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2024 Asia Pacific Conference on Innovation in technology, APCIT 2024

作者： Mahato, Shashank Saranyaraj, D. Amrita Vishwa Vidyapeetham Amrita School of Engineering Department of Electronics and Communication Engineering Chennai India Vellore Institute of Technology School of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350361537

The main objective of this innovative project is to transform modern-day neurological healthcare, additionally pairing and synchronizing EEG signals with facial recognition information for efficient detection of neurological sicknesses. Machine learning algorithms are used for promptitude, ensuring rapid interventions during the course of the disease, and for careful and efficient balancing of the patient's conditions. The system based on the above-discussed approach is characterized by a patient-centered nature ensuring that trust and ethical liability are the top priorities of the developed model. Such system supported by multiple machine learning algorithms also increase the accuracy of the diagnosis, its potential for early identification, and targeted therapy, ultimately having a beneficial effect on the public health. The researches findings demonstrate that there are convincing proofs that machine learning can be used for predictive healthcare: VGG19 achieved 86.28%, Random Forest Classifier 94.48%, and for epilepsy, Random Forest and Gradient Boosting for brain tumors 92.12% and for Parkinson's disease 90.52%, respectively. Ensembled EEG analysis had the accuracy of 91.83%. Importantly, a result of 82.51% accuracy was achieved with the final decision-making process using transfer learning with the method of ensembled models and VGG19. Thus, it is possible to conclude that different machine learning algorithms are effective in predictive healthcare and can promote the progress of medical technology to benefit public health. © 2024 IEEE.

关键词： Emotion Recognition

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Modeling and Analysis of MEMS Electrostatic Energy Harvesting System 6

Modeling and Analysis of MEMS Electrostatic Energy Harvestin...

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6th International Conference on Advancements in Materials and Manufacturing, ICAAMM 2024

作者： Karthik Reddy, G. Singh, Pulkit Ravi, Kiran Chand Anusha, B. Gowri, Chaduvula Vivek, R. Department of Electronics and Communication Engineering MLR Institute of Technology Hyderabad500043 India Department of Electronics and Communication Engineering Godavari Institute of Engineering & Technology Rajahmundry India Department of Mechanical Engineering Sri Eshwar College of Engineering Coimbatore India

Energy harvesting generators for low-power wireless electronic devices have drawn more attention in recent years. The design and analysis of a MEMS energy harvester based on electrostatic transduction are discussed in this study. Because a folded beam design has the advantage of being able to move huge dimensions, be compliant in the desired direction, and stiffer in the orthogonal direction. Large displacement of the energy harvester's proof mass results in improved performance. The spice circuit of the harvester has been modelled and performed simulation to evaluate the output power of the harvester in LTSPICE. FEM simulations using COMSOL were used to assess the natural frequency and mode shape of the system and compare results with those of analytically determined values. © Published under licence by IOP Publishing Ltd.

关键词： engineering education

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Design and Optimization of Saturation Based Image Dehazing Algorithm 10

Design and Optimization of Saturation Based Image Dehazing A...

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

作者： Anishfathima, B. Deepak, A. Dhanushree, V.M. Elakiya, K.P. Mahaboob, M. Vasanthanayaki, C. Sri Krishna College of Engineering and Technology Coimbatore India Sri Krishna College of Engineering and Technology Electronics and Communication Engineering Coimbatore India Sri Eshwar College of Engineering Electronics and Communication Engineering Coimbatore India Government College of Engineering Theni India

ISBN: (纸本)9798350384369

The apparent quality of photos taken by systems that operate in real time for oversight, object detection, and remote sensing is diminished by hazy weather. The effectiveness of these real-time systems is impacted by this. To address these issues, a real-time remover of haze mechanism must be implemented on hardware. This article offers one such solution. This article presents the hardware used to implement an image dehazing method using saturation. A 15 x 15 window lowest filter is used, which estimates the ambient light using the down sampled fuzzy image in order to achieve precise estimates. Moreover, our method is pixel-based instead of patch-based as we have used saturation-based propagation map estimate. Contrary to current patch-based techniques, the suggested technique suppresses halo artifacts around edges without the need for either an image filtering unit or an edge detecting unit. The suggested dehazing system has a seven-stage pipelined VLSI architecture. Both FPGA and ASIC (65-nm technology scale) devices are used to implement it. With only 13.2k logic gates, the suggested dehazing system's ASIC version can handle 3840 × 2160 resolution at a rate above 70 frames per second, with an optimal throughput of 624 Pixels/s. © 2024 IEEE.

关键词： Demulsification

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Parametric analysis in the machining of gun metal using computer numerical control turning process

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Interactions 2025年第1期246卷 1-11页

作者： Santhanakrishnan, R. Marichamy, S. Anandavelu, K. Gomathy, V. Vinu, A. Thava Veerappan, G. Ram, S. Sheeba, T. Blesslin Department of Mechanical Engineering & Registrar Evaluation CMR University Bengaluru India Department of Mechanical Engineering MRK Institute of Technology Tamil Nadu Kattumannarkoil India Department of Electrical and Electronics Engineering Kathir College of Engineering Coimbatore India DMI College of Engineering Aralvaimozhi India Department of Mechatronics Engineering Sri Krishna College of Engineering and Technology Tamilnadu Coimbatore India Department of Mechanical Engineering Gokaraju Rangaraju Institute of Engineering and Technology Hyderabad India Department of Electronics and Communication Engineering R.M.K. Engineering College Kavaraipettai India

The quality of the machining of the materials is depending on the input constrains of the process and its composition of different alloying elements. The outstanding material properties of gun metal are achieved by the composition of copper, tin and zinc. This paper to investigate the machining behaviors of gun metal through computer numerical control turning process with different input constrains. The response factors such as cutting force, tool tip temperature and surface roughness are evaluated by manipulate the input factors. The experimental results are compared with response surface methodology model (RSM). It is used to optimize the input and output factors. The minimized cutting force, tool tip temperature and surface roughness are 84.87 N, 200.10 C and 0.75 microns respectively. The surface plots are used to correlate the dependent and independent variables. The novelty of the experiment is that parametric analysis in the machining of gun metal using computer numerical control turning process. Investigate the cutting force, tool temperature and surface roughness of the gun metal and it can be recommended to rotating elements such as gears and bearings. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Cutting force Gun metal Machining behaviors RSM Tool tip temperature Turning

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Efficiency Evaluation of Scalable Multiply and Accumulate Architectures in DSP: A Comparative Study of LUT Based and LUT-Less Based Approaches 2

Efficiency Evaluation of Scalable Multiply and Accumulate Ar...

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2nd IEEE International Conference on Intelligent and Innovative Technologies in Computing, Electrical and electronics, ICIITCEE 2024

作者： Bharathi, M. Shirur, Yasha Jyothi M. Mohan Babu University Electronics and Communication Engineering Andhra Pradesh Tirupati India BNM Institute of Technology Electronics and Communication Engineering Bangalore India

ISBN: (纸本)9798350306415

Multiply and Accumulate (MAC) units are widely used in digital signal processing. They are crucial for activities like correlation, convolution, and filtering, which allow for fast and effective signal processing. A fundamental component in modern digital signal processing systems, these scalable units serve as the foundation for a wide variety of DSP algorithms. The distributed arithmetic method, which offers reduced computational complexity while preserving accuracy through parallelism and distributed multiplication operations, is a highly effective way for creating Multiply and Accumulate (MAC) structures in digital signal processing. A scalable Multiply and Accumulate (MAC) architectures are shown in this article. Also, explored the design of multiply and accumulate structures at various bit-widths: 4, 8, 16, 32 and 64-bit versions, as well as analyzed LUT-based and LUT-less approaches. Significant variations in space and power consumption between LUT-based and LUT-less systems are highlighted by the data in the article for a variety of bit-width configurations. A quantitative examination shows that whereas LUT-less devices continue to have a smaller footprint and lower power consumption even on larger bit-widths, LUT-based solutions clearly consume large area and consumes more power as width of the bits expands. The proposed method is designed and simulated using Xilinx Vivado 2022.2 software. © 2024 IEEE.

关键词： Distributed Arithmetic (DA) LUT LUT-Less Multiply and Accumulate (MAC) Xilinx Vivado 2022.2

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Design and Analysis of an Octagonal Chipless RFID System

Design and Analysis of an Octagonal Chipless RFID System

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2024 Asia Pacific Conference on Innovation in technology, APCIT 2024

作者： Saranyaraj, D. Maheswari, A Uma Vellore Institute of Technology School of Computer Science and Engineering Chennai India Amrita School of Engineering Department of Electronics and Communication Engineering Amrita Vishwa Vidyapeetham Chennai India

ISBN: (纸本)9798350361537

The proposed research introduces an approach to design an Octagonal chipless RFID tag to achieve tag identification to encode the information. These tags work by reflecting a unique electromagnetic signal when it is read by an RFID reader. The unique characteristics of the tag's structure or material cause modulation or reflection of the radio waves, which can be decoded by the reader to retrieve stored information. In this research, we propose an innovative approach for designing chipless RFID tags using electromagnetic resonators arranged in a 2x2 matrix configuration. While the design can be adapted to any nxn matrix, we specifically focus on the 2x2 arrangement in this study. The resonators are strategically positioned to achieve optimal performance, considering read range, robustness, and scalability factors. This paper provides a comprehensive review of Chipless RFID technology, covering its working principles, encoding techniques, applications, advantages, and challenges. © 2024 IEEE.

关键词： Scalability

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Enhancing Autism Spectrum Disorder Diagnosis Using Machine Learning Techniques 2

Enhancing Autism Spectrum Disorder Diagnosis Using Machine L...

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2nd IEEE International Conference on Integrated Intelligence and communication Systems, ICIICS 2024

作者： Tauseef, Md. Patil, Pujitha Chandana, J. Mishra, Shruthi School of Electronics and Communication Engineering REVA University Benguluru India

ISBN: (纸本)9798331504960

Accurate diagnosis of autism spectrum disorder (ASD) is challenging due to its complex nature and reliance on subjective, time-consuming assessments. This study explores the use of machine learning (ML) algorithms to improve ASD diagnosis accuracy and efficiency. We evaluate multiple ML models, including Random Forest, Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), Decision Tree, and Logistic Regression, using datasets that include genetic, behavioral, and demographic data. The aim is to identify patterns associated with ASD and assess the strengths and limitations of each model. The findings suggest that ML algorithms have the potential to revolutionize early ASD detection, offering clinicians more objective tools for timely diagnosis and intervention. Ultimately, this research contributes to advancing our understanding of ASD and supports the development of personalized treatment strategies. © 2024 IEEE.

关键词： Logistic regression

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A Novel Approach for Generic Plant Disease Classification 1

A Novel Approach for Generic Plant Disease Classification

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1st International Conference on Advances in Computer Science, Electrical, electronics, and communication Technologies, CE2CT 2025

作者： Mugabasav, Puneet Salotagi, Shreyas M. Kulkarni, Akash Mallibhat, Kaushik School of Electronics and Communication Engineering KLE Technological University Hubli India

ISBN: (纸本)9798331518578

With advances in the globalization of the world market, several new varieties of crop cultivation have popped up. The advances have led to habitat changes, and new varieties of diseases and plants have surfaced to challenge the farmer community. Several advancements have been made to assist today's agriculture. One among them is the utilization of learning-based models to identify plant diseases. However, the literature review shows that studies were carried out to identify specific diseases in particular plants. The exacting models failed to achieve cross-identification of the diseases irrespective of the type of plant. Thus, the proposed study focusses on novel classifier intending towards generic plant disease classification across various crops. The study was trained and tested for mildew, spot, and rot diseases. Through the training and testing for seven plants and blind validation across six other plants, an accuracy of 96.43% in testing and 63% accuracy in validation was obtained. © 2025 IEEE.

关键词： Plant diseases

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Nine Level Quadra Boost Inverter with Modified Level Shifted Pulse Width Modulation Technique 4

Nine Level Quadra Boost Inverter with Modified Level Shifted...

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4th International Conference on Intelligent Technologies, CONIT 2024

作者： Peter, Geno Arun, Vijayakumar Stonier, Albert Alexander Praghash, K. Jency Rubia, J. Iderus, Samat University of Technology Crisd School of Engineering and Technology Sarawak Malaysia Mohan Babu University Department of Electrical and Electronics Engineering India Vellore Institute of Technology School of Electrical Engineering Vellore India Christ University Department of Electronics and Communication Engineering India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Engineering India

ISBN: (纸本)9798350349900

This research initiatives to introduce a switched capacitor based nine level boost inverter (SC-9LBI) powered by modified level shifted pulse width modulation (PWM) technique. The SC-9LBI equipped with single DC source along with three capacitors and eight controlled switches to develop nine level inverter output voltage. The suggested inverter configuration has the ability of boosting the inverter input voltage into 1:4 ratio. Also, this research involves modified level shifted PWM technique to enhance the quality of inverter output voltage. The effectiveness of the NLMLI is assessed through parameters such as harmonic distortion, peak voltage, and output voltage root mean square value (rms). Simulation studies have been conducted using MATLAB/Simulink to evaluate the proposed inverter's performance. © 2024 IEEE.

关键词： Harmonic distortion

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NPConvNet: A Lightweight Network for Gesture Recognition Based on Millimeter-Wave Radar 9

NPConvNet: A Lightweight Network for Gesture Recognition Bas...

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9th International Conference on Intelligent Computing and Signal Processing, ICSP 2024

作者： Xiong, Wenxin Huan, Sha Yang, Xiaoxuan Guangzhou University School of Electronics and Communication Engineering Guangzhou China

ISBN: (纸本)9798350376548

Radar gesture recognition provides a more flexible and intuitive way of non-contact human-machine interaction in smart homes and intelligent vehicles. Existing methods have insufficient consideration for the lightweighting of the recognition algorithms or networks in embedded applications. In this paper, we propose a new partial convolution (NPConv) by changing PConv forward fusion to reverse fusion that achieves higher accuracy compared to PConv. Building upon our NPConv and Depthwise Separable Convolution, we further propose NPConvNet, whilch utilizes preprocessed radar Range Time Maps (RTM) and Doppler Time Maps (DTM) to identify different hand gestures. And the NPConvNet achieves lightweighting while ensuring the performance. Experimental results validate the superiority of this network compared to traditional networks. © 2024 IEEE.

关键词： Convolution

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