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74 articles for “spatial analysis”
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Deep Learning-Based Thermal Prediction Models for Solid-State Electronic Devices
Abstract: The rapid advancement of solid-state electronic devices in high-performance computing, communication systems, automotive electronics, and renewable energy applications has significantly increased concerns related to thermal management and device reliability. Excessive heat generation in semiconductor devices adversely affects operational efficiency, switching performance, lifespan, and overall system stability. Traditional thermal prediction methods often require complex numerical computations and extensive simulation time, making them less suitable for real-time monitoring and adaptive control applications. …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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AI-Driven Inverse Design of Functionally Graded Bio-Nanocomposites for Sustainable High-Barrier Packaging
Abstract: Multilayer plastic packaging realizes high barrier performance through laminated heterogeneous structures, but the heterogeneous structure has severe end-of-life challenges caused by the interfacial incompatibility of materials and the poor recyclability. This study proposes the inverse design of functionally graded PLA-nanoclay composite films by reinforcement learning as a monolithic alternative to traditional multilayer systems. Twin-screw extrusion is designed as a continuous control Markov decision process, and proximal policy optimization (PPO) is …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1547–1564 Read article
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Integrated Spatial and Statistical Assessment of Groundwater Quality in Rupbas Tehsil of Bharatpur, Rajasthan: A WQI-based Approach
Abstract: This study presents a comprehensive evaluation of groundwater quality in Rupbas Tehsil of Bharatpur District, Rajasthan, through the application of the Water Quality Index (WQI) and hydrogeochemical techniques. A total of 32 groundwater samples, 16 collected during the pre-monsoon and 16 during the post-monsoon seasons, were analyzed for key physicochemical parameters including pH, electrical conductivity (EC), total dissolved solids (TDS), dissolved oxygen (DO), oxidation-reduction potential (ORP), total hardness (TH), total …
Published in Journal of Water Pollution & Purification Research · Vol. 12, Issue 3, 2025 · pp. 84–93 Read article
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Spatiotemporal Modeling of Soil Erosion Under Agricultural Expansion in the Amravati Basin, India Using RUSLE–GIS
Abstract: Agricultural expansion and soil erosion are important environmental issues in areas where agriculture is a major source of livelihood. This study analyzes the spatial and temporal patterns of soil erosion in the Amravati Basin of Maharashtra and evaluates the impact of agricultural expansion using the Revised Universal Soil Loss Equation (RUSLE) integrated with Geographic Information System (GIS) techniques. Multi-source data, such as satellite imagery, rainfall records, soil characteristics, and topography …
Published in International Journal of Land · Vol. 3, Issue 1, 2026 · pp. 50–62 Read article
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Groundwater Quality Assessment for Drinking and Irrigation Purposes in Tadimarri Mandal, Sri Sathya Sai District, Andhra Pradesh Using Water Quality Index and Geospatial Techniques
Abstract: Groundwater is the primary source of potable water and supports agriculture worldwide. Assessing its quality is vital to determine its suitability for various purposes, especially as a safe drinking water source. This study focuses on evaluating the quality of groundwater used for drinking and irrigation in Tadimarri Mandal, Anantapur district, Andhra Pradesh, India. During the pre-monsoon season, 30 groundwater samples were collected from boreholes and analyzed for physicochemical parameters. The …
Published in Journal of Remote Sensing & GIS · Vol. 15, Issue 3, 2024 · pp. 1–19 Read article
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Xypher Bot: Autonomous Surveying Robot
Abstract: Xypher Bot is a fully autonomous robot built to carry out tasks like height measurement, estimating distance, and detecting objects. It uses affordable and easily available components such as the MPU6050 sensor, ultrasonic sensors, and a laser pointer. By using simple trigonometry, the bot can measure object height with good accuracy. The top part of the bot, which is responsible for height measurement, has already been built and tested. The …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 2, 2025 · pp. 49–62 Read article
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ArcGIS Applications in COVID-19 Spatial Epidemiology: A Comprehensive Systematic Review
Abstract: Addressing complicated community health concerns frequently necessitates the establishment of health practices. Professionals who study community health using information technology require a thorough framework. Health care professionals and authorities have had the ability to comprehend health-related geographical data and make timely judgments in different situations. In the field of epidemic disease prevention, including a viral spread model into a GIS is a popular issue. As a result, a GIS as …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 2, 2025 · pp. 17–25 Read article
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The Impact of Using High-Resolution Satellite Images on Improving Geographic Maps
Abstract: By integrating high-resolution satellite images into pre-existing mapping frameworks, this study tackles the problem of guaranteeing correctness and dependability in geospatial data updates. The main goal is to assess which satellite imagery sources—SuperView, Ikonos, QuickBird, and WorldView—are appropriate for updating maps at 1:2500 and 1:5000 scales. The process entails evaluating radiometric quality, geometric dependability, spatial correctness, and picture resolution and comparing the results to the specifications of different mapping tasks. …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 1, 2026 Read article
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Kinematic and Dynamic Modelling of a 6-DOF Robotic Manipulator for Industrial Applications
Abstract: The rapid evolution of industrial automation has intensified the need for highly accurate, flexible, and intelligent robotic systems capable of operating in dynamic and demanding environments. Among these systems, six-degree-of-freedom (6-DOF) robotic manipulators have emerged as a versatile solution due to their superior dexterity, large workspace, and human-arm-like motion capabilities. This research focuses on the comprehensive kinematic and dynamic modelling of a 6-DOF robotic manipulator designed for various industrial tasks …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 2, 2025 · pp. 27–32 Read article
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Generative AI for VR: Creating Physically Realistic Models
Abstract: Virtual Reality has revolutionized the traditional learning system by creating and interactive and engaging environment. However, its ability to show precise real-world experiences is limited due to lack of physical realism. This study investigates the potential of Generative Adversarial Network (GAN) in creating physically realistic 3D models. Proposed system incorporates deep learning techniques along with physics-based constraints to enhance model’s accuracy and usability. To achieve this, experiments were conducted on …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 3, 2025 · pp. 14–22 Read article
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Application of Convolutional Neural Networks in Design of Efficient Pipe Flow System
Abstract: Convolutional Neural Networks exhibit remarkable capabilities in flow pattern recognition, pressure drop prediction, leak detection, and system optimization through their ability to process complex spatial and temporal data patterns. The study examines CNN architectures specifically adapted for fluid dynamics applications, including data preprocessing techniques, feature extraction methods, and performance optimization strategies. Key applications include real-time flow monitoring, predictive maintenance, design parameter optimization, and anomaly detection in pipe networks. Comparative analysis …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 1–9 Read article
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Approach to Examine the Effect of Atomic Number on Single – Electron System of Group III Elements
Abstract: This study investigates the ionization energy, kinetic energy, and mass relationships among Group III elements (Boron, Aluminum, Gallium, Indium, and Thallium) to provide a comprehensive understanding of their atomic and physical properties. A detailed analysis of ionization energy trends reveals that Boron exhibits the highest ionization energy, while Thallium has the lowest, consistent with periodic trends influenced by increasing atomic radius and electron shielding. Gallium deviates slightly from this trend …
Published in International Journal of Crystalline Materials · Vol. 1, Issue 2, 2024 · pp. 01–09 Read article
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High-Definition Electroencephalography: A New Horizon in Neurological Pathology Research
Abstract: The advent of high-density electroencephalography (HD-EEG) has catalyzed a paradigm shift in the exploration of neurological pathologies. This editorial underscore its transformative potential in elucidating brain dynamics and refining diagnostic approaches for a spectrum of conditions, spanning from epilepsy and dementia to cognitive impairments in preterm infants. Our objective is to optimize the utility of HD-EEG by emphasizing the imperative for methodological homogenization and fostering collaborative endeavors. The remarkable spatial …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 15–21 Read article
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Explainable GeoAI-Based Multi-Temporal Remote Sensing Framework for Early Detection of Climate-Induced Land Cover Transformation
Abstract: Climate change has emerged as one of the primary drivers of rapid land cover transformation, affecting ecosystems, agricultural productivity, biodiversity, and regional sustainability. Traditional remote sensing approaches often face challenges in detecting subtle and early-stage land cover changes due to limitations in temporal analysis and model interpretability. This study proposes an Explainable GeoAI-based multi-temporal remote sensing framework for the early detection of climate-induced land cover transformation using multi-source satellite imagery …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 2, 2026 Read article
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Early Alzheimer's Disease Detection Using Deep Ensemble Learning and MRI Image Analysis
Abstract: Early detection of Alzheimer's disease (AD) is crucial to slowing cognitive decline and enabling timely clinical interventions. Traditional diagnostic methods, including cognitive tests and single-model classifiers, have limited sensitivity during early stages of the disease. This paper presents a deep ensemble learning approach that integrates multiple convolutional neural networks (CNNs) for accurate Alzheimer's disease detection using structural Magnetic Resonance Imaging (MRI) data. The proposed framework utilizes ResNet50, VGG16, and DenseNet121 …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
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Comprehensive study of Entanglement Entropy in Quantum Field Theory: Analysis of Conformal Field Theory to Massive Field Extensions and Holographic Entanglement
Abstract: This paper provides an in-depth analysis of entanglement entropy (EE) in quantum field theory (QFT), with a particular focus on its computation using the replica trick and its applications to both conformal and non-conformal systems. Beginning with an introduction to the basics of QFT, the study explains how entanglement entropy quantifies the quantum correlations between subsystems in a pure state, represented by the von Neumann entropy of the reduced density …
Published in Research & Reviews : Journal of Physics · Vol. 13, Issue 3, 2024 · pp. 33–58 Read article
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Next-Generation Photochemical Research Using Cathodoluminescence: Mapping Optical Properties and Resonances at the Nanoscale
Abstract: This study explores the principles and diverse applications of CL, particularly in the analysis of inorganic compounds and nanophotonic structures. It examines various facets of CL, including aperture effects, transmission modes, resolution, momentum, scanning techniques, and modulation within CL imaging. The study underscores significant advancements in CL technology, highlighting its utility in characterizing nanostructures, plasmonic materials, and optoelectronic devices. The discussion emphasizes CL's role in mapping the Local Density of …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 2, Issue 2, 2024 · pp. 01–05 Read article
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Disaster Impact Assessment Using Multi-Sensor Satellite Data: An AI-Based Remote Sensing Approach
Abstract: Natural disasters such as floods, earthquakes, and wildfires cause significant damage to human life and infrastructure every year. Rapid and accurate assessment of the affected areas is essential for effective disaster response and recovery planning. Traditional image-based analysis using single-sensor data often fails under adverse conditions such as cloud cover, smoke, or poor lighting. To overcome these limitations, this study proposes a novel framework for disaster impact assessment using multi-sensor …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 10–22 Read article
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Micro Level Mobility Intervention in Urban Spatial Structure in Reducing GHG Emissions: A Case of The City of Lucknow, Prayagraj and Varanasi
Abstract: In contemporary times, the Greenhouse Effect has emerged as a paramount concern in urban areas. With India undergoing rapid urbanization, cities are witnessing soaring temperatures. Greenhouse gas emissions are one of the main causes of the Greenhouse Effect. India stands among the highest emitters of GHGs, primarily stemming from the energy sector, particularly in electricity generation. The period from 2005 to 2018 saw a noteworthy surge in India's emissions, largely …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 25–33 Read article
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Optimizing Sampling Techniques Using Fuzzy Set Theory: A Comprehensive Approach
Abstract: Sampling is a critical process in statistics, used to estimate population parameters without needing to examine the entire population. Traditional sampling methods, such as simple random sampling, stratified sampling, and cluster sampling, face limitations when applied to complex or heterogeneous populations with imprecise boundaries. These methods often fail to accurately represent populations with overlapping characteristics or missing data, resulting in sampling bias and reduced accuracy. To address these challenges, this …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 29–43 Read article