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66 articles for “space complexity”
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Integrating Genetic Algorithms with Lean Manufacturing for Enhanced Production Efficiency
Abstract: Lean manufacturing is a well-established philosophy focusing on the systematic reduction of waste and the ongoing development of value supplied to the customer. It emphasizes efficiency, quality, and adaptability through ideas such as just-in-time production, continuous improvement (Kaizen), and value stream optimization. However, the increased complexity of modern production systems, driven by global rivalry, product variety, and rapid technology innovation, has shown the limitations of classic lean tools in achieving …
Published in Journal of Production Research & Management · Vol. 15, Issue 3, 2025 · pp. 38–43 Read article
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Enhancement of Horizontal Jet Impingement Heat Transfer Analysis on Vertical Flat Plate
Abstract: This research investigates the heat transfer characteristics and heat flux distribution associated with parallel jet impingement on a vertical flat plate. A comprehensive computational fluid dynamics (CFD) analysis is carried out and systematically validated against available experimental data to ensure the accuracy and reliability of the numerical model. The jet length is maintained constant at 12 mm, while the jet-to-plate separation distance is varied at 6, 12, 18, and 24 …
Published in Journal of Experimental & Applied Mechanics · Vol. 17, Issue 1, 2026 · pp. 65–80 Read article
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Spatiotemporal Analysis of Mean-Field Coupled Lorenz Oscillators for Applications in Electronic Network Design and Chaotic Synchronization
Abstract: This study investigates the spatiotemporal behavior of a network of 100 coupled Lorenz oscillators interacting through mean-field coupling with coupling strength κ = 0.1 and explores its relevance to electronic system design and nonlinear network architectures. While each oscillator follows classical Lorenz dynamics, the coupling mechanism enables collective behavior that resembles synchronization phenomena observed in distributed electronic and communication systems. Numerical simulations reveal rich dynamical characteristics including partial synchronization, emergent …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 2, 2026 Read article
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A Dynamic Text Compression Model for Big Data Applications Using Hadoop
Abstract: In today’s data-driven era, efficiently handling vast amounts of information has become increasingly important. Data compression plays a vital role in this regard — it is essentially a method of encoding information in such a way that significantly reduces the number of bits required to store or transmit a file. By shrinking data to its most compact form, compression techniques help save storage space, reduce bandwidth consumption, and improve the …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 2, 2026 Read article
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Automating Compiler Optimization: A Machine Learning Approach
Abstract: This study reports on an ML-based approach to compiler optimization, complementing traditional optimization methods that rely strongly on hand-tuned settings. Compiler optimization plays a key role in performance-speedup and energy optimization of complex contemporary software systems. However, the traditional approach to optimizer settings involves laborious, error-prone, and scale-insensitive human-in-the-loop intervention, especially in the complex and high-demand environments in which today's computing application thrives. By integrating RL and GA, we can …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 12–16 Read article
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A Study on Leveraging Sensors and AI in Insect-Inspired Robotics for Unstructured Environments: Bio-Inspired Autonomy
Abstract: Insects, with their unparalleled agility, resilience, and highly efficient sensory-motor control in complex, unstructured environments, offer a rich blueprint for the next generation of autonomous robots. This study explores the design, implementation, and potential of insect-inspired robots, focusing on the synergistic integration of miniaturized sensor arrays and advanced Artificial Intelligence (AI) algorithms. We delve into bio-mimetic sensing, drawing inspiration from compound eyes, olfactory systems, and tactile hairs, to equip robots …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 2, 2025 · pp. 7–21 Read article
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Free Vibration Analysis of Circular Perforated Laminated Plates
Abstract: This study investigates the free vibration characteristics of circular perforated laminated composite plates. A finite element model is created to analyze the effects of perforation patterns, hole sizes, and laminate configurations on the natural frequencies and mode shapes of these structures. The model incorporates shear deformation theory and accounts for the anisotropic nature of composite materials. Parametric studies were held to examine how varying perforation geometries, including hole diameter, spacing, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 281–296 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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Design and Fabrication of Tapered Optical Fiber Related Devices
Abstract: By joining conical single-mode fibers, a Mach-Zehnder interferometer with a refractive index (RI) sensor was produced. Sensors were made directly from conical SMFs using a Vytran engine. Compared to the single-taper sensor, the dual-taper sensor turned out to be more efficient. With a 10mm gap between the two taper sites in the dual-taper sensor arrangement, the RI fluctuation was quite noticeable. The principles underlying the design and fabrication of tapered …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 1, 2024 · pp. 1–7 Read article
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Accelerating Unsupervised Feature Learning: Parallelized Training of Denoising Autoencoders
Abstract: Unsupervised representation learning has become a cornerstone of contemporary machine learning, enabling algorithms to extract informative features from un-labelled, high-dimensional data. This work investigates the efficacy of stacked denoising autoencoders (SDAEs) trained via parallelized stochastic gradient descent (SGD) as a scalable approach to feature extraction. By strategically leveraging multi-threaded computation, our study systematically examines the trade-offs between increased parallelism, training efficiency, and the preservation of model accuracy. Experiments on the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 56–64 Read article
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Advances in Solubility Enhancement Strategies for Poorly Water-soluble Drugs: A Comprehensive Review
Abstract: Solubility enhancement holds significant importance in the field of pharmaceutical research as it aims to augment the solubility and bioavailability of drugs that possess low solubility. Poorly soluble drugs pose a considerable challenge in drug development due to their tendency to display inadequate absorption, bioavailability, and therapeutic efficacy. The advancement of solubility enhancement techniques encompasses a wide range of approaches, including physical and chemical methods, as well as innovative technologies …
Published in International Journal of Vaccines · Vol. 1, Issue 1, 2024 · pp. 01–09 Read article
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Artificial Intelligence in Robotics: Current Trends, Applications, and Future Challenges
Abstract: The incorporation of artificial intelligence (AI) into robotics has transformed the industry by greatly improving robots' capacity to carry out complex and autonomous functions in a wide range of sectors. This paper explores the evolution, applications, and challenges associated with AI-driven robotics. It examines key AI methodologies employed in robotics, including machine learning, natural language processing (NLP), computer vision, and planning/control algorithms, which enable robots to perceive, learn, and interact …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 2, 2025 · pp. 31–43 Read article
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Integrating Counseling into ESRD Care: Addressing Mental Health to Enhance Patient Outcomes
Abstract: End-Stage Renal Disease (ESRD), also referred to as Chronic Kidney Disease Stage 5 (CKD-5), profoundly impacts patients' physical health as well as their emotional and psychological well-being. As individuals approach renal failure, they commonly encounter complex mental health challenges such as depression, anxiety, chronic stress, and a markedly diminished quality of life. This study underscores the critical importance of integrating emotional and mental health support into the care of ESRD …
Published in Research and Reviews: A Journal of Medicine · Vol. 15, Issue 3, 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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High-Energy Astrophysics: Exploring the Extreme Universe Through Radiation, Relativistic Phenomena, and Cosmic Cataclysms
Abstract: High-energy astrophysics is a fast-developing area of astrophysical research dedicated to exploring the universe’s most powerful and extreme events. It involves investigating dense and energetic cosmic objects and phenomena, including black holes, neutron stars, supernova remnants, gamma-ray bursts, and active galactic nuclei. These sources emit radiation predominantly in the X-ray and gamma-ray regions of the electromagnetic spectrum and are often associated with high-energy particles, including cosmic rays and neutrinos. Investigating …
Published in International Journal of Universe · Vol. 2, Issue 1, 2026 · pp. 10–15 Read article
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A Comprehensive Review on Impact of Natural Selection Leading to Convergence
Abstract: This tale explores the complex relationship between genetic creativity, adaptation and common ecological problems that is arranged by the master sculptor, natural selection. Convergence reveals the adaptive genius that runs throughout the structure of evolution and is an acknowledgment to the continued power of natural selection. This journey aims to solve the enigma of convergent evolution. Natural selection has been influencing every link in the complex web of life on …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 14, Issue 1, 2024 · pp. 1–7 Read article
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Radiation-Resilient AI: Next-Generation Robotic Systems with Adaptive Machine Learning for Nuclear Facility Management
Abstract: The increasing complexity of nuclear facility operations, decommissioning activities, and emergency response scenarios necessitates the development of advanced autonomous systems capable of functioning in highly radioactive environments. This paper presents a comprehensive review of radiation-resilient artificial intelligence systems integrated with next-generation robotic platforms, specifically designed for nuclear facility management applications. We examine the convergence of adaptive machine learning algorithms, radiation-hardened hardware architectures, and intelligent robotic systems that can operate autonomously …
Published in Journal of Nuclear Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 12–21 Read article
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Radiation-Resilient AI: Next-Generation Robotic Systems with Adaptive Machine Learning for Nuclear Facility Management
Abstract: The increasing complexity of nuclear facility operations, decommissioning activities, and emergency response scenarios necessitate the development of advanced autonomous systems capable of functioning in highly radioactive environments. This paper presents a comprehensive review of radiation-resilient artificial intelligence systems integrated with next-generation robotic platforms, specifically designed for nuclear facility management applications. We examine the convergence of adaptive machine learning algorithms, radiation-hardened hardware architectures, and intelligent robotic systems that can operate autonomously …
Published in Journal of Thermal Engineering and Applications · Vol. 15, Issue 2, 2025 · pp. 12–21 Read article
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Physiographic, Climatic, and Hydrogeological Determinants of Urban Flooding in Bhopal: A Spatial Assessment
Abstract: Bhopal, capital city of Madhya Pradesh, is uniquely shaped by hilly terrain, lake systems, and complex hydrogeological characteristics, which historically supported efficient natural drainage. However, rapid urbanization, encroachment, and alterations in land use have increasingly disrupted these natural systems, amplifying the city’s susceptibility to urban flooding. The city’s physiography, defined by five major hills, undulating slopes, and a network of natural drainage channels, directs runoff toward low-lying zones that frequently …
Published in Journal of Water Resource Engineering and Management · Vol. 13, Issue 1, 2026 · pp. 25–32 Read article
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Classification and Detection of Brain Tumor using Convolutional Neural Network
Abstract: Tumors are masses created when brain cells multiply uncontrollably. A brain tumor is the medical term for this condition. Brain tumors are a serious and aggressive disease that can lead to a reduced life expectancy. Developing a treatment plan is essential to raising a patient's standard of living. Tumors in different regions of the body are evaluated using a variety of imaging techniques, with MRI pictures being utilized mostly for …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 8–13 Read article