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475 articles for “computational analysis”
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IoT Integration in Sustainable Agriculture
Abstract: The increasing demand for food production, environmental concerns, and resource limitations have necessitated the adoption of Internet of Things (IoT)-based innovative farming solutions. The current paper introduces an IoT-based system that integrates hydroponics, aquaponics, and poultry to promote sustainability, resource utilization, and agricultural productivity. Conventional farming practices are riddled with ineffective use of resources, uncertain environmental effects, and expensive operations. The new system facilitates real-time monitoring, automated decision support, and …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 69–84 Read article
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Research Paper A Review of Symmetry in Mechanical Systems: Theoretical Systems Foundations and Engineering Applications
Abstract: In mechanical system analysis and design, symmetry is of mechanical systems. This article examines the idea of symmetry in mechanical systems, exploring its mathematical foundations (such as Lie algebras and group theory) and how these ideas help explain the behavior, stability, and control of the system. We explore the applications of symmetry in a range of mechanical systems, from basic mechanical connections to intricate multi-body dynamics, emphasizing the benefits of …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 1, 2025 · pp. 15–19 Read article
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Predicting Multiple Diseases Using Machine Learning: A Data-Driven Approach
Abstract: The increasing prevalence of chronic and life-threatening diseases highlights the need for innovative healthcare solutions that enable early detection and proactive management. The Multiple Disease Prediction Platform is a web-based system utilizing machine learning (ML) and deep learning (DL) algorithms to analyze user-inputted health data, generating real-time predictions of potential health risks. By leveraging Python’s Streamlit library, the platform provides an interactive and accessible diagnostic experience, eliminating the need for …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 16–35 Read article
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Multi-Objective Optimization of Polymer-Based Functionally Graded Composites for Lightweight Structures
Abstract: Functionally graded composites (FGCs) improve lightweight structural performance by allowing material properties to change smoothly across a component. Polymer-based FGCs (P-FGCs), in particular, are gaining prominence in aerospace, automotive, and biomedical industries due to their excellent strength-to-weight ratio, tunability, and ease of processing. However, optimizing these materials for lightweight structural applications requires addressing conflicting design objectives, such as maximizing stiffness while minimizing weight or enhancing thermal resistance while maintaining manufacturability. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 961–973 Read article
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From Noise to Insight: An Academic Study of Electrical Signal Processing
Abstract: Electrical signal processing is very important for turning raw, often noisy data into useful and actionable information. This article gives a simple and easy-to-understand summary of the basic ideas and methods used in electrical signal processing, such as filtering, signal representation, modulation, and spectrum analysis. The focus is on how to effectively eliminate noise and interference to improve the quality and dependability of signals. The conversation connects ideas from theory …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 Read article
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The Molecular Structure of Chemical Compounds by using Quantitative Calculations in Chemistry
Abstract: Computational chemistry has its roots in the early attempts of theoretical physicists, beginning in 1928, to solve the Schrödinger equation using mechanical calculating machines. These calculations verified that the solutions of the Schrödinger equation quantitatively reproduced experimentally observed properties of simple systems such as the helium atom and the hydrogen molecule. These approximate solutions of larger systems and exact solutions of simple model problems allowed chemists and physicists to provide …
Published in Journal of Catalyst & Catalysis · Vol. 12, Issue 2, 2025 · pp. 01–08 Read article
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Comparative Analysis of AI-Based Approach vs. Traditional Methods in Climate Modeling
Abstract: Climate modeling helps to predict the future of climate variations and human interference with environment. The traditional General Circulation Models (GCMs) are based on physics-derived mathematical equations but are very expensive in terms of computation. There are alternative ways to perform climate modeling in recent years with the rise and improvement of Artificial Intelligence (AI) based approaches in term of predictability, efficiency, and classification of extreme events compared to conventional. …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 26–32 Read article
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Enhancing Data Processing and Storage in Computing Environments: A Survey on the Use of NVMe SSDs
Abstract: In the current era of fast pace technological growth, the efficiency of data processing and storage systems has become a key factor of various computing environments. This survey explores the transformative role of Non-Volatile Memory Express (NVMe) Solid-State Drives (SSDs) across different domains, including Big Data processing, Cloud Computing, High Performance Computing (HPC), and containerized applications. The motivation behind this comprehensive review is to understand how NVMe SSDs, known for …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 3, 2025 · pp. 01–21 Read article
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A Comparative Analysis of Machine Learning Techniques for Fruit Defect Detection Systems
Abstract: With evolving technologies in machine learning, significant advancements have been made in the livestock industry, helping to reduce waste, increase yield, achieve cost savings, and improve competitiveness in the marketplace. Fruit defect detection models support precision agriculture by providing valuable data for decision-making and enhancing overall efficiency through automated inspection processes. This study implements and comparatively evaluates machine learning models including MobileNetV2, a custom-designed convolutional neural network (CNN) model, ResNet50, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 37–47 Read article
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Recognition and Detection of Content in Video Using OpenCV
Abstract: The emergence and continued reliance on the Internet and related technologies has resulted in massive amounts of data that can be analysed. Humans, on the other hand, do not have the cognitive abilities to comprehend such vast amounts of data. Machine learning (ML) is a mechanism that enables humans to process large amounts of data, gain insights into the data's behaviour, and make more informed decisions based on the analysis's …
Published in International Journal of Image Processing and Pattern Recognition Read article
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Comparative Study of Facial Spoofing Detection using CNN Architecture
Abstract: Facial recognition systems face a high risk of security breach due to various facial spoofing attacks. This challenge was addressed by the study of several deep learning models. This study proposes an idea to detect facial spoofing using deep learning architecture to differentiate live faces form various types of spoofed images/videos using different CNN models. In addition, the study seeks to strengthen security measured in facial recognition system demonstrating that …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 3, 2024 · pp. 9–17 Read article
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Structural Performance Evaluation of Circular Perforated Plates under Mechanical Loading
Abstract: Circular perforated plates are structurally critical components in aerospace, automotive, and marine sectors, where perforation-induced stress concentrations govern failure under mechanical loading. This study conducts a systematic finite element analysis of stress distribution, deformation, and interlaminar behavior in aluminum and glass-epoxy laminates ([−45/45/90/0]S and [−45/45/90/0]AS) under uniform transverse pressure with clamped-free boundary conditions. Four perforation configurations—no hole, central hole, single-series, and 25-hole grid—were evaluated using ANSYS Shell-181, verified against Kirchhoff–Love, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 1–20 Read article
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Design and Implementation of 256-bit Vedic Multiplier on Reconfigurable Platform
Abstract: Multiplication is a fundamental arithmetic operation in digital signal processing and embedded systems. Traditional multiplier architectures often suffer from increased latency and resource utilization when scaled to higher bit widths. Vedic Mathematics, an ancient Indian technique, offers a novel and efficient alternative. This paper presents the design and implementation of a 256-bit Vedic multiplier using the Urdhva Tiryakbhyam Sutra on a reconfigurable hardware platform, specifically FPGA. The proposed architecture decomposes …
Published in Journal of Materials & Metallurgical Engineering · Vol. 15, Issue 3, 2025 · pp. 56–65 Read article
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Acoustic Sensing for City Flow: Quasi-Supervised Recognition of Sirens and Traffic for Urban Mobility Intelligence
Abstract: This paper frames environmental audio as a mobility telemetry source, extending a benchmark urban-sound corpus with transportation-critical classes—ambulance, firetruck, police, and traffic—and training spectrogram-based models under a quasi-supervised regime to support real-time city operations; leveraging 10-fold protocols, class-weighted objectives, and audiospecific augmentations (time stretch, pitch shift, SpecAugment, PatchAugment), the system benchmarks multiple CNN backbones combined with self-supervised learning paradigms enable the extraction of rich, discriminative acoustic representations, achieving strong multi-class …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 42–50 Read article
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Fractal-Entropy Guided Adaptive Signal Reconstruction for Non-Stationary Biomedical and Communication Systems
Abstract: This paper presents a novel Fractal-Entropy Guided Adaptive Signal Reconstruction (FEG- ASR) framework designed for accurate processing of non-stationary signals in biomedical and communication systems. The proposed approach integrates fractal dimension analysis with entropy- based feature evaluation to capture the intrinsic complexity and irregularity of time-varying signals. By dynamically adapting reconstruction parameters based on fractal-entropy measures, the method effectively separates noise from meaningful signal components while preserving critical information. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 Read article
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Synthesis, spectroscopic, crystal structure, Hirshfeld surface, computational, and biological investigations on Isophorone derivatives: 3-(3,4-dimethoxystyryl)-5,5-dimethylcyclohex-2-en-1-one
Abstract: FT-IR, 1H NMR, and 13C NMR spectroscopy were among the spectroscopic methods used to synthesize and analyze 3-(3,4-dimethoxystyryl)-5,5-dimethylcyclohex-2-en-1-one, a new isophorone derivative. Single-crystal X-ray diffraction (SCXRD) was used to determine the crystal structure, which showed that the molecule crystallizes in a monoclinic system (space group P121/c1) with packing configurations and intermolecular interactions. To learn more about the non-covalent interactions influencing the crystal packing, Hirshfeld surface analysis was used. In order …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 16, Issue 2, 2025 · pp. 51–69 Read article
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The Electromagnetic Transients in Compensated High Voltage Power Lines
Abstract: This paper addresses the simulation of the transients developed in high voltage lines, which are initiated by lightning discharges. The analysis allows for compensated and uncompensated lines. Both the individual and simultaneous series inductive and shunt capacitive compensation types can be dealt with. The sizes and locations of the compensating elements are included in the analysis. Numerous studies on the transient concentrated stresses across these elements and the related protection …
Published in International Journal of Electrical Power and Machine Systems · Vol. 1, Issue 2, 2023 · pp. 1–8 Read article
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AI-Assisted Gain Scheduling for Real-Time Temperature Control in Chemical Reactors
Abstract: Temperature control in continuous stirred-tank reactors (CSTR) represents a critical challenge in chemical process industries due to inherent nonlinearities, time-varying dynamics, and parametric uncertainties. Conventional proportional-integral-derivative (PID) controllers with fixed gains often fail to maintain optimal performance across varying operating conditions, leading to temperature excursions that compromise product quality and safety. This paper presents a novel AI-assisted gain scheduling framework that integrates artificial neural networks (ANN) with adaptive PID control …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 24–33 Read article
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An Integrated Study to Extrapolate the Interaction of NMDAR with Potential Ligands for the Treatment of Alzheimer’s Disease Symptoms
Abstract: Objective: Alzheimer’s disease (AD) is the most common neurodegenerative disease affecting the health status of older adults especially those above the age of 60 years. As an outcome, two types of medications have been developed for the treatment of its symptoms which are acetylcholinesterase (AChE) and N-methyl-D-aspartate receptor (NMDAR) antagonist. This paper uses the computational approach to understand the interaction of NMDAR with four major phytocompounds (curcumin, L-epicatechin, ginsenosides, and …
Published in International Journal of Biochemistry and Biomolecule Research · Vol. 1, Issue 1, 2023 · pp. 15–27 Read article
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A Hybrid Multi-Physics Ensemble Deep Learning Framework for Simultaneous Prediction of Thermal and Electrical Conductivity in Functional Polymer-Based Nanocomposites
Abstract: Polymer-based nanocomposites have become promising materials for applications in energy storage, flexible electronics, biomedical devices, aerospace components, and advanced engineering because of their tunable thermal and electrical properties. Reliable prediction of these properties is essential for accelerating material design; however, existing analytical models and conventional machine learning techniques often fail to represent the complex interactions among filler characteristics, polymer matrices, processing conditions, and interfacial transport phenomena. This work presents HMEP-Net, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1062–1082 Read article