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An amalgamation of integrated features with DeepSpeech2 architecture and improved spell corrector for improving Gujarati language ASR system

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International Journal of Speech technology 2024年第1期27卷 87-99页

作者： Dua, Mohit Bhagat, Bhavesh Dua, Shelza Department of Computer Engineering National Institute of Technology Kurukshetra India Department of Electronics Communication and Engineering Punjab Engineering College Chandigarh India

Automatic Speech Recognition systems that convert language into written text have greatly transformed human–machine interaction. Although these systems have achieved results, in languages building accurate and reliable ASR models for low resource languages like Gujarati comes with significant challenges. Gujarati lacks data and linguistic resources, making developing high-performance ASR systems quite difficult. In this paper, we propose an approach to enhance the effectiveness of a Gujarati ASR model despite resources. We achieve this by incorporating integrated features such as Mel Frequency Cepstral Coefficients (MFCC) and Gammatone Frequency Cepstral Coefficients (GFCC) utilizing the DeepSpeech2 architecture and implementing an improved spell correction technique based on the Bidirectional Encoder Representations from Transformers (BERT) algorithm. Our approach has demonstrated superiority over previous state-of-the-art methodologies through testing and evaluation. The experimental results demonstrate that our proposed method consistently reduces the Word Error Rate (WER) by 10–12 percentage points compared to the existing work, surpassing the most significant improvement of 5.87%. Our findings demonstrate the viability of developing accurate and dependable ASR systems for languages with limited resources, such as Gujarati. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Character recognition

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Verification of news and certificate, and plagiarism detector

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Multimedia Tools and Applications 2025年 1-28页

作者： Jain, Pushpak Anand, Dewansh Rajni Behal, Vansh Kapoor, Vipul Sharma, Neha Jindal, Neeru Department of Electronics and Communication Engineering Thapar Institute of Engineering and Technology Punjab Patiala India Department of Computer Science and Engineering Chitkara University Institute of Engineering and Technology Chitkara University Punjab Patiala India

Fake news, Fake certification, and Plagiarism are the most common issues arising these days. During this COVID-19 situation, there are a lot of rumors and fake news spreading and some of us are using fake certification to avoid vaccination and plagiarism became the most common topic during online studies. It is found that several apps and websites are present for the detection of false news and plagiarism. However, there is no single website for the detection of fake certificates. Moreover, nothing is made that consists of all these features in one platform. So, this proposed work develops a website for detecting fake news, Fake certificate, and plagiarism detector. The proposed method uses Natural Language Processing techniques for detecting NPC (news, plagiarism, and certificate). The proposed work uses image processing with some Python libraries like OpenCV in all the detections and that makes it quite interesting. For detecting NPC (news, plagiarism, and certificate) the algorithm is built using a k-mean model, logistic regression, and neural network. The proposed work uses the datasets that are trained using the count vectorizer method for the detection and to get its accuracy which will be tested using machine learning algorithms. The proposed method has shown an accuracy rate of 94.28% on Logistics Regression in comparison to existing methods. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Fake news Machine learning Natural language processing Plagiarism Social media platform

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A Novel Access Point Deployment Framework for mmWave Cell-Free Massive MIMO Networks

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IEEE Transactions on Wireless Communications 2025年第6期24卷 4581-4597页

作者： Topal, Ozan Alp Demir, Ozlem Tugfe Bjornson, Emil Cavdar, Cicek School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Electrical and Electronics Engineering TOBB University of Economics and Technology Ankara Turkey

Millimeter-wave network deployment is an essential and ongoing problem due to the limited coverage and expensive network infrastructure. In this work, we solve a joint network deployment and resource allocation optimization problem for a mmWave cell-free massive MIMO network considering indoor environments. The objective is to minimize the number of deployed access points (APs) for a given environment, bandwidth, AP cooperation, and precoding scheme while guaranteeing the rate requirements of the user equipments (UEs). Considering coherent joint transmission (C-JT) and non-coherent joint transmission (NC-JT), we solve the problem of AP placement, UE-AP association, and power allocation among the UEs and resource blocks jointly. For numerical analysis, we model a mid-sized airplane cabin in ray-tracing as an exemplary case for IDS. Results demonstrate that a minimum data rate of 1 Gbps can be guaranteed with less than 10 APs with C-JT. From a holistic network design perspective, we analyze the trade-off between the required fronthaul capacity and the processing capacity per AP, under different network functional split options. We observe an above 600 Gbps fronthaul rate requirement, once all network operations are centralized, which can be reduced to 200 Gbps under physical layer functional splits. 2002-2012 IEEE.

关键词： Integer programming

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PERFORMANCE ENHANCEMENT OF CIRCULARLY POLARIZED MICROSTRIP ANTENNA USING SINGLE-LAYER FOAM SUBSTRATE FOR 5.8 GHZ ISM BAND APPLICATIONS

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Telecommunications and Radio engineering (English translation of Elektrosvyaz and Radiotekhnika) 2025年第2期84卷 43-65页

作者： Hake, Shahadev Jaiswal, Rupesh Moon, Sunil Nikam, Pritam Kumar, Jayendra Department of Electronics and Telecommunication Engineering SCTR’s Pune Institute of Computer Technology Pune India Department of Electronics and Telecommunication Engineering KIT’s College of Engineering Kolhapur India School of Electronics Engineering VIT-AP University Andhra Pradesh India

Since last decade, a microstrip patch antenna has played a very important role in industrial, scientific, and medical (ISM) band applications, but single-layer antennae suffer from low gain and low radiation efficiency. For an ISM band, there is always a trade-off between these parameters, so maintaining it on a single-layer microstrip antenna is a big challenge. A circularly polarized (CP) microstrip antenna using a single-layer foam substrate has been designed for 5.8 GHz ISM band which offers high gain, improved radiation efficiency, and a lightweight design. It is constructed as a low-profile, single coaxial feed microstrip antenna on a foam substrate, achieving circular polarization by integrating two slots into the radiating patch antenna has dimensions of 0.98 λ0 × 0.98 λ0 × 0.096 λ0, impedance bandwidth of 600 MHz (5.56–6.16) GHz, which underscores its adaptability across a wide range of frequencies within the specified band. Furthermore, it elaborates the axial ratio bandwidth which extends over 130 MHz (5.77–5.90) GHz, showing the antenna’s ability to maintain circular polarization characteristics over a significant frequency range with a gain of 8.87 dB. The experimental and simulation results confirmed a remarkable radiation efficiency of 95.62%, showing its superior effectiveness compared to any existing single-layer microstrip antenna. © 2025 by Begell House, Inc.

关键词： Slot antennas

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From Past to Present: A Comprehensive Review of Antenna technology in Modern Wireless Communication

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Journal of engineering Science and technology Review 2024年第3期17卷 179-200页

作者： Mishra, Brijesh Singh, Aditya Kumar Satheesha, T.Y. Verma, Ramesh Kumar Singh, Vivek Department of Electronics and Communication Engineering School of Engineering and Technology CMR University Karnataka Bengaluru India Department of Electronics and Communication Engineering Noida Institute of Engineering and Technology U.P. Greater Noida India School of Computer Science Engineering REVA University Karnataka Bengaluru India Department of Computer Science and Engineering IMS Engineering College Uttar Pradesh Ghaziabad India Department of Electronics and Communication Engineering Nagarjuna College of Engineering and Technology Karnataka Bengaluru India

This research looks at microwave devices, specifically, patch antenna along with electromagnetic spectrum, shape, mechanism, analytical methods, simulation tools, and feeding procedures. Patch antennas are distinguished by their rectangular form, with a patch on one side and a ground plane on the other. Patch antennas work by exciting electromagnetic waves inside the patch, which are subsequently transmitted into the surrounding environment. The report also outlines numerous ways for evaluating the performance of microstrip patch antennas. The electromagnetic characteristics of the antenna are analyzed using the transmission line model, cavity model, and multiport network model (MNM). The integral equations that regulate the behavior of the antenna are solved using the method of moments (MoM) and the finite element method (FEM). The spectral domain technique (SDT) is used to analyze the antenna’s frequency response, while the finite difference time domain (FDTD) approach is used to analyze the antenna’s time-domain behavior. Overall, these methodologies give a thorough understanding of microstrip patch antenna performance and may be utilized to optimize their design. Furthermore, several patch antenna feeding methods, such as probe feed, microstrip line feeding, aperture coupling, proximity coupling, and CPW feed, are investigated. Attaching a microstrip line to the patch, which is subsequently linked to the RF source, is what microstrip line feeding entails. Aperture coupling entails making a hole in the ground plane that allows the RF source to feed the patch directly. Proximity coupling is accomplished by placing a probe near the patch, which creates an electromagnetic field on the patch. Patch antenna simulation software includes programmers such as HFSS, CST, and FEKO. These tools simulate the patch antenna’s performance, including its radiation pattern, gain, and input impedance. These simulations may be used to optimize the patch antenna design for specific a

关键词： Microstrip antennas

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A review on Gujarati language based automatic speech recognition (ASR) systems

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International Journal of Speech technology 2024年第1期27卷 133-156页

作者： Dua, Mohit Bhagat, Bhavesh Dua, Shelza Chakravarty, Nidhi Department of Computer Engineering National Institute of Technology Kurukshetra India Department of Electronics Communication and Engineering Punjab Engineering College Chandigarh Chandigarh India

Automatic speech recognition (ASR) plays a crucial role in facilitating natural and efficient human–computer interaction. This paper offers a comprehensive review of ASR systems tailored specifically for the Gujarati language. Existing literature on Gujarati ASR indicates that most survey papers have focused solely on back-end classification methods. This paper aims to fill this gap by presenting a comprehensive survey that encompasses feature extraction techniques, backend models, speech datasets, and evaluation metrics. This review provides an in-depth analysis of the cutting-edge methodologies employed in the development of Gujarati ASR systems. Firstly, the paper discusses various feature extraction techniques. Secondly, it covers classification models and their impact on ASR performance. Thirdly, the study delves into available speech datasets relevant to the Gujarati language, offering valuable insights for researchers and practitioners. Finally, the paper reviews the evaluation parameters used in ASR systems. Additionally, it gives an overview of online toolkits, resources, and language models pertinent to Gujarati ASR. This review serves as a comprehensive reference for academics and professionals involved in the research and development of ASR systems for the Gujarati language. The parameters selected for comparison include front-end feature extraction methods, back-end classification techniques, speech dataset, and evaluation metrics. Furthermore, the paper discusses both the contributions and limitations encountered by current ASR systems during the review. Finally, it addresses various challenges that still persist and provides directions for future research in this critical field. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Extraction

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Continuous word level sign language recognition using an expert system based on machine learning

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International Journal of Cognitive Computing in engineering 2023年第1期4卷 170-178页

作者： Sreemathy, R. Turuk, M.P. Chaudhary, S. Lavate, K. Ushire, A. Khurana, S. Department of Electronics and Telecommunication Engineering Pune Institute of Computer Technology Pune India

The study of sign language recognition systems has been extensively explored using many image processing and artificial intelligence techniques for many years, but the main challenge is to bridge the communication gap between specially-abled people and the general public. This paper proposes a python-based system that classifies 80 words from sign language. Two different models have been proposed in this work: You Only Look Once version 4 (YOLOv4) and Support Vector Machine (SVM) with media-pipe. SVM utilizes the linear, polynomial and Radial Basis Function (RBF) kernels. The system does not need any additional pre-processing and image enhancement operations. The image dataset used in this work is self-created and consists of 80 static signs with a total of 676 images. The accuracy of SVM with media-pipe is 98.62% and the accuracy of YOLOv4 obtained is 98.8% which is higher than the existing state-of-the-art methods. An expert system is also proposed which utilizes both the above models to predict the hand gesture more accurately in real-time. © 2023

关键词： Support vector machines

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COVID-19 Pandemic: A Worldwide Critical Review with the Machine Learning Model-Based Prediction

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Journal of The Institution of Engineers (India): Series B 2025年第1期106卷 339-349页

作者： Misra, Neeraj Kumar Das, Sanchali Satpathy, Sambit Addula, Santosh Reddy Trivedi, Munesh Chandra School of Electronics Engineering VIT-AP University Andhra Pradesh Amaravathi522237 India School of Computer Science Engineering and Technology Bennett University Greater Noida India Computer Science and Engineering Galgotias College of Engineering and Technology Greater Noida India Information Technology University of the Cumberlands Williamsburg United States Computer Science and Engineering PSSCIVE Bhopal Bhopal India

Machine learning (ML) with data analysis has many successful applications and is widely employed daily. Additionally, they have played a significant role in combating the global coronavirus (COVID-19) outbreak. International occurrences of the COVID-19 pandemic have resulted from the rapid global spread of the SARS-CoV-2 virus. In this study, we examine the ML and data analysis techniques for diagnosis, treatment, and impact of COVID-19, which are based on artificial intelligence (AI). Moreover, we provide an overview of the current state of the art in AI-based machine learning and deep learning techniques as well as the datasets, tools, and performance of the tools that can be used to combat COVID-19. In this survey, we have attempted to provide a comprehensive overview of the most recent state-of-the-art approaches available to researchers in Mathematical and Statistical analysis and the larger medical community as a whole. It also includes information on how data and ML can be used to improve COVID-19 status and encourage further research to prevent COVID-19 outbreaks. Future directions and problems are also described in detail. © The Institution of Engineers (India) 2024.

关键词： COVID-19

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"Survey and analysis of blockchain technologies with respect to: properties, algorithms, architecture, models, evolution and framework"

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Multimedia Tools and Applications 2025年第14期84卷 13571-13615页

作者： Tiwari, Nikita Ranjan, Prakash Biswal, Pradeep Kumar Barde, Chetan Sinha, Neha Department of Computer Science and Engineering Indian Institute of Information Technology Bhagalpur Bhagalpur India Department of Electronics and Communication Engineering Indian Institute of Information Technology Bhagalpur Bhagalpur India

The growing realm of blockchain technology has captivated researchers and practitioners alike with its promise of decentralized, secure, and transparent transactions. This paper presents a comprehensive survey and analysis of various blockchain technologies, focusing on their fundamental properties, architectural designs, operational models, evolutionary trends, and overarching frameworks. Through an extensive review of existing literature and empirical studies, this research synthesizes the multifaceted landscape of blockchain, elucidating key concepts such as consensus mechanisms, smart contracts, scalability, interoperability, and privacy protocols. By examining the evolution of blockchain from its inception to its current state and beyond, this paper delineates the trajectory of technological advancements and identifies emerging paradigms. Furthermore, it critically evaluates the strengths and limitations of diverse blockchain architectures and models, offering insights into their applicability across different domains and use cases. Finally, this study culminates in the proposal of a comprehensive framework that encapsulates the essential elements necessary for understanding, implementing, and harnessing the transformative potential of blockchain technologies. Through this holistic analysis, this research contributes to a deeper understanding of blockchain ecosystems and provides valuable guidance for future research directions and practical implementations. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Blockchain

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Deep learning and machine learning based highly accurate reflection prediction model for multi layers anti-reflection coatings

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Optical and Quantum electronics 2025年第1期57卷 1-22页

作者： Oktay, Semih Duru, İremnur Bakır, Halit Tabaru, Timuçin Emre Department of Electrical-Electronics Engineering Sivas University of Science and Technology Sivas Turkey Computer Engineering Department Sivas University of Science and Technology Sivas Turkey

This study focuses on creating an accurate reflection prediction model that will guide the design of filters with multilayer Anti-Reflection Coating (ARC) to optimize the thickness parameters using Machine Learning (ML) and Deep Learning (DL) techniques. This model aims to shed light on the design process of a multilayer optical filter, making it more cost-effective by providing faster and more precise production. In creating this model, a dataset containing data obtained from 3000 (1500 Ge–Al2O3, 1500 Ge–SiO2) simulations previously performed on a computer based on the thicknesses of multilayer structural materials was used. The data are generated using Computational Electromagnetic simulation software based on the Finite-Difference Time-Domain method. To understand the mechanism of the proposed model, two different two-layer coating simulations were studied. While Ge was used as the substrate in both coatings, Al2O3 and SiO2 were used as the second layers. The data set consists of the 3–5 µm and 8–12 µm bands typical for the mid-wave infrared (MWIR) and long-wave infrared (LWIR) bands and includes reflectance values for wavelengths ranging between these spectra. In the specified 2-layer data set, the average reflectance was obtained with a minimum of 0.36 at 515 nm Ge and 910 nm SiO2 thicknesses. This value can be increased by adapting the proposed model to more than 2 layers. Six ML algorithms and a DL model, including artificial neural networks and convolutional neural networks, are evaluated to determine the most effective approach for predicting reflectance properties. Furthermore, in the proposed model, a hyperparameter tuning phase is used in the study to compare the efficiency of ML and DL methods to generate dual-band ARC and maximize the prediction accuracy of the DL algorithm. To our knowledge, this is the first time this has been implemented in this field. The results show that ML models, particularly decision tree (MSE: 0.00000069, RMSE: 0.00083), rand

关键词： Antireflection coatings

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