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1074 articles for “prediction system”
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A Survey of Role-Based Access Control Implementation in HMI Systems for Industrial Automation
Abstract: The convergence of Role-Based Access Control (RBAC) and Human-Machine Interface (HMI) systems presents a transformative approach to secure and efficient industrial automation in Industry 4.0. By integrating RBAC with Multi-Factor Authentication (MFA), this framework enhances cybersecurity while maintaining operational flexibility, mitigating both external threats and internal vulnerabilities. Modern adaptive HMIs further optimize user experience through personalized and intuitive interfaces, though challenges remain in balancing functionality with simplicity in complex industrial …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 2, 2025 · pp. 10–19 Read article
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Mental Health and Artificial Intelligence (AI): Marching towards Future
Abstract: One of the most crucial but frequently disregarded facets of our wellbeing is our mental health. In the medical domains of dermatology, radiology, and oncology, artificial intelligence (AI) is being used more and more. AI hasn't been heavily utilised in mental healthcare, though. The need for AI to help identify high-risk individuals and give interventions to prevent and treat mental illnesses is essential due to the high morbidity and mortality …
Published in Research and Reviews: A Journal of Health Professions · Vol. 13, Issue 3, 2023 · pp. 91–95 Read article
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MedVerse AI: An Intelligent Digital Health Platform for Patient-Centric Healthcare and Proactive Disease Prediction
Abstract: The rapid digitization of healthcare has led to an unprecedented growth in medical data, ranging from diagnostic images and laboratory reports to electronic health records and clinical notes. Despite this abundance, patients and healthcare providers often struggle to extract meaningful insights due to data complexity and fragmentation. MedVerse AI proposes an intelligent digital health platform that unifies medical image analysis, clinical report interpretation, real-time interaction, and predictive disease analytics into …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 2, 2026 · pp. 1–7 Read article
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Enhancing Explainability in Machine Learning Based Spam Email Detection Using LIME and SHAP
Abstract: Spam emails represent a continual and irritating cybersecurity issue due to the fast expansion of cyberspace communication. These messages are unwanted and, in some cases, dangerous, such as phishing schemes, identity theft, and the propagation of malware. They cause severe financial and data security threats to individuals and organizations. Conventional spam detection techniques, such as rule-based spamming, blacklisting, and keyword classification, are techniques that find it difficult to match adaptive …
Published in Journal Of Network security · Vol. 14, Issue 2, 2026 · pp. 35–48 Read article
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Perforated Forced Convection Peculiarities and Implications
Abstract: Transfer of heat through perforated forced convection within a confined passage on a flat plate is investigated for varying flow speeds. Experimentation relates to the need of comprehensive understanding of complicated heat transference requirement particularly in space propulsion domain. The optimal utilization of perforated enclosures with distinct shapes and sizes is predicted for wide-ranging applications. Systematic experimentation is carried out and effect of controlling parameters is explored. Results indicate that …
Published in Journal of Aerospace Engineering & Technology · Vol. 10, Issue 1, 2020 · pp. 27–46 Read article
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Machine Learning-Based Quantification of Polymer Structure Property Relationships for Predictive Material Design
Abstract: Polymer structures exhibit complex, hierarchical arrangements that strongly influence macroscopic properties, yet consistent quantification remains challenging due to nonlinear interactions and limited unified modeling strategies. Existing approaches inadequately capture generalized structure–property mappings across diverse polymer systems. This research aims to establish a machine learning-based quantification model for polymer structure–property relationships to support predictive material design. A Polymer Structure Property Dataset of 5,000 polymer samples includes structural descriptors and experimentally measured …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 737–754 Read article
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AI-Powered Solutions for Sustainable Waste Management in Construction Projects
Abstract: The construction industry is a significant contributor to global waste, posing challenges to sustainability and environmental health. This research explores AI-powered solutions for sustainable waste management in construction projects, focusing on optimizing waste reduction, recycling, and resource efficiency. By integrating machine learning algorithms and IoT-enabled sensors, real-time monitoring of waste generation and segregation can be achieved. Predictive analytics and AI-driven decision-making tools are employed to enhance material reuse and minimize …
Published in Recent Trends in Civil Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 1–5 Read article
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Short-Term Load Demand Forecasting using Chaos Theory and ANFIS
Abstract: In the electrical power sector, forecasting of load demand is an important process for effective planning of future expansion and periodical operations including unit commitments, fuel scheduling, short-term maintenance, security assessments, reducing spinning reserve, reliability analysis etc. Accurate load predictions are also necessary to utilize the electrical energy efficiently and to minimize the conflicts between the demand and supply of electricity. As electric load pattern of a region is very …
Published in Trends in Electrical Engineering · Vol. 6, Issue 2, 2016 · pp. 50–57 Read article
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Robotics and Automation in Mechanical Engineering: Transforming Modern Manufacturing Systems
Abstract: Robotics and automation have significantly transformed mechanical engineering, particularly in manufacturing, precision assembly, and intelligent systems integration. With the advancement of sensors, control systems, artificial intelligence, and mechatronics, robotic systems are now capable of performing complex tasks with high accuracy, repeatability, and efficiency. This article explores the role of robotics in modern mechanical applications, including industrial automation, collaborative robots, predictive maintenance, and smart manufacturing. It also discusses design considerations, challenges, …
Published in International Journal of Manufacturing and Production Engineering · Vol. 4, Issue 1, 2026 · pp. 27–33 Read article
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The Role of Mathematical Reasoning in Legal Analysis: Bridging Two Disciplines
Abstract: This research paper explores the integration of mathematical reasoning into legal analysis, emphasizing the inherent similarities between the two disciplines. Both fields rely on logical structures, such as deductive reasoning, inductive reasoning, and other formal methods of thought. By examining these parallels, the paper reveals the nascent but growing interaction between mathematics and law, uncovering how the organizational schemes that underpin mathematical principles can enhance legal argumentation, decision-making, and analysis. …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 3, 2024 · pp. 1–5 Read article
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Explainable Artificial Intelligence in Personalized Medicine: Emerging Clinical Perspectives
Abstract: The convergence of artificial intelligence (AI) and precision medicine has transformed contemporary healthcare by enabling data-driven clinical decision-making, individualized therapeutic interventions, and predictive diagnostics. However, despite remarkable advances in machine learning (ML) and deep learning (DL), the widespread adoption of AI in healthcare remains constrained by the “black-box” nature of many computational systems. Clinicians, regulatory agencies, and patients increasingly demand transparency, interpretability, and trustworthiness in AI-guided medical recommendations. Explainable Artificial …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 13–29 Read article
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Need for Documentation of Traditional Knowledge (TK) of Rainfall Forecasting in Murshidabad District of West Bengal: A Survey in the Light of the Attitudes of the Young Generation towards TK and the Need for Documentation of TK
Abstract: This study documents the traditional knowledge of rainfall forecasting in Murshidabad district of West Bengal. It explores the attitudes of the farmers, especially young generation of farmers equipped with modern and formal education, towards the Traditional Knowledge. Altogether, sixteen 16 different TKs relating to rainfall prediction have been found. The farmers in the study area predict rainfall through their observation, experiences and understanding of nature. Traditionally they use indicators like …
Published in Journal of Advancements in Library Sciences · Vol. 6, Issue 2, 2019 · pp. 88–95 Read article
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Artificial Intelligence for Real-time Water Management
Abstract: Effective water management is vital for sustainable development, requiring the strategic allocation and utilization of water resources to satisfy the diverse demands of agriculture, industry, and households. Traditional methods are increasingly inadequate due to escalating challenges from climate change and population growth, which amplify water scarcity and distribution issues. To overcome these challenges, we need innovative solutions. Artificial intelligence offers significant potential in revolutionizing realtime water management through advanced techniques …
Published in Journal of Water Resource Engineering and Management · Vol. 11, Issue 2, 2024 · pp. 13–20 Read article
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An Innovational Approach for Estimation of Reliability Indices Accounting Repair Time of Hose Reel System-Safety Empirical Outlook
Abstract: Numerous reliability indices estimation of a system or component or element is very important in order to predict its availability and unavailability. Reliability is the specification which tells about the availability of the system under proper working conditions for a given period of time. Reliability of numerous complex engineering systems has been estimated in literature. In view of above, in this paper an innovational approach for estimation of various reliability …
Published in Journal of Control & Instrumentation · Vol. 12, Issue 3, 2021 · pp. 12–18 Read article
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A Transaction Pattern Generation Tool (TPGT) for Prediction of Online Financial Transactions
Abstract: ABSTRACTThe Internet all over the world is growing rapidly. It has given rise to new opportunities in every field we can think of – be it entertainment, business, sports or education. There are two sides to a coin. Internet also has its own disadvantages. One of the major disadvantages is cyber crime – illegal activity committed on the Internet. The Internet, along with its disadvantages, has also exposed us to …
Published in Journal of Computer Technology & Applications · Vol. 3, Issue 3, 2012 · pp. 1–12 Read article
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Classification Of Music Genre Using Machine Learning
Abstract: Machine Learning is a way that helps the systems to automatically learn from experience and improve the performance and predict the outcome more accurately without any requirement of being explicitly programmed. Music is one of the most significant and influential part of people’s life. Also, music is known as a universal language as it has the power to unite people from different places and cultures. This helps in the recognition …
Published in Journal of Instrumentation Technology & Innovations · Vol. 12, Issue 1, 2022 · pp. 11–16 Read article
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A Smart Framework that Combines Data Mining and Optimization for Different Applications
Abstract: Blending predictive data mining with metaheuristic optimization has become essential for tackling tough, real-world problems across all kinds of fields. Most existing methods stick to fixed algorithms, each focused on a tiny slice of the puzzle, barely budging when new variables or unpredictability show up—especially with messy, human-generated data. So, here’s the idea: a Unified Metaheuristic and Predictive Data Mining (UMPDM) framework that finally connects adaptive search methods with powerful …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 · pp. 10–14 Read article
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Performance Evaluation of Solar Refrigeration System Using the Numerical Methods
Abstract: Abstract Nonconventional sources of energy are main alternate resources which can provide a solution for the faster rate of depletion of fossil fuels. All renewable energy comes ultimately from the sun. We can use the sun directly (as in solar heating systems) or indirectly (as in hydroelectric power, wind power, and power from biomass fuelsetc.).Directly, the solar energy can be used to the maximum extent in ice making industries, air-conditionings, …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 4, Issue 1, 2017 · pp. 1–12 Read article
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Survey on Progress in Agricultural Yield Prediction-from Machine Learning to Deep Learning
Abstract: Machine learning has offered new prospects for data-intensive study in the multidisciplinary field of Agri-technology, especially with the rise of big data systems and advanced computers. Machine learning is a powerful decision-making tool for predicting crop yields, as well as determining which crops to plant and what activities to engage in during the crop's growing season. To facilitate the study of the prediction of the agricultural yield many techniques of …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 12, Issue 1, 2022 · pp. 6–16 Read article
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Predicting Employees Performance using Data Mining Techniques
Abstract: Human resources management (HRM) has become one of the essential interests of managers and 4decision-makers in almost all types of businesses to adopt plans for correctly discovering highly qualified employees. In this research, data mining techniques were utilized to build a classification model for predicting the performance of employees using a real dataset. For this, we are using different methods such as support vector machine, Logistic Regression and Neural Network. …
Published in Recent Trends in Parallel Computing · Vol. 8, Issue 1, 2021 · pp. 4–13 Read article