Search
435 articles for “sub-modeling”
-
AI-Driven Optimization of Biopolymer Composite Formulations Using IoT Data Streams
Abstract: Biodegradable polymer composites have emerged as a sustainable alternative to petroleum-based materials in packaging, biomedical, and structural applications. However, traditional formulation techniques for reinforced polymer composites often lack precision and fail to adapt to real-time variations during processing, resulting in suboptimal material performance. This research proposes a real-time AI-IoT-enabled framework to optimize biopolymer composite formulations. The goal is to intelligently tune composite properties such as mechanical strength, moisture resistance, and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 85–100 Read article
-
Signal Feature Extraction and Machine Learning Techniques for Human Activity Recognition
Abstract: Human Activity Recognition (HAR) has emerged as a critical field of study with diverse applications in healthcare, fitness tracking, smart homes, and human-computer interaction. The aim of this research is to create an efficient HAR system through advanced techniques characterized by signal feature extraction and machine learning algorithms. The MEMS sensors are used appropriately during data mining to extract time-domain, frequency-domain, and statistical features, which are subsequently passed to the …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 1, 2025 · pp. 24–41 Read article
-
Phygital: An Innovative Model for Developing Receptive Skills in English Through Learner Autonomy
Abstract: The study named “Phygital: An Innovative Model for Developing Receptive Skills in English through Learner Autonomy” tries to establish that it is an innovative scientific model, evidently distinguished from other prototypes such as blended learning, e-learning, flip learning, online learning, hybrid learning etc. The paper also tries to emphasize that it is best suited for the new age learners and that it enhances the receptive skills (listening and reading) in …
Published in Emerging Trends in Languages · Vol. 2, Issue 2, 2025 · pp. 1–9 Read article
-
Traffic Detection Algorithms Analysis using ML
Abstract: It is difficult to watch traffic on crowded roads. Traffic monitoring procedures are time-consuming, expensive, labor-intensive, and require human operators. The limited accessibility hindered the storing and processing of large-scale video streams. Nonetheless, it is now possible to employe video feeds from traffic monitoring systems for number plate recognition, object tracking, traffic behavior analysis, and surveillance. Static image recognition and vehicle identification in a traffic surveillance system are very useful …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
-
Advanced Anomaly Detection in Cloud Infrastructures Using Deep Learning Algorithms
Abstract: It is critical to guarantee the stability and security of cloud environments as cloud computing is becoming the backbone of contemporary IT infrastructures. Neglecting to quickly identify and resolve anomalies, which might point to security breaches, performance problems, or system breakdowns, can lead to disastrous outcomes. The increasing size and complexity of cloud infrastructures are challenging the effectiveness of traditional anomaly detection methods. These approaches often depend on rule-based systems …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 1–11 Read article
-
Optimizing Sampling Techniques Using Fuzzy Set Theory: A Comprehensive Approach
Abstract: Sampling is a critical process in statistics, used to estimate population parameters without needing to examine the entire population. Traditional sampling methods, such as simple random sampling, stratified sampling, and cluster sampling, face limitations when applied to complex or heterogeneous populations with imprecise boundaries. These methods often fail to accurately represent populations with overlapping characteristics or missing data, resulting in sampling bias and reduced accuracy. To address these challenges, this …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 29–43 Read article
-
Continuous Commissioning Techniques for Ground Source Heat Pumps: Review
Abstract: This study offers a model-based continuous commissioning methodology to find control-related performance gaps in HVAC systems with ground-source heat pumps. Traditional continuous commissioning is still helpful in finding energy performance gaps, even if MBCCx employs a system model as a reference to find operational inefficiencies and control issues arising from subsystem integration. A calibrated physics-based model that depicts the system performance as intended during the design phase forms the basis …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 12, Issue 3, 2025 · pp. 22–36 Read article
-
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
-
Role of Artificial Intelligence in Structural Health Monitoring-A Brief Evaluation
Abstract: Artificial intelligence (AI) refers to the capacity of a machine or a computer to ‘think’ or reason in the way a human would, utilizing experience, learned facts, and flexible rules to solve problems that may not fit the standard outlines for a normal algorithm. From this follows the utilization of AI in various sectors, such as the information technology (IT) industry, media, healthcare and medicine, logistics, environmental sustainability, finance, business, …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 1, 2026 · pp. 34–39 Read article
-
Integrative Structural-Functional Genomics of Fc and Fab: Precision Models for Monoclonal Antibody Stability and Anti-Aggregation Engineering
Abstract: Monoclonal antibodies (mAbs) represent the cornerstone of biotherapeutics, yet aggregation propensity compromises up to 50% of candidates during development, driven by Fab hypervariability and Fc vulnerabilities.(1,2) This review integrates functional genomics from OAS (4B+ sequences)(5) and structural databases (SAbDab: 10K+ structures)(6) with machine learning models achieving R=0.97 for SAP prediction.(11) We dissect biophysical mechanisms, benchmark predictive tools (DeepSP, ESM2), and engineering strategies (YTE, FW mutations) that enhance Tm by 5-10°C …
Published in International Journal of Molecular Biotechnological Research · Vol. 4, Issue 1, 2026 Read article
-
Fracture Analysis of Functionally Graded Material (FGM) Plates Using Extended Finite Element Method: A Review.
Abstract: Functionally Graded Materials (FGMs), have drawn a lot of interest in various engineering applications due to their superior mechanical properties and ability to withstand extreme conditions. Fracture analysis in FGMs focuses on understanding how cracks initiate and propagate within these complex materials. The stress distribution becomes irregular due to spatial property variations which produces different crack paths than what occurs in homogeneous materials. The examination of FGM plates under fracture …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 4, Issue 1, 2026 · pp. 9–15 Read article
-
Time Series Methods in Meteorology: A Review of Predictive Models and Applications
Abstract: The accurate prediction of time series data holds substantial significance in various fields, enabling informed decision-making and resource optimization. In this study, temperature variations over time are predicted using the Autoregressive Integrated Moving Average (ARIMA) model. Reliable temperature projections are more important now than ever because of climate change and its effects. For time series prediction problems, the ARIMA model—which is well-known for its ability to capture temporal dependencies in …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 2, 2024 · pp. 35–46 Read article
-
Fracture Analysis of FRP Composites under Thermo-Mechanical Loads for Different Geometry Cutouts
Abstract: Fiber-reinforced composites (FRPs) are used extensively in structural and non-structural components of the aerospace and automotive industries. To utilize these materials for structural applications, it is necessary to understand the fracture behavior of the material. In the present investigation of carbon fiber laminates, studies were carried out to understand the fracture toughness characteristics of the carbon fiber laminates with mechanical, thermal, and thermo-mechanical loadings of modes I, II, and III. …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 2, 2025 · pp. 1–10 Read article
-
Therapeutic Potential of Plant-Derived Phytochemicals in Targeting Receptor Pathways Related to Non-Enzymatic Glycation: A Meta-Analysis
Abstract: Background: Non-enzymatic glycation, where reducing sugars react with proteins, lipids, and nucleic acids, contributes to various pathological conditions, such as diabetic complications and cardiovascular diseases. This process is facilitated by the receptor for advanced glycation end-products (RAGE), which is pivotal in driving inflammation and causing tissue damage. Objective: This meta-analysis evaluates the effects of plant-derived phytochemicals on RAGE expression and associated signaling pathways, assessing their therapeutic potential in glycation-related diseases. …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 3, Issue 1, 2025 · pp. 60–73 Read article
-
Transfer Learning in Deep Learning Models for Medical Imaging: Utilizing Pretrained Models to Improve Performance in Medical Image Analysis
Abstract: Transfer learning is now a trending technique in deep learning, especially in medical imaging. This technique solves landmark problems by utilizing the pre-trained models, including the limited availability of the annotated medical data and the time-consuming computational costs of training deep learning models from scratch. The generalizability of deep models could increase diagnostic precision for specific medical tasks, require fewer samples to train, and take less time to train due …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 67–85 Read article
-
Application of Artificial Neural Networks in Optimizing Polyhouse Roof Truss Design
Abstract: Polyhouses are specialised agricultural structures developed to maintain controlled environmental conditions for crop cultivation, thereby ensuring consistent productivity even under adverse climatic circumstances. The performance of these systems largely relies on the structural stability and cost efficiency of the roof truss, which must achieve an effective balance between strength, adaptability, and economy. In this research, an Artificial Neural Network (ANN)-based modelling framework is introduced to optimise the members of polyhouse …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 15–25 Read article
-
Enhancing Profanity Detection in Dravidian Languages: Leveraging Language Models for Optimization and Improvement
Abstract: Detecting and documenting instances of abusive behaviour can significantly improve the quality of virtual environments. Given the vast amount of content published daily on social media, it is impractical for human annotators to manually identify potentially harmful content. Recent algorithmic initiatives, especially on platforms like Twitter, have advanced in abuse detection. However, for Dravidian texts, there remains a need to understand the context better and build robust language models for …
Published in Recent Trends in Programming languages · Vol. 11, Issue 2, 2024 · pp. 17–23 Read article
-
Modeling of ZnO Based Nano Sensor Device for Evaluating Electronic Interaction with NO2 Pollutant: Combining Multiphysics Simulation and DFT Study
Abstract: This study focuses on the designing and modeling of a sensor device employing zinc oxide (ZnO) nanowires (NWs), and the evaluation of the chemical response of the same in the presence of nitrogen dioxide (NO2), which is an acute harmful pollutant for human health and environment. Experimentally synthesized ZnO nanostructures were used as the basis for modeling of the ZnO NWs based sensor device along with a single ZnO NW, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 211–219 Read article
-
A Comprehensive Analysis of Classification Methods for Churn Prediction in Financial Services
Abstract: Persistent issues that affect long-term revenue in the banking sector include excessive client attrition. Customary churn models depend on measures related to customer satisfaction, which often result in low predictive accuracy due to their subjective nature. This study proposes an effective early warning model to address customer churn in financial services. Data is preprocessed through cleaning, one-hot encoding, Z-score normalization, and Min-max scaling. To handle class imbalance, the SMOTE algorithm …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 2, 2025 · pp. 47–61 Read article
-
Novel Strategic Framework between Polymer Manufacturers and Waste Management Companies: A Mixed-Method Approach for Enhancing Circular Efficiency in Polymer Industries
Abstract: The study describes the perspectives of the industry stakeholders and qualitatively and quantitatively assesses the recycling efficiency, cost optimization, and environmental performance using a mixed-method approach. The framework features processes, as it were: onboard invention, coupling, and sustainable valorization of the intersection, thus solidly connecting the production side with the waste management. The primary function of the patterns of interaction between the plant waste-management system, the retrieval of polymer composites, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1570–1609 Read article