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403 articles for “risk management”
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Early Flood Detection and Avoidance Using IoT
Abstract: This project presents an advanced flood alert system powered by IoT technology, designed to enhance public safety and minimize flood-related damage in high-risk areas. The system uses various sensors to keep track of environmental conditions, especially changes in water levels. These sensors are strategically placed in critical zones to detect early indicators of flooding, such as sudden increases in water level, surface runoff, and river overflow. The gathered information is …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 1–5 Read article
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Digital Transformation of Urban Infrastructure with the Help of AI Guardians
Abstract: The construction industry continues to face challenges related to quality control, safety protocols, and meeting project deadlines. These issues often result in significant cost overruns and project delays. Traditional inspection and site management approaches rely heavily on manual work and individual judgment. As a result, human errors can easily occur, and these methods provide only limited snapshots of site conditions over time. This paper presents a comprehensive framework that uses …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 16–25 Read article
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Role of Ginger (Zingiber officinale Roscoe) in Sustainable Health
Abstract: Attaining sustainable health involves a comprehensive blend of multiple factors, including structural, physiological, metabolic, and psychological aspects, alongside the cultivation of self-awareness and a sense of fulfillment. The World Health Organization (WHO) underscores in its 2030 Agenda for Sustainable Development that lifestyle-related illnesses, especially non-communicable diseases (NCDs), present considerable hurdles to sustainable progress, stressing the importance of mitigating their risk factors. Nutrition is acknowledged as a cornerstone of health preservation, …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 3, 2024 · pp. 72–76 Read article
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Non-Invasive Glucose Monitoring Device Using Max30102 Sensor
Abstract: Diabetes mellitus is a chronic metabolic disorder affecting millions globally, requiring continuous blood glucose monitoring to prevent complications such as cardiovascular disease, kidney failure, neuropathy, and retinopathy. Conventional invasive finger- prick techniques result in pain, skin irritation, and an increased risk of infection, which lowers patient compliance, particularly in young patients and the elderly. This paper presents a non-invasive glucose monitoring prototype using the MAX30102 optical biosensor interfaced with the …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 1, 2026 · pp. 36–44 Read article
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Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
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Design and Implementation of Agricultural Spraying Drone
Abstract: In this brief an attempt has been made to develop an agricultural drone to spray pesticides in an agricultural farm. In India, agriculture is one of the key economic sectors. Crop production rates are influenced by factors such as temperature, moisture content, rainfall, etc. The field of husbandry is also influenced by other elements, such as pests, complaints, diseases, etc., which can be managed by giving crops the right care. …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 1, Issue 1, 2023 · pp. 28–33 Read article
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Association of Metabolic Syndrome with Cholelithiasis in Female Patients and Its Impact on Clinical Management and Surgical Outcome
Abstract: Background: Metabolic syndrome (MetS) is associated with obesity, insulin resistance, dyslipidemia, and hypertension, which may predispose to gallstone formation. This study aimed to evaluate the association between MetS and cholelithiasis in female patients and to assess its impact on clinical presentation, surgical difficulty, and postoperative outcomes. Methods: A prospective observational study was conducted on 88 female patients with ultrasonography-confirmed cholelithiasis. Patients were divided into two groups: MetS (n=44) and non-MetS …
Published in Research and Reviews : Journal of Surgery · Vol. 14, Issue 3, 2025 · pp. 1–7 Read article
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The Heat of Competition: Assessing Climate Vulnerabilities and Adaptive Governance in Endurance, Winter, and Youth Sports
Abstract: Background: Climate change is fundamentally reshaping the environmental parameters of global sport, posing unprecedented risks to athlete health, safety, and performance. As rising temperatures, frequent extreme heat events, and deteriorating air quality become the new normal, athletic environments from community fields to elite international arenas face an existential threat. Purpose: This study provides an interdisciplinary synthesis of the multifaceted impacts of climate change on athletes, integrating evidence from sports medicine, …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 9–17 Read article
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Integrated Dam Automation: Real-Time Monitoring and Controlling Using IoT
Abstract: Dam automation is a critical area in water resource management, especially given the rising demand for sustainable and safe water control systems. An integrated approach to dam automation involves implementing advanced sensors and monitoring systems to improve structural safety, water quality, and resource management. This paper presents a comprehensive automation model that combines crack detection, convolutional neural networks (CNNs), water level monitoring, turbidity sensing, and rainfall data to ensure real-time …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 31–38 Read article
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Blockchain Infused Decentralized Land Registry System
Abstract: Accurate land measurement and documentation of land ownership and use are critical for effective land administration and management. However, traditional land measurement systems are often inefficient, inaccurate, and lack transparency, which can lead to disputes, fraud, and corruption. To address these issues, we propose a smart contract-based land measurement system that provides a secure, transparent, and efficient way to measure and document land ownership. Our system utilizes smart contracts, which …
Published in Current Trends in Signal Processing · Vol. 14, Issue 2, 2024 · pp. 11–19 Read article
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Design and Development of an Automated Robotic Algorithm for Blasting, Painting, and Barnacle Cleaning of Offshore Structures
Abstract: Marine surface maintenance tasks such as barnacle removal, abrasive blasting, and protective painting are traditionally carried out using manual methods that are labor-intensive, hazardous, and prone to variability in quality. These challenges are particularly significant for offshore structures, where harsh environmental conditions and restricted accessibility increase operational risks and maintenance costs. This paper presents the design and evaluation of an autonomous robotic system for automated surface preparation and coating of …
Published in Journal of Offshore Structure and Technology · Vol. 13, Issue 1, 2026 · pp. 1–12 Read article
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A Threshold-Weighted Mathematical Fusion Model for Epidemic Outbreak Prediction Using SEIR Residual Dynamics and Cloud-Based Machine Learning
Abstract: Accurate prediction of epidemic outbreaks is critical for effective public health management, resource planning, early warning generation, and timely intervention by municipal authorities. Traditional compartmental models such as Susceptible–Exposed–Infectious–Recovered (SEIR) offer valuable epidemiological insights and mathematical interpretability; however, they may not adequately capture the complex nonlinear relationships present in real-world urban health systems. Conversely, data-driven machine learning techniques can identify hidden patterns in large datasets but often lack epidemiological structure …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 12–19 Read article
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Necrotizing Enterocolitis (NEC): A Devastating Neonatal Gastrointestinal Disorder
Abstract: Necrotizing enterocolitis (NEC) represents a formidable challenge in neonatal medicine, particularly afflicting premature infants with its characteristic features of severe intestinal inflammation and necrosis. Despite advancements in neonatal care, NEC continues to exact a heavy toll, standing as a prominent cause of morbidity and mortality in this vulnerable population. Its multifaceted etiology, encompassing prematurity, enteral feeding practices, alterations in microbial colonization, and episodes of intestinal ischemia, underscores the complexity of …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 78–83 Read article
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Integrating Atmospheric Science: Understanding Greenhouse Gases, Aerosols, and Air Quality Dynamics
Abstract: Atmospheric science investigates the Earth’s atmospheric systems to understand their composition, dynamics, and the implications for climate, weather, and air quality. This review explores five primary areas within the field: atmospheric composition, atmospheric modeling, remote sensing, air pollution, and boundary layer dynamics, highlighting critical challenges and advancements. Rising levels of greenhouse gases (GHGs), including carbon dioxide and methane, continue to drive global warming, while feedback mechanisms—like cloud interactions and surface …
Published in International Journal of Atmosphere · Vol. 1, Issue 1, 2024 · pp. 32–35 Read article
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Enhancing Border Security: Smart Surveillance System
Abstract: Advanced technology solutions are required to assure safety, prevent infiltration, and efficiently monitor activities in light of the growing risks to national security along international borders. The Enhancing Border Security System: Smart Surveillance System" project suggests a reliable, economical, and clever surveillance system designed for in-the-moment border monitoring. In order to provide a thorough security framework, this system combines contemporary sensors, motion detectors, infrared cameras, and wireless communication modules. Detecting …
Published in Journal of Microcontroller Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 11–19 Read article
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Innovative Approaches to Reducing Data Traffic in IoT Networks Using Deep Learning and Compressive Sensing
Abstract: The exponential growth of internet of things (IoT) devices has posed unprecedented challenges in managing the massive data generated by real-time monitoring, automation, and analytics. Existing network infrastructures lack scalability, bandwidth, and suffer from latency problems, further making data transmission less efficient. This study surveys innovative approaches using deep learning and compressive sensing to reduce IoT data traffic. Deep learning is able to upgrade data processing by means of very …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 46–62 Read article
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A Study on Heavy Metal Contamination in Workers Handling Electronic Waste in North India
Abstract: Background E-waste contains hazardous substances like leads, cadmium, mercury, and arsenic which can be harmful for informal workers and recyclers. In North India, one finds an informal sector of e-waste workers who work in extremely micro-manageable conditions with lack of order policy and protective equipment. This study explores the processes and cavities of heavy metals as well as assessing the knowledge, safety measures, and health symptoms of the reclaimers. Objectives …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 15, Issue 2, 2025 Read article
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Exploring the Effects of Yogic Meditation on Stress, Anxiety, and Cardiovascular Health: A Prospective Cross-Sectional Cohort Study at Desh Bhagat Hospital
Abstract: Background: Stress and anxiety are significant risk factors for cardiovascular disorders, with growing evidence suggesting that yogic meditation can mitigate these effects. This prospective cross-sectional cohort study was conducted to evaluate the impact of yogic meditation on stress, anxiety, and cardiovascular parameters among patients attending Desh Bhagat Hospital. Methods: A cohort of 350 patients was recruited, comprising individuals presenting with elevated stress, anxiety, or cardiovascular conditions. Participants underwent a guided …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 14, Issue 1, 2025 Read article
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Assessment of dietary sources, eating habits, and lifestyle among Pharmacy students in India
Abstract: Aim and Objective: Balanced Diet and their sources play a vital role in maintaining physical, mental and health, especially in college students and in teenagers. Knowledge regarding the dietary source, and eating habits of Pharmacy students is important as health care professionals play critical and central role in management and in accessing the quality of health care population. The purpose of this survey study is assessment of dietary sources, eating …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 14, Issue 2, 2024 · pp. 49–55 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