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79 articles for “assessment metrics”
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Balancing Welfare-Productivity Trade-Offs: Logical Frameworks and Strategic Approaches for Sustainable Dairy Development
Abstract: Balancing animal welfare and productivity remains a critical challenge in modern dairy farming. This study explores diverse frameworks for evaluating the welfare-productivity trade-offs essential for achieving sustainable dairy systems. Key approaches are categorized into six thematic areas: animal-centric frameworks, management-oriented models, environmental assessments, economic and policy perspectives, technological innovations, and holistic methodologies. Each framework offers unique metrics and evaluation tools, including behavioral assessments, physiological indicators, precision livestock farming, cost-benefit analyses, …
Published in Research and Reviews : Journal of Veterinary Science and Technology · Vol. 14, Issue 2, 2025 · pp. 16–24 Read article
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Evaluating the Performance of Test Cricket Players Using Principal Component Analysis and the Weighted Average Method
Abstract: This study evaluates cricket player performance using Principal Component Analysis (PCA) and a weighted average approach. In order to achieve this, we analyzed detailed batting and bowling datasets from the International Cricket Council (ICC) to calculate player performance based on various performance indicators. The datasets included comprehensive statistics from multiple matches and tournaments, allowing for an in-depth evaluation of players’ skills and contributions. PCA ranked players according to their participation …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 20–30 Read article
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A Machine Learning Approach to Forecasting Outcomes in Limited Overs Cricket
Abstract: This study explores the application of machine learning techniques to forecasting outcomes in limited overs cricket matches, with a particular focus on One Day Internationals (ODIs). The research investigates how classification algorithms can be effectively utilized to analyze both contextual and dynamic factors that influence match results, including venue details, toss decisions, team strength, and historical performance records. By employing a structured methodology encompassing feature selection, data preprocessing, model training, …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 09–19 Read article
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Enhancement in Biomedical Polymer Nanocomposites: Biocompatibility and Mechanical Property Predictions using Machine Learning
Abstract: A machine learning (ML)-based framework is developed and validated through experimental analysis and comparative modeling to enhance system dependability and improve prediction performance. The proposed framework includes key stages such as data preprocessing, feature evaluation, model training, and performance benchmarking to determine the most effective prediction technique. Several machine learning models were evaluated, including Ensemble models, Artificial Neural Networks (ANN), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 275–296 Read article
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Evaluating Pain and Quality of Life Improvement in Endometriosis: A Prospective Interventional Study
Abstract: Background: World-wide about 10% of reproductive-age women affects with endometriosis, drastically reducing their quality of life. This study assessed the effectiveness of a combination medicinal and lifestyle intervention approach in controlling endometriosis-related pain and enhancing quality of life. Methods: A prospective interventional study was conducted with 350 women diagnosed with endometriosis between August 2022 to September 2024. Participants received a structured intervention combining hormonal therapy, pain management, and lifestyle modifications. …
Published in Research and Reviews: A Journal of Medicine · Vol. 15, Issue 1, 2025 · pp. 38–45 Read article
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Nano‑Enabled CT for Cancer Imaging: From Molecular Targeting to Image‑Guided Therapy
Abstract: Nano‑enabled computed tomography (CT) exploits high‑atomic‑number (high‑Z) nanomaterials engineered with targeting ligands and therapeutic payloads to enhance contrast, enable molecular imaging, and support image‑guided interventions in oncology. Tumor‑specific nanoprobes such as RGD‑modified gold nanorods, polymer‑coated bismuth nanoparticles, and peptide, antibody, or aptamer‑functionalized platforms can intensify tumor conspicuity, allow early lesion detection and staging, and provide real‑time treatment monitoring. Integration of CT visibility with photothermal, photodynamic, chemo‑, radio‑, and immunotherapeutic functions …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 1, 2025 · pp. 40–49 Read article
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Predictive Maintenance in Semiconductor Systems: Insights from Machine Intelligence and Data-Driven Methods
Abstract: With the fast-paced development of semiconductor technology comes the need to focus on device reliability, or how long devices will function and the likelihood of devices having operational issues. Predicting failures and avoiding downtime with the implementation of timely, actionable, and data-driven maintenance strategies are essential to insure devices function sustainably within predetermined performance levels. The implementation of predictive maintenance within artificial intelligence and machine learning technologies will provide the …
Published in Journal of Semiconductor Devices and Circuits · Vol. 13, Issue 1, 2026 Read article
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Hybrid Approach for Community Detection Using Deep Learning Techniques
Abstract: Community detection in complex networks is a fundamental problem with applications across diverse domains, ranging from social networks to biological systems and beyond. Traditional methods based on graph theory have been widely used for identifying communities within networks. However, the intricate and evolving nature of modern networks demands more sophisticated approaches. This research work proposes a hybrid approach that combines the strengths of deep learning techniques with traditional community detection …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 3, 2024 · pp. 18–26 Read article
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Automated Intelligence, Machine Learning, and Big Data in Education: A Practical Framework, Synthetic Demonstration, and Deployment Guidance
Abstract: Artificial intelligence (AI), machine learning (ML), and big-data methods are increasingly used to improve educational decision making through personalization, early-warning systems, scalable feedback, and operational analytics. This manuscript proposes a practical end-to-end framework for educational AI/ML projects, covering problem definition, data engineering, modeling, evaluation, intervention design, and responsible governance. To provide a complete and reproducible template without exposing sensitive student data, we present a synthetic demonstration study that mirrors typical …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
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AI-Enabled Recycling of Thermoplastic Polymer Waste in Hospitals: A Circular Economy Pathway Toward Green Hospital Certification
Abstract: This review research explores the latest role of AI in improving thermoplastic waste management for hospitals in terms of segregation accuracy, operational efficiency, and circular economy outcomes. Seventy-five relevant studies were analysed, and it was reported that AI-based systems, especially CNNs, YOLO models, and sensor-fusion approaches, achieved high accuracy in the identification and sorting of medical plastics, often above 90%. Early evidence also reveals improvements in the reduction of contaminants, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 170–182 Read article
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Institutional Engagement with Indigenous Knowledge: A Global Scientometric Analysis
Abstract: This study provides a comprehensive global scientometric analysis of institutional engagement with Indigenous Knowledge (IK) research from 1992 to 2025. It seeks to chart the transition from traditional preservation to contemporary digital curation and identify key geopolitical and disciplinary shifts. A corpus of 304 peer-reviewed publications was retrieved from Scopus. The study utilized science mapping via VOSviewer and performance metrics through the R-package Bibliometrix to assess longitudinal changes and thematic …
Published in Journal of Advancements in Library Sciences · Vol. 13, Issue 2, 2026 · pp. 55–69 Read article
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Enhancing Sustainability in Building Design: Optimizing Energy Efficiency and Reducing Carbon Footprint Using BIM Tools and Polymer Matrix Composites
Abstract: Sustainable construction is an imperative that transcends the immediate and future horizons of the construction industry, propelled by the escalating recognition of the sector's ecological impact. Building Information Modelling (BIM) has firmly established itself as a pivotal instrument within the industry due to its unique capacity to seamlessly merge the physical and analytical dimensions of construction, thereby ushering in transformative practices. This research paper offers an all-encompassing exploration of the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 181–189 Read article
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Enhancing MRO Documentation Through Automated Translation of Non-Standard English to Simplified Technical English Using Offline LLMS
Abstract: Maintenance, Repair, and Overhaul (MRO) operations rely heavily on accurate and consistent documentation to ensure operational safety and compliance. However, the presence of non-standard English in technical documents often leads to ambiguity, misinterpretation, and inefficiencies in maintenance processes. This study presents an innovative solution that leverages an offline Large Language Model (LLM) to automatically translate non-standard English in MRO documents into standardized and technically precise language. By integrating predefined linguistic …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 9–15 Read article
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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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Structure–Property Modeling of Cement-Based Multi-Component Composites Using Ensemble Machine Learning and Explainable Feature Attribution
Abstract: Accurate prediction of compressive strength is central to structure–property optimization, quality control, and sustainability-driven design in cement-based composite materials. Cementitious systems represent heterogeneous multi-phase composites composed of reactive binder matrices and dispersed aggregate phases, whose macroscopic mechanical performance emerges from complex nonlinear interactions among constituents and curing-dependent microstructural evolution. This study develops a data-driven structure–property modeling framework to quantify the nonlinear dependence of compressive strength on multi-component composite composition and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 112–131 Read article
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House Price Estimation Using Linear Regression: A Machine Learning Perspective
Abstract: House price prediction plays a crucial role in the real estate industry, helping buyers, sellers, and investors make well-informed decisions. Accurate estimation of property values enables stakeholders to assess market trends, plan investments, and minimize financial risks. This study focuses on the application of linear regression, a fundamental and widely used machine learning algorithm, to predict house prices based on multiple influencing factors. These factors include location, property size, number …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 Read article
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Identification and Evaluation of Safety Factors in Construction Industry Using Fuzzy Reasoning Technique
Abstract: Modern construction projects, characterized by their complexity and uniqueness, are inherently susceptible to various risks. These risks represent uncertain events that may arise during the project's life cycle, potentially influencing its objectives either positively or negatively. Positive risks are referred to as opportunities, while negative risks are identified as threats. To effectively harness these opportunities and mitigate threats, the implementation of Risk Management is essential. A novel theoretical framework known …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 3, 2025 · pp. 7–12 Read article
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Application of Resource Allocation Similarity Based Link Prediction in Wireless Networks
Abstract: Link prediction in wireless networks plays a crucial role in predicting missing connections within multiplex networks. This study focuses on the utilization of similarity-based link prediction methods in wireless networks. These methods assume that the likelihood of linkage between nodes is determined by their similarity, based on shared features. Several similarity measures, such as Common Neighbors (CN), Preferential Attachment (PA), Adamic-Adar (AA), and Resource Allocation (RA) indices, are commonly employed …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 2, 2023 · pp. 37–42 Read article
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A Comparative Analysis of Safety Performance in Commercial and Residential Construction: Unraveling Critical Insights
Abstract: The comparative examination of safety performance in the domains of commercial and residential construction is an all-encompassing investigation that imparts valuable understandings into the distinct challenges and considerations within these two sectors. The research places emphasis on the significance of tailoring safety protocols to address the specific requisites of each domain, considering factors such as project magnitude, intricacy, and inherent characteristics. The study delves into safety climates by scrutinizing individuals, …
Published in Journal of Control & Instrumentation · Vol. 15, Issue 1, 2024 · pp. 1–10 Read article
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Sustainable Cotton Crop Productivity through Precision Weed Detection: A Deep Learning-Based Approach with UAV Integration
Abstract: Weeds present a major challenge to crop productivity by competing with crops for vital resources, including water, sunlight, and nutrients, often resulting in significant yield reductions. On a global scale, weeds are responsible for approximately 13.2% of annual crop losses, a quantity sufficient to feed nearly one billion people. These invasive plants disrupt agricultural systems and adversely impact crop yields. Given their uneven distribution in fields, ground or aerial robots …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 19–26 Read article