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1st International Conference on Intelligent Systems and Computational Networks, ICISCN 2025

作者： Abbas, Haayder M. Raju, P. V. Narasimha Shanthi, T. Venkateshwaran, P. Durgadevi, G. The Islamic University of Al Diwaniyah College of Technical Engineering Department of Computers Techniques Engineering Al Diwaniyah Iraq Sagi Rama Krishnam Raju Engineering College Department of Information Technology Bhimavaram India Sona College of Technology Department of Electronics and Communication Engineering Salem India Dhanalakshmi Srinivasan College of Engineering and Technology Department of Electronics and Communication Engineering Mamallapuram India New Prince Shri Bhavani College of Engineering and Technology Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798331529246

In recent days, the growing demand for automated language processing had brought Cross-Lingual Text Classification (CLTC) into focus as powerful approach for categorizing text across multiple languages which enabled users to classify documents in different languages. Traditional approaches for CLTC had faced several issues which include translation errors, dependency on parallel data and language representation gaps. Therefore, this research proposes Bidirectional Encoder Representations from Transformers (BERT) based Transfer Learning. Initially, data is collected from AG news, preprocessed by using Punctuation removal and Lemmatization which reduces irregularities in text data. After that, feature extraction is performed by using Term Frequency-Inverse Document Frequency (TF-IDF) which calculates word frequencies across documents by creating a high-dimensional feature vector representation. Further, features like semantic and contextual features are selected by using Mutual Information (MI). Finally, classification is done by using BERT-based transfer learning. The proposed BERT-based Transfer Learning achieved better results in terms of accuracy (95.5%) when compared with existing Indian Sentence BERT (IndicSBERT) model. © 2025 IEEE.

关键词： Semantics

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Optimizing Dual-Channel QMF Banks with Linear Phase Using Modified-GABC Approach: A Pathway to Enhanced Signal Processing

Optimizing Dual-Channel QMF Banks with Linear Phase Using Mo...

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2024 International Conference on Integrated Circuits, communication, and Computing Systems, ICIC3S 2024

作者： Daulat, Himani Varma, Tarun Chauhan, Krishna Gopal, Girdhar Malviya National Institute of Technology Department of Electronics and Communication Engineering Rajasthan Jaipur India VIT Bhopal University Department of Electronics and Communication Engineering Madhya Pradesh Bhopal India National Institute of Technology Department of Electronics and Communication Engineering Bihar Patna India

ISBN: (纸本)9798350364088

This work significantly advances optimized Quadrature Mirror Filter (QMF) bank design methodologies for promising signal processing and communication systems applications. An innovative approach to design a two-channel QMF bank utilizing Modified Gbest-Guided Artificial Bee Colony (Modified-GABC) optimization is presented. The primary goal is to optimize prototype filter coefficients, effectively minimizing the algebraic sum of prevalent errors in QMF bank design. The investigation showcases two design scenarios focusing on filter tap weights for N=32, and 100. A comprehensive analysis of performance parameters, encompassing pass band and stop band errors and squared error at quadrature frequency, is systematically conducted in MATLAB environment. Comparative assessment for N=32 underscores the superior performance of the proposed design, characterized by a reduced Measure Of Ripple (MOR) compared to existing techniques. © 2024 IEEE.

关键词： Optimization

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Position Estimation for Mobile Robots using Machine Learning 3

Position Estimation for Mobile Robots using Machine Learning

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3rd International Conference on Intelligent Data communication Technologies and Internet of Things, IDCIoT 2025

作者： Varma, Kallepalli Rahul Sreenivasan, Medha Srivani, N. Bhattacharya, Shourjyo Glace Varghese, T. Kochuvila, Sreeja Dept. of Electronics and Communication Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

Robot localization is a critical challenge present in autonomous robots to estimate their position within the environment, ensuring accurate navigation and task execution. This research project compares the position estimation capabilities of advanced machine learning methods Gradient Boosting and K-Nearest Neighbors. In this work Machine Learning (ML) models are built using a dataset from *** that tracked Received Signal Strength Indicator (RSSI) readings and tested them against strong performance measurements. This work findings show GB provides better results than KNN because it reaches an R2 score of 0.9341. These insights are applicable in various fields, including autonomous vehicles, industrial automation, service robotics, and multi-robot coordination, guiding the selection of appropriate algorithms for specific localization challenges. © 2025 IEEE.

关键词： Gradient Boosting K-Nearest Neighbors Machine learning Navigation Robot localization

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Design of a Compact Dual Band Antenna for 5G and Wimax Applications 3

Design of a Compact Dual Band Antenna for 5G and Wimax Appli...

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3rd IEEE International Conference on Distributed Computing and Electrical Circuits and electronics, ICDCECE 2024

作者： Suganyadevi, S. Priyadharsini, S. Raaghul Ganesh, S. Ramakrishnan, R. Sowmiya, R. Srinithi, P. Kpr Institute Of Engineering And Technology Department Of Electronics And Communication Engineering Tamil Nadu Coimbatore India

ISBN: (数字)9798350318609

ISBN: (纸本)9798350318609

For 5th Generation (5G) communications, a dual-band microstrip patch antenna system design is presented in this paper. It operates at two different frequencies: S-band (5.2 GHz) for Worldwide Inter-operability for Microwave Access (WiMAX) and sub-6 (3.5 GHz) for 5G communication. The antenna is meticulously designed to meet the exacting requirements of modern wireless communication systems, providing enhanced performance and versatility. Using a FR-4 substrate with a dielectric constant of 4.3 and a thickness of 2.4 mm, the antenna was developed. The VSWR value obtained is 1.38 dB and 1.75 dB which is acceptable. This study enhances connections for satellite navigation systems and 5G networks by combining sub-6 and S-band frequencies into a single antenna design, providing a small and affordable solution for a variety of communication needs. The suggested antenna design has excellent performance characteristics, which makes it a useful component for next-generation wireless communication technologies. © 2024 IEEE.

关键词： Wimax

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Multi-Channel CNN based image classification using SKIP connection and MSVM

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International Journal of Computers and Applications 2022年第10期44卷 981-990页

作者： Kesav, Nivea Jibukumar, M.G. Division of Electronics and Communication School of Engineering Cochin University of Science & Technology Kochi India

Deep learning innovations have paved way for effective classification algorithms using the Convolutional Neural Networks (CNNs). The current scenario uses very deep networks to improve the overall efficiency. This deep nature will result in increased complexity, a high number of parameters, increased execution time, and a more complex hardware platform for execution. Our research focuses on minimizing this complex nature of architecture. To achieve this, we employed the multi-channel CNN with a shallow layers approach, which consists of the main channel and side channels. The proposed work uses the Multi class Support Vector Machione (MSVM) as classifier and three distinct architectures with varied filter widths to acquire different performance characteristics. All these models are trained and tested on a brain tumor type database and performance parameters are compared to deep architectures like the Alexnet, VGG16, VGG19, and Resnet 50. When compared to deep architectures for the same database, our model can reduce the overall number of parameters and execution time with comparable accuracy. To improve the overall efficiency, our final architecture includes a skip connection. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Convolutional neural networks

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Smart Solutions for Automated Restaurant Service with Machine Learning 5

Smart Solutions for Automated Restaurant Service with Machin...

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5th International Conference on Data Intelligence and Cognitive Informatics, ICDICI 2024

作者： Srilekha, M.K. Shivaram Kumar, V.R. Umamaheswari, S. Sanjay Kumar, S. Srm Institute of Science and Technology College of Engineering and Technology Department of Electronics and Communication Engineering Kattankulathur India Srm Institute of Science and Technology Department of Electronics College of Engineering and Technology India

ISBN: (纸本)9798350389609

The Robotic technology has dramatically improved, sometimes exceeding even human capabilities and is now even invading every sphere of our lives. This development is used in hospitality industry where robots are increasingly being applied in speeding up processes in service deliveries, thereby optimizing service quality. Restaurants have recently become trendy towards a widespread use of robotic systems that can undertake an extremely wide range of tasks. These include taking orders, retrieving items from the kitchen, delivering food to tables, and even processing billing transactions as part of making the dining experience beautiful. This project deals with a smart delivery robot to deliver food in an efficient manner. The primary challenge in traditional restaurants has been the ability to deal with inconsistency in service, human errors, quicker and faster food and beverage delivery. Mechanically, the system is a line-following robot vehicle equipped with an Arduino module and advanced algorithms designed to navigate through a restaurant environment. The use of an RFID-based table identification and localization technique ensures precise delivery. The robot can follow a predetermined path into the destination with minimal deviation to ensure that orders are delivered accurately and promptly. The robots are to manage typical orders as best it could to retain the quality of service in a restaurant setting. Furthermore, distance travelled by the delivery robot and percentage of error is predicted through Gaussian Regression model. © 2024 IEEE.

关键词： Robot learning

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A Comparative Analysis of 8-Bit Parallel Prefix Adder Architectures 5

A Comparative Analysis of 8-Bit Parallel Prefix Adder Archit...

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5th International Conference on Smart electronics and communication, ICOSEC 2024

作者： Bharathi, M. Madhurima, V. Sandhyakumari, G. Poornima, M. Tabassum, Saleha Mohan Babu University Electronics and Communication Engineering Andhra Pradesh Tirupati India S V College of Engineering Electronics and Communication Engineering AndraPradesh Tirupati India Siddartha Institute of Science and Technology Electronics and Communication Engineering AndraPradesh Puttur India Ksrmce Electrical and Electronics Engineering AndraPradesh Kadapa India

ISBN: (纸本)9798331504403

Digital adders are crucial parts of contemporary computer systems that influence the efficiency of specific arithmetic processes. Parallel prefix adders, like Sparse Kogge, Hancarlson and Brent Kung enhance performance by calculating results leading to faster and more efficient arithmetic operations compared to traditional adders that process data sequentially. This paper thoroughly compares four 8 bit designs;Sparse Kogge, Han Carlson, Brent Kung and Binary Coded Decimal (BCD) adder. Evaluation criteria include propagation latency (ns) power consumption (W) and area utilization (LUTS). When comparing the Brent Kung adder with the BCD adder there is a 18.33% increase in propagation delay but a significant 83.87% decrease in power consumption and a fifty percent reduction in area usage. The primary focus of the Hancarlson adder is power efficiency leading to an 87.10% drop in power usage but a substantial 93.49% increase in propagation latency. The Sparse Kogge adder strikes a balance with a 58.06% decrease in power consumption and a moderate 18.75% reduction in area utilization while maintaining a propagation delay, as the BCD adder. These results illustrate trade-offs between various adder architectures in terms of power, latency, and area utilization. These designs are designed and simulated using Xilinx Vivado 2022.2 software. © 2024 IEEE.

关键词： Binary codes

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Modified Visual Geometric Group Architecture for MRI Brain Image Classification

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Computer Systems Science & engineering 2022年第8期42卷 825-835页

作者： N.Veni J.Manjula Department of Electronics and Communication Engineering SRM Institute of Science and TechnologyChennaiTamil NaduIndia Department of Electronics and Communication Engineering SRM Institute of Science and TechnologyChennaiIndia

The advancement of automated medical diagnosis in biomedical engineering has become an important area of *** classification is one of the diagnostic approaches that do not require segmentation which can draw quicker *** proposed non-invasive diagnostic support system in this study is considered as an image classification system where the given brain image is classified as normal or *** ability of deep learning allows a single model for feature extraction as well as classification whereas the rational models require separate *** of the best models for image localization and classification is the Visual Geometric Group(VGG)*** this study,an efficient modified VGG architecture for brain image classification is developed using transfer *** pooling layer is modified to enhance the classification capability of VGG *** show that the modified VGG architecture outperforms the conventional VGG architecture with a 5%improvement in classification accuracy using 16 layers on MRI images of the REpository of Molecular BRAin Neoplasia DaTa(REMBRANDT)database.

关键词： MRI brain images image classification deep learning VGG architecture pooling layers

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Modeling and Simulation of Virtual Reality Assistive Tool for Children with Autism Spectral Disorder 2nd

Modeling and Simulation of Virtual Reality Assistive Tool fo...

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2nd International Conference on Deep Sciences for Computing and communications, IconDeepCom 2023

作者： NirmalaPriya, G. Shree Aravindh, S.S. Tharun, D. Deepak, M. Hermalin, Cynthiya S. Department of Electronics and Communication Engineering Rajalakshmi Institute of Technology Chennai India Department of Computer and Communication Engineering Rajalakshmi Institute of Technology Chennai India

ISBN: (纸本)9783031689079

Autism spectrum disorder (ASD) is a prevalent issue contributing to deprivation among people in terms of their capability to maintain social relationships and interact normally with fellow members of society. Teens with ASD battle to exercise proper sociable behavior as well as mingle with others sharing the same age range. It affects all sorts of races, ethnicities and budgets alike. Despite its long- term nature, ASD has therapies and treatments that can help address issues associated with it such as restlessness, aggression, repetitive behavior, focus difficulties, worry and depression through the use of medicine. The use of virtual reality-based training, in addition to medical intervention, may be used to address various behavioral tradeoffs through repeated conditioning and learning. A variety of learning scenarios that would be unsafe, challenging, or time-consuming to set up or frequently recreate in the real world can now be simulated using virtual reality (VR) technology. In this paper, a virtual reality simulator for with the aid of social educators, achieve this goal. This study used the gaming program Social Activity Trainer to simulate and construct a virtual reality (VR)-based assistive aid (SAT). The assistive tool was created to help youngsters with ASD interact and use social skills. Based on three key skills—facial expression recognition, reading comprehension, and task delivery—seven tasks were created for the VR assistive tool. There are seven modules in a virtual reality scenario, including one for music therapy. The EEG signals are looked at to assess the degree of autism in 10 ASD children who participated in the test. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Diseases

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Maximizing WSN Lifetime Through Hierarchical Clustering for Efficient Energy Utilization and Prolonged Network Operation 10

Maximizing WSN Lifetime Through Hierarchical Clustering for ...

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10th International Conference on Advanced Computing and communication Systems, ICACCS 2024

作者： Murthy, M.V. H. Bhaskara Mohan, G. S. S. S. S. V. Krishna Shaik, Mahammad Firose Babu, G. Usandra Raja, Inakoti Ramesh Ansari, Shaik Tameem Aditya Institute of Technology and management Department of Electronics and Communication Engineering Tekkali India V R Siddhartha Engineering College Department of Electronics and Instrumentation Engineering Vijayawada India Aditya Engineering College Department of Electronics and Communication Engineering Surampalem India

ISBN: (纸本)9798350384369

This study presents a novel hierarchical clustering routing protocol for Wireless Sensor Networks (WSNs) designed to extend the network's overall lifespan. The protocol incorporates a (Cluster Head) CH rotating election mechanism, with the election criterion based on the weighted ratio total of residual energy and location information for nodes within each CH candidate area. Validation of the protocol's effectiveness involves assessing key metrics such as the initial node's death round, half of a node's death round, 80% of a node's death round, and the remaining energy after 80% of a node's death. Notably, the findings ensures a well-balanced impact on both operational rounds and the overall residual energy of the network. This cluster-based routing protocol not only demonstrates immediate utility but also lays the groundwork for future implementations and comprehensive performance metric analyses. It represents a significant step toward optimizing WSN lifetime by enhancing energy efficiency and promoting prolonged network operation. © 2024 IEEE.

关键词： Hierarchical clustering

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