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166 articles for “Spatial”
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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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Modeling and Simulation of Radiative MHD Casson-Type Polymer Composite Flow over a Porous Wedge with Variable Thermal Source and Sink
Abstract: This study presents a numerical investigation of the radiative magnetohydrodynamic (MHD) flow and heat transfer characteristics of a Casson-type polymer fluid over a moving and extending porous wedge under the influence of a spatially varying heat source and sink. The Casson fluid model, representing a class of viscoplastic polymeric materials, is analyzed within the MHD framework to explore the combined effects of magnetic field intensity, rheological behavior, and porous medium …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 837–850 Read article
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A New Computational Method for Dust and Gas Dynamics in Protoplanetary Discs
Abstract: The simultaneous evolution of dust and gas in protoplanetary discs regulates essential events in planet formation, such as dust accumulation, migration, and the initiation of gravitational instabilities. Nevertheless, precisely modelling this interaction continues to provide a significant computing problem owing to the extensive variety of spatial and temporal scales involved. In this study, we introduce an innovative computational framework for simulating dust-gas dynamics in protoplanetary discs, integrating a two-fluid hydrodynamical …
Published in International Journal of Universe · Vol. 1, Issue 2, 2025 · pp. 35–46 Read article
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Effectiveness of 3-D Printing Technology in Education and Teaching-Learning
Abstract: Education is the key to releasing the true potential of human ingenuity. The emphasis of education should be on both academic and practical, hands-on techniques. It covers the gap between conceptual understanding and real-world execution. 3-D printing, a new educational technology, claims that it will equip pupils for a more technologically advanced future. By incorporating 3-D printing into education, cutting-edge technology is made accessible to ambitious students and future entrepreneurs. …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 113–125 Read article
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Photoreceptor Dynamics: Light Sensing and Cellular Responses for Photochemistry
Abstract: Photoreceptor dynamics represent a fundamental aspect of photochemistry, encompassing the mechanisms by which biological systems detect and respond to light stimuli. Photoreceptors are specialized proteins that undergo structural and functional changes upon photon absorption, initiating a cascade of molecular events that translate light signals into cellular responses. These proteins are ubiquitous across life forms, including microbial rhodopsins, plant phytochromes, and animal opsins, each finely tuned to specific wavelengths and light …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 3, Issue 2, 2025 · pp. 28–32 Read article
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A study in Leveraging Deep Learning and IoT Arrays for Dynamic, Hyper-Local Atmospheric Intelligence
Abstract: The critical demand for high-resolution, actionable atmospheric data is challenged by the high cost and sparse coverage of traditional regulatory monitoring stations. This paper explores the synergistic paradigm shift enabled by integrating low-cost, dense Internet of Things (IoT) sensor arrays with advanced Artificial Intelligence (AI) methodologies, specifically Deep Learning (DL) models. We address the primary limitations of low-cost sensors—inherent bias, sensitivity to environmental drift (temperature/humidity), and calibration inconsistency—by utilizing AI …
Published in International Journal of Atmosphere · Vol. 2, Issue 2, 2025 · pp. 50–62 Read article
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Thermal Effects in High-Power Laser Systems: Modeling and Mitigation
Abstract: High-power laser systems are increasingly employed in industrial manufacturing, defense, medical procedures, and scientific research due to their ability to deliver high energy density with excellent spatial coherence. However, the performance and reliability of these systems are significantly influenced by thermal effects arising from optical absorption, non-radiative recombination, and inefficient heat dissipation within laser gain media and optical components. These thermal phenomena lead to adverse effects such as thermal lensing, …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 2, 2025 · pp. 9–13 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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Harmonically Varying Moving Load on Time-Dependent Uniform Beam Resting on Pasternak Foundation
Abstract: In this paper, we investigated elastic beam whose properties does not varies with spatial coordinate but constant along the span L of the beam. The moving load considered in this work is harmonically varying moving load with non-classical boundary conditions, time dependent boundary conditions in particular. Also, considered in this work is two parameters foundation which are Winkler and Pasternak foundations. Closed form solutions in plotted form are obtained using …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 2, 2025 · pp. 38–47 Read article
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Progress and Uses of Satellite Remote Sensing
Abstract: Satellite remote sensing has become an important tool for watching, studying, and controlling both natural and man-made systems on Earth. Satellite sensors collect electromagnetic radiation that is reflected or transmitted from the Earth's surface. This data is needed for environmental monitoring, resource management, and hazard assessment. Recent improvements in sensor resolution, data processing techniques, and cloud-based platforms have made remote sensing applications much more accurate and easier to use. The …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 2, 2025 · pp. 8–19 Read article
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Power of Optical Sensors in Remote Sensing: A Study
Abstract: Imagine having eyes that could pierce the veil of the visible, discerning the subtle whispers of light beyond the spectrum our everyday vision allows. This isn't a superpower from science fiction, but the very essence of optical sensors in remote sensing – our planet's watchful, silent sentinels, meticulously translating the electromagnetic symphony into actionable insights. Optical sensors, operating within the visible, near-infrared, and short-wave infrared portions of the electromagnetic spectrum, …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 2, 2025 · pp. 29–36 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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A Mini Review of Synthesis and Applications of Functionally Graded Materials
Abstract: Material composition or microstructure varies gradually along the thickness over a specific volume in functionally graded material (FGM) that results in spatial change in properties like thermal conductivity, strength, stiffness, electrical, magnetic, and light properties, etc. Application of the concept of FGM leads to a single product that has multiple properties in it as demanded by the operational or functional requirements of the product under service conditions. It also allows …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 54–65 Read article
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Recent Trends in Heavy Metal Pollution of Groundwater: A Review
Abstract: Heavy metal pollution in groundwater has emerged as a major environmental and public health concern worldwide due to its persistence, toxicity, and potential for bioaccumulation. Rapid industrialisation, urban expansion, intensive agriculture, mining activities, and improper waste disposal have significantly increased the release of heavy metals into subsurface environments. Groundwater, being a primary source of drinking water in many regions, is particularly vulnerable to contamination, posing serious risks to human health …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 14–24 Read article
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Intelligent Earth: AI As A Catalyst For Climate Action
Abstract: Artificial Intelligence (AI) is assuming an increasingly influential role in climate science, providing advanced tools capable of interpreting vast, complex, and multi-dimensional environmental datasets. Traditional climate modeling approaches, while grounded in physical principles, frequently struggle to deliver high-resolution, real-time, and region-specific forecasts because of heavy computational demands, incomplete observations, and uncertainties in representing small -- scale processes. Artificial intelligence (AI) techniques, especially machine learning and deep learning, provide strong substitutes …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 48–52 Read article
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The Parasitic Fingerprint: Tracing Infection to Host Illness
Abstract: Parasitic infections remain a major global health burden, causing significant morbidity and mortality, particularly in tropical and subtropical regions. A critical aspect of disease pathogenesis is the unique molecular and cellular imprint left by parasites in their hosts, termed the “parasitic fingerprint.” These fingerprints encompass parasite-derived proteins, nucleic acids, metabolites, extracellular vesicles, and host responses, including gene expression changes, cytokine profiles, and metabolic adaptations. Advances in multi-omics technologies, which integrate …
Published in Recent Trends in Infectious Diseases · Vol. 3, Issue 1, 2026 · pp. 29–50 Read article
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A SEIR-Informed Stacked Fusion of Prophet, XGBoost, and LSTM for Ward-Level Epidemic Forecasting in Amravati Municipal Corporation
Abstract: Municipal epidemic preparedness depends on accurate short-horizon forecasts at fine spatial granularity. Ward-level incidence series are typically nonstationary due to changing contact patterns, interventions, reporting delays, and heterogeneous demographic and environmental factors. This paper presents a mathematically formulated hybrid forecasting architecture designed for Amravati Municipal Corporation (AMC). The method decomposes observed incidence into (i) a mechanistic SEIR baseline that enforces epidemiological structure and (ii) a data-driven residual learned using Prophet …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 1, 2026 · pp. 17–23 Read article
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Assessing Land use Dynamics and Policies in the Waghur Basin Using Geospatial Techniques
Abstract: Changes in land use and land cover (LULC) are key indicators of human–environment interactions, especially in river basins where anthropogenic pressure is increasing. This study evaluated land use change and policy implications in the Waghur Basin, India, through a geospatial analysis of 35 years (1990–2025). Remote sensing and GIS-based supervised classification with the help of machine learning methods were applied to multi-temporal Land satellite images to create LULC maps and …
Published in International Journal of Land · Vol. 3, Issue 1, 2026 · pp. 38–49 Read article
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An Overview on Quantum dot technology in Temperature sensor design
Abstract: Quantumdot (QD) thermometry harnesses the sizedependent electronic structure of semiconductor nanocrystals to translate minute temperature variations into robust optical signals. In this work we present a systematic design framework for QDbased temperature sensors that integrates (i) bandgap engineering through precise colloidal synthesis, (ii) surfacestate passivation to suppress nonradiative pathways, and (iii) a planar photonicreadout architecture compatible with lowcost, CMOSfriendly fabrication. By exploiting the linear redshift of the photoluminescence (PL) peak …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 1, 2026 · pp. 10–17 Read article
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“Microvita‑Inspired Informational Field Dynamics as a Nonlinear Signal‑Generation Mechanism in Matter–Life–Mind Systems”
Abstract: Recognizing how matter, life, and consciousness relate to one another continues to be among the most essential challenges faced by modern science. Contemporary physical theories successfully describe the behavior of elementary particles and large-scale cosmological structures, yet they do not fully explain the emergence of informational complexity and organized patterns observed in biological and cognitive systems. This study proposes a theoretical framework in which Microvita are interpreted as subtle informational …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 Read article