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821 articles for “process modelling”
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Integrating Atmospheric Science: Understanding Greenhouse Gases, Aerosols, and Air Quality Dynamics
Abstract: Atmospheric science investigates the Earth’s atmospheric systems to understand their composition, dynamics, and the implications for climate, weather, and air quality. This review explores five primary areas within the field: atmospheric composition, atmospheric modeling, remote sensing, air pollution, and boundary layer dynamics, highlighting critical challenges and advancements. Rising levels of greenhouse gases (GHGs), including carbon dioxide and methane, continue to drive global warming, while feedback mechanisms—like cloud interactions and surface …
Published in International Journal of Atmosphere · Vol. 1, Issue 1, 2024 · pp. 32–35 Read article
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Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 Read article
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The Convergence of AI and Composites - A Review Anchored in Patent Trends
Abstract: The integration of artificial intelligence (AI) and machine learning (ML) techniques is revolutionizing the design, analysis, and optimization of polymer (PC/FRP), metal (MC), and ceramic matrix composites (CC). Techniques such as artificial neural networks (ANN), deep learning (DL), genetic algorithms (GA), and physics-informed machine learning (PIML) are employed to enhance property estimation, process optimization, and predictive modeling. These AI-driven frameworks enable virtual testing, application-specific material design, and real-time decision-making, while …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 182–198 Read article
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Nitrosamine Accumulation, Processing Variables, and Indigenous Plant Inhibitors in Nigerian Traditionally Processed Meats
Abstract: N-nitrosamines are classified as probable or possible human carcinogens by the International Agency for Research on Cancer. Carcinogenic N-nitrosamines — principally N-nitrosodimethylamine (NDMA) and N-nitrosodiethylamine (NDEA) — are formed in abundance during the preparation of widely consumed Nigerian traditional processed meats including suya, kilishi, and balangu. This original investigation combined a six geopolitical zone of Nigerian market survey with laboratory-controlled model system experiments, effects of processing parameters on N-Nitrosamine formation …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 17, Issue 1, 2026 · pp. 61–72 Read article
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Automated Car License Plate Detection and Recognition Using Deep Learning
Abstract: The use of automated license plate detection and recognition (ALPR) systems to automate processes such as number plate detection is gaining popularity in traffic control, security, and law enforcement. This research focuses on achieving more accurate and efficient detection and recognition of number plates by leveraging deep learning techniques. The systems outlined in this study aim to improve the effectiveness of ALPR systems using advanced convolutional neural networks (CNNs) and …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 23–29 Read article
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Open Educational Resources and Open Access Publishing in Higher Education: Policies, Challenges, and Collaborative Models
Abstract: Open Educational Resources (OER) and Open Access (OA) publishing are transforming higher education by promoting equitable access to knowledge, reducing costs, and fostering collaborative innovation. While OER focus on openly licensed teaching and learning materials, OA ensures unrestricted online access to scholarly research. Together, they form an integrated open knowledge ecosystem aligned with global policy frameworks such as the UNESCO OER Recommendation (2019) and the Budapest Open Access Initiative. This …
Published in International Journal of Trends in Humanities · Vol. 3, Issue 1, 2026 · pp. 7–12 Read article
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Digital Frontiers in Life Sciences: The Transformative Role of Computing in Modern Biology
Abstract: The integration of computers in the biological sciences has revolutionized research and experimentation, facilitating advancements in areas such as genomics, bioinformatics, systems biology, and ecological modeling. The ability to process vast amounts of biological data efficiently has transformed how scientists study complex biological systems and phenomena. Computational tools enable the analysis of DNA sequences, protein structures, metabolic pathways, and ecological dynamics, which were previously beyond the reach of traditional laboratory …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 Read article
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Enhancement of Flexural Strength in FDM-Printed Components through Taguchi-Based Process Parameter Optimization
Abstract: Additive manufacturing (AM), especially Fused Deposition Modeling (FDM), has emerged as a widely adopted and versatile method for producing three-dimensional components. The process involves the deposition of a thermoplastic filament in a semi-molten state, which solidifies in successive layers to form the final structure. While this method enables the production of complex geometries at relatively low cost, the printed parts often exhibit inferior surface quality and reduced mechanical performance compared …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 272–280 Read article
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An Analysis of Machining Parameters for Metal Matrix Composite
Abstract: The electro-discharge machining analysis of hybrid Composite is presented in this work. Variables are chosen for the input process parameters. The material removal rate is acknowledged as an output parameter, together with the current, graphite and silicon carbide percentage and pulse on time. We used the Taguchi Method to conduct our experiments. To create the theoretical model and look into how process parameters affect the rate at which material is …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 76–85 Read article
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Enhancing Robot Autonomy: Integrating AI for Advanced Decision-making in Autonomous Robotic Systems
Abstract: The capabilities of autonomous robotic systems have been drastically changed by the rapid progress in artificial intelligence (AI) technologies. In this work, we investigate the integration of AI approaches to improve robot autonomy by presenting even more advanced mechanisms for decision-making. Almost all traditional robotic systems involve predefined algorithms, making them unable to cope with dynamic environments. They can also help with learning based on machine learning and deep learning …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 3, 2024 · pp. 28–37 Read article
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Strategic Integration of Machine Learning in Polymer Composite Development: A Framework for R&D Portfolio Management and Technological Adoption
Abstract: The progress of advanced polymer composites is slow, costly and unpredictable due to traditional methods of trial-and-error research. As materials informatics and data-driven modeling speed up the process of discovering technology, there exists a huge disconnect between computational predictions on one hand and strategic decision-making on the other in research and development (R&D). To solve this issue, this paper presents the Agile Materials-Intelligence (AMI) Framework, a systematic combined methodology that …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1272–2286 Read article
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3D Printing of Polymer-Based Functionally Graded Materials: Recent Developments and Challenges
Abstract: Additive manufacturing (AM), specifically 3D printing, has become a useful technique for fabricating functionally graded materials (FGMs) because it can facilitate the spatial distribution of materials. Polymer FGMs (P-FGMs) have gained a great deal of interest due to their lightweight, customizable, multifunctional properties. In comparison to conventional fabrication, 3D printing allows better control of composition and microstructure, which results in materials with controlled mechanical, thermal, and biological properties. This review …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 338–347 Read article
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Exploring the Influence of Machining Parameters on Geometric Form and Orientation Controls (23 Design)
Abstract: This work explores the influence of machining parameters using on geometric form controls flatness and straightness as well as orientation control parallelism using an aluminum 6061 workpiece. Due to its good strength, machinability and cost- effectiveness, aluminum 6061 is widely used. In this experimental work, full factorial design is used and each factor has two levels. The response parameters chosen include flatness, straightness, and parallelism, which govern the form and …
Published in Journal of Experimental & Applied Mechanics · Vol. 16, Issue 1, 2025 · pp. 10–16 Read article
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Kinematic Relations of Particle Motion using Polar Cylindrical Coordinates System: Applications in Robotics and AI
Abstract: This paper explores the motion of a particle in space using the cylindrical polar coordinate system. It presents the physics of particle motion by defining spatial positions in three-dimensional polar coordinates and examining the particle’s kinematics—namely its position, velocity, and acceleration—in vector form. These quantities are mathematically expressed as functions of time, accounting for the changing coordinates in radial, angular, and vertical directions. This coordinate system proves especially useful for …
Published in Research & Reviews : Journal of Physics · Vol. 14, Issue 1, 2025 · pp. 12–16 Read article
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A Conceptual Framework for AI-Integrated Metabolomics in Predictive Health Systems for Resource-Constrained Environments
Abstract: The increasing prevalence of non-communicable diseases (NCDs) continues to place a significant strain on healthcare systems, particularly in low- and middle-income regions where access to early diagnostic infrastructure is limited. Conventional healthcare approaches remain largely reactive, often detecting diseases at advanced stages when treatment effectiveness is reduced. This challenge underscores the need for predictive, cost-effective, and data-driven healthcare solutions. This study presents a conceptual framework that integrates metabolomics with artificial …
Published in Emerging Trends in Metabolites · Vol. 3, Issue 2, 2026 Read article
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A study on Bridging Chemical Transformation and Climate Feedbacks in the Earth System
Abstract: The atmosphere operates as a vast and complex chemical reactor, where minute-scale transformations exert profound influence on planetary-scale climate stability. This research investigates the multi-scale coupling between reactive tropospheric chemistry and large-scale climate feedbacks, challenging traditional modeling approaches that often divorce chemical kinetics from dynamic processes. By integrating high-resolution chemical transport models (CTMs) with comprehensive Earth System Models (ESMs), we map the flow of energy and matter from the molecular …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 1–8 Read article
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Cardiovascular Modeling with Computational and Mathematical Methods
Abstract: The cardiovascular system, a complex network responsible for delivering life-sustaining oxygen and nutrients throughout the body, is a prime target for advanced understanding and improved therapies. Due to the inherent difficulties in directly observing internal physiological processes and the complexities of interactions within the system, computational and mathematical modeling have emerged as powerful tools in cardiovascular research. This article explores the significance of these methods in unveiling the heart's secrets …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 2, 2025 · pp. 11–21 Read article
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Optimization of FDM 3D Printer Process Parameters For PETG Material Using TOPSIS Technique
Abstract: 3D printing is a quickly evolving process that builds the desired shape by layering on material. In the era of modern production, additive manufacturing has grown in significance due to its user-friendliness. By using this technique, one can produce complex & intricate geometries with much ease when compared to conventional manufacturing. With the increased demand for 3D printing, consideration towards strength quality and other mechanical properties is also increasing progressively. …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 601–609 Read article
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Evaluation of AGO Adsorption Rate Isotherms Using Adsorbent Formulation of Plantain Agbagba1 and Clay of Different Mix Ratio in Pollutant Remediation in Salt Water
Abstract: The application of some agro-based materials in combination with day soil, for the production of adsorbents were investigated in relationship to their performance in AGO (Diesel) treatment in a batch process unit. The research allows the model concept of Langmuir isotherm, Frundlich isotherm and Temkin Isotherm for the determination of the adsorption rate of the various isotherms with respect to the effect of the particle size and the mixed ratios …
Published in International Journal of Pollution: Prevention & Control · Vol. 2, Issue 2, 2024 · pp. 31–42 Read article
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Implement Explainable Machine Learning to Improve Conductivity in Polymer-CNT Nanocomposites: Supporting Adaptive, Flexible, and Long-Lasting IoT Wrap-Around Electronics Applications
Abstract: The rapid growth of Internet of Things (IoT) technologies requires electronic components that are adaptable, lightweight, and durable, and that can continue to function well in diverse contexts and circumstances. Polymer–carbon nanotube (CNT) nanocomposites have become interesting choices for these kinds of uses because they are more flexible, conduct electricity better, and can be made to fit specific needs. However, improving conductivity in these heterogeneous systems remains a major challenge …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 238–254 Read article