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503 articles for “predictive analysis”
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Comparative Analysis of Kinetic Models for Simulation of Biogas Production from Cow Dung and Fruit Waste via Anaerobic Digestion
Abstract: This study investigates the optimization of biogas and biofertilizer production from cow dung and fruit waste through anaerobic digestion, utilizing various microbial growth kinetic models. Simulations were conducted using the Monod, Moser, Contois, and Tessier models to predict biogas yield and assess model accuracy. Results indicated that the Tessier model provided the closest fit to experimental data, with a biogas yield of 0.45 m³/kg VS, while the Monod model overestimated …
Published in International Journal of Membranes · Vol. 2, Issue 1, 2025 · pp. 47–63 Read article
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Prediction of Customer Churn Using Machine Learning Classification Models
Abstract: Customer churn prediction is a critical task in both the telecommunication and medical industries, where retaining customers or patients is essential for ensuring long-term profitability and maintaining high-quality service. To address this, a range of machine learning models—including logistic regression, decision trees, random forests, gradient boosting machines, and support vector machines—were employed to accurately forecast churn behavior. Prior to model training, the dataset underwent thorough preprocessing, which included handling missing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 86–92 Read article
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Review and Opportunities for Thermal examination approaches Used to Investigate the Thermal Properties of Composite Compounds
Abstract: The use of thermal examination approach to assess the thermal quality of energy materials in “China” is concisely described. They are often used to calculate thermal stability, compatibility, and thermophysical constants, as well as to study thermal breakdown kinetics, causes, and interactions. Furthermore, a few studies focused on creativity or advancement, such as analyzing the mechanisms of topochemical reactions, assessing condensed-phase reaction kinetics by tracking the change in functional groups …
Published in Journal of Polymer & Composites · Vol. 12, Issue 6, 2024 · pp. 96–106 Read article
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AI-Enabled Feedback Management for Enhancing Education
Abstract: Institutions are becoming more aware of the importance of student input in improving learning experiences in the current educational environment. However, the intricate and complex patterns found in this feedback are frequently missed by conventional techniques like manual reviews and simple statistics. Our proposal suggests a novel method for analyzing student input and more accurately predicting sentiment by utilizing Long Short-Term Memory (LSTM) algorithms. We can learn more about student …
Published in International Journal of Electronics Automation · Vol. 3, Issue 2, 2025 · pp. 21–27 Read article
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Reliability-Based Prediction of Bearing Capacity of Shallow Foundation Along Ajaokuta-Kaduna-Kano Pipeline Track
Abstract: This paper investigates the geotechnical properties and reliability-based bearing capacity predictions for shallow foundations along the proposed Ajaokuta-Kaduna-Kano (A-K-K) pipeline track in Nigeria. The variability of subsoil properties along this route poses significant challenges to ensuring foundation stability and safety, necessitating an in-depth study. A total of twenty boreholes were strategically drilled at key locations to a maximum depth of 30 meters, providing comprehensive subsurface profiles. Soil samples collected from …
Published in Journal of Geotechnical Engineering · Vol. 12, Issue 1, 2025 · pp. 9–17 Read article
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Advancements in Metal-Plastic Hybrid Structures: Experimental Analysis and Design Optimization of 3D-Printed Honeycomb Frameworks
Abstract: The exploration of metal-plastic hybrid structures has gained significant attention due to their potential for lightweight, high-strength applications across industries such as aerospace, automotive, and construction. This study investigates the experimental and design enhancements of a metal-plastic hybrid structure utilizing a honeycomb architecture produced through 3D printing. By integrating metals with plastic polymers in a honeycomb configuration, this hybrid approach aims to combine the high strength and stiffness of metals …
Published in Trends in Machine design · Vol. 11, Issue 3, 2024 · pp. 36–43 Read article
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Assessment of Matrix Cracking and Fiber Breakage in Hybrid Composite Materials.
Abstract: Hybrid composite materials, combining two or more distinct fiber or matrix constituents, have emerged as advanced structural solutions for aerospace, automotive, marine, and civil engineering applications. However, their complex microstructure makes them susceptible to multiple interacting damage mechanisms, particularly matrix cracking and fiber breakage. This study provides a comprehensive assessment of these damage modes, emphasizing their initiation, evolution, and combined effects on the mechanical integrity of hybrid composites. Matrix cracking …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 2, 2025 · pp. 1–5 Read article
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Parametric Study of Laser Drilling Process Using Multi Variable Regression Analysis
Abstract: The laser drilling process is an advanced manufacturing technique extensively employed for intricate and high-value components in aerospace, automotive, and electronics industries. Laser drilling technology offers opportunities to meet the contemporary demands of industries using a broad spectrum of engineering materials. However, this process encounters several engineering challenges such as thermal damage, dimensional inaccuracies, and the formation of a recast layer in the drilled components. This study focuses on examining …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1000–1015 Read article
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Cognitive AI-Based Quality Control and Operational Optimization of Polymer Composites for Healthcare Applications
Abstract: The use of polymer composite materials in healthcare is on the rise because of their adjustable mechanical characteristics, biocompatibility and structural flexibility. Yet, it is difficult to ensure stable quality of such composites due to process-related defects, heterogeneity of the material and the lack of real-time adaptive control. The proposed study suggests the use of cognitive AI-based framework of quality control and optimization of operation of polymer composite systems which …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 571–591 Read article
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Enhancing Maintenance Decision-Making in Thermal Power Plants Using Generative AI-Based Fault Diagnosis
Abstract: The growing complexity of operation and power consumption of thermal power stations involve the need to have intelligent fault diagnosis systems that can be used to guarantee reliability and safety in operation. In this research, a Generative AI (GenAI)-based hybrid architecture of early fault detection and predictive maintenance is proposed to improve the decision-making process of the maintenance team. The data-driven analytic approach combines methods of data-driven analytics, Generative AI …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 25–33 Read article
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Design Conceptualization and Computational Analysis of Cryogenic Engine Nozzle-ABYOM
Abstract: The main purpose of this paper is to design a cryogenic engine nozzle with specified dimensions using CATIA V5 software and analyze the nozzle using ANSYS software. The realizable k-ε viscous model was used for calculation and the Hydrogen (H2) had retained as an ideal gas. The CFD simulations were done on the nozzle to find the pressure, density, velocity, and temperature. In the graph, there are 500 points streamlined …
Published in Journal of Materials & Metallurgical Engineering Read article
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Sequence analysis, DNA Methylation and Molecular therapy of Oral cancer caused by Human Papilloma Virus
Abstract: DNA methylations with oral cancer are been associated with high-risk Human Papillomavirus (HPV) and Epstein-Barr Virus (EBV) onco-proteins interactions may cooperate to increase disease severity. The work focused on human papillomavirus strain 16, a high-risk, sexually transmitted responsible for 95% of all cervical cancers and a large portion of oropharyngeal cancers. The prediction of genes from has shown seven genes from HPV16 strain. Based on gene identification studies, Human papilloma …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 2, 2026 · pp. 1–9 Read article
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Ai-Driven Healthcare System for Enhanced Diagnosis and Patient Interaction
Abstract: Deep learning techniques are used in an AI-driven healthcare system to improve disease identification and medical picture analysis. Data collection, preprocessing, model training, and evaluation are all part of the system's systematic workflow. Various deep learning architectures, such as ResNet50, VGG-16, and U-Net, are employed for precise classification and segmentation of medical images. The approach incorporates advanced techniques such as optimization, transfer learning, and data augmentation to significantly enhance the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 Read article
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Deep Learning-Based Pneumonia Diagnosis: A Comparative Review of Models and Metrics
Abstract: Pneumonia is a common viral infection that affects a large percentage of people worldwide. It is more common in developing and impoverished areas because of factors like poor sanitation, crowded living quarters, pollution in the environment, and restricted access to medical facilities. In order to improve survival chances and gain access to therapeutic therapies, pneumonia must be diagnosed as soon as possible. A type of artificial intelligence called deep learning …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 Read article
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Python's Applications in the Profession of Data Science
Abstract: Because of its ease of use, adaptability, and huge ecosystem of libraries, Python has become one of the most influential programming languages in the field of data science. Python is highly valued for its straightforward and versatile nature. This study delves into its various uses in data science, including tasks like data preprocessing, exploratory data analysis (EDA), statistical modeling, machine learning, and creating visualizations. Libraries like Pandas and NumPy make …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 23–30 Read article
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A Review on Advances in Polymer Composites and Nanocomposites: Design, Applications, and Life Cycle Assessment
Abstract: Materials based on polymer composites and nanocomposites have won the main status in several regions of industry by mare possessing excellent properties and broad range of application. This review focuses on the advancements in the design of fiber-reinforced polymers, structural composites, multifunctional composites, and biomimetic and eco-friendly composites. Emerging developments in biomedical composites, polymer foams, and smart composites are explored, highlighting their applications in medical, aerospace, automotive, and structural engineering. …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 244–251 Read article
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Particle Swarm Optimization Framework for Accurate Battery State-of-Charge and Remaining Useful Life Estimation
Abstract: Accurate estimation of the State of Charge (SOC) and State of Health (SOH) of a battery is key to safe and efficient management of batteries in electric vehicles and energy-storage systems. However, it is challenging due to high nonlinearity, varying operating conditions, measurement noise, and limited access to comprehensive electrochemical parameters. Traditional data-driven models often generalize poorly and require heavy tuning, which can produce unstable predictions. To address these problems, …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 53–64 Read article
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Harvestify: ML Based Tool for Home Gardening and Farming
Abstract: This study presents a cutting-edge application that will transform home gardening and agriculture practices using machine learning (ML) approaches. The main goal is to provide data-driven insights to home gardeners and farmers, enabling them to implement efficient and sustainable farming practices. Crop disease detection, fertiliser recommendation, and a community section for user engagement comprise the three main elements that make up the system's architecture. The Crop Disease Detection module analyses …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 2, 2024 · pp. 18–28 Read article
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Non-Lethal Protection of Farmlands Against Wild Animals and Crop Estimation
Abstract: This paper is an integrated smart system that aims to enhance productivity related to agriculture along with agricultural safety through modern technology. Crop estimation system uses IoT sensors and machine learning algorithms for the analysis of real-time environmental data in terms of soil moisture, temperature, pH levels, and humidity. This data will further be used to provide the optimal crop for cultivation and appropriate fertilizer requirements for prediction of requirements. …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 1, 2025 · pp. 18–24 Read article
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Gene Annotation of Cancer Vaccine for Homo sapiens
Abstract: Objectives: Gene annotation helps us to deduce the structural and functional aspects of a gene that encodes for a functional protein in our body. Thus, by determining the coding sequence and gene location we can derive meaningful insights as to what these genes do in our body. In this study, an unknown gene, cancer vaccine for Homo sapiens has been studied and annotated. Methods: This study was based on a …
Published in International Journal of Molecular Biotechnological Research · Vol. 2, Issue 1, 2024 · pp. 1–14 Read article