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459 articles for “Detection Algorithm”
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Development of a Soft Computing-Based Island Detection System and Performance Analysis
Abstract: There has been an overestimation of the global energy consumption in the last few years. Distributed Generators are being propelled forward by the motivation provided by the absence of suitable transmission capacity, exaggerated transmission and distribution mishaps, and the release of power marketing (DGs). It's a distributed age unit (DG slash hack expansion) and regional units linked to distribution that power the system, which has yet to have hundreds of …
Published in Journal of Semiconductor Devices and Circuits · Vol. 8, Issue 3, 2021 · pp. 1–15 Read article
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Intelligent Robotics using microelectronics Exploring the Future of Smart Machines
Abstract: In the past few years, robotics technology has made remarkable progress. In order to assist humans in their work, robots that can recognise and track people are required; as a result, tools like the "Human Following Load carrier" that can converse and live with people must be created. Localising the robot and its surroundings is one of the primary obstacles in enabling the robot to do different jobs in the …
Published in Journal of Nuclear Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 10–17 Read article
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Predicting Multiple Diseases Using Machine Learning: A Data-Driven Approach
Abstract: The increasing prevalence of chronic and life-threatening diseases highlights the need for innovative healthcare solutions that enable early detection and proactive management. The Multiple Disease Prediction Platform is a web-based system utilizing machine learning (ML) and deep learning (DL) algorithms to analyze user-inputted health data, generating real-time predictions of potential health risks. By leveraging Python’s Streamlit library, the platform provides an interactive and accessible diagnostic experience, eliminating the need for …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 16–35 Read article
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Speed Measurement of Moving Object using Arduino
Abstract: This research paper presents the design, construction, and testing of a low-cost and reliable system for measuring the speed of moving objects using an Arduino micro controller. The project employs Infrared (IR) sensors as photo gates to detect the time taken by an object to travel between two fixed points, allowing the Arduino to calculate the speed using basic timing algorithms. The design provides an affordable and educational alternative to …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 1, 2026 · pp. 1–8 Read article
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Improving Dataset Integrity Through Automated Data Cleaning Techniques
Abstract: High-quality data is a fundamental requirement in data science for producing trustworthy analytical insights and effective machine learning models. Problems, including incomplete records, inconsistent entries, duplicate observations, and anomalous values, can severely reduce the accuracy and robustness of predictive systems. As modern datasets continue to expand in both volume and structural complexity, relying on manual data cleaning methods become time-consuming and error-prone, highlighting the growing importance of automated data preprocessing …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 40–45 Read article
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Self-Regulated Automatic Ventilation of Vehicle Interior
Abstract: In order to mitigate overheated interior of a vehicle parked in the hot summer sun and thereby to make the entering into the vehicle more comfortable, microcontroller managed module for automatic ventilation of vehicle interior is made. The module is implemented using a microcontroller as a central logical unit and a series of sensors which provide sufficient data to ensure functional, but also efficient, reliable and safe ventilation. The ventilation …
Published in Journal of Mechatronics and Automation · Vol. 3, Issue 2, 2016 · pp. 48–53 Read article
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Tank Water Quality Analysis Using Machine Learning
Abstract: Tank Water quality is a critical factor for public health, agriculture, as well as industry. Continuous monitoring of tank water quality: temperature, humidity, water level, CO2 concentration, and pH, is vital for safe usage. Using machine learning, real-time data analysis can detect anomalies, predict issues, and optimize water management, ensuring timely responses and improved safety. This intelligent approach enhances decision-making and maintains water quality effectively in various environments.We develop an …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 2, 2025 · pp. 27–34 Read article
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AI-Driven Psychological Profiling on Social Media: Mechanisms, Ethical Breaches, and Regulatory Challenges in Data Inference
Abstract: This literature review examines AI-driven psychological profiling on social media, analyzing 21 academic studies that focus on machine learning techniques such as supervised learning, deep neural networks, sentiment analysis, and natural language processing. These methodologies infer mental health indicators—such as depression, anxiety, and stress—from users' digital footprints, encompassing linguistic patterns, engagement metrics, and temporal behaviors. While these tools offer potential for early detection of psychological distress, they also raise significant …
Published in Recent Trends in Social Studies · Vol. 2, Issue 1, 2025 · pp. 1–7 Read article
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AI and IoT in Sustainable Agriculture: A Review
Abstract: Artificial Intelligence (AI) and Internet of Things (IoT) integration have transformed the world of sustainable agriculture, presenting new ways of resource optimization, increasing crop yields, and making environmental sustainability more accessible. The current literature review analyzes the applications of AI and IoT in three significant agricultural systems: aquaponics, hydroponics, and poultry farming. By critically analyzing recent studies, this paper emphasizes how deep learning- enabled computer vision techniques allow for the …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 2, 2025 · pp. 32–45 Read article
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Development of a Generative AI Model for Early Detection and Prevention of Electrical Faults in Thermal Power Plants
Abstract: Electrical faults in thermal power plants can lead to severe equipment damage, production downtime, and safety hazards if not detected in advance. This study presents the development of a Generative Artificial Intelligence (GenAI) model for the early detection and prevention of electrical faults using predictive analytics. The proposed framework integrates Generative Adversarial Networks (GANs) with deep learning (CNN) and machine learning algorithms (Random Forest, Logistic Regression) to enhance data diversity, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 45–54 Read article
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Applications of Depth-First Search
Abstract: AbstractIn this paper, various applications of depth-first search algorithms (DFS) are surveyed. The value of DFS or “Backtracking” as a technique for solving problem is illustrated by many applications such as cycle detection, strongly connected components, topological sort, and find articulation point in a graph. The time complexity in different applications of DFS is also summarized.Keywords: depth-first search, articulation point, strongly connected component, detecting cycle, graph, topological sort, railway rescheduling
Published in Journal of Computer Technology & Applications · Vol. 4, Issue 2, 2013 · pp. 1–9 Read article
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A Conceptual Framework for AI-Integrated Metabolomics in Predictive Health Systems for Resource-Constrained Environments
Abstract: The increasing prevalence of non-communicable diseases (NCDs) continues to place a significant strain on healthcare systems, particularly in low- and middle-income regions where access to early diagnostic infrastructure is limited. Conventional healthcare approaches remain largely reactive, often detecting diseases at advanced stages when treatment effectiveness is reduced. This challenge underscores the need for predictive, cost-effective, and data-driven healthcare solutions. This study presents a conceptual framework that integrates metabolomics with artificial …
Published in Emerging Trends in Metabolites · Vol. 3, Issue 2, 2026 Read article
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Detecting Phishing Websites Using Hybrid Methodologies
Abstract: In the digital era, personal information theft has become a widespread and increasingly severe crime. Cybercriminals, often known as hackers, use deceptive strategies, with phishing websites being a major method for stealing confidential data. These fake websites imitate legitimate ones, tricking users into revealing sensitive personal and financial information, which has led to a rise in fraud cases. To address this escalating threat, a comprehensive research paper is proposed. This …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 59–65 Read article
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Classification and Detection of Brain Tumor using Convolutional Neural Network
Abstract: Tumors are masses created when brain cells multiply uncontrollably. A brain tumor is the medical term for this condition. Brain tumors are a serious and aggressive disease that can lead to a reduced life expectancy. Developing a treatment plan is essential to raising a patient's standard of living. Tumors in different regions of the body are evaluated using a variety of imaging techniques, with MRI pictures being utilized mostly for …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 8–13 Read article
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Enhancing Crop Health: A Review of Image Processing Methods for Leaf Disease Identification
Abstract: This research presents an overview of different image processing techniques for the identification of leaf disease. Many algorithms can be used to identify and categorize leaf diseases in plants, and digital image processing provides a quick, dependable, and accurate method of disease detection. This paper presents various techniques used on multiple crops and the achieved accuracy for each model. Leaf disease detection is a critical task in agriculture to ensure …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 10–14 Read article
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AI-Driven Home Security System
Abstract: The fast-paced growth in Artificial Intelligence (AI) and computer vision technologies has created new opportunities in the realm of home security. This paper outlines a developed model of an AI-powered home security system that encompasses face recognition technology for accessing and conducting surveillance at a home in real time. The real time system is designed with advanced algorithms for facial recognition, allowing it to target authorized individuals and intruders from …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 3, 2025 Read article
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Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article
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Deploying Optimal Number of Sensors and Damage Detection in Structural Health Monitoring Using SEM-GA Method
Abstract: Detecting damages is the most important criterion in any engineering creation—be it a machine or a building. Among the engineering creation, civil engineering structures need a continuous monitoring to check their operations, performance and the health status of the structures. Damage detection cannot be done manually every time. Automated systems have to be developed in order to monitor the health of the structure periodically. Hence, structural health monitoring (SHM) aims …
Published in Current Trends in Signal Processing · Vol. 6, Issue 2, 2016 · pp. 28–35 Read article
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Arduino Fire Guardian: Empowering Fire Safety with Robotics
Abstract: Identification of early fires is crucial in preventing losses. Fires often result in significant damage due to the lack of timely detection. Detecting and extinguishing fires early can protect lives and property. Robotics has become popular due to many advances in technology. A properly equipped robot will detect the fire. In the situation of a fire, a mounted robot will be directed to extinguish it. Equipped with sensors and a …
Published in Journal of Thermal Engineering and Applications · Vol. 11, Issue 1, 2024 · pp. 20–27 Read article
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Predictive Maintenance Strategies for Safety-critical Mechanical Systems
Abstract: Ensuring the reliability and safety of industrial systems is essential, especially in high-risk sectors such as aerospace, manufacturing, and energy. Predictive maintenance (PdM) has become a crucial approach for minimizing operational failures and improving maintenance efficiency. This research introduces an advanced PdM framework that enhances industrial safety by integrating Internet of Things (IoT) technology, machine learning (ML), and big data analytics. By enabling real-time monitoring and predictive fault detection, this …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 1, 2025 · pp. 12–17 Read article