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697 articles for “Computational Studies”
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Controlling Animals and People Near Railway Tracks Using the Internet of Things
Abstract: A lot of people are opting to use the train instead of the bus now as bus tickets have become so expensive. In order to keep the railroad network running well, it is necessary to constantly inspect and monitor the tracks. Till now, the train track inspection process and monitoring system are done manually, which is laborious and wasteful since human error is likely to happen at any point. Because …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 2, 2025 · pp. 01–10 Read article
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Air Flow Analysis in Sensor-Based Aircraft Wings Design
Abstract: Airflow analysis, at its core, is an application of fluid mechanics principles to the specific study of air movement. Airflow analysis plays a crucial role in diverse fields, impacting everything from the comfort of our homes to the efficiency of jet engines. The pursuit of more efficient, safer, and more responsive aircraft wings is a constant driver of innovation in the aerospace industry. The quest for more efficient, safer, and …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 2, 2025 · pp. 29–39 Read article
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Examining the Role of Synthetic Biology in Cellular Restoration Mechanisms
Abstract: Synthetic biology has emerged as a transformative field with the potential to revolutionize cellular repair mechanisms, offering innovative solutions to repair damaged DNA, stabilize proteins, regenerate tissues, and treat a wide range of diseases. By combining principles from genetic engineering, biotechnology, and computational biology, synthetic biology enables the design of cellular systems capable of performing functions that repair cellular damage and restore normal cellular processes. This article explores the application …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 19–29 Read article
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Evaluation of Small Vessel Disease by Advanced Brain Imaging
Abstract: Studying and comprehending brain small vessel disease requires extensive imaging. Recent applications of cutting-edge brain imaging techniques have led to the discovery of several significant results. Diffusion-weighted MRI studies have demonstrated the diagnostic accuracy of using clinical features alone or in combination with CT scan results to identify small vessel disease as the underlying cause is suboptimal in patients with acute lacunar syndromes. Acute infarcts caused by small vessel disease …
Published in International Journal of Cheminformatics · Vol. 2, Issue 1, 2024 · pp. 15–19 Read article
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In Silico Pharmacological Evaluation of Certain Commercially Available Terpenoids As Αlpha-Amylase Inhibitors for The Management of Diabetes Mellitus.
Abstract: The objective of this study was to investigate the α-amylase inhibitory activity of certain commercially available terpenoids using in silico docking studies. In this perspective, terpenoids like Abietane, Artemisinin, Carvone, Cucurbitane, Ferruginol, Lupeol, Nerolidol, Retinol, Sabinene, and Zingiberene were selected. Glibenclamide, a well-known antidiabetic drug was used as the standard. In silico docking studies were carried out using AutoDock 4.2, based on the Lamarckian genetic algorithm as the working principle. …
Published in Research and Reviews : Journal of Computational Biology Read article
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AI/ML-Based Approach to Solar Irradiance Prediction and Energy Suitability
Abstract: In this paper, due to challenges in precisely predicting solar irradiance, which is essential for solar power system optimization, we employed six diverse machine learning (ML) techniques: Linear Regression, Decision Tree, Random Forest, Gradient Boosting methods (including XGBoost), and Neural Networks—to analyze and predict outcomes using a dataset containing meteorological and temporal features. Key variables include wind speed, humidity, and temperature, which significantly influence the model’s predictive capability. Each method …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 3, 2025 · pp. 36–48 Read article
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Harmonic Elimination in Photovoltaic (PV) Systems Using Various Multilevel Inverter Topologies
Abstract: The increasing penetration of photovoltaic (PV) systems into modern power grids necessitates advanced power electronic interfaces capable of delivering high-quality electrical power with minimal harmonic distortion. Multilevel inverters (MLIs) have emerged as an effective solution due to their ability to synthesize near-sinusoidal output voltages with reduced switching losses and electromagnetic interference. This study presents a comprehensive investigation of harmonic elimination in grid-connected PV systems using 5-level, 7-level, and 11-level multilevel …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 01–18 Read article
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A Conceptual Framework for AI-Integrated Metabolomics in Predictive Health Systems for Resource-Constrained Environments
Abstract: The increasing prevalence of non-communicable diseases (NCDs) continues to place a significant strain on healthcare systems, particularly in low- and middle-income regions where access to early diagnostic infrastructure is limited. Conventional healthcare approaches remain largely reactive, often detecting diseases at advanced stages when treatment effectiveness is reduced. This challenge underscores the need for predictive, cost-effective, and data-driven healthcare solutions. This study presents a conceptual framework that integrates metabolomics with artificial …
Published in Emerging Trends in Metabolites · Vol. 3, Issue 2, 2026 Read article
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Advanced Anomaly Detection in Cloud Infrastructures Using Deep Learning Algorithms
Abstract: It is critical to guarantee the stability and security of cloud environments as cloud computing is becoming the backbone of contemporary IT infrastructures. Neglecting to quickly identify and resolve anomalies, which might point to security breaches, performance problems, or system breakdowns, can lead to disastrous outcomes. The increasing size and complexity of cloud infrastructures are challenging the effectiveness of traditional anomaly detection methods. These approaches often depend on rule-based systems …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 1–11 Read article
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The Integration of Machine Learning in VLSI IC Design
Abstract: It represents the first use of AI in the domain of integrating circuits, which has been impacted by it. The conventional VLSI design process that is now in use is replaced by this technology. The laborious manual concepts created by people have been replaced with automated design innovations. This development would trigger a profound change in the fields of AI education and hardware computation. With the introduction of contemporary chips, …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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IoT and Smart Sensors for Structural Health Monitoring: Trends, Challenges, and Future Directions
Abstract: Structural Health Monitoring (SHM) plays a critical role in ensuring the safety, resilience, and sustainability of civil infrastructure systems. In recent years, the convergence of Internet of Things (IoT) technologies and smart sensor systems has revolutionized the field of SHM. This integration enables continuous, real- time monitoring, facilitates predictive maintenance, and reduces the costs associated with structural inspections. IoT-based SHM frameworks leverage wireless sensor networks, cloud computing platforms, and intelligent …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 3, 2025 · pp. 1–6 Read article
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A Comprehensive survey of robust image quality metrics for satellite imagery
Abstract: Satellite imagery is essential for applications like environmental monitoring, urban development, precision agriculture, defence surveillance, and disaster response. The reliability of these applications is closely tied to the quality of the captured images, which may be compromised by atmospheric effects, sensor imperfections, compression artifacts, and transmission noise. As a result, accurate image quality assessment (IQA) is essential to ensure trustworthy analysis and informed decision-making in satellite-based systems. The distinctive properties …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 1, 2026 · pp. 7–20 Read article
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Application of Resource Allocation Similarity Based Link Prediction in Wireless Networks
Abstract: Link prediction in wireless networks plays a crucial role in predicting missing connections within multiplex networks. This study focuses on the utilization of similarity-based link prediction methods in wireless networks. These methods assume that the likelihood of linkage between nodes is determined by their similarity, based on shared features. Several similarity measures, such as Common Neighbors (CN), Preferential Attachment (PA), Adamic-Adar (AA), and Resource Allocation (RA) indices, are commonly employed …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 2, 2023 · pp. 37–42 Read article
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Molecular Docking of Nigella Sativa Phytocompound as Inhibitors of Transcription Factors NF-KB Implicated in Rheumatoid Arthritis
Abstract: Objectives: Nigella sativa, a plant considered around the world as the most treasured nutrient-rich herb for centuries together in different civilizations, is exceptionally known for its high levels of antioxidant properties. Free radical intensification due to oxidative stress plays a key role in the pathogenesis of rheumatoid arthritis by activating the NF-KB protein that regulates the expression of the genes involved in inflammation. Methods: This study involves in-silico approach to …
Published in International Journal of Molecular Biotechnological Research · Vol. 2, Issue 2, 2024 · pp. 42–55 Read article
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Nitro IDE: Exploring Integrated Development Environments: Current Trends and Innovations
Abstract: Integrated Development Environments (IDEs) have become essential in modern software development, offering a centralized platform that brings together source code management, debugging tools, version control, and compilation features. This study offers an in-depth analysis of various IDE platforms, with a particular focus on Eclipse as a widely used open-source integration environment. It also explores specialized IDEs tailored for embedded systems and enterprise-level Java (J2EE) application development. Additionally, the study examines …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 35–40 Read article
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The Emergence of Personal Desktop Voice Assistants for Effortless Task Management
Abstract: In an era defined by rapid technological advancement, desktop voice assistants have emerged as crucial tools, not only for enhancing productivity but also for fundamentally reshaping digital interactions. This study delves into the transformative potential of voice-enabled artificial intelligence in task automation, emphasizing its profound impact on efficiency, accessibility, and overall user experience. By harnessing the power of natural language processing and machine learning, these desktop assistants facilitate hands-free operation, …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 3, 2025 · pp. 11–16 Read article
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Study on the Profile and Flow Field Variation of Parachute Coating by Seven-hole Probe Method
Abstract: In general, the parachute test is a long test cycle, expensive, and difficult to measure with accuracy, which makes it a very laborious and time-consuming task. Therefore, attempts have been made to overcome this by using a parachute test stand or by simulation, but in our country, there is no numerical simulation of the parachute and there is no research on it. In this paper, the variation of the shape …
Published in Journal of Aerospace Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 26–37 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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Advancements in Agricultural Forecasting: A Review of Machine Learning Based Crop Yield Prediction
Abstract: Agricultural productivity plays a critical role in global food security, and accurate crop yield prediction is essential for optimizing resource allocation and decision-making in farming. The rapid advancements in Machine Learning (ML) and Deep Learning(DL)have transformed agricultural forecasting, enabling data-driven approaches for crop prediction. This review paper provides a comprehensive analysis of various ML and DL techniques applied in crop yield forecast, highlighting the ineffectiveness, challenges, and future directions. The …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 32–38 Read article
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Productivity Estimation of any Manufacturing Industry Using Fuzzy Logic in MATLAB Software
Abstract: In every industry/organization Labor Productivity plays a major part in the overall growth and production. Many time it is observed that industries do not attain their desired goals due to poor labor productivity. Labor Productivity is dependent on many different factors like Delay in Payment, management supervision over workers, proper work planning and scheduling, poor site safety program, lack of financial motivation system, etc. In this study, we estimated labor …
Published in International Journal of Manufacturing and Production Engineering · Vol. 2, Issue 2, 2024 · pp. 1–14 Read article