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60 articles for “computational theory”
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Asymptotic Notations: A Review
Abstract: Asymptotic notations play a fundamental role in assessing the efficiency and performance of algorithms, particularly as input sizes grow larger. This paper delves into three key asymptotic notations: Big O, Theta, and Omega, which are essential for understanding the upper, average, and lower bounds of an algorithm’s runtime. Big O notation specifically helps in determining the worst-case scenario of an algorithm’s growth rate, providing an upper bound on time or …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 17–33 Read article
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Hybrid Best-Response Algorithms for Mobile Computing Offloading: A Comprehensive Review
Abstract: The exponential growth of mobile applications with intensive computational requirements has necessitated innovative offloading strategies in mobile computing ecosystems. This comprehensive review examines hybrid best-response offloading algorithms integrated with game-theoretic optimization frameworks to address resource allocation challenges in mobile edge computing (MEC) environments. The proliferation of Internet of Things (IoT) devices and bandwidth-intensive applications has created unprecedented demands on mobile network infrastructure, compelling researchers to develop sophisticated offloading mechanisms that …
Published in International Journal of Mobile Computing Technology · Vol. 3, Issue 2, 2025 · pp. 20–26 Read article
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A Mathematical Perspective on Recent Cloud-Computing Trends for Scalable and Secure Social-Media Platforms
Abstract: Cloud computing underpins modern social-media platforms by providing elastic compute, storage, and data-processing pipelines capable of absorbing highly bursty workloads. This paper surveys recent cloud-native trends—serverless and event-driven design, container orchestration, edge/CDN offload, streaming analytics, and privacy-enhancing security controls—and formalizes their impact through a compact mathematical model. We express workload volatility using arrival-rate functions, use queueing-based capacity sizing to derive auto-scaling rules, and formulate an optimization objective that balances cost …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 35–40 Read article
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The Scientific Foundations of Programming Languages: Bridging Theory and Practical Application
Abstract: The study of programming languages within computer science is fundamental to the development of efficient, reliable, and scalable software systems. However, the degree to which these languages adhere to scientific principles remains a topic of debate. This paper explores the scientific nature of computer science languages by examining their theoretical foundations, design principles, and practical applications. It evaluates how programming languages are grounded in mathematical logic, formal semantics, and computational …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 1, 2025 · pp. 32–41 Read article
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Computational Modeling of Polymer Semiconductors for Electronic Applications
Abstract: Polymer semiconductors have become important materials in modern electronic applications because they combine semiconducting behavior with mechanical flexibility, low-cost processing, and tunable molecular structure. Their growing use in organic field-effect transistors, organic photovoltaics, organic light-emitting diodes, and flexible sensing devices has increased the need for accurate computational approaches that can predict material properties and device performance before experimental fabrication. This paper reviews the major computational modeling techniques used for polymer …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 132–146 Read article
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Study of Algebraic Structures in Discrete Mathematics and Its Applications
Abstract: Algebraic structures such as groups, rings, fields, semi groups, and lattices form the foundational framework of discrete mathematics. These structures are defined by specific sets and operations that follow algebraic laws, enabling a systematic approach to problem-solving in various domains. This paper explores the theoretical principles of these algebraic systems and highlights their vital role in computer science, cryptography, automata theory, coding theory, and software engineering. By examining their properties …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 1, 2025 · pp. 35–40 Read article
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Density Functional Theory (DFT): Understanding and Quantifying Molecular Structure of 2-D Materials
Abstract: Density Functional Theory (DFT) has emerged as a cornerstone in computational chemistry and materials science, offering a powerful framework for predicting electronic structures and properties of atoms, molecules, and solids. By focusing on electron density rather than wave functions, DFT simplifies the many-body problem through approximations like the local density approximation (LDA) and generalized-gradient approximations (GGAs). The Hohenberg-Kohn theorems establish the theoretical foundation, proving that ground-state properties are uniquely determined …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 2, 2025 · pp. 33–40 Read article
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Modelling Electronic Diode Networks with PSPICE Simulation
Abstract: The dual of Thevenin, Norton equivalent circuit is used in place of any circuit/network of linear sources and immittances at at a given frequency. Both Thevenin with Norton theorem is useful for analyses and modification of circuits, to study /obtain network’s steady state response and initial condition. Methods to represent different circuits with Thevenin/Norton impedances connected at desired nodes are given using Spice/Pspice. The Thevenin/Norton impedances connected are of other …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 2, Issue 2, 2024 · pp. 17–37 Read article
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An Analytical Review of Machine Learning Methodologies
Abstract: Machine Learning (ML) is a dynamic and rapidly developing area of computer science that enables the system to learn from data and improve its performance without clear programs. Rooted in statistical theory and computer algorithms, ML has become a major technology that progresses in artificial intelligence. It strengthens the detection of the recommendations and speech for extensive applications from autonomous vehicles and medical diagnoses. This paper has reviewed the basics …
Published in Recent Trends in Mathematics · Vol. 3, Issue 1, 2026 · pp. 13–21 Read article
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Perfect Numbers: Computational and Technical Exploration
Abstract: This paper explores perfect numbers, by getting into their historical significance and computational journey from ancient times to the present day. The discussion covers the mathematical definition of perfect numbers, their importance in number theory, and the major milestones in their discovery. Also, it elaborates how the coders are using their skillsets to identify new perfect numbers and the transforming outcome of getting more and more perfect numbers found. By …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 1, 2026 · pp. 9–16 Read article
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Scaling of Machine Learning Techniques in Medical Imagining and Biomedical Applications Concerning Healthcare
Abstract: Machine learning refers to a field within computer science enabling computers to learn without explicit programming. Stemming from artificial intelligence's study of pattern recognition and computational learning theory, machine learning develops algorithms capable of learning from vast datasets and making predictions. Its applications span diverse computing tasks like email filtering, network intrusion detection, optical character recognition, and computer vision, where conventional algorithm design proves challenging. Notably, in computer vision, a …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 41–44 Read article
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Predicting Dielectric Constants of Polymers Using Molecular Structural Descriptors and Explainable Machine Learning: A Data-Driven Approach
Abstract: Accurate prediction of dielectric constants in polymeric materials is fundamental to the rational design of advanced electronic components, energy storage capacitors, flexible substrates, and high-frequency communication circuits. Conventional approaches to identifying suitable polymer dielectrics rely on extensive experimental synthesis and characterisation, which are both time-consuming and resource-intensive. In this work, an explainable machine learning framework is developed to predict the dielectric constant of polymers directly from molecular structural descriptors derived …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 297–304 Read article
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Study on the Method of Constructing a System of Linear Equations for Calculating Aerodynamic Derivatives
Abstract: The aerodynamic derivatives can be calculated from the unsteady hydrodynamic forces experienced by the harmonic-oscillating vehicle. Until now, unsteady flow field analysis in aerodynamic derivative calculations has been applied mainly to thin bodies based on potential theory MSC. Nastran is a typical application based on potential theory MSC. Natran can calculate the aerodynamic derivatives of the vehicle relatively well in the subsonic region, but in the supersonic region, the fuselage …
Published in Journal of Experimental & Applied Mechanics · Vol. 16, Issue 3, 2025 · pp. 14–24 Read article
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Role of Quantum Chemistry in Catalysis: A Comprehensive Review
Abstract: Catalysis plays a crucial role in modern chemical manufacturing, energy conversion, and environmental protection by enabling chemical reactions to occur more rapidly, selectively, and with reduced energy consumption. A fundamental understanding of catalytic processes at the atomic and electronic levels is essential for the rational design and optimization of catalysts. Quantum chemistry has emerged as a powerful theoretical and computational framework that enables detailed investigation of electronic structure, reaction energetics, …
Published in Journal of Catalyst & Catalysis · Vol. 13, Issue 1, 2026 · pp. 01–16 Read article
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Fundamental Principles of Fluid Behavior and Emerging Trends in Modern Fluid Mechanics Research
Abstract: Fluid behavior forms the foundation of numerous engineering technology and scientific applications, including aerospace flows, energy systems, and environmental processes. This paper presents a comprehensive overview of the fundamental principles governing fluid behavior, with a strong emphasis on their relevance to recent trends in fluid mechanic’s research. Core concepts such as fluid statics, fluid dynamics, and conservation laws are discussed to establish a solid theoretical framework. The study further examines …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 1, 2026 · pp. 14–21 Read article
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Use of AI Tools to Create New Drugs
Abstract: The emergence of artificial intelligence in pharmaceutical research [in drug discovery] is a revolution in pharmaceutical research, often combining computational methods with traditional research methods to solve problems. This review article describes various applications of artificial intelligence at various stages of drug development and highlights significant advances and approaches. He explores the critical role of intelligence in drug design, polypharmacology, drug synthesis, drug repurposing, and prediction of drug properties, such …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 2, Issue 2, 2024 · pp. 22–49 Read article
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Intelligent Design Approaches in Microwave Engineering Using Machine Learning Techniques
Abstract: In microwave engineering, machine learning (ML) has become a potent technology allowing quicker design cycles, improved modelling accuracy, and automatic optimisation of complicated systems. Recent developments in the use of ML methods to microwave components and systems, including antennas, filters, and high-frequency circuits, are summarised in this study. In the framework of electromagnetic simulation, surrogate modelling, and parameter extraction, supervised and unsupervised learning algorithms are addressed. Moreover, the study looked …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 2, 2025 · pp. 31–38 Read article
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Comprehensive study of Entanglement Entropy in Quantum Field Theory: Analysis of Conformal Field Theory to Massive Field Extensions and Holographic Entanglement
Abstract: This paper provides an in-depth analysis of entanglement entropy (EE) in quantum field theory (QFT), with a particular focus on its computation using the replica trick and its applications to both conformal and non-conformal systems. Beginning with an introduction to the basics of QFT, the study explains how entanglement entropy quantifies the quantum correlations between subsystems in a pure state, represented by the von Neumann entropy of the reduced density …
Published in Research & Reviews : Journal of Physics · Vol. 13, Issue 3, 2024 · pp. 33–58 Read article
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Configuration and Properties of Group III Elements in the Periodic Table
Abstract: Group III elements comprise those found in the third column of the periodic table, including boron, aluminum, gallium, indium, and thallium. These elements possess three valence electrons in their outermost shell, characterized by the electron configuration ns2np1, which influences their location and characteristics within the periodic table. The distribution of electron pairs, formal charges, oxidation states, and molecular morphologies of Group III elements and their compounds are illustrated in this …
Published in Journal of Materials & Metallurgical Engineering · Vol. 15, Issue 2, 2025 · pp. 23–30 Read article
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Exploration of Diverse Epoxy-Based Surface Coating Methods for Enhancing Anticorrosion Characteristics
Abstract: Epoxy-based polymers, commonly referred to as polyepoxides, constitute one of the most versatile and widely adopted categories of polymeric materials due to their exceptional structural, mechanical, and chemical characteristics. Their unique macromolecular framework enables strong interfacial bonding, high mechanical stability, and superior resistance to environmental and chemical degradation, positioning them as advanced alternatives to many traditional organic corrosion inhibitors that often fail under prolonged exposure to aggressive conditions When polyepoxides …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 167–177 Read article