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4th IEEE International Conference on Applied Electromagnetics, Signal Processing, and communication, AESPC 2024

作者： Dandapat, Soumya Bebortta, Sujit Prabhu, Smitha Mukherjee, Tanmay University Department of Computer Science and Engineering Bhubaneswar751030 India Ravenshaw University Department of Computer Science Cuttack753003 India NMIT Department of Electronics and Communication Engineering Bengaluru560064 India

ISBN: (纸本)9798331528171

Fading channels are a common problem in real-world wireless communication environments, causing signal deterioration over the propagation path. This study portrays the fading channels effects in wireless communication systems. Main objective is to provide contrasting approximation methods to improve wireless communication performance and reliability in fading scenarios. The study will examine innovative signal processing techniques in context to symbol error probability (SEP) towards different adaptive modulation schemes, and channel coding strategies to counteract the negative impacts of fading. The challenges refer to the random fluctuations in signal intensity and quality resulting from fading channels. These fluctuations have the potential to cause data loss, increased error rates, and decreased communication efficiency in general. Through comprehension and characterization of the fading phenomenon, the research aims to develop resilient solutions that guarantee smooth communication in different environments. In this setting, the SEP evaluation with respect to two different approximations have been portrayed and analyzed. The integrals required to compute the SEP have been assessed and presented in closed form considering the Nakagami-m fading channels. © 2024 IEEE.

关键词： Adaptive modulation

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A novel enhanced lemurs optimization-based hybrid attention network for classifying arrthymia from ECG signal using optimal weighted feature

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Australian Journal of Electrical and electronics engineering 2024年第3期21卷 311-335页

作者： Wajgi, Rakhi Brammya, G. Ramesh, Gopisetty Deotare, Vilas Vasudeo Govindasamy, Chinnaraj Preetha, N.S. Ninu Department of Computer Technology Yeshwantrao Chavan College of Engineering Nagpur India Department of Electronics and Communication Engineering Resbee Info Technologies Private Limited Chennai India Department of EIE CVR College of Engineering Mangalpalli India Professor in E&TC Savitribai Phule Pune University Pune India Department of Computer Science and Engineering Saveetha School of Engineering Kuthambakkam India

An arrhythmia is just a disease associated with irregular heart rhythm. Any kind of arrhythmia can be determined with an ECG test. However, this requires long and excellent-quality of ECG samples. This makes an affordable, reliable, and automated system for recognizing and diagnosing arrhythmias. To meet the aforementioned criteria, a new technique with the aid of an attention-aided deep learning approach is proposed to classify arrhythmia in this paper. "Higher-order statistical (HOS)" features are extracted from the original EEG signal and the deep features are obtained from the analyzed QRS complex signals and RR interval by means of a "One-Dimensional Convolution Neural Network (1DCNN)". The Risk Rate Enhanced Lemurs Optimization Algorithm (RRE-LOA) is utilized to modify the weight, and the extracted features are selected optimally before carrying out the feature selection followed by feature concatenation with weight fusion in order to generate the Weighted Fused Features (WFF). A range of indicators is used to compare the performance of the executed classification model with the traditional models. The results demonstrate that the proposed methodology for classifying arrhythmias offers an enhanced performance while classifying the arrhythmia thus aiding in faster treatment of the arrhythmia disease. ©, Engineers Australia.

关键词： Electrocardiograms

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Design and Analysis of a UWB Slotted Vivaldi Antenna for Microwave Imaging Applications

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IEIE Transactions on Smart Processing and Computing 2023年第4期12卷 350-357页

作者： Paul, Liton Chandra Majumder, Akash Rani, Tithi Hossain, Md. Najmul Rahim, Md. Abdur Shin, Jungpil Yun, Keun Soo Department of Electrical Electronic and Communication Engineering Faculty of Engineering and Technology Pabna University of Science and Technology Pabna6600 Bangladesh Department of Electronics & Telecommunication Engineering Faculty of Electrical & Computer Engineering Rajshahi University of Engineering & Technology Rajshahi6204 Bangladesh Department of Computer Science and Engineering Faculty of Engineering and Technology Pabna University of Science and Technology Pabna6600 Bangladesh School of Computer Science and Engineering The University of Aizu / Fukushima Aizuwakamatsu965-8580 Japan School of Computer and Information Technology Ulsan College / Dong-gu Ulsan44610 Korea Republic of

An ultra-wideband (UWB) slotted compact Vivaldi antenna with a microstrip line feed was evaluated for microwave imaging (MI) applications. The recommended FR4 substrate-based Vivaldi antenna is 50×50×1.5 mm3 in size. The proposed compact Vivaldi antenna showed good radiation characteristics and spanned an ultra-wide bandwidth of 10 GHz, ranging from 3.6 to 13.6 GHz, using a microstrip line feed with a radial stub, tapered slots, and resonant cavities. After analyzing the simulation findings, the proposed compact slotted UWB Vivaldi antenna was compared with the basic Vivaldi antenna. The maximum gain and efficiency were 7.35 dB and 82%, respectively. The antenna was simulated in the time domain using the computer simulation technology (CST) microwave studio. The frequency domain solver was also used for cross-validation, and the results were equally good. In conclusion, the proposed compact Vivaldi antenna is a good option for microwave imaging applications. © 2023 The Institute of electronics and Information Engineers.

关键词： Cavity resonators

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Med-tech device security through advanced server cryptography

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International Journal of Information Technology (Singapore) 2025年第2期17卷 1015-1022页

作者： Sharan, Preeta Yasmeen, M.S. Nagesh, N. Parimi, Pranav Chetan, V. Roy, Sandip Kumar Department of Electronics and Communication (R & D) The Oxford College of Engineering Bangalore India Department of Electronics and Communication Engineering The Oxford College of Engineering Bangalore India Department of Computer Science Engineering Amrita Vishwa Vidyapeetham Bangalore India Research and Development The Oxford College of Engineering Bangalore India S P Jain School of Global Management Dubai United Arab Emirates

To protect secrecy without compromising data, the study outlines a strong security framework for communications between mobile devices and servers and recommends encryption as the best option. Traditional encryption techniques are not immediately transferable due to the limitations of e-health data, including its size, redundancy, and bandwidth especially when patient data is moving across public networks. Patient privacy may be compromised as a result of this security flaw. Strong encryption measures must be put in place in the healthcare industry to combat this and ensure that confidential patient data may only be retrieved securely and by authorised personnel, protecting data integrity and privacy. To strengthen communication in the healthcare industry, the study presents a new, simplified encryption and decryption technique. We carefully examine, evaluate, and then benchmark this technique against accepted encryption standards. © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Data Security Healthcare device security RSA algorithm Secured communication

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Medi-Connect: An End-to-End Intelligent Framework to Facilitate New Era Online Consultations Toward Sustainable Healthcare 5th

Medi-Connect: An End-to-End Intelligent Framework to Facilit...

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5th International Conference on Entrepreneurship, Innovation, and Leadership, ICEIL 2023

作者： Yadav, Jayash Raj Singh Jain, Paras Sharma, Shanu Dubey, Ashwani Kumar Department of Computer Science and Engineering ABES Engineering College Ghaziabad India Department of Electronics and Communication Engineering Amity School of Engineering and Technology Amity University Uttar Pradesh Noida India

ISBN: (纸本)9789819716814

The healthcare industry has undergone a significant transformation in recent years, with the integration of information technology and online platforms revolutionizing the way medical services are delivered. One such development is the emergence of online consultations, enabling patients to seek medical advice from doctors without the need for in-person visits. The increasing popularity of online consultations in the healthcare industry has highlighted the need for efficient systems to support remote medical services. In this paper, an intelligent framework is proposed to assist patients and doctors during online consultations. The framework offers end-to-end services starting from patient registration, doctors’ availability, the online appointment of doctors, etc., required during an online consultation. The proposed framework is also capable of assisting the doctors during diagnosis of diseases and drug recommendation through intelligent decision-making capability based on the symptoms provided by the patient. The use of the Naïve Bayes algorithm is explored here to perform classification on patient data and the determination of the probability of specific diseases. In addition to accurate diagnoses, the system recommends appropriate medicinal treatments and provides a database of specialist doctors for further consultation. This integration of technology and health expertise seeks to streamline the healthcare process, saving time and reducing costs for both patients and doctors. By presenting a streamlined framework for online consultations, the main aim of this work is to contribute to the advancement of virtual healthcare services and to bridge the gap between traditional healthcare practices and the evolving digital landscape, ultimately improving healthcare accessibility and outcomes for patients worldwide. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Diagnosis

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A Review on DeepLungNet: CNN-Based Lung Cancer Detection Techniques Using CT Images

A Review on DeepLungNet: CNN-Based Lung Cancer Detection Tec...

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2024 International Conference on Advances in Data engineering and Intelligent Computing Systems, ADICS 2024

作者： Nair, Surabhi S. John, Asha Susan Raju, Juby Musaliar College Of Engineering And Technology Department Of Electronics And Communication Engineering Pathanamthitta India Kalasalingam Academy Of Research And Education Department Of Electronics And Communication Engineering Virudhanagar Tamil Nadu Krishnan kovil626 126 India Hindustan Institute Of Technology And Science Department Of Computer Science Engineering TamilNadu India

ISBN: (纸本)9798350364828

The disease known as lung cancer, which is common and frequently deadly, starts in the cells of the lungs and causes symptoms like exhaustion, chest pain, and persistent coughing. Since small cell lung cancer (SCLC) is less frequent but more dangerous than non-small cell lung cancer (NSCLC), knowledge of its causes, including smoking, pollution, and genetic factors, is essential. Survival rates are greatly increased by early identification by about 20%. This study comprehensively analyzes deep learning and machine learning models-based lung cancer prediction methods from 2016 to 2023. The review emphasizes how well these models work to achieve greater accuracy. Expanding on this, a new method is suggested that combines data augmentation and denoising preprocessing methods with a CNN in a ResNet architecture for classification. The goal of this hybrid model is to maintain and improve accuracy levels in the identification of benign and malignant lung pictures. This methodology offers promising promises for more accurate and reliable lung cancer prediction by utilizing advances in both preprocessing and classification techniques. © 2024 IEEE.

关键词： Diseases

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Modelling of 7-Segment Hex Decoder using Silicon Microring Resonator

Modelling of 7-Segment Hex Decoder using Silicon Microring R...

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2024 IEEE Silchar Subsection Annual Conference, SILCON 2024

作者： Raju, Kommisetti Murthy Nirmala Bai, K.S. Mondal, Bikas Roy, Bhaskar Banerjee, Sudipta Kundu, Sumanta Electronics and Communication Engineering Shri Vishnu Engineering College for Women Bhimavaram India Electronics and Communication Engineering Jntua College of Engineering Kalikiri Kalikiri India Electronics and Computer Science Narula Institute of Technology Kolkata India Asansol Engineering College Asansol India Pune India Electrical Engineering Narula Institute of Technology Kolkata India

ISBN: (纸本)9798331540821

A creative design for a 7-segment hex decoder that makes use of an optical microring Resonator (OMRR). Digital devices called decoders are used to transform binary input into the required output format. The hexadecimal is widely used in programming languages, memory addressing, error codes, etc. The main advantage of 'Hexadecimal' numerals is that they require less memory to store more numbers. After processing the binary code, the decoder accepts it and converts it back into a format that output devices can understand. The entire design has been simulated step-by-step in MATLAB. An all-optical decoder with a quick response time can significantly enhance various aspects of digital data communication and processing. The microring resonator is modulated utilizing an optical pump signal, which is the powerful optical laser beam. This microring resonator-based optical decoder can be applied to optical communication and networking, as well as optical secure coding circuits, as a basic building block. © 2024 IEEE.

关键词： Laser beams

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Crop Disease and Pest Management in Agriculture via UAV Remote Sensing and Advanced Machine Learning Models 3

Crop Disease and Pest Management in Agriculture via UAV Remo...

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3rd International Conference on Integrated Circuits and communication Systems, ICICACS 2025

作者： Punitha, A. Jayamangala, S. Joel Josephson, P. Bharathi, K. Sindhu, V. Singh, Kamlesh Chettinad College of Engineering and Technology Department of Computer Science and Engineering Karur India Santhiram Engineering College Nandyal Department of Electronics and Communication Engineering Nandyal India Malla Reddy Engineering College Department of Electronics and Communication Engineering Dhulapally Medchal India Erode Sengunthar Engineering College Department of Agricultural Engineering Erode India Christ University Department of Computer Science Bangalore India School of Management Sciences Department of Mechanical Engineering Uttar Pradesh India

ISBN: (纸本)9798331508456

Pests and diseases greatly reduce crop quality and yield;therefore, IA relies on effective pest and disease control. UAVs have become a crucial remote sensing (RS) tool for agricultural process monitoring and management. This study will examine major advances in this field using bibliometric methodologies including author co-occurrence and keyword co-contribution studies. The suggested technique involves preprocessing, feature extraction, and model training. Data quality improves with preprocessing. UAV images are used for feature extraction, focusing on canopy structure and height. PPO is trained the prediction model. Compared to ultramodern GANs and LSTM networks, the recommended model wins. The model consistently outperforms competitors with 91.17 percent accuracy. The study suggests employing UAVs in smart farming to reduce pests and diseases. The suggested model's accuracy and reliability improve crop quality and production by solving agricultural monitoring and management problems. © 2025 IEEE.

关键词： Insect control

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Exploring the Impact of Node Velocity on communication Overhead and Energy Consumption in WSNs Using Fuzzy Clustering

Exploring the Impact of Node Velocity on Communication Overh...

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2024 International Conference on Advances in Computing Research on science engineering and Technology, ACROSET 2024

作者： Sharma, Dilip Kumar Yadav, Aaditya Patidar, Mukesh Patil, Pooja Sanjay Patidar, Praveen Kumar Mandloi, Devendra Singh Sheikh, Rashid Rajpoot, Shivshankar Ujjain Engineering College Department of Electronics and Communication Engineering Ujjain India Piet Parul University Department of Computer Science and Engineering Vadodara India Credit Acceptance Financial Institution in Southfield Michigan United States Parul Institute of Technology Parul University Department of Computer Science & Engineering Vadodara India Indore Institute of Science and Technology Department of Electronics and Communication Engineering Indore India Acropolis Institute of Technology and Research Department of Computer Science and Engineering Indore India

ISBN: (纸本)9798350388800

Clustering, an unsupervised machine learning technique with numerous practical applications, has received a great deal of research attention. Along with deterministic and probabilistic approaches, fuzzy C-means clustering (FCM) is commonly employed. Over time, improvements to the FCM approach have been implemented to improve clustering efficiency. In this paper, we perform the results of communication overhead, energy consumption, and link distance travel in WSN with different velocities for the clustering-based protocol. In this performance, we are considering the number of nodes in the networks as 100, 175, and 200, having considered the start node as five using fuzzy clustering methodology in the unsupervised ML technique. In the communication overhead result analysis, we observed that the communication overhead increases as the nodes velocity increases, and another case of energy consumption also increases with the rising trend as node velocity increases. The results presented in this paper have been simulated using the Matlab R2020a tool. © 2024 IEEE.

关键词： Fuzzy clustering

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Artificial Intelligence powered chatbots for the speech disabled and hearing impaired using Feedforward Neural Network 1

Artificial Intelligence powered chatbots for the speech disa...

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1st IEEE International Conference on Advances in Computing, communication and Networking, ICAC2N 2024

作者： Mukherjee, Subhayan Chatterjee, Anusuya Chandrakar, Khushbu Saxena, Sandeep Asansol Engineering College Artificial Intelligence and Machine Learning Asansol India Asansol Engineering College Electronics and Communication Engineering Asansol India Asansol Engineering College Computer Science and Engineering Asansol India Greater Noida Institute of Technology Computer Science and Engineering Delhi India

ISBN: (纸本)9798350356816

Speech has been the catalyst for natural human communication, and any disability in this field presents a significant barrier to normal communication. Sign language is the primary method of communication, but its education is not available in all parts of the country. This research paper titled 'Artificial Intelligence Powered Chatbots for the Speech Disabled and Hearing Impaired using Feedforward Neural Network' provides a novel integration of Artificial Intelligence to guide and empower the daily routines of people with speech disabilities. By introducing a specialized chatbot tailored to the unique needs of speech-disabled individuals, this paper addresses the pressing need for advanced assistive technologies in the daily lives of speech-disabled individuals. This paper underscores the transformative impact of AI in fostering inclusivity and empowerment in the lives of people with disabilities. © 2024 IEEE.

关键词： Assistive technology

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