204.674 hasil untuk machine learning
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Artikel Jurnal
Machine learning approach for multidimensional poverty estimation
…analysis. This study proposes the use of technologies such as Machine Learning (ML) are the answers to solving this data scarcity. The objective is to estimate the multidimensional poverty index at the personal level in a particular territory of Ecuador by using Machine Learning (ML) regression…
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Artikel Jurnal Teks lengkap
Machine Learning Predictors for Min-Entropy Estimation
This study investigates the application of machine learning predictors for the estimation of min-entropy in random number generators (RNGs), a key component in cryptographic applications where accurate entropy assessment is essential for cybersecurity. Our research indicates that these predictors…
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Artikel Jurnal
Improving fluoroprobe sensor performance through machine learning
…taxonomic groups possess similar or the same pigments. Here, we use machine learning models to enhance assessment and identification of the major prevailing taxa by FP implementation in the well-studied Lake Kinneret (Sea of Galilee), Israel. We compared Extreme Gradient Boosting, Support Vector…
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Artikel Jurnal
Implementasi Machine Learning untuk Pengenalan Penggunaan Makeup
Learning makeup can be challenging, especially for beginners who need to understand face shapes, color gradients, and composition. This study presents a machine learning-based system designed to recognize face shapes and recommend makeup styles. Key features include video tutorials tailored to the…
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Artikel Jurnal
COVID-19 detection using federated machine learning.
The current COVID-19 pandemic threatens human life, health, and productivity. AI plays an essential role in COVID-19 case classification as we can apply machine learning models on COVID-19 case data to predict infectious cases and recovery rates using chest x-ray. Accessing patient's private data…
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Artikel Jurnal
Intelligent nanophotonics: when machine learning sheds light
Abstract The synergistic development of nanophotonics and machine learning has inspired tremendous innovations in both fields in the past decade. In diverse photonics research, deep-learning methods using artificial neural networks become the key game changer that greatly facilitates rapid…
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Artikel Jurnal
Neuromorphic devices assisted by machine learning algorithms
…neural networks, high fault tolerance, robustness, autonomous learning capability, and ultralow energy dissipation. The algorithms of artificial neural network (ANN) have also been widely used because of their facile self-organization and self-learning capabilities, which mimic those of the human…
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Artikel Jurnal
Hands-On Introduction to Quantum Machine Learning
This tutorial covers a hands-on introduction to quantum machine learning. Foundational concepts of quantum information science (QIS) are presented (qubits, single and multiple qubit gates, measurements, and entanglement). Building on that, foundational concepts of quantum machine learning (QML) are…
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Artikel Jurnal
Predicting Employee Turnover Using Machine Learning Techniques
Background: Employee turnover is a persistent issue in human resource management, leading to significant costs for organizations. This study aims to identify the most effective machine learning model for predicting employee attrition, thereby providing organizations with a reliable tool to…
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Artikel Jurnal
Classification of musculoskeletal pain using machine learning
Abstract Musculoskeletal pain is a significant health concern affecting individuals across various demographics and professions, often leading to reduced productivity and impaired quality of life. This study proposes a framework leveraging Particle Swarm Optimization (PSO) to evaluate and assess…
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Artikel Jurnal
Advanced machine learning for innovative drug discovery
Abstract This editorial presents an analysis of the articles published in the Journal of Cheminformatics Special Issue “AI in Drug Discovery”. We review how novel machine learning developments are enhancing structural-based drug discovery; providing better forecasts of molecular properties while…
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Artikel Jurnal
Detecting phishing websites using machine learning technique.
…In this study, the author proposed a URL detection technique based on machine learning approaches. A recurrent neural network method is employed to detect phishing URL. Researcher evaluated the proposed method with 7900 malicious and 5800 legitimate sites, respectively. The experiments' outcome…
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Artikel Jurnal
Traffic congestion forecasting using machine learning methods
…methodology is proposed that combines time series analysis and deep learning, which is highly relevant for modeling nonlinear dependencies and patterns in traffic data. Purpose. The purpose of this study is to develop and test a predictive model capable of accurately forecasting traffic congestion…
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Artikel Jurnal
Inteligência artificial: machine learning na Administração Pública
…– com destaque para uma técnica de indução inteligente de hipótese, o Machine Learning – e a possível aplicação destes mecanismos na Administração Pública, ressaltando os pontos positivos e negativos destes novos modelos tecnológicos e visualizando os possíveis cenários de impacto causados pela…
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Artikel Jurnal Teks lengkap
Advances in Corneal Diagnostics Using Machine Learning
…are crucial points of discussion. This paper also examines the use of machine learning models, specifically Decision Tree and Nearest Neighbor Analysis, which enhance the accuracy of diagnosing based on topographical corneal parameters from corneal topography. These models provide valuable insights…
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Artikel Jurnal
Discovering nuclear models from symbolic machine learning
…all nuclei remains an open challenge. Here, we explore whether symbolic Machine Learning (ML) can rediscover traditional nuclear physics models or identify alternatives with improved simplicity, fidelity, and predictive power. To address this challenge, we developed a Multi-objective Iterated…
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Artikel Jurnal
In-depth Analysis on Machine Learning Approaches
Machine learning (ML) approaches cover several aspects of daily life tasks, including knowledge representation, data analysis, regression, classification, recognition, clustering, planning, reasoning, text recommendation, and perception. The ML approaches enable applications to learn and adapt with…
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Artikel Jurnal
Cartesian atomic moment machine learning interatomic potentials
Abstract Machine learning interatomic potentials (MLIPs) have substantially advanced atomistic simulations in materials science and chemistry by balancing accuracy and computational efficiency. While leading MLIPs rely on representing atomic environments using spherical tensors, Cartesian…
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Artikel Jurnal
Hybrid Machine Learning for CNC Process Monitoring
…and anomaly detection. This study explores the efficacy of hybrid machine learning (ML) models in predicting reference signals for CNC axes using features derived from a physical model. Furthermore, relevant but difficult-to-measure features such as process forces and material removal rate (MRR)…
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