Search
543 articles for “predictive algorithm”
-
Fuzzy Mathematics in Decision-Making: A Quantitative Perspective
Abstract: Fuzzy mathematics plays an increasingly generalized role in decision-making, and thus, this paper details different types of fuzzy mathematics and highlights other possible alternatives alongside fuzzy methodologies. Fuzzy models offer a versatile and precise approach to assessing complex and uncertain situations using fuzzy sets, membership functions, linguistic variables, and aggregation methods. Through the lenses of time, cost, and quality, the project management case study illustrates how fuzzy logic effectively evaluates …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 6–12 Read article
-
Analysis of Various Tools of Natural Language Processing Based on Developers Perspective
Abstract: The subject of natural language method has visible mind-blowing development in current years, with neural network community substitution numerous of the traditional structures. A subset of artificial intelligence known as “natural language processing”, or NLP, analyses, comprehends, and generates natural human languages so that computers can reuse written and spoken human language without resorting to computer-generated language. Semantics and syntax are used in natural language processing, which is sometimes referred …
Published in Journal of Communication Engineering & Systems · Vol. 12, Issue 2, 2022 · pp. 1–5 Read article
-
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
-
Various Routing Algorithms in Wireless Sensor Networks for Energy Minimization
Abstract: The past few years have witnessed increased interest in the potential use of wireless sensornetworks (WSNs) in a wide range of applications and it has become a hot research area. Lot ofresearchers are showing interest in WSN for disaster management where prediction ofupcoming disaster is required well in advance before it happens and in critical areas wherehuman presence is not possible directly; wired communication dose not suit well for suchapplications. …
Published in Recent Trends in Sensor Research & Technology · Vol. 7, Issue 3, 2020 · pp. 26–37 Read article
-
Versatile CNC Machine for Tabletop Use Enhanced with Machine Learning Integration
Abstract: In the realm of tabletop multipurpose CNC machines, the integration of machine learning represents a groundbreaking advancement potentially revolutionary in the field of desktop manufacturing. This research explores the seamless incorporation of machine learning algorithms into tabletop CNC machines to enhance their capabilities, performance, and user experience. Through case studies and examples, we demonstrate the profound impact of machine learning integration in key areas of CNC machining, such as accurate …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 · pp. 353–361 Read article
-
Enzyme Stability Prediction using BERT and CNN-A Deep Learning Approach for Enhanced Biocatalysis
Abstract: An important factor in determining the efficacy of industrial enzymes used in various biotechnological applications is their stability. The goal of this study is to develop a predictive model for industrial enzyme stability, which is essential to the efficiency of these enzymes in biotechnological applications. The research takes a comprehensive strategy to comprehend the parameters affecting enzyme stability by combining statistical analysis, deep learning algorithms (BERT and CNN), and molecular …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 2, 2024 · pp. 19–35 Read article
-
Predicting the Physical Property of Asphaltene Molecule using Fuzzy System
Abstract: Asphaltenes — the heaviest and most aromatic compounds of crude oil— have a strong tendency to aggregate in solution to form complex colloidal structures. They generally impede producing, transporting and refining of crude oil resources. An indepth knowledge of the physical behavior of asphaltenes is needed to mitigate these effects. Predicting the physical behavior of asphaltene such as density is complex and nonlinear as it is a complex molecular mixture …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 5, Issue 3, 2014 · pp. 1–9 Read article
-
Nanomedicine in Combination with Artificial Intelligence (AI): Transforming Cancer Treatment
Abstract: The convergence of nanomedicine and artificial intelligence (AI) holds transformative potential for advancing cancer treatment, particularly in liver cancer. Nanomedicine enables the development of targeted drug delivery systems, enhanced imaging modalities, and precise therapeutic interventions, while AI facilitates data-driven decision-making, personalized treatment plans, and predictive analytics. This synergistic approach can significantly improve the diagnosis, treatment, and monitoring of liver cancer by optimizing the use of nanoparticle-based therapies. AI-powered algorithms can …
Published in Trends in Drug Delivery · Vol. 12, Issue 1, 2025 · pp. 27–30 Read article
-
Multi-Objective Optimization of Polymer-Based Functionally Graded Composites for Lightweight Structures
Abstract: Functionally graded composites (FGCs) improve lightweight structural performance by allowing material properties to change smoothly across a component. Polymer-based FGCs (P-FGCs), in particular, are gaining prominence in aerospace, automotive, and biomedical industries due to their excellent strength-to-weight ratio, tunability, and ease of processing. However, optimizing these materials for lightweight structural applications requires addressing conflicting design objectives, such as maximizing stiffness while minimizing weight or enhancing thermal resistance while maintaining manufacturability. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 961–973 Read article
-
21st Century Cognitive Landscapes: Integrating ICT-Driven Pedagogies for Holistic, Inclusive Education
Abstract: The rapid advancement of Information and Communication Technology (ICT) has revolutionized digital pedagogies, reshaping modern education by improving accessibility, learner engagement, and academic outcomes. This review critically explores the psychological ramifications of digital learning environments while assessing the effectiveness of ICT tools in fostering inclusive and sustainable education. By integrating insights from contemporary research, this paper examines the impact of digital pedagogies on cognitive function, emotional health, and social interactions …
Published in International Journal of Education Sciences · Vol. 2, Issue 2, 2025 · pp. 75–81 Read article
-
Green AI-Enabled Opto-Electronic Communication Systems for Carbon-Neutral Digital Networks
Abstract: The rapid expansion of digital communication infrastructure, driven by cloud computing, Internet of Things (IoT), 6G networks, and artificial intelligence applications, has significantly increased the energy consumption and carbon footprint of modern communication systems. Conventional optical communication networks often rely on static resource allocation and energy-intensive signal processing mechanisms, resulting in inefficient utilization of network resources and elevated operational costs. This study proposes a Green Artificial Intelligence (Green AI)-Enabled Opto-Electronic …
Published in Trends in Opto-electro & Optical Communication · Vol. 16, Issue 2, 2026 Read article
-
Diabetic Risk Prediction Using Machine Learning
Abstract: The global prevalence of Type 2 diabetes has risen dramatically in recent years, posing a serious public health risk. Long-term risk prediction is an important technique for evaluating who is most likely to develop type 2 diabetes. Early detection and response can lead to better management and prevention of diabetes complications. Developing a user-friendly Windows program for long-term Type 2 diabetes risk prediction could revolutionize preventive healthcare due to technological …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 1, 2024 · pp. 11–17 Read article
-
Home Automation System Using IoT
Abstract: The proposed project puts forward a systematic implementation of internet of things (IoT). Since, the technology is becoming more advanced day-by-day. Therefore, manual systems are being replaced by the automatic system. Today, the internet has become an integral part of life. The idea that devices can be controlled remotely across the world is made possible by IoT—the interconnection of devices via a global network. This paper deals with the home …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 11, Issue 1, 2023 · pp. 24–30 Read article
-
Massive Data Capturing and Transmission using Big Data Analytics Model with Machine Learning Prediction
Abstract: Deep learning techniques are widely used in many branches of research and engineering, including language processing, image classification, and speech recognition. Similar to this, processing vast amounts of data is restricted by a number of classical data processing approaches. To deal with information progressively with incredible exactness and effectiveness, huge information investigation requests spic and span, complex calculations in light of machine and profound learning methods. Recent research has, however, …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 9, Issue 3, 2022 · pp. 23–30 Read article
-
Drug-likeness and 3D-QSAR Analysis of 1,2,3-triazoles as Novel Potent HIV-1 Vif Inhibitors: An approach in the development of Leads in the Treatment of HIV Infection
Abstract: AbstractThe human immunodeficiency virus type 1 (HIV-1) Vif protein is one of various primate lentiviral accessory proteins that act as a virulence factor to advance viral duplication and persistence. 3D quantitative structure-activity relationship (QSAR) modeling of thirty-six (36) newly discovered 1,2,3-triazole analogs as potent novel inhibitors of HIV-1 Vif to predict their biological activity (pIC50), to try to improve/optimize it using some numerical data of HIV-1 Vif inhibitors based on …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 9, Issue 3, 2022 · pp. 23–37 Read article
-
Data-Driven Energy Forecasting for Smart Homes: Ensemble Learning from IoT Meters and Relevance for Polymer-Composite Based Smart Infrastructure
Abstract: Reliable estimation of household electricity demand is relevant in creating efficiency in energy usage, optimization of the loads, and intelligent demand-side management in intelligent grid systems. This paper introduces a varied machine learning model that approaches residential electric consumption prediction using an assortment of ensemble regression boosts, including Linear Regression, Lasso Regression, Decision Tree Regressor, Random Forest, and Gradient Boosting, to predict residential electricity consumption environments on a time-series arrested …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 29–64 Read article
-
Study Of Uber-Related Data Using Machine Learning
Abstract: This paper describes the operation of the machine learning algorithm used in the Uber database, which contains data generated by the Uber Movement for a few locations in Hyderabad and the big apple City. Uber is known as a peer-to-peer program. This program connects you to the nearest drivers available to take you to your destination. This database includes Uber capture data with information such as time, ride date additional …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 9, Issue 2, 2022 · pp. 1–6 Read article
-
A Supervised Learning Approach for Toxic Comment Detection on Social Media Platforms
Abstract: Nowadays everyone uses social media platforms like X (formerly Twitter), Instagram, Facebook, etc. for various purposes. With the help of this, we share our opinions, ideas, and feelings. Generally, the datasets obtained from the internet are constructive; however, there is a significant proportion of toxic ones. The datasets are filtered to remove noise, and noise is removed in post-processing. The study initiates with the upload and preprocessing of a toxic …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 2, 2024 · pp. 7–14 Read article
-
Exploring AI-Driven Student Performance Analysis as a Dimension of an AI-Powered Assessment and Feedback System: A Comprehensive Review
Abstract: The rapid proliferation of artificial intelligence (AI) in educational technology has heralded a paradigmatic transformation in assessment methodologies, transitioning from static, summative evaluations to dynamic, data-driven systems that emphasize continuous formative feedback. This comprehensive review interrogates AI-driven student performance analysis as a cardinal dimension of AI-powered assessment and feedback systems (AI-PAFS), synthesizing findings from forty-five rigorously curated open-access empirical studies published between 2015 and 2024. Employing a methodological lens, the …
Published in Current Trends in Information Technology · Vol. 16, Issue 1, 2025 · pp. 24–31 Read article
-
Forward Collision Avoidance System in a Self-driving Remote Controlled Car: An Application of Machine Intelligence
Abstract: Abstract: The paper discusses the experimental vision-based forward collision avoidance system (FORCAS), an autonomous bot car based on machine learning using Raspberry Pi as a processing platform. Using HD camera images as a primary input, Raspberry Pi combines processes and predict path using convolutional neural network and distance estimation models. It distinguishes the stationary objects on a drivable road surface and estimates their distances from a single camera’s view. Classification …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 6, Issue 3, 2019 · pp. 13–18 Read article