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1126 articles for “prediction”
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Radiation-Resilient AI: Next-Generation Robotic Systems with Adaptive Machine Learning for Nuclear Facility Management
Abstract: The increasing complexity of nuclear facility operations, decommissioning activities, and emergency response scenarios necessitate the development of advanced autonomous systems capable of functioning in highly radioactive environments. This paper presents a comprehensive review of radiation-resilient artificial intelligence systems integrated with next-generation robotic platforms, specifically designed for nuclear facility management applications. We examine the convergence of adaptive machine learning algorithms, radiation-hardened hardware architectures, and intelligent robotic systems that can operate autonomously …
Published in Journal of Thermal Engineering and Applications · Vol. 15, Issue 2, 2025 · pp. 12–21 Read article
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The Role of Simulation and Digital Twins in Enhancing Mechanical Production Efficiency: A Systematic Review
Abstract: In the evolving landscape of smart manufacturing, simulation technologies and digital twin (DT) systems have emerged as pivotal tools for enhancing the efficiency, agility, and sustainability of mechanical production processes. This systematic review investigates how the integration of simulations and DTs contributes to performance improvements across various stages of mechanical manufacturing—ranging from design and process optimization to predictive maintenance and real-time monitoring. While simulations provide the ability to model, test, …
Published in Journal of Production Research & Management · Vol. 15, Issue 2, 2025 · pp. 31–36 Read article
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Optimizing Marketing Campaigns Using Random Forest and A/B Testing
Abstract: Marketing initiatives play a vital role in driving business growth by reaching targeted consumer segments through tailored strategies across multiple channels. The success of these initiatives is influenced by various factors, including the type and duration of the campaign, the characteristics of the target audience, the communication channels employed, and the overall efficiency of each strategy. These factors collectively impact key performance metrics such as conversion rates, customer acquisition costs, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 01–09 Read article
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Leveraging Information Technologies (IoT, Sensor Technologies, AI, and Data Analytics) in Healthcare and Agriculture
Abstract: This paper explores the powerful convergence of digital technologies — the Internet of Things (IoT), Sensor Technologies, Artificial Intelligence (AI), and Data Analytics — in transforming healthcare and agriculture. Both sectors face pressing global challenges: rising population demands, environmental stress, disease burdens, unequal access to services, and food insecurity. Conventional systems alone cannot meet future needs. However, technology-driven, real-time data-driven systems offer innovative solutions: from automating diagnostics to forecasting pest …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 3, 2025 · pp. 20–28 Read article
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Data to Diagnosis: A Systematic Review of AI/ML in Healthcare
Abstract: Artificial Intelligence (AI) and Machine Learning (ML) are fast revolutionizing the diagnosis of healthcare by augmenting accuracy, speed, and efficiency. AI/ML technologies facilitate earlier and more accurate disease identification with advanced algorithms for image processing, predictive modelling, and pattern recognition, frequently outperforming conventional diagnostic techniques. This review delves into the key contribution of AI/ML in contemporary healthcare, such as its use in clinical data analysis, imaging reports, and patient histories …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 2, 2025 Read article
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A Decade of Viral Evolution (2015–2025): Emergence, Mutations, and Implications for Global Health
Abstract: Over the past decade (2015-2025), viral evolution has profoundly reshaped the global health landscape, challenging healthcare systems, diagnostic tools, therapeutic strategies, and vaccine efficacy. This review comprehensively analyzes the evolutionary trajectories of major human and zoonotic viruses, with a focus on pandemic-prone, drug-resistant, and emerging pathogens. Viral evolution is driven by diverse molecular mechanisms including high mutation rates, recombination, reassortment, host immune pressure, and antiviral interventions, leading to genetic diversification, …
Published in International Journal of Vaccines · Vol. 2, Issue 2, 2025 · pp. 31–40 Read article
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A Detailed Review on Intelligent and Robust Control Strategies for Autonomous Underwater Vehicles with Emphasis on Navigation, Path Tracking, and Stability Enhancement
Abstract: Autonomous Underwater Vehicles (AUVs) have gained significant attention due to their applications in ocean exploration, underwater surveillance, environmental monitoring, and offshore industries. The control of AUVs presents various challenges due to the highly dynamic and uncertain underwater environment, nonlinear hydrodynamics, and external disturbances. This review paper explores various control strategies employed for AUVs, including classical control methods such as Proportional-Integral-Derivative (PID) controllers, modern techniques like Model Predictive Control (MPC), and …
Published in International Journal of Electronics Automation · Vol. 3, Issue 2, 2025 · pp. 28–52 Read article
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A Study on accelerating threat of Emerging Infectious Diseases (EIDs) and imperative for a proactive, interdisciplinary Global Health Security Framework
Abstract: Emerging Infectious Diseases (EIDs) represent one of the most critical and persistent threats to global health security in the 21st century. Driven primarily by the synergy of unprecedented human encroachment into wild habitats, climate change-induced ecological disruption, accelerated international travel, and antimicrobial resistance, the frequency and severity of zoonotic spillover events are rapidly increasing. Traditional, reactive public health measures—focused on containment after an emergence—have repeatedly proven insufficient, leading to catastrophic …
Published in International Journal of Tropical Medicines · Vol. 3, Issue 1, 2026 · pp. 8–21 Read article
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Machine Learning for Finding Materials for Membranes
Abstract: Traditionally, finding and improving membrane materials has depended on trial-and-error experiments, which can take a long time, cost a lot of money, and only cover a small area. Recent improvements in machine learning (ML) have the potential to change the way membrane materials are designed by making it possible to make predictions about performance, selectivity, and stability based on data. ML algorithms can find hidden links between the structure, composition, …
Published in International Journal of Membranes · Vol. 3, Issue 1, 2026 · pp. 1–7 Read article
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Enhancing Construction Safety Performance Through Artificial Intelligence: A Systematic Review
Abstract: The construction industry is still one of the most dangerous sectors globally because of its dynamic working environment, the employment of heavy machinery, and the complexity of operational processes. Traditional safety management methods are largely dependent on manual monitoring and reactive measures, which are not always effective for accident prevention. In recent years, Artificial Intelligence (AI) has been recognized as a revolutionary technology in construction safety, with capabilities such as …
Published in Journal of Industrial Safety Engineering · Vol. 13, Issue 1, 2026 · pp. 13–30 Read article
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Harnessing Deep Learning to Explore Microbial Community Structure and Carbon Storage Capacity in Mangrove Ecosystems: A Framework for Computationally
Abstract: Mangrove ecosystems represent one of the most efficient natural carbon sinks on Earth, functioning as critical blue carbon habitats that sustain diverse microbial communities responsible for biogeochemical cycling and long-term carbon storage. Despite their global ecological significance, accurately quantifying and predicting carbon sequestration in mangrove systems remains challenging due to the complex interactions between microbial diversity, sediment chemistry, and environmental drivers. This study presents a comprehensive and sustainable artificial intelligence …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
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IoT-Enabled Monitoring of AC Condensate Water for Quality Assessment and Early Detection of HVAC System Health
Abstract: The shortage of water and expensive reactive maintenance of HVAC are major problems in the modern building management. The paper introduces an Internet of Things (IoT)-enabled air conditioning (AC) condensate to water resource (predictive maintenance) and sustainable water reuse. The nature of our approach defines the quality of the condensate water at the baseline and indicates that it contains low levels of total dissolved solids (TDS) and has almost neutral …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 1, 2026 · pp. 25–35 Read article
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Design and Validation of an Artificial Intelligence-Driven Digital Twin for Real-Time Monitoring and Control in Polymer Composite Manufacturing
Abstract: Polymer Matrix Composites (PMCs) have become indispensable in high-performance sectors such as aerospace and automotive engineering, offering exceptional strength-to-weight ratios that outperform traditional metals in many demanding applications. However, the reliability of manufacturing PMCs via Vacuum-Assisted Resin Transfer Molding (VARTM) is frequently undermined by stochastic process variabilities. Unpredictable fluctuations in thermal history, preform permeability, resin rheology, and ambient conditions often lead to some defects; namely voids, dry spots, and incomplete …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 224–233 Read article
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The Influence of Data Analytics on Sports Performance
Abstract: Data analytics has drastically changed how we evaluate, improve, and maintain athletic performance. Coaches used to use subjective observations as well as only limited numbers of statistics to consider player performance; however, tracking technology is now advancing at a fast pace. There are now very large amounts of real-time data available on athletes in regards to speed, movement patterns, fatigue, efficiency, etc. This enables all teams to more accurately make …
Published in Recent Trends in Sports · Vol. 3, Issue 1, 2026 · pp. 15–21 Read article
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Explainable Machine Learning Integrated with Polymer-Based Diagnostic Technologies for Liver Health Classification
Abstract: Early and reliable assessment of liver health is essential for timely treatment, yet most machine-learning approaches face limitations such as class imbalance and low clinical interpretability. This study proposes a polymer-integrated, explainable machine-learning framework that combines SMOTE-based data balancing, Logistic Regression, and XAI techniques (SHAP and LIME) for transparent liver-health classification. In addition to ML modelling, the study emphasizes the emerging role of polymer-based biosensors, microfluidic polymer chips, polymer nanomaterials, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 631–643 Read article
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Advancements and Challenges in Automated Guided Vehicles for Smart Industrial Automation
Abstract: Automated Guided Vehicles (AGVs) are increasingly central to modern industrial automation, enhancing operational efficiency in manufacturing, warehousing, and logistics. Traditionally reliant on fixed paths using magnetic tapes or wired tracks, AGVs were limited in flexibility. However, recent technological advances have enabled the development of autonomous AGVs equipped with sensor fusion, LiDAR, computer vision, and artificial intelligence (AI). These features support real-time obstacle detection, dynamic path planning, and robust performance in …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 1–5 Read article
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Integrated Frameworks for Artifical Intelligence in Radioactive Waste Characterization and Nuclear Lifecycle Safety
Abstract: The management and characterization of radioactive waste represent a pivotal challenge for the global energy sector, requiring the convergence of advanced physics, material science, and computational intelligence. As the nuclear industry undergoes a paradigm shift toward decommissioning legacy facilities and establishing deep geological repositories, the limitations of traditional, manually-intensive waste management processes have become increasingly apparent. Rigid separation from the biosphere is required for radioactive waste, which is defined by …
Published in Journal of Nuclear Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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Develop the Design of Sustainable Polymer Materials: Applying Reinforcement Learning, IoT-Enabled Monitoring, and Data-Driven Manufacturing Approaches
Abstract: Sustainable polymer materials development is a must due to resource constraints, environmental concerns, and the demand for designed materials with high performance. When it comes to material optimization, energy utilization, process unpredictability, and lifecycle sustainability, traditional polymer production methods have their challenges. Reinforcement Learning (RL), Internet of Things (IoT) monitoring, and data-driven production are utilized in the design and manufacturing of sustainable polymer materials. It is recommended to use Internet …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Valeton Phytoconstituents from Curcuma Phaeocaulis as Prion Protein Mutant V210I Inhibitors: A Computational Docking and Virtual Screening Study
Abstract: Objective: Creutzfeldt-Jakob disease (CJD), a neurological disorder that is sporadic, fatal, communicable, and worsens rapidly, is caused by abnormal folding of prion proteins. Identifying and assessing the potential of phytocompounds from the Curcuma phaeocaulis Valeton plant as a new therapeutic candidate aimed at the treatment of CJD is the objective of this research article. Methods: In this experiment, we assessed outcomes following an in-silico assessment to design a new oral …
Published in International Journal of Biochemistry and Biomolecule Research · Vol. 1, Issue 2, 2023 · pp. 1–16 Read article
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A Machine Learning Based Artificial Intelligence Model for Detecting Heart Illness
Abstract: This study centers around the improvement of an artificial intelligence- and computerized reasoning-based heart sickness determination framework. We exhibit how AI can help with foreseeing whether an individual will get cardiovascular infection. In this review, a Python-based application for medical care research is created since it is more reliable and helps track and lay out many kinds of well-being observing applications. We show information handling, which incorporates working with all …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 50–58 Read article