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776 articles for “decisions”
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Energy-efficient HVAC System with Decision Tree Classifier and Real-time SMS Notification
Abstract: This research paper explores the design and implementation of an energy-efficient heating, ventilation, and air conditioning (HVAC) system aimed at optimizing energy consumption and enhancing operational efficiency. The system incorporates high-efficiency components, including axial flow fans, motors, and intelligent variable frequency drives, achieving an overall system efficiency of up to 85%. By utilizing both static and dynamic pressures, the HVAC system operates more effectively under varying conditions compared to traditional …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 2, Issue 2, 2024 · pp. 29–34 Read article
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AI-Based Software-Defined Satellite in Decision Making: A Study
Abstract: For decades, satellites have been a vital infrastructure, relaying communication signals, observing Earth's climate, and providing critical navigation data. However, the traditional model of satellite operation is often rigid and reactive, relying heavily on pre-programmed instructions and ground-based control. This limits their flexibility and responsiveness in a rapidly changing environment. Enter software-defined satellites (SDS), and now, the game-changer: artificial intelligence (AI). Imagine a satellite that can independently analyze its surroundings, …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 1, 2025 · pp. 63–72 Read article
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Predictive Modeling and Optimization of Tensile and Flexural Strength in FDM 3D Printing Using Decision Trees and Bayesian Optimization.
Abstract: This research investigates predictive modelling and optimization technique for the tensile and flexural strength of PlA (Poly Lactic Acid) in Fused Deposition Modelling (FDM) 3D printing. Employing Decision Trees and Bayesian Optimization enhances comprehension and control of 3D printing process. Precise model predicts PLA material properties based on input parameters. Methodology involves rigorous data preprocessing, encompassing, cleaning, transformation, and normalization. Hyperparameter optimization via grid search systematically explores configurations, optimizing model …
Published in Journal of Polymer & Composites · Vol. 11, Issue 12, 2023 · pp. 203–214 Read article
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Data-Driven Predictive Analytics and Decision- Making in FinTech Using MongoDB and High-Throughput Data Pipelines
Abstract: This paper examines the implementation of MongoDB and high-throughput data pipelines within the financial technology (FinTech) sector to drive data-informed predictive analytics and decision-making. The study focuses on the architectural components, scalability, and challenges of integrating NoSQL databases into real-time data ingestion and analytics pipelines. The transformative potential of these technologies in modern financial systems is highlighted through practical use cases such as fraud detection, credit scoring, and personalized financial …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 1–15 Read article
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Optimized Design and Control of Oil Exploitation Strategies: An Assisted Approach
Abstract: Because there are so many factors and scenarios to consider, optimizing oil exploitation tactics requires complicated decision-making. Conventional approaches frequently concentrate on particular elements of the design infrastructure, which restricts their capacity to fully handle the process. In order to maximize a set of oil exploitation variables in a hierarchical fashion, this research proposes a novel assisted optimization technique that combines mathematical algorithms with engineering analysis. By grouping variables into …
Published in Journal of Petroleum Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 29–34 Read article
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A Study of the Impact of AI-Powered Recommendation Systems on Consumer Purchase Decisions in the E-Commerce Industry
Abstract: Through personalized suggestions, the e-commerce industry has been affected so much that it has been overtaken by AI-powered recommendation systems. This paper examines the effects of AI-powered recommendations on online shoppers and how they influence product discovery, the engagement level of shoppers, and unplanned purchases. Emerging from the results of a survey of 55 graduates and MBA students, more than 70% of respondents claim that AI has helped them find …
Published in Current Trends in Information Technology · Vol. 16, Issue 1, 2025 · pp. 01–06 Read article
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Role of Artificial Intelligence in Health Care Decision Making: Balancing Innovation and Caution
Abstract: Healthcare is undergoing a transformation powered by artificial intelligence, which improves monitoring, diagnosis, and treatment capabilities. Among Artificial Intelligence (AI's) shortcomings is the dearth of an emotional relationship between individuals and medical personnel. Robotic surgery procedures pose the possibility of malfunctioning machinery and mistaken assumptions. So, the present systematic review focused on exploring the boon and bane of the role of AI in predicting various abnormalities in advance to improve …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 24–35 Read article
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A Fuzzy Integrated Web-based Quality Function Deployment Application:A Conceptual Analysis
Abstract: The 'voice of customers' drives the Quality Function Deployment (QFD) process, which is a customer-focusedproduct development method. Making decisions is a critical component of the QFD process. Although QFD aids decision-making, its subjectivity results in ambiguity and uncertainty, resulting in less accurate and consistent findings. Fuzzy ideas must be incorporated to deal with the ambiguity and uncertainty inherent in the QFD process. This will result in better decision-making. Businesses can …
Published in Journal of Web Engineering & Technology Read article
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A Parametric Approach for Decision Making of Low-carbon Building Envelope Design
Abstract: Buildings are major contributors of total carbon emissions than all other categories globally. to reduce these emissions by some quantity must propose the better design before construction. For that, this study proposed a different combinations of building envelope analyzed. From that the best configuration can be implemented for construction to reduce emissions from building at different stages. Through the use of e-QUEST version 3.65, a total of some wall construction …
Published in Journal of Polymer & Composites · Vol. 11, Issue 5, 2023 · pp. 35–43 Read article
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Cloud-driven Fraud Detection: Evaluating Decision Tree and Random Forest Classifiers for Credit Card Transaction Security
Abstract: With the alarming rise in global financial fraud, necessitating substantial annual losses, modern techniques for fraud detection are continuously evolving across various business domains. Fraud detection involves constant monitoring of user activities to estimate, perceive, or prevent undesirable behaviour. Cloud Computing emerges as a promising solution, accelerating application deployment, fostering creativity and innovation, reducing costs, and enhancing overall business acumen. This study introduces a cloud-driven approach to fraud detection, specifically …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 1, 2024 · pp. 13–27 Read article
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The Relevance of Green University Concept on Students’ Enrollment Decision for Higher Education: The Role of Circular and Green Polymer Science
Abstract: Students today increasingly evaluate the commitment of higher education institutions to sustainability and environmental stewardship when making enrollment decisions. As prospective students research colleges and universities, they meticulously assess each institution's environmental policies, initiatives, and programs. This focus on sustainability reflects a broader trend of rising environmental awareness among young people, who often prioritize their values in their educational choices. The present study uniquely examines how the concept of a …
Published in Journal of Polymer & Composites · Vol. 12, Issue 7, 2024 · pp. 47–53 Read article
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The Role of Generative AI in Enhancing Administrative Efficiency: Innovations in Workforce Support Systems
Abstract: Generating AI is the primary form of artificial intelligence that disrupts administrative work across multiple industries by redesigning and promoting the automation of traditional tasks and improving the workforce efficiency of decision-making. In a conventional setting, executive positions have been equally associated with paper-bound responsibilities, common with tedious activities like appointment making, filing, data input, etc. However, improvement in the area of generative AI makes these natural functions assignable, thus …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 47–68 Read article
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Fuzzy Probability Distributions and Their Applications in Uncertain Data Analysis
Abstract: This study explores the use of fuzzy probability distributions in data analysis under uncertain conditions, with a specific focus on their implementation in evaluating call center customer satisfaction. Traditional probability models rely on precise parameters, often failing to account for the inherent variability and subjectivity present in real-world data. In contrast, fuzzy probability distributions, which integrate fuzzy logic principles, offer a more adaptable and realistic framework for addressing such complexities. …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 3, 2024 · pp. 1–8 Read article
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Strategic Optimization of CNC Machining in Production Systems: A Managerial Review of Methods, Metrics, and Industry 4.0 Integration
Abstract: Computer numerical control (CNC) machining has significantly influenced modern production systems by enabling higher efficiency, quality, and sustainability. As industrial operations strive for leaner production and strategic competitiveness, optimization of machining parameters—including cutting speed, feed rate, depth of cut, and tool path strategies—has emerged as a cornerstone of production planning. This review evaluates the optimization methodologies developed from 2015 to 2025, spanning traditional mathematical models to artificial intelligence (AI)-driven metaheuristic …
Published in Journal of Production Research & Management · Vol. 15, Issue 2, 2025 · pp. 25–30 Read article
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Integrating Digital Twins, Smart Materials, and Human Machine Collaboration for Sustainable Smart Manufacturing: Smart CNC & Industry 4.0 Applications
Abstract: The rapid evolution of Industry 4.0 and the emerging transition toward Industry 5.0 have been catalyzed by the convergence of intelligent digital technologies such as digital twins, cyber–physical systems (CPS), artificial intelligence (AI), the Internet of Things (IoT), and human-in-the-loop (HITL) frameworks. These technologies have transformed traditional manufacturing into adaptive, data-centric ecosystems capable of real-time optimization and predictive decision-making. In recent years, the fusion of computer numerical control (CNC) machines, …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 2, 2025 · pp. 1–8 Read article
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A Novel Symmetric Anchor Scoring (SAS) Method for Industrial Location Selection: Application to Electric Vehicle Manufacturing in Tamil Nadu, India
Abstract: This work highlights the city-level detail of decision-making enabled by a new MCDM method Symmetry Anchor Scoring (SAS). Generally conventional methods are good at selecting one best and one worst alternative, but not differentiating among the many strong contenders more likely in practice. Linking MCDM methods to the tradition of decision making, the paper discusses the mathematics and analogical basis of SAS design, provides a visual proof of its ideal …
Published in International Journal of Industrial and Product Design Engineering · Vol. 4, Issue 1, 2026 · pp. 8–19 Read article
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Intelligent Decision Support System for Production Planning and Control in an Automotive Assembly Line
Abstract: The automobile industry has realized the importance of Intelligent Decision Support Systems (IDSS) to improve production planning and control on assembly lines. In the context of automobile manufacturing, this review paper examines the most recent developments, methodology, and applications of IDSS. Key trends, obstacles, and possibilities are discovered through an in-depth examination of the literature. Examining real-world case studies and success stories, the integration of artificial intelligence (AI) and machine …
Published in International Journal of Industrial and Product Design Engineering · Vol. 1, Issue 1, 2023 · pp. 16–21 Read article
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Big Data, Big Impact: The Role of Analytics in Modern Business
Abstract: In modern business, “Big Data” signifies the vast amount of data collected from various sources, and “Big Data Analytics” refers to the process of analyzing this data to extract valuable insights, enabling companies to make data-driven decisions, optimize operations, better understand customers, and ultimately gain a competitive edge by identifying trends, patterns, and opportunities that might otherwise be missed. This study analyzes large datasets, by which businesses can gain deeper …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 2, 2025 · pp. 01–11 Read article
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The Decision of the Maximum Synchronous Torque During the Solar Array Deployment Using the Closed Cable Loop
Abstract: It was a long time since mankind explored and studied the universe, but the early-age power sources have not changed a lot over that period. Solar panels have been used long ago and are still in use today. However, their efficiency has improved considerably. Large and complicated solar arrays are now used instead of simply attaching the panels directly on the face of the satellite. A solar array is essential …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 37–49 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article