Search
971 articles for “Pre-detection”
-
Cloud-driven Fraud Detection: Evaluating Decision Tree and Random Forest Classifiers for Credit Card Transaction Security
Abstract: With the alarming rise in global financial fraud, necessitating substantial annual losses, modern techniques for fraud detection are continuously evolving across various business domains. Fraud detection involves constant monitoring of user activities to estimate, perceive, or prevent undesirable behaviour. Cloud Computing emerges as a promising solution, accelerating application deployment, fostering creativity and innovation, reducing costs, and enhancing overall business acumen. This study introduces a cloud-driven approach to fraud detection, specifically …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 1, 2024 · pp. 13–27 Read article
-
Hormonal Shifts and Vision Changes: Addressing the Needs of Women During and After Pregnancy
Abstract: Pregnancy and the postpartum period are marked by significant hormonal fluctuations that can profoundly affect a woman’s vision health. This review explores the relationship between hormonal shifts during pregnancy and the onset of common vision changes, including but not limited to dry eyes, blurred vision, and retinal changes. These changes are often temporary but can indicate underlying complications such as gestational diabetes, preeclampsia, and other pregnancy-related conditions that may threaten …
Published in International Journal of Women's Health Nursing And Practices · Vol. 3, Issue 1, 2025 · pp. 19–24 Read article
-
Mycotoxins in Grains: Toxicological Impact, Detection Strategies, and Public Health Implications
Abstract: Many types of fungi create mycotoxins, which contaminate cereal grains like wheat, maize, rice, and barley. Even at low doses, aflatoxins, ochratoxins, fumonisins, and deoxynivalenol are harmful to humans and animals. This study covers mycotoxin occurrence, detection, toxicological consequences, and public health concerns in grain-based food systems. Advanced analytical methods, like LC–MS, ELISA, and biosensors, are discussed for their sensitivity and routine monitoring applications. Experimental and epidemiological studies analyze chronic …
Published in Research and Reviews: A Journal of Toxicology · Vol. 15, Issue 3, 2025 · pp. 8–18 Read article
-
Autonomous Fire Suppression Robot Based on Arduino
Abstract: Fire hazards continue to pose serious risks in homes, workplaces, and industrial facilities, making rapid detection and early suppression crucial for minimizing damage and protecting lives. This paper presents the design and development of an autonomous fire suppression robot built around an Arduino- based control system. The robot is engineered to independently detect, approach, and extinguish small fires with minimal human interaction. It incorporates multiple sensing components, including flame sensors …
Published in Journal of Advancements in Robotics · Vol. 13, Issue 1, 2026 · pp. 26–32 Read article
-
Deep Learning Based Detection and Classification of Brain Tumors Using MRI Images
Abstract: Brain tumor detection using magnetic resonance imaging (MRI) is a critical task in the early detection and treatment of brain tumors. Manual analysis of brain tumor detection using MRI is a tedious task that requires expertise in the field. Therefore, this study proposes a deep learning-based approach for brain tumor detection and classification using Convolutional Neural Networks (CNN). The proposed approach preprocesses the MRI image using normalization, resizing, and noise …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
-
Cross-Domain Comparative Analysis of Microwave Imaging Systems for Medical Diagnostics and Industrial Testing
Abstract: Microwave imaging is gaining significant traction as a non-ionizing, low-cost, and portable alternative to conventional diagnostic and inspection modalities in both medical and industrial domains. Leveraging the dielectric contrast between healthy and anomalous tissues or materials, microwave imaging systems enable early-stage detection and characterization of pathological or structural anomalies. This review provides a detailed comparative analysis of microwave imaging systems tailored for three critical applications: breast cancer detection, brain stroke …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 2, 2025 · pp. 39–48 Read article
-
Advanced Energy Metering and Automated Control System
Abstract: In this paper need for energy efficiency especially combining smart metering with control of load and prepaid billing becomes insistent. An ESP32-based Advanced Energy Metering and Automated Load Control System, is presented in this paper taking advantage of an IoT-capable smart meters, real-time data analytics, motion detector-based automation scheduling, Real-time clock (RTC) module-enabled scheduling, and GSM based prepaid billing notifications. The central controller, responsible for real-time energy monitoring, automated load …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 2, 2026 Read article
-
Drug Induced Immune Mediated Nephritis: Molecular Mechanism , Pathways and Clinical Implications
Abstract: Drug-induced immune-mediated nephritis (DI-IMN) has become a more widely known cause of acute kidney injury (AKI), with the potential for development to chronic kidney disease if not detected and treated promptly. T-cell hypersensitivity to pharmaceuticals, such as antibiotics, proton pump inhibitors, nonsteroidal anti-inflammatory drugs, and immunological drugs, are the major causes for it. Beyond clinical burden, DI-IMN reflectsintricate molecular interactions that sustain interstitial inflammation and tubular injury. These interactions include …
Published in International Journal of Toxins and Toxics · Vol. 3, Issue 1, 2026 · pp. 13–29 Read article
-
Machine Learning-Based Disease Prediction: A Comparative Analysis for Diabetes, Brain Tumor, and Parkinson's Disease
Abstract: This paper presents a web-based disease prediction system that integrates machine learning and deep learning techniques to assist in the early detection of Parkinson’s Disease, Diabetes, and Brain Tumors. By utilizing clinical data and MRI images, the platform provides rapid and interpretable predictions to support proactive health management. Logistic Regression models are applied to classify structured datasets for predicting Parkinson’s disease and Diabetes, making use of their effectiveness in binary …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 44–54 Read article
-
AI For Climate Vulnerability Assessment
Abstract: Climate change is one of the biggest problems we face every day. The main problems are high temperatures, rising sea levels, and changes in weather, which will be worse in the upcoming years. To predict and adapt to these impacts, we need to create data-driven solutions. The main tool for predicting climate change was artificial intelligence, which can also be utilised to predict the weather and alert people of impending …
Published in International Journal of Radio Frequency Innovations · Vol. 3, Issue 1, 2025 · pp. 18–33 Read article
-
Multimodal Disease Detection Using Deep Learning
Abstract: Artificial Intelligence (AI) is playing an increasingly pivotal role in modern healthcare, particularly in improving the speed and accuracy of disease detection. With the evolution of Machine Learning (ML), Deep Learning (DL), and high-performance computing, AI-based solutions are now capable of processing extensive medical datasets, ranging from patient records to diagnostic images, with remarkable efficiency. These systems offer immense potential for early intervention, improved clinical decision-making, and alleviating pressure on …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 129–139 Read article
-
Efficient Machine Defect Detection with Sugeno Fuzzy Membership and GRU Networks for Robust Industrial Automation
Abstract: Machine fault detection is of immense significance in industrial automation to achieve efficient operations, reduced downtime, and reduced economic losses. Sugeno fuzzy logic and Gated Recurrent Unit (GRU) networks are used in this research to provide a new hybrid solution that addresses problems such as noisy data, evolving defect patterns, and real-time detection. To improve readability and reliability, the Sugeno fuzzy logic unit preprocesses fuzzy and uncertain input data into …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 17–26 Read article
-
Early Alzheimer's Disease Detection Using Deep Ensemble Learning and MRI Image Analysis
Abstract: Early detection of Alzheimer's disease (AD) is crucial to slowing cognitive decline and enabling timely clinical interventions. Traditional diagnostic methods, including cognitive tests and single-model classifiers, have limited sensitivity during early stages of the disease. This paper presents a deep ensemble learning approach that integrates multiple convolutional neural networks (CNNs) for accurate Alzheimer's disease detection using structural Magnetic Resonance Imaging (MRI) data. The proposed framework utilizes ResNet50, VGG16, and DenseNet121 …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
-
Infrared Radiation: A Non-Invasive Approach to Cholesterol Measurement
Abstract: Cholesterol levels and Diabetes have become prevalent worldwide. People who are physically disabled or unresponsive need to have their glucose and cholesterol levels constantly checked because it is hard to get accurate readings through invasive procedures or blood samples. Based on the proposed model, Hyperglycemia and Cholesterol amounts might be found without touching or taking blood specimens. The Arduino UNO and basic infrared sensors are used to make this happen. …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 3, 2024 · pp. 28–34 Read article
-
Retinal Disease Detection Using Deep CNN
Abstract: Age-related macular degeneration, glaucoma, and diabetic retinopathy are the three main causes of blindness in the globe. To avoid visual loss, early identification and treatment of these disorders are essential. The goal of this research is to create an automated method for detecting retinal diseases by analyzing retinal fundus pictures with machine learning techniques. Python and the Tkinter package for the graphical user interface are used in the construction of …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 46–50 Read article
-
Deep Learning Applications in Bone Fracture Detection for Improved Radiographic Diagnostics
Abstract: Bone fracture detection is a critical aspect of medical diagnostics, traditionally relying on manual interpretation of radiographic images by experienced radiologists. This discipline has undergone a revolution with the introduction of machine learning (ML), which can improve accuracy, shorten diagnosis times, and lessen human error. This study investigates the use of different machine learning methods to enhance and automate the identification of bone fractures in radiography pictures. We utilized a …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 17–22 Read article
-
An Integrated Satellite and Underwater IoT Framework for Real-Time Oceanic Disaster Monitoring and Resilient Communication
Abstract: Ocean-based environmental disasters such as tsunamis and underwater earthquakes pose significant risks to human life, coastal infrastructure, and regional stability. However, traditional communication networks often collapse during such events, leading to delayed alerts and uncoordinated response efforts. This study presents an integrated framework that combines underwater Internet of Things (IoT) systems with satellite communication technologies to enable real-time oceanic disaster monitoring and reliable emergency communication. The system connects underwater sensor …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 2, 2025 · pp. 34–40 Read article
-
Comparative Study of Change Detection Methods in High Resolution Images
Abstract: Natural phenomena including weathering, erosion, volcanic eruptions, and plate tectonics, as well as human activities like agriculture, deforestation, and urbanization, cause the Earth's surface to change continuously. In many different applications, such as environmental monitoring, disaster management, urban planning, agriculture and forestry, climate change studies, resource management, and infrastructure monitoring, it may be extremely beneficial to detect and track these changes. There are various algorithms and methods proposed by many …
Published in Journal of Remote Sensing & GIS · Vol. 15, Issue 2, 2024 · pp. 1–5 Read article
-
IoT-Based Manhole Detection and Monitoring System
Abstract: Urban drainage systems face numerous challenges, including blockages, harmful gas accumulation, and flooding, which pose risks to public safety and environmental health. This project introduces an IoT-enabled solution designed to monitor and address these issues efficiently. The system incorporates sensors to detect critical parameters such as gas levels, temperature, water presence, and nearby obstacles. A unique lifting mechanism ensures the hardware adapts to challenging conditions, maintaining uninterrupted operation. The system …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 3, 2025 · pp. 1–6 Read article
-
Arduino Empowered: Smart Glove Review and Analysis
Abstract: In recent years, there has been a growing interest in wearable technology, particularly in the realm of human-computer interaction (HCI). Smart gloves, equipped with various sensors and actuators, have emerged as a promising interface for facilitating seamless interaction between humans and digital devices. This paper presents the development of Arduino-based smart gloves designed to augment conventional HCI methods by incorporating gesture recognition and tactile feedback capabilities. The smart gloves feature …
Published in Journal of Microcontroller Engineering and Applications · Vol. 11, Issue 1, 2024 Read article