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343 articles for “optimization framework”
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Enhancing Mechanical Properties by Parameter Optimization in Fiber and Particle Reinforced Composites
Abstract: This research focuses on optimizing the mechanical and thermal properties of hybrid fiber and particle-reinforced composites through systematic parameter optimization using the Taguchi method and Grey Relational Analysis (GRA). Composites were fabricated using varying fiber volume fractions (20%, 30%, and 40%), particle sizes (20 μm, 60 μm, and 100 μm), and curing temperatures (60°C, 80°C, and 100°C) in a 3-factor, 3-level experimental design. Key properties such as tensile strength, impact …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 75–85 Read article
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Computer Aided Drug Designing for Targeted Drug Delivery Systems
Abstract: The discovery and development of a contemporary sedate is widely acknowledged as an extremely difficult task that requires significant resources and effort. Therefore, computer-aided medication design techniques are widely utilized today to increase the productivity of the drug discovery and development process. Among structure-based and ligand-based drug design approaches, both recognized for their efficiency in drug discovery and development, various CADD (Computer-Aided Drug Design) techniques are evaluated based on specific …
Published in Trends in Drug Delivery · Vol. 11, Issue 2, 2024 · pp. 34–41 Read article
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Farming Forward: Integrating IoT, AI, and Image Processing for Sustainable Agriculture
Abstract: Farming Forward: Integrating IoT, AI, and Image Processing for Sustainable Agriculture" explores the convergence of cutting-edge technologies in revolutionizing traditional farming practices towards sustainability. This study investigates the integration of Internet of Things (IoT), Artificial Intelligence (AI), and Image Processing techniques in agricultural contexts, aiming to enhance efficiency, productivity, and environmental stewardship. Through a comprehensive review of recent advancements and case studies, this research elucidates the transformative potential of IoT-enabled …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 52–69 Read article
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Controlled Release Drug Delivery Using 3D Printing Techniques: A Current Scenario In Personalized Medicine
Abstract: Three-dimensional (3D) printing is particularly influencing the pharmaceutical manufacturing sector in the creation of controlled release drug delivery systems. This technology enables the precise fabrication of personalized medicines with tailored drug release profiles, dosages, and geometries, marking a significant advancement over traditional mass production methods. An array of 3D printing techniques, including extrusion-based, powder-based, and others, can be used to build complex dosage forms that regulate drug release through processes …
Published in Trends in Drug Delivery · Vol. 12, Issue 3, 2025 · pp. 28–43 Read article
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A Novel Symmetric Anchor Scoring (SAS) Method for Industrial Location Selection: Application to Electric Vehicle Manufacturing in Tamil Nadu, India
Abstract: This work highlights the city-level detail of decision-making enabled by a new MCDM method Symmetry Anchor Scoring (SAS). Generally conventional methods are good at selecting one best and one worst alternative, but not differentiating among the many strong contenders more likely in practice. Linking MCDM methods to the tradition of decision making, the paper discusses the mathematics and analogical basis of SAS design, provides a visual proof of its ideal …
Published in International Journal of Industrial and Product Design Engineering · Vol. 4, Issue 1, 2026 · pp. 8–19 Read article
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Intuitionistic Fuzzy Hypergraph Laplacians and Dominating Transversals for Resilient Discrete Network Design
Abstract: This manuscript develops a discrete mathematical framework for resilience analysis on networks whose interactions are polyadic, uncertain, and partially conflicting. Classical graphs compress multi-way coordination into pairwise edges, while ordinary fuzzy graphs often ignore the non-membership information that becomes critical in emergency logistics, infrastructure interdependence, and cyberphysical coordination. We therefore formulate an intuitionistic fuzzy hypergraph in which each vertex hyperedge incidence carries membership, non-membership, and hesitation, and we construct a …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 2, 2026 · pp. 15–21 Read article
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A Sustainable and Green Prototyping Framework for Low-carbon and Resource-efficient Virtual Product Development
Abstract: The increasing emphasis on sustainable manufacturing has intensified the need for environmentally responsible design and development methodologies for polymer and polymer-composite materials, where material selection, processing routes, and waste generation play a critical role in overall environmental impact. This paper presents a Sustainable and Green Prototyping (SGP) framework that integrates Virtual Prototyping (VP), Life Cycle Assessment (LCA), and multi-objective optimization to systematically reduce carbon footprint, energy consumption, and material waste …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 459–471 Read article
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Machine Learning Assisted Optimization of Nanoscale MOSFET Parameters Using TCAD Simulation
Abstract: This paper presents a machine learning (ML) assisted framework for the multi-objective optimization of nanoscale bulk n-channel metal-oxide-semiconductor field-effect transistors (nMOSFETs) with a 10 nm physical gate length, high-k HfO₂ gate dielectric, and TiN metal gate. Technology computer-aided design (TCAD) simulations employing drift-diffusion transport, Shockley-Read-Hall recombination, Lombardi mobility degradation, and density- gradient quantum correction models are used to generate a parametric dataset of 2,400 device configurations spanning gate length (L), …
Published in Journal of Microelectronics and Solid State Devices · Vol. 13, Issue 1, 2026 · pp. 10–19 Read article
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Group-Theoretic Symmetry Indices for Modular Building Layouts under Seismic Load Redistribution
Abstract: Symmetry in modular buildings operates simultaneously as an architectural language, a structural regularizer, and a computational design variable. This paper develops a group-theoretic framework for evaluating and optimizing plan symmetry in modular buildings subjected to seismic load redistribution. The building layout is modeled as a finite occupancy–stiffness field defined on a rectangular lattice, where each module encodes both mass and stiffness contributions. Planar reflections and quarter-turn rotations are represented as …
Published in Emerging Trends in Symmetry · Vol. 2, Issue 1, 2026 · pp. 01–07 Read article
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AI-Accelerated Development of Gradient Polymer Nanocomposite Thin Films
Abstract: Gradient polymer nanocomposite thin films are an active field of materials research due to the fact that it enables scientists to de-facto regulate the optical, electrical, and mechanical properties of a film by merely altering its composition on a layer-by-layer basis. This type of control opens the gate to the improved flexible electronics, long lasting protective coats, and the new smart gadgets. The problem is, though, that it is a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 456–469 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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Mathematical Modelling of Semiconductor Device Physics: An Analytical Approach
Abstract: Semiconductor device physics forms the foundation of modern electronic and optoelectronic technologies. Mathematical modelling provides a rigorous framework for understanding, predicting, and optimizing the behavior of semiconductor devices by linking physical principles with device-level performance. This work presents an analytical approach to the mathematical modelling of semiconductor devices, emphasizing the derivation and interpretation of governing equations that describe charge transport and electrostatic behavior. The model is based on fundamental physical …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 1, 2026 · pp. 36–42 Read article
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Design and Optimization of Domain-Specific Languages for High-Performance Computing Applications
Abstract: The accelerating demand for computational power in scientific, engineering, and data-intensive domains has driven High-Performance Computing (HPC) systems toward unprecedented levels of parallelism and architectural complexity. Contemporary HPC platforms integrate multicore CPUs, many-core GPUs, accelerators, and deep memory hierarchies, creating significant challenges for software development and performance optimization. Traditional general-purpose programming languages and parallel programming frameworks provide low-level control over hardware resources but require extensive manual tuning, resulting in poor …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
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Comparative Analysis of Processing-Property Relationships in Metal and Polymer Matrix Composites: A Unified Statistical Framework for Hardness Characterization
Abstract: Composite materials, encompassing both metal matrix composites (MMCs) and polymer matrix composites (PMCs), exhibit complex processing-property relationships that fundamentally govern their mechanical performance across diverse applications. This study presents a unified statistical framework for analyzing hardness characteristics in composite systems, using aluminum-tungsten carbide (Al-WC) metal matrix composites as a representative model system while establishing connections to polymer matrix composite behavior. The investigation employed comprehensive processing parameter optimization, microstructural characterization, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 419–430 Read article
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Machine Learning Assisted Timing Violation Prediction in Sub-7nm VLSI Physical Design
Abstract: The continuous scaling of semiconductor technology into the sub-7nm regime has introduced significant challenges in timing closure due to process variability, interconnect delay, power density, and manufacturing uncertainties. Conventional static timing analysis techniques often require extensive computational resources and iterative optimization cycles, resulting in increased design complexity and longer turnaround time. This research proposes a Machine Learning Assisted Timing Violation Prediction framework for sub-7nm VLSI physical design to improve early-stage …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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Cloud-based Application Development and Optimization
Abstract: As cloud computing powers today’s applications, optimizing cloud-based development is crucial to achieve performance, cost effectiveness, and scalability. This research focuses on enhancing the design, deployment, and maintenance of cloud applications, tackling challenges in resource management, scalability, and resilience. We specifically explore dynamic resource allocation algorithms that use predictive analytics for auto-scaling based on workload variations, aiming to cut costs while preserving high performance. The study also investigates cross-cloud optimization …
Published in Journal of Open Source Developments · Vol. 12, Issue 1, 2025 · pp. 37–42 Read article
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How Beagle View of OWASP Top-10 Can Restrict the Optimal Web-App Security: The Security Ladder for Optimal Posture
Abstract: Is OWASP Top-10 good enough to ensure that your web application is secure enough? When it comes to application security, many of us in the information security community, are generally overwhelmed with the OWASP Top-10. Even when we deliberate with developers, OWASP Top-10 is on top of our agenda, and surprisingly the only agenda in many discussions. The approach adopted for this paper is two-pronged: Secondary data – Open source, …
Published in International Journal of Information Security Engineering · Vol. 3, Issue 1, 2025 · pp. 19–39 Read article
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Optimizing Urban Mobility with AI-Based Traffic Management
Abstract: Urban mobility is a pressing concern in modern cities, plagued by issues like traffic congestion and pollution. This research involves, "Optimising Urban Mobility with AI-based Traffic Management", delves into the potential of Artificial Intelligence (AI) to revolutionize traffic management. Focusing on AI algorithms, data analytics, and sensor technologies, the research aims to enhance traffic flow, reduce congestion, and improve overall efficiency. Through statistical analysis and simulations, the research evaluates the …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 34–43 Read article
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Intelligent Electromagnetic Synthesis: An AI-Driven IoT Framework for Adaptive Antenna Design in Missile Navigation
Abstract: The rapid evolution of hypersonic and long-range tactical missile systems necessitates antenna architecture capable of maintaining robust communication links under extreme thermal, mechanical, and signal-jamming environments. Traditional antenna design methodologies often relying on iterative simulation cycles and static optimization are increasingly insufficient for the real-time requirements of modern aerospace navigation. This paper proposes an AI-driven, IoT- integrated framework that facilitates autonomous antenna design and performance optimization. By deploying a distributed …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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Deep Reinforcement Learning-Based Intelligent Energy Management Strategy for Battery–Supercapacitor Hybrid Energy Storage Systems in Electric Vehicles
Abstract: As the number of EVs increases, smart solutions for energy management are needed that will optimize energy use, prolong battery life and boost vehicle performance. The application of conventional rule based and optimization-based Energy Management Strategies (EMS) for Battery–Supercapacitor Hybrid Energy Storage Systems (HESS) often leads to sub-optimal power management, supercapacitor mismatch and battery degradation when subjected to varying driving conditions. This study aims to design an intelligent energy management …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 2, 2026 Read article