Search
627 articles for “Hybridization”
-
Comprehensive Analysis of Advanced Methods, Materials and Technologies for Portable Water Purifier in Domestic and Industrial Applications
Abstract: Safe drinking water is still a major problem in developing countries, especially in areas with water scarcity, pollution or poor infrastructure. Portable water purifiers have come to the fore as solutions that are realistic to narrow this gap providing flexibility and accessibility in household and industrial environments as well. In this study, promising techniques, materials and technologies used in portable water treatment equipment design have been reviewed. We review important …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 8–19 Read article
-
Entangled Shields: Securing Digital Systems in the Quantum Cryptographic Revolution
Abstract: Quantum computing utilizing principles of superposition and entanglement is poised to revolutionize the computational landscape, presenting unprecedented challenges and opportunities across various disciplines. Among these, cryptography stands at the forefront due to its reliance on computational hardness assumptions, which Quantum algorithms, such as Grover’s and Shor’s, can efficiently exploit. This study explores theoretical foundations and practical applications of quantum-safe cryptographic primitives, such as lattice-based cryptography, hash-based signature schemes, code-based systems, …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 33–43 Read article
-
Deep Learning Architectures for Predictive Modeling in Financial Time Series
Abstract: This study investigates the application of deep learning architectures, particularly convolutional neural networks (CNNs), to the challenging task of financial time series forecasting. Financial markets are inherently complex and influenced by a range of factors, making accurate prediction of price movements a difficult problem. In this research, historical financial data including stock prices, volumes, and other relevant indicators are used to train CNN models aimed at capturing the underlying patterns …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 45–55 Read article
-
Mathematical Modeling of Epidemics Using Stochastic Differential Equations: A Review
Abstract: The accurate modeling of infectious disease dynamics is crucial for predicting outbreaks and informing public health interventions. While deterministic models such as the SIR (Susceptible-Infected-Recovered) framework have traditionally been used to understand disease transmission, they often fail to account for the randomness inherent in real-world scenarios. Disease spread is influenced by numerous uncertain factors, including individual behavioral changes, environmental fluctuations, and imperfect data reporting. These uncertainties can significantly impact model …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 1–6 Read article
-
Polymer Chemistry-Guided Development of Biomimetic Composite Scaffolds
Abstract: Polymer chemistry plays a fundamental role in advancing biomaterials for anatomical tissue engineering, particularly in the design of composite scaffolds that replicate the intrinsic characteristics of native tissues. The regeneration of damaged tissues, especially within anatomically complex structures such as bone, cartilage, and skin, necessitates biomaterials that closely emulate the hierarchical architecture and biological functions of native extracellular matrices (ECMs). The capacity to replicate both mechanical and biochemical cues of …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 7–13 Read article
-
Strategic Optimization of CNC Machining in Production Systems: A Managerial Review of Methods, Metrics, and Industry 4.0 Integration
Abstract: Computer numerical control (CNC) machining has significantly influenced modern production systems by enabling higher efficiency, quality, and sustainability. As industrial operations strive for leaner production and strategic competitiveness, optimization of machining parameters—including cutting speed, feed rate, depth of cut, and tool path strategies—has emerged as a cornerstone of production planning. This review evaluates the optimization methodologies developed from 2015 to 2025, spanning traditional mathematical models to artificial intelligence (AI)-driven metaheuristic …
Published in Journal of Production Research & Management · Vol. 15, Issue 2, 2025 · pp. 25–30 Read article
-
Polymer Chemistry-Driven Design of a Severable Dental Prophylaxis Instrument: Leveraging PEEK and Composites for Enhanced Functionality
Abstract: Polymer chemistry unlocks new possibilities for dental prophylaxis instruments by leveraging molecular design for enhanced functionality. This study explores Polyether Ether Ketone (PEEK), a semi-crystalline thermoplastic, in a novel instrument with a severable working end, featuring a tubular structure with internal screw threads (0.5–0.8 cm) anchoring replaceable elements via a threaded mechanism. PEEK’s aromatic backbone, alternating ether and ketone groups, yields a tensile strength of ~100 MPa, chemical inertness against …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 869–877 Read article
-
Carbon-Al Synergy: Investigation of Fiber Stacking and Orientation on the Mechanical Properties of Al-CFRP Metal Matrix Composites
Abstract: The current study examines the mechanical behaviour of Aluminum-Carbon Fiber Reinforced Polymer (Al-CFRP) composites fabricated using compression moulding technique, a novel approach combining lightweight aluminium’s ductility with CFRP’s high strength-to-weight ratio. The polymer composites were fabricated by stacking aluminum alloy sheet of 0.5mm thickness and pre-impregnated by 12 layers of carbon fiber cloth of 200 gsm, with epoxy resin between layers, followed by consolidation under controlled temperature and pressure in …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 340–354 Read article
-
The Future of Mathematics Education in the Era of Artificial Intelligence
Abstract: The rapid integration of Artificial Intelligence (AI) into education is fundamentally reshaping the landscape of mathematics teaching and learning. This study examines how AI-powered tools are converting conventional math training into inclusive, individualized, and data-driven learning environments. Through an in-depth examination of global case studies—including Squirrel AI, Carnegie Learning’s MATHia, Khan Academy, Microsoft Math Solver, DIKSHA, Photomath, ALEKS, and BYJU’S—the study highlights AI’s ability to tailor content, deliver real-time feedback, …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 2, 2025 · pp. 37–44 Read article
-
Dielectric Elastomers in Actuation and Energy Applications: Material Behavior and Design Strategies
Abstract: Dielectric elastomers (DEs), a class of electroactive polymers, have attracted significant attention for their ability to undergo large, reversible deformations under electric stimulation. This unique capability makes them highly suitable for a range of actuation and energy harvesting applications, especially in the emerging fields of soft robotics, flexible electronics, artificial muscles, and sustainable power generation systems. DEs offer compelling advantages such as low weight, mechanical flexibility, high energy density, and …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 1, 2025 · pp. 13–18 Read article
-
Conductive Polymers for Electro-Mechanical Systems: Structure–Property Relationships and Mechanical Behavior Under Stress
Abstract: Conductive polymers represent a unique class of functional materials that combine the electrical characteristics of metals with the mechanical flexibility of polymers. These dual properties are critical for the next generation of electro-mechanical systems, including wearable sensors, soft robotics, structural health monitoring (SHM), and biomedical actuators. However, the mechanical performance of conductive polymers under diverse stress conditions—such as elongation, cyclic loading, bending, and impact—remains a key challenge, limiting their long-term …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 1, 2025 · pp. 25–30 Read article
-
Automated Crop Disease Detection Using Convolutional Neural Networks
Abstract: Crop diseases contribute to major losses in agricultural production worldwide generating enormous economic costs. This study investigates the possibility of Convolutional Neural Networks (CNN) imaging techniques to auto-detect diseases associated with plants through image processing. A model was developed and trained on a publicly available plant disease dataset containing labeled images of several diseases. The CNN could classify various plant diseases with accuracy of 95%, precision of 92%, and recall …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article
-
Synthesis, Characterization, Antibacterial Evaluation and Study of Organic Separation Behavior for Five Membered Ring for Pyridine Derivatives
Abstract: Imidazoles can be prepared by condensation between amines and various aldehydes and ketones. Imidazole derivatives are important compounds due to their broad biological activity and pharmacological properties, such as antifungal, antioxidant, cytotoxic, anti-inflammatory, analgesic, anti-YFV (yellow fever virus), anti-tuberculosis, and antimicrobial activity. In recent years, many studies have been conducted on the preparation of biological imidazole derivatives, especially derivatives linked to heterogeneous rings containing nitrogen or any other donor atom. …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 3, 2025 · pp. 106–121 Read article
-
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
-
Machine Learning Pipelines: A Survey on Automation, Scalability, and Deployment Strategies
Abstract: Machine learning (ML) has become a critical enabler of intelligent applications across domains, requiring robust, efficient, and scalable deployment workflows. This review paper provides an in-depth overview of machine learning pipelines, emphasizing three key dimensions: automation, scalability, and deployment methodologies. It begins by exploring automation techniques that reduce manual effort in data ingestion, preprocessing, model selection, and hyperparameter tuning. Tools such as AutoML, TFX, and workflow orchestration platforms are examined …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 17–28 Read article
-
Harnessing Machine Learning for Stock Movement Prediction: A Review of Current Approaches
Abstract: Stock price prediction is a crucial task in financial analysis, aiding investors and traders in making informed decisions. This study investigates the use of deep learning methods, particularly Long Short-Term Memory (LSTM) networks, for predicting stock prices based on historical market data. The dataset, sourced from Yahoo Finance, consists of time-series stock price data, which is preprocessed, feature-engineered, and visualized to improve prediction accuracy. The model's performance is assessed using …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 29–40 Read article
-
Forecasting Commodity Prices Using Deep Learning Techniques: An Empirical Evidence from India
Abstract: Commodity price forecasting is instrumental in financial markets, providing framework for investment choices and risk management practices. Traditional models, including statistical and machine learning approaches, have limitations in capturing the nonlinear and volatile nature of commodity prices. Deep learning (DL) techniques have emerged as promising alternatives, leveraging advanced neural networks to enhance predictive accuracy. This study presents a thorough and comprehensive examination of deep learning applications in commodity price prediction, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 08–12 Read article
-
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
-
Full-Stack Web Development for Intelligent User Interfaces: Integration of MERN and Rails
Abstract: In the modern era of web development, by providing users with flexible, responsive, and interactive designs, Intelligent User Interfaces (IUIs) greatly improve the user experience. A hybrid method for constructing intelligent, scalable, as well as efficient online apps is discussed in this review work, which focuses on the integration of Ruby on Rails with the MERN stack (MongoDB, React.js, Express.js, Node.js). The MERN stack excels in dynamic frontend development, while …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 3, 2025 · pp. 15–25 Read article
-
Selection of Ionic Liquids for the Design of Separation Processes of CO₂ + H₂S Mixed Waste Gases with Different Compositions
Abstract: The waste gas from chemical plants contains H 2 S gas and a large amount of CO 2 gas. These flue gases can be treated in various ways, and in this paper, the mixed flue gas CO 2 +H 2 S was treated by using ionic liquids (IL) as an absorbent. Ionic liquids are considered green solvents with remarkable good properties. In particular, it is known as a very effective …
Published in Journal of Catalyst & Catalysis · Vol. 12, Issue 3, 2025 · pp. 44–58 Read article