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704 articles for “Predictive Modelling”
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RFID-Enabled Smart Shelves and Cart System
Abstract: With the fast-paced development of Radio Frequency Identification (RFID) technology, the retail sector is seeing a revolutionary change to improve stock management, cut operational costs, and improve consumer satisfaction. The comparative advantages of RFID-smart shelves and carts over conventional stock management practices, such as barcode scanning and manual stock management, are investigated in this work. Compared to the other methods, in terms of accuracy, efficiency, cost-effectiveness, and scalability, RFID smart …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 2, 2025 · pp. 31–37 Read article
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Drug Screening Using Stem Cell Technology
Abstract: Stem cell technology in drug screening has transformed the research and development sector of pharmaceuticals. Although stem cells imitate their human counterparts in terms of both safety and potential, it is a new paradigm for mimicking diseases of humans and scale measuring for toxicity. These tissues will, therefore, be more predictive of what will happen in humans during clinical situations, compared to conventional cell lines or animal models, since they …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 3, 2025 · pp. 42–51 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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Demand Forecasting for Perishable Food Commodities Using Data Analytics
Abstract: This paper introduces a comprehensive study aimed at enhancing the forecasting of perishable food item demand. Focusing on solving the critical issue of waste management within the supply chain of food products, the research undertakes a comparative analysis of various machine learning models. The development of an optimized model that is capable of accurately forecasting the demand for perishable food items is the focus of this research. The research includes …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 11, Issue 3, 2024 · pp. 27–37 Read article
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The Integration of AI Technologies in Automating Cyber Defense Mechanisms for Cloud Services
Abstract: The swift growth of cloud computing has transformed how organizations handle and store data, providing greater scalability and adaptability. However, the transition to cloud-based environments has heightened the complexity of cybersecurity challenges, especially in detecting and responding to security incidents. Conventional methods of incident response, which heavily depend on manual efforts, are no longer adequate to address the rapidly evolving and complex nature of modern cyber threats. This study explores …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 1–14 Read article
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Diabetes Prediction Using ML Techniques
Abstract: Diabetes mellitus, commonly referred to as diabetes, denotes a cluster of prevalent endocrine disorders characterized by persistent elevated levels of blood sugar. Diabetes is classified into two main types: type 1 and type 2. Type 1 diabetes arises when the body is unable to produce insulin, while type 2 diabetes involves either insulin resistance or insufficient insulin production. Early detection and intervention are essential to reduce its harmful impacts. The …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
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E-Commerce Study Using AR/VR and Ethical Convergence of Commerce
Abstract: The landscape of E-commerce is undergoing a fundamental transformation, shifting from a platform-centric model of transactional exchange to an immersive, ecosystem-driven experience. This analysis examines the critical trends and disruptive forces that define the immediate and long-term trajectory of digital commerce. The study identifies three foundational pillars driving future growth: Hyper-Personalization via Generative AI, Spatial Commerce (AR/VR Integration), and Sustainable Supply Chain Resilience. Future E-commerce will be characterized by the …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 3, 2025 · pp. 20–26 Read article
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Advancements in Agricultural Forecasting: A Review of Machine Learning Based Crop Yield Prediction
Abstract: Agricultural productivity plays a critical role in global food security, and accurate crop yield prediction is essential for optimizing resource allocation and decision-making in farming. The rapid advancements in Machine Learning (ML) and Deep Learning(DL)have transformed agricultural forecasting, enabling data-driven approaches for crop prediction. This review paper provides a comprehensive analysis of various ML and DL techniques applied in crop yield forecast, highlighting the ineffectiveness, challenges, and future directions. The …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 32–38 Read article
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Smart Water Harvester
Abstract: Smart water harvester is a wiser use of Data Science in the optimization of rainwater harvesting, taking into account the forecast of precipitation and ideal catchment areas, and basically image processing using machine learning. In that respect, the system, via predictive algorithms like Random Forests, predicts the amount of rainfall by taking into consideration historical and real-time data, while Digital Elevation Models (DEM) and visualization methodologies of images make geographical …
Published in Journal of Water Resource Engineering and Management · Vol. 11, Issue 3, 2024 · pp. 1–7 Read article
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AI For Climate Vulnerability Assessment
Abstract: Climate change is one of the biggest problems we face every day. The main problems are high temperatures, rising sea levels, and changes in weather, which will be worse in the upcoming years. To predict and adapt to these impacts, we need to create data-driven solutions. The main tool for predicting climate change was artificial intelligence, which can also be utilised to predict the weather and alert people of impending …
Published in International Journal of Radio Frequency Innovations · Vol. 3, Issue 1, 2025 · pp. 18–33 Read article
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Smart Polymer Composites with Multifunctional Capabilities Integrating Electroactive Polymers Conductive Nanofillers and Flexible Electronics for Advanced Sensing and Actuation Systems
Abstract: Smart polymer composites have gained significant attention to their ability to integrate polymer matrices with conductive nanofillers, offering tunable electrical, mechanical, and electroactive properties. These composites are highly responsive to external stimuli such as electrical fields, mechanical stress, and temperature variations, making them ideal for applications in flexible electronics, soft robotics, and adaptive sensing systems. This research investigates the effect of nanofiller dispersion on the performance of polymer composites, optimizing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 946–965 Read article
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The Early Brain Hemorrhage Prediction System Using Machine Learning
Abstract: Brain hemorrhage is a critical medical emergency that requires immediate attention, as delays in diagnosis can result in severe neurological damage or death. The condition involves bleeding within or around brain tissues, leading to increased intracranial pressure and disruption of normal brain function. Although imaging techniques such as CT scans and MRI provide accurate diagnosis, their availability is limited in emergency and rural settings. In recent years, machine learning has …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 Read article
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Comparative Analysis of Polymer-Enhanced and Conventional Magnetorheological Fluids in E-Bicycle Semi-Active Suspension
Abstract: In light of the increased use of electric bicycles as a sustainable transport means, various mechanical challenges emerge which were absent in traditional bicycles, primarily concerning vibration isolation and riding comfort. Indeed, hub motors, batteries and the entire drivetrain system produce dynamic excitations which passive suspension cannot handle effectively. This paper presents a comparison of conventional magnetorheological (MR) fluid and the polymer-based MR nanocomposite fluid within the context of semi-active …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Static Structural Analysis and Bridge Modeling Using ANSYS
Abstract: Structural analysis is a crucial discipline within civil engineering that ensures built structures are safe, durable, and capable of performing the functions for which they are intended. This scientific approach is essential for confirming that all safety requirements are met, thereby allowing structures to fulfill their purpose efficiently and economically over their design lifespan. The principles of structural analysis originate from the collaborative efforts of engineers across various domains, all …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 27–32 Read article
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A Study and Prediction of Psychological Disorders Through Machine Learning
Abstract: Physical illness is very much visible but not psychological illness therefore, it requires more attention and care. Psychological disorders also known as psychiatric disorders refer to a wide range of conditions affecting a person’s thought process, leading to significant changes in the behavior of an individual. The most prevalent psychological disorders include depression, anxiety disorders, and post-traumatic stress disorder (PTSD). Symptoms of psychological disorders vary greatly but include common symptoms …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 2, 2024 · pp. 32–38 Read article
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AI Powered Fault Detection in DC Motor using STM32
Abstract: This work presents the design and implementation of an embedded artificial intelligence system for real-time fault detection in a direct current (DC) motor using the STM32 Nucleo- F411RE microcontroller. The objective of the study is to develop a low-cost and efficient predictive maintenance solution capable of identifying abnormal motor behavior at an early stage. Vibration and temperature signals are acquired using an MPU6050 sensor and processed directly on the microcontroller …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 39–49 Read article
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Cybersecurity of AI and IoT Integrated for Mechanical Industries
Abstract: By facilitating the concept of Industry 4.0, the intersection of artificial intelligence (AI) and the Internet of Things (IoT) has changed the mechanical industries. When combined, these technologies are advancing process optimization, predictive maintenance, real-time condition monitoring, and smarter automation. In order to give proactive system control and intelligent decision-making, AI algorithms mine large datasets generated via IoT devices for relevant patterns. In the meanwhile, IoT guarantees smooth communication between …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 27–33 Read article
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Intelligent Aquaculture System for Fish Disease Detection Using Machine Learning
Abstract: Aquaculture is one of the key factors for global food security, but fish diseases bring about heavy economic losses and jeopardize sustainability. One of the most important aspects of global food security is aquaculture, but fish infections endanger sustainability and cause significant financial losses. Early diagnosis is not possible since traditional disease detection techniques are laborious and necessitate expert intervention. To effectively detect fish infections, this study suggests an Intelligent …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 2, 2025 · pp. 30–37 Read article
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Intelligent Optimization of Drilling Parameters in Polymer Composites using Machine Learning and Metaheuristic Techniques
Abstract: The study tests different ways to use ML and metaheuristic algorithms to determine the best drilling parameters for polymer matrix composites. The research uses a composite matrix made from 55.25% vinyl ester, 44.0% Nickel–Phosphorous coated glass fiber and 0.75% Al₂O₃ nanowires which are tested for tensile strength (64.57 MPa), flexural strength (85.86 MPa) and impact strength (71.79 kJ/m²). By applying a Taguchi orthogonal array, it is observed that a slower …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1795–1810 Read article
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Pneumonia Identification Using Explainable Artificial Intelligence
Abstract: Pneumonia, including tuberculosis (TB), remains one of the leading causes of death worldwide, especially in regions where access to healthcare is limited. Early and accurate diagnosis is critical for effective treatment and better patient outcomes, but traditional methods are time-consuming and require specialized expertise. This study explores the use of advanced deep learning models VGG16, VGG19, and ResNet50 to detect pneumonia and TB from chest X-ray images. By leveraging transfer …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 01–11 Read article