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112 articles for “space optimization”
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Transforming the Healing Spaces: Exploring the Impact of Interior Design on Art Therapy Rooms
Abstract: Art Therapy is one of the widely used therapeutic methodologies in psychology with the motive of dealing and eliminating a person’s anxious thoughts or emotions by teaching them how they can cope with their cognitive conditions. However, it is often noted that the clinical environment this procedure takes place in may hinder with the proper development of a patient’s mental health. Therefore, an art therapy clinic should be designed in …
Published in International Journal of Behavioral Sciences · Vol. 1, Issue 1, 2024 · pp. 01–08 Read article
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A Study of Fixed-Point and Best Proximity Point
Abstract: Fixed-point theory plays a fundamental role in nonlinear analysis and has significant applications in optimization, differential equations, and applied mathematics. This study investigates the existence and properties of fixed points and best proximity points for various classes of mappings defined on metric and normed spaces. While fixed-point results guarantee the existence of a point that remains invariant under a given mapping, such points may not exist when the mapping is …
Published in Recent Trends in Mathematics · Vol. 3, Issue 1, 2026 · pp. 28–39 Read article
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Aerodynamic Optimization of UAV Wings Using Machine Learning
Abstract: Unmanned Aerial Vehicles (UAVs) are increasingly deployed across defense, transportation, agriculture, and environmental monitoring, demanding improved aerodynamic efficiency to enhance endurance, stability, and payload capacity. Traditional aerodynamic optimization approaches, relying on computational fluid dynamics (CFD) simulations and wind tunnel experiments, are often time-consuming and computationally expensive. This study proposes a machine learning (ML)-driven framework for the aerodynamic optimization of UAV wing geometries, aiming to significantly reduce design cycles while improving …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 1–7 Read article
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Bayesian Optimization–Driven Operating Parameter Tuning for Maximizing Methane Yield in Anaerobic Digestion
Abstract: To achieve maximum methane production in an anaerobic digestion (AD) process, a combination of various operational parameters must be tuned nonlinearly in the digestion ecosystem. The conventional trial and error optimization methods are slow, resource consuming, and in most instances, cannot model the intricate parameter interaction in biogas production. The current work introduces a Bayesian Optimization-based model to optimize the set of conditions to maximize the level of methane produced …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 1–8 Read article
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Learning Data Structures: Key to Good Programming
Abstract: Data structures are the most crucial feature of good programming and are needed to solve hard computational problems. This model makes use of two different recurrent neural network architectures, specifically long short-term memory (LSTM), and gated recurrent unit (GRU) networks. It explains how selecting and using the correct data structures may speed up computations, optimize memory, and scale code. How data structures and algorithms relate and how to think about …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 29–39 Read article
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Understanding Significance, Challenges and Barriers in Home-Based Medical Care – A Thematic Review of Literature
Abstract: Home-based medical care (HBMC) is emerging as a cornerstone of modern healthcare, offering a pragmatic solution to the evolving needs of patients. This form of care, which delivers personalized and patient-centric services, catering to individual needs within the familiar environment of their homes, is gaining traction for its ability to improve patient outcomes while simultaneously reducing healthcare costs. This thematic review of the literature aims to shed light on the …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 1, 2024 · pp. 66–71 Read article
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A Journey through Fixed Points and Non-expansive Mappings
Abstract: Fixed points in non-expansive mappings are elements that remain unchanged under the action of the mapping. Non-expansive mappings preserve or contract distances in a metric space. The rigorous proof of the Banach fixed-point theorem is presented at the outset of the paper, highlighting its fundamental significance. According to this theorem, every contraction mapping (a particular kind of non-expansive mapping that strictly reduces distances) has a single fixed point in a …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 1, 2024 Read article
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Reduction of Air Pollutants of Urban Canyons through Management of Particulate Matters 2.5 in the Streets
Abstract: Urban canyons are long and high sky-scrappers closely to narrow streets result in very different microclimate challenges. These spaces often trap pollutants and restrict air circulation and intensify more retention of heat making them very uncomfortable for pedestrians. In order to resolve this issue a strong set of design guidelines and frameworks were needed which can balance out the human comfort and environmental aspects. This research studies strategies to improve …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 1, 2025 · pp. 11–23 Read article
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Artificial intelligence-integrated nanobiotechnology for precision medicine, smart diagnostics, and sustainable environmental applications
Abstract: Background: Nanobiotechnology integrates nanoscale materials with biological systems, enabling breakthroughs in drug delivery, biosensing, and environmental monitoring. However, the complexity of biological interactions and the vast parameter space of nano‑bio interfaces limit conventional design. Artificial intelligence (AI) offers powerful tools for modelling, predicting, and optimising these systems. Objective: This review provides a systematic, STM‑compliant overview of AI‑integrated nanobiotechnology across three domains: precision medicine (AI‑optimised nanocarriers, personalised therapeutics), smart diagnostics (AI‑powered …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 2, 2025 Read article
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Neuro-Symbolic Agentic AI for Autonomous Scientific Discovery: Integrating Deep Reinforcement Learning, Quantum Simulation, and XAI-Audited LLM Hypothesis Generation in Drug Target Identification
Abstract: The exponential growth of multi-omics data and the increasing complexity of disease-associated protein interactomes have rendered conventional drug target identification pipelines computationally and epistemologically inadequate. This paper presents the Neuro-Symbolic Agentic AI for Scientific Discovery (NS-AASD) framework, a unified architecture that cohesively integrates deep reinforcement learning (DRL) exploration strategies, variational quantum simulation (VQS) of protein conformational dynamics, and XAI-audited large language model (LLM) hypothesis generation within an autonomous scientific discovery …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article
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Analysis and Design of Modern Parking Structure by Considering Optimised Bracing Systems Under the Dynamic Load
Abstract: The design and implementation of effective bracing systems are crucial for ensuring the structural stability and safety of G+10 parking buildings, particularly in regions prone to seismic and wind loads. This study evaluates and optimizes various bracing systems, including X-type, V-type, Inverted V-type, and Eccentric bracing, to determine their suitability for use in G+10 parking structures in the Chhatrapati Sambhajinagar City area. The research focuses on assessing each bracing system's …
Published in Recent Trends in Civil Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 61–76 Read article
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The Role of Optimization and Probability in Shaping Artificial Intelligence
Abstract: This study discusses the basic roles of optimization algorithms and the theory of probability in the process of evolution and development of Artificial intelligence (AI). First, we introduce the role played by the next generation of leading-edge optimization algorithms developed since gradient descent to evolutionary strategies with respect to the learning of high-level AI models and how to enable them to learn to effectively explore high-dimensional parameter spaces. At the …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 123–128 Read article
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Analytical exploration of self-consolidating concrete (SCC) mix proportions via the Taguchi method
Abstract: To address the challenge of limited space within structural elements containing densely packed reinforcement, Self-Compacting Concrete (SCC) was developed. This study focuses on optimizing the experimentation process using Design of Experiments (DoE). Taguchi's standard L(3) orthogonal array (OA) was utilized, consisting of four factors with three levels each, resulting in nine trial mixes. The factors examined include water-powder ratio, cementitious material content, superplasticizer dosage, and steel fiber content. The aim …
Published in Journal of Geotechnical Engineering · Vol. 11, Issue 1, 2024 · pp. 1–16 Read article
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Optimizing the Work Environment for Interior Designers: Enhancing Creativity, Collaboration, and Well-being in Design Studios and Beyond
Abstract: In the field of interior design, the conventional office setup is no longer adequate to unleash the full creative potential of designers. This paper advocates for environments that go beyond the basic provisions of a laptop and chair, emphasizing the necessity of spaces that truly ignite creativity. By delving into the unique requirements of interior designers, this research underscores the critical importance of environments that engage the senses and facilitate …
Published in International Journal of Atmosphere · Vol. 1, Issue 1, 2024 · pp. 1–14 Read article
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AI-Designed Functionally Graded Polymer Composites for Multifunctional Thin Films
Abstract: The design of multifunctional polymer composite thin films requires simultaneous optimization of mechanical, optical, barrier, and thermal properties—objectives often in conflict when using conventional homogeneous materials. This study presents an artificial intelligence-driven framework for designing functionally graded material (FGM) architectures in polymer nanocomposite thin films. We integrated machine learning with physics-based modeling to optimize compositional gradients across film thickness, achieving superior performance compared to homogeneous and discrete multilayer alternatives. A …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1026–1041 Read article
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Generative AI-Based Inverse Design of Sustainable Biodegradable Polymers with Target Mechanical and Thermal Properties
Abstract: The escalating global plastic pollution crisis has intensified the urgent need for sustainable biodegradable polymer alternatives that can match or exceed the performance of conventional petroleum-based plastics while minimizing environmental impact. However, traditional polymer discovery approaches are severely constrained by high experimental costs, protracted development cycles spanning years, and fundamental inability to simultaneously optimize multiple conflicting material properties such as mechanical strength, thermal stability, and degradation kinetics. This study presents …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Algorithmic Strategies for Complex Data Handling: Optimizing Data Structures for Enhanced Computational Performance
Abstract: We live in an age of big data and processing very large often complicated datasets can be crucial to efficient algorithmic performance. This paper discusses different algorithmic techniques when working with difficult data and how to arrange your information structures correctly for better functionality in large-scale methods. It checks the impact of different algorithms like sorting, searching, and hashing in boosting its processing speed as well as memory use. This …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 2, 2024 · pp. 1–10 Read article
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A Survey on Cognitive Radio Ad Hoc Network Architecture
Abstract: Cognitive radio ad hoc networks (CRAHNs) represent an innovative paradigm in wireless communication, leveraging the dynamic spectrum access capabilities of cognitive radios (CRs) to enhance network performance and spectrum efficiency. The architecture of CRAHNs integrates cognitive radio capabilities with ad hoc networking principles, enabling devices to manage spectrum resources autonomously and intelligently in a decentralized manner. This abstract outlines the key components and functionalities of CRAHN architecture, highlighting its potential …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 3, 2024 · pp. 1–7 Read article
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Application of Artificial Neural Networks in Optimizing Polyhouse Roof Truss Design
Abstract: Polyhouses are specialised agricultural structures developed to maintain controlled environmental conditions for crop cultivation, thereby ensuring consistent productivity even under adverse climatic circumstances. The performance of these systems largely relies on the structural stability and cost efficiency of the roof truss, which must achieve an effective balance between strength, adaptability, and economy. In this research, an Artificial Neural Network (ANN)-based modelling framework is introduced to optimise the members of polyhouse …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 15–25 Read article
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Reviving Retro: Exploring the Resurgence of Vintage and Mid-Century Modern Design in Contemporary Residential Interiors
Abstract: The revival of vintage and mid-century modern design within contemporary residential interiors has emerged as a prominent trend, captivating homeowners, designers, and enthusiasts alike. This research paper aims to comprehensively explore this phenomenon, delving into its historical roots, the multifaceted factors driving its resurgence, the defining characteristics of vintage and mid-century modern design, its enduring appeal, and its implications for contemporary interior design practices. Through an extensive review of literature, …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 13, Issue 1, 2024 Read article