• Journal of the Korean Society for information Management
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• v.35 no.4
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• pp.141-164
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• 2018

Recently, as the amount of academic literature has increased rapidly and complex researches have been actively conducted, researchers have difficulty in analyzing trends in previous research. In order to solve this problem, it is necessary to classify information in units of academic papers. However, in Korea, there is no academic database in which such information is provided. In this paper, we propose an automatic classification system that can classify domestic academic literature into multiple classes. To this end, first, academic documents in the technical science field described in Korean were collected and mapped according to class 600 of the DDC by using K-Means clustering technique to construct a learning set capable of multiple classification. As a result of the construction of the training set, 63,915 documents in the Korean technical science field were established except for the values in which metadata does not exist. Using this training set, we implemented and learned the automatic classification engine of academic documents based on deep learning. Experimental results obtained by hand-built experimental set-up showed 78.32% accuracy and 72.45% F1 performance for multiple classification.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.266-274
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• 2021

Ship officers are subject to excessive job stress, which has negative physical and psychological impacts and may adversely affect the smooth supply and demand of human resources. In this study, a mobile web application was developed as a tool for systematic job stress measurement and management of officers and verified through quality evaluation. Requirement analysis was performed by ship officers and staff in charge of human resources of shipping companies, and the results were reflected in the application configuration step. The application was designed according to the waterfall model, which is a traditional software development method, and functions were implemented using JSP and Spring Framework. Performance evaluation on the user interface, confirmed that proper input and output results were implemented, and the respondent results and the database were configured in the administrator interface. The results of evaluation questionnaires for quality evaluation of the interface based on ISO/IEC 9126-2 metric were significant 4.60 for the user interface and 4.65 for the administrator interface in a 5-point scale. In the future, it is necessary to conduct follow-up research on the development of data analysis system through utilization of the collected big-data sets.

• Journal of Korea Water Resources Association
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• v.54 no.10
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• pp.795-805
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• 2021

In this study, after developing an LSTM-based deep learning model for estimating daily runoff in the Soyang River Dam basin, the accuracy of the model for various combinations of model structure and input data was investigated. A model was built based on the database consisting of average daily precipitation, average daily temperature, average daily wind speed (input up to here), and daily average flow rate (output) during the first 12 years (1997.1.1-2008.12.31). The Nash-Sutcliffe Model Efficiency Coefficient (NSE) and RMSE were examined for validation using the flow discharge data of the later 12 years (2009.1.1-2020.12.31). The combination that showed the highest accuracy was the case in which all possible input data (12 years of daily precipitation, weather temperature, wind speed) were used on the LSTM model structure with 64 hidden units. The NSE and RMSE of the verification period were 0.862 and 76.8 m³/s, respectively. When the number of hidden units of LSTM exceeds 500, the performance degradation of the model due to overfitting begins to appear, and when the number of hidden units exceeds 1000, the overfitting problem becomes prominent. A model with very high performance (NSE=0.8~0.84) could be obtained when only 12 years of daily precipitation was used for model training. A model with reasonably high performance (NSE=0.63-0.85) when only one year of input data was used for model training. In particular, an accurate model (NSE=0.85) could be obtained if the one year of training data contains a wide magnitude of flow events such as extreme flow and droughts as well as normal events. If the training data includes both the normal and extreme flow rates, input data that is longer than 5 years did not significantly improve the model performance.

• Korean Journal of Construction Engineering and Management
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• v.3 no.3 s.11
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• pp.49-57
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• 2002

This paper describes the second stage of the work aiming at proposing a reasonable risk management response system for construction safety. By means of questionnaires/interviews and two sample t-tests, significant risk factors are identified for three different conditions. Then a Case-Based Reasoning System is built for use at construction sites to simulate possible accidents. This Construction Management Reasoning System(CMRS) nay be used by safety managers at sites every day (or education and training of workers to prevent accidents. The case base built so far is limited to the construction of expressway bridges. There is much need for further research since the simulation of possible accidents is to be a good means to enhance safety awareness of construction workers.

• Research in Community and Public Health Nursing
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• v.13 no.4
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• pp.795-807
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• 2002

Objectives: The purpose of this study was to develop a community-based nursing center model that can provide health promotion for infants and toddlers as well as a research and practice site for nursing faculty and students. Methods: Review of current health care system and health promotion programs, and workshops with brain-storming were carried out to identify needy areas of services to be provided by the nursing center. Finally, the community nursing center model was developed through expert consultation and filed visits. Results: The services and programs were developed for infants and toddlers residing in Seoul area. These services and programs include growth and developmental screening, environment and health problem assessment, infant stimulation and parent education, and self-help group. Full-time and part-time staff nurses and nurse practitioners will provide those services and offer home visiting if needed. Database system, health information system, and trainers' training programs were developed as well. Conclusion: The nursing center model developed in this study will ensure clients direct access to nursing care and increase of autonomy and accountability of nursing practices. The nursing center model focused on disease prevention and health promotion will enhance the quality of life of the infants, toddlers and their families as well as to decrease national health care expenditure.

• Journal of Agricultural Extension & Community Development
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• v.15 no.3
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• pp.461-497
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• 2008

The objective of the study was to evaluate the impact of the Call System of agricultural extension services in Korea. The respondents were satisfied on the speedy solution (74.5%), consultation (88.4%), and accessibility (79.7%) of the call system. However, satisfaction of farmers on in-depth consultation was higher (74.3%) than the satisfaction rated by the public servants of RDA (48.9%). Both groups replied positively (70.4%) on the need for expansion of the call system. The analyses of the results leads to a conclusion that there is a need to increase marketing on the importance of RDA's Call System to customers of agricultural extension and to improve accessibility through expansion of the system in other areas. These could solve the decreasing number of extension professionals and improve the quality and efficiency of extension services. These analyses may be useful as bases for a nationwide Call System that connects the center with other districts and for planning a renovation of information-oriented agricultural extension services. The issue that needs improvement is to abandon the grounds of agricultural technology information provider and respond to the customers' needs efficiently by building an established Call System which can minimize the side effect of the trends of reforming and downsizing the organization. It is needed to develop a unified management Call System of agricultural technology information that could provide real-time information, and database the results simultaneously for use as feedback to the Rural Development Programs. Related laws and policies need to be improved to establish a nationwide information network that maximizes the current network in agricultural regions to spread information, to provide institutional support, and to encourage development of training system and research and development by concerned institutes.

• The Journal of the Acoustical Society of Korea
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• v.19 no.2
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• pp.90-94
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• 2000

In this paper, we propose an efficient method of estimating a critical threshold which is used to reject unreliable patterns in a HMM based recognition system. The rejection methods based on the anti-models which are formulated as the statistical hypothesis determine whether or not to accept an input pattern by comparing the likelihood ratio of HMM and anti-models to a critical threshold. It is quite difficult to fix a threshold for the probability of a HMM because the range of such probabilities varies severely depending on the chosen class model. We estimate the critical threshold, which is very class-dependent, using the likelihood scores for the training database. In our experiments, we applied the proposed estimating method of the threshold to the HMM based 3D hand gesture recognition system. We found that this method can be used successfully for rejecting unreliable input gestures regardless of the types of anti-models.

• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.484-491
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• 2015

Aerial scene is greatly increased by the introduction and supply of the image due to the growth of digital optical imaging technology and development of the UAV. It has been used as the extraction of ground properties, classification, change detection, image fusion and mapping based on the aerial image. In particular, in the image analysis and utilization of deep learning algorithm it has shown a new paradigm to overcome the limitation of the field of pattern recognition. This paper presents the possibility to apply a more wide range and various fields through the segmentation and classification of aerial scene based on the Deep learning(ConvNet). We build 4-classes image database consists of Road, Building, Yard, Forest total 3000. Each of the classes has a certain pattern, the results with feature vector map come out differently. Our system consists of feature extraction, classification and training. Feature extraction is built up of two layers based on ConvNet. And then, it is classified by using the Multilayer perceptron and Logistic regression, the algorithm as a classification process.

• Journal of the Korean Institute of Navigation
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• v.24 no.5
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• pp.343-360
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• 2000

The information technology(IT) development of telecommunication, along with the informationalization over the world, enables the firms to process their inner and outer operations through Electronic Data Interchange (EDI) system. And the concept of logistics has become more important to the enterprises in strategic sense because it had aggrandized itself to more comprehensive and integrative concept. Also the world shipping market is more competitive than any other market. In these environment, to maintain competitve power, shipping firms process operations by Logistics Information system(LIS), And then, reduce the working processes, working time and its costs. So the LIS has become more important in developing our national logistics system and industry. Therefore, this study purposes on empirically analyzing the activation factors of shipping LIS and the relationship these factors with logistic performances in the shipping industry. Considering environments of Shipping logistics information system, this study sets up the research model and hypothesis to examine the activation factors of shipping LIS and the relationship these factors with logistic performances. We used the field data on the 163 numbers of firms(29 overseas shipping companies and 133 forwarding Agency) to get the empirical evidence. According to the study results, The shipping LIS activation factors which the sample firms recognized as important: were top manager's support, well structured communication channel, strategic plan's connection and inner informationalization level. And IS organization ＆ human resources, IS discipline ＆ training, software development, IS organizational alignment, database management system, information standardization, competitive advantage, financial support and government support represent partially significant. Also, the current shipping LIS's main problems are expensive system cost, standardization of working process's, institution's imperfection and system's interaction defect. So these problems must be improved to activate shipping LIS.

• Journal of the Korean Society for Library and Information Science
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• v.50 no.4
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• pp.55-75
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• 2016

We analyzed the characteristics of the physicians preferred information sources and barriers through in-depth interviews. Information searches for patient treatment were subdivided into deciding patient treatment methods, understanding the latest treatment trends, and preparing presentation materials for conferences. The variables that affected the search behaviors were identified as being background knowledge on the topic, clinical experience, job title, search skills, user training, and familiarity with the library homepage. PubMed was the most preferred choice because of users' familiarity, reliability, and the vastness of information; Google was also used frequently for easy access and fast search result. The accuracy and the recentness of information were the most significant criteria. Easy interface and convenient access were also considered important due to physicians' time constraints. Searching obstacles were divided into difficulty of searching system, unfamiliar term, too vast resources, difficulty to get fulltext articles and complex advanced search features. The results of this study can be utilized as a basis for improving information service of library and curriculum development for physicians.