• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.1-6
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• 2013

Three Surface cracks are among the more common flaws in aircraft and pressure vessel components. Accurate stress intensity analyses and crack growth rate data of surface-cracked components are needed for reliable prediction of their fatigue life and fracture strengths. Three Dimensional finite element method (FEM) was used to obtain the stress intensity factor for surface cracks existing in structures. A geometry model, i.e. a solid containing one or several 3D cracks is defined. Nodes are generated by bucket method, and quadratic tetrahedral solid elements are generated by the Delaunay triangulation techniques. To examine accuracy and efficiency of the present system, the stress intensity factor for a semi-elliptical surface crack in cylindrical structures subjected to pressure is calculated. Analysis results by present system showed good agreement with those by ASME equation and Raju-Newman's equation.

• Journal of the Korea Society of Computer and Information
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• v.15 no.3
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• pp.111-119
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• 2010

An artificial light source has a character that a light emits from a point to all directions with many radial and straight ray shapes. It is very difficult and complex to render those emitting lights. Also, users have difficulty in expressing exactly 3D objects because of colors varying with changing of a light and having many parameters. In this paper, to solve those problems we design an artificial light source using X3D to create a model that represents easily many radial and straight ray shapes and propose the online system that each factors of colors to be reflected by a light is separated and then users can control them to detect object's colors by a mouse. Various light sources with reality can be easily created using proposed system.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.37-44
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• 2021

This study is implemented as a sensor-less position controller capable of multi-turn detection to replace the expensive absolute encoder used in the turret servo system. For sensor-less control, the position information of the rotor is essential. For this, a magnetic flux estimator was implemented from the mathematical model of IPMSM used in the turret servo system. The position of the rotor and the angular velocity of the rotor were obtained using the rotor magnetic flux calculated from the magnetic flux estimator. Using the zero-crossing technique, one pulse was generated for each rotation of the estimated rotor magnetic flux to measure the number of multi-turns. Simulation and experiment results confirmed the usefulness of the proposed method.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.4
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• pp.270-279
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• 2017

Regional assessment of crop productivity using a gridded simulation approach could aid policy making and crop management. Still, little effort has been made to develop the systems that allows gridded simulations of crop growth using ORYZA 2000 model, which has been used for predicting rice yield in Korea. The objectives of this study were to develop a series of data processing modules for creating input data files, running the crop model, and aggregating output files in a region of interest using gridded data files. These modules were implemented using C++ and R to make the best use of the features provided by these programming languages. In a case study, 13000 input files in a plain text format were prepared using daily gridded weather data that had spatial resolution of 1km and 12.5 km for the period of 2001-2010. Using the text files as inputs to ORYZA2000 model, crop yield simulations were performed for each grid cell using a scenario of crop management practices. After output files were created for grid cells that represent a paddy rice field in South Korea, each output file was aggregated into an output file in the netCDF format. It was found that the spatial pattern of crop yield was relatively similar to actual distribution of yields in Korea, although there were biases of crop yield depending on regions. It seemed that those differences resulted from uncertainties incurred in input data, e.g., transplanting date, cultivar in an area, as well as weather data. Our results indicated that a set of tools developed in this study would be useful for gridded simulation of different crop models. In the further study, it would be worthwhile to take into account compatibility to a modeling interface library for integrated simulation of an agricultural ecosystem.

• Annual Conference on Human and Language Technology
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• 2022.10a
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• pp.465-469
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• 2022

자동 음성 인식 (Automatic Speech Recognition) 기술이 발달함에 따라 자동 음성 인식 시스템의 성능을 높이기 위한 방법 중 하나로 자동 후처리기 연구(automatic post-processor)가 진행되어 왔다. 후처리기를 훈련시키기 위해서는 오류 유형이 포함되어 있는 병렬 말뭉치가 필요하다. 이를 만드는 간단한 방법 중 하나는 정답 문장에 오류를 삽입하여 오류 문장을 생성하여 pseudo 병렬 말뭉치를 만드는 것이다. 하지만 이는 실제적인 오류가 아닐 가능성이 존재한다. 이를 완화시키기 위하여 Back TranScription (BTS)을 이용하여 후처리기 모델 훈련을 위한 병렬 말뭉치를 생성하는 방법론이 존재한다. 그러나 해당 방법론으로 생성 할 경우 노이즈가 적을 수 있다는 관점이 존재하다. 이에 본 연구에서는 BTS 방법론과 인위적으로 노이즈 강도를 추가한 방법론 간의 성능을 비교한다. 이를 통해 BTS의 정량적 성능이 가장 높은 것을 확인했을 뿐만 아니라 정성적 분석을 통해 BTS 방법론을 활용하였을 때 실제 음성 인식 상황에서 발생할 수 있는 실제적인 오류를 더 많이 포함하여 병렬 말뭉치를 생성할 수 있음을 보여준다.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.21-30
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• 2024

This research aims to design a system capable of generating real web pages based on deep learning and big data, in three stages. First, a classification system was established based on the industry type and functionality of e-commerce websites. Second, the types of components of web pages were systematically categorized. Third, the entire web page auto-generation system, applicable for deep learning, was designed. By re-engineering the deep learning model, which was trained with actual industrial data, to analyze and automatically generate existing websites, a directly usable solution for the field was proposed. This research is expected to contribute technically and policy-wise to the field of generative AI-based complete website creation and industrial sectors.

• The KIPS Transactions:PartA
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• v.10A no.2
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• pp.165-172
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• 2003

In this paper, we constructed horizontal and vertical virtual spaces using the projection table and the projection wall. We then implemented a system that stereoscopically visualizes three-dimensional (3D) buildings in the virtual environments in accordance with the user's viewing point. The projection table, a kind of horizontal display equipment, is effectively used in reproducing operations on a table or desk as well as in areas that require bird-eye views because its viewing frustum allows to view things from above. On the other hand, the large projection wall, a kind of vertical display equipment, is effectively used in navigating virtual spaces because its viewing frustum allows to take a front view. In this paper, we provided quick interaction between the user and virtual objects by representing major objects as detail 3D models and a background as images. We also augmented the reality by properly integrating models and images with user's locations and viewpoint in different virtual environments.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.6
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• pp.425-434
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• 2019

It is important to ensure the seismic safety of pile-bent bridges constructed in areas with thick soft ground consisting of various soil layers against seismic motion in these layers. In this study, several synthetic seismic waves that are compatible with the seismic design spectrum for rock sites were generated, and the ground acceleration history of each soil layer was obtained based on ground analyses. Using these acceleration histories, each soil layer was modeled using equivalent linear springs, and multi-support excitation analyses were performed using the input motion obtained at each soil layer. Due to the nonlinear behavior of the soft soil layers, the intensity of the input ground motion was not amplified, which resulted in the elastic behavior of the bridge. In addition, inputting the acceleration history obtained from a particular layer simultaneously into all the ground springs reduced the response. Therefore, the seismic performance of this type of bridge might be overestimated if multi-excitation analysis is not performed.

• The Mathematical Education
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• v.63 no.2
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• pp.165-186
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• 2024

Despite the growing attention on artificial intelligence-based automated scoring technology as a support method for the introduction of descriptive items in school environments and large-scale assessments, there is a noticeable lack of foundational research in mathematics compared to other subjects. This study developed an automated scoring model for two descriptive items in first-year middle school mathematics using the Random Forest algorithm, evaluated its performance, and explored ways to enhance this performance. The accuracy of the final models for the two items was found to be between 0.95 to 1.00 and 0.73 to 0.89, respectively, which is relatively high compared to automated scoring models in other subjects. We discovered that the strategic selection of the number of evaluation categories, taking into account the amount of data, is crucial for the effective development and performance of automated scoring models. Additionally, text preprocessing by mathematics education experts proved effective in improving both the performance and interpretability of the automated scoring model. Selecting a vectorization method that matches the characteristics of the items and data was identified as one way to enhance model performance. Furthermore, we confirmed that oversampling is a useful method to supplement performance in situations where practical limitations hinder balanced data collection. To enhance educational utility, further research is needed on how to utilize feature importance derived from the Random Forest-based automated scoring model to generate useful information for teaching and learning, such as feedback. This study is significant as foundational research in the field of mathematics descriptive automatic scoring, and there is a need for various subsequent studies through close collaboration between AI experts and math education experts.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.6
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• pp.11-20
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• 2023

The cost of medical treatment for motor vehicle accidents is increasing every year. In this study, we created a model to predict long-term hospitalization(more than 18 days) among minor patients, which is the main item of increasing traffic accident medical expenses, using five algorithms such as decision tree, and analyzed the factors affecting long-term hospitalization. As a result, the accuracy of the prediction models ranged from 91.377 to 91.451, and there was no significant difference between each model, but the random forest and XGBoost models had the highest accuracy of 91.451. There were significant differences between models in the importance of explanatory variables, such as hospital location, name of disease, and type of hospital, between the long-stay and non-long-stay groups. Model validation was tested by comparing the average accuracy of each model cross-validated(10 times) on the training data with the accuracy of the validation data. To test of the explanatory variables, the chi-square test was used for categorical variables.