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541 articles for “Computational methods”
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Mobile Technology for Libraries: Trends, Challenges, and Future Prospects
Abstract: Mobile technology has a great impact on both individuals and organizations. Over the time, the computational capabilities of these sophisticated technologies have become more accessible and reasonably priced. These technologies have an impact on how people choose to communicate, how they use and access the internet, and how they produce and consume content or services. Furthermore, these technologies have permeated the educational field and changed the way universities and other …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 3, 2025 · pp. 22–29 Read article
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Scaling of Machine Learning Techniques in Medical Imagining and Biomedical Applications Concerning Healthcare
Abstract: Machine learning refers to a field within computer science enabling computers to learn without explicit programming. Stemming from artificial intelligence's study of pattern recognition and computational learning theory, machine learning develops algorithms capable of learning from vast datasets and making predictions. Its applications span diverse computing tasks like email filtering, network intrusion detection, optical character recognition, and computer vision, where conventional algorithm design proves challenging. Notably, in computer vision, a …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 41–44 Read article
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Advances in Shell Programming: Techniques, Tools, and Emerging Trends
Abstract: Shell programming has undergone a significant transformation, shifting from simple command-line interactions to a mature, versatile scripting environment that supports modern computing needs. Over time, shells such as Bash, Zsh, and PowerShell have expanded far beyond basic task execution, evolving into powerful tools capable of handling complex automation workflows, system configuration tasks, and cross-platform orchestration. These environments now offer improved error handling, stronger security features, integrated performance-monitoring options, and more …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 3, 2025 Read article
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A Framework for Privacy-preserving AI Models in Cloud Computing: Challenges and Solutions
Abstract: The growing adoption of cloud computing for deploying artificial intelligence (AI) models has led to significant advancements in sectors such as healthcare, finance, and e-commerce. However, the integration of AI with cloud computing raises critical privacy concerns, particularly when handling sensitive data. This paper presents a comprehensive framework for implementing privacy-preserving AI models in cloud environments, addressing the unique challenges, and proposing effective solutions. The suggested framework employs advanced privacy-preserving …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 1–12 Read article
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Computational investigation of the influence of process parameters of 3D printed PLA material
Abstract: This study uses numerical simulation to examine the relationship between critical process parameters say, feed rate, layer height, and raster angle, on residual stresses and distortions and on the achievable density of FFF prints to identify the optimal input parameter combinations for ISO 527-2 type 1A. Methods of additive manufacturing that are utilised widely used to manufacture thermoplastic parts is fused filament fabrication. High residual stresses are one of the …
Published in Journal of Polymer & Composites · Vol. 12, Issue 1, 2024 · pp. 259–269 Read article
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Machine Learning in Nuclear Medical Applications: A Review of Research Frontiers
Abstract: Nuclear medicine, encompassing PET, SPECT, and targeted radionuclide therapy, generates high-dimensional, quantitative data uniquely suited for machine learning (ML) analysis. This review synthesizes current research applications of ML across six key domains. Positron emission tomography (PET), single-photon emission computed tomography (SPECT), and targeted radionuclide therapy are examples of nuclear medicine modalities that generate high- dimensional, quantitative datasets that are particularly well-suited for machine learning (ML)-driven analysis. These imaging methods provide …
Published in Journal of Nuclear Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 19–24 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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Intrusion Detection Using ANN Machine Learning for MIM, DOS, BO
Abstract: Intrusion detection system is a software program developed to use on computer systems so that it can identify intrusion attack with help of different techniques like the machine learning algorithms. The variety of assaults over the internet has multiplied through the years because of the development and smooth availability of computing technologies. Attackers develop new attack types, so in order to save you from those assaults, intrusion detection systems must …
Published in Journal Of Network security 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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LLM Evolution: Secrets and Disadvantages
Abstract: The advancement of large language models (LLMs) has initiated a significant transformation in artificial intelligence, with substantial effects on fields including natural language processing, machine learning, and human-computer interaction. This research examines the diverse improvements in LLMs, emphasizing significant milestones from early models such as GPT-2 to contemporary state-of-the-art designs. The investigation highlights the novel training methodologies, such as unsupervised learning and transfer learning, which have markedly improved the capabilities …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 1, 2025 · pp. 25–36 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
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Tb3+ activated Boro Phosphate Glass: Synthesis and Photoluminescence (PL) Characteristics
Abstract: The (40B2O3+ 3Al2O3+(10-x) P2O5 + xTb + 7ZnO+5LiCO3+ 10H6NO4P+25SrCO3) boro phosphate glass was successfully synthesized via melt quenching method. The structural confirmation is supported with X-ray diffraction (XRD) data and surface morphology was defined by scanning electron microscope (SEM). The (40B2O3+ 3Al2O3+(10-x) P2O5 + xTb+ 7ZnO+5LiCO3+ 10H6NO4P+25SrCO3) boro phosphate glass has been investigated for its Photoluminescence (PL) under UV excitation. At 544 nm, the excitation was observed, and at 222 …
Published in Journal of Polymer & Composites · Vol. 12, Issue 6, 2024 · pp. 43–47 Read article
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Identifying and Implementing a Machine Learning Model Suitable for Processing Visually Evoked Potential
Abstract: A Brain-Computer Interface (BCI) is a system that translates brain activity patterns into computer commands, bypassing physical movement. Electroencephalography (EEG) is commonly used to acquire signals in BCI research. Visual evoked potentials (VEPs) are brain responses in the visual cortex to visual stimuli. Recent studies show that exposing individuals to flickering at a consistent frequency generates EEG signals synchronized with the stimulation. Efficient extraction of VEP signals begins with preprocessing …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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Exploring The Multitarget Pharmacological Mechanism of Diabex for T2dm by Combining Network Pharmacology and Molecular Docking Techniques
Abstract: Objective: Hyperglycemia brought on by an absolute or relative absence of insulin synthesis or action characterises a set of illnesses known as diabetes mellitus. Chronic hyperglycemia in diabetes mellitus has been linked to organ damage, heart, and blood vessels. The persistent metabolic condition Diabetes is a severe global issue with negative social, health, and economic effects. It is a type of metabolism disorder that interferes with food digestion in the …
Published in International Journal of Bioinformatics and Computational Biology Read article
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Advancements in Humanoid Robot Locomotion: A Review of Control Strategies and Kinematic Models
Abstract: Humanoid robot locomotion has significantly improved over the past few decades, driven by improvements in control strategies and kinematic models. Researchers aim to develop robots that can walk, run, and navigate complex terrains with efficiency and stability. This review explores recent developments in humanoid locomotion, highlighting control strategies such as model predictive control, reinforcement learning, and central pattern generators. Additionally, it examines kinematic models, including inverted pendulum models and zero …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 1, 2025 · pp. 24–30 Read article
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Fault Diagnosis of Air Compressor (AC) System using Local Mean Decomposition (LMD) and Logistic Regression (LR) Machine Learning Classifier
Abstract: This article presents a detailed and systematic procedure for performing fault diagnosis in an air compressor (AC) system by analyzing the audio signals generated during its operation. The analysis covers both normal (healthy) conditions and seven distinct types of faults, including bearing failure, flywheel malfunction, inlet valve leakage, outlet valve leakage, non-return valve failure, piston ring defect, and rider belt issues. To acquire the acoustic signals, the researchers utilized a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 416–427 Read article
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Novel Perspectives in Quantum Safe Crypto algorithms for Enhanced Cyber Security
Abstract: This paper explores novel perspectives in quantum-safe cryptographic algorithms to bolster cybersecurity in the face of impending quantum computing advancements. Due to the efficient resolution of intricate mathematical problems by quantum computers, posing a substantial threat to existing cryptographic systems, there is a pressing requirement to create resilient alternatives. This study delves into innovative approaches, drawing from quantum-resistant cryptographic primitives, lattice-based cryptography, code-based cryptography, and hash-based cryptography. By examining the …
Published in International Journal of Computer Science Languages · Vol. 1, Issue 2, 2023 · pp. 18–22 Read article
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A Comprehensive Review of Machine Learning and Explainable AI Techniques for Disease Prediction Systems
Abstract: Large amounts of diverse medical data have been produced because of the quick development of digital healthcare systems, offering substantial chances to use machine learning methods for clinical decision support and illness prediction. By identifying intricate patterns in clinical data, machine learning-based models have shown great promise in early disease detection, risk assessment, and personalised healthcare. However, issues with transparency, interpretability, and reliability have been brought up by the growing …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 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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A Hybrid Algorithm for Processor Scheduling Using Game Theory Variants
Abstract: This study proposes a novel hybrid algorithm for processor scheduling in modern operating systems, integrating the strengths of traditional scheduling methods with game theory variants. Traditional schedulers often struggle to adapt to dynamic workload changes, leading to suboptimal performance. Our hybrid approach addresses this by treating processes as "players" in a game, where the "payoff" is CPU time. A base scheduler (e.g., Weighted Fair Queuing, Earliest Deadline First) provides a …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 48–56 Read article