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2023 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2023

作者： Jeong, Seunghun Park, Yejin Kim, Hong Kook Ai Graduate School Korea Republic of Gwangju Institute of Science and Technology School of Electrical Engineering and Computer Science Gwangju61005 Korea Republic of

ISBN: (纸本)9798350344318

This paper proposes an end-of-sentence (EOS) token modeling approach for streaming conformer-based Korean children's speech recognition applied to a social robot. The baseline system for speech recognition is a streaming conformer-based speech recognition model with the joint connectionist temporal classification attention-based encoder-decoder architecture, and it is trained with the AIHub Child•Infant Free-Talk dataset. However, it is difficult to determine sentence boundaries in children's speech because the speaking style of children is somewhat different from that of adults. Thus, the proposed approach is to insert EOS tokens into each sentence of a large children's dataset to detect sentence boundaries. Finally, we evaluated the performance of the proposed approach on a dataset collected under scenarios of a voice interaction between children and a social robot. Consequently, the proposed EOS token modeling decreased character error rate by 1.7%, compared to the baseline. © 2023 IEEE.

关键词： Speech recognition

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A Novel Method for Testing Digital ICs 3

A Novel Method for Testing Digital ICs

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3rd IEEE International Conference on Industrial Electronics: Developments and Applications, ICIDeA 2025

作者： Saw, Anjishnu Pradhan, Arjyadhara Dash, Nabakishor Rout, Minakhi Samal, Sarita School of Computer Science and Engineering KIIT Deemed to be University Bhubaneswar India School of Electrical Engineering KIIT Deemed to be University Bhubaneswar India

ISBN: (纸本)9798331533205

Digital Logic is the foundation of circuits and are used almost everywhere. The most commonly found and used digital logic are manufactured and used in the form of 16 pin DIP Package. The magnitude of its usage in both common and sophisticated electronics necessitates the verification of these ICs for their proper functioning. However traditional IC testers are often bulky as well as expensive and is not a popular option among hobbyists and small-scale industries. A novel and simple method has been employed to check these ICs in the form of Cloud Database Integration to check these ICs. The development of such an IC tester has been discussed in detail, highlighting all the aspects. This paper also explores all the benefits that are associated with this low-cost IC tester including accessibility and ease of use. Overall, this research paper aims to contribute in the field of IC testing by providing an efficient and feasible solution © 2025 IEEE.

关键词： Integrated injection logic circuits

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Retinal Blood Vessel Tracking and Diameter Estimation via Gaussian Process With Rider Optimization Algorithm

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IEEE Journal of Biomedical and Health Informatics 2024年第3期28卷 1173-1184页

作者： Ahmad, Nehal Lai, Kuan-Ting Tanveer, M. Indian Institute of Technology Indore Simrol Department of Mathematics Indore453552 India National Taipei University of Technology Department of International Program of Electrical Engineering and Computer Science Taipei106 Taiwan National Taipei University of Technology Department of Electronic Engineering Taipei106 Taiwan

Retinal blood vessels structure analysis is an important step in the detection of ocular diseases such as diabetic retinopathy and retinopathy of prematurity. Accurate tracking and estimation of retinal blood vessels in terms of their diameter remains a major challenge in retinal structure analysis. In this research, we develop a rider-based Gaussian approach for accurate tracking and diameter estimation of retinal blood vessels. The diameter and curvature of the blood vessel are assumed as the Gaussian processes. The features are determined for training the Gaussian process using Radon transform. The kernel hyperparameter of Gaussian processes is optimized using Rider Optimization Algorithm for evaluating the direction of the vessel. Multiple Gaussian processes are used for detecting the bifurcations and the difference in the prediction direction is quantified. The performance of the proposed Rider-based Gaussian process is evaluated with mean and standard deviation. Our method achieved high performance with the standard deviation of 0.2499 and mean average of 0.0147, which outperformed the state-of-the-art method by 6.32%. Although the proposed model outperformed the state-of-the-art method in normal blood vessels, in future research, one can include tortuous blood vessels of different retinopathy patients, which would be more challenging due to large angle variations. We used Rider-based Gaussian process for tracking blood vessels to obtain the diameter of retinal blood vessels, and the method performed well on the 'STrutred Analysis of the REtina (STARE) Database' accessed on Oct. 2020 (https://***/~ahoover/stare/). To the best of our knowledge, this experiment is one of the most recent analysis using this type of algorithm. © 2013 IEEE.

关键词： Blood vessels

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Dynamic Analysis and Stability Enhancement of a Weak Grid-Tied Hybrid System Integrating PV, Full-Scale Wind Turbine, and Battery Storage

IEEE Open Journal of Industry Applications

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IEEE Open Journal of Industry Applications 2025年 6卷 325-349页

作者： Magableh, Mohammad Adnan K. Radwan, Amr Mohamed, Yasser Abdel-Rady I. Jordan University of Science and Technology Electrical Engineering Department Irbid22110 Jordan University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G2V4 Canada Western Washington University Engineering and Design Department BellinghamWA98225 United States

Hybrid generation systems integrating photovoltaics (PV), full-scale wind turbines (WT), and battery energy storage systems (BESS) have garnered substantial interest for utility-scale grid-tied applications due to their enhanced efficiency and reliability. However, in a hybrid system integrating these resources at the dc-side of a voltage-source converter, the dc-link stability remains largely unexplored in existing literature, particularly under weak grid conditions and across different operational regions of the PV, WT, and BESS. This article presents a comprehensive small-signal stability analysis of a hybrid PV-WT-BESS system using detailed state-space and incremental impedance models. The analysis reveals that the hybrid system exhibits low-frequency oscillation instability in weak grid conditions when the PV operates in the current-limited region. A novel active damping strategy is introduced to mitigate these instabilities, effectively suppressing negative interaction dynamics and improving overall system stability;this is achieved by repositioning unstable eigenmodes and reshaping the dc-link dynamics to comply with the Nyquist stability criterion. The proposed compensation technique offers several key advantages: 1) it is simple yet effective and can be designed using linear analysis methods;2) it ensures stable operation under varying grid conditions without altering steady-state performance;3) it enhances the low-voltage ride-through capability;and 4) it eliminates the need for additional measurement sensors, thereby simplifying the implementation and reducing costs compared to alternative stabilization methods. Offline and real-time software-in-the-loop simulations validate the accuracy of the developed models and dynamic interactions, as well as the effectiveness of the proposed active stabilization approach across typical operating conditions. © 2020 IEEE.

关键词： Battery storage

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Information Constrained Optimal Transport: From Talagrand, to Marton, to Cover

Information Constrained Optimal Transport: From Talagrand, t...

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作者： Bai, Yikun Wu, Xiugang Ozgur, Ayfer Department of Electrical and Computer Engineering University of Delaware NewarkDE19716 United States Department of Computer Science Vanderbilt University NashvilleTN37212 United States Department of Electrical Engineering Stanford University StanfordCA94305 United States

The optimal transport problem studies how to transport one measure to another in the most cost-effective way and has wide range of applications from economics to machine learning. In this paper, we introduce and study an information constrained variation of this problem. Our study yields a strengthening and generalization of Talagrand's celebrated transportation cost inequality. Following Marton's approach, we show that the new transportation cost inequality can be used to recover old and new concentration of measure results. Finally, we provide an application of this new inequality to network information theory. We show that it can be used to recover almost immediately a recent solution to a long-standing open problem posed by Cover regarding the capacity of the relay channel. © 1963-2012 IEEE.

关键词： Machine learning

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A Comprehensive Analysis of Cloud Computing in Wireless Communications 2

A Comprehensive Analysis of Cloud Computing in Wireless Comm...

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2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Bansal, Anurag Sharma, Surbhi Shukla, Ajay Narayan Badhoutiya, Arti Research and Technology 13D Research & Strategy India Abes Engineering College Department of Computer Applications UP Ghaziabad India Computer Science & Engineering Graphic Era Hill University Uttarakhand Dehradun India Gla University Department of Electrical Engineering UP Mathura India

ISBN: (纸本)9798350371055

In the present-day digital landscape, cloud computing has grown to be a ubiquitous generation that offers numerous advantages to numerous businesses. Its software in wi-fi communications has had a mainly revolutionary effect, ultimately converting how data is transferred, considered, and saved. This looks at a thorough examination of how cloud computing has affected wireless communications, including its records, most important ideas, and programs. The primary phase of the object appears to be how cloud computing has changed over the years, moving from conventional on-premise computing to its current country, which includes a spread of service offerings and deployment methodologies. Subsequently, it explores the fundamental thoughts of cloud computing, which have virtualization, scalability, and on-demand provisioning, and talks about how these apply to wireless communications. The ability of cloud computing to grow network availability and dependability is one of its primary benefits for wi-fi communications. Using cloud-based computing and garage sources, network operators may additionally lower downtime and increase uptime for their services. They can also better manage unforeseen surges in community visitors and provide a higher user revel. The look additionally addresses how cloud computing helps the short rollout of the latest services and packages within the wireless communications industry. © 2024 IEEE.

关键词： Cloud Computing Data Storage Mobile Technology Network Security Wireless Communications

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Image based and Point Cloud based Methods for 3D View Reconstruction in Real-time Environment 14

Image based and Point Cloud based Methods for 3D View Recons...

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2024 IEEE 14th Annual Computing and Communication Workshop and Conference, CCWC 2024

作者： Agrawal, Arya Sharma, Teena Verma, Nishchal K. Vasikarla, Shantaram Vellore Institute of Technology School of Computer Science and Engineering Vellore India Indian Institute of Technology Mehta Family School of Data Science and Artificial Intelligence Guwahati India Indian Institute of Technology Dept. of Electrical Engineering Kanpur India California State University Dept. of Computer Science NorthridgeCA United States

ISBN: (纸本)9798350360134

3D view reconstruction in a real-time unknown environment poses several challenges to vision-based applications. Herein, this paper outlines real-time experimental results and analysis of 3D view reconstruction methods. Since real-time experimentation requires inputs from different sensors, this paper outlines the results of methods from the following categories: image based methods and point cloud based methods. This paper explains the detailed steps involved in 3D view reconstruction followed by an explanation of the methods. It provides detailed discussions, advantages, limitations, and empirical results, along with presenting differences between algorithms. For analysis of experimental results, two benchmarked datasets i.e., KITTI 3D benchmark suite and ShapeNet are considered. Furthermore, the paper explores potential future scopes, including the utilization of generative models, unsupervised learning, advanced sensors, and many more. © 2024 IEEE.

关键词： Network coding

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Adaptive Video Streaming: An AI-Driven Approach Leveraging Cloud and Edge Computing

Adaptive Video Streaming: An AI-Driven Approach Leveraging C...

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2023 IEEE International Conference on Artificial Intelligence, Blockchain, and Internet of Things, AIBThings 2023

作者： Darwich, Mahmoud Khalil, Kasem Ismail, Yasser Bayoumi, Magdy University of Mount Union Department of Mathematics and Computer Science AllianceOH44601 United States University of Mississippi University Department of Electrical and Computer Engineering MS38677 United States Southern University and AandM College Electrical Engineering Department Baton RougeLA70807 United States University of Louisiana at Lafayette Department of Electrical and Computer Engineering LA70504 United States

ISBN: (纸本)9798350322347

Video streaming efficiency remains a major challenge, with increasing demands for high-resolution content and minimal buffering times. We propose a novel solution to enhance user experiences. Our approach combines adaptive streaming, AI algorithms predicting network conditions, and edge computing to optimize task allocation. These technologies aim to reduce latency, lower network traffic, and facilitate seamless transitions in video quality. Our results improve the streaming services and enable real-time video applications in remote or mobile environments, presenting substantial implications for the future of video streaming. © 2023 IEEE.

关键词： Video streaming

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Robust Tweets Classification Using Arithmetic Optimization with Deep Learning for Sustainable Urban Living

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SN computer science 2024年第5期5卷 549页

作者： Hamza, Manar Ahmed Hashim, Aisha Hassan Abdalla Motwakel, Abdelwahed Elhameed, Elmouez Samir Abd Osman, Mohammed Kumar, Arun Singla, Chinu Munjal, Muskaan Department of Electrical and Computer Engineering International Islamic University Malaysia Kuala Lumpur 53100 Malaysia Department of Computer and Self Development Preparatory Year Deanship Prince Sattam bin Abdulaziz University AlKharj Saudi Arabia Department of Management Information Systems College of Business Administration in Hawtat bani Tamim Prince Sattam bin Abdulaziz University AlKharj Saudi Arabia Department of Computer Science College of Post-Graduated Studies University of Science and Technology Omdurman Sudan Department of Information System Faculty of Computer Science and Information Technology Omdurman Islamic University Omdurman Sudan Department of Electronics and Communication Engineering New Horizon College of engineering Bengaluru India Computer Engineering Thapar Institute of Engineering and Technology Punjab Patiala India

Natural Language Processing (NLP) with Deep Learning (DL) for Tweets Classification includes use of advanced neural network designs to analyse and classify Twitter messages. DL techniques like recurrent neural network (RNN) or transformer-based frameworks like BERT are used to mechanically learn difficult linguistic patterns and contextual info from tweet data. These techniques able to capture subtleties of language with sarcasm, sentiment, and context-specific meanings and making them suitable for tasks like sentiment analysis or topic classification in realm of social media. Leveraging deep symbols learned from great amounts of textual data, these NLP techniques permit precise and nuanced classification of tweets, donating to enhanced information retrieval, sentiment tracking, and trend analysis in dynamic and fast-paced world of social media communication. In this view, this research develops an arithmetic optimization algorithm with deep learning based tweets classification (AOADL-TC) approach for sustainable living. The goal of the AOADL-TC technique is to identify and discriminate different kinds of sentiments that exist in the tweet data. At the initial stage, the AOADL-TC model pre-processes tweet data to convert uniform data into a useful format. For sentiment detection, the AOADL-TC technique applies a parallel bidirectional gated recurrent unit (BiGRU) model. At last, tuning of parameters related to parallel BiGRU model performed by AOA. An wide set of tests carried out to illustrate better performance of AOADL-TC model. The experimental outcomes portrayed that AOADL-TC technique demonstrates the supremacy of the AOADL-TC technique in terms of different evaluation metrics. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Deep learning Machine learning Natural language processing Sentiment analysis Social media

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Smart Processing of Exceptional Values in electrical Networks Using Neuro-Fuzzy Algorithms

Smart Processing of Exceptional Values in Electrical Network...

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2024 IEEE International Students' Conference on electrical, Electronics and computer science, SCEECS 2024

作者： Anwar, Mahammad Kothiyal, Arnav Nandankar, Praful V. Barve, Amit Patil, Harshal Maranan, Ramya Ballari Institute of Technology and Management Ballari Visvesvaraya Technological University Department of Electrical and Electronics Engineering Karnataka India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun248002 India Government College of Nagpur Department of Electrical Engineering Maharashtra 441108 India Parul Institute of Technology Faculty of Engineering and Technology Parul University Department of Computer Science and Engineering P.O. Limda Gujarat 391760 India Department of Computer Science and Engineering Maharashtra Pune412115 India Saveetha School of Engineering Simats Department of Research and Innovation Tamil Nadu Chennai602105 India

ISBN: (纸本)9798350348460

This research introduces a novel smart meter topology within the context of an integrated PV-Wind hybrid system for DC electric micro-networks. The proposed topology incorporates advanced techniques such as Linear Interpolation, Artificial Neural Network (ANN), and Adaptive Neuro-Fuzzy Inference System (ANFIS) for identifying and correcting outliers in the collected data. The integration of the smart meter with outlier detection and correction modules enhances the accuracy and reliability of the measurements, contributing to the overall efficiency of the micro-network. Linear Interpolation is employed to estimate and fill in missing data points, ensuring a continuous and consistent dataset. The ANN module is designed to identify outliers by learning patterns from historical data, allowing for real-time anomaly detection. Furthermore, the ANFIS module enhances the system's adaptability by providing a fuzzy logicbased approach to correct outliers, taking into account the dynamic nature of renewable energy sources in the hybrid system. The proposed smart meter topology offers a comprehensive solution for ensuring the integrity of data collected in DC electric micronetworks. By leveraging the synergies of Linear Interpolation, ANN, and ANFIS, the system demonstrates improved robustness against data anomalies, thereby enabling more accurate monitoring, control, and optimization of the PV-Wind hybrid system. This research contributes to the advancement of smart grid technologies, particularly in the realm of renewable energy micro-networks, by addressing the challenges associated with data quality and reliability. © 2024 IEEE.

关键词： Integrated Control Mean Squared Error Micro-Networks Modeling outliers smart meter

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