• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.48-57
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• 2019

The purpose of this study is to understand the intention of the inquirer from the single text type question in Goal-oriented dialogue. Goal-Oriented Dialogue system means a dialogue system that satisfies the user's specific needs via text or voice. The intention analysis process is a step of analysing the user's intention of inquiry prior to the answer generation, and has a great influence on the performance of the entire Goal-Oriented Dialogue system. The proposed model was used for a daily chemical products domain and Korean text data related to the domain was used. The analysis is divided into a speech-act which means independent on a specific field concept-sequence and which means depend on a specific field. We propose a classification method using the word embedding model and the CNN as a method for analyzing speech-act and concept-sequence. The semantic information of the word is abstracted through the word embedding model, and concept-sequence and speech-act classification are performed through the CNN based on the semantic information of the abstract word.

• Tuberculosis and Respiratory Diseases
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• v.82 no.1
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• pp.27-34
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• 2019

Background: Understanding the burden of disease is important to establish cost-effective treatment strategies and to allocate healthcare resources appropriately. However, little reliable information is available regarding the overall economic burden imposed by chronic obstructive pulmonary disease (COPD) in Korea. Methods: This study is a multicenter observational research on the COPD burden in Korea. Total COPD costs were comprised of three categories: direct medical, direct non-medical, and indirect costs. For direct medical costs, institutional investigation was performed at 13 medical facilities mainly based on the claims data. For direct non-medical and indirect costs, site-based surveys were administered to the COPD patients during routine visits. Total costs were estimated using the COPD population defined in the recent report. Results: The estimated total costs were approximately 1,245 million US dollar (1,408 billion Korean won). Direct medical costs comprised approximately 20% of the total estimated costs. Of these, formal medical costs held more than 80%. As direct non-medical costs, nursing costs made up the largest percentage (39%) of the total estimated costs. Costs for COPD-related loss of productivity formed four fifths of indirect costs, and accounted for up to 33% of the total costs. Conclusion: This study shows for the first time the direct and indirect costs of COPD in Korea. The total costs were enormous, and the costs of nursing and lost productivity comprised approximately 70% of total costs. The results provide insight for an effective allocation of healthcare resources and to inform establishment of strategies to reduce national burden of COPD.

• Korean Chemical Engineering Research
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• v.59 no.2
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• pp.209-218
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• 2021

First principle-based modeling studies have been performed to improve the heat exchange efficiency of ORV and optimize operation, but the heat transfer coefficient of ORV is an irregular system according to time and location, and it undergoes a complex modeling process. In this study, FNN, LSTM, and AutoML-based modeling were performed to confirm the effectiveness of data-based modeling for complex systems. The prediction accuracy indicated high performance in the order of LSTM > AutoML > FNN in MSE. The performance of AutoML, an automatic design method for machine learning models, was superior to developed FNN, and the total time required for model development was 1/15 compared to LSTM, showing the possibility of using AutoML. The prediction of NG and seawater discharged temperatures using LSTM and AutoML showed an error of less than 0.5K. Using the predictive model, real-time optimization of the amount of LNG vaporized that can be processed using ORV in winter is performed, confirming that up to 23.5% of LNG can be additionally processed, and an ORV optimal operation guideline based on the developed dynamic prediction model was presented.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.31 no.4
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• pp.191-212
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• 2020

In this study, a study on the cooperative system of the Chungnam Library's joint preservation data center and a plan for the construction of the use service was proposed based on the analysis of the current status of the preservation library of the Chungcheongnam-do public library. In order to establish a cooperative plan for the joint preservation archive and to promote the provision of services, the current state of the collection of 62 public libraries in Chungnam-do and the status of the preservation archives that are operating separately were identified. As a result of the study, it was found that all matters related to the operation of the joint preservation archive should be made through agreements or consultations between the participants, and the operation of the joint preservation archive should also be made under a systematic cooperation system between the participants. To this end, it is necessary to establish a cooperative system for the Chungnam Library Joint Preservation Archives, and to form and operate the Joint Preservation Archives Steering Committee, a consultative body (cooperation network). In addition, all matters related to the operation of the Joint Preservation Archive, such as transfer criteria, must be regulated and implemented through consultation with the Joint Preservation Archive Steering Committee.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.77-83
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• 2020

The heat treatment facility is in a situation where the scope of application of the remote IOT system is expanding due to the harsh environment caused by high heat and long working hours among the root industries. In this heat treatment process environment, the IOT middleware is required to play a pivotal role in interpreting, managing and controlling data information of IoT devices (sensors, etc.). Until now, the system controlled by the heat treatment remotely was operated with the command of the operator's batch system without overall monitoring of the site situation. However, for the safety and precise control of the heat treatment facility, it is necessary to control various sensors and recognize the surrounding work environment. As a solution to this, the heat treatment safety support system presented in this paper proposes a support system that can detect the access of the work manpower to the heat treatment furnace through thermal image detection and operate safely when ordering work from a remote location. In addition, an OPEN CV-based deterioration analysis system using DNN deep learning network was constructed for faster and more accurate recognition than general fixed hot spot monitoring-based thermal image analysis. Through this, we would like to propose a system that can be used universally in the heat treatment environment and support the safety management specialized in the heat treatment industry.

• Journal of Internet of Things and Convergence
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• v.8 no.6
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• pp.55-63
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• 2022

In recent years, with the rapid development of large and medium-sized urban rail transit in China, the total operating mileage of high-speed railway and the total number of EMUs(Electric Multiple Units) are rising. The system complexity of high-speed EMU is constantly increasing, which puts forward higher requirements for the safety of equipment and the efficiency of maintenance.At present, the maintenance mode of high-speed EMU in China still adopts the post maintenance method based on planned maintenance and fault maintenance, which leads to insufficient or excessive maintenance, reduces the efficiency of equipment fault handling, and increases the maintenance cost. Based on the intelligent operation and maintenance technology of PHM(prognostics and health management). This thesis builds an integrated PHM platform of "vehicle system-communication system-ground system" by integrating multi-source heterogeneous data of different scenarios of high-speed EMU, and combines the equipment fault mechanism with artificial intelligence algorithms to build a fault prediction model for traction motors of high-speed EMU.Reliable fault prediction and accurate maintenance shall be carried out in advance to ensure safe and efficient operation of high-speed EMU.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.297-304
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• 2021

This study aims not only to access the visual thought-oriented approach that has been implemented in established art therapy and education but also to integrate language education and therapeutic approach to support the development of school-age children. Thus, text mining technique was applied to search for areas where different areas of language and art can be integrated. This research was conducted in accordance with the procedure of basic research, preliminary DB construction, text screening, DB pre-processing and confirmation, stop-words removing, text mining analysis and the deduction about the convergent areas. These results demonstrated that this study draws convergence areas related to regional, communication, and learning functions, areas related to problem solving and sensory organs, areas related to art and intelligence, areas related to information and communication, areas related to home and disability, topics, conceptualization, peer-related areas, integration, reorganization, attitudes. In conclusion, this study is meaningful in that it established a framework for designing an activity-centered convergence program of art and language in the future and attempted a holistic approach to support child development.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.1
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• pp.1-8
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• 2021

In the political field of news articles, there are polarized and biased characteristics such as conservative and liberal, which is called political bias. We constructed keyword-based dataset to classify bias of news articles. Most embedding researches represent a sentence with sequence of morphemes. In our work, we expect that the number of unknown tokens will be reduced if the sentences are constituted by subwords that are segmented by the language model. We propose a document embedding model with subword tokenization and apply this model to SVM and feedforward neural network structure to classify the political bias. As a result of comparing the performance of the document embedding model with morphological analysis, the document embedding model with subwords showed the highest accuracy at 78.22%. It was confirmed that the number of unknown tokens was reduced by subword tokenization. Using the best performance embedding model in our bias classification task, we extract the keywords based on politicians. The bias of keywords was verified by the average similarity with the vector of politicians from each political tendency.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.5
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• pp.31-39
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• 2018

Recently, there has been active studies to provide a user-friendly interface in a virtual reality environment by recognizing user hand gestures based on deep learning. However, most studies use separate sensors to obtain hand information or go through pre-process for efficient learning. It also fails to take into account changes in the external environment, such as changes in lighting or some of its hands being obscured. This paper proposes a hand gesture recognition method based on deep learning that is strong in external environments without the need for pre-process of RGB images obtained from general webcam. In this paper we improve the VGGNet and the GoogLeNet structures and compared the performance of each structure. The VGGNet and the GoogLeNet structures presented in this paper showed a recognition rate of 93.88% and 93.75%, respectively, based on data containing dim, partially obscured, or partially out-of-sight hand images. In terms of memory and speed, the GoogLeNet used about 3 times less memory than the VGGNet, and its processing speed was 10 times better. The results of this paper can be processed in real-time and used as a hand gesture interface in various areas such as games, education, and medical services in a virtual reality environment.

• 한국사회정책
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• v.20 no.3
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• pp.141-170
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• 2013

The purpose of this study is to find out the relationship among the degree to provide emotional labor, personal relationship and the intent to stay of female care service workers. Specifically, this study focuses on the mediating effect of the personal relationship (client and agency relation). The path analysis and structural equation modeling analysis were performed on the collected data using SPSS18.0. and AMOS 8.0. And Sobel test conducted for examine the mediating effect. The results are the followings. First, the result of the analysis showed that agency relationship was an indirect factor as the partial mediating effect on relationship between the degree to provide emotional labor and the intent to stay for the care women workers. The result suggests that education utilizing various techniques and strategies to overcome the difficulty accompanied by emotional labor such as communication education and the government try to effort managing and controlling the agency which impact on the labor condition of care workers. Second, the government also tries to provide the trust and collaboration network system which construct a good relationship between the care worker and the agency.