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1st IEEE Global Emerging Technology Blockchain Forum: Blockchain and Beyond, iGETblockchain 2022

作者： Zikos, Ioannis Sendros, Andreas Drosatos, George Efraimidis, Pavlos S. Democritus University of Thrace Department of Electrical and Computer Engineering Xanthi67100 Greece Athena Research Center Institute for Language and Speech Processing Xanthi67100 Greece

ISBN: (纸本)9781665451987

Hyperledger Fabric is an open-source private permissioned blockchain that supports the use of smart contracts (chaincode). It is aimed mainly at private networks of companies. To serve the different needs of each company and to be flexible in customer requirements, it consists of various adaptive components. Although this structure efficiently addresses a wide range of needs, deploying such a network for research purposes or rapid development is complex. In this paper, we present a web-based system architecture for the automated deployment of a Hyperledger Fabric network, and in addition, we describe the tools needed to manage and update such a network. Finally, as a proof-of-concept, we implement the proposed architecture to demonstrate the feasibility of our approach. © 2022 IEEE.

关键词： Blockchain

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The Role of Artificial Intelligence (AI) in the Accounting and Auditing Professions 10

The Role of Artificial Intelligence (AI) in the Accounting a...

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10th IEEE Uttar Pradesh Section International Conference on electrical, Electronics and computer engineering, UPCON 2023

作者： Kaur, Harshdeep Arora, Geeta Salaria, Archana Singh, Arun Rakhra, Manik Dhiman, Gaurav Lovely Professional University Department of Mathematics Phagwara India University Institute of Engineering and Technology Department of Computer Science and Engineering Kathua India School of Computer Science and Engineering Lovely Professional University Phagwara India Lovely Professional University Department of Computer Science and Engineering Phagwara India Lebanese American University Department of Electrical and Computer Engineering Lebanon School of Sciences and Emerging Technologies Jagat Guru Nanak Dev Punjab State Open University Patiala India

ISBN: (纸本)9798350382471

The fast growth of business, science, and technology has ushered in the age of artificial intelligence, which has had far-reaching effects in every sphere of human existence. This article explains how AI may be used to detect and prevent accounting fraud and enhance the reliability of financial statements. Accounting and auditing firms may benefit or suffer from the advancement and use of artificial intelligence (AI). This article explains how AI can be used to reduce accounting fraud and boost the credibility of financial statements. The use of AI in these fields is not without its merits and drawbacks. Change is inevitable, and the accounting and auditing industry will undergo significant change in the near future. The report concludes by stressing the importance, in the broader context of AI, of accounting staff members developing their own expertise and proficiency. This research highlights the possible impacts of artificial intelligence (AI) on the accounting industry and the steps that need to be taken to prepare for a workforce in the future where AI plays a larger role. © 2023 IEEE.

关键词： component formatting insert style styling

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Object Acquizition of Stationary and Moving Targets 17

Object Acquizition of Stationary and Moving Targets

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17th IEEE International Conference on Advanced Trends in Radioelectronics, Telecommunications and computer engineering, TCSET 2024

作者： Riabyi, Myroslav Lyshevski, Sergey Edward Odarchenko, Roman National Aviation University Faculty of Computer Sciences and Technologies Kyiv Ukraine Rochester Institute of Technology Department of Electrical and Microelectronic Engineering RochesterNY United States National Aviation University Faculty of Air Navigation Electronics and Telecommunications Kyiv Ukraine

ISBN: (纸本)9798331520564

This paper studies near real time obj ect acquisition by means of detection, identification and engagement on stationary, moving and maneuvering targets in the air and land domains. Using the streamed videos from monochrome and color cameras, a machine vision concept accomplishes object detection by recognizing the object-specific edges and shapes which yield unique geometric features. Object recognition with descriptive identification at reasonable accuracy is performed using the Jaccard index. The region proposal detectors with the intersection over union is implemented by a convolutional neural network. The machine learning models, implemented by the low power system-on-module, were trained. These machine learning algorithms and models support feature detection and matching, localization, and, three-dimensional spatiotemporal reconstruction. The two-and three-dimensional geometry with object and background contrast and color mappings are considered. Subsequent tracking and locking on maneuverable targets is performed using spatio-temporal three-dimensional analytics. The airborne machine acquisition module with trained models is demonstrated. A concept suits monochrome, color and thermal analog and digital cameras. Experiments in typified operational environments demonstrate acceptable accuracy, convergence, low latency and near real-time capabilities for different object categories and classes within developed custom datasets. © 2024 IEEE.

关键词： Convolutional neural networks

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Coil Optimization using Metaheuristic Techniques for Wireless Charging of Electric Vehicles - A Comparative Analysis. 5

Coil Optimization using Metaheuristic Techniques for Wireles...

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5th International Conference on Power and Energy Technology, ICPET 2023

作者： Imtiaz, Tabish Elsanabary, Ahmed Mekhilef, Saad Mubin, Marizan Binti Soon, Tey Kok Aziz, Nur Fadilah Ab Universiti Malaya Department of Electrical Engineering Kuala Lumpur Malaysia Universiti Tenaga Nasional Institute of Power Engineering Selangor Kajang Malaysia Swinburne University of Technology School of Science Computing and Engineering Technologies Melbourne Australia Universiti Malaya Department of Computer System & Technology Kuala Lumpur Malaysia Universiti Tenaga Nasional Department of Electrical & Electronic Engineering Selangor Malaysia

ISBN: (纸本)9798350339673

Wireless Power Transfer (WPT) used for charging of electric vehicles (EVs), suffers from the problem of misalignment. In this paper metaheuristic optimizing techniques are used to increase the misalignment tolerance of the receiver coil. This is done by optimizing the length of each turn of the transmitter coil such that a uniform magnetic field density is produced over the charging area, which is kept 26% higher than the transmitting coil area which further aids to accommodate misalignment of the receiver coil. Differential Evolution (DE), Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) optimization algorithms are used to obtain the lengths of all the turns of the transmitter coil. These algorithms are also compared by varying the number of turns while keeping the number of iterations to a fixed value. © 2023 IEEE.

关键词： ABC Coil DE Misalignment Opti-mization PSO Wireless Power Transfer

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Steady State Analyses of DC-DC Converters Using MATLAB 3

Steady State Analyses of DC-DC Converters Using MATLAB

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3rd IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems, ICPEICES 2024

作者： Surya, Sumukh Chhetri, Ahilya Madhu, S. Williamson, Sheldon Bosch Global Software Technologies Pvt. Limited Bengaluru India Cactus Communications Mumbai India Bnm Institute of Technology Department of Electrical and Electronics Bengaluru India Ontario Tech University Electrical Computer and Software Engineering ONL1G0C5 Canada

ISBN: (纸本)9798350387193

Steady state analysis of a DC-DC converter is extremely important while designing controllers. In this paper, the steady-state analyses of different isolated and non-isolated dc-dc converters, such as Buck, Cuk, and Flyback, operating in continuous conduction mode (CCM) are conducted by solving non-linear algebraic equations using 'fsolve' in MATLAB software tool. In addition, the central processing unit (CPU) execution time and real-time taken by the software to solve these equations are measured. Furthermore, the minimum time required to achieve the steady state condition of different converters is measured. The number of iterations required to solve equations is found to be independent of the switching frequency but dependent on state variables. © 2024 IEEE.

关键词： MATLAB

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A Reliable 79GHz Band Ultra-Short Range Radar for ADAS/AD Vehicles Using FMCW Technology

A Reliable 79GHz Band Ultra-Short Range Radar for ADAS/AD Ve...

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2023 IEEE International Automated Vehicle Validation Conference, IAVVC 2023

作者： Ekolle, Zie Eya Kohno, Ryuji Ochiai, Hideki Sadamasa, Sawada Ikenji, Ishikawa Hiroshi, Ikeda Naomi, Ohashi Yokohama National University Yokohama Japan Infineon Technologies Atv Adas Shibuya Japan Yrp International Alliance Institute Yokosuka Japan Yokohama National University Department of Electrical and Computer Engineering Yokohama Japan Infineon Technologies Atv Adas Department Shibuya Japan

ISBN: (纸本)9798350322538

Vehicles can only be autonomous if their driving and parking operations are done by a driving assistant. Advanced driver assistance systems (ADAS) are driving assistant technolo-gies that aim to achieve this objective. ADAS generally consist of sensing and control technologies, and their performance definitely depends on the performance of these technologies. In this study, we present a sensing technology using radar, specifically the Frequency modulated continuous wave (FMCW) radar, of an ADAS-enhanced vehicle in a collision avoidance situation. We focus on close proximity collisions, which are difficult to detect by conventional short-range radars. We carried out a simulation based on an ADAS parking scenario, and the performance of the radar was measured in terms of its estimation limit, resolution, and accuracy, with values of 0-10m, 0.38m, and 0.2m, respectively. © 2023 IEEE.

关键词： Millimeter waves

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Improving Speaker Representations Using Contrastive Losses on Multi-scale Features

arXiv

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arXiv 2024年

作者： Dixit, Satvik Baali, Massa Singh, Rita Raj, Bhiksha Dept. of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh United States Language Technologies Institute Carnegie Mellon University Pittsburgh United States

Speaker verification systems have seen significant advancements with the introduction of Multi-scale Feature Aggregation (MFA) architectures, such as MFA-Conformer and ECAPA-TDNN. These models leverage information from various network depths by concatenating intermediate feature maps before the pooling and projection layers, demonstrating that even shallower feature maps encode valuable speaker-specific information. Building upon this foundation, we propose a Multi-scale Feature Contrastive (MFCon) loss that directly enhances the quality of these intermediate representations. Our MFCon loss applies contrastive learning to all feature maps within the network, encouraging the model to learn more discriminative representations at the intermediate stage itself. By enforcing better feature map learning, we show that the resulting speaker embeddings exhibit increased discriminative power. Our method achieves a 9.05% improvement in equal error rate (EER) compared to the standard MFA-Conformer on the VoxCeleb-1O test set. © 2024, CC BY.

关键词： Contrastive Learning

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Greek Sign language Recognition for the SL-ReDu Learning Platform 7

Greek Sign Language Recognition for the SL-ReDu Learning Pla...

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7th Workshop on Sign language Translation and Avatar Technology: The Junction of the Visual and the Textual Challenges and Perspectives, SLTAT 2022

作者： Papadimitriou, Katerina Potamianos, Gerasimos Sapountzaki, Galini Goulas, Theodor Efthimiou, Eleni Fotinea, Stavroula-Evita Maragos, Petros Department of Electrical & Computer Engineering University of Thessaly Volos Greece Department of Special Education University of Thessaly Volos Greece Institute for Language & Speech Processing Athena Research & Innovation Center Athens Greece School of Electrical & Computer Engineering National Technical University of Athens Greece

ISBN: (纸本)9791095546825

There has been increasing interest lately in developing education tools for sign language (SL) learning that enable self-assessment and objective evaluation of learners' SL productions, assisting both students and their instructors. Crucially, such tools require the automatic recognition of SL videos, while operating in a signer-independent fashion and under realistic recording conditions. Here, we present an early version of a Greek Sign language (GSL) recognizer that satisfies the above requirements, and integrate it within the SL-ReDu learning platform that constitutes a first in GSL with recognition functionality. We develop the recognition module incorporating state-of-the-art deep-learning based visual detection, feature extraction, and classification, designing it to accommodate a medium-size vocabulary of isolated signs and continuously fingerspelled letter sequences. We train the module on a specifically recorded GSL corpus of multiple signers by a web-cam in non-studio conditions, and conduct both multi-signer and signer-independent recognition experiments, reporting high accuracies. Finally, we let student users evaluate the learning platform during GSL production exercises, reporting very satisfactory objective and subjective assessments based on recognition performance and collected questionnaires, respectively. © European language Resources Association (ELRA), licensed under CC-BY-NC 4.0.

关键词： Deep learning

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Collage: Decomposable Rapid Prototyping for Information Extraction on Scientific PDFs

arXiv

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arXiv 2024年

作者： Gururaja, Sireesh Zhang, Yueheng Tang, Guannan Zhang, Tianhao Murphy, Kevin Yi, Yu-Tsen Seo, Junwon Rollett, Anthony Strubell, Emma Language Technologies Institute School of Computer Science United States Department of Materials Science and Engineering Carnegie Mellon University United States

Recent years in NLP have seen the continued development of domain-specific information extraction tools for scientific documents, alongside the release of increasingly multimodal pretrained transformer models. While the opportunity for scientists outside of NLP to evaluate and apply such systems to their own domains has never been clearer, these models are difficult to compare: they accept different input formats, are often black-box and give little insight into processing failures, and rarely handle PDF documents, the most common format of scientific publication. In this work, we present Collage, a tool designed for rapid prototyping, visualization, and evaluation of different information extraction models on scientific PDFs. Collage allows the use and evaluation of any HuggingFace token classifier, several LLMs, and multiple other task-specific models out of the box, and provides extensible software interfaces to accelerate experimentation with new models. Further, we enable both developers and users of NLP-based tools to inspect, debug, and better understand modeling pipelines by providing granular views of intermediate states of processing. We demonstrate our system in the context of information extraction to assist with literature review in materials science. Copyright © 2024, The Authors. All rights reserved.

关键词： Information retrieval

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Push-Pull based Grid tied Micro inverter for Photovoltaic Applications

Push-Pull based Grid tied Micro inverter for Photovoltaic Ap...

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2023 IEEE International Conference on Power Electronics, Smart Grid, and Renewable Energy, PESGRE 2023

作者： Paul, Preenu Jose, Babita R Shahana, T.K. Abraham, Chikku Mathew, Jimson Sandeep, J. Cochin University of Science and Technology Division of Electronics School of Engineering Cochin India Muthoot Institute of Technology and Science Department of Electrical and Electronics Engineering Ernakulam India Indian Institute of Technology Department of Computer Science and Engineering Patna India Sfo Technologies R & D Solutions Power Electronics Cochin India

ISBN: (纸本)9798350310573

This paper presents the harnessing of solar energy using a two-stage grid-tied micro inverter with an isolated high gain DC-DC converter as first stage and a single-phase grid tied inverter as second stage. High gain converter is implemented using a quasi-switched boost network, switched capacitor topology and push-pull circuit. High frequency transformer in first stage improves gain and provides isolation between solar Photovoltaic (PV) circuit and grid connection which add safety margins. Micro inverter topology, control logic for Maximum Power Point Tracking (MPPT) and H - bridge inverter is presented. The operation of a 250 V micro inverter is verified using MATLAB Simulink tool. © 2023 IEEE.

关键词： Grid tied inverter Isolated DC-DC converters MPPT One cycle control Switched boost topology Switched capacitor

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