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182 articles for “driving behavior”
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Role of a Nurse in Addressing Mobile Addictions
Abstract: Nurses are essential in recognizing, evaluating, and addressing mobile addiction by using their skills in thorough screening and assessing patients' histories. Through keen observation and structured assessments, nurses can detect signs of mobile addiction, such as social withdrawal, disrupted sleep patterns, and neglect of personal responsibilities. It is crucial to establish this initial identification promptly to begin timely interventions and provide necessary support to those affected. Patient education stands at …
Published in Journal of Nursing Science & Practice · Vol. 14, Issue 3, 2024 · pp. 25–29 Read article
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Facial Expression Recognition Using Convolutional Neural Network
Abstract: The recognition of facial expression is a key step in nonverbal human communication in the field of computer vision. The Facial Expression Recognition (FER) system reflects emotions as well as mental activities, social interaction with people and expressing positive or negative attitude in general. It has many applications like human machine interaction, understanding human behavior and emotions, mental state identification, drowsiness detection for driving safety and health care. One of …
Published in Journal of Open Source Developments · Vol. 6, Issue 1, 2019 · pp. 18–27 Read article
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IMPLEMENTATION OF LIGHT WEIGHT CARBON COMPOSITE DRIVESHAFT FOR A LIGHT COMMERCIAL VEHICLE
Abstract: The automotive drive shaft is a crucial component for power and torque transmission in vehicles, with a tubular shape that spins due to engine power. The current drive shaft is made of heavy-duty mild steel, increasing the vehicle's weight and fuel consumption. To reduce the weight, a composite material called carbon fiber was used. Carbon fiber showed better performance in driveshaft operation, and its properties were evaluated using universal testing …
Published in Journal of Polymer & Composites · Vol. 12, Issue 1, 2024 · pp. 52–65 Read article
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Integrated Surface Water–Groundwater Dynamics: Implications for Pollution Pathways, Prevention, and Environmental Control
Abstract: Water resources worldwide are increasingly threatened by pollution pressures amplified by climate change and intensified human activities. The vulnerability of surface water and groundwater systems to contamination is strongly governed by their dynamic hydrologic connectivity, which is often overlooked in pollution prevention and control frameworks. Rising global temperatures, altered precipitation regimes, land-use change, and intensified abstraction patterns modify recharge processes, flow paths, and contaminant transport mechanisms across environmental landscapes. This …
Published in International Journal of Pollution: Prevention & Control · Vol. 4, Issue 1, 2026 · pp. 34–40 Read article
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Develop the Design of Sustainable Polymer Materials: Applying Reinforcement Learning, IoT-Enabled Monitoring, and Data-Driven Manufacturing Approaches
Abstract: Sustainable polymer materials development is a must due to resource constraints, environmental concerns, and the demand for designed materials with high performance. When it comes to material optimization, energy utilization, process unpredictability, and lifecycle sustainability, traditional polymer production methods have their challenges. Reinforcement Learning (RL), Internet of Things (IoT) monitoring, and data-driven production are utilized in the design and manufacturing of sustainable polymer materials. It is recommended to use Internet …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1207–1231 Read article
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The AI Revolution: Transforming Business Decision-Making
Abstract: Industries undergo a transformation thanks to artificial intelligence, which makes machines capable of activities that previously required human intelligence. This interdisciplinary field of computer science models human thought processes, impacting sectors from autonomous vehicles to creative AI tools. Integrating AI into business operations transforms decision-making and enhances corporate performance. AI-driven methodologies analyze vast datasets to provide valuable insights and facilitate decisions beyond human capability. Predictive modeling anticipates consumer behavior, market …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 2, 2024 · pp. 25–32 Read article
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Sentiment Analysis for Financial Predictions: A Review
Abstract: AbstractSentiment analysis is one of the popular research areas in computer science, as it finds its application in numerous areas like finance, election and product reviews. Behavioral economics suggests that decision of investing in financial markets is driven by feelings like greed, fear etc. With widespread adoption of technology and digitization of corporate disclosures, news and social media platforms, and information expressed through words can be mined and used to …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 6, Issue 1, 2019 · pp. 59–68 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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Understanding of Environmental and Cultural Factors Affecting Online Purchase Behavior
Abstract: Online purchase behavior is influenced by a complex interplay of environmental and cultural factors, which are critical to understanding the context of e-commerce. This research aims to explore how these factors shape consumer behavior, providing insights for businesses to enhance their online strategies. Environmental factors include technological infrastructure, economic conditions, and regulatory policies that create the backdrop against which online transactions occur. For instance, a robust internet infrastructure and favorable …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 3, 2024 · pp. 29–36 Read article
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Self Driving Car Simulation Using Deep Learning
Abstract: Every year, traffic accidents account for 2.2% of worldwide deaths. That accumulates to a few millions a year. On prime of this, some individuals are seriously lacerate in auto-related accidents annually in large numbers mostly due to human error. From distracted driving to drunk driving to reckless driving to careless driving, one poor or inattentive call may be the distinction between a typical drive and a critical state of affairs. …
Published in Journal of Advancements in Robotics · Vol. 8, Issue 1, 2021 · pp. 6–13 Read article
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Computational Approaches to Understanding Cellular Signaling Pathways
Abstract: Cellular signaling pathways are fundamental in regulating vital processes, such as cell growth, differentiation, and apoptosis. The intricate and interconnected nature of these signaling networks requires sophisticated methods for their analysis. Computational approaches, including mathematical modeling, network analysis, and machine learning, have revolutionized the way researchers analyze and simulate cellular signaling. This article provides a comprehensive overview of computational strategies employed to model signaling pathways, with a focus on integrating …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 8–13 Read article
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Leveraging Generative AI for Test Case Creation in Complex Systems
Abstract: Modern software systems exhibit increasing complexity, demanding sophisticated testing methodologies to ensure reliability and functionality. Traditional manual testing approaches often struggle to keep pace with this complexity, leading to inadequate test coverage and increased risk of unforeseen issues. This study explores the potential of Generative AI (GAI) in revolutionizing test case creation for complex systems. We delve into the practical application of GAI techniques, such as Variational Autoencoders (VAEs) and …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 16–22 Read article
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Characterization of Thermochemical Properties and Combustion Behavior In AP/HTPB Polymer Composite Solid Propellant for Enhanced Performance
Abstract: The thermal decomposition of solid propellants containing hydroxyl-terminated polybutadiene (HTPB) binder is a complex process, driven by multiple interacting chemical and physical factors. Solid propellant combustion characteristics are profoundly influenced by the composition of the propellant, the conditions of pressure, the starting temperature, and a range of aero-thermochemical parameters. The paper explores the influence of polymeric structure in the HTPB binder on thermal decomposition characteristics of the AP/HTPB composite propellants …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 502–511 Read article
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Big Data Analytics for Effective Decision Making in Business Intelligence
Abstract: In this study, we explore the significance of Big Data Analytics (BDA) in enhancing decision-making processes within Business Intelligence (BI) frameworks. It involves processing vast volumes of data from various sources, enabling businesses to identify patterns, trends, and correlations that were previously unnoticed. This analytical power enhances strategic planning, customer understanding, operational efficiency, and competitive advantage. Through advanced algorithms and machine learning techniques, businesses can predict future trends, optimize operations, …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 1, 2024 · pp. 23–28 Read article
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A Study on AI-Driven Multi-Layered Defense in 6G Ecosystems
Abstract: The 6G networks bring about new degrees of possible functions related to connectivity, latency, data throughput, and integration with artificial intelligence (AI). This enables advances within healthcare, autonomous systems, and smart cities. The positive impact of rapid advancements must also be balanced with heightened risks due to the sheer volume of gaps that can be exploited, and the complex nature of the alignments and breaches. This results in the breaches …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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A Study on the Impact of Seasonal Sales on E-Commerce Trends in India: Insights from Amazon and Flipkart
Abstract: This study investigates the growing impact of seasonal sales on e-commerce trends in India, with a particular emphasis on two leading platforms, Amazon and Flipkart. Large-scale events such as the Great Indian Festival and the Big Billion Days have become defining moments in the country’s online retail calendar, creating noticeable shifts in consumer purchasing behavior, sales volumes, and digital marketing approaches. The research examines how heavy discounts, limited-time offers, and …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 3, 2025 · pp. 01–06 Read article
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Enhanced Sustainable Concrete Mix Design Using LLMs and Advanced Machine Learning Techniques
Abstract: Large Language Models (LLMs) are emerging as transformative tools in materials science, offering human-like reasoning, zero-shot problem solving, and the ability to integrate fuzzy laboratory knowledge with structured data. This study extends and reinterprets the original systematic benchmark for using LLMs in sustainable concrete design, particularly for Alkali-Activated Concrete (AAC). We introduce an enhanced, multi-model framework combining LLM-based inverse design, Random Forest regression, Gaussian Process Regression (GPR), and a lightweight …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 26–33 Read article
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Improving Supply Chain Resilience through Predictive Analytics and Real-Time Data Integration
Abstract: Demand forecasting has under gone major changes because to the incorporation of automated analytics into supply chain management (SCM), which has improved company productivity, accuracy, and responsiveness. Central to this transformation is the application of machine learning (ML), which enables the analysis of large and complex datasets to identify patterns, detect trends, and generate precise forecasts. Conventional methods for predicting frequently rely on linear models and historical sales data, which …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 8–17 Read article
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A Survey of Role-Based Access Control Implementation in HMI Systems for Industrial Automation
Abstract: The convergence of Role-Based Access Control (RBAC) and Human-Machine Interface (HMI) systems presents a transformative approach to secure and efficient industrial automation in Industry 4.0. By integrating RBAC with Multi-Factor Authentication (MFA), this framework enhances cybersecurity while maintaining operational flexibility, mitigating both external threats and internal vulnerabilities. Modern adaptive HMIs further optimize user experience through personalized and intuitive interfaces, though challenges remain in balancing functionality with simplicity in complex industrial …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 2, 2025 · pp. 10–19 Read article
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Phase – Field Modeling of Brittle and Ductile Fracture Under Complex Loading Conditions
Abstract: Phase-field modeling has emerged as a powerful computational framework for predicting fracture behavior in engineering materials, offering a unified description of crack initiation, propagation, branching, and coalescence without the need for explicit crack tracking. This study presents an in-depth examination of phase-field modeling applied to both brittle and ductile fracture under complex loading conditions, including multiaxial stress states, cyclic loading, thermal gradients, and dynamic impact. The phase-field approach regularizes the …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 2, 2025 · pp. 13–18 Read article