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1074 articles for “prediction system”
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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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Symmetry Breaking in Mathematical Models: Bifurcation, Chaos, and Pattern Formation
Abstract: Symmetry breaking serves as a central organizing principle in the understanding of nonlinear systems across physics, biology, chemistry, and engineering. When a system transitions from a symmetric state to an asymmetric configuration, it often signals the onset of new structures, dynamic behaviors, or even chaotic regimes. This review explores symmetry breaking from the theoretical and mathematical perspectives of bifurcation theory, chaos theory, and pattern formation. We discuss how small parameter …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 2, 2025 · pp. 25–30 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. 11–23 Read article
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Advancements in Heat Exchanger Design for Improved HVAC System Efficiency
Abstract: Due to their direct impact on usage of energy, operational effectiveness, and environmental sustainability, heat exchangers have become vital components of the air conditioning, ventilation, and heating (HVAC) systems. The growing demand for energy-efficient HVAC solutions has driven extensive research and development efforts aimed at improving heat exchanger performance. Traditional designs, such as shell-and-tube and fin-and-tube heat exchangers, have long been utilized in HVAC applications. Nevertheless, these traditional types frequently …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 12, Issue 1, 2025 · pp. 44–52 Read article
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Development of a Blockchain-Based System for Drug Counterfeiting and Traceability in the Pharmaceutical Supply Chain
Abstract: Counterfeit drugs present a major risk to public health and pose a substantial threat to the pharmaceutical industry, leading to severe economic losses and risking patient lives. Ensuring the safety and authenticity of the pharmaceutical supply chain is critical to addressing this issue. This study presents a novel approach for enhancing the security and authenticity of the pharmaceutical supply chain through the integration of blockchain technology, decentralized storage, and artificial …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 3, 2024 · pp. 99–114 Read article
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AI-Driven Optimization of Biopolymer Composite Formulations Using IoT Data Streams
Abstract: Biodegradable polymer composites have emerged as a sustainable alternative to petroleum-based materials in packaging, biomedical, and structural applications. However, traditional formulation techniques for reinforced polymer composites often lack precision and fail to adapt to real-time variations during processing, resulting in suboptimal material performance. This research proposes a real-time AI-IoT-enabled framework to optimize biopolymer composite formulations. The goal is to intelligently tune composite properties such as mechanical strength, moisture resistance, and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 85–100 Read article
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Node Deployment Techniques for Link Prediction in Heterogeneous Social Networks
Abstract: AbstractThis research analyses the coverage problem in heterogeneous social network system with two types of sensor nodes having different sensing ranges. The Particle Swarm Optimization (PSO) algorithm is implemented for coverage optimization in heterogeneous network system. This algorithm is used for finding the optimal deployment of the sensor nodes by using specific fitness function. The performance of sensor nodes after running PSO algorithm is evaluated by using Euclidean distances for …
Published in Recent Trends in Sensor Research & Technology · Vol. 7, Issue 1, 2020 · pp. 16–22 Read article
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Model Predictive Control for a Distillation Column Model
Abstract: Model Predictive Control (MPC) is a multivariable control (requires specific handling of each input as coupling and interaction is of a far greater effect) and uses the internal dynamic model of the process, past control moves and an optimization cost function over the receding prediction horizon, to calculate the optimum control moves. In this paper, the relation between MPC parameters was studied on process constraints. Conical tank level single-input-single-output (SISO) …
Published in Journal of Mechatronics and Automation · Vol. 1, Issue 3, 2014 · pp. 11–19 Read article
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Time Series Model for National Stock Price Prediction
Abstract: The national stock exchange is widest and fully automatic trading system in India. Analysis and prediction of stock market time series data have involved considerable interest from the researchers over the last decade. In this paper, the Nifty 50 closing stock market prices were computed and predicted the trend of stock market fluctuations using time series modeling techniques, like exponential smoothing and autoregressive integrated moving average. The forecasted values of …
Published in Research & Reviews : Journal of Statistics · Vol. 7, Issue 1, 2018 · pp. 85s–90s Read article
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The Cybernetics Perspective of AI
Abstract: The complicated connection between cybernetics and AI is investigated in detail in this study. The focus was on the cybernetic basis of AI, specifically the part that control systems and feedback loops play. Norbert Wiener was one of the founders of cybernetics, which is important for understanding how machines and animals direct and talk to each other. It explains the basic ideas that have led to the progress in AI, …
Published in Journal Of Network security · Vol. 12, Issue 1, 2024 · pp. 26–30 Read article
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MediSense AI - Smart Health Analysis System
Abstract: MediSense AI is a revolutionary health analysis system that empowers users by transforming complex medical data into understandable insights. This platform utilizes advanced technologies, particularly natural language processing and machine learning, to make intricate medical terminologies accessible to individuals without a healthcare background. Leveraging Llama 3, a cutting-edge AI model developed by Meta AI, the system can analyze various forms of medical data, including the ability for users to upload …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 · pp. 20–30 Read article
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Automated Evaluation of Descriptive Answers
Abstract: This paper offers a smarter system of automatic evaluation of descriptive responses in educational tests. The time-consuming aspect of testing with traditional manual marking, the subjectivity of that process, and the impossibility of scaling it makes it inapplicable, particularly to large academic environments. To resolve the issues, the proposed solution combines the methods of Natural Language Processing (NLP) and hybrid image-text processing on the responses of handwriting and typed answers. …
Published in Emerging Trends in Languages · Vol. 3, Issue 2, 2026 · pp. 1–9 Read article
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Survey of Advanced Control Techniques for Active Power Filters in Grid Integration
Abstract: Active power filters (APFs) can increase power quality, dependability, and stability on power utilities by compensating for harmonic and reactive current components in power supplies. The performance and stability of active power filters are greatly enhanced by the control strategies used with them. When these two crucial elements start to compete, it is impossible to achieve both unity power factor (UPF) and flawless correction of current harmonics. A systematic review …
Published in Current Trends in Signal Processing · Vol. 13, Issue 3, 2023 · pp. 24–34 Read article
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Ai-Driven Healthcare System for Enhanced Diagnosis and Patient Interaction
Abstract: Deep learning techniques are used in an AI-driven healthcare system to improve disease identification and medical picture analysis. Data collection, preprocessing, model training, and evaluation are all part of the system's systematic workflow. Various deep learning architectures, such as ResNet50, VGG-16, and U-Net, are employed for precise classification and segmentation of medical images. The approach incorporates advanced techniques such as optimization, transfer learning, and data augmentation to significantly enhance the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 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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CIPHER Intelligence: AI-Powered Global Military Expenditure Analysis and Predictive Modeling
Abstract: Military expenditure analysis has emerged as a critical component of economic and geopolitical intelligence in the modern era. This paper presents CIPHER Intelligence, a comprehensive AI-powered platform for analyzing and predicting global military spending patterns across 211 countries spanning54 years (1970-2024). We employ advanced machine learning techniques, particularly Random Forest regression models, to achieve 99.5% prediction accuracy for military expenditure forecasting based on economic indicators. The platform integrates data from …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 · pp. 1–8 Read article
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Dynamic Price Model for E-Commerce
Abstract: Retailers may now respond to fluctuating demand, inventory levels, competitor activities, consumer traits, and market circumstances using dynamic pricing, a data-driven technique that has become more significant in e-commerce. Modern pricing systems are much more complex and responsive than they were in the past due to the fast advancements in artificial intelligence (AI), machine learning (ML), big data analytics, and reinforcement learning. This review critically examines recent developments in dynamic …
Published in E-Commerce for Future & Trends · Vol. 13, Issue 2, 2026 · pp. 45–55 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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Travel-Time Prediction: A Short Survey
Abstract: AbstractTravel-time information could be applied in various fields and its purpose is to improve the reliability and service quality. From the traveler’s point of view, the travel-time information helps to save the time and improve reliability through the selection of travel routes pre-trip and en-route. One way to accomplish this is to provide driver or passenger with current traffic information throughout their trip. In the application of logistics, travel-time information …
Published in Recent Trends in Parallel Computing · Vol. 4, Issue 3, 2017 · pp. 13–19 Read article