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567 articles for “model evaluation”
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Assessing the Robustness of Machine Learning Models for Wireless Intrusion Detection Under Adversarial Traffic Perturbations
Abstract: As the Internet of Things (IoT) devices and wireless communication networks continue to grow rapidly, protecting systems from cyber threats has become increasingly important. Machine learning–based intrusion detection systems (IDS) have shown strong potential in detecting abnormal and malicious network activities, yet their effectiveness and resilience when facing adversarial attacks are still not sufficiently explored. This research evaluates Machine Learning (ML) models–XGBoost, random forest, and multi-layer perceptron (MLP)—in detecting attacks …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 29–34 Read article
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Disease Prediction Using Ensemble Learning Models: A Comprehensive Approach
Abstract: In recent years, ensemble learning techniques have become pivotal in advancing predictive analytics within healthcare, particularly for early disease detection. The inherent variability and complexity of medical data, often characterized by high dimensionality, class imbalance, and noise, make it challenging for standalone classifiers to maintain high predictive accuracy. Ensemble learning, by integrating multiple models through bagging, boosting, or stacking, offers a more robust and generalizable approach. This study explores the …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 3, 2025 · pp. 26–33 Read article
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Polymer-Based Acousto-Optic Ultrasonic Sensor for Non-Destructive Evaluation of Dielectric Insulation
Abstract: A dual-polymer fiber-optic sensor for monitoring partial discharge (PD) activity in high-voltage polymeric insulation is presented in this work for non-destructive evaluation and dielectric testing applications. Dielectric weakness within polymeric insulation leads to partial discharge activity, generating ultrasonic acoustic waves that propagate through the medium. The developed sensing assembly comprises a conical polymer-based horn that gathers and concentrates the ultrasonic acoustic emission energy generated by dielectric weakness, and a single-mode …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 11–24 Read article
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Intelligent Planning of Transmission Networks: Addressing Uncertainties Through Artificial Intelligence
Abstract: Power grid planning is a critical aspect of power grid topology, traditionally relying on manual methods that are prone to various uncertainties. These uncertainties, both subjective (stemming from human judgment) and objective (resulting from data limitations), can significantly affect the reliability and efficiency of the planning process. This paper presents an artificial intelligence (AI) method aimed at improving the smart planning of transmission networks. By utilizing AI, the proposed method …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 40–46 Read article
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Role of Fatigue and Creep in Structural Damage: A Comprehensive Review
Abstract: Fatigue and creep are two critical degradation mechanisms that significantly influence the structural integrity and longevity of engineering materials. These phenomena arise due to different loading and environmental conditions but often coexist in various industrial applications, leading to severe material degradation over time. Fatigue primarily results from cyclic loading, where repeated stress variations induce microstructural damage and crack initiation, ultimately causing catastrophic failure. Conversely, creep occurs under sustained stress at …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 1, 2025 · pp. 22–26 Read article
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Exploring the Genetic and Environmental Factors Contributing to Ovarian Cancer in Women in Mumbai, India
Abstract: Background: Ovarian cancer incidence in Mumbai has risen by 30% over the past decade, with an age-standardized rate of 9.1 per 100,000 women, contrasting stable trends in Western nations. This study investigates the interplay of genetic and environmental factors driving this disparity in Mumbai’s diverse population. Methods: A hospital-based case-control study was conducted at a hospital, enrolling 200 epithelial ovarian cancer cases (aged 30–70 years) and 400 age-matched controls. Germline …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 3, 2025 · pp. 12–17 Read article
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Multi-Scale Analysis of Polymer Based Energy Storage Systems for High Performance Battery Applications
Abstract: The energy storage systems based on polymers are becoming promising materials for the next generation of high performance batteries because of their excellent mechanical flexibility, improved safety, and favorable electrochemical properties. Even with computational tools in Python, polymer-based energy storage systems remain plagued by poor ionic conductivity, complicated electrochemical reactions and potential thermal runaway. Therefore, a multi-scale model is proposed to improve battery performance, thermal stability, reliability, and large-scale deployment …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1035–1048 Read article
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Application of Grey Wolf Optimizer (GWO) strategy for Malware Analysis
Abstract: The ever-evolving landscape of cybersecurity necessitates continuous advancements in malware analysis techniques. This study explores the deployment of the Grey Wolf Optimizer (GWO) algorithm as a novel bio-inspired optimization mechanism to address the challenges posed by modern malware threats. The primary objective is to enhance various facets of malware analysis, including feature selection, parameter optimization, and the overall efficacy of malware detection models. The study begins by introducing the GWO …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 2, 2023 · pp. 43–53 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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Evaluating the Efficiency of LLMs-SA (Sentiment Analysis) via Social Media Texts
Abstract: Sentiment analysis (SA) is becoming popular in business and scientific communities as the processing of natural language (NLP), computational linguistics, text analytics, image-based processing or video- based processing is used in extracting and mining subjective information in the web, social network, etc. It is able to detect positive, negative or neutral information and can be selected to absorb polarity, sentiments, urgency and goals of mount importance. The majority of the …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 Read article
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Experimental Validation and Implementation Framework for Optimized Methane Yield Prediction in Anaerobic Digestion
Abstract: The correct validation and realistic application of optimized anaerobic digestion (AD) models are essential steps in transferring biogas production systems to real-life. This paper outlines an experimental validation and deployment pipeline of an AI-optimized model of the methane yield prediction model based on the application of more advanced machine learning and Bayesian optimization methods. Others The validated surrogate-assisted optimization model was tested with controlled laboratory-scale AD experiments at optimized operating …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 25–32 Read article
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An Empirical Study of Hyperparameter Impact on Deep Learning Models for Cardamom Leaf Disease Classification
Abstract: Recent advancements in deep learning models like convolutional neural networks and self- attention mechanisms have achieved great success in the field of plant disease classification. This study investigates the efficacy of two pre-trained models, ConvNeXT-Tiny and Swin Transformer-Tiny, for leaf disease classification in cardamom using a publicly available dataset constituting three categories of leaves, namely Healthy, Colletotrichum Blight and Phyllosticta Leaf Spot. The effectiveness of the models highly depends on …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 48–60 Read article
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Modal Analysis of RC Masonry Infill Model and Prototype Frames with Openings
Abstract: Modal evaluation is the technique of figuring out the inherent dynamic traits of the shape in phrases of herbal frequencies and mode shapes and the usage of them to create a mathematical version for its dynamic behavior. The dynamics of a structure is defined by frequency and position. Modal evaluation offers the records regarding to exceptional modes of vibration, exceptional form that may be taken up via way of means …
Published in Journal of Structural Engineering and Management Read article
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Plant Disease Detection Using Machine Learning
Abstract: Plant diseases significantly threaten global crop yields and affect both nutritional safety and farmer income. Accurate and early detection of plant diseases is essential for effective intervention and treatment. In this study, we used the CNN model (convolutional neural network) to explore a deep learning-based approach for plant disease classification. The model was trained and evaluated on a large dataset encompassing 38 different classes of plant disease, including healthy leaves. …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 2, 2025 · pp. 07–19 Read article
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Modelling of The Viscoelastic Composite Curved Panel for The Time Domain Analysis Using TTBDF, β1 / β2−Bathe and Newmark Method
Abstract: Viscoelastic materials are extensively used in structures, especially thin-walled structures, for damping. The accurate modelling of the time domain dynamics of the viscoelastic material is essential for appropriately capturing the damping of the viscoelastic material. Various implicit and explicit time integration schemes are available to evaluate time domain response. However, the rightness of the implementation of the time integration scheme to the viscoelastic material model is very essential. In this …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 204–222 Read article
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Prediction of Depth-Induced Stress Distribution and Maintenance Cost Implications for Submerged Structural Components
Abstract: This study investigates the influence of water depth on stress distribution and structural integrity of submerged mechanical components . Structural models fabricated from mild steel, stainless steel, carbon steel, and copper alloy were examined under hydrostatic loading corresponding to water depths between 30 cm and 150 cm. Results indicate that normal and shear stresses increased proportionally with depth due to intensified hydrostatic pressure. Mild steel exhibited the highest stress concentrations, …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 2, 2025 · pp. 29–35 Read article
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Assessment of Water Quality and Quantity Trends at Reuse Locations within the Bahr El- Baqar Drainage Catchment under Water Stress Reduction Scenarios
Abstract: Many countries face the pressing challenge of water scarcity, affecting around 20% of the global population in areas with water shortages. Egypt, one of the most populous countries in Africa and the Middle East, is severely impacted by this issue. To address this, Egypt is focusing on developing alternative water resources, including the reuse of agricultural drainage water for irrigation. In this study, the SIWARE model was employed to evaluate …
Published in Journal of Water Resource Engineering and Management · Vol. 12, Issue 3, 2025 · pp. 1–11 Read article
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Tailoring the Compressive Behavior of Tetra-Chiral Auxetic Structures through FDM Process Parameters
Abstract: This research evaluates how fused deposition modeling (FDM) fabrication process parameters affect the compressive behavior of tetra-chiral auxetic structures created from Polylactic Acid (PLA). Auxetic materials have a number of useful properties, including reversible deformation and high-energy absorbing capabilities, which are beneficial to creating ultra-lightweight structural, protective, and shock-resistance designs. Among the available auxetic topologies, the tetra-chiral configuration is particularly attractive for engineering use, because its rotation-dominated node–ligament deformation gives …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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DFT/Data Guided Predictive Modelling of Absorption Maxima in the OLED Rubrene Derivatives
Abstract: This study investigates the optical properties of rubrene derivatives to develop an accurate predictive model for absorption maxima using computational chemistry and chemoinformatic techniques. We benchmarked various quantum chemical methods, identifying that the M06-2X/aug-cc-pVDZ method in dichloromethane (DCM) provided the strongest correlation with experimental data. Key molecular descriptors such as band gap, ionization potential, and electrophilicity index were calculated and analyzed using principal component analysis (PCA) to identify significant factors …
Published in International Journal of Cheminformatics · Vol. 4, Issue 1, 2026 · pp. 41–56 Read article
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MentaLLaMA: Advancing Mental Health Insights with Instruction-Finetuned Large Language Models
Abstract: The growing prevalence of mental health challenges in contemporary society has highlighted the urgent need for advanced, interpretable, and reliable artificial intelligence solutions that can support mental health assessment and intervention. In response to this need, this research introduces a novel collection of open-source, instruction-tuned large language models (LLMs) specifically designed to facilitate transparent and accurate mental health evaluations. Leveraging a newly developed dataset, which integrates multiple tasks and diverse …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 08–15 Read article