543624

ISBN: (纸本)9798331543631

An innovative full-stack project called “StreamlinePro Next-Gen Recruitment Solution” aimsto transform the hiring process. With its modern technologies, this fully inclusive platform enhances the hiring process to satisfy the demands of administrators, HR professionals, and job seekers. The Job Board Application is developed around a powerful system for posting jobs and accepting applications. Experts in human resources can readily post job openings, andneed to offer corporate papers to validate their skills. This ensures that reliable sources are used to publish job openings. Conversely, candidates can use the website to look for jobs that fit their qualifications and apply immediately. Posting resumes is required, and an applicant tracking system (ATS) reviews them after are uploaded. After reviewing the entries, the ATS rates the resumes according to theirquality and applicability. One of the primary aspects of the StreamlinePro Next-Gen Recruitment Solution is its exclusive referral mechanism. Employees in a company may indicate that are willing to suggest others. Job searchers can contact these references, and if accepted, both parties can communicate through an integrated chat system. This recommendation system encourages networking and enhances job-seeking opportunities by leveraging existing staff networks. The application also offers the capability of real-time job status tracking. Applicants can monitor the progress of their applications and receive alerts regarding their receipt, review, and acceptance by employers. This tool helps clarity and informs job seekers during the hiring process.

关键词： Reviews Resumes Companies Transforms Real-time systems Reliability Recommender systems Monitoring Recruitment Qualifications

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Early Thermal Forest Fire Detection using UAV and Saliency map 5

Early Thermal Forest Fire Detection using UAV and Saliency m...

引用

5th International Conference on Contemporary Computing and Informatics, IC3I 2022

作者： Dilli, B. Suguna, M. Thiagarajar College of Engineering Dept. of Mechanical Engineering Tamil Nadu Madurai India Thiagarajar College of Engineering Dept. of Computer Science Engineering Tamil Nadu Madurai India

ISBN: (纸本)9798350398267

Wildfire is a dangerous disaster that threatens not only animals but also humans. Traditionally, Ground crew inspections form the basis for firefighting monitoring systems, which have several limitations. With the help of UAVs, before a wildfire becomes out of control, it is simple to spot it in its early stages. The last few years have seen a surge in interest in autonomous wildfire early detection using various deep learning algorithms based on UAV-based visual data. But the area of night vision surveillance is unattended. In this research, we concentrate on detecting the early stage of wildfires using YOLO model, a DL based object detection library on thermal images from UAVs and also the drawbacks in using the thermal images are solved using saliency maps fused with thermal images, which is then compared with the benchmark of the YOLO model trained only on thermal images. The proposed methodology is found to be capable enough to provide technical support in night surveillance to reduce the catastrophic losses of wild forest fires in their early stages and in terms of forest resources, and human and animal lives. © 2022 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Evaluating Large Language Model Understanding of Due Process

Evaluating Large Language Model Understanding of Due Process

引用

Computing and Machine Intelligence (ICMI), International Conference on

作者： Joshua P. Johnson Adrian P. Lauf Dept. of Computer Science and Engineering University of Louisville Louisville US

In this paper the Llama-2 and GPT-2 large language models are evaluated for their fundamental understanding of basic due process concepts. The reference implementations and versions fine-tuned on judicial opinions wer... 详细信息

ISBN: (数字)9798350372977

ISBN: (纸本)9798350372984

关键词： Law Computational modeling Large language models Decision making Reliability Machine intelligence Context modeling

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Advanced Cryptocurrency and Stock Prices Forecasting via Bidirectional Long Short-Term Memory Model

Advanced Cryptocurrency and Stock Prices Forecasting via Bid...

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data science, Agents & Artificial Intelligence (ICDSAAI), International Conference on

作者： Ramsriprasaath D R. Bhavani S. Pavithra Dept. of Computer Science and Engineering Chennai Institute of Technology Chennai India

ISBN: (数字)9798331537555

ISBN: (纸本)9798331537562

Truthful prediction of the values of the cryptocurrencies and stocks is critical in the financial marketplace. We developed a Bi-Lstm model to forecast the next day prices of Bitcoin, Ethereum, and Microsoft stock. The model expands the temporal resolution to the 60-day sequence window, making predictions of financial time series more reliable due to higher temporal dependencies. The effectiveness of the model is evaluated using three error metrics: Hence, use of Mean Squared Error, Root Mean Squared Error, and Mean Absolute Percentage Error was employed to guarantee accurate evaluation. Anticipating prices for the year 2025, the proposed system provides information for overall long-term tendencies and possible gains from investments. The findings reveal that the application of Bi-Lstm model can avert the categories of fluctuation that characterises the financial market and is a powerful instrument for making future predictions. The future work might improve the accuracy of the predictions by incorporating other features like market sentiment and macroeconomic indicators.

关键词： Sentiment analysis Recurrent neural networks Accuracy Operating systems Time series analysis Bitcoin Predictive models Macroeconomics Blockchains Long short term memory

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Nonparametric Estimation of Local Bandwidth from Level Crossings Sampling

Nonparametric Estimation of Local Bandwidth from Level Cross...

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2023 International Conference on Sampling Theory and Applications, SampTA 2023

作者： Pawlak, Miroslaw Rzepka, Dominik Miskowicz, Marek Agh University of Science and Technology Dept. of Measurement and Electronics Krakow Poland University of Manitoba Canada Dept. of Electrical and Computer Engineering WinnipegR3T 5V6 Canada

ISBN: (纸本)9798350328851

We study the problem of a local bandwidth recovery for nonstationary stochastic signals when the measured information is given in terms of level crossings. We propose a kernel estimate of the local bandwidth from samples generated from level crossings of stochastic signals being the time-warped version of stationary Gaussian processes. The positivity and bandlimited nature of the local intensity is captured by the properly selected class of bandlimited and positive kernel functions. The asymptotic properties of the estimator are derived. © 2023 IEEE.

关键词： Railroad crossings

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Printed Direction Finding Antenna Array Based on a Center-End Feed Dipole-Like Radiator 16

Printed Direction Finding Antenna Array Based on a Center-En...

引用

16th IEEE International Scientific and Technical Conference Actual Problems of Electronic Instrument engineering, APEIE 2023

作者： Kolesnikov, Andrey A. Alekseytsev, Sergey A. Gorbachev, Anatoly P. Dept. of Radio Receivers and Radio Transmitters Novosibirsk State Technical University Novosibirsk Russia Dept. of Automation and Computer Science Novosibirsk State Technical University Novosibirsk Russia

ISBN: (纸本)9798350330885

The article analyses a dipole-like radiator with a central-end feed. On the base of the method of induced electromotive forces and mirror images, expressions for the description of the input impedance of the radiator above ground have been obtained. According to the results of calculations the graphs of dependences of real and imaginary parts of the complex input impedance of the dipole-like radiator with center-end feed on the height above the ground are plotted, which can be used in the future for the formation of the initial antenna topology. Electrodynamic models of printed antenna arrays with sum and difference radiation patterns based on a center-end fed dipole-like radiator are presented. Using the simulation results, a prototype antenna with difference radiation pattern has been designed and synthesized. The presented prototype is characterized by a high matching degree between the experimental and simulated characteristics. The proposed antenna with a differential radiation pattern can be used in radiolocation equipment, radio monitoring and radio control system. © 2023 IEEE.

关键词： Radiators

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Intelligent Route Planning for Post-Earthquake Rescues Using IoT

Intelligent Route Planning for Post-Earthquake Rescues Using...

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International Conference on Electrical engineering and Information & Communication Technology (ICEEICT)

作者： Rahat Tamzid Ehfaz Faisal Mahee Ashikur Rahman Tahira Akhtar Tamanna Muntasir Rahman Md. Mamun Hossain Dept. of Computer Science and Engineering Bangladesh University of Business and Technology

ISBN: (数字)9798350385779

ISBN: (纸本)9798350385786

Starting rescue operations quickly after an earth-quake is the best way to save lives in such disasters. In the case of large-scale earthquakes, current post-earthquake response systems cannot determine which building or rescue route would save the most lives due to the lack of real-time data availability. Research gaps include a lack of automation in earthquake damage assessment of buildings, location identification, and estimation of the number of trapped people. To fill these gaps, this article proposed an innovative solution using advanced sensors and cloud services for post-earthquake rescue route planning systems. This system aims to improve rescue operations to save the maximum number of lives in the shortest time and minimize impacts by optimizing resource allocation and overall response efficiency. By filling the existing research gap, our system seeks to provide more responsive and effective solutions to post-earthquake emergencies. Tested in a simulated environment with 16 samples, our system successfully collects and processes data from IoT devices deployed in buildings, classifies structural damage, and estimates the number of people affected. Our approach significantly reduces the time required to initiate rescue operations by providing rescuers with optimized routes to disaster sites, which has potential implications for disaster management strategies.

关键词： Navigation Disasters Earthquakes Buildings Sensor systems Real-time systems Planning

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