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277 articles for “model interpretability”
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Heterosis in Plants
Abstract: It refers to hybrid vigor or heterosis; herein, the offspring expressed better traits than one or both parent lines. This most often manifests in crop breeding as increased yield in F1 hybrids compared with their parents. Developing high-yielding hybrid cultivars across a wider range of crops represents an important strategy for addressing future food security. However, conventional hybrid breeding approaches are fraught with significant challenges in many self-pollinating crops, such …
Published in Research & Reviews : Journal of Botany · Vol. 14, Issue 2, 2025 · pp. 21–31 Read article
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A Review Paper on The Mathematical Foundations of Artificial Intelligence
Abstract: Artificial Intelligence (AI) is deeply rooted in various branches of mathematics, which provide the theoretical foundation and practical tools for developing intelligent systems. This paper explores the crucial role of mathematics in AI, focusing on key areas such as Linear Algebra, Probability and Statistics, Optimization Techniques, Calculus, Graph Theory, and Fourier and Wavelet Transforms. Linear Algebra is fundamental for representing and manipulating data, with applications in dimensionality reduction and neural …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 3, 2025 · pp. 7–14 Read article
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Signal Drift Compensation in Polymer-Based Wearable Biosensors Using Data Processing Techniques
Abstract: Polymer-based wearable biosensors have emerged as promising platforms for continuous physiological monitoring due to their mechanical flexibility, low operating voltage, and compatibility with soft biological interfaces. However, their long-term deployment remains challenging because of signal drift caused by polymer ageing, hydration–dehydration cycles, ionic trapping, and environmental variations. These effects introduce baseline fluctuations and sensitivity degradation, which compromise the reliability and interpretability of physiological measurements. This study proposes a data-processing–driven framework …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 197–207 Read article
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Harnessing NLP for Automation and Intelligence Across Sectors
Abstract: Natural Language Processing or NLP is a vital subset of Artificial Intelligence or AI which enables machines to interpret, understand, and communicate using human language in a remarkable way. From the traditional rule-based approaches to the modern advanced deep learning techniques such as transformers, neural networks, and hybrid models, NLP has been evolving year by year. This study reflects on various applications of NLP, including sentiment analysis, machine translation, analysis …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 23–32 Read article
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Maadhyam: Sign Language Translator (ASL)
Abstract: There are several million deaf and dumb people around the world and their only means of communication is sign language. They are usually not able to receive education and even some of them are unemployed due to lack of communication. This often leads to mental health issues among them. Deaf and dumb people rely on sign language interpreters for communications because other people do not prefer learning their language. However, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 8, Issue 2, 2021 · pp. 42–50 Read article
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Automated Microstructure Classification with Class-Specific Segmentation for Titanium Based Composite Materials
Abstract: In engineering, characterisation of microstructure is required to determine and forecast behaviour of titanium alloys. Our proposal in this work has been a deep-learning-based framework in the automatic classification and segmentation of Titanium Based Composite Material. The framework then uses EfficientNetB0 backbone, where we have chosen the backbone to scale the performance of classification and the computational efficiency with the assistance of the transfer learning and the compound scaling. In …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 424–433 Read article
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Analysis of World Population Growth Using Python
Abstract: In this research work, we studied data analysis using the Python programming language. The fundamental steps in data analysis, such as cleansing, converting, and modelling of data is briefly explained in this study. In order to come up with good results, data analysis is required. Python has been used by us for data analysis. This language is interactive, interpreted, and follows an object-oriented programming paradigm. It is open source and …
Published in Recent Trends in Programming languages · Vol. 11, Issue 1, 2024 · pp. 15–20 Read article
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Microvita‑Inspired Informational Field Dynamics as a Nonlinear Signal‑Generation Mechanism in Matter–Life–Mind Systems
Abstract: Recognizing how matter, life, and consciousness relate to one another continues to be among the most essential challenges faced by modern science. Contemporary physical theories successfully describe the behavior of elementary particles and large-scale cosmological structures, yet they do not fully explain the emergence of informational complexity and organized patterns observed in biological and cognitive systems. This study proposes a theoretical framework in which Microvita are interpreted as subtle informational …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 · pp. 34–49 Read article
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AI-Based Early Diagnosis & Prevention of Diabetes
Abstract: The worldwide burden of Diabetes Mellitus, especially Type 2 diabetes (T2D) has escalated to a critical level. Early detection of diabetes is essential to reduce long‑term complications and healthcare costs. This study explores the use of artificial intelligence (AI) techniques to improve the early diagnosis and prevention of diabetes. We developed an AI model using the Random Forest algorithm, the model predicts diabetes risk based on clinical and lifestyle variables …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Fuzzy Variable Frame Analysis for Speech Recognition
Abstract: AbstractRecent works in machine learning has focused on models such as support vector machine (SVM), artificial neural network (ANN) and long short-term memory (LSTM), for automatically controlling the generalization and parameterization of the optimization process. This paper presents a fuzzy interpretation frame analysis procedure using LSTM classifier for noisy speech at word level using thresholding and local maxima procedure at framing level for the recognition process. Front end MFCC procedure …
Published in Current Trends in Signal Processing · Vol. 9, Issue 3, 2019 · pp. 9–18 Read article
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Comparative Study of BERT Variants for Sentiment Analysis with Error Analysis
Abstract: The use of media is going up fast in India, and this has led to the rise of Hinglish. Hinglish is an informal blend of Hindi and English that people commonly use in everyday conversations, especially across social media platforms such as Twitter, Facebook, and WhatsApp. People use Hinglish to talk to each other in a way that is not very formal. Hinglish blends English vocabulary with informal usage, often …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 39–48 Read article
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Lip Reading: Transforming Speech to Text
Abstract: Lip reading, the ability to interpret spoken language by observing lip movements, is a valuable skill that can aid in various applications, particularly in enhancing speech recognition systems. This project explores the implementation of a deep learning-based lip-reading model to improve the accuracy and robustness of speech recognition in challenging environments, such as noisy or audio-limited settings. The proposed lip-reading system leverages Convolutional Neural Networks (CNNs) and Recurrent Neural Networks …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 23–33 Read article
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Detecting Winding Movement by Fuzzy Logic for Frequency Response of Power Transformer
Abstract: Power transformers are basically one of the most efficient devices that are used in Power Plant or in any substation. Its maintenance is bit some tedious but has to be done to diagnose any severe fault that may damage the transformer. Sweep Frequency Response Analysis (SFRA) is used to detect any winding or core deformation in transformer that would arise during transportation, due to severe short circuits or due to …
Published in Journal of Power Electronics and Power Systems · Vol. 5, Issue 3, 2015 · pp. 25–34 Read article
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U-Net Based Approach for Automated Brain Tumor Classification
Abstract: Brain tumor detection and identification play vital roles in diagnostic procedures in the field of medicine, with the conventional analysis of MRI images requiring a lot of time and also subject to variability. The proposed study involves the use of a CNN-U-Net based approach for brain tumor detection and identification automatically. The study uses a database of 3,064 contrast-enhanced T1-weighted MRI images from 233 patients with the tumors of meningioma, …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 Read article
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Explainable Machine Learning Integrated with Polymer-Based Diagnostic Technologies for Liver Health Classification
Abstract: Early and reliable assessment of liver health is essential for timely treatment, yet most machine-learning approaches face limitations such as class imbalance and low clinical interpretability. This study proposes a polymer-integrated, explainable machine-learning framework that combines SMOTE-based data balancing, Logistic Regression, and XAI techniques (SHAP and LIME) for transparent liver-health classification. In addition to ML modelling, the study emphasizes the emerging role of polymer-based biosensors, microfluidic polymer chips, polymer nanomaterials, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 631–643 Read article
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YOLOv8 in Focus: A Review of its Application in Driver Monitoring Systems
Abstract: This research presents a novel Driver Monitoring System (DMS) that utilises Convolutional Neural Networks (CNNs) to achieve remarkable results. Specifically, the YOLOv8 (You Only Look Once version 8) detection technique is used. The main goal is to increase road safety by using cutting-edge computer vision techniques to analyse driver behaviour in real-time. The YOLOv8 detection method, a cutting-edge CNN model renowned for its precision and effectiveness in object recognition, is …
Published in Journal of Electronic Design Technology · Vol. 14, Issue 3, 2023 · pp. 35–40 Read article
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Machine Learning Approach to Detect and Analyze Attention-Deficit/Hyperactivity Disorder
Abstract: Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder characterized by difficulties with attention, impulse control, behavioral regulation, and daily functioning that persist across childhood and adulthood. Clinical diagnosis is predominantly based on behavioral assessments and expert interpretation, which may result in subjectivity and delayed clinical decisions. To reduce reliance on subjective evaluation, this study introduces an automated ADHD identification framework that integrates resting-state functional Magnetic Resonance Imaging (rs-fMRI) with advanced machine …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 22–26 Read article
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A Shell Programming Framework for Automated Risk Assessment and Security Control in Linux Operating Systems
Abstract: Linux operating systems are widely used in servers, embedded platforms, cloud infrastructure, and high-performance computing environments, making continuous system monitoring and risk assessment essential for maintaining security and operational reliability. Conventional risk assessment approaches often rely on individual system commands and manual interpretation of processor, memory, process, file, and security information, which can limit timely identification of abnormal system conditions. This paper proposes a Bash shell programming-based automated risk assessment …
Published in Journal of Advances in Shell Programming · Vol. 13, Issue 2, 2026 · pp. 55–66 Read article
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Exploring Practical Applications of Artificial Neural Networks: A Review
Abstract: Computational models called artificial neural networks (ANNs) are modeled after the structure of the human brain. These models are designed to process information and learn from data. Artificial neural networks, or ANNs, are composed of interconnected artificial neurons layered to resemble the brain's neural network.. Through training, ANNs adjust the connections between neurons based on labeled data, enabling them to recognize patterns and perform specific tasks. Despite their efficacy in …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 2, 2024 · pp. 1–11 Read article
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Modelling of Beam Pumping System using Simulation with Case Study
Abstract: The study deals with analyzing the performance of beam pumping system or sucker rod pump (SRP) through automation and counter balancing. In order to operate the pump in an efficient manner, the performance of SRP is also analyzed in the conditions of under balanced, normally balanced and even for precisely balanced wells. The main focus of the work is to troubleshoot by systematic analysis of dynamometer card, correct interpretation and …
Published in Journal of Petroleum Engineering & Technology · Vol. 6, Issue 1, 2016 · pp. 9–24 Read article