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230 articles for “Resolution”
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A Study on AI-Enhanced Environmental Toxicology: Sensor-Driven Predictive Framework
Abstract: Traditional environmental toxicology relies heavily on labor-intensive, often retrospective, sampling and analysis, limiting our understanding of dynamic pollutant behaviors and their real-time impact on ecosystems and human health. This study presents a novel, integrated framework leveraging advanced sensor networks and artificial intelligence (AI) to revolutionize the monitoring, assessment, and predictive modeling of environmental contaminants. We deployed a sophisticated array of multi-parameter sensors (e.g., electrochemical, optical, biosensors for heavy metals, organic …
Published in Research and Reviews: A Journal of Toxicology · Vol. 15, Issue 3, 2025 Read article
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Revolutionizing Petrology and Mineralogy: The Study of AI and Advanced Sensor Technologies
Abstract: Petrology and mineralogy are fundamental to understanding Earth's intricate processes, from crustal evolution to economic resource formation. However, traditional methods, while precise, are often laborious, time-consuming, and occasionally subject to interpretive bias. This abstract explores the transformative potential of integrating cutting-edge Artificial Intelligence (AI) and advanced sensor technologies to revolutionize data acquisition, analysis, and interpretation in these critical geosciences. Advanced sensor technologies, including high-resolution spectral imaging (hyperspectral, Raman), automated X-ray …
Published in International Journal of Minerals · Vol. 2, Issue 2, 2025 · pp. 1–11 Read article
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A Comprehensive Review on Nanostructured Polymer Composites for CT Imaging Contrast Enhancement in Brain Tumor Diagnosis
Abstract: The detection and characterization of brain tumors require high-resolution and non-invasive imaging modalities that have the ability of differentiating tumorous tissues and healthy brain tissues. Computed tomography (CT) can be included in this number because, in addition to providing speedy scans and penetration to deep tissue, the diagnostic capability in soft tissue organ such as the brain is poor despite low natural contrast. The review is dedicated to the emerging …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 148–162 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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Integration of Multispectral Satellite data with Ensemble Machine Learning Models for Wetland Classification: a new Ramsar Site in Central India
Abstract: For biodiversity conservation, several wetlands in India have been classified as Ramsar sites, and Sirpur Lake is a recent addition to the list. The objective of this paper is to use Sentinel optical data with 10-meter resolution to prepare a robust and accurate classified map which will be crucial for further analysis. The data on thirteen spectral bands along with four essential spectral indices, Normalized Difference Vegetation Index (NDVI), Normalized …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 3, 2025 Read article
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Physical Modeling of Mass Transport Processes in Extraterrestrial Landscapes
Abstract: Currently the progress in physical models based on mass transport in both the Earth's surface and extraterresterial landscape has been growing. It is a frame work involving different natural and made made processes including aeline process, fluid flow process, magmal movement, Geomagnetic stroms, and clould flow modesl etc. These process encorporates Physical models and appraches which help to simulate, compute and experiment in order to reduce complexity. However, their operating …
Published in International Journal of Universe · Vol. 1, Issue 2, 2025 · pp. 47–54 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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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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Passenger car fuel economy: Insights from big data analytics
Abstract: The increasing availability of real-world vehicle telematics through On-Board Diagnostics II (OBD-II) systems has enabled data-driven evaluation of passenger car fuel economy beyond conventional laboratory-based test cycles. While standardized certification procedures ensure repeatability, they often fail to capture the influence of real-world traffic conditions, driver behaviour, and transient vehicle operation. This study presents a structured Big Data Analytics (BDA) approach for analysing high-frequency OBD-II data collected from a gasoline passenger …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 9–21 Read article
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A Legal Analysis of Contract Negotiations in Professional Sports
Abstract: Contract negotiations are crucial aspect of professional sports, involving complex legal considerations and complex interactions between athletes, agents and team owners. This article provides a comprehensive legal analysis of contract negotiations in professional sports, examining the role of collective bargaining agreements, individual player contracts, and agent-player relationships. Through a critical examination of relevant statutes, case law and collective bargaining agreements, this article identifies key principles and trends shaping contract negotiations …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 31–45 Read article
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Clinical Medicine Done with Clinical Accuracy
Abstract: The advancement of clinical medicine has progressively underscored the significance of accuracy in diagnosis and therapy. This article examines the concept of "Clinical Medicine Administered with Clinical Precision," emphasising how innovations in diagnostics, data analytics, and personalised treatments are transforming the healthcare environment. Clinicians can provide therapy that is not only successful but also personalised to each patient's requirements by combining evidence-based practices with patient-specific factors including genetic profiles, comorbidities, …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 6–19 Read article
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Data-Driven Energy Forecasting for Smart Homes: Ensemble Learning from IoT Meters and Relevance for Polymer-Composite Based Smart Infrastructure
Abstract: Reliable estimation of household electricity demand is relevant in creating efficiency in energy usage, optimization of the loads, and intelligent demand-side management in intelligent grid systems. This paper introduces a varied machine learning model that approaches residential electric consumption prediction using an assortment of ensemble regression boosts, including Linear Regression, Lasso Regression, Decision Tree Regressor, Random Forest, and Gradient Boosting, to predict residential electricity consumption environments on a time-series arrested …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 29–64 Read article
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Shadows of Uncertainty: When Pneumonia Isn’t Pneumonia
Abstract: Pneumonia is a common medical condition encountered in hospitalized patients and remains a cause of morbidity worldwide. Identifying and initiating appropriate treatment in febrile patients who present with respiratory symptoms and radiographic infiltrates, reduce hospital stay, minimize complications, and lower healthcare costs. However, the assumption that every pulmonary infiltrate or opacity seen on a radiological imaging represents an infectious process such as pneumonia can lead to misdiagnosis, unnecessary investigations, prolonged …
Published in International Journal of Pathogens · Vol. 3, Issue 1, 2026 · pp. 24–29 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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Impact of Hypoxia on Cardiopulmonary Adaptation in Canines: A Comprehensive Review
Abstract: Hypoxia triggers a series of cardiopulmonary responses that play an important role in oxygen delivery and the continuation of physiological activity in mammals. Canines are also a useful translational model of study to examine these adaptive responses because of their anatomical, physiological, and cardiopulmonary differences with humans. This review summarizes the experimental data of acute, subacute and chronic hypoxia in dogs with particular focus on the variations in cardiac functioning, …
Published in Research and Reviews : Journal of Veterinary Science and Technology · Vol. 15, Issue 1, 2026 · pp. 13–24 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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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 · pp. 22–33 Read article
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3D Printing of Polymer-Based Functionally Graded Materials: Recent Developments and Challenges
Abstract: Additive manufacturing (AM), specifically 3D printing, has become a useful technique for fabricating functionally graded materials (FGMs) because it can facilitate the spatial distribution of materials. Polymer FGMs (P-FGMs) have gained a great deal of interest due to their lightweight, customizable, multifunctional properties. In comparison to conventional fabrication, 3D printing allows better control of composition and microstructure, which results in materials with controlled mechanical, thermal, and biological properties. This review …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 338–347 Read article
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Optimization of Pesticide Requirement Calculations for IoT-Operated Hexacopter Delivery Systems
Abstract: The integration of Internet of Things (IoT) technology into precision agriculture has transformed pesticide application strategies, enabling resource-efficient and environmentally sustainable practices. This study presents a computational methodology for optimizing pesticide requirements in an IoT-operated hexacopter system, designed for dynamic, data-driven pesticide delivery. Leveraging a fusion of real-time telemetric data from onboard LiDAR, multispectral imaging sensors, and environmental monitoring modules, the system employs predictive analytics and edge computing to calculate …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 08–14 Read article