204,674 results for machine learning
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Journal Article
Breast cancer detection by leveraging Machine Learning
…a novel method to detect breast cancer by employing techniques of Machine Learning. The authors carried out an experimental analysis on a dataset to evaluate the performance. The proposed method has produced highly accurate and efficient results when compared to the existing methods.
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Journal Article
Terahertz optical machine learning for object recognition
We demonstrate an optical machine learning method in the terahertz domain, which allows the recognition of objects within a single measurement. As many materials are transparent in the terahertz spectral region, objects hidden within such materials can be identified. In contrast to typical object…
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Journal Article
Machine learning in vehicular networking: An overview
…enable operators to capitalize on emerging infrastructure capabilities. Machine Learning (ML), a powerful methodology for adaptive and predictive system development, has emerged in both vehicular and conventional wireless networks. Adopting data-centric methods enables ML to address highly dynamic…
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Journal Article
Machine learning identifies key microbial signatures for
…as well as presence of Salmonella . Using random forest-based machine learning approach, Escherichia coli, Shigella dysenteriae , and Shigella flexneri were identified to be positively correlated to Salmonella , while Romboutsia timonensis was negatively correlated with Salmonella -presence. In…
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Journal Article Full text
Predicting Football Match Outcomes Using Machine Learning
Football match outcomes are influenced by a complex interplay of dynamic team strategies and stochastic match events, posing a significant challenge for predictive analytics. In this paper, we present a unified benchmarking study for football match outcome classification, using a dataset of 225,474…
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Journal Article
Machine-learning in optimization of CRISPR technology
…hindered by several inherent limitations. This review surveys a range of machine-learning based approaches that aim to address these challenges. In particular, we focus on the optimization of key components of the CRISPR system, including protospacer adjacent motif recognition…
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Journal Article Full text
Detecting Information Operations Using Machine Learning Algorithms
…information operations. This paper explores the application of machine learning (ML) algorithms in detecting and classifying disinformation as a means of supporting experts engaged in combating influence campaigns. We utilize a labelled English dataset, and a custom collected Bulgarian news dataset…
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Journal Article
Exploring Trajectory Prediction Through Machine Learning Methods
…multi-user multi-step trajectory prediction, we first design a basic deep learning-based prediction framework, where the long short-term memory (LSTM) network is directly applied as the most critical component to learn user-specific mobility pattern from the user's historical trajectories and…
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Journal Article
Airport resource allocation using machine learning techniques
…demands. this research presents a comparison between the most used machine learning techniquesimplemented in many different fields for demand prediction and resource allocation. The prediction model nomi-nated and used in this research is the Support Vector Machine (SVM) to predict the required…
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Journal Article
Application of machine learning in SNP discovery
…SNP predictions even with stringent parameter values. We developed a machine learning (ML) method to augment PolyBayes to improve its prediction accuracy. ML methods have also been successfully applied to other bioinformatics problems in predicting genes, promoters, transcription factor binding…
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Journal Article
Machine learning on thyroid disease: a review
This study reviews the recent progress of machine learning for the early diagnosis of thyroid disease. Based on the results of this review, different machine learning methods would be appropriate for different types of data for the early diagnosis of thyroid disease: (1) the random forest and…
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Journal Article
Machine learning coarse grained models for water
A computationally efficient description of ice-water systems at the mesoscopic scale is challenging due to system size and timescale limitations. Here the authors develop a machine-learned coarse-grained water model to elucidate the ice nucleation process much more efficiently than previous models.
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Journal Article
Optimized machine learning for BIST profitability prediction
Abstract Forecasting firm profitability from financial-panel data requires flexibility in prediction and time-respecting validation. In this study, we forecast Return on Assets (ROA), Return on Equity (ROE) and Net Profit Margin (NPM) for technology firms listed on Borsa Istanbul exactly…
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Journal Article Full text
Machine Learning Approaches to House Price Determinants
This study takes housing prices in Jinan as an example. Data were collected from official government websites and official housing price platforms. The Hadoop platform was used for distributed storage and preprocessing. Linear regression and recurrent neural network (RNN) models were constructed to…
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Journal Article
Probability-based efficiency analysis through machine learning
This study presents a novel framework that integrates Data Envelopment Analysis (DEA) with machine learning (ML) classification techniques to improve robustness, interpretability and relevance of efficiency assessments. The method reinterprets DEA as a probabilistic classification task, using ML to…
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Journal Article
Managing Disruptions in Production with Machine Learning
…intervention altogether. This paper presents one possible application of Machine Learning (ML) in disruption management on a real-life use case in mixed model continuous production, specifically in the final assembly. The aim is to ensure high-quality online decision support for PPC tasks. This…
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Journal Article
Head Impact Detection Using Machine Learning Algorithms
…safety measures. This study addresses this crucial need by utilizing machine learning algorithms applied to data from piezoelectric sensors on a simulated head model. Employing a systematic approach, this work utilizes Random Forest (RF) and Extreme Gradient Boosting (XGBoost) models to process the…
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Journal Article Full text
Designing Multilayered Electromagnetic Absorbers with Machine Learning
This work presents a generative machine learning model that predicts upper graphene element configurations for a multilayer flexible electromagnetic absorber. The model uses the lower graphene layer as input and S-parameters as conditional input. It is increasingly difficult to fabricate multilayer…
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