Search Results - "Machine"

A Machine Learning Model for Identifying Sexual Health Influencers to Promote the Secondary Distribution of HIV Self-Testing Among Gay, Bisexual, and Other Men Who Have Sex With Men in China: Quasi-Experimental Study by Yuxin Ni, Ying Lu, Fengshi Jing, Qianyun Wang, Yewei Xie, Xi He, Dan Wu, Rayner Kay Jin Tan, Joseph D Tucker, Xumeng Yan, Jason J Ong, Qingpeng Zhang, Hongbo Jiang, Wencan Dai, Liqun Huang, Wenhua Mei, Yi Zhou, Weiming Tang

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The use and maintenance of the automatic cleaning machine in the Central Sterile Supply Department of Traditional Chinese Medicine hospital (中医院消毒供应室全自动清洗消毒机的使用及维护) by MIAO Yanmei (苗艳梅), WANG Jingju (王京菊)

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Combinatorial Use of Machine Learning and Logistic Regression for Predicting Carotid Plaque Risk Among 5.4 Million Adults With Fatty Liver Disease Receiving Health Check-Ups: Population-Based Cross-Sectional Study by Yuhan Deng, Yuan Ma, Jingzhu Fu, Xiaona Wang, Canqing Yu, Jun Lv, Sailimai Man, Bo Wang, Liming Li

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Advantages of taguchi method compared to response surface methodology for achieving the best surface finish in wire electrical discharge machining (WEDM) / Ananta Venkata Uday Kiran Kandala, Darius Gnanaraj Solomon and Joseph Jeyapaul Arulraj by Uday Kiran Kandala, Ananta Venkata, Solomon, Darius Gnanaraj, Arulraj, Joseph Jeyapaul

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PENGARUH KINERJA MULTI MEREK TERHADAP VOLUME PENJUALAN NOTEBOOK MULTI MEREK ACER:Sensus Pada Toko-toko Penjualan Notebook Multi Merek Acer (eMachines dan Gateway) di Kota Bandung by Irfan Febrianto, -

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HUBUNGAN SOSIALISASI PENGGUNAAN VENDING MACHINE TIKET KERETA API LISTRIK (KRL) DENGAN PENGETAHUAN PENGGUNA JASA COMMUTER LINE( Survei pada Pengguna Jasa Commuter Line di Stasiun Sudirman - Jakarta Pusat) by Yolanda Irsyad, -

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Advances in Intelligent Data Analysis XVIII 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27-29, 2020, Proceedings /

Table of Contents: “…Multivariate Time Series as Images: Imputation Using Convolutional Denoising Autoencoder -- Dual Sequential Variational Autoencoders for Fraud Detection -- A Principled Approach to Analyze Expressiveness and Accuracy of Graph Neural Networks -- Efficient Batch-Incremental Classification Using UMAP for Evolving Data Streams -- GraphMDL: Graph Pattern Selection Based on Minimum Description Length -- Towards Content Sensitivity Analysis -- Gibbs Sampling Subjectively Interesting Tiles -- Even Faster Exact k-Means Clustering -- Ising-Based Consensus Clustering on Special Purpose Hardware -- Transfer Learning by Learning Projections from Target to Source -- Computing Vertex-Vertex Dissimilarities Using Random Trees: Application to Clustering in Graphs -- Towards Evaluation of CNN Performance in Semantically Meaningful Latent Spaces -- Vouw: Geometric Pattern Mining Using the MDL Principle -- A Consensus Approach to Improve NMF Document Clustering -- Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams -- Widening for MDL-Based Retail Signature Discovery -- Addressing the Resolution Limit and the Field of View Limit in Community Mining -- Estimating Uncertainty in Deep Learning for Reporting Confidence: An Application on Cell Type Prediction in Testes Based on Proteomics -- Adversarial Attacks Hidden in Plain Sight -- Enriched Weisfeiler-Lehman Kernel for Improved Graph Clustering of Source Code -- Overlapping Hierarchical Clustering (OHC) -- Digital Footprints of International Migration on Twitter -- Percolation-Based Detection of Anomalous Subgraphs in Complex Networks -- A Late-Fusion Approach to Community Detection in Attributed Networks -- Reconciling Predictions in the Regression Setting: an Application to Bus Travel Time Prediction -- A Distribution Dependent and Independent Complexity Analysis of Manifold Regularization -- Actionable Subgroup Discovery and Urban Farm Optimization -- AVATAR - Machine Learning Pipeline Evaluation Using Surrogate Model -- Detection ofDerivative Discontinuities in Observational Data -- Improving Prediction with Causal Probabilistic Variables -- DO-U-Net for Segmentation and Counting -- Enhanced Word Embeddings for Anorexia Nervosa Detection on Social Media -- Event Recognition Based on Classification of Generated Image Captions -- Human-to-AI Coach: Improving Human Inputs to AI Systems -- Aleatoric and Epistemic Uncertainty with Random Forests -- Master your Metrics with Calibration -- Supervised Phrase-Boundary Embeddings -- Predicting Remaining Useful Life with Similarity-Based Priors -- Orometric Methods in Bounded Metric Data -- Interpretable Neuron Structuring with Graph Spectral Regularization -- Comparing the Preservation of Network Properties by Graph Embeddings -- Making Learners (More) Monotone -- Combining Machine Learning and Simulation to a Hybrid Modelling Approach -- LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-Label Classification -- Angle-Based Crowding Degree Estimation for Many-Objective Optimization.…”
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Multimedia Forensics

Subjects: “…Machine learning.…”
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Learning to Quantify by Esuli, Andrea

Subjects: “…Machine learning bicssc…”
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Learning to Quantify by Esuli, Andrea

Subjects: “…Machine learning bicssc…”
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Chapter 20 Data Quality and Privacy concerns in Digital Trace Data Insights from a Delphi study on machine learning and robots in human life by Engel, Uwe

Subjects: “…AI, big data, data analysis, data archives, data ownership, data science, digital trace, ethical standards, ethics, human-robot interaction, information technology, machine learning, open data, politics, policy, quantitative, replication, social, social media, socio-robots, survey data, survey design, survey methodology, unstructured data…”
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Chapter 20 Data Quality and Privacy concerns in Digital Trace Data Insights from a Delphi study on machine learning and robots in human life by Engel, Uwe

Subjects: “…AI, big data, data analysis, data archives, data ownership, data science, digital trace, ethical standards, ethics, human-robot interaction, information technology, machine learning, open data, politics, policy, quantitative, replication, social, social media, socio-robots, survey data, survey design, survey methodology, unstructured data…”
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Process Mining Workshops ICPM 2022 International Workshops, Bozen-Bolzano, Italy, October 23-28, 2022, Revised Selected Papers /

Subjects: “…Machine learning.…”
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Development of machine learning models predicting mortality using routinely collected observational health data from 0-59 months old children admitted to an intensive care unit in Bangladesh: critical role of biochemistry and haematology data by Subhasish Das, Mustafa Mahfuz, Shah Mohammad Fahim, Tahmeed Ahmed, Md Ashraful Alam, S M Tafsir Hasan, Mark Hoogendoorn, Robert H J Bandsma, Teun Zuiderent-Jerak, Lauren Erdman, Wieger Voskuijl, Daniella Brals, Bartlomiej Boczek, Paraskevi Massara

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A Novel Approach for Continuous Health Status Monitoring and Automatic Detection of Infection Incidences in People With Type 1 Diabetes Using Machine Learning Algorithms (Part 2): A Personalized Digital Infectious Disease Detection Mechanism by Woldaregay, Ashenafi Zebene, Launonen, Ilkka Kalervo, Albers, David, Igual, Jorge, Årsand, Eirik, Hartvigsen, Gunnar

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Modelo de predição de risco de internação em pacientes com Diabetes mellitus tipo 2 atendidos na atenção primária de Curitiba - uma abordagem da inteligência artificial com machine learning by Guilherme Silva Julian, Daniel Ferraz de Campos Filho

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Effectiveness of sexual health influencers identified by an ensemble machine learning model in promoting secondary distribution of HIV self-testing among men who have sex with men in China: study protocol for a quasi-experimental trial by Ying Lu, Yuxin Ni, Qianyun Wang, Fengshi Jing, Yi Zhou, Xi He, Shanzi Huang, Wencan Dai, Dan Wu, Joseph D. Tucker, Hongbo Jiang, Liqun Huang, Weiming Tang

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GIS and Spatial Analysis

Subjects: “…machine learning…”
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Electroencephalography From Basic Research to Clinical Applications

Subjects: “…epilepsy, eeg, encephalopathy, brain-machine interface, depression, rehabilitation…”
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Managing Cybersecurity Threats and Increasing Organizational Resilience

Subjects: “…machine learning…”
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