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388 articles for “time complexity”
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Role of Modified Egg Membrane in Donor Site Wound Healing
Abstract: An ulcer is essentially a small gap or tear in the skin that struggles to heal properly, persisting either suddenly or over an extended period. These persistent ulcers can present significant challenges for individuals, prolonging their discomfort and recovery. Medical professionals employ various techniques to aid in healing, including using skin grafts from different body parts, specialized coverings, or temporary solutions to protect the wound.In our research, we explored an …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 2, 2024 · pp. 16–20 Read article
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An Overview of Artificially Generated Neural Networks Inside the Brain’s Structure in an Alzheimer’s Disease Patient
Abstract: Alzheimer’s disease produces significant neuronal loss, while the precise mechanisms and timing are yet unknown. Other types of cell death, such necroptosis, parthanatosis, ferroptosis, and cuproptosis, need further investigation. Based on brain images of people with mild cognitive impairment, this study assesses artificial neural networks (ANNs) used to diagnose and predict Alzheimer’s disease (AD). This research was conducted considering growing recognition among researchers and medical professionals regarding the importance of …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 2, 2025 Read article
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Dynamic Modeling and Simulation of Multi-Body Mechanical Systems: A Comprehensive Review of Methods, Tools, and Applications
Abstract: The dynamic modeling and simulation of multi-body mechanical systems (MBS) form a cornerstone in modern mechanical engineering, enabling in-depth analysis of the kinematic and kinetic behaviors of interconnected rigid and flexible components. MBS are foundational to a range of critical applications, from automotive suspensions and aerospace mechanisms to robotics and biomechanical structures. As system complexity and performance requirements increase, accurate and scalable modeling techniques are essential for both design validation …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 1, 2025 · pp. 35–42 Read article
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The Role of Simulation and Digital Twins in Enhancing Mechanical Production Efficiency: A Systematic Review
Abstract: In the evolving landscape of smart manufacturing, simulation technologies and digital twin (DT) systems have emerged as pivotal tools for enhancing the efficiency, agility, and sustainability of mechanical production processes. This systematic review investigates how the integration of simulations and DTs contributes to performance improvements across various stages of mechanical manufacturing—ranging from design and process optimization to predictive maintenance and real-time monitoring. While simulations provide the ability to model, test, …
Published in Journal of Production Research & Management · Vol. 15, Issue 2, 2025 · pp. 31–36 Read article
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Electronic Drones: Technology, Applications, and Future Directions
Abstract: Electronic drones, commonly referred to as Unmanned Aerial Vehicles (UAVs), have transitioned from exclusively military platforms to indispensable tools across commercial, scientific, industrial, and recreational domains. The rapid evolution of electronics, flight control systems, communication networks, onboard sensors, and artificial intelligence has reshaped drone capabilities, enabling high-precision remote sensing, autonomous navigation, swarm behavior, and integration into complex systems like the Internet of Drones (IoD). This paper examines the technological building …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 15–19 Read article
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The Interface of Hardware and Intelligence: The Function of Operating Systems
Abstract: Operating systems play a central role in bridging the gap between computer hardware and user interaction. They simplify complex machine-level operations and transform them into user-friendly and efficient digital experiences. At their core, operating systems are responsible for managing essential tasks such as process scheduling, memory allocation, file system organization, and device coordination. By handling these functions effectively, they ensure that hardware resources are used in an optimal and balanced …
Published in Journal of Operating Systems Development & Trends · Vol. 13, Issue 1, 2026 Read article
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Improving Polymer Composite Properties Through Reinforcement Learning Guided Prototyping A Novel Approach for Material Engineering
Abstract: Innovative approaches integrating reinforcement learning (RL) and machine learning (ML) into the fields of polymer composite prototyping and soft actuator manufacturing for applications. This new an algorithm utilizing RL optimizes polymer composite fabrication parameters to enhance material properties efficiently. By iteratively adjusting parameters based on predefined objectives, the RL agent guides the prototyping process, promising to revolutionize polymer composite engineering. A finest control method for locked loop control of Shape …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 208–218 Read article
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Recent Trends in Ocular Drug Delivery: Challenges and Approaches
Abstract: Drug topically regulation can be accessed most easily in the eye. When given topically as eye drops, medication ocular bioavailability is quite low. Drug entry into specific ocular locations is complicated by the complex anatomy and physiology of the human eye. Research has long been interested in the topical administration of successful treatments. To provide a suitable ocular penetration and extend the duration of drug residence is their challenging task. …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 11, Issue 3, 2024 · pp. 22–38 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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A Machine Learning-based Analysis of Climate Change
Abstract: Climatic variations are a pressing global challenge that demands immediate and comprehensive attention. A wealth of articles has been published on climate change mitigation and adaptation, yet there remains a need for innovative methods to explore the complexities of climatic variations and to devise more efficient and effective strategies for adjustment and alleviation. With technological advancements, machine learning (ML) and deep learning (DL) approaches have derived significant popularity across various …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 2, 2024 · pp. 1–10 Read article
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Machine Learning-Based Approach for Heart Disease Prediction
Abstract: Heart disease is a significant global health challenge, with early diagnosis and prediction being essential for reducing mortality rates. Machine Learning (ML), an efficiently developing field within Artificial Intelligence, provides innovative methods for analyzing complex clinical data to predict heart disease. This review examines the basic machine learning techniques, data, and metrics used in cardiovascular disease prediction. It explores the role of supervised learning, such as decision trees and logistic …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 64–73 Read article
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Advances in Biological Systems Modeling for Predicting Drug Effects in Chronic Disease
Abstract: Biological systems modeling has emerged as a promising tool for understanding and predicting the effects of drugs in the treatment of chronic diseases. Chronic diseases, such as diabetes, cardiovascular diseases, and neurodegenerative disorders pose significant challenges to traditional drug development due to their complex, multifactorial nature. Systems biology approaches, which integrate computational modeling with experimental data, provide a holistic view of disease mechanisms and treatment responses. This review explores recent …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 17–22 Read article
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Building Scalable Microservices with Micronaut, Kotlin, and AWS DynamoDB: A Comprehensive Architecture Study
Abstract: The evolution of enterprise software has trended steadily toward microservice architectures due to their inherent scalability and resilience advantages over monolithic systems. This research explores a comprehensive implementation approach using Micronaut, an innovative JVM-based framework specifically designed for resource-efficient microservices. The study combines Micronaut with Kotlin programming language and leverages AWS DynamoDB as a scalable NoSQL persistence layer, with Apache Kafka providing event-driven communication capabilities. We explore the critical role …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 2, 2025 · pp. 40–57 Read article
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Schizophenia – An Ayurvedic Review and Treatment – A Case study
Abstract: Schizophrenia is a complex, heterogeneous disorder. It is neuro developmental disorder characterized by problems with thinking (cognition),behavior- not focused on goals, negative symptoms, suicidal thoughts This means having a reduced or impaired ability to function normally and having noemotions(notmakingeyecontact,notchangingfacialexpressions,orspeakinginamonotone).Additionally, the person may lose interest in daily activities, withdraw from relationships, or be unable to sustain and reflection often associated with hearing or speech disorders, extreme confusion and associated functional impairments. …
Published in Research and Reviews : A Journal of Ayurvedic Science, Yoga and Naturopathy · Vol. 11, Issue 1, 2024 · pp. 40–48 Read article
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A Review of AI-Based Intrusion Detection Systems for Mobile Ad Hoc Networks (MANETs)
Abstract: Mobile Ad Hoc Networks (MANETs) comprise wireless networks that lack any conventional infrastructure . Their chief features include highly changing network topologies, lack of centralized administration, and open nature of communication, which collectively result in making MANETs of the wireless kind very susceptible to a diverse range of cyber-attacks like blackhole, greyhole, wormhole, flooding, Sybil and denial-of-service (DoS) among others. Conventionally, Intrusion Detection Systems (IDS) relying on static rule-based methods …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Animated Transient Response of High Voltage Power Line Towers Equipped with Nonlinear Footing Resistances
Abstract: This study focuses, among other objectives, on the use of animation techniques for visualizing the electromagnetic transients in high voltage power line towers. The model includes parameters such as the tower’s footing resistance and its location-dependent surge impedance. It describes the governing algebraic/partial differential equations expressed in terms of the current and voltage distributions as functions of time and location. The transients are assumed initiated by a lightning discharge of …
Published in Trends in Electrical Engineering · Vol. 14, Issue 1, 2024 · pp. 44–52 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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Optimal PMU Placement in Power Systems Using Graph Theory and PSAT
Abstract: Phasor measurement units (PMUs) play a vital role in modern power systems by delivering synchronized, real-time measurements. These devices enhance system reliability by supporting functions such as monitoring, protection, and control. By accurately capturing voltage and current phasors across different locations, PMUs enable better situational awareness and more effective decision-making in grid operations and management. Determining the optimal location of PMUs is essential to ensure system observability, reduce installation costs, …
Published in Trends in Electrical Engineering · Vol. 15, Issue 2, 2025 · pp. 26–32 Read article
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AI-Driven Pharmacogenomics and Precision Medicine: Future of Personalized Therapy
Abstract: Pharmacogenomics and artificial intelligence (AI) are emerging as important drivers of precision medicine, enabling healthcare systems to adopt individualized therapeutic approaches. Pharmacogenomics examines how genetic variations influence drug response, efficacy, metabolism, and toxicity, while AI provides advanced computational tools for analyzing complex genomic and clinical data. This review highlights the integration of AI-driven pharmacogenomics in personalized therapy and its potential to improve treatment outcomes. Machine learning, deep learning, natural language …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 1–12 Read article