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3rd International Conference on communication, Control, and Intelligent Systems, CCIS 2024

作者： Veerraju, Sampenga Varshini, Nakka Navya, Yadagiri Srinivas, Jonnakuti Venkata Siva Arasavali, Nalineekumari Putcha, Poornapriya Dadi Institute of Engineering & Technology Dept of Electronics and Communication Engineering Anakapalle India

ISBN: (纸本)9798331528201

The neurodegenerative disorder Alzheimer's disease is indicated by cognitive deficits and memory loss. Early identification and diagnosis of the disease contribute positively to therapeutic intervention opportunities, and can improve patient outcomes following diagnosis. Structural brain abnormalities linked with Alzheimer's can be reliably measured through magnetic resonance imaging, making it a strong imaging modality for cognitive impairment assessment, including Alzheimer's. This study develops an ensemble learning strategy to diagnose patients with Alzheimer's using MRI data. Specifically, an ensemble strategy uses the strengths of multiple less complex machine learning models to improve predictive accuracy and robustness locally or across populations, as compared to using a single model. The proposed ensemble diagnostic model utilizes pre-processed MRI images in order to extract relevant features of interest, and the software stack publishes the assessment of various machine learning models. The proposed method exhibits key performance metrics as accuracy-0.99, F1 score-0.98, recall-1.00 and precision-0.96. It shows that ensemble learning is a very powerful machine learning method to use for machine learning predictions when compared to traditional and individual approaches. © 2024 IEEE.

关键词： Contrastive Learning

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PUF based on chip comparison technique for trustworthy scan design data security against side channel attack

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International Journal of Cloud Computing 2023年第2-4期12卷 201-223页

作者： Mukkath, Shiny I. Devi, Nirmala M. Department of Electronics and Communication Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore641 112 India

All fields of computational technology, including cloud computing and cryptography, are vulnerable to different types of external threads. Scan-based testing method is a well-known tool for testing integrated chips, but at the same time, it helps hacking the secret code from the chip. The scan hardware can act as a platform for attackers to hack the secret data from the chip. Most of the existing solutions are based on the alteration of the conventional scan structure with more complex design which focused only on security but violates the testability. In this paper, we propose a dynamic reconfiguration architecture using embedded PUF design, which protects the chip from brute force attack, hamming distance-based attack with optimal deployment configuration. Additional on-chip comparison and masking were also used to enhance security. The experimental results are evaluated on standard benchmark circuits. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Hardware security

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Design and Implementation of Autonomous Firefighting Rover

Design and Implementation of Autonomous Firefighting Rover

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2024 International Conference on Smart electronics and communication Systems, ISENSE 2024

作者： Ram Nivas, D. Kathirvelu, M. Sajitha, T. Sowmithra, S. KPRInstitute of Engineering and Technology Department of Electronics and Communication Engineering Coimbatore641407 India

ISBN: (纸本)9798331528126

The firefighting rover is built to work in dangerous fire situations where it's too risky for firefighters to be directly involved. It uses a four-wheel design to move over rough terrains and handle high temperatures, making it suitable for places like forests, mountains, uneven roads, and caves. The rover is equipped with a Raspberry Pi and other components to detect fires using image recognition. It has a water tank and hose system to spray water on the fire, with a motor to pump the water and move the rover. A gas sensor helps detect toxic gasses in the area, and everything is controlled by an Arduino Uno. The rover is enclosed in a strong, simple design. The system is trained with 3,000 examples of fire, gas, and smoke, allowing it to be about 90% accurate in detecting hazards, with results recorded for reference. © 2024 IEEE.

关键词： Water tanks

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Design and Implementation of 4 Bit Carry Generator Circuit Using Pass Transistor Logic with 2 × 1 Mux Approach

Design and Implementation of 4 Bit Carry Generator Circuit U...

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2024 International Conference on communication, Computer Sciences and engineering, IC3SE 2024

作者： Samsudeen, S. Mohamed Sulaiman Jaiswal, Isha Rawat, Ishita Belani, Jatin Galgotias College Of Engineering And Technology Electronics And Communication Engineering Greater Noida India

ISBN: (纸本)9798350366846

This study employs the pass transistor logic technique to design and implement Very Large-Scale Integration (VLSI) factors in the context of various adders. The area consumption, power consumption, and propagation latency of traditional adders, like Carry Lookahead Adders (CLA) and Ripple Carry Adders (RCA), are frequently problematic. The study investigates the use of the pass transistor logic technique in the design and construction of several adder circuits in order to overcome these issues. This method is well known for its ability to increase efficiency by providing lower power consumption and shorter signal propagation delays. Using 2 × 1 multiplexers in the adder circuits is a crucial part of this strategy. After that, the design stage entails creating modules that are especially suited for various adder configurations while taking into account the particular circumstances in which the carry input (Cin) is either 0 or 1. By selecting the right outputs according to the encoded state, 2 × 1 multiplexers-controlled bypass transistor logic simplify the total number of states the circuit has to handle. The project's goal is to improve adder circuit efficiency by in-depth research and testing, which will further VLSI design for digital circuits. © 2024 IEEE.

关键词： Adders

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Flexible Antenna with AMC Backing for Non-Invasive Blood Glucose Monitoring 2

Flexible Antenna with AMC Backing for Non-Invasive Blood Glu...

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2nd International Conference on Microwave, Antenna and communication, MAC 2024

作者： Upadhyay, Nidhi Kaur, Amanpreet Pattanayak, Arnab Thapar Institute of Engineering and Technology Department of Electronics and Communication Engineering Punjab India

ISBN: (纸本)9798350350104

This study discusses the design of a non-implantable and flexible antenna for blood glucose level (BGL) monitoring purposes. In this work, a sensor consisting a circular shaped patch antenna divided in four sectors with a volume of, 56.5 mm x 30 mm x 0.16 mm, and a beehive inspired, artificial magnetic conductor (AMC) metasurface both operating in ISM band, is proposed. The proposed antenna has a reduced and defected ground plane. The antenna is simulated in CST MWS'23 and the reflection parameter (S11), gain, and bandwidth of the antenna are -42 dB, 2.54 dBi, 3.7 GHz respectively. Bend Test is carried out using the simulator for validating conformability of the proposed antenna. The beehive metasurface unit cell of dimensions 23 mm x 37 mm is designed as an AMC. The antenna is then, backed by the 3 x 3 AMC which acts as a ground plane of the antenna. After optimizing the distance between CDRA and metasurface to 3 mm, the gain is improved to 8.09 dBi. The antenna is tested with a three layer bio mimic human phantom and SAR is simulated. The antenna showed a permissible value of SAR as 0.00812 W/kg. For BGL monitoring, the antenna is simulated and analysed for different BGL values. For this purpose, the Debye Model is referred for extracting dielectric properties of human blood for different glucose levels. The designed sensor is small, robust, low cost and easy to fabricate which favours BGL monitoring. © 2024 IEEE.

关键词： Glucose sensors

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Innovative Models for Advanced Military IoT communications using Improved Optimization with Connection-based Clustering Routing 3

Innovative Models for Advanced Military IoT Communications u...

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3rd International Conference on electronics and Renewable Systems, ICEARS 2025

作者： Ramkumar, G. Saveetha University Saveetha School of Engineering Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798331509675

Unmanned Aerial Vehicles (UAVs) are unmanned aircraft that fly without a human operator. Due to their maneuverability and accessibility, they are used in various applications such as aerial surveillance, delivery, and mapping and as well connected to the Internet of Things (IoT) devices. IoT includes smart home devices to industrial machinery, improving automation, and data-driven decision-making. Limited battery life limits the duration of work;sensitivity to weather conditions affects reliability. Data breaches are a potential outcome of security vulnerabilities, and the lack of interoperability makes it difficult to integrate diverse platforms. To overcome this drawback, this article introduced a novel approach called Improved Optimization with Connection-based Clustering Routing with MEC (IO-CBCM). IO-CBCM is used to enhance secure device-to-device communication in IoT networks through UAVs and Mobile Edge Computing (MEC) servers. The IO-CBCM framework is designed to optimize the Cluster Head (CH) selection and control cost reduction, while also improving overall system performance through particle swarm optimization (PSO) and increasing efficiency in Mobile Ad Hob Networks (MANETs). IO-CBCM-oriented clustering utilizes the system's structure to create clusters, which guarantees uninterrupted connectivity, decreases delay, maximizes energy savings, and boosts packet ratio. This holistic approach aims to strengthen network security, optimize resource allocation, and improve overall network performance in IoT environments. Here the performance analysis is calculated for the IO-CBCM model and compared with IDMB, ECDR, and SFTK with some parameters like false positive, clustering efficiency, packet delivery ratio, packet drop ratio, and throughput to achieve high performance. © 2025 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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GCET Virtual Help Desk 'Chat Bot' using Python and Telegram API 15

GCET Virtual Help Desk 'Chat Bot' using Python and Telegram ...

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15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Yadav, Akash Singh, Gavendra Galgotia College of Engineering and Technology Electronics and Communication Engineering Greater Noida India

ISBN: (纸本)9798331300579

This paper proposes a method for generating a chatting bot's back-channel responses in a text-based chat. We studies methods for triggering text-bases discussions. The Python programming language is used in this Chatbot system. The Chatbot software system is very important in the studies field, particularly for communicating information directly and in a way that is acceptable to a large number of users at the same time. This paper concentrated on the use of the Telegram application for the Chatbot system. As a result, not every query was carefully addressed by the conversation participants. If the chatting bot posts back-channel comments in reaction to what the other users have said, we assume that the chatting bot is acknowledged as a conversation participant and that the queries of the chatbot are attentively participants of the conversation respond. The results suggest that posting both back-channel queries and replies by the chatbot boosts conversation activation. The various back-channels responses were properly posted as follows rather than a condition, A backchannel response is posted by the chatbot whenever a remark contains a question mark, signifying acceptance of the second response. © Grenze Scientific Society, 2024.

关键词： Chatbots

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COVID-19 Detection from Cough Sound Signal using Random Forest Learning of Deep Spectral Features

COVID-19 Detection from Cough Sound Signal using Random Fore...

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2024 IEEE International Conference on Signal Processing, Information, communication and Systems, SPICSCON 2024

作者： Puja, Waishari Das Sultana, Shafrin Aowlad Hossain, A.B.M. Department of Electronics and Communication Engineering Khulna University of Engineering & Technology Khulna Bangladesh

ISBN: (纸本)9798331510213

The COVID-19 epidemic and its subsequent rise have brought attention to the need for quick, precise, and reasonably priced testing techniques. Existing assays such as RT-PCR are slow and conditionally sensitive, which presents difficulties, particularly in low-resource settings. Researchers have shown that COVID-19 can be accurately detected by audio-based AI algorithms using cough sounds. In this work, a cough sound-based COVID-19 detection framework is presented. It utilizes a 1D Convolutional Neural Network (CNN) deep feature extractor from handcrafted spectral features and Random Forest classifier for classifying the healthy and Covid-19 subjects from cough sounds. The research considered the cough sound from two datasets named Coswara and Virufy emphasizing the generalization capability of the proposed framework. With the help of feature engineering, spectral features like Short-Term Fourier Transform (STFT), Mel Spectrogram, Mel Frequency Cepstrum Coefficient (MFCC), RMS Energy, Spectral Bandwidth, Zero Crossing Rate (ZCR), Spectral Centroid, and Spectral roll-off have been extracted which are further fed into a CNN based algorithm for extracting deep features. The deep features are more crucial for complex pattern analysis compared to the simple frequency domain analysis. Finally, the Random Forest model is used for classification tasks, which shows a predictive accuracy of 93% with robustness against data diversity. The proposed framework might be useful for smartphone-based COVID-19 detection applications. © 2024 IEEE.

关键词： Decision trees

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Reconfigurable FPGA Based ASK, FSK and PSK Modulator and Automatic Demodulator

Reconfigurable FPGA Based ASK, FSK and PSK Modulator and Aut...

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2024 Asia Pacific Conference on Innovation in technology, APCIT 2024

作者： Kaza, Karthikeya Pallapu, Saiteja Chintala, Thanush Reddy Samson, Mamatha Gokaraju Rangaraju Institute of Engineering and Technology Electronics and Communication Engineering Hyderabad India

ISBN: (纸本)9798350361537

This paper presents the design and implementation of a Software Defined Radio (SDR) system leveraging FPGA technology to generate and demodulate Amplitude Shift Keying (ASK), Frequency Shift Keying (FSK), and Phase Shift Keying (PSK) signals. The system comprises of modulating units capable of generating these three Shift Keying signals based on binary input data and a demodulating unit that can automatically detect the modulation scheme and demodulate the signals. The simulated outputs can be observed through ModelSim, while actual outputs, including modulated signals and the demodulated binary outputs for test signals, are obtained using Xilinx ChipScope. This project showcases a flexible and cost-effective approach to signal modulation and demodulation within the realm of digital communication systems. © 2024 IEEE.

关键词： Digital communication systems

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Malaria Cell Detection using Advanced SVM Techniques 2

Malaria Cell Detection using Advanced SVM Techniques

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2nd IEEE International Conference on Networks, Multimedia and Information technology, NMITCON 2024

作者： Shashikiran, S. Sunitha, H.D. New Horizon College of Engineering Electronics and Communication Engineering Bengaluru India R.R. Institute of Technology Electronics and Communication Engineering Bangalore India

ISBN: (纸本)9798350372892

Malaria, caused by Plasmodium parasites, is a blood disease carried via the bite of a female Anopheles mosquito. Instances of this occur nearly 240 million times in the coastal and rural regions of India. The disease affects about 40% of people annually. There is a threat to one-third of the world's population. In general, macroscopic examinations are time-consuming. Examine both thin and thick blood smears to determine what causes a disease or condition and to identify risk factors in individuals. However, a smear's accuracy is dependent on both its quality and the situation's information. Cells with and without parasites are categorized and tallied. Manual assessment is the gold standard for diagnosis, yet it only yields 50% accuracy. It requires multiple steps to be finished. We will use various Support vector machine (SVM) algorithms for malaria cell detection, which provide varying degrees of accuracy and alleviate the time complexity difficulties associated with Deep learning methods. SVM-76%, SVM + t-distributed stochastic neighbor (t- SNE)-82%, SVM + Principal Component Analysis (PCA)-86%, and SVM in the Convolutional Neural Network (CNN) Model-96% are the outcomes of the various SVM approaches. This paper covers various Support Vector Machine (SVM) approaches for classifying malaria cells. © 2024 IEEE.

关键词： Convolutional neural networks

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