Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

 
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Session Overview
Session
Regular Session : Classification and data management methods
Time:
Wednesday, 08/Sept/2021:
12:00pm - 2:00pm

Session Chair: Georges Abdul-Nour
Session Chair: Belgacem Bettayeb
Virtual location: Wednesday Room 2


External Resource:
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Presentations
ID: 198 / RS-08: 1
Regular Paper Submission
Data-driven Production Management: Machine Learning and Artificial Intelligence
Keywords: Sawmill simulator metamodels, Artificial Intelligence, Iterative Closest Point dissimilarity

Dissimilarity to class medoids as features for 3D point cloud classification

Sylvain Chabanet, Valentin Chazelle, Philippe Thomas, Hind Bril El-Haouzi

CRAN, France



ID: 278 / RS-08: 2
Regular Paper Submission
Data-driven Production Management: Machine Learning and Artificial Intelligence
Keywords: Agglomerative Hierarchical clustering, BIRCH clustering, COVID-19, K-means clustering, P-median

A Comparative Study of Classification Methods on the States of the USA based on COVID-19 Indicators

İbrahim Miraç ELİGÜZEL1, Eren ÖZCEYLAN2

1Gaziantep University, Turkey; 2Gaziantep University, Turkey



ID: 334 / RS-08: 3
Regular Paper Submission
Data-driven Production Management: Machine Learning and Artificial Intelligence
Smart Manufacturing & Industry 4.0: Intelligent Maintenance Systems
Keywords: Condition-Based Maintenance (CBM), Maintenance data, Data management

Maintenance data management for condition-based maintenance implementation

Humberto Teixeira, Catarina Teixeira, Isabel Lopes

ALGORITMI Research Centre, University of Minho, Guimarães, Portugal



ID: 392 / RS-08: 4
Regular Paper Submission
Data-driven Production Management: Machine Learning and Artificial Intelligence
Smart Manufacturing & Industry 4.0: Intelligent Maintenance Systems
Keywords: Smart maintenance, Predictive maintenance, Machine learning, Health assessment, Feature selection and fusion

A machine learning based health indicator construction in implementing predictive maintenance: A real world industrial application from manufacturing

Harshad Kurrewar, Ebru Turanoglu Bekar, Anders Skoogh, Per Nyqvist

Chalmers University of Technology, Sweden



ID: 571 / RS-08: 5
Regular Paper Submission
Keywords: Artificial Intelligence, Machine Learning, aviation security, X-ray detection

Development of Convolutional Neural Network Architecture for Detecting Dangerous Goods for X-ray Aviation Security in Artificial Intelligence

Woong Kim1, Chulung Lee2

1Department of Industrial Management Engineering, Korea University, Korea, Republic of (South Korea); 2School of Industrial Management Engineering, Korea University, Korea, Republic of (South Korea)