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76 articles for “predictive move.”
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REVIEW OF NANO MATERIALS FOR PREDICTING STRENGTH AND VOLUME CHANGE BEHAVIOUR OF EXPANSIVE SOILS
Abstract: Expansive soils are problematic to Civil Engineering by increase and decrease its volume due to movement of water in and out. This kind of soils is portrayed by its outrageous hardness while drying and with high swelling process on the wetting. Several researches during the past 20 years have proposed different nano materials for the soil stabilization approaches to counter the hazards present in the soils. This paper elaborates various …
Published in Journal of Geotechnical Engineering · Vol. 5, Issue 3, 2018 · pp. 8–13 Read article
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Study of Social Trends Prediction Using AI
Abstract: AI (Artificial Intelligence) has fundamentally changed the ability to analyze social trends by using large datasets to develop predictions about human behavior, public sentiment, and global events. Using methodologies such as Natural Language Processing (NLP), Time-Series Forecasting, and Graph-Based Social Network Analysis, AI is able to find hidden correlations in a variety of available datasets, from social media to economic indicators to public records, and fundamentally changes decision-making based on …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 19–29 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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Analysis of Vibrational Induced Structure Considering Rail and Seismic Load Using ETABS
Abstract: In the past, buildings next to railroad tracks were not taken into account when designing them, which resulted in catastrophic damage to the buildings as well as fatalities. For these structures to be designed safely, the vibrational loading must diminish. This study's case study is the Rani Kamlapati railway station in Bhopal, which was renovated by the Bansal Group and is the nation's first private railroad station. They suggested building …
Published in Journal of Industrial Safety Engineering · Vol. 10, Issue 3, 2023 · pp. 1–13 Read article
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Personalized Therapy Using Drug Delivery Devices
Abstract: The persistent challenge in modern medicine lies in inter-patient heterogeneity, rendering standardized drug dosing protocols suboptimal for many chronic conditions. Traditional pharmacokinetics fail to account for real-time biological fluctuations, leading to cycles of ineffective treatment or dose-limiting toxicity. This paper explores the critical intersection of advanced drug delivery devices (DDDs) and personalized medicine, positioning these technologies as the vital link translating genomic and biological data into tangible, patient- specific interventions. …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 53–62 Read article
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Study Of Uber-Related Data Using Machine Learning
Abstract: This paper describes the operation of the machine learning algorithm used in the Uber database, which contains data generated by the Uber Movement for a few locations in Hyderabad and the big apple City. Uber is known as a peer-to-peer program. This program connects you to the nearest drivers available to take you to your destination. This database includes Uber capture data with information such as time, ride date additional …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 9, Issue 2, 2022 · pp. 1–6 Read article
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Robotics and Automation in Mechanical Engineering: Transforming Modern Manufacturing Systems
Abstract: Robotics and automation have significantly transformed mechanical engineering, particularly in manufacturing, precision assembly, and intelligent systems integration. With the advancement of sensors, control systems, artificial intelligence, and mechatronics, robotic systems are now capable of performing complex tasks with high accuracy, repeatability, and efficiency. This article explores the role of robotics in modern mechanical applications, including industrial automation, collaborative robots, predictive maintenance, and smart manufacturing. It also discusses design considerations, challenges, …
Published in International Journal of Manufacturing and Production Engineering · Vol. 4, Issue 1, 2026 · pp. 27–33 Read article
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A Review of Semiconductor Solar PV Cell and Development of Solar Radiation Estimation Models
Abstract: Today’s life could not be imagined without energy (Power). It has become an integral part of day to day life. Traditionally, dependency was there on conventional sources of energy like coal, hydroelectric etc. But they are limited resources; also, they offer residue or pollution to the environment which is not desirable. These are the main reasons that the researchers inclined themselves towards the maximum exploration and make optimal use of …
Published in Journal of Semiconductor Devices and Circuits · Vol. 5, Issue 1, 2018 · pp. 20–26 Read article
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Application of Artificial intelligence in Single Point Incremental Forming for Surface Roughness Prediction
Abstract: The sheet metal forming industries always try to find an emerging trend to form sheet-metal in a cost-effective manner. In this regard, a forming technique is trending termed as single point incremental forming (SPIF) in which a simple forming tool having hemispherical end rod is moving and simultaneously deforming the clamped metal sheet according to predetermined toolpath command and forms a complete shape. The achievement of required surface quality is …
Published in Journal of Polymer & Composites · Vol. 12, Issue 1, 2024 · pp. 237–246 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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The Mediating Role of Label Trust in Shaping Green Purchase Attitudes Among Young Consumers: Sustainable Chemical Transparency in FMCG Packaging
Abstract: This study looks at the function of Perceived Chemical Transparency (PCT) in influencing consumers' Green Purchase Attitude (GPA) in the Fast-Moving Consumer Goods (FMCG) sector, with Label Trust (LT) serving as a significant mediating factor and Environmental Concern (EC) acting as a direct predictor. Based on the Theory of Planned Behavior and Signaling Theory, the study hypothesizes that clear disclosure of chemical and polymer-related information increases trust in eco-labels and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1308–1319 Read article
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Analyzing the Influence of Soil-Structure Interaction on High-Speed Rail Embankments: A Plaxis 3D Simulation Study
Abstract: The introduction of high-speed rail (HSR) in India has seen an increase in travel demand and areduction in travel time. However, the stability and deformation characteristics of railwayembankments and soil structure interaction behavior under high-speed design requirements forIndian soil conditions need to be predicted using simplified 3-D finite element modelling. Theobjective of this research is to analyze the rigid ballast-less and flexible ballast-based high-speed railtrack embankments for various critical conditions …
Published in Trends in Transport Engineering and Applications · Vol. 10, Issue 1, 2023 · pp. 18–45 Read article
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Entomo-Analytics: Insect Behavioral Intelligence for Climate-Smart Environmental Monitoring Systems
Abstract: Rapid environmental change driven by climate variability, urbanization, and ecological degradation has intensified the need for innovative monitoring systems capable of providing real-time ecological intelligence. Traditional environmental monitoring methods often rely on satellite imaging and stationary sensors, which may lack fine-scale biological sensitivity. In contrast, insects—due to their abundance, ecological diversity, and rapid responsiveness to environmental shifts—offer a powerful yet underutilized source of bio-sensing data. This paper introduces the concept …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 17–26 Read article
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Fruit Adulteration Detection Utilizing Machine Learning Methods
Abstract: A device utilizing Internet of Things (IoT) technology was developed for the identification of fruit adulteration through machine learning methods, specifically targeting formalin content assessment. The identification of the fruits based on their extracted traits has been accomplished using a variety of machine-learning techniques. The formalin concentration can be detected as an estimate of the generated voltage of any fruit via an Arduino Uno board 3 and a volatile compound …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 1, Issue 1, 2023 · pp. 32–45 Read article
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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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Comparative Study of Aggregate and Disaggregate Traffic Forecasting Technique for Industrial Corridor: Case Study of Vadodara District
Abstract: AbstractTransportation occupies a prominent place in modern life and its impact is spread in all domains of life. Transport planning is a discipline to study problems rising while planning transport facilities at urban, regional or national level and to prepare efficient basis for providing such facilities. Aim of transport planning at regional level is provision of connectivity and circuity with other regions as well as for expansion of existing facility …
Published in Trends in Transport Engineering and Applications · Vol. 5, Issue 1, 2018 · pp. 14–21 Read article
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IoT Integration in Logistics Network System–A Glance
Abstract: Transportation and logistics play a most essential role in operations and supply chain management applications. As a medium, it makes it easier for people, things, and products to move from one place to another. At one stage of the supply chain, from 90% to 95% of produced goods are transported in containers. Additionally, the global consumer class is predicted to grow by 35% to 40% by 2030, increasing the demands …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 1, 2025 · pp. 1–11 Read article
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Heart Disease AI-based Prediction: A Comparative Analysis
Abstract: The present investigation looks at how well various machine learning algorithms predict cardiac disease. Since heart disease is one of the major causes of death worldwide, early detection and precise diagnosis are essential for managing and treating the condition. Our goal is to enhance diagnostic processes and improve patient outcomes by leveraging machine learning techniques. Six widely-used machine learning algorithms are evaluated in this research paper. These algorithms were selected …
Published in Trends in Mechanical Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 21–29 Read article
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Using Elliot Wave Theory and Fibonacci Retracement and in Algorithmic Trading
Abstract: The analysis technique used in predicting stock prices consists of Fundamental analysis and Technical analysis. These analyses are complex in nature and usually unreliable. The algorithmic trading systems offered today consists of primitive technical analysis techniques such as, simple moving averages, exponential moving average, moving averages convergence and diversions and volume weighted average price. The primitive nature of this techniques makes them very unreliable and has a low success rate. …
Published in Trends in Machine design · Vol. 7, Issue 3, 2020 · pp. 22–29 Read article
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Second Wave COVID-19 Predictions and Forecasting of Confirmed Cases in West Bengal Using ARIMA Model
Abstract: Infection and death rates surged drastically during the second wave of the COVID-19 (called delta variant) in India, owing to the destructive virus. As our country's economic load makes it more difficult to control the measures and it is critical for states such as West Bengal to forecast future cases. The present study introduced a time series forecasting model aimed at predicting and forecasting the number of confirmed and active …
Published in Research and Reviews : A Journal of Immunology · Vol. 13, Issue 1, 2023 · pp. 1–8 Read article