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184 articles for “Performance Metrics”
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A Comparative Analysis of Machine Learning Techniques for Fruit Defect Detection Systems
Abstract: With evolving technologies in machine learning, significant advancements have been made in the livestock industry, helping to reduce waste, increase yield, achieve cost savings, and improve competitiveness in the marketplace. Fruit defect detection models support precision agriculture by providing valuable data for decision-making and enhancing overall efficiency through automated inspection processes. This study implements and comparatively evaluates machine learning models including MobileNetV2, a custom-designed convolutional neural network (CNN) model, ResNet50, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 37–47 Read article
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Hybrid Quantum–Machine Learning Framework for Nonlinear Rheological Modeling of Polymer and Composite Materials
Abstract: In polymer and composite materials, a major challenge lies in predicting their nonlinear rheological response, owing to complex multiscale interactions that are not captured by traditional constitutive laws or conventional machine learning approaches. In this study, a hybrid Quantum Machine Learning (QML) model comprising Quantum Support Vector Machine (QSVM) and Quantum Neural Network (QNN) architectures is proposed for viscosity prediction without requiring any specific rheological equation. To train and test …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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Smart Service Solutions AI: AI-driven Multimodal Search for Home Appliance Support
Abstract: The global home appliance services market is projected to reach USD 1,203.11 billion by 2032, driven by smart household appliances. Essential services like installations, maintenance, and repairs ensure optimal performance and longevity, leading to higher customer satisfaction and loyalty. The service station partner ecosystem is crucial for ongoing support and profitability. However, challenges such as identifying the right manuals, finding relevant parts, and providing accurate instructions must be addressed to …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 3, 2025 · pp. 27–43 Read article
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The Influence of Soil Types on the Performance of the Building Frames: A Dynamic Analysis
Abstract: The dynamic response of the building structure is to a large extent dependent on the nature of the supporting soil. Soil stiffness and damping metrics fluctuation can cause significant tension in the behaviour of building skeleton when exposed to dynamic loads such as earthquake or wind. This research aims to evaluate how different soil conditions namely hard, medium, and soft soils impact the seismic performance of building frames under dynamic …
Published in Journal of Geotechnical Engineering · Vol. 12, Issue 2, 2025 · pp. 25–27 Read article
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Predicting Student Placement Readiness: A Machine Learning Approach Using Coding Activities and Multi-Dimensional Performance Indicators
Abstract: In the modern information-driven academic world, identifying student employability and placement preparedness has predicted. be made a part and parcel of academic planning and career. development. This study provides a machine learning-based. structure to evaluate and forecast student placement pre-paredness by combining various performance aspects-academic achieve- ment, coding activity, aptitude and behavioral engage-ment metrics. Multi-source was gathered and preprocessed in the study. student information, such as student records (CGPA, attendance), …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 Read article
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Elderly Healthcare Using Federated Learning Approach
Abstract: The healthcare system for elderly people faces several challenges, which can be addressed using advanced machine learning models. These models can help monitor chronic diseases, detect falls, and provide personalized health recommendations. The study uses comprehensive datasets like MIMIC-III/IV, WESAD, and UCIHAR to explore human movements, device limitations, and the differences in fall occurrences. A detailed review of existing literature discusses current technologies for activity monitoring and fall detection, focusing …
Published in Current Trends in Information Technology · Vol. 16, Issue 1, 2025 · pp. 13–23 Read article
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Design and Development of an Automated Robotic Algorithm for Blasting, Painting, and Barnacle Cleaning of Offshore Structures
Abstract: Marine surface maintenance tasks such as barnacle removal, abrasive blasting, and protective painting are traditionally carried out using manual methods that are labor-intensive, hazardous, and prone to variability in quality. These challenges are particularly significant for offshore structures, where harsh environmental conditions and restricted accessibility increase operational risks and maintenance costs. This paper presents the design and evaluation of an autonomous robotic system for automated surface preparation and coating of …
Published in Journal of Offshore Structure and Technology · Vol. 13, Issue 1, 2026 · pp. 1–12 Read article
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Crop Disease Prediction by Machine Learning
Abstract: The classification of Crop can be classified into several methods. The data set of crop leaf illnesses, notably Bacterial Leaf Blight disease (BLB), a crop leaf disease with significant outbreaks throughout Thailand, and Brown Spot Crop disease (BSR), is classified employing image classification in this study. Additionally, image processing technology is used for identifying different types of crop leaf disease. These algorithms include the Random Forest, Decision Tree, Gradient Boost, …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 21–25 Read article
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Formulation and Evaluation of Saliva Substitute
Abstract: The development and evaluation of saliva substitutes play a vital role in managing xerostomia, a condition marked by insufficient saliva production that adversely affects oral health and overall well-being. This study investigates various formulations of saliva substitutes intended to replicate the functionality of natural saliva. The key goals are to assess their moisturizing effectiveness, physical and chemical properties, and in vitro performance. These formulations generally incorporate hydrators, lubricants, thickeners, and …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 11, Issue 3, 2024 · pp. 32–47 Read article
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Card Fraud Detection Using Artificial Neural Network and Multilayer Perception Algorithm
Abstract: Fraud has posed a significant challenge for merchants, especially in the online business sector, over the course of many years. This is primarily due to the advancements in technology that have made credit card transactions a common method of payment. Credit card fraud refers to the unauthorized use of a credit card by an individual for personal purposes, without the owner's consent and with no intention of paying for the …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 1, Issue 1, 2023 · pp. 21–30 Read article
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Characterization and Performance of a Multiphase Lignocellulosic-Polymeric Composite Growth Media in an IoT-Automated NFT Hydroponic System
Abstract: Hydroponics utilizing the Nutrient Film Technique (NFT) entails a type of soilless agriculture involving the delivery of a continuously flowing and thin film of nutrient-filled solution onto the roots of plants. With the move toward sustainable and efficient urban agriculture in the contemporary world and need to produce more effective and resource-efficient solutions, there have been significant efforts aimed at improving these techniques through advanced materials and automation. A consistent …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 542–555 Read article
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Mechanical and Thermal Performance of PETG Composites Reinforced with Short Carbon Fibers via Fused Filament Fabrication
Abstract: The study investigates the fabrication and characterization of polyethylene terephthalate glycol (PETG) composites reinforced with short carbon fibers (CF) using the fused filament fabrication (FFF) technique. Composite filaments with varying CF weight fractions (0, 5, 10, 15, and 20 wt%) were produced and evaluated for their mechanical, thermal, and morphological performance. The influence of CF reinforcement on tensile, flexural, and impact behavior was systematically examined, alongside thermal stability metrics including …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1219–1238 Read article
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Aerodynamic Analysis of Foliage Stimulated Airfoil Design for Enhanced Strength with Carbon Fibre-reinforced Polymer
Abstract: Ever since the beginning of aviation, there has been an unwavering desire to improve airfoil design in order to improve aircraft performance. This insatiable desire for improvement has driven innumerable aerodynamicists to create a diverse range of revolutionary airfoils. This research investigates a revolutionary method to airfoil design, inspired by the complicated structures and aerodynamic qualities of natural leaves. Using biomimicry, the project seeks to increase the performance and efficiency …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 560–616 Read article
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CNN-Based Wound Segmentation: A Review of Models and Performance Evaluation
Abstract: Deep learning, particularly convolutional neural networks (CNNs), has altered medical image processing by automating and precisely segmenting complex medical pictures. Wound segmentation, a critical application in automated wound assessment, is essential for wound size estimation, classification, and healing progress monitoring. This study presents a comprehensive review of CNN-based wound segmentation models, focusing on their architectures, methodologies, and performance on diverse datasets. Four deep learning models, including two U-Net variants (5-layer …
Published in Current Trends in Signal Processing · Vol. 15, Issue 1, 2025 · pp. 33–46 Read article
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A Lightweight Cost-Sensitive Explainable Ensemble Framework for Early Heart Disease Risk Prediction
Abstract: Cardiovascular disease is still one of the leading causes of death, and hence, the early prediction of risk is a very important task in preventive medicine. Although recent studies have shown encouraging results in the application of machine learning algorithms to the prediction of heart disease, it has been noticed that most of the algorithms are more concerned with accuracy-driven optimization than the concerns of safety and false negatives. In …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Fibre Orientation and Void Distribution Analysis in Polymer Composite Structures Using Image Processing
Abstract: Fibre orientation and void distribution are critical microstructural features that govern the mechanical performance and reliability of polymer composite materials. Accurate and simultaneous characterisation of these features remains challenging due to their complex spatial interactions and dependence on processing conditions. In this work, an integrated image-processing framework is proposed for the quantitative analysis of fiber orientation and void distribution in polymer composite structures. High-resolution composite microstructure images are processed through …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 925–933 Read article
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Heart Disease AI-based Prediction: A Comparative Analysis
Abstract: The present investigation looks at how well various machine learning algorithms predict cardiac disease. Since heart disease is one of the major causes of death worldwide, early detection and precise diagnosis are essential for managing and treating the condition. Our goal is to enhance diagnostic processes and improve patient outcomes by leveraging machine learning techniques. Six widely-used machine learning algorithms are evaluated in this research paper. These algorithms were selected …
Published in Trends in Mechanical Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 21–29 Read article
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Integrative Machine Learning Approaches for Predicting the Rheological Behaviour of Soft Magnetorheological Elastomers
Abstract: Magnetorheological Elastomers (MREs) are advanced composite materials known for their ability to alter mechanical properties under external magnetic fields, making them highly valuable in adaptive damping systems, vibration control, and smart devices. The accurate prediction of rheological behavior in soft MREs remains a significant challenge due to the complex interplay between material composition and magnetic fields. To address this challenge, this study employs a multi-pronged approach that integrates traditional material …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1083–1096 Read article
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Timestamp Extraction and Log Classification Using Supervised Machine Learning: A Comparative Study
Abstract: In modern software systems, logs are vital for monitoring application behavior, diagnosing issues, and analyzing performance. Timestamps are especially important for sequencing events, identifying anomalies, and understanding system failures. However, detecting timestamps in logs is challenging due to inconsistent formatting across systems and the presence of timestamp-like strings in non-timestamp fields. Traditional rule-based methods often fail in such cases. This study proposes a supervised machine learning approach to accurately classify …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 26–38 Read article
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Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article