Girijesh Prasad
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View article: Health Monitoring and Drift Detection of Bearing Using Direct Density Ratio Estimation
Health Monitoring and Drift Detection of Bearing Using Direct Density Ratio Estimation Open
Prognostics and health management (PHM) has been widely employed for condition monitoring, fault diagnosis and failure prediction in mechanical systems. However, the presence of uncertainty and transient fluctuations in condition monitorin…
View article: Neurophysiological Fluctuation Detects Mental Fatigue Prior to Subjective Awareness
Neurophysiological Fluctuation Detects Mental Fatigue Prior to Subjective Awareness Open
Objective and timely detection of mental fatigue is critical to its understanding and intervention. However, previous studies did not clearly dissociate mental fatigue from other arousal states. Here, we propose an adaptive, cognitively de…
View article: Using Continuous Glucose Monitoring as a Guide for Better Diabetes Management: A New Strategy Assessed at 20 HCP Clinics Across India
Using Continuous Glucose Monitoring as a Guide for Better Diabetes Management: A New Strategy Assessed at 20 HCP Clinics Across India Open
Introduction: Diabetes mellitus (DM) has been a global public health concern for decades contributing to increasing morbidity and mortality. The glucocentric approach of management has been effective yet inadequate in achieving glycemic co…
View article: Artificial Intelligence In Audit Process – Its Use And Challenges In Indian Perspective And Advanced Countries
Artificial Intelligence In Audit Process – Its Use And Challenges In Indian Perspective And Advanced Countries Open
Artificial intelligence (AI) is transforming the auditing landscape by improving accuracy and efficiency while lowering auditor risk when auditing an entity's financial statements. The study aims to comprehend how AI is used to carry out t…
View article: Machine Learning with Heuristic Search-Based Hybrid Framework for Cycle Time Optimization in Semiconductor Production
Machine Learning with Heuristic Search-Based Hybrid Framework for Cycle Time Optimization in Semiconductor Production Open
This paper aims to optimise cycle time (CT) in semiconductor wafer production, a critical factor for enhancing operational efficiency and competitiveness in the semiconductor manufacturing industry. A hybrid methodology, based on statistic…
View article: Smart City Simulation and Design using AI
Smart City Simulation and Design using AI Open
The idea of smart cities is a viable answer to the problems that urbanization is posing to cities worldwide, and artificial intelligence (AI) is a key component of this change. With an emphasis on its six primary domains—smart mobility, sm…
View article: A Hybrid Spiking Neural Network-Quantum Classifier Framework: A Case Study Using EEG Data
A Hybrid Spiking Neural Network-Quantum Classifier Framework: A Case Study Using EEG Data Open
The study introduces a hybrid computational framework that combines neuro-inspired information processing using spiking neural networks (SNN) and quantum information processing using quantum kernels to develop quantum-enhanced machine lear…
View article: Vision-to-Voice: AI for generating Description & Audio of Visual Content
Vision-to-Voice: AI for generating Description & Audio of Visual Content Open
- The seamless transformation of visual content into descriptive text and naturalistic speech, termed Vision-to-Voice, represents a significant interdisciplinary advancement at the intersection of computer vision, natural language processi…
View article: Performance Analysis of Quantum-Enhanced Kernel Classifiers Based on Feature Maps: A Case Study on EEG-BCI Data
Performance Analysis of Quantum-Enhanced Kernel Classifiers Based on Feature Maps: A Case Study on EEG-BCI Data Open
View article: Visual Angles and Emotional Valence Affect Temporal Dynamics of Neural Representations of Facial Expression: An MEG Study
Visual Angles and Emotional Valence Affect Temporal Dynamics of Neural Representations of Facial Expression: An MEG Study Open
Emotion processing has been a focus of research in Cognitive Neuroscience for decades. While the evoked neural markers as brain activations in response to different emotions have been reported, the temporal dynamics of emotion processing h…
View article: Two-Step Framework for Predictive Maintenance of Cryogenic Pumps in Semiconductor Manufacturing
Two-Step Framework for Predictive Maintenance of Cryogenic Pumps in Semiconductor Manufacturing Open
Semiconductor manufacturing involves many critical steps, wherein maintaining an ultra-high vacuum is mandatory. To this end, cryogenic pumps are used to create a controlled ultra-low-pressure environment through the use of cryogenic cooli…
View article: Estimation of Interferences in Magnetoencephalography (MEG) Brain Data Using Intelligent Methods for BCI-based Neurorehabilitation Applications
Estimation of Interferences in Magnetoencephalography (MEG) Brain Data Using Intelligent Methods for BCI-based Neurorehabilitation Applications Open
Brain-Computer Interface (BCI) neurorehabilitation offers the potential to improve recovery and quality of life for stroke survivors. It aims to restore lost physical and mental abilities through motor and cognitive therapies. Magnetoencep…
View article: Detection of Digital Image Forgery Using Deep-Learning
Detection of Digital Image Forgery Using Deep-Learning Open
In contemporary times, digital images serve as a primary medium for disseminating information across social media platforms.However, malicious software can manipulate these images to spread false information.So, it's crucial to identify th…
View article: An Automated Detection of Amyotrophic Lateral Sclerosis from Resting-State MEG Data Using 3D Deep Convolutional Neural Network
An Automated Detection of Amyotrophic Lateral Sclerosis from Resting-State MEG Data Using 3D Deep Convolutional Neural Network Open
A novel 3D deep convolutional neural network (3D-CNN) model called MEGNet3D has been proposed in the paper. MEGNet3D is designed to differentiate between amyotrophic lateral sclerosis (ALS) and healthy individuals from their resting state …
View article: A systematic review on artifact removal and classification techniques for enhanced MEG-based BCI systems
A systematic review on artifact removal and classification techniques for enhanced MEG-based BCI systems Open
Neurological disease victims may be completely paralyzed and unable to move, but they may still be able to think. Their brain activity is the only means by which they can interact with their environment. Brain-Computer Interface (BCI) rese…
View article: Mapping and decoding cortical engagement during motor imagery, mental arithmetic, and silent word generation using <scp>MEG</scp>
Mapping and decoding cortical engagement during motor imagery, mental arithmetic, and silent word generation using <span>MEG</span> Open
Accurate quantification of cortical engagement during mental imagery tasks remains a challenging brain‐imaging problem with immediate relevance to developing brain–computer interfaces. We analyzed magnetoencephalography (MEG) data from 18 …
View article: Detection of Dyslexic Children Using Machine Learning and Multimodal Hindi Language Eye-Gaze-Assisted Learning System
Detection of Dyslexic Children Using Machine Learning and Multimodal Hindi Language Eye-Gaze-Assisted Learning System Open
Children with dyslexia need specific instructions for spelling and word analysis from an early age. It is important to provide appropriate tools using technology for writing aids to such children that can help them to input text, while pro…
View article: A Comprehensive Study on Machine Learning Methods to Increase the Prediction Accuracy of Classifiers and Reduce the Number of Medical Tests Required to Diagnose Alzheimer's Disease
A Comprehensive Study on Machine Learning Methods to Increase the Prediction Accuracy of Classifiers and Reduce the Number of Medical Tests Required to Diagnose Alzheimer's Disease Open
Alzheimer's patients gradually lose their ability to think, behave, and interact with others. Medical history, laboratory tests, daily activities, and personality changes can all be used to diagnose the disorder. A series of time-consuming…
View article: Correction to: Regional optimum frequency analysis of resting-state fMRI data for early detection of Alzheimer’s disease biomarkers
Correction to: Regional optimum frequency analysis of resting-state fMRI data for early detection of Alzheimer’s disease biomarkers Open
View article: Regional optimum frequency analysis of resting-state fMRI data for early detection of Alzheimer’s disease biomarkers
Regional optimum frequency analysis of resting-state fMRI data for early detection of Alzheimer’s disease biomarkers Open
View article: Imaging cortical engagement during motor imagery, mental arithmetic, and silent word generation using MEG beta rhythm
Imaging cortical engagement during motor imagery, mental arithmetic, and silent word generation using MEG beta rhythm Open
Accurate mapping of cortical engagement during mental imagery or cognitive tasks remains a challenging brain-imaging problem with immediate relevance to the development of brain-computer interfaces (BCI). We analyzed data from fourteen ind…
View article: Multiple Cost Optimisation for Alzheimer's Disease Diagnosis
Multiple Cost Optimisation for Alzheimer's Disease Diagnosis Open
Current machine learning techniques for dementia diagnosis often do not take into account real-world practical constraints, which may include, for example, the cost of diagnostic assessment time and financial budgets. In this work, we buil…
View article: Multiple Cost Optimisation for Alzheimer’s Disease Diagnosis
Multiple Cost Optimisation for Alzheimer’s Disease Diagnosis Open
Current machine learning techniques for dementia diagnosis often do not take into account real-world practical constraints, which may include, for example, the cost of diagnostic assessment time and financial budgets. In this work, we buil…
View article: Electroencephalography and psychological assessment datasets to determine the efficacy of a low-cost, wearable neurotechnology intervention for reducing Post-Traumatic Stress Disorder symptom severity
Electroencephalography and psychological assessment datasets to determine the efficacy of a low-cost, wearable neurotechnology intervention for reducing Post-Traumatic Stress Disorder symptom severity Open
The datasets described here comprise electroencephalography (EEG) data and psychometric data freely available on data.mendeley.com. The EEG data is available in .mat formatted files containing the EEG signal values structured in two-dimens…
View article: Non-stationarity Removal Techniques in MEG Data: A Review
Non-stationarity Removal Techniques in MEG Data: A Review Open
Brain Computer Interface (BCI) enables communication solely through mental activity. For patients who have lost complete voluntary muscle control, it serves as a potential communication and rehabilitation channel. In a number of recent inv…
View article: Alzheimer’s Disease Assessments Optimized for Diagnostic Accuracy and Administration Time
Alzheimer’s Disease Assessments Optimized for Diagnostic Accuracy and Administration Time Open
Overall, our analysis and accompanying sandbox tool can facilitate clinical users and other stakeholders to apply their own domain knowledge to analyse and decide which dementia diagnostic assessment items are useful, and aid the redesigni…
View article: Integrated space–frequency–time domain feature extraction for MEG-based Alzheimer’s disease classification
Integrated space–frequency–time domain feature extraction for MEG-based Alzheimer’s disease classification Open
Magnetoencephalography (MEG) has been combined with machine learning techniques, to recognize the Alzheimer’s disease (AD), one of the most common forms of dementia. However, most of the previous studies are limited to binary classificatio…
View article: 877 Effects of continued folic acid supplementation during the second and third trimesters of pregnancy on children`s neurocognitive development at 11 years
877 Effects of continued folic acid supplementation during the second and third trimesters of pregnancy on children`s neurocognitive development at 11 years Open
View article: Detection of Mild Cognitive Impairment with MEG Functional Connectivity Using Wavelet-Based Neuromarkers
Detection of Mild Cognitive Impairment with MEG Functional Connectivity Using Wavelet-Based Neuromarkers Open
Studies on developing effective neuromarkers based on magnetoencephalographic (MEG) signals have been drawing increasing attention in the neuroscience community. This study explores the idea of using source-based magnitude-squared spectral…
View article: Neurofeedback with low-cost, wearable electroencephalography (EEG) reduces symptoms in chronic Post-Traumatic Stress Disorder
Neurofeedback with low-cost, wearable electroencephalography (EEG) reduces symptoms in chronic Post-Traumatic Stress Disorder Open