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543 articles for “predictive algorithm”
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FoodieHUB: Food Recipe Suggestion Using AI-ML On Web
Abstract: Finding a delicious recipe to cook with limited ingredients at home can be a challenging task. Many individuals struggle to prepare meals using only the ingredients they have on hand, creating uncertainty and limiting options. This project aims to develop a recipe recommendation system that utilizes machine learning algorithms to suggest recipes based on available ingredients, dietary preferences, cuisine types, cooking time, and user ratings. The project utilizes a Gradient …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 01–07 Read article
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Investigation of Mechanical Properties of Banana, Linen and Their Hybrid Reinforced Composite Laminates in Adverse Condition and Analyze Using ML
Abstract: This research investigates the mechanical performance of composite laminates reinforced with banana and linen fibers, focusing on both individual and hybrid fiber combinations. The primary objective is to assess how these natural fiber composites behave under extreme environmental conditions, particularly high humidity and fluctuating temperatures, which are common in aerospace and automotive applications.Key mechanical properties—tensile strength, flexural strength, and impact resistance—are experimentally evaluated to assess the performance and long-term reliability …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 25–31 Read article
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AI-Accelerated Development of Gradient Polymer Nanocomposite Thin Films
Abstract: Gradient polymer nanocomposite thin films are an active field of materials research due to the fact that it enables scientists to de-facto regulate the optical, electrical, and mechanical properties of a film by merely altering its composition on a layer-by-layer basis. This type of control opens the gate to the improved flexible electronics, long lasting protective coats, and the new smart gadgets. The problem is, though, that it is a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 456–469 Read article
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Sensors-Based Electric Machine Design for Industry
Abstract: The integration of advanced sensors is fundamentally changing the economics and reliability of electric machines. It moves design focus from minimizing material cost and adhering to conservative standards toward maximizing operational availability and energy efficiency. In the industry of tomorrow, the electric motor will not be a passive collection of coils and steel, but a self-diagnosing, self-optimizing, and perhaps even self-healing asset—a sentient motor—driven by its highly refined sixth sense, …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 1–10 Read article
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The Impact of AI-Driven Decision-Making on Consumer Behavior and Sustainable Consumption Patterns in Modern Management
Abstract: The accelerating integration of Artificial Intelligence (AI) into business management systems has fundamentally transformed the dynamics of consumer decision-making and organizational marketing strategies. This paper investigates the multidimensional impact of AI-driven technologies, including predictive analytics, recommendation engines, chatbots, natural language processing, and machine learning algorithms, on consumer behavior and sustainable consumption patterns within contemporary management frameworks. Drawing upon a comprehensive synthesis of empirical studies, theoretical literature, and bibliometric analyses, the …
Published in Journal of Production Research & Management · Vol. 16, Issue 2, 2026 · pp. 12–19 Read article
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Artificial Intelligence -Driven in Clinical Pharmacy Practice: Transforming Medication Management and Patient-Centred Care
Abstract: Artificial intelligence (AI) is transforming clinical pharmacy practice by enhancing the safety, accuracy, and efficiency of medication management while supporting evidence-based clinical decision-making. Recent advances in machine learning, deep learning, natural language processing, and predictive analytics have enabled the integration of AI into various aspects of pharmacy practice, including drug discovery, pharmacovigilance, clinical decision support, personalized medicine, medication adherence, and patient counselling. The objective of this review is to provide …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 3, 2026 Read article
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Machine Learning Assisted Timing Violation Prediction in Sub-7nm VLSI Physical Design
Abstract: The continuous scaling of semiconductor technology into the sub-7nm regime has introduced significant challenges in timing closure due to process variability, interconnect delay, power density, and manufacturing uncertainties. Conventional static timing analysis techniques often require extensive computational resources and iterative optimization cycles, resulting in increased design complexity and longer turnaround time. This research proposes a Machine Learning Assisted Timing Violation Prediction framework for sub-7nm VLSI physical design to improve early-stage …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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A Study on AI-Enhanced Environmental Toxicology: Sensor-Driven Predictive Framework
Abstract: Traditional environmental toxicology relies heavily on labor-intensive, often retrospective, sampling and analysis, limiting our understanding of dynamic pollutant behaviors and their real-time impact on ecosystems and human health. This study presents a novel, integrated framework leveraging advanced sensor networks and artificial intelligence (AI) to revolutionize the monitoring, assessment, and predictive modeling of environmental contaminants. We deployed a sophisticated array of multi-parameter sensors (e.g., electrochemical, optical, biosensors for heavy metals, organic …
Published in Research and Reviews: A Journal of Toxicology · Vol. 15, Issue 3, 2025 Read article
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The Scientific Foundations of Programming Languages: Bridging Theory and Practical Application
Abstract: The study of programming languages within computer science is fundamental to the development of efficient, reliable, and scalable software systems. However, the degree to which these languages adhere to scientific principles remains a topic of debate. This paper explores the scientific nature of computer science languages by examining their theoretical foundations, design principles, and practical applications. It evaluates how programming languages are grounded in mathematical logic, formal semantics, and computational …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 1, 2025 · pp. 32–41 Read article
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AI-Driven Pharmacogenomics and Precision Medicine: Future of Personalized Therapy
Abstract: Pharmacogenomics and artificial intelligence (AI) are emerging as important drivers of precision medicine, enabling healthcare systems to adopt individualized therapeutic approaches. Pharmacogenomics examines how genetic variations influence drug response, efficacy, metabolism, and toxicity, while AI provides advanced computational tools for analyzing complex genomic and clinical data. This review highlights the integration of AI-driven pharmacogenomics in personalized therapy and its potential to improve treatment outcomes. Machine learning, deep learning, natural language …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 1–12 Read article
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Comparative Analysis of Neural Network and Linear Regression Applied to Black Friday Data
Abstract: AbstractIn this study, it compares two different types of neural networks. First is a single layer neural network and other is multiple hidden layer neural network. For just comparisons it is ensured that both uses the same activation and output functions and have the same number of nodes and parameters. The networks are trained by the gradient descent algorithm to approximate linear and quadratic functions and examine their convergence properties. …
Published in Current Trends in Signal Processing · Vol. 9, Issue 3, 2019 · pp. 1–4 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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Photosynthetic Living Plant–Integrated Cybernetic Sensors for Autonomous Environmental Intelligence
Abstract: The increasing demand for sustainable and autonomous environmental monitoring systems has motivated the development of biologically integrated sensing technologies that combine living organisms with advanced cybernetic intelligence. This study proposes a novel framework of Photosynthetic Living Plant–Integrated Cybernetic Sensors for Autonomous Environmental Intelligence, where living plants act as self-sustaining sensing platforms capable of continuously monitoring environmental conditions without external energy sources. By integrating bioelectrical signal acquisition modules, flexible nanomaterial electrodes, …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 2, 2026 Read article
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Sustainable Biomedical Polymer Composites Designed through Artificial Intelligence Approaches
Abstract: The development of sustainable biomedical polymer composites has become one solution that can be used to combat increasing environmental issues that have been presented by traditional medical materials without compromising functional performance. Implementation of the artificial intelligence (AI) in material design presents a paradigm shift of data-driven development, which improves the efficiency, accuracy, and scalability of composite development. The given work can serve as a universal guideline in developing biodegradable …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Breast Cancer Diagnosis Using Data Mining Classification Techniques Using Weka
Abstract: Breast cancer is currently posing a serious threat and is the second leading cause of death in women. A good and accurate diagnosis is important in order to control the very high recurrence rate of breast cancer. In this work, we explore the applicability of various data mining classifier to predict the presence of breast cancer. The performance of conventional supervised learning algorithms such as NaïveBayes, J4.8, SMO, IBk and …
Published in Recent Trends in Programming languages · Vol. 4, Issue 3, 2017 · pp. 7–15 Read article
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Statistical Models for Predicting Genetic Variability and Disease Susceptibility
Abstract: Differences in genetics are key to understanding why some individuals are more prone to certain diseases than others. Recent advancements in genomic research, combined with statistical modeling techniques, have made significant strides in predicting disease risk based on genetic factors. This review explores the application of statistical models for predicting genetic variability and their role in disease susceptibility. We discuss traditional methods like linear regression and genome-wide association studies (GWAS), …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 30–34 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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Using Machine Learning to Guess Photochemical Reaction Pathways
Abstract: Photochemical reactions are crucial to many activities in the fields of energy conversion, environmental cleanup, and synthetic chemistry. However, predicting their causes and results effectively is still very hard since they entail excited electronic states, nonadiabatic transitions, and complicated potential energy surfaces. Machine learning (ML) has been a powerful technique to go along with classic quantum chemistry methods in the last few years. It offers better prediction capability and lower …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 3, Issue 2, 2025 · pp. 01–12 Read article
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Comparison of Tuning Methods of PID Controllers of Two Conical Tank System of Interacting Type
Abstract: The rapid increasing complexity of modern control systems has accentuated the idea of applying new modern approaches in order to solve design problems for various control engineering applications. This paper deals with the tuning of PID controllers for complex nonlinear process of two interacting Conical Tank Systems. Conical tanks play vital role in leaching extractions in pharmaceutical and chemical industries, as well as in food processing industry. It is a …
Published in Journal of Control & Instrumentation · Vol. 5, Issue 3, 2014 · pp. 8–14 Read article
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Supply Chain Optimization Using Big Data
Abstract: In the references to add productivity and short the appendences, and increase customer value, supply chain optimization is a very crucial part of contemporary business operations. Supply chain management has been transformed by the emergence of big data, which can provide analysis and insight from many different sources of information. This content explores the importance of using big data analytics to improve the delivery process. Thanks to the evolution of …
Published in Journal of Production Research & Management · Vol. 14, Issue 2, 2024 · pp. 19–25 Read article