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2024 Asia Pacific Conference on Innovation in Technology, APCIT 2024

作者： Vinotha, R. Hepsiba, D. Vijay Anand, L.D. Karunya Institute of Technology and Sciences Division of Biomedical Engineering Coimbatore India Karunya Institute of Technology and Sciences Division of Robotics Engineering Coimbatore India

ISBN: (纸本)9798350361537

Automatic Speech Recognition (ASR) systems are pivotal in facilitating human-technology interactions through voice commands. However, individuals with dysarthria face significant challenges in benefiting from these technologies due to their speech disorder. This paper proposes finetuning the Whisper model for Dysarthric Speech Recognition (DSR) by incorporating additional features extracted from Mel-frequency cepstral coefficients (MFCCs). By combining spectrograms and MFCCs within an attention mechanism, the model creates a richer feature representation, with spectrograms providing broader context and MFCCs highlighting crucial formant frequencies. The attention mechanism dynamically weighs the importance of each feature based on specific speech segments and dysarthric speech characteristics. Furthermore, a hierarchical attention approach is adopted, which encompasses a two-stage attention mechanism. This mechanism directs attention at both local and global levels, facilitating the capture of both fine-grained details and broader contextual information within the speech signal. This study involved the development and training of 45 speaker-adaptive dysarthric ASR systems. The proposed model achieves an average Word Recognition Accuracy (WRA) of 74.08%, showing a notable enhancement compared to the benchmark of 69.23%. The findings underscore the efficacy of the proposed approach in addressing dysarthria-related challenges in ASR systems. © 2024 IEEE.

关键词： Spectrographs

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Comparative Analysis of PID Controller Tuning Methods for Heat Exchanger Control: A MATLAB Simulation Study

Comparative Analysis of PID Controller Tuning Methods for He...

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2024 Asia Pacific Conference on Innovation in Technology, APCIT 2024

作者： Jencia, J. Anand, L.D. Vijay Hepsiba, D. Karunya Institute of Technology and Sciences Division of Robotics Engineering Coimbatore India Karunya Institute of Technology and Sciences Division of Biomedical Engineering Coimbatore India

ISBN: (纸本)9798350361537

This paper compares the performance of Proportional-Integral-Derivative (PID) controller tuning methods for a heat exchanger process using MATLAB simulations. The effectiveness of two popular techniques, Ziegler-Nichols, Cohen and coon, and Internal Model Control (IMC), is investigated. The three methods are applied to tune the PID controller for a first-order plus time delay (FOPDT) model of the heat exchanger. The simulation results are analyzed to evaluate the closed-loop response characteristics, focusing on metrics like settling time, rise time, and overshoot. The performance of the Ziegler-Nichols, Cohen and coon and IMC tuning methods are compared in achieving desired control objectives for the heat exchanger process. The study aims to identify which tuning approach offers a superior response in terms of stability, speed, and accuracy for this specific application. © 2024 IEEE.

关键词： MATLAB

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Machine Learning-Based Early Seizure Detection: A Random Forest Classifier Approach for Pre-Ictal Stage Prediction in Epilepsy 10

Machine Learning-Based Early Seizure Detection: A Random For...

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10th International Conference on Biosignals, Images and Instrumentation, ICBSII 2024

作者： Mohammed Vishar, M Anaz Hepsiba, D. Prasanna, R. Vijay Anand, L.D. Karunya Institute of Technology and Sciences Division of Biomedical Engineering Tamil Nadu Coimbatore India Karunya Institute of Technology and Sciences Division of Robotics Engineering Tamil Nadu Coimbatore India

ISBN: (纸本)9798350350951

Abrupt and irregular spikes in the brain's electrical activity are the cause of seizures. This could cause transient aberrant behaviors, sensations, or altered states of awareness or unconsciousness. Movements could include jerky, alternatively tensed arms and legs. One of the most prevalent neurological conditions worldwide, epilepsy affects almost 50 million individuals worldwide, according to a report. Over 25% of epileptic individuals experience uncontrollable seizures even with existing medication and surgical treatment options. Preventing Sudden Unexpected Death in Epilepsy (SUDEP) is aided by early seizure detection. A machine learning methodology for seizure detection was introduced by the proposed *** recognized seizure is diagnosed using the Random Forest Classifier algorithm. Using datasets from the ECG (electrocardiogram) and EEG (electroencephalogram), a pre-trained model is created using supervised and machine learning techniques. Finding seizures in the pre-ictal period is the aim. Using the datasets that are available, the model is trained, demonstrating that there are several causes of epilepsy. The answer is the same despite these variations in the causes. The model predicts and alerts carers, nurses, and hospital administration to an upcoming seizure. For doctors, this early warning is very helpful in enabling timely treatment. © 2024 IEEE.

关键词： Electroencephalography

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Cardiac Arrhythmia Diagnosis Using Deep Learning: A 1D CNN-GRU Approach with Multiclass SVM and DWT Analysis 10

Cardiac Arrhythmia Diagnosis Using Deep Learning: A 1D CNN-G...

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10th International Conference on Biosignals, Images and Instrumentation, ICBSII 2024

作者： Hepsiba, D. Vijay Anand, L.D. Jencia, J. Vinotha, R. Amy Fedora, F. Reshma Immaculate, S. Karunya Institute of Technology and Sciences Division of Biomedical Engineering Tamil Nadu Coimbatore India Karunya Institute of Technology and Sciences Division of Robotics Engineering Tamil Nadu Coimbatore India

ISBN: (纸本)9798350350951

Arrhythmia is a cardiovascular disease characterized by an abnormal heartbeat in rate or rhythm. An electrocardiogram (ECG) is an important part of cardiac arrhythmia diagnosis in clinical practice. Recording ECG for the detection of arrhythmias can pose challenges under certain circumstances. This paper's objective is to employ deep learning methods in cardiac arrhythmia diagnosis based on ECG signals, with the least amount of data pre-processing. The proposed algorithm architecture is characterized by pre-processing, feature extraction and 1-Dimension Convolutional Neural Network (1D CNN) Gate Recurrent Unit (GRU) classification for arrhythmia detection. In this paper, the following arrhythmia categories have been considered: Normal beats, premature contractions originating in the ventricles (PVCs), disruptions in the electrical conduction through the left bundle branch (LBBB), interruptions in the conduction through the right bundle branch (RBBB), and artificially initiated depolarizations (paced beats). Classifiers produce vectors, and the highest element in each vector indicates the degree of membership in the corresponding class. The proposed approach involves employing a 1D CNN coupled with GRU for classification, alongside a multi-Class SVM, resulting in an impressive accuracy of 99.97%. Though the characteristics of Discrete Wavelet Transform (DWT) are similar, their output from Multiclass Support Vector Machine (Multi SVM) is hardly different. © 2024 IEEE.

关键词： Electrocardiograms

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Evaluation of optimal responses in Monel 400 alloy using computer based unconventional machining process

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Interactions 2025年第1期246卷 1-11页

作者： Manohar, Gunaselvi Chandrasekar, G. Radhakrishnan, G. Raj, P. Anantha Christu Ram, S. Department of Electronics and Instrumentation Engineering Easwari Engineering College Chennai India Department Mechanical Engineering PSNA College of Engineering and Technology Dindigul India Department of Electrical and Electronics Engineering Sri Krishna College of Engineering and Technology Tamilnadu Coimbatore India Division of Robotics Engineering Karunya Institute of Technology and Sciences Tamilnadu Coimbatore India Department of Mechanical Engineering Gokaraju Rangaraju Institute of Engineering and Technology Hyderabad India

The unconventional machining is an essential role in metal forming process. The dimensional accuracy and super finish are the main features of modern machining methods. Electric discharge machining is a competent process to any materials and composites. In this article is used to machining characteristics of Monel 400 alloy with monitored by computer networks. The response variables are mainly depending on input variables and their levels. Taguchi method is utilized to evaluate the optimal control factors. The mean and SN ratio is evaluated by based on the criteria of the responses. The involvement of control variables to the responses have been validated by variance analysis. The best possible MR was attained at a discharge current of 40 A, pulse on time of 140µs, and spark voltage of 25 *** finest RTW and SR was occurred at a discharge current of 40 A, pulse on time of 140µs, and spark voltage of 20 V. The scope of the work is to maximize the metal removal and minimize the tool wear. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Metal forming

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Segmentation of Retina Vessels in 2D OCT-Reconstructed Fundus Images with 3D UNet 26

Segmentation of Retina Vessels in 2D OCT-Reconstructed Fundu...

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26th IEEE Signal Processing: Algorithms, Architectures, Arrangements, and Applications, SPA 2023

作者： Marciniak, Tomasz Stankiewicz, Agnieszka Zaradzki, Przemyslaw Poznan University of Technology Division of Electronic Systems and Signal Processing Institute of Automatic Control and Robotics Department of Control Robotics and Electrical Engineering Poznan Poland

ISBN: (纸本)9798350304985

This paper presents an analysis of the effectiveness of blood vessel segmentation in human retinal images. The segmentation process was carried out for three-dimensional optical coherence tomography (OCT) scans using the author's publicly available CAVRI-C database. A 3D version of the U-Net artificial neural network was used. Various dimensions of the input blocks were investigated to determine their influence on the segmentation process. The effectiveness of the proposed solutions was evaluated using various metrics and the results obtained were compared with the 2D solution, also based on neural networks. The use of the proposed solutions allowed us to improve the segmentation even by 15% (in the case of the F1-score). © 2023 division of Signal Processing and Electronic Systems, Poznan University of Technology (DSPES PUT).

关键词： Optical tomography

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Basis change, projection, and relative linear algebra tricks in signal and image processing 27

Basis change, projection, and relative linear algebra tricks...

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27th IEEE Signal Processing: Algorithms, Architectures, Arrangements, and Applications, SPA 2024

作者： Dabrowski, Adam Poznań University of Technology Faculty of Control Robotics and Electrical Engineering Institute of Automatic Control and Robotics Division of Signal Processing and Electronic Systems Jana Pawla II 24 Poznań60-965 Poland

ISBN: (纸本)9788362065486

In this tutorial some basic linear algebra problems: basis change and projection, are discussed together with examples of their applications in signal and image processing. In typical linear algebra university courses perpendicular projections are only discussed. However, in image processing, for defining various color spaces, we need non-perpendicular projections. That is why this is the key problem in this tutorial. © 2024 division of Signal Processing and Electronic Systems, Poznan University of Technology (DSPES PUT).

关键词： Matrix algebra

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Role of IoT in characterization and material properties of synthesis of chromel composite

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Interactions 2024年第1期245卷 1-9页

作者： Siva, T. Bruno, A. Dyson Hepsiba, D. Vijay Anand, L.D. Ram, S. Priya, L. Department of Mechanical Engineering Meenakshi Ramaswamy Engineering College Tamilnadu Thathanur Ariyalur India Department of Mechanical Engineering PSNA College of Engineering and Technology Dindigul India Division of Biomedical Engineering Karunya Institute of Technology and Sciences Coimbatore India Division of Robotics Engineering Karunya Institute of Technology and Sciences Coimbatore India Department of Mechanical Engineering Gokaraju Rangaraju Institute of Engineering andTechnology Hyderabad India Department of Information Technology Bannari Amman Institute of Technology Erode Sathyamangalam638 401 India

The chromel metal matrix composite (MMC) was fabricated through stir casting process reinforced with Tantalum Carbides (TaC). It was used to further increase the substance properties. The morphology characteristics and chemical compositions have been studied through Scanning Electron Microscope (SEM) and Energy Dispersive Analysis of X- Ray (EDAX) respectively. The substance properties such as hardness, density, impact and tensile strength were measured. The quality of the casting components are achieved through monitoring of internet of things (IoT). IoT enabled stir casting system is used to fabricate the chromel composite. The casting process is fully automated by IoT. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Tensile strength

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Camera-based light source localization for precise luminous intensity measurement of airport lamps 27

Camera-based light source localization for precise luminous ...

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27th IEEE Signal Processing: Algorithms, Architectures, Arrangements, and Applications, SPA 2024

作者： Podbucki, Kacper Marciniak, Tomasz Poznan University of Technology Faculty of Automatic Control Robotics and Electrical Engineering Institute of Automatic Control and Robotics Division of Electronic Systems and Signal Processing Jana Pawla II 24 Poznań60-965 Poland

ISBN: (纸本)9788362065486

Measuring luminous intensity using electronic sensors requires their precise positioning. In the case of mobile measurement platforms, it is important to detect the light source and thus determine the correct direction of movement of the measuring device. This article presents research on a solution for the initial detection of glowing airport lamps based on camera images. The impact of the selection of parameters and image processing methods on the prepared data set was assessed. The histogram filtration method was introduced to improve the effectiveness of airport lamp localization. The proposed solution was investigated in different weather and daytime conditions. The overall accuracy of the proposed solution is more than 90%. © 2024 division of Signal Processing and Electronic Systems, Poznan University of Technology (DSPES PUT).

关键词： Image enhancement

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Early Detection and Treatment of Skin Diseases Using Advanced Image Preprocessing and Machine Learning Techniques 4

Early Detection and Treatment of Skin Diseases Using Advance...

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4th International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2024

作者： Pandian, Jeswin Paul Jegan, R. Jerlinkasmir, R. Jose, P. Subha Hency Raj, P. Anantha Christu Karunya Institute of Technology and Science Division of Biomedical Engineering Coimbatore India Karunya Institute of Technology and Science Department of Mathematics Coimbatore India Karunya Institute of Technology and Science Division of Robotics and Automation Engineering Coimbatore India

ISBN: (纸本)9798331529635

This research aims to develop a more accurate and efficient system for classifying skin diseases, including both malignant and non-cancerous conditions. The study utilizes a comprehensive dataset encompassing various skin diseases, including melanomas, basal cell carcinomas, and benign conditions like nevi and warts. To address the challenge of class imbalance with a higher number of melanoma images, the researchers employ techniques like SMOTE (Synthetic Minority Oversampling Technique) to create synthetic data for under-represented classes. The pre-processing stage involves crucial steps like image scaling, augmentation, normalization, and data cleaning to ensure the quality and consistency of the data. Following pre-processing, feature extraction and model training will be conducted. This research has the potential to significantly contribute to the field of dermatology by enabling faster and more precise diagnosis of skin diseases through the use of advanced pre-processing techniques and a diversified dataset. © 2024 IEEE.

关键词： Lung cancer

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