• Journal of information and communication convergence engineering
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• v.21 no.3
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• pp.244-251
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• 2023

Engineering or humanities data are stored in databases and are often used for search services. While the latest deep-learning technologies, such like BART and BERT, are utilized for data analysis, humanities data still rely on traditional databases. Representative analysis methods include n-gram and lexical statistical extraction. However, when using a database, performance limitation is often imposed on the result calculations. This study presents an experimental process using MariaDB on a PC, which is easily accessible in a laboratory, to analyze the impact of the database on data analysis performance. The findings highlight the fact that the database becomes a bottleneck when analyzing large-scale text data, particularly over hundreds of thousands of records. To address this issue, a method was proposed to provide real-time humanities data analysis web services by leveraging the open source database, with a focus on the Seungjeongwon-Ilgy, one of the largest datasets in the humanities fields.

• Journal of Internet Computing and Services
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• v.20 no.4
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• pp.29-38
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• 2019

Currently, information society is rapidly changing and demands innovation and creativity in various fields. Therefore, the importance of mathematics, which can be the basis of creativity and logic, is emphasized. The purpose of this paper is to develop a math education application that can further expand the logical thinking of mathematics and allow voluntary learning to occur through the use of readily available teaching aid for children to form motivation and interest in learning. This paper provides math education applications using a smartphone and blocks for children. The main function of the application is to shoot with the camera and show the calculated values. When a child uses a block to make a formula and shoots a block using a camera, you can directly see the calculated value of your formula. The preprocessing process, text extraction, and character recognition of the photographed images have been implemented using OpenCV libraries and Tesseract-OCR libraries.

• Journal of KIBIM
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• v.9 no.2
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• pp.1-10
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• 2019

In this research, schedule optimization is defined as balancing the number of workers while keeping the demand and needs of the project resources, creating the perfect schedule for each activity. Therefore, when one optimizes a schedule, multiple potentials of schedule changes are assessed to get an instant view of changes that avoid any over and under staffing while maximizing productivity levels for the available labor cost. Optimizing the number of workers in the scheduling process is not a simple task since it usually involves many different factors to be considered such as the development of quantity take-offs, cost estimating, scheduling, direct/indirect costs, and borrowing costs in cash flow while each factor affecting the others simultaneously. That is why the optimization process usually requires complex computational simulations/modeling. This research attempts to find an optimal selection of daily maximum workers in a project while considering the impacts of other factors at the same time through OPEN BIM based multiple computer simulations in resource leveling. This paper integrates several different processes such as quantity take-offs, cost estimating, and scheduling processes through computer aided simulations and prediction in generating/comparing different outcomes of each process. To achieve interoperability among different simulation processes, this research utilized data exchanges supported by building SMART-IFC effort in automating the data extraction and retrieval. Numerous computer simulations were run, which included necessary aspects of construction scheduling, to produce sufficient alternatives for a given project.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.556-570
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• 2021

The existing video expression recognition methods mainly focus on the spatial feature extraction of video expression images, but tend to ignore the dynamic features of video sequences. To solve this problem, a multi-mode convolution neural network method is proposed to effectively improve the performance of facial expression recognition in video. Firstly, OpenFace 2.0 is used to detect face images in video, and two deep convolution neural networks are used to extract spatiotemporal expression features. Furthermore, spatial convolution neural network is used to extract the spatial information features of each static expression image, and the dynamic information feature is extracted from the optical flow information of multiple expression images based on temporal convolution neural network. Then, the spatiotemporal features learned by the two deep convolution neural networks are fused by multiplication. Finally, the fused features are input into support vector machine to realize the facial expression classification. Experimental results show that the recognition accuracy of the proposed method can reach 64.57% and 60.89%, respectively on RML and Baum-ls datasets. It is better than that of other contrast methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.7
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• pp.67-77
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• 2016

In this paper, we propose an algorithm for open/closed eye detection based on modified Hausdorff distance. The proposed algorithm consists of two parts, face detection and open/closed eye detection parts. To detect faces in an image, MCT (Modified Census Transform) is employed based on characteristics of the local structure which uses relative pixel values in the area with fixed size. Then, the coordinates of eyes are found and open/closed eyes are detected using MHD (Modified Hausdorff Distance) in the detected face region. Firstly, face detection process creates an MCT image in terms of various face images and extract criteria features by PCA(Principle Component Analysis) on offline. After extraction of criteria features, it detects a face region via the process which compares features newly extracted from the input face image and criteria features by using Euclidean distance. Afterward, the process finds out the coordinates of eyes and detects open/closed eye using template matching based on MHD in each eye region. In performance evaluation, the proposed algorithm achieved 94.04% accuracy in average for open/closed eye detection in terms of test video sequences of gray scale with 30FPS/$320{\times}180$ resolution.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.1
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• pp.145-149
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• 2014

In this study, using X-ray cargo container scanning device and to differentiate the concept of three-dimensional information extraction applied for X-ray scanning device as an ingredient in the rotation of the X-Ray Linear Pushbroom Stereo System by introducing the geometric How to model was introduced. Three-dimensional information obtained through the matching of a single voxel space filled with a random vector operations for each voxel in the three dimensional shape reconstruction algorithm using the definition, and in time, the time required for each step were analyzed. Using OpenCV in each step by applying parallelization techniques approximately 1.8 times improvement in the processing time of the check, but do not meet the target within one minute levels. The other hand, X-ray images by the primary process to convert the point View the results of real-time stereo through a three-dimensional could feel the comfort level.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.685-694
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• 2022

Building information is essential for various urban spatial analyses. For this reason, continuous building monitoring is required, but it is a subject with many practical difficulties. To this end, research is being conducted to extract buildings from satellite images that can be continuously observed over a wide area. Recently, deep learning-based semantic segmentation techniques have been used. In this study, a part of the structure of the context-based ResU-Net was modified, and training was conducted to automatically extract a building from a 30 cm Worldview-3 RGB image using SpaceNet's building v2 free open data. As a result of the classification accuracy evaluation, the f1-score, which was higher than the classification accuracy of the 2nd SpaceNet competition winners. Therefore, if Worldview-3 satellite imagery can be continuously provided, it will be possible to use the building extraction results of this study to generate an automatic model of building around the world.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.12
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• pp.7385-7392
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• 2014

Extension IFC schema of subsidiary facilities were developed for the purpose of establishing an information model standard for roads. The IFC entities, types and properties for subsidiary facilities were defined through an analysis of the road design documents for the extraction physical component and design information. The converter and viewer for applying the new schema were then developed. Subsidiary facilities BIM models were converted to new IFC models to verify the research results. Standard BIM-based delivery and verification systems are enabled by using a standard model converted by new schema. Furthermore, it can establish an open BIM environment using an IFC over the entire life cycle of the civil engineering project.

• Proceedings of the KSRS Conference
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• v.1
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• pp.98-101
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• 2006

In general, stereo images are widely used to remote sensing or photogrametric applications for the purpose of image understanding and feature extraction or cognition. However, the most cases of these stereo-based application deal with 2-D satellite images or the airborne photos so that its main targets are generation of small-scaled or large-scaled DEM(Digital Elevation Model) or DSM(Digital Surface Model), in the 2.5-D. Contrast to these previous approaches, the scope of this study is to investigate 3-D stereo processing and visualization of true geo-referenced 3-D features based on anaglyph technique, and the aim is at the prototype development for stereo visualization system of complex typed 3-D GIS features. As for complex typed 3-D features, the various kinds of urban landscape components are taken into account with their geometric characteristics and attributes. The main functions in this prototype are composed of 3-D feature authoring and modeling along with database schema, stereo matching, and volumetric visualization. Using these functions, several technical aspects for migration into actual 3-D GIS application are provided with experiment results. It is concluded that this result will contribute to more specialized and realistic applications by linking 3-D graphics with geo-spatial information.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.11a
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• pp.55-60
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• 2005

지리 공간 정보에 대한 관심 증가와 더불어 활용 분야도 다양해지고 있다. OGC(Open GIS Consortium)에서는 XML(extensible Markup Language)을 GIS 분야에 도입한 GML(Geography Markup Language)을 개발하였으며 여러 활용 분야에서 GML을 사용하고 계속적으로 연구되고 있다. 본 연구에서는 기존의 XML 문서를 기반으로 연구되었던 데이터 마이닝 방법 중 하나인 연관규칙을 GML 데이터에 사용하여 의미 있는 규칙을 찾아내려 한다. 규칙을 찾는 방법에는 2가지가 있을 수 있는데 하나는 GML 데이터의 내용만을 뽑아내어 그에 따른 규칙을 찾아내는 방법이고, 다른 하나는 사용된 태그와 속성을 기반으로 규칙을 찾아내는 방법이다. 본 연구에서는 2가지 방법을 통해 규칙을 찾는 것에 대하여 기술할 것이다. 본 연구를 바탕으로 GML문서를 사용하는 여러 분야에서 기본 정보뿐만 아니라 함축적이고 의미 있는 정보도 얻어 낼 수 있을 것으로 기대한다.