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192 articles for “predictive systems”
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Application of Resource Allocation Similarity Based Link Prediction in Wireless Networks
Abstract: Link prediction in wireless networks plays a crucial role in predicting missing connections within multiplex networks. This study focuses on the utilization of similarity-based link prediction methods in wireless networks. These methods assume that the likelihood of linkage between nodes is determined by their similarity, based on shared features. Several similarity measures, such as Common Neighbors (CN), Preferential Attachment (PA), Adamic-Adar (AA), and Resource Allocation (RA) indices, are commonly employed …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 2, 2023 · pp. 37–42 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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Cyclist Safety Enhancement: A Multi-Modal Hazard Detection System
Abstract: This study presents a multi-modal hazard detection system to enhance cyclist safety in urban environments. Lever- aging a combination of computer vision, object tracking, and predictive modeling, the system offers a comprehensive approach to identifying and mitigating potential risks. Key contributions include improved depth estimation through object size priors, multi-class tracking utilizing KCF and Brisk, and a novel recurrent neural network architecture for predicting bicycle movement. The system’s collision detection …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 1, Issue 2, 2023 · pp. 35–83 Read article
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IoT-Based Battery Health Monitoring for Electric Vehicles Using Machine Learning
Abstract: With increasing utilization of the Electric Vehicles (EV)s in global scale, battery health management becomes a critical factor which has great impact on vehicle performance, safety and longevity. Battery materials, such as NMC LFP lithium-ion batteries and lithium-ion batteries, degrade over time from charging behaviour, heat stress, discharging voltage profiles and environmental limits. Conventional BMS only offer threshold based health diagnostics and cannot perform accurate degradation prediction. This work presents …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 Read article
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Solar Thermal Energy Utilization: Design Innovations and Performance Enhancement Techniques
Abstract: The utilization of solar thermal energy has become increasingly significant in the pursuit of sustainable and low-carbon energy solutions. Unlike photovoltaic technologies that directly convert sunlight into electricity, solar thermal systems focus on harnessing solar radiation to generate heat, which can then be applied to diverse sectors such as water heating, space conditioning, industrial process heating, and power generation. In recent years, substantial research efforts have been directed toward enhancing …
Published in International Journal of Energy and Thermal Applications · Vol. 3, Issue 2, 2025 · pp. 1–5 Read article
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GenChrome-ML: A Machine Learning Framework for Early Detection of Chromosomal Disorders Using Genomic Data
Abstract: The increasing burden of chronic disease and cancer demands innovative, more rapid and effective diagnostic tools in the field of healthcare. The majority of current diagnostic tools are dependent upon clinical symptomology and manual evaluation, leading to delays in early detection and treatment. The development of artificial intelligence (AI) and machine learning (ML), in recent years, has offered opportunities for the enhancement of disease prediction, diagnosis and personalization of treatment …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Smart-Waste-Management-System
Abstract: The rapid urbanization and increasing waste generation pose significant challenges to traditional waste management systems, necessitating innovative solutions that integrate economic principles and management strategies. In order to enhance trash transportation and recycling procedures, this paper investigates the deployment of a Smart trash Management System that makes use of Internet of Things (IoT) components and machine learning algorithms. By applying economic principles such as cost-benefit analysis and resource allocation, and …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 18–27 Read article
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Strategy for Improving Software Maintenance Using Machine Learning for Security Requirements: A Review
Abstract: Within the area of software technical education, the significance of software defect discovery has increased as a research focus to enhance program reliability. By maximizing testing resources and assisting developers in identifying potential problems using program defect predictions, program dependability is increased. Applying software engineering (SE) techniques to critical and intricate systems, like networking and security systems, is imperative. Traditional methods of predicting software maintainability have limitations, particularly in balancing …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 2, 2024 · pp. 36–48 Read article
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Human-robot Collaboration in Manufacturing: Safety, Efficiency, and Technological Developments
Abstract: Human-robot collaboration (HRC) has emerged as a transformative force in modern manufacturing, significantly enhancing productivity, operational flexibility, and overall efficiency. This review article explores the fundamental aspects of HRC, with a particular focus on safety protocols, efficiency optimization, and technological advancements that are shaping the future of collaborative robotics. Ensuring safety in HRC environments is a primary concern, necessitating the implementation of advanced safety measures, risk assessment methodologies, and compliance …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 1, 2025 · pp. 18–23 Read article
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Multimodal Data Fusion with Hybrid Machine Learning for Enhanced Prediction of Li-Ion Battery Remaining Useful Life and State of Charge
Abstract: Lithium-ion battery materials used in modern energy storage systems are required to exhibit high reliability, safety, and long lifecycle performance under varying operational and environmental conditions. Accurate prediction of Remaining Useful Life (RUL) and State of Charge (SoC) is therefore essential for understanding material degradation behavior, improving manufacturing quality, and enabling effective lifecycle management. However, nonlinear electrochemical aging, load variability, and thermal uncertainty significantly complicate accurate estimation of these parameters. …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 4, Issue 1, 2026 · pp. 1–5 Read article
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Revolutionizing Petrology and Mineralogy: The Study of AI and Advanced Sensor Technologies
Abstract: Petrology and mineralogy are fundamental to understanding Earth's intricate processes, from crustal evolution to economic resource formation. However, traditional methods, while precise, are often laborious, time-consuming, and occasionally subject to interpretive bias. This abstract explores the transformative potential of integrating cutting-edge Artificial Intelligence (AI) and advanced sensor technologies to revolutionize data acquisition, analysis, and interpretation in these critical geosciences. Advanced sensor technologies, including high-resolution spectral imaging (hyperspectral, Raman), automated X-ray …
Published in International Journal of Minerals · Vol. 2, Issue 2, 2025 · pp. 1–11 Read article
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Smart Monitoring and Controlling of the Battery and Motor
Abstract: The demand for effective battery and motor monitoring and management to guarantee dependability, safety, and peak performance has increased due to the quick development of electric vehicles and smart industrial systems. The smart monitoring and control methods used in battery management systems and motor control systems are thoroughly reviewed in this paper. In addition to speed, torque, efficiency, and fault situations in motors, it emphasizes important characteristics like temperature, voltage, …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 11–15 Read article
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AI-driven Flood Surveillance and Dam Control: Advancing Resilience Through Data Science
Abstract: This study presents the development and real-world deployment of an intelligent system for flood monitoring and automated dam gate control using artificial intelligence (AI) and internet of things (IoT) sensors. Supervised machine learning models are developed to predict floods up to 48 h in advance. An automated dam gate operation system is designed to leverage the flood forecasts and real-time stream water levels for emergency control. The complete end-to-end infrastructure …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 2, 2023 · pp. 9–17 Read article
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Use of Emerging Technologies in Disaster Management
Abstract: India, one of the most disaster-prone nations, faces increasing challenges from natural and man- made disasters. To address these risks, the country has developed a multi-tiered institutional framework, led by the National Disaster Management Authority (NDMA) and supported by state and local bodies. While these efforts provide a strong foundation, the integration of emerging technologies is reshaping disaster management. Technologies like Artificial Intelligence (AI), drones, and advanced early warning systems …
Published in International Journal of Pollution: Prevention & Control · Vol. 3, Issue 1, 2025 · pp. 01–07 Read article
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Remote Sensing in Atmospheric Studies: Enhancing Understanding of Climate Dynamics and Air Quality, Atmospheric Monitoring and Analysis; Emerging Technologies and Future Directions
Abstract: Remote sensing has emerged as a transformative tool in atmospheric sciences, providing detailed and comprehensive insights into various atmospheric phenomena. Its advanced capabilities have revolutionized our understanding of climate dynamics, air quality, and atmospheric composition, enabling more accurate monitoring and analysis. This paper reviews the critical role of remote sensing technologies in enhancing knowledge of atmospheric processes and their practical applications in areas such as climate change monitoring, air pollution …
Published in International Journal of Atmosphere · Vol. 2, Issue 1, 2025 · pp. 1–5 Read article
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Explainable GeoAI-Based Multi-Temporal Remote Sensing Framework for Early Detection of Climate-Induced Land Cover Transformation
Abstract: Climate change has emerged as one of the primary drivers of rapid land cover transformation, affecting ecosystems, agricultural productivity, biodiversity, and regional sustainability. Traditional remote sensing approaches often face challenges in detecting subtle and early-stage land cover changes due to limitations in temporal analysis and model interpretability. This study proposes an Explainable GeoAI-based multi-temporal remote sensing framework for the early detection of climate-induced land cover transformation using multi-source satellite imagery …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 2, 2026 Read article
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Hand Gesture Recognition Systems: A Review of Vision-based and Sensor-based Approaches
Abstract: With many real-world uses, such as sign language translation and human-computer interaction, hand gesture detection is a crucial area of study in the science of computer vision. In this study, we propose a Convolutional Neural Network (CNN) model that uses real-time camera images to recognise hand gestures. A collection of hand motion photographs spanning the English alphabet (A-Z) was gathered, and the images were pre-processed to exclude any backdrop and …
Published in International Journal of Optical Innovations & Research · Vol. 1, Issue 1, 2023 · pp. 15–20 Read article
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IoT-Based Motor Protection and Control System Using PLC and ESP8266
Abstract: Because of their straightforward design and affordable price, single-phase induction motors are frequently utilized in residential and small-scale industrial settings. However, conventional direct-on-line (DOL) control provides fixed-speed operation and offers limited protection against thermal overload and fault conditions. This article describes the design and implementation of an ESP8266 Node MCU-based PLC- based closed-loop motor control system with Internet of Things features. To increase operating flexibility and maintenance efficiency, the suggested …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 1, 2026 · pp. 54–62 Read article
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History and Applications of Kalman Filter: A Review
Abstract: The Kalman filter is a powerful algorithm that is used to estimate the dynamic system states with noisy measurements and uncertain behaviors. It is an optimal estimator that minimizes the average squared error between the estimated states and the true states, given the noisy data and a model of the system. The recursive algorithm is highly effective in tracking and predicting the state of complex systems over time. Kalman filters …
Published in International Journal of Electrical Power and Machine Systems · Vol. 2, Issue 1, 2024 · pp. 14–23 Read article
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A review on polyhouse monitoring system
Abstract: The integration of Internet of Things (IoT) technology in agriculture has revolutionized traditional farming practices, offering innovative solutions to enhance productivity, sustainability, and resource efficiency. This study explores the role of loT-based systems in smart agriculture, focusing on applications such as environmental monitoring, automated irrigation, crop health prediction, and precision farming. The reviewed systems utilize advanced sensors to monitor parameters like temperature, humidity, soil moisture, and light intensity, transmitting real-time …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 2, 2025 · pp. 1–9 Read article