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165 articles for “hybrid machine”
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A Threshold-Weighted Mathematical Fusion Model for Epidemic Outbreak Prediction Using SEIR Residual Dynamics and Cloud-Based Machine Learning
Abstract: Accurate prediction of epidemic outbreaks is critical for effective public health management, resource planning, early warning generation, and timely intervention by municipal authorities. Traditional compartmental models such as Susceptible–Exposed–Infectious–Recovered (SEIR) offer valuable epidemiological insights and mathematical interpretability; however, they may not adequately capture the complex nonlinear relationships present in real-world urban health systems. Conversely, data-driven machine learning techniques can identify hidden patterns in large datasets but often lack epidemiological structure …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 12–19 Read article
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Intelligent Optimization of Drilling Parameters in Polymer Composites using Machine Learning and Metaheuristic Techniques
Abstract: The study tests different ways to use ML and metaheuristic algorithms to determine the best drilling parameters for polymer matrix composites. The research uses a composite matrix made from 55.25% vinyl ester, 44.0% Nickel–Phosphorous coated glass fiber and 0.75% Al₂O₃ nanowires which are tested for tensile strength (64.57 MPa), flexural strength (85.86 MPa) and impact strength (71.79 kJ/m²). By applying a Taguchi orthogonal array, it is observed that a slower …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1795–1810 Read article
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A Survey on Ensemble Technique for Enhanced Cyberattack Detection
Abstract: It is now more difficult than ever to safeguard enterprises against cyberattacks due to their fast growth and growing sophistication. Stronger cyberattack detection systems are becoming more and more necessary as hostile strategies continue to evolve in order to safeguard information, preserve corporate trust, and protect sensitive data. An overview of contemporary detection techniques is given in this study, with a focus on integrating machine learning (ML) to increase efficacy. …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 50–54 Read article
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Differential Privacy-Aware Data Sanitization for Multi-Level Security
Abstract: Multi-level security (MLS) models are fundamental for enforcing mandatory access control in high-security environments such as government, military, healthcare, and finance. However, traditional MLS frameworks, including the Bell-LaPadula and Biba models, often create rigid data silos, preventing efficient data utilization. Differential privacy (DP) presents a novel solution by enabling controlled information leakage while preserving confidentiality. By injecting statistical noise into query results, DP allows lower-clearance users to access sanitized versions …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 1, 2025 · pp. 42–52 Read article
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Intelligent Automated Guided Vehicle (AGV) System for Optimized Material Handling
Abstract: This project is the development of an Automated Guided Vehicle (AGV) system that has been developed to handle materials in the high-accuracy, reliability, and efficiency in industrial settings. The AGV is a combination of a blend of advanced technologies including sensor fusion, real-time path planning, and AI-based navigation to allow smooth and intelligent operation with minimal human intervention. The vehicle is able to efficiently identify, and evade obstacles by using …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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Intelligent Automated Guided Vehicle (AGV) System for Optimized Material Handling
Abstract: This project is the development of an Automated Guided Vehicle (AGV) system that has been developed to handle materials in the high-accuracy, reliability, and efficiency in industrial settings. The AGV is a combination of a blend of advanced technologies including sensor fusion, real-time path planning, and AI-based navigation to allow smooth and intelligent operation with minimal human intervention. The vehicle is able to efficiently identify, and evade obstacles by using …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 1–7 Read article
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An Experimental Investigation of Machining Parameters on Aluminum Composites
Abstract: The need for a material with good mechanical, thermal, and wear resistant properties is satisfied by aluminum composite. However, the biggest obstacle to substituting it with alternative materials is the machining challenges. For this kind of hard-to-cut material, electric discharge machining is a very efficient method. Thus, using a Taguchi-based method, an attempt has been made to determine the most advantageous amount of input parameters for EDM of Al composite. …
Published in Journal of Polymer & Composites · Vol. 12, Issue 6, 2024 · pp. 8–13 Read article
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Harnessing NLP for Automation and Intelligence Across Sectors
Abstract: Natural Language Processing or NLP is a vital subset of Artificial Intelligence or AI which enables machines to interpret, understand, and communicate using human language in a remarkable way. From the traditional rule-based approaches to the modern advanced deep learning techniques such as transformers, neural networks, and hybrid models, NLP has been evolving year by year. This study reflects on various applications of NLP, including sentiment analysis, machine translation, analysis …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 23–32 Read article
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Study of Proximity Points and Fixed Points
Abstract: This paper explores the concepts of proximity points and fixed points, which are fundamental in mathematical analysis and nonlinear functional analysis. Fixed-point theorems play a crucial role in optimization, game theory, differential equations, and dynamic systems. Proximity points, an extension of fixed points, provide a more generalized approach, allowing near-coincidence rather than exact identity. The study discusses classical fixed-point theorems, such as Banach’s contraction principle, Brouwer’s fixed-point theorem, and Schauder’s …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 28–31 Read article
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Optimization of WEDM Process Parameters Using a Hybrid Multi-Criteria Decision Making Approach
Abstract: The effectiveness of the manufactured parts is typically measured by more than one performance characteristics. Hence the manufacturing engineers frequently experience the difficulty in optimizing the multiple responses at a time. The present work is to explore the effect of wire electrical discharge machining (WEDM) process parameters in machining of Aluminum metal matrix composite (AMMC). The multiple performance characteristics of material removal rate (MRR) and surface roughness (Ra) are optimized …
Published in Journal of Mechatronics and Automation · Vol. 5, Issue 3, 2018 · pp. 24–30 Read article
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Enhancing Power Conversion Efficiency in Tandem Solar Cells with Temporal Dynamic Graph Neural Network
Abstract: In modern homes, people want good comfort and also less electricity bill, so managing heating load and cooling load become very important. Heating Load (HL) and Cooling Load (CL) depend on many things like wall material, window size, sunlight, ventilation, and weather. Because of this many factors, calculation and optimization of HL and CL is little difficult and many time normal formulas give wrong or not perfect results. So in …
Published in Journal of Semiconductor Devices and Circuits · Vol. 13, Issue 2, 2026 · pp. 12–19 Read article
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Selection of Maintenance Strategy Using Hybrid AHP-VIKOR Approach for a Smart Manufacturing Application in Industry 4.0
Abstract: In Industry 4.0, choosing the right maintenance strategy is important for improving machine performance, reducing downtime, and ensuring smooth operation in smart manufacturing systems. This study aims to find the most suitable maintenance strategy for a customized machine-making company by using a combination of AHP and VIKOR methods. In this study, four types of maintenance strategies are considered: breakdown maintenance, time-based maintenance, condition-based maintenance, and predictive maintenance. First, the AHP …
Published in Journal of Production Research & Management · Vol. 16, Issue 2, 2026 · pp. 1–11 Read article
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Machine Learning Framework for Optimizing Polymer–Metal Oxide Composites as Charge Selective Layers in Perovskite Solar Cells
Abstract: To achieve high-performance and stability of perovskite solar cells (PSCs), it was important to incorporate innovative interfacial materials to tune the balanced charge extraction, low recombination, and enhanced operational lifespan. On this note, polymer composites with metal oxides have been proposed as promising candidates as charge selective layers (CSLs), whereby they present a rare combination of tunable energy levels, improved film forming abilities, and better interface engineering capabilities. In this …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 1073–1098 Read article
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Eco-Design Approaches in Modern Machine Tool Construction
Abstract: In the contemporary landscape of manufacturing, sustainability is no longer optional; it is imperative. Within this context, machine tool construction presents a unique set of challenges and opportunities: these heavy, energy-intensive pieces of capital equipment operate across long lifecycles, consume substantial embodied energy and materials, and eventually require disposal or remanufacture. This study explores eco-design approaches tailored specifically to modern machine tools, covering the full lifecycle from material sourcing and …
Published in Trends in Machine design · Vol. 12, Issue 3, 2025 · pp. 23–29 Read article
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Microstructural Characterisation and Analysis of Mechanical Behaviour of Hybrid AA 7075/7178 Fabricated Using Die Casting Technique
Abstract: AA are being increasingly used in the field of structural engineering owing to their desirable mechanical properties coupled with their recyclable and sustainable nature, thus contributing significantly towards reduction of carbon footprints and development of circular economy. Till date numerous research projects have been prompted to investigate the structural performance of aluminium alloy structures and develop alternatives with enhanced performance parameters. AA 7xxx (Al-Zn-Mg-Cu) are being widely used in variety …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 441–451 Read article
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A Survey On Leveraging Machine Learning for Phishing Attack Prediction and Detection
Abstract: Phishing is one of the biggest cybersecurity threats that exploits user trust by masquerading as a legitimate site or email to steal personal and sensitive information. A state- of-the-art-phishing detection systems survey, this review showcases the evolution from traditional list-based techniques, including blacklisting and whitelisting to machine learning and deep learning models. While list-based systems cannot evolve to detect new and zero-day attacks, the ML algorithms of Decision Tree, Random …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 3, 2025 · pp. 1–10 Read article
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A Hybrid Multi-Physics Ensemble Deep Learning Framework for Simultaneous Prediction of Thermal and Electrical Conductivity in Functional Polymer-Based Nanocomposites
Abstract: Polymer-based nanocomposites have become promising materials for applications in energy storage, flexible electronics, biomedical devices, aerospace components, and advanced engineering because of their tunable thermal and electrical properties. Reliable prediction of these properties is essential for accelerating material design; however, existing analytical models and conventional machine learning techniques often fail to represent the complex interactions among filler characteristics, polymer matrices, processing conditions, and interfacial transport phenomena. This work presents HMEP-Net, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1062–1082 Read article
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Fuzzy Mathematics in Decision-Making: A Quantitative Perspective
Abstract: Fuzzy mathematics plays an increasingly generalized role in decision-making, and thus, this paper details different types of fuzzy mathematics and highlights other possible alternatives alongside fuzzy methodologies. Fuzzy models offer a versatile and precise approach to assessing complex and uncertain situations using fuzzy sets, membership functions, linguistic variables, and aggregation methods. Through the lenses of time, cost, and quality, the project management case study illustrates how fuzzy logic effectively evaluates …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 6–12 Read article
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Interfacial and Tribo-Mechanical Performance of a TiO₂–Castor Oil Polymeric Nanofluid During Sustainable Machining of AISI 316L Stainless Steel Under MQL Conditions
Abstract: This research examines the tribo-mechanical performance and interfacial film characteristics of a TiO₂-reinforced castor-oil polymeric nanofluid during the turning of AISI 316L stainless steel under minimum-quantity lubrication (MQL). A Taguchi L9 orthogonal array was utilized to assess the synergistic effects of cutting speed, depth of cut, and coolant composition on surface integrity, while machining experiments were performed under dry, conventional, and TiO₂-nanofluid lubrication techniques. ANOVA and multiple-regression modeling were used …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 901–914 Read article
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Role of Machine Learning Principles for Efficient Nuclear Fuel Management and Design
Abstract: The introduction of machine learning (ML) and evolutionary computation methods in addressing complex nuclear fuel management challenges has brought a significant positive change in the domain of nuclear fuel management. Key applications include fuel assembly design optimization, core loading pattern determination, burnup calculation acceleration, fuel performance prediction, and spent fuel characterization. The analysis reveals significant improvements in computational efficiency, prediction accuracy, and optimization capabilities when ML techniques are properly integrated …
Published in Journal of Nuclear Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 22–33 Read article