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697 articles for “Computational Studies”
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Role of the Surgical-Ward Nurse in Identifying, Escalating, and Managing Postoperative Anastomotic Leak in Colorectal Patients: A Narrative Synthesis in an Australian Nursing Perspective
Abstract: Purpose: Postoperative colorectal anastomotic leak (AL) is one of the most feared complications after colorectal surgery because of its association with sepsis, reoperation, mortality, prolonged hospital stay, delayed adjuvant therapy, and permanent stoma formation. This narrative practice review outlines the frontline role of surgical-ward nurses in the early identification, escalation, and interim management of AL within the Australian acute-care context. Methods: A narrative synthesis of contemporary consensus statements, systematic reviews, …
Published in Research and Reviews : Journal of Surgery · Vol. 15, Issue 1, 2026 · pp. 7–12 Read article
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The Kinectics of Petroleum Hydrocarbon Degradation in Soil: The Concept of Ponderosa Lemon Integrity as Bio-stimulant
Abstract: The kinesics of petroleum hydrocarbon degradation in soil: the concept of ponderosa lemon integrity as bio-stimulant with respect to the impact of preparation condition of room and sun-dried was monitored. The kinetic values of the effect of the biostimulant dosage were monitored and the data obtained from the experimental investigation was useful in the computation of the maximum specific rate of the substrate degradation and the dissociation constant of the …
Published in Journal of Petroleum Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 22–32 Read article
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Exploring the Therapeutic Potential of Phytochemicals in Aloe Barbadensis Miller Through Molecular Docking for Ulcerative Colitis Management
Abstract: Ulcerative colitis (UC) is a chronic inflammatory bowel disease characterized by mucosal inflammation of the colon, often associated with immune dysregulation and oxidative stress. Natural compounds have gained significant attention as alternative therapeutic agents due to their efficacy and minimal side effects. Quercetin, a flavonoid abundantly found in Allium cepa (onion), has demonstrated potent anti-inflammatory and antioxidant properties. This study employs an in silico approach to evaluate the therapeutic potential …
Published in Research & Reviews: A Journal of Pharmacognosy · Vol. 13, Issue 1, 2026 · pp. 06–12 Read article
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Robotic Arm Vision Systems: Advances and Applications in Manufacturing Automation
Abstract: Robotics might be defined more practically as the study, development, and use of robot systems for industry. The first industrial robot was made by George Charles Devol, who is commonly regarded to as the father of robotics. Their absolute precision can range from several mms (±5–10 mm, ±0.5–1.8 mm) due to mechanical tolerances, elasticities, temperature, and other factors. Historically, their position can be altered frequently with a modest repeatability error …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 1, 2024 · pp. 38–44 Read article
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A Comprehensive Analysis of Machine Learning Models for Credit Card Fraud Detection
Abstract: This paper presents an indepth comparison of various machine learning models—Logistic Regression, Support Vector Classification (SVC), and Neural Networks (NN)—in the context of credit card fraud detection. The analysis spans multiple performance metrics, including accuracy, F1 score, precision, recall, and computational efficiency. Logistic Regression demonstrates competitive performance in terms of accuracy, but its poor precision renders it unsuitable for fraud detection tasks. Conversely, the Neural Network exhibits balanced precision and …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 Read article
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Enhancing Worker Comfort in High-Heat Environments: A Triangular Bladeless Cooling Fan Approach
Abstract: Workers in high-heat industrial environments frequently encounter thermal stress, fatigue, and dehydration, which significantly impact both productivity and safety. Existing cooling solutions such as pedestal fans, ceiling fans, and central air-cooling systems often fall short due to limited airflow reach, safety concerns from exposed blades, high energy consumption, and poor suitability for dynamic workshop layouts. To address these challenges, this study presents a novel triangular bladeless fan designed specifically for …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 25–31 Read article
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A Factorial Investigation of Hyperparameter Tuning Strategies for Lasso- Based Genomic Prediction
Abstract: In an earlier comparative study of machine-learning methods for genomic prediction of wheat grain yield, we reported a counter-intuitive result: automated nested-cross-validation tuning of the Lasso regularization penalty reduced mean predictive ability relative to a fixed, arbitrarily chosen penalty (mean Pearson r falling from 0.408 to 0.349 across four environments), the opposite of the expected effect of hyperparameter tuning. We hypothesized two possible explanations at the time — high-variance penalty …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article
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Coupled Magneto–Thermal–Diffusion Transport in an Unsteady Maxwell Polymer Fluid with Activation Energy over a Porous Stretching Surface
Abstract: The present study investigates the combined effects of activation energy and diffusion-thermo (Dufour) processes on unsteady magnetohydrodynamic (MHD) flow, heat, and mass transfer of a Maxwell viscoelastic fluid past a porous exponentially stretching vertical sheet. The electrically conducting and incompressible polymeric fluid flows through a saturated porous medium under a transverse magnetic field. The governing momentum, energy, and concentration equations are transformed into nonlinear ordinary differential equations using similarity transformations …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 581–590 Read article
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A Novel Direct Weighted Deviation (DWD) Method for Agricultural Enterprise Selection: A Case Study of Namakkal District, Tamil Nadu
Abstract: The study proposes a novel Direct Weighted Deviation (DWD) method for Multi-Criteria Decision Making (MCDM) by eliminating normalization, distance metrics, and pairwise comparisons. DWD is thereafter used to evaluate and select ten rainfed agricultural enterprises against ten generic and context-specific viability criteria in Namakkal District, Tamil Nadu, a water-scarce region in India. Subsequently, other methods (AHP, SAW, WPM, and TOPSIS) are used to obtain a comparative second opinion and validate …
Published in International Journal of Industrial and Product Design Engineering · Vol. 4, Issue 1, 2026 · pp. 1–7 Read article
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Polymers for Sustainable Energy Generation: Advancing Green Building Technologies
Abstract: Implementing technologies for sustainable energy generation is essential to promote green building and minimize environmental effects. Owing to their diverse properties, polymers have gained immerging prominence in improving the efficiency and functionalities of various energy systems. Thermal energy storage Exploring the potential usage of polymers in energy generation for green buildings 1. The goals include assessing the performance and efficiency of polymer-based alternative technologies, while also investigating their environmental and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 339–348 Read article
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Real-Time System Monitoring and Resource Optimization Using Shell Scripts in UNIX/Linux Environments
Abstract: Real-time system monitoring is a fundamental aspect of system administration in UNIX/Linux environments, as it ensures optimal system performance, reliability, and continuous availability of services. In modern computing infrastructures, systems are expected to operate efficiently under varying workloads, and any degradation in performance, such as CPU overload, memory exhaustion, disk bottlenecks, or network congestion, can significantly impact user experience and system stability. Regular observation and prompt action are crucial for …
Published in Journal of Advances in Shell Programming · Vol. 13, Issue 1, 2026 · pp. 08–15 Read article
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Identification of Papaya Fruit Ripening Process Using AI
Abstract: Identifying the ripening process of papaya fruit using artificial intelligence involves employing machine learning algorithms to analyze various features such as color changes, texture alterations and chemical compositions. This model is capable of analyzing visual cues to determine the stage of ripeness. The dataset compares images of papaya at various ripening stages, and our AI model demonstrated high accuracy in classifying these stages. Employing machine learning algorithms and image processing …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 13, Issue 2, 2024 · pp. 23–30 Read article
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The Evolution and Impact of Numbers: From Ancient Tallies to Quantum Computing: Review Article on Numbers
Abstract: Numbers are among the most fundamental constructs in human civilization, serving as the backbone of mathematics, science, technology, and virtually every aspect of daily life. They represent not only quantities and measures but also relationships, structures, and patterns that underpin the fabric of human understanding. From the earliest tallies etched on bones by prehistoric humans to the sophisticated numerical systems embedded in today’s artificial intelligence and quantum computing, the evolution …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 3, 2025 · pp. 15–19 Read article
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Assessing the Performance of DL Methods in Handwritten Digit Recognition
Abstract: Handwritten digit recognition is a computer vision task that involves the automatic identification and classification of hand-written digits. The objective is to develop models capable of accurately recognizing and distinguishing digits handwritten by humans. With the development of machine learning and deep learning techniques, this field has advanced remarkably. The convolutional neural network (CNN) is the most often used technique for this purpose. By utilizing CNN, the model can learn …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 1, 2023 · pp. 25–32 Read article
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The Importance of DNA Profiling Today
Abstract: DNA profiling has changed a lot of sectors, from health and criminal justice to ancestry research and animal conservation. It is one of the most important scientific instruments of our time. This technique makes it possible to identify people, analyse family relationships, and learn more about biology by looking at unique genetic markers in a person's DNA. DNA profiling has changed the way forensic science works by making it easier …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 4, Issue 1, 2026 Read article
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Real-time Operating Systems in the Era of IoT: Challenges and Solutions for Time-Critical Applications
Abstract: Real-time operating systems (RTOS) are essential in the Internet of Things (IoT), as they ensure timely responses to events, which is critical for the performance and reliability of connected devices. This paper delves into the unique challenges faced by RTOS in IoT environments, highlighting issues such as limited computational resources, strict latency requirements, and the increasing need for robust security mechanisms. The resource constraints inherent in many IoT devices, which …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 13–24 Read article
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The Role of Adaptive Filters in Enhancing Acoustic Echo Cancellation Efficiency in Noisy Environments
Abstract: The novel approach that this work discusses is a DCD-based iterative learning filter approach improved with deep learning methodologies, designed to improve the efficiency of acoustic echo cancellation. The proposed system can really manage both linear and nonlinear echo scenarios, dynamically adapting to fluctuating acoustic environments. The above comparative evaluations with standard filter, the standard RLS filter, indicate that the mean square error, and the standard deviation of the correlation …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 2, 2024 · pp. 9–24 Read article
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Personalized Virtual Interior Design Using Generative AI
Abstract: This study presents an AI-driven virtual interior design system that allows users to effectively redesign their home or workspace with an integrated shopping experience. The system tailors designs according to room type, style, and purpose, ensuring that the created layouts are aesthetically pleasing, well-organized, and functional. In contrast to conventional interior design, which involves professional skill, hand labor, and much time consumption, this AI-based method uses technology to automate fundamental …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 07–12 Read article
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IoT-Based Real-Time Weather Monitoring System
Abstract: In the evolving landscape of the Internet of Things (IoT), real-time environmental monitoring has become increasingly vital across various domains, including agriculture, smart cities, and climate research. This study presents the design and implementation of an IoT-based real-time weather monitoring system that utilizes the ESP32 microcontroller in conjunction with AWS cloud services. Temperature and humidity data are captured using onboard sensors and transmitted using the MQTT protocol to AWS IoT …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 14, Issue 3, 2025 · pp. 19–25 Read article
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Modeling Dispersed Count Data: Evaluating the Conway–Maxwell–Poisson Regression with COVID-19 Mortality Data
Abstract: Count data are prevalent in diverse fields such as biology, healthcare, psychology, and marketing, characterized by non-negativity and inherent heteroskedasticity, often exhibiting overdispersion or underdispersion. Traditional Poisson regression, which assumes equal mean and variance, is inadequate for such dispersed data. To address this, various generalized linear models (GLMs) and their extensions, including negative binomial (NB) and Conway–Maxwell–Poisson (CMP) regressions, are utilized. This study evaluates the performance of CMP regression compared …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 3, 2024 · pp. 18–26 Read article