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1089 articles for “data modelling”
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Performance Analysis And Battery Management System Optimization In Electric Vehicles
Abstract: The rapid electrification of the automotive industry has led to an increased need for battery management systems that are not only efficient and safe but also intelligent. BMS is the device that guarantees the best use of the battery, prolongs its life, and allows its safe operation even under different environmental and load conditions. Through the synthesis of literature and industry practices, this paper acts as a tribute to the …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 Read article
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Monoclonal Antibodies in Next Generation Animal Nutrition: Mapping Nutrient Immune Interaction Networks in Livestock Systems
Abstract: Sustainable livestock production is increasingly constrained by disease pressure, antimicrobial resistance, and declining feed efficiency under intensifying environmental stressors. Conventional nutritional strategies, while essential, remain insufficient to precisely regulate immune function and metabolic resilience. This review explores the emerging role of Monoclonal antibodies as advanced biologics in next generation animal nutrition, with a focus on mapping nutrient immune interaction networks in livestock systems. It synthesizes current knowledge on how nutrients …
Published in International Journal of Molecular Biotechnological Research · Vol. 4, Issue 1, 2026 Read article
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Integrated Surface Water–Groundwater Dynamics: Implications for Pollution Pathways, Prevention, and Environmental Control
Abstract: Water resources worldwide are increasingly threatened by pollution pressures amplified by climate change and intensified human activities. The vulnerability of surface water and groundwater systems to contamination is strongly governed by their dynamic hydrologic connectivity, which is often overlooked in pollution prevention and control frameworks. Rising global temperatures, altered precipitation regimes, land-use change, and intensified abstraction patterns modify recharge processes, flow paths, and contaminant transport mechanisms across environmental landscapes. This …
Published in International Journal of Pollution: Prevention & Control · Vol. 4, Issue 1, 2026 · pp. 34–40 Read article
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Recent Trends in Fluid Mechanics with Emphasis on Aeroacoustics and Flow-Induced Noise Control
Abstract: Fluid mechanics continues to evolve rapidly due to increasing demands in aerospace, automotive, energy, and environmental engineering applications. Recent trends in this field highlight significant advancements in both theoretical understanding and practical implementations, particularly in complex flow phenomena. Among these, aeroacoustics and flow-induced noise control have emerged as critical research areas due to their direct impact on system performance, efficiency, and environmental sustainability. Aeroacoustics deals with the generation, propagation, and …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 1, 2026 · pp. 32–38 Read article
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AI-Driven Framework for Accelerating Polymer Nanocomposite Commercialization in Computational Materials Engineering
Abstract: The remarkable mechanical strength increased functional qualities, lightweight structure, and thermal stability of polymer nanocomposites have prompted modern materials research to prioritize their rapid commercialization. Advanced materials can be created by adding nanoscale fillers such as carbon nanotubes, graphene, silica, and metal oxides to polymer matrices. These materials have applications in biomedical engineering, aerospace, electronics, packaging, and automobile manufacture. Research and development of polymer nanocomposites has traditionally relied on costly …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1–19 Read article
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Machine Learning in Nuclear Medical Applications: A Review of Research Frontiers
Abstract: Nuclear medicine, encompassing PET, SPECT, and targeted radionuclide therapy, generates high-dimensional, quantitative data uniquely suited for machine learning (ML) analysis. This review synthesizes current research applications of ML across six key domains. Positron emission tomography (PET), single-photon emission computed tomography (SPECT), and targeted radionuclide therapy are examples of nuclear medicine modalities that generate high- dimensional, quantitative datasets that are particularly well-suited for machine learning (ML)-driven analysis. These imaging methods provide …
Published in Journal of Nuclear Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 19–24 Read article
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Innovations in Mineral Science and Engineering for Sustainable Resource Development
Abstract: The growing global demand for mineral resources, coupled with increasing environmental and social concerns, has intensified the need for sustainable approaches in mineral science and engineering. Traditional mining and mineral processing practices, while essential for industrial development, are often associated with high energy consumption, resource depletion, and environmental degradation. In response, recent innovations in mineral science and engineering have focused on improving resource efficiency, minimizing environmental impact, and ensuring long-term …
Published in International Journal of Minerals · Vol. 3, Issue 1, 2026 · pp. 31–36 Read article
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Thermo-Fluid Characterization of Corrugated U-Tube Shell-and-Tube Heat Exchanger with Polymer Composite Tube Wall: A Combined CFD and Experimental Investigation
Abstract: Shell-and-tube heat exchangers built with metallic tubes work well thermally, but corrosion problems, extra weight, and the inability to adjust the wall’s thermal properties through material choice remain genuine engineering headaches, particularly for corrosive or weight-critical applications. Over the past few years there has been a fair amount of interest in replacing metal tubes with polymer composite alternatives, since blending thermally conductive fillers — graphite nanoplatelets, boron nitride platelets and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 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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AI-Based Outfit Rating and Suggestion System
Abstract: The increasing demand for personalised fashion advice in the digital era has highlighted the need for intelligent, automated styling solutions. The AI-Based Outfit Rating and Suggestion System is a web- based platform that assists users in evaluating and improving their clothing choices through intelligent image analysis. Unlike conventional fashion applications that merely identify garment categories or suggest purchases, this system performs a holistic assessment of complete outfits by analysing colour …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 2, 2026 Read article
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Multimodal Disease Detection Using Deep Learning
Abstract: Artificial Intelligence (AI) is playing an increasingly pivotal role in modern healthcare, particularly in improving the speed and accuracy of disease detection. With the evolution of Machine Learning (ML), Deep Learning (DL), and high-performance computing, AI-based solutions are now capable of processing extensive medical datasets, ranging from patient records to diagnostic images, with remarkable efficiency. These systems offer immense potential for early intervention, improved clinical decision-making, and alleviating pressure on …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 129–139 Read article
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A Machine Learning-Based Non-Invasive System for Blood Group Prediction Using Fingerprint Biometrics
Abstract: The research is targeted at the creation of innovative solution "Fingerprint Based Blood Group Prediction" for instant, non-invasive blood group determination from analysis of finger impressions, a breakthrough possibility in emergency health care. Sophisticated machine learning can be employed to map fingerprint patterns to corresponding blood group information and overcome the current lack of a direct connection between the two. Integration of various technologies: employed React for frontend development, Flask …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 9–18 Read article
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Hybrid Techniques in Mango Leaf Disease Identification: Evaluating Neural Networks and Support Vector Machines
Abstract: Mango leaf diseases pose a significant threat to mango production, impacting both yield and fruit quality. Early and accurate detection of these diseases is crucial for effective management. This paper evaluates the use of hybrid techniques, specifically the integration of neural networks (NNs) and support vector machines (SVM), in the identification and classification of mango leaf diseases. NN excel in extracting complex features from images, while SVMs are robust classifiers, …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 3, 2024 · pp. 19–27 Read article
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Unveiling Fairness: A Quest for Ethical Artificial Intelligence and Bias Mitigation
Abstract: Artificial intelligence (AI) systems have become ubiquitous across areas like finance, healthcare, employment, and criminal justice. However, they suffer from issues of unfair bias, lack of transparency, and broad ethical implications impacting vulnerable societal groups disproportionately. This paper reviews key challenges around AI ethics and bias while proposing data-driven guidelines mitigating such algorithmic harms through rigorous statistical testing, predictive modeling ensembles adjusting distortion vectors and AI audits by domain experts …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 2, 2023 · pp. 28–31 Read article
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Comparative Analysis of MCNN and RCNN for Speech Emotion Recognition Using Gender Information
Abstract: Speech emotion recognition is a speech processing task and a computer-based approach designed to identify and classify the emotions conveyed in audio signals. The aim of this system is to evaluate a speaker's emotional state, such as happiness, anger, sadness, or frustration, by analyzing their speech patterns, which include prosodic features like pitch, frequency, and rhythm. Speech emotion recognition is used in various real-life scenarios that include Customer Service, Healthcare, …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 1, 2025 · pp. 1–10 Read article
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Crop Disease Prediction Using Image Processing
Abstract: For any country in the world, its livelihood depends on agriculture. However, crop diseases affect the production and food supply of any country because we are unable to detect crop diseases. This paper presents a machine learning CNN (convolutional neural network) model, which uses images of crops to detect diseases. This model detects the diseases in the early stage and provides us with a solution to the crop diseases. It …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 9–16 Read article
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Polymer Composite-Supported Jackfruit Peel Adsorbent for Enhanced Copper (II) Removal from Wastewater: Batch Equilibrium and Isotherm Analysis
Abstract: The increasing concern of disposal of copper-containing effluents into the environment has led to heightened interest in designing cost-effective, eco-friendly and scalable adsorbent systems. Traditional metals and synthetically engineered sorbents prove to be effective; however, these systems are energy intensive. Agricultural residues entrapped in polymer composite systems constitute an economically feasible solution to this environmental challenge. This work reports on the design, characterization and performance evaluation of an economical adsorbent …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 375–390 Read article
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AI and ML in the Chemical Industry: A Review of Transformative Applications and Future Prospects
Abstract: The chemical industry, a key growth indicator of the global manufacturing ecosystem, is experiencing a digital transformation driven mainly by advancements in Artificial Intelligence (AI) and Machine Learning (ML) in this sector. These technologies are totally revolutionizing current and traditional methodologies by significantly improving process efficiency, reducing costs of manufacturing, accelerating R&D, and improving safety and sustainability standards. Proper utilization of Artificial intelligence (AI) and machine learning (ML) in chemical …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 1–6 Read article
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Advances in Biological Systems Modeling for Predicting Drug Effects in Chronic Disease
Abstract: Biological systems modeling has emerged as a promising tool for understanding and predicting the effects of drugs in the treatment of chronic diseases. Chronic diseases, such as diabetes, cardiovascular diseases, and neurodegenerative disorders pose significant challenges to traditional drug development due to their complex, multifactorial nature. Systems biology approaches, which integrate computational modeling with experimental data, provide a holistic view of disease mechanisms and treatment responses. This review explores recent …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 17–22 Read article
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Quantum Error Correction on Cryptography
Abstract: This article introduces novel concepts in quantum error correction and cryptography. It explores “approximate quantum error correction” (AQEC), which relaxes the requirement for perfect error correction in quantum systems. AQEC specializes in creating codes tailored to specific types of noise models. The study establishes a universal, near-optimal recovery map for AQEC, simplifying the identification of effective approximate codes. In the realm of noisy-storage cryptography, the research envisions secure two-party cryptographic …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 18–23 Read article