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239 articles for “PROACTIVE”
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Malicious Network Traffic Detection Using Hybrid Feature Selection with Ensemble Neural Network
Abstract: The detection of malicious network traffic is a critical aspect of cybersecurity, aiming to protect sensitive data and maintain the integrity of network systems. This study introduces a novel approach that combines hybrid feature selection with ensemble neural networks to enhance the accuracy and efficiency of malicious network traffic detection. The dataset used in this study was obtained from Kaggle and offers a wide-ranging and varied collection of network traffic …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 3, 2025 Read article
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Application-Driven Rule-Based Framework for Lubrication Failure Modes in Industrial Systems
Abstract: Modern lubricants increasingly rely on polymer-based composites, integrating synthetic base oils, polymer thickeners and solid additives like MoS₂ and PTFE for high-performance applications. These formulations not only enhance thermal and mechanical stability but also enable low-friction operation across diverse industrial conditions. Lubrication-related failures represent a critical cause of unplanned downtime and reduced reliability in industrial machinery. This paper presents an application-driven, rule-based framework designed to assess and mitigate lubrication failure …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 522–531 Read article
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Integrated, Geospatial Risk Assessment of Air, Water, and Soil Pollution Impacts on Agricultural Sustainability using Advanced Digital Technologies
Abstract: The systemic threat posed by the convergence of air, water, and soil contaminants represents a critical challenge to global agricultural resilience and food security. Traditional, site-specific pollutant monitoring methods are insufficient for capturing the dynamic, diffuse, and often nonlinear nature of environmental risk pathways that permeate agrarian landscapes. This study presents a robust framework for comprehensive risk assessment utilizing a synergistic suite of modern tools designed for spatial, temporal, and …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 28–37 Read article
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The Impact of Sleep Quality on Academic Performance and Burnout Among College Students
Abstract: In today’s academic environment, college students face a multitude of challenges that disrupt their well-being—one of the most overlooked being sleep quality. While balancing coursework, social obligations, and personal goals, sleep often becomes a casualty of the student lifestyle. Many students often sacrifice sleep without fully realizing how it affects their mental sharpness and emotional well-being. This study delves into the complex connection between how well students sleep, how they …
Published in International Journal of Behavioral Sciences · Vol. 2, Issue 2, 2025 · pp. 59–65 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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AI-Powered Defense: Advancing Cybersecurity Through Artificial Intelligence Innovations
Abstract: In the current landscape of escalating cyber threats and increasingly sophisticated attack vectors, integrating artificial intelligence (AI) within cybersecurity strategies has become a critical step forward. This study explores the role of AI in strengthening cybersecurity by utilizing its strengths in data analysis, pattern recognition, and predictive modeling. Through AI, organizations can greatly enhance their ability to detect and respond to threats. Machine learning algorithms enable ongoing adaptation to new …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 1, 2026 · pp. 35–41 Read article
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VERONICA: AI-Driven Edge System for Comprehensive Bike Safety and Assistance Through Multi-Source Data Fusion
Abstract: Road safety for bike riders remains a significant concern, with accident rates highlighting the need for advanced solutions to ensure rider protection and awareness. This paper presents “VERONICA: AI-Driven Edge System for Comprehensive Bike Safety and Assistance Through Multi-Source Data Fusion”, a voice-activated, continuously operating assistance system designed to provide real-time, intelligent solutions for various riding scenarios. VERONICA integrates accident detection, low-traffic route navigation, traction control advisories, and weather updates …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 14, Issue 1, 2025 · pp. 09–17 Read article
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AI and Sensor Systems Revolutionizing Intoxication and Smoking Pre- Detection
Abstract: In an increasingly interconnected and safety-conscious world, the pervasive issues of intoxication and uncontrolled smoking continue to pose significant threats to public health, safety, and productivity. From impaired driving incidents to workplace accidents, and from chronic health conditions linked to smoking to the risk of fires, the societal and economic costs are staggering. However, a new frontier in preventative technology is emerging: sophisticated AI and sensor-based systems designed for the …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 3, 2025 · pp. 14–25 Read article
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IoT-Based Industrial Safety Management Systems
Abstract: The integration of the Internet of Things (IoT) in industrial safety management has transformed workplace safety by enabling real-time monitoring, predictive analytics, and automated hazard mitigation. IoT-Based Industrial Safety Management Systems utilize interconnected sensors, wearable devices, and intelligent analytics platforms to proactively detect and respond to potential risks in high-risk environments such as manufacturing, oil and gas, and construction. These systems continuously monitor critical safety parameters, including temperature, pressure, gas …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 1, 2025 · pp. 18–22 Read article
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A Systematic Review on Coronary Heart Disease: A Transient Ischemic Stroke
Abstract: Coronary Heart Disease (CHD) and Transient Ischemic Attack (TIA) are significant cardiovascular and cerebrovascular disorders that often share similar risk factors and underlying pathophysiological processes. CHD involves the narrowing or obstruction of the coronary arteries due to atherosclerosis, resulting in diminished blood flow to the heart. A transient ischemic attack (TIA), often called a "mini stroke," occurs when blood flow to the brain is briefly disrupted, usually due to a …
Published in Research and Reviews : Journal of Surgery · Vol. 14, Issue 3, 2025 Read article
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Advanced Lithium-Ion Battery Prognostics: A Comprehensive Review of Machine Learning Approaches for Remaining Useful Life Prediction
Abstract: The lithium-ion battery (LIB), as one of the main sources for portable power systems, has been increasingly popular owing to its widespread applications in electric vehicles, consumer electronics, aerospace and renewable energy. Despite their advantages in high energy density and long cycle life, LIBs suffer from degradation over time of aging and cycling, resulting in loss of performance, safety issues, and economic bottlenecks. Predicting their Remaining Useful Life (RUL) is …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 2, 2025 · pp. 12–27 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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Epidemiology and transmission of infectious diseases study using Machine learning
Abstract: Infectious diseases remain a formidable global health challenge, characterized by rapid evolution and complex transmission dynamics that often outpace traditional epidemiological surveillance and response mechanisms. This study investigates the transformative potential of machine learning (ML) methodologies to enhance our understanding and prediction of infectious disease epidemiology and transmission. Leveraging diverse datasets—including clinical records, genomic sequences, environmental factors, social mobility data, and real-time digital footprints—we studies and presented various ML models …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 Read article
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A study on IoT and AI for Predictive Modeling and Control of Infectious Disease Transmission
Abstract: Background: The global response to novel and recurring infectious diseases is frequently hindered by surveillance systems that are slow, siloed, and reactive. Traditional epidemiology relies on retrospective analysis of clinical reports, often missing the critical early phase of autocatalytic spread. The urgency of modern public health necessitates a shift toward real-time, predictive intelligence. Methods: This study investigates the development and deployment of a synergistic paradigm integrating the Internet of Things …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 Read article
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Identification and Evaluation of Safety Factors in Construction Industry Using Fuzzy Reasoning Technique
Abstract: Modern construction projects, characterized by their complexity and uniqueness, are inherently susceptible to various risks. These risks represent uncertain events that may arise during the project's life cycle, potentially influencing its objectives either positively or negatively. Positive risks are referred to as opportunities, while negative risks are identified as threats. To effectively harness these opportunities and mitigate threats, the implementation of Risk Management is essential. A novel theoretical framework known …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 3, 2025 · pp. 7–12 Read article
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Embracing Health, Safety, and a Greener Environment in the Construction of Offshore Structures
Abstract: Offshore infrastructure (oil and gas platforms, offshore wind farms, subsea cables, ports, and associated works) plays a vital role in energy, communications, and trade. However, construction activities offshore create complex safety, public health and environmental risks from worker injuries and exposure to hazardous substances, to marine pollution and ecosystem damage with downstream human health effects. This paper reviews the hazards, regulatory and management frameworks, lessons from major incidents, and practical …
Published in Journal of Offshore Structure and Technology · Vol. 12, Issue 3, 2025 · pp. 30–41 Read article
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IoT and Smart Sensors for Structural Health Monitoring: Trends, Challenges, and Future Directions
Abstract: Structural Health Monitoring (SHM) plays a critical role in ensuring the safety, resilience, and sustainability of civil infrastructure systems. In recent years, the convergence of Internet of Things (IoT) technologies and smart sensor systems has revolutionized the field of SHM. This integration enables continuous, real- time monitoring, facilitates predictive maintenance, and reduces the costs associated with structural inspections. IoT-based SHM frameworks leverage wireless sensor networks, cloud computing platforms, and intelligent …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 3, 2025 · pp. 1–6 Read article
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Sensors and Artificial Intelligence based Intelligent Thermos
Abstract: For more than a century, the traditional thermos bottle—a passive container for temperature control—has essentially not altered. This offers a huge chance for innovation in a time when health and wellness technology are intertwined. In order to bridge the gap between basic fluid containment and proactive personal health management, this paper presents the design concept for an Intelligent Thermos, a smart hydration system. A low-power microprocessor with Bluetooth connectivity controls …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 3, 2025 · pp. 37–45 Read article
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Disaster Preparedness and Response (Comparison Between Delhi, Mussoorie and Kerala)
Abstract: Disaster preparedness and response are critical for minimizing the adverse impacts of natural and man-made disasters. These practices play a crucial role in saving lives, reducing economic losses, and ensuring the resilience and recovery of communities. By prioritizing preparedness and response, societies can build resilience against the inevitable occurrence of natural and man-made disasters. This comparative analysis examines the distinct strategies employed by Delhi, Mussoorie, and Kerala, highlighting how each …
Published in International Journal of Urban Design and Development · Vol. 3, Issue 2, 2025 · pp. 71–78 Read article
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A Study of Optical Sensor in Clinical applications
Abstract: The escalating demand for precise, real-time, and minimally invasive diagnostic and monitoring tools in clinical practice has propelled the development of sophisticated sensor technologies. Among these, optical sensors have emerged as a cornerstone, leveraging the interaction of light with biological matter to translate molecular or cellular events into quantifiable signals. Their inherent advantages – including high sensitivity, specificity, rapid response times, non-ionizing nature, and potential for miniaturization – make them …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 1–7 Read article