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159 articles for “Computational methods”
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Different Aspects and Processes in 3D Printing: An Overview
Abstract: 3D Printing or Additive manufacturing produces actual items from geometric representations by layering on materials one after the other. 3D printing is a rapidly developing technology. These days, 3D printing is employed all over the world. The application of 3D printing technology is expanding in the fields of agricultural, healthcare, automotive, locomotive, and aviation. It is utilized for mass modification and fabrication of various open-source designs. An object can be …
Published in International Journal of Manufacturing and Production Engineering · Vol. 2, Issue 1, 2024 · pp. 24–30 Read article
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From Differential Equations to Data Science: A Survey on Analytical Methods in Contemporary Problems
Abstract: The integration of differential equations and data science methods represents a dynamic and evolving approach to solving contemporary challenges across a wide range of disciplines, including engineering, physics, biology, economics, and finance. Differential equations have long served as fundamental tools for modeling continuous systems and processes, offering powerful insights into the behavior of natural and man-made phenomena. For example, they describe how heat diffuses through materials, how populations grow in …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 1–6 Read article
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The Role of Artificial Intelligence in Enhancing Athlete Performance and Training Strategies
Abstract: Artificial Intelligence (AI) is transforming modern sports by improving athlete performance, training methods, and decision-making processes. The integration of AI technologies such as machine learning, data analytics, wearable sensors, and computer vision has enabled coaches and sports scientists to analyze large amounts of performance data with greater accuracy and efficiency. Athletes' physiological indicators, movement patterns, injury risks, and recuperation processes are all monitored by these technology. Training regimens can therefore …
Published in Recent Trends in Sports · Vol. 3, Issue 2, 2026 · pp. 1–7 Read article
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A Review on Artificial Intelligence Techniques for Analyzing Deforestation and Illegal Logging Using Satellite Imagery
Abstract: Deforestation and illegal logging remain critical environmental threats, driving biodiversity loss, climate change, and socio-economic disruption. Conventional monitoring techniques frequently do not yield real-time, large-scale insights. Recent developments in Artificial Intelligence (AI), especially in deep learning and computer vision, have revolutionized the ability to analyze high-resolution satellite images for detecting deforestation and monitoring illegal logging. This review synthesizes recent developments in AI-driven approaches, highlighting convolutional neural networks (CNNs), anomaly detection …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
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Facial Emotion Detection and Its Applications
Abstract: Facial emotion detection (FED) is an interdisciplinary field that integrates artificial intelligence, computer vision, and machine learning to recognize and interpret human emotions based on facial expressions. The development of FED systems has been propelled by advancements in deep learning, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which enhance recognition accuracy. Feature extraction techniques, including geometric and appearance-based methods, play a crucial role in classifying emotional states. …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 8–12 Read article
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Data Privacy in AI: Securing the Sensitive Information Through Homomorphic Encryption
Abstract: Artificial intelligence (AI) technology increasingly relies on sensitive user data, particularly finance and healthcare. While legacy encryption technologies safeguard data in transit and at rest, they are of no use when data must be decrypted to be processed. This is a bleak privacy threat, particularly in AI applications that call for constant processing of data. The objective of this study is to apply homomorphic encryption, a feature in which operations …
Published in International Journal of Information Security Engineering · Vol. 3, Issue 2, 2025 · pp. 25–30 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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Effect of Nebulization With 3% Hypertonic Saline for Airway Clearance on Mechanically Ventilated Patients Admitted in ICUs of Pt. B.D. Sharma, PGIMS, Rohtak
Abstract: Background of the Study: The ability to breathe artificially prolongs life in many situations. Patients requiring mechanical breathing in the intensive care unit are more likely to have complications and even death due to a variety of interconnected causes. As a result, it became critical to rapidly ventilate in the safest and most efficient manner available. Intubated patients have benefited from nebulized suctioning, as it improves lung clearance and decreases …
Published in International Journal of Emergency and Trauma Nursing and Practices · Vol. 1, Issue 2, 2023 · pp. 20–27 Read article
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Procedure for Conventional Facial Emotion Detection Algorithms Based on Machine Learning
Abstract: Researchers in psychology, computer science, linguistics, neurology, and allied fields have become more interested in a human-computer interface system for autonomous face recognition or facial expression recognition. This study has recommended an Automatic Facial Expression Recognition System (AFERS). The proposed methodology consists of face detection, feature extraction, and facial expression identification processes. The initial phases of the face detection procedure include skin color identification using the YCbCr color model, illumination …
Published in International Journal of Electronics Automation · Vol. 1, Issue 1, 2023 · pp. 07–13 Read article
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Data Representation and Abstraction in Computer Systems: An Interactive Study
Abstract: Data abstraction simplifies data, while data representation stores or encodes it. Data abstraction in programming involves constructing a data type that hides data representation. This lets consumers concentrate on the data’s primary features rather than its implementation. Data abstraction is common in object-oriented programming and database administration. Computers store data in binary format. The smallest binary unit is a bit, or “binary digit”. Bytes typically have eight bits. Data abstraction …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 2, 2024 · pp. 22–31 Read article
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Land surface dynamics: A Multiphysics Approach to Modeling Mass Transport
Abstract: Land surface dynamics are governed by complex interactions among hydrological, atmospheric, and geomorphological processes that collectively drive the transport of mass across terrestrial environments. Traditional modeling approaches often isolate individual mechanisms, limiting their ability to capture the coupled feedbacks that shape landscape evolution. This study presents a multiphysics framework for modeling mass transport on land surfaces, integrating fluid flow, sediment transport, heat exchange, and chemical reactions within a unified computational …
Published in International Journal of Land · Vol. 2, Issue 2, 2025 · pp. 31–36 Read article
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Microstructural Design and Functional Properties of Polycrystalline Materials
Abstract: Polycrystalline materials, composed of an aggregate of crystallites or grains, are foundational to modern engineering applications due to their versatile functional properties. The microstructural design—encompassing grain size, shape, orientation, phase distribution, and grain boundary characteristics—plays a pivotal role in determining mechanical, thermal, electrical, and magnetic behavior. This abstract explores the intricate relationship between microstructure and functionality, emphasizing how tailored processing techniques such as thermomechanical treatments, sintering, and additive manufacturing can …
Published in International Journal of Crystalline Materials · Vol. 2, Issue 2, 2025 · pp. 16–20 Read article
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In Silico Prediction of Multitarget Mechanism of Quinoline and Its Analogs on Phosphoinositide-3-Kinase Pathway Proteins
Abstract: Objective: Phosphoinositide 3-kinases (PI3Ks), the target of rapamycin (PI3K/Akt/mTOR, PAM), are a family of enzymes that play a role in the growth, proliferation, differentiation, motility, survival, and intracellular trafficking of cells, all of which are essential for healthy cellular function and are also connected to cancer. In this study, quinoline and its derivatives were employed to analyze its inhibition activity on the phosphoinositide-3-kinase pathway. Methods: In this work, eight phytocompounds …
Published in International Journal of Molecular Biotechnological Research · Vol. 1, Issue 1, 2023 · pp. 57–76 Read article
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Semantics Analysis of Expected Goals in Soccer Data Using Machine Learning
Abstract: In recent years, the increasing availability of soccer data has greatly enhanced the accuracy and depth of player performance evaluation. Soccer, being one of the most popular sports worldwide, attracts millions of fans due to its simple rules, minimal equipment requirements, and high entertainment value. However, analyzing an entire match manually can be time-consuming, leading to a growing demand for automated methods that can summarize and interpret game data efficiently. …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 31–47 Read article
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Optimized Machine Learning Framework for Battery State Prediction in Smart Charging Systems
Abstract: Good estimation of battery states, including State-of-Charge (SoC), State-of-Health (SoH), and Remaining Useful Life (RUL), are important in managing energy wisely and controlling the adaptive charging. This work introduces a streamlined machine learning model based on the ability to use multi-dimensional sensor measurements in terms of voltage, current, temperature, and cycle number to forecast battery conditions with high accuracy. Decent preprocessing, such as noise elimination, feature scaling, and calculated features, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 11–23 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
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Optimizing Power Generation from Building Ventilation Systems: A Study on Exhaust Fan Efficiency
Abstract: Due to population growth, the world's energy consumption has increased dramatically in both wealthy and developing nations in recent years, and by 2042, it is predicted to have doubled or more. Since a few years ago, the use of innovative sustainable power sources to meet energy demands has been gradually increasing. We've chipped away at a different idea because of this. As an alternative energy source, renewable energy (RE) resources …
Published in International Journal of Electrical Power and Machine Systems · Vol. 1, Issue 2, 2023 · pp. 22–27 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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Exploring the Therapeutic Potential of Grapeseed Phytoconstituent Through Molecular Docking Analysis for Multiple System Atrophy Treatment
Abstract: Objective: Alpha-synuclein (α-Syn) aggregates are a common neurodegenerative disorder associated with Parkinson’s disease and multiple system atrophy (MSA). As a fruit that is extensively grown, grapes have several pharmacological advantages when it comes to reducing oxidative stress. Research has indicated that grape seed phytoconstituents have a major effect on α-Syn. The objective of this study is to inquire into the pharmacological characteristics and potential therapeutic applications of grape seed derivatives …
Published in International Journal of Molecular Biotechnological Research · Vol. 2, Issue 2, 2024 · pp. 14–26 Read article
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Valeton Phytoconstituents from Curcuma Phaeocaulis as Prion Protein Mutant V210I Inhibitors: A Computational Docking and Virtual Screening Study
Abstract: Objective: Creutzfeldt-Jakob disease (CJD), a neurological disorder that is sporadic, fatal, communicable, and worsens rapidly, is caused by abnormal folding of prion proteins. Identifying and assessing the potential of phytocompounds from the Curcuma phaeocaulis Valeton plant as a new therapeutic candidate aimed at the treatment of CJD is the objective of this research article. Methods: In this experiment, we assessed outcomes following an in-silico assessment to design a new oral …
Published in International Journal of Biochemistry and Biomolecule Research · Vol. 1, Issue 2, 2023 · pp. 1–16 Read article