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ANFIS-Based Inverse Kinematics and Forward Dynamics of 3 DOF Serial Manipulator 1

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20th International Conference on Hybrid Intelligent Systems, HIS 2020 and 12th World Congress on Nature and Biologically Inspired computing, NaBIC 2020

作者： Deshmukh, Deepak Pratihar, Dilip Kumar Deb, Alok Kanti Ray, Hena Ghosh, Alokesh Indian Institute of Technology Kharagpur India Centre for Development of Advanced Computing Kolkata India

ISBN: (数字)9783030730505

ISBN: (纸本)9783030730499

Study of a serial manipulator involves many non-linear functions and complex sets of equations. The complexity of the problem increases as mobility of the system increases and it becomes a very tedious task to analyse the robotic system especially the inverse kinematics and forward dynamics. This study is aimed to reduce the complexity of analysis by implementing adaptive neuro-fuzzy inference system-based inverse kinematic analysis and forward dynamic analysis. The CAD model of serial manipulators is prepared using SOLIDWORKS to get geometrical and inertial information. The manipulator is also mathematically modelled in MATLAB and its forward kinematics (FK), inverse kinematics (IK), and dynamic analyses are carried out. The ANFIS networks are trained using data generated by a mathematical model, and it is then tested for a new set of data. Finally, the results are validated by comparing with that of the mathematical model. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Inverse kinematics

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Emotion Recognition Using Chatbot System

Emotion Recognition Using Chatbot System

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International Conference on Recent Trends in Machine Learning, IOT, Smart Cities and Applications, ICMISC 2020

作者： Pophale, Shraddha Gandhi, Hetal Gupta, Anil Kumar Walchand College of Engineering Sangli India Centre for Development of Advanced Computing Pune India

ISBN: (纸本)9789811572333

It is observed that the number of suicide attempts among students is increasing day by day. The reasons behind these attempts can be tough competitions, comparisons with others in college, or at home or partial nature of teachers towards students. In this context, the computer chatbot system may be built to recognize the emotions from the text conversations done by students. Such a system will also help teachers to understand student’s psychological behavior to monitor the information of students and take prior precautions. The goal of this paper is to provide an effective conversational interface for the same. We are using the hybrid model to improve the performance of recognizing human emotions. The system employs the structural characteristics of chatting using NLP techniques. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Emotion Recognition

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Real-Time Webcam-Based Eye Tracking for Gaze Estimation: Applications and Innovations

Real-Time Webcam-Based Eye Tracking for Gaze Estimation: App...

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International Conference on computing and Networking Technology (ICCNT)

作者： Tanmay Jain Samiksha Bhatia Chandan Sarkar Priyanka Jain N. K. Jain Centre for Development of Advanced Computing (C-DAC) Delhi India DeenBandhu Chhotu Ram University Of Science And Technology Murthal Haryana

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Webcam-based eye-tracking systems offer a costeffective and accessible solution for capturing eye movements and gaze direction, facilitating applications in human-computer interaction (HCI), virtual reality (VR), and market research. This paper presents a novel webcam-based eye-tracking system, addressing accessibility, affordability, and usability by leveraging ubiquitous webcam technology, eliminating the need for specialized hardware. The methodology improves gaze estimation accuracy and stability by addressing inherent noise and variability by an average of 79 percent. A Multioutput Regressor with Support Vector Regression (SVR) as the base model, refined through linear regression, aligns predicted gaze points with actual screen coordinates. The Kalman filter stabilizes tracking by recursively predicting and updating state estimates. A responsive web application was developed using Flask, HTML, CSS, and JavaScript. Real time pupil detection was facilitated by MediaPipe, with data transmitted via Web-Sockets using the *** library. Frame-by-frame data collection, processed through stacking models and Kalman filtering, enhances accuracy and precision. Applications include early detection of neurological diseases like Parkinson’s, Alzheimer’s, and autism spectrum disorder (ASD), and assisting individuals with disabilities in controlling devices via eye movements. In education, eye-tracking enhances student engagement and personalized learning. Businesses can optimize product placement and advertisement effectiveness. In gaming and VR, integrating eye-tracking enhances natural interactions and immersive experiences. Future developments focus on enhancing algorithmic performance, integrating with AI, AR, and VR, and providing real-time feedback. Ethical guidelines and privacy safeguards are crucial for data security, democratizing eye-tracking technology for diverse applications.

关键词： Solid modeling Accuracy Webcams Estimation Gaze tracking Real-time systems Hardware Kalman filters Usability Pupils

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Spatially Varying Regularization for Microwave Imaging 11

Spatially Varying Regularization for Microwave Imaging

引用

11th International Conference on Internet of Everything, Microwave Engineering, Communication and Networks, IEMECON 2023

作者： Magdum, Dhananjay Kadam, Sanjay Abhyankar, Aditya Ghaisas, Subhash Erramshetty, Mallikarjun Magdum, Amit Savitribai Phule Pune University Department of Technology Pune India Savitribai Phule Pune University Department of Technology Centre for Development of Advanced Computing Pune India National Institute of Technology Goa Department of Ece Goa India

ISBN: (纸本)9781665475129

This paper presents a new spatial-based regularization technique to efficiently reconstruct unknown scatterers using microwave imaging. In general, a constant regularization parameter is used to obtain an inverse solution. However, the major drawback of using this parameter is that it produces ghost images, often known as artifacts. To overcome this problem, a spatially varying regularization parameter is developed in this work. The main contribution of this approach is that it removes unwanted artifacts and provides uniform reconstruction over the entire investigation domain. This results in improved reconstruction quality. The effectiveness of this approach is demonstrated using several numerical examples utilizing both synthetic and experimental data. In all the cases, the proposed method is able to provide an optimal solution free of speckle artifacts. Consequently, better reconstruction results are obtained compared to a standard Tikhonov method with constant regularization parameter. © 2023 IEEE.

关键词： Inverse problems

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Integrating AI and Semi-Immersive AR Technology for Brain Tumor Diagnosis 10

Integrating AI and Semi-Immersive AR Technology for Brain Tu...

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10th International Conference on Engineering and Emerging Technologies, ICEET 2024

作者： Amara, Kahina Guerroudji, Mohamed Amine Kerdjidj, Oussama Khedir, Meriem Zenati, Nadia Atalla, Shadi Mansoor, Wathiq Ramzan, Naeem Centre for Development of Advanced Technologies Algiers Algeria College of Engineering and It University of Dubai Dubai United Arab Emirates Higher School of Computer Science Sidi Bel Abbes Algeria School of Computing Engineering and Physical Sciences University of the West of Scotland Scotland Paisley United Kingdom

ISBN: (纸本)9798331532895

Brain tumours, characterised by abnormal cell development inside the brain, pose a significant risk to individuals due to their high mortality rate. Early identification is essential for accurate diagnosis and successful treatment to enhance patient outcomes. However, diagnosing small tumours can be difficult and error-prone, as it largely depends on the experience and qualifications of medical personnel. Therefore, an automated diagnostic approach that reduces diagnostic time while increasing accuracy is desperately needed. This study addresses the challenges of manual diagnosis by applying deep learning algorithms to brain tumour segmentation. Additional challenges in applying deep learning for tumour segmentation include handling low-quality scans, variations in tumour features, and insufficient data. We present an emerging concept combining Artificial Intelligence and Augmented Reality as a valuable tool, providing deep learning model deployment, immersive visualisation, and interactive functionalities to support diagnosis and surgical interventions for brain tumours. The achieved performance is competitive with the literature, and feedback from medical professionals after deployment evaluation is satisfactory. © 2024 IEEE.

关键词： Magnetic resonance imaging

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“Performance Evaluation of Variant Calling Tools for Human and Microbial Genomes”

“Performance Evaluation of Variant Calling Tools for Human ...

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International Conference on Emerging Trends in Networks and Computer Communications (ETNCC)

作者： Kirti Bhadhadhara Muthukumar Balamurugan Neeraj Bharti Ruma Banerjee Sunitha Manjari Kasibhatla Rajendra Joshi HPC-Medical & Bioinformatics Applications Group Centre for Development of Advanced Computing (C-DAC) Pune India

Analyzing the data deluge generated by next generation sequencing technologies is a challenging task. Variant calling aids in characterizing phenotype of an organism. The objective of this work is to compare popular variant calling protocols available in terms of their accuracy for human and microbial genomes. Three popular read aligners viz. BWA-MEM, Bowtie2 and NovoAlign were used for the human genome benchmark dataset of Genome in a Bottle (GIAB). Variant calling was performed using four popular variant callers viz. samtools-bcftools, VarScan2, GATK-HC and DeepVariant. For microbial genomes, BWA-MEM was used for reference mapping followed by variant calling using above-mentioned tools (excluding DeepVariant) along with FreeBayes and PILON. The predicted variants were assessed in terms of true positives, false positives and false negatives. Consensus approach was used for identifying SNPs (predicted by more than one variant calling pipeline) in the false positive dataset that satisfied the threshold criteria to be included as true positives. Precision and Recall were measured for evaluating each of the variant calling pipelines. Variant calling pipeline using BWA-MEM for read mapping along with either VarScan2 or samtools-bcftools predicted optimal number of single nucleotide polymorphisms (SNP) for high coverage human datasets. For Indel calling, GATK-HC with any aligner was preferred over VarScan2 and samtools-bcftools. Variant calling using bcftools, Pilon and GATK-HC with default parameters for heterogeneous microbial datasets revealed optimal performance. SNP calling with minimum errors was evident when $\sim\mathbf{95}\%$ of the samples from a population was taken into cognizance for variant prediction. Predicted variants were validated by comparing with gold standard data which aided in improved identification of actionable high confidence variants, reduced prediction of false positives and this approach has proved to be valuable for prioritization of act

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Implementation of a FHIR Specification for the Interoperability of a Remote Monitoring Platform of Patients with Vascular Diseases 20th

Implementation of a FHIR Specification for the Interoperabil...

引用

20th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2022

作者： Vieira, Ana Conceição, Luís Faria, Luiz Novais, Paulo Marreiros, Goreti GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Institute of Engineering – Polytechnic of Porto Porto Portugal ALGORITMI Centre University of Minho Braga Portugal

ISBN: (纸本)9783031186967

To address the current burdens in the healthcare of patients with vascular diseases, the Portuguese consortium of the Inno4Health project is currently developing a remote monitoring platform that aims to support the self-management of patients with vascular diseases. With the continuous remote monitoring of patients, it is intended that the platform supports both patients and health professionals. Patients will be supported through the presentation of personalized recommendations of activities to perform and health professionals will be supported in the clinical decision making through the presentation of meaningful insights. As the platform is composed by several components, including monitoring sensors, data processing modules and user applications, theressss is a need for the standardization of the data used. This work presents the implementation of a Fast Healthcare Interoperability Resources (FHIR) specification in the remote monitoring platform to ensure the standardization of the data that will be collected and exchanged between the several components of the platform. With this work, it will be possible to easily and securely exchange data, as well as integrating new monitoring sensors and user applications in the platform. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Standardization

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Electrochemical based Gas Sensing for Ambient Air Quality Monitoring in Opencast Coal Mines 1

Electrochemical based Gas Sensing for Ambient Air Quality Mo...

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1st International Conference on Electrical, Electronics, Information and Communication Technologies, ICEEICT 2022

作者： Krishnan, Arun K. Panicker, Senju Thomas Sandeep, S. Jithin, S. Daniel, Jerry J. Sajjad, Tarique Centre for Development of Advanced Computing Control and Instrumentation Group Kerala Thiruvananthapuram India Central Mine Planning and Design Institute Mining Electronics Department Jharkhand Ranchi India

ISBN: (纸本)9781665436472

Air quality monitoring is mandatory in many industries like mining, refining and semiconductor industries owing to detrimental impact of air pollutants on the health of human beings, animals and the environment. There is a growing concern regarding the health impact of air pollutants on personal working in coal mines, both opencast and underground. Toxic gases in the ambient air can rapidly become a danger if not kept within safe permissible limits. The first step in maintaining air quality in coal mining areas is continuous monitoring of the atmospheric air. Toxic gases like carbon monoxide, nitric oxide, nitrogen dioxide and sulphur dioxide produced by various mining activities contribute to polluting the air. Several techniques are being used worldwide to sense the presence of various pollutant gases. This paper explores the various techniques for sensing of toxic gases in ambient air and sheds light into their pros and cons. It showcases a simple and cost-effective way of sensing toxic gases in areas near opencast mines by using electrochemical gas sensors. The paper also sheds light on the design of an ambient air quality monitoring instrument which uses electrochemical gas sensors for sensing the concertation of SO2, NO2, NO and CO at areas near opencast coal mines © 2022 IEEE.

关键词： Sulfur dioxide

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Remote Photoplethysmography (rPPG) for Contactless Blood Oxygen Saturation Monitoring

Remote Photoplethysmography (rPPG) for Contactless Blood Oxy...

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IEEE International Conference on Electronics, computing and Communication Technologies (CONECCT)

作者： Yaythish Kannaa G S Sayantani Bhattacharya N Aishwarya Department of Electronics and Communication Engineering Amrita School of Engineering Chennai India Centre for Development of Advanced Computing (C-DAC) Chennai India

ISBN: (数字)9798350385922

ISBN: (纸本)9798350385939

The increasing demand for healthcare technologies in Ambient Assisted Living, accentuated by recent global health challenges, necessitates advanced solutions for continuous and non-invasive vital sign monitoring. This research addresses this imperative by introducing a novel application utilizing remote photoplethysmography-based techniques. Focused on frail and elderly individuals, the application aims to measure key vital signs, like SpO2. Unlike traditional methods, our approach requires no wearable sensors, providing a comfortable and convenient monitoring solution. The application's development involves a comprehensive pipeline for vital sign estimation, overcoming challenges posed by diverse skin tones and facial characteristics in elderly subjects. The system had achieved notable results in terms of accuracy measuring 1.2 in MSE and 1.09 in RMSE. This innovative application represents a significant step forward in non-invasive vital sign monitoring, offering a promising avenue for enhancing healthcare in Ambient Assisted Living environments.

关键词： Patient monitoring Ambient assisted living Telemedicine Refining Medical services Cameras Skin

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A Quantum Machine Learning framework for Driver Drowsiness Detection using Biopotential Signals and Head Movement Analysis

A Quantum Machine Learning framework for Driver Drowsiness D...

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Women in Innovation, Technology & Entrepreneurship (ICWITE), IEEE International Conference for

作者： Sagnik De Anil Kumar Gupta Institute of Radio Physics and Electronics University of Calcutta Kolkata India Centre for Development of Advanced Computing (C-DAC) Pune Maharashtra India

Road accidents claim numerous lives annually, with drowsiness identified as a primary catalyst for a substantial portion of these incidents. This study addresses this critical issue by introducing an innovative approach to gauge human drowsiness levels during driving. The primary objective of this study is to introduce a novel deep-learning technique capable of detecting various alertness levels—awake, drowsy, and very sleepy—while driving. For this purpose, a hybrid model is proposed, leveraging Convolutional Neural Networks (CNN) in conjunction with an Attention-based Quantum Long Short-Term Memory (QLSTM) network. The designed model employs different biopotential signals, including electroencephalogram (EEG), facial electromyography (EMG), pulse rate, and head movement, to discern a person’s alertness level. Demonstrating remarkable accuracy, the proposed model achieves detection rates of 99%, 98.5%, and 99% for awake, drowsy, and very sleepy states, respectively, thus offering a promising solution to mitigate the impact of drowsiness-related accidents.

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