First Half of 2020

Development of Application to Deal with Large Data Using Hadoop for 3D Printer

3D printing is one of the emerging technologies and getting a lot of attention. To do 3D printing, 3D model is first generated, and then converted to G-code which is 3D printer’s operations. Facet, which is a small triangle, represents a small surfac...
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Topic Analysis of the National Petition Site and Prediction of Answerable Petitions Based on Deep Learning

Since the opening of the national petition site, it has attracted much attention. In this paper, we perform topic analysis of the national petition site and propose a prediction model for answerable petitions based on deep learning. First, 1,500 peti...
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Estimating Gastrointestinal Transition Location Using CNN-based Gastrointestinal Landmark Classifier

Since the performance of deep learning techniques has recently been proven in the field of image processing, there are many attempts to perform classification, analysis, and detection of images using such techniques in various fields. Among them, the...
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An Energy Consumption Prediction Model for Smart Factory Using Data Mining Algorithms

Energy Consumption Predictions for Industries has a prominent role to play in the energy management and control system as dynamic and seasonal changes are occurring in energy demand and supply. This paper introduces and explores the steel industry's ...
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Second Half of 2019

Enhanced Sound Signal Based Sound-Event Classification

The explosion of data due to the improvement of sensor technology and computing performance has become the basis for analyzing the situation in the industrial fields, and various attempts to detect events based on such data are increasing recently. I...
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Evaluation of Sentimental Texts Automatically Generated by a Generative Adversarial Network

Recently, deep neural network based approaches have shown a good performance for various fields of natural language processing. A huge amount of training data is essential for building a deep neural network model. However, collecting a large size of ...
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A Node2Vec-Based Gene Expression Image Representation Method for Effectively Predicting Cancer Prognosis

Accurately predicting cancer prognosis to provide appropriate treatment strategies for patients is one of the critical challenges in bioinformatics. Many researches have suggested machine learning models to predict patients’ outcomes based on their g...
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A Technique for Detecting Companion Groups from Trajectory Data Streams

There have already been studies analyzing the trajectories of objects from data streams of moving objects. Among those studies, there are also studies to discover groups of objects that move together, called companion groups. Most studies to discover...
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First Half of 2019

Sentiment Analysis of Foot-and-Mouth Disease Using Tweet Text-Mining Technique

Due to the FMD(foot-and-mouth disease), the domestic animal husbandry and related industries suffer enormous damage every year. Although various academic researches related to FMD are ongoing, engineering studies on the social effects of FMD are very...
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A Study on the Identification of Open Source License Compatibility Violations

Open source software is used in various ways when developing new softwares all around the world. It requires rights and responsibilities as a form of an open source software license. Because the license is a contract between original software develop...
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Deep Neural Network-Based Scene Graph Generation for 3D Simulated Indoor Environments

Scene graph is a kind of knowledge graph that represents both objects and their relationships found in a image. This paper proposes a 3D scene graph generation model for three-dimensional indoor environments. An 3D scene graph includes not only objec...
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Evaluation of Sentimental Texts Automatically Generated by a Generative Adversarial Network

Recently, deep neural network based approaches have shown a good performance for various fields of natural language processing. A huge amount of training data is essential for building a deep neural network model. However, collecting a large size of ...
show more