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Integrating Advanced Applications in Industrial ADMS for Estimating PV Resources and Topology

IEEE Transactions on Industry Applications 2022年 1-6页

作者： Bajagain, Surendra Qin, Chuan Pannala, Sanjeev Srivastava, Anurag Dubey, Anamika School of Electrical Engineering and Computer Science Washington State University Pullman WA Lane Department of Computer Science and Electrical Engineering West Virginia University Morgantown WV

In contrast to traditional utility monitoring and operational tools, advanced distribution management systems (ADMS) provide the advanced operational features to monitor, secure and operate the distribution system in an integrated man- ner. Large-scale adoption of ADMS at utilities is in the early stage since advanced applications within ADMS environments are still evolving. The topology estimation module is one of the important and challenging ADMS application with enhanced automation. For accurate topology estimation, the topology estimator should capture both uncertainties due to load and PV injection in node measurement data. Load/PV estimation module can provide individual/disaggregated load and PV estimates and supports accurate network estimates. This paper provides a proof-of- the concept for the integration of advanced applications (Load/PV estimation and topology estimation) within an industrial ADMS environment using utility feeder data. IEEE

关键词： Network topology

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Novel Double-Damped Tuned AC Filters in HVDC Systems

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computers, Materials & Continua 2023年第4期75卷 1467-1482页

作者： Rana Shaheer Mehmood Asif Hussain Usman Ali Muhammad Tariq Mahmood Department of Electrical Engineering University of Management and TechnologyLahore54782Pakistan Department of Electrical and Computer Engineering Sungkyunkwan University2066Seobu-roJangan-guSuwon-si16419Gyeonggi-doKorea School of Computer Science and Engineering Korea University of Technology and Education1600ChungjeolnoByeogchunmyunCheonan31253Korea

This paper presents a performance analysis of novel doubledampedtuned alternating current (AC) filters in high voltage direct current(HVDC) systems. The proposed double-damped tuned AC filters offer theadvantages of improved performance of HVDC systems in terms of betterpower quality, high power factor, and lower total harmonic distortion (THD).The system under analysis consists of an 878 km long HVDC transmissionline connecting converter stations at Matiari and Lahore, two major cities inPakistan. The main focus of this research is to design a novel AC filter usingthe equivalent impedance method of two single-tuned and double-dampedtuned AC filters. Additionally, the impact of the damping resistor on the ACchannel is examined. TheTHDof theHVDCsystem with and without currentAC filters was also compared in this research and a double-damped tuned ACfilter was proposed. The results of the simulation represent that the proposeddouble-damped tuned AC filter is far smaller in size, offers better powerquality, and has a much lower THD compared to the AC filters currently inplace in the converter station. The simulation analysis was carried out utilizingpower systems computer-aided design (PSCAD) software.

关键词： Double-damped tuned AC filters harmonics high voltage DC systems long distance transmission power quality total harmonic distortion

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Navigation On Mobile computing Devices with A Walking Using Object-Oriented Techniques to Communicate Stick 3

Navigation On Mobile Computing Devices with A Walking Using ...

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3rd International Conference on Communication, Control, and Intelligent Systems, CCIS 2024

作者： Ramesh Prabhakaran, R. Guhan, P. Raj, E George Dharma Prakash Karthika, K. Angel Maanu, P. Mizoram University Department of Computer Engineering Mizoram India Panimalar Engineering College Department of Electrical and Electronical Engineering Chennai India Bharathidasan University School of Computer Science and Engineering Trichy India Karpagam College of Engineering Department of Information Technology Coimbatore India Panimalar Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798331528201

Moving around in their surroundings is challenging for elderly people and people with visual impairments. The majority of functional sticks in use today are not intelligent and lack an innate ability to recognize obstacles. In an effort to address this issue, mobility and orientation specialists who assist the blind by teaching them to move freely and safely using their remaining senses are brought in. They can navigate around obstacles with the aid of guidance dogs as well. These techniques have drawbacks, such as the dogs' inability to comprehend complicated instructions, the high cost of maintaining these trained dogs, and the need to hire an expert. In light of the aforementioned difficulties, the "Smart walking stick"has become a potential answer. The "Mobile based walking stick"is a useful mobility aid with the capacity to call a relative who can help in the event of an accident, detect obstacles above ground level and pits using ultrasonic sensors, recognize when a collision has occurred, and call the user's mobile phone if it has been misplaced to share the location's GPS for use with GSM connectivity and to share with the user's mention contacts. With some visually disabled people as test subjects, a test case was run, and 95% of the time it was successful. © 2024 IEEE.

关键词： Ultrasonic sensors

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A Comprehensive Review of Large Language Models in Abstractive Summarization of News Articles

A Comprehensive Review of Large Language Models in Abstracti...

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2024 Asia Pacific Conference on Innovation in Technology, APCIT 2024

作者： Bharathi Mohan, G. Akashvarma, M. Yashaswini, G. Keerthana, E. Siddharth, S. Saipooja, K. Prasanna Kumar, G. Doss, Srinath Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Chennai India Botho University Faculty of Engineering and Technology Botswana

ISBN: (纸本)9798350361537

Recent years have seen significant advancements in Large Language Models (LLMs), particularly in their application to natural language processing tasks. One prominent application is the abstractive summarization of news articles, a process that distills extensive textual information into a succinct yet comprehensive representation. The significance of this task lies in its capacity to efficiently distill key information. This paper focuses on evaluating the performance of various LLMs - Llama-2-7b, T5, Bart, and Pegasus - specifically fine-tuned on the CNN Daily dataset of news articles. QLoRA and Prompt-Based Fine-Tuning Approaches are employed systematically to compare the efficacy of these models in generating summaries that capture the essence of news articles. Evaluation metrics, including ROUGE, BLEU, and cosine similarity, are utilized to assess summarization quality. The findings reveal distinctive results among the selected LLMs such that Llama-2 excels in ROUGE-1 and ROUGE-L with scoreS of 0.45 and 0.427, Pegasus demonstrates remarkable performance in ROUGE-2 and cosine similarity with scores 0.19 and 0.6 respectively. © 2024 IEEE.

关键词： Natural language processing systems

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A roulette wheel-based pruning method to simplify cumbersome deep neural networks

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Neural computing and Applications 2024年第22期36卷 13915-13933页

作者： Chan, Kit Yan Yiu, Ka Fai Cedric Guo, Shan Jiang, Huimin School of Electrical Engineering Computing and Mathematics Sciences Curtin University Bentley Australia Department of Applied Maths The Hong Kong Polytechnic University Hong Kong School of Business Macau University of Science and Technology China

Deep neural networks (DNNs) have been applied in many pattern recognition or object detection applications. DNNs generally consist of millions or even billions of parameters. These demanding computational storage and requirements impede deployments of DNNs in resource-limited devices, such as mobile devices, micro-controllers. Simplification techniques such as pruning have commonly been used to slim DNN sizes. Pruning approaches generally quantify the importance of each component such as network weight. Weight values or weight gradients in training are commonly used as the importance metric. Small weights are pruned and large weights are kept. However, small weights are possible to be connected with significant weights which have impact to DNN outputs. DNN accuracy can be degraded significantly after the pruning process. This paper proposes a roulette wheel-like pruning algorithm, in order to simplify a trained DNN while keeping the DNN accuracy. The proposed algorithm generates a branch of pruned DNNs which are generated by a roulette wheel operator. Similar to the roulette wheel selection in genetic algorithms, small weights are more likely to be pruned but they can be kept;large weights are more likely to be kept but they can be pruned. The slimmest DNN with the best accuracy is selected from the branch. The performance of the proposed pruning algorithm is evaluated by two deterministic datasets and four non-deterministic datasets. Experimental results show that the proposed pruning algorithm generates simpler DNNs while DNN accuracy can be kept, compared to several existing pruning approaches. © The Author(s) 2024.

关键词： Deep neural networks

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One-Step Plasma Jet Deposition and Self-Sintering of Gold Nanoparticle Inks on Low-Temperature Substrates

IEEE Journal on Flexible Electronics

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IEEE Journal on Flexible Electronics 2024年第5期3卷 197-204页

作者： Manzi, Jacob Varghese, Tony Eixenberger, Josh Prakasan, Lakshmi Estrada, David Subbaraman, Harish Oregon State University School of Electrical Engineering and Computer Science CorvallisOR97331 United States Boise State University Department of Electrical and Computer Engineering Micron School of Material Science and Engineering BoiseID83725 United States Boise State University Micron School of Material Science and Engineering Center for Advanced Energy Studies BoiseID83725 United States Idaho National Laboratory Idaho FallsID83415 United States INFlex Labs LLC BoiseID83706 United States

Flexible electronics on low-temperature substrates like paper are very appealing for their use in disposable and biocompatible electronic applications and areas like healthcare, wearables, and consumer electronics. Plasma-jet printing (PJP) uses a dielectric barrier discharge plasma to focus aerosolized nanoparticles onto a target substrate. The same plasma can be used to change the properties of the printed material and even sinter in situ. In this work, we demonstrate the one-step deposition of gold structures onto flexible and low-temperature substrates without the need for thermal or photonic postprocessing. We also explore the plasma effect on the deposition of the gold nanoparticle ink. The plasma voltage is optimized for the sintering of the gold nanoparticles, and a simple procedure for manufacturing traces with increased adhesion and conductivity is presented, with a peak conductivity of 6.2\times 10{5} S/m. PJP-printed gold LED interconnects and microheaters on flexible substrates are developed to demonstrate the potential of this single-step sintered deposition of conductive traces on low-temperature substrates. © 2022 IEEE.

关键词： Sintering

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Leveraging LSTM and CNN for Video Understanding 6

Leveraging LSTM and CNN for Video Understanding

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6th Parul International Conference on engineering and Technology, PICET 2024

作者： Nishitha, Kapuluri Mohan, Bharathi G. Doss, Srinath Department of Computer Science and Engineering Amrita School of Computing Amrita University Chennai India Faculty of Engineering and Technology Botho University Gaborone Botswana

ISBN: (纸本)9798350369748

This research introduces a sophisticated framework for real-time video captioning that seamlessly integrates a cohesive ensemble of machine learning *** development of open-domain video descriptions that can manage variable-length input (sequences of words) and output (sequences of frames)while being sensitive to temporal structure is required due tothe complex dynamics present in real-world films. Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks are used to extract descriptive narratives and brief summaries from movies. LSTMs have demonstrated state-of- the-art performance in the generation of picture captions andare great at capturing sequential information. Our algorithmis trained on pairs of videos and matching texts to provide relevant captions for video events. It gains the ability to connecta string of words to a sequence of video frames. The modelnot only learns the temporal structure inside the sequence of frames, but also develops a language model for generating coherent and contextually relevant sentences. Our approach usesthe VGG16 model to extract visual features, which results in a rich representation of the video information. These visual cues, along with the LSTM-based sequence-to-sequence model, enable the production of elaborate captions that faithfully capture the temporal dynamics and visual aspects of the video clips. © 2024 IEEE.

关键词： Convolutional neural networks

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Analysis of Security Mechanisms Used in ETL Tools 32

Analysis of Security Mechanisms Used in ETL Tools

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32nd Telecommunications Forum, TELFOR 2024

作者： Jeftovic, Milica Vuletic, Pavle Stanisavljevic, Zarko Capgemini Engineering Belgrade Serbia University of Belgrade School of Electrical Engineering Department of Computer Science and Information Technology Belgrade Serbia

ISBN: (纸本)9798350391053

This paper analyses current best practices for using security mechanisms in extract, transform, and load (ETL) tools. The results of the analysis are visually represented in a form of an optimal security model used in these tools at the moment. In order to test the recommended model, it was implemented in a selected open source ETL tool. At the end, advantages and disadvantages of the recommended model are enlisted and directions for further improvement of the model are given. © 2024 IEEE.

关键词： ETL tools Security Mechanisms Security Model

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Feature Enhancer Segmentation Network (FES-Net)for Vessel Segmentation

Feature Enhancer Segmentation Network (FES-Net)for Vessel Se...

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2023 International Conference on Digital Image computing: Techniques and Applications, DICTA 2023

作者： Khan, Tariq M. Arsalan, Muhammad Iqbal, Shahzaib Razzak, Imran Meijering, Erik School of Computer Science & Engineering Unsw Sydney Australia Qatar University Kindi Center for Computing Research Doha2713 Qatar Department of Electrical and Computer Engineering Islamabad Pakistan

ISBN: (纸本)9798350382204

Diseases such as diabetic retinopathy and age-related macular degeneration pose a significant risk to vision, highlighting the importance of precise segmentation of retinal vessels for tracking and diagnosis of progression. However, existing vessel segmentation methods that heavily rely on encoder-decoder structures struggle to capture contextual information about retinal vessel configurations, leading to challenges in reconciling semantic disparities between encoder and decoder features. To address this, we propose a novel feature enhancement segmentation network (FES-Net) that achieves accurate pixel-wise segmentation without requiring additional image enhancement steps. FES-Net directly processes the input image and utilizes four prompt convolutional blocks (PCBs) during downsampling, complemented by a shallow upsampling approach to generate a binary mask for each class. We evaluate the performance of FES-Net on four publicly available state-of-the-art datasets: DRIVE, STARE, CHASE, and HRF. The evaluation results clearly demonstrate the superior performance of FES-Net compared to other competitive approaches documented in the existing literature. © 2023 IEEE.

关键词： Image enhancement

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Performance Analysis of Multiple HAPS-Based Hybrid FSO/RF Space-Air-Ground Network 16

Performance Analysis of Multiple HAPS-Based Hybrid FSO/RF Sp...

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16th International Conference on COMmunication Systems and NETworkS, COMSNETS 2024

作者： Singh, Deepshikha Swaminathan, R. Marrapu, Aravind Madhukumar, A.S. Indian Institute of Technology Indore Department of Electrical Engineering India School of Computer Science and Engineering Nanyang Technological University Singapore

ISBN: (纸本)9798350383119

Sixth generation (6G) networks are anticipated to support increasingly data-hungry applications by expanding the network capabilities and connectivity. Free space optics (FSO) communication with space-air-ground (SAG) network becomes a potential solution to meet the enormous traffic demands and ubiquitous connectivity requirement in 6G networks. In spite of various advantages offered by FSO communication such as high bandwidth availability, large unlicensed spectrum, better security, etc., the FSO link exhibits a high degree of responsiveness to atmospheric turbulence, attenuation, and pointing errors. Thus to mitigate the severe atmospheric effects, we propose a multiple high-altitude platform station (HAPS)-based SAG network, where HAPS functions as a decode-and-forward (DF) relay node between ground station and satellite. We take into account a hybrid FSO/radio frequency (RF) link for connecting ground station and HAPS nodes and an FSO link between HAPS and satellite. The performance analysis of the proposed SAG network involves evaluating the outage probability and average symbol error rate (SER) considering the presence of pointing errors and assuming Málaga distribution in case of FSO and shadowed k - μ fading distribution in case of RF link. Furthermore, asymptotic analysis is conducted to determine the diversity gain of the proposed system. Numerical results demonstrate that the proposed multiple HAPS-based hybrid FSO/RF SAG network outperforms all other existing HAPS-based SAG network models in the literature. © 2024 IEEE.

关键词： DF relaying free space optics (FSO) high-altitude platform station (HAPS) hybrid FSO/RF performance analysis

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