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1126 articles for “predict”
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Analysis of Gold Price Trend Using the Hidden Markov Model
Abstract: This study aims to analyze the behavior of gold prices in India through a two-state Hidden Markov Model (HMM). We first formulated crucial parameters, such as the Transition Probability Matrix (TPM), Initial Probability Vector (IPV), and Emission Probability Matrix (EPM). Subsequently, we constructed a hidden Markov probability distribution and evaluated Pearson’s coefficients to gauge the correlations separately for each state. The goodness of fit of the developed model was assessed …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 2, 2024 · pp. 7–16 Read article
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Integration of GIS and AI in Urban Planning and Disaster Management
Abstract: The rapid pace of urbanization, combined with the increasing frequency and intensity of natural disasters, necessitates the development of innovative solutions for urban planning and disaster management. Geographic information systems (GIS) and artificial intelligence (AI) have emerged as transformative technologies capable of addressing these challenges. GIS provides a robust framework for spatial data analysis, while AI enhances decision-making through predictive analytics and automation. This paper explores the integration of GIS …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 1, 2025 · pp. 20–36 Read article
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Machine Learning Revolutionizing Server Management and Performance
Abstract: The modern data center is a complex and dynamic environment, grappling with ever-increasing workloads, stringent performance demands, and the constant pressure for cost optimization. As such, applying machine learning (ML) directly to the server infrastructure offers a powerful avenue for achieving advanced automation, resource optimization, and proactive problem resolution. This article explores the transformative potential of integrating machine learning into server systems, leveraging insights gleaned from the abstract and conclusion …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 36–44 Read article
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Human-robot Collaboration in Manufacturing: Safety, Efficiency, and Technological Developments
Abstract: Human-robot collaboration (HRC) has emerged as a transformative force in modern manufacturing, significantly enhancing productivity, operational flexibility, and overall efficiency. This review article explores the fundamental aspects of HRC, with a particular focus on safety protocols, efficiency optimization, and technological advancements that are shaping the future of collaborative robotics. Ensuring safety in HRC environments is a primary concern, necessitating the implementation of advanced safety measures, risk assessment methodologies, and compliance …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 1, 2025 · pp. 18–23 Read article
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Advancing Asthma Management: The Synergy of Systems Biology, Artificial Intelligence, and Next-Generation Therapeutics
Abstract: Asthma is an inflammatory disorder of the respiratory tract that is chronic and heterogeneous in nature and has various effects on millions of people. Being a chronic inflammatory disease, asthma remains incurable and the major conventional treatments offer limited success due to the mask nature of its pathophysiology. Systems biology/(AI), and next-generation has greatly enhanced knowledge and the management of asthma. The approaches based on gene, transcript, protein, and metabolite …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 1–12 Read article
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Integrated Dam Automation: Real-Time Monitoring and Controlling Using IoT
Abstract: Dam automation is a critical area in water resource management, especially given the rising demand for sustainable and safe water control systems. An integrated approach to dam automation involves implementing advanced sensors and monitoring systems to improve structural safety, water quality, and resource management. This paper presents a comprehensive automation model that combines crack detection, convolutional neural networks (CNNs), water level monitoring, turbidity sensing, and rainfall data to ensure real-time …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 31–38 Read article
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Improving Indoor Room Air Conditioning Using PID Control
Abstract: Energy use in building air conditioning contributes significantly to power demand; therefore, in this work, we propose an improved methodology to achieve comfort conditions through PID control assistance. The project develops a mathematical model based on analytical heat transfer equations for comfort conditions by fulfilling the Fanger equation, considering environmental parameters (ambient temperature), metabolic rate, and people’s physical activity (internal heat generation) to reduce power consumption and improve energy efficiency. …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 12, Issue 1, 2025 · pp. 1–21 Read article
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Smart City Solutions for Waste Management and Pollution Control
Abstract: Recent trends in the role of artificial intelligence, IoT, and other smart technologies have a critical role toward addressing urban environmental challenges related to air quality and waste management in the context of a smart city. This changes the scope of managing air quality as, with the integration of IoT sensors, big data, and AI, they are able to predict pollution levels through real time monitoring and analysis. These technologies …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 1, 2025 · pp. 11–22 Read article
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Fault Detection in Solar PV Systems Integrated with the Power Grid: Evaluating Logistic Regression through Confusion Matrix Analysis
Abstract: This paper proposes a method for failure detection in grid-integrated solar photovoltaic (PV) systems using logistic regression and real-time sensor data. The approach effectively classifies and identifies seven distinct fault types. The developed model demonstrates a high fault identification accuracy, ranging from 93% to 96.5% across various fault types and operational conditions. By leveraging logistic regression, the system utilizes key independent variables that significantly influence the classification process. Additionally, the …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 2, 2025 · pp. 45–52 Read article
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AI-based Drug Discovery-Revolutionizing Pharmaceutical Research
Abstract: The traditional drug discovery process is often costly, time-consuming, and prone to high failure rates. The advent of Artificial Intelligence (AI) has revolutionized this field by significantly enhancing efficiency, reducing costs, and improving success rates. AI-driven approaches, including machine learning (ML), deep learning (DL), and natural language processing (NLP), have transformed key areas such as drug target identification, molecular screening, lead optimization, and clinical trial design. AI models can analyze …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 30–44 Read article
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Role of Machine Learning Principles for Efficient Nuclear Fuel Management and Design
Abstract: The introduction of machine learning (ML) and evolutionary computation methods in addressing complex nuclear fuel management challenges has brought a significant positive change in the domain of nuclear fuel management. Key applications include fuel assembly design optimization, core loading pattern determination, burnup calculation acceleration, fuel performance prediction, and spent fuel characterization. The analysis reveals significant improvements in computational efficiency, prediction accuracy, and optimization capabilities when ML techniques are properly integrated …
Published in Journal of Nuclear Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 22–33 Read article
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Comparative Evaluation of GPBB and CK-MB in Early Diagnosis of Acute Myocardial Infarction in Diabetic and Non-Diabetic Patients
Abstract: Background: Acute myocardial infarction (AMI) continues to be a leading cause of morbidity and death among people worldwide. To lower the risk of problems, early and precise diagnosis is essential, particularly for diabetes patients. The study investigates the diagnostic value of Glycogen Phosphorylase BB (GPBB), a potential early biomarker of myocardial necrosis, and compares it with CK-MB, a widely used cardiac marker, in AMI diagnosis. Inflammatory markers (hs-CRP, IL-6, TNF-α) …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 2, 2025 · pp. 33–37 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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Recent Advances in Quality Control and Quality Assurance: Enhancing Pharmaceutical Product Integrity and Compliance
Abstract: The pharmaceutical industry is undergoing a paradigm shift driven by stringent regulatory expectations and the demand for high-quality, safe, and efficacious drug products. Quality Control (QC) and Quality Assurance (QA) serve as the two foundational pillars that ensure pharmaceutical integrity from raw material acquisition through to product release. Traditional QC and QA practices, while effective, have been challenged by complex formulations, biologics, and personalized medicine, requiring innovative methodologies and technologies. …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 2, 2025 · pp. 54–62 Read article
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Role of Inflammatory Markers and Lipid Abnormalities in Glycemic Dysregulation Among Type 2 Diabetics
Abstract: Background: Diabetes mellitus (DM) is a chronic metabolic disorder characterized by systemic inflammation and associated with various complications in multiple organs. Type 2 diabetes mellitus (T2DM) specifically involves insulin resistance, hyperglycemia, and inflammatory responses. This study investigates the levels of various inflammatory markers and their correlation with glycaemic control in T2DM patients. Objective: To evaluate the levels of inflammatory markers (including NLR, PLR, SII, SIRI, CRP, IL-6, TNF-α, TGF-β, MCP-1, …
Published in Emerging Trends in Metabolites · Vol. 2, Issue 2, 2025 Read article
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Machine Learning-Assisted Design and Optimization of Lightweight Polymer Composites for IoT-Enabled Automotive Applications
Abstract: This study aims to develop an integrated machine learning and optimization framework for the intelligent design of lightweight polymer composites suited for IoT-enabled automotive applications. The goal is to enhance material performance while satisfying multiple design constraints such as mechanical strength, thermal stability, and process compatibility. A curated dataset of polymer composite formulations was used to train a Random Forest Regression (RFR) model capable of predicting tensile strength, thermal conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 12–27 Read article
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Feature Extraction and Analysis of Bearing Faults: A Review
Abstract: One of the most important steps in identifying bearing problems is feature extraction. In order to provide a more meaningful dataset, it entails locating and extracting pertinent features from raw bearing vibration signals. Tasks involving categorization and prediction can then make use of these attributes. In many practical applications, such as monitoring rotating machinery or electronic components, the raw signals collected (e.g., vibration, current, temperature) are often complex, high-dimensional, and …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 20–28 Read article
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Chemical Reactor Design and Analysis: A Review
Abstract: Chemical reactors play a critical role in industries such as oil and gas, chemical processing, and power generation, where they operate under extreme pressure and handle highly toxic, compressible fluids. The growing need for alternative energy sources has led to an increased demand for vessels capable of withstanding high pressure and temperature, especially in the chemical and petroleum industries. Recent innovations in chemical reactor technology have concentrated on creating new …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 2, 2025 · pp. 49–59 Read article
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Mathematical Modeling of Epidemics Using Stochastic Differential Equations: A Review
Abstract: The accurate modeling of infectious disease dynamics is crucial for predicting outbreaks and informing public health interventions. While deterministic models such as the SIR (Susceptible-Infected-Recovered) framework have traditionally been used to understand disease transmission, they often fail to account for the randomness inherent in real-world scenarios. Disease spread is influenced by numerous uncertain factors, including individual behavioral changes, environmental fluctuations, and imperfect data reporting. These uncertainties can significantly impact model …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 1–6 Read article
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AI and Access to Justice: An Indian Perspective
Abstract: Artificial intelligence is set to transform the legal profession, influencing everything from legal research and document review to legal advice and decision-making. This study investigates the possible uses of AI in the legal area, such as predictive analytics and AI-powered legal research tools. This study explains the role of AI in Judicial Systems. The study covers the related literature, challenges and opportunities in Indian judicial system. The usage of AI …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 30–37 Read article