• Korean Journal of Remote Sensing
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• v.33 no.2
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• pp.189-199
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• 2017

Thisstudy quantitatively analyzed the research trendsin the use ofICT ofthe environmental field using the text mining technique. To that end, the study collected 359 papers published in the past two decades(1996-2015)from the National Digital Science Library (NDSL) using 38 environment-related keywords and 16 ICT-related keywords. It processed the natural languages of the environment and ICT fields in the papers and reorganized the classification system into the unit of corpus. It conducted the text mining analysis techniques of frequency analysis, keyword analysis and the association rule analysis of keywords, based on the above-mentioned keywords of the classification system. As a result, the frequency of the keywords of 'general environment' and 'climate' accounted for 77 % of the total proportion and the keywords of 'public convergence service' and 'industrial convergence service' in the ICT field took up approximately 30 % of the total proportion. According to the time series analysis, the researches using ICT in the environmental field rapidly increased over the past 5 years (2011-2015) and the number of such researches more than doubled compared to the past (1996-2010). Based on the environmental field with generated association rules among the keywords, it was identified that the keyword 'general environment' was using 16 ICT-based technologies and 'climate' was using 14 ICT-based technologies.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.1
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• pp.113-126
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• 2017

This study aimed to quantitatively analyze the trends in environmental research that utilize environmental geospatial information through text mining, one of the big data analysis technologies. The analysis was conducted on a total of 869 papers published in the Republic of Korea, which were collected from the National Digital Science Library (NDSL). On the basis of the classification scheme, the keywords extracted from the papers were recategorized into 10 environmental fields including "general environment", "climate", "air quality", and 20 environmental geospatial information fields including "satellite image", "numerical map", and "disaster". With the recategorized keywords, their frequency levels and time series changes in the collected papers were analyzed, as well as the association rules between keywords. First, the results of frequency analysis showed that "general environment"(40.85%) and "satellite image"(24.87%) had the highest frequency levels among environmental fields and environmental geospatial information fields, respectively. Second, the results of the time series analysis on environmental fields showed that the share of "climate" between 1996 and 2000 was high, but since 2001, that of "general environment" has increased. In terms of environmental geospatial information fields, the demand for "satellite image" was highest throughout the period analyzed, and its utilization share has also gradually increased. Third, a total of 80 correlation rules were generated for environmental fields and environmental geospatial information fields. Among environmental fields, "general environment" generated the highest number of correlation rules (17) with environmental geospatial information fields such as "satellite image" and "digital map".

• Knowledge Management Research
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• v.21 no.4
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• pp.129-156
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• 2020

The sharing economy is recognized as a new economic system based on the digital service platform, but the sharing economy has yet to be established in Korea due to a lack of social awareness and understanding. There is a need to enhance understanding and awareness of the sharing economy in positive perspective in order to make up business with advanced economies global and explore new markets. In this study, after collecting papers of the sharing economy over the past decade published by each academic field around the world, we reviewed them from academic lens and conducted a comprehensive analysis using meta analysis methodology. Then, we selected papers of MIS field and analyzed the trends of the MIS field research in these papers. As a result we identified the research trend of the sharing economy and the MIS research and drew the necessity of interdisciplinary research between the two studies by examining importance and relevance of MIS research in the sharing economy research. Therefore, we expect that this study contributes to promote interdisciplinary research with neighboring disciplines and to establish a positive social, economical and industrial position in Korea.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.2 s.48
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• pp.39-50
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• 2006

Site response analyses were peformed based on equivalent linear technique using the shear wave velocity profiles of 162 sites collected around the Korean Peninsula. The she characteristics, particularly the shear wave velocities and the depth to bedrock, are compared to those in the western United States. The site coefficients of short period $(F_a)$ and the long period $(F_v)$ obtained from this study were significantly different compared to 1997 Uniform Building Code (1997 UBC). $F_a$ underestimated the motion in shot period ranges and $F_v$ overestimated the motion in mid period ranges in Korean seismic guideline. It is found that the existing Korean seismic design code were is required to be modified considering geological site conditions in Korea for the reliable estimation of sue amplification. Problems of the current seismic design code were dicussed in this paper and the development of site classification method and modification of desing response spectra were discussed in the companion papers(II-Development of Site Classification System and III-Modification of Dosing Response Specra).

• Journal of the Korean Society for Library and Information Science
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• v.48 no.3
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• pp.491-510
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• 2014

As a major factor for efficient management and retrieval of the articles in databases, keywords are classified into uncontrolled keywords and controlled keywords. Most of Korean scholarly databases fail to provide controlled vocabularies to indexing research articles which help users to retrieve relevant papers exhaustively. In this paper, we carried out automatic descriptor assignment experiments to Korean articles using automatic classifiers learned with descriptors in international database. The results of the experiments show that the classifier learning with descriptors in international database can potentially offer controlled vocabularies to Korean scholarly articles having English s. Also, we sought to improve the performance of automatic descriptor assignment using various classifiers and combination of them.

• Journal of Information Technology Services
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• v.19 no.4
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• pp.49-61
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• 2020

Prior studies on technology predictions attempted to predict the emergence and spread of emerging technologies through the analysis of correlations and changes between data using objective data such as patents and research papers. Most of the previous studies predicted future technologies only from the viewpoint of technology development. Therefore, this study intends to conduct technical forecasting from the perspective of the consumer by using keyword search frequency of search portals such as NAVER before and after the introduction of emerging technologies. In this study, we analyzed healthcare technologies into three types : measurement technology, platform technology, and remote service technology. And for the keyword analysis on the healthcare, we converted the classification of technology perspective into the keyword classification of consumer perspective. (Blood pressure and blood sugar, healthcare diagnosis, appointment and prescription, and remote diagnosis and prescription) Naver Trend is used to analyze keyword trends from a consumer perspective. We also used the ARIMA model as a technology prediction model. Analyzing the search frequency (Naver trend) over 44 months, the final ARIMA models that can predict three types of healthcare technology keyword trends were estimated as "ARIMA (1,2,1) (1,0,0)", "ARIMA (0,1,0) (1,0,0)", "ARIMA (1,1,0) (0,0,0)". In addition, it was confirmed that the values predicted by the time series prediction model and the actual values for 44 months were moving in almost similar patterns in all intervals. Therefore, we can confirm that this time series prediction model for healthcare technology is very suitable.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.617-620
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• 2017

The periodic monitoring of crop conditions and timely estimation of crop yield are of great importance for supporting agricultural decision-makings, as well as for effectively coping with food security issues. Remote sensing has been regarded as one of effective tools for crop condition monitoring and crop type classification. Since 2010, RDA (Rural Development Administration) has been developing technology for monitoring on crop condition using remote sensing and model. These special papers address recent state-of-the-art of remote sensing and geospatial technologies for providing operational agricultural information, such as, crop yield estimation methods using remote sensing data and process-oriented model, crop classification algorithm, monitoring and prediction of weather and climate based on remote sensing data,system design and architecture of crop monitoring system, history on rice yield forecasting method.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.12
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• pp.635-640
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• 2016

It is important factors for a production system to get a profitable result in quality and reliability process. For this reason, there's are various type of research papers in a certain type of data acquisition and application to reliability and quality of the level of M2M devices. In general, a classification problem of slightly different signal such as sensing data is difficult to do with classical statistical methods. There's required real-time and instantaneous calculation properties in machine process. Especially a type of injection molding machine which has a property to be decided in accordance with short-term cycle process needs a solution that can be done a certain type of decision like as good or bad quality immediately. This paper presents a simple application of Kalman Filtering by single sensing data to injection molding process in order to get a correct answer from the real time sensing data.

• Journal of Physiology & Pathology in Korean Medicine
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• v.30 no.2
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• pp.124-130
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• 2016

The aim of this study was to suggest the future direction of diagnostic and evaluative pattern identification questionnaire (PIQ) by reviewing the state of development and utilization of PIQ according to Korean classification of disease-U (KCD-U). We surveyed the database of OASIS, NDSL, KISS, DBPIA, and Pub-med to know the kinds of developed and developing PIQ of Korean medicine. We used 'Pattern Identification' and 'Questionnaire' to find suitable papers. The inclusion criteria met 47 cases. The number of PIQ before 2000yrs, between 2001 to 2005, 2006-2010, 2011-2015 were 2, 5, 18, 22cases. The number of PIQ belonged to the disease of Korean medicine, the pathological symptom of korean medicine, the Sasang constitutional pattern identification and etc according to KCD-U were 20(42.6%), 8(17%), 9(19.1%) and 10(21.3%). Twenties among forty seven PIQ were validated, and the rest of them were not validated. The distribution of the numbers of PIQ were significantly different according to KCD-U (p=0.003). The direction of Utilization of PIQ was 36 questionnaires in diagnosing PI, 14 cases in evaluating health state, 4cases in evaluating effects of a treatment and 8 ones in diagnosing Sasang constitutional types. This study reveals the status on validated and non-validated PIQ of Korean medicine and suggests the basic information for the direction of developing PIQ in the future.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.245-258
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• 2016

This paper aims to present the way to bring about significant results through performance improvement of learning algorithm in the research applying to machine learning. Research papers showing the results from machine learning methods were collected as data for this case study. In addition, suitable machine learning methods for each field were selected and suggested in this paper. As a result, SVM for engineering, decision-making tree algorithm for medical science, and SVM for other fields showed their efficiency in terms of their frequent use cases and classification/prediction. By analyzing cases of machine learning application, general characterization of application plans is drawn. Machine learning application has three steps: (1) data collection; (2) data learning through algorithm; and (3) significance test on algorithm. Performance is improved in each step by combining algorithm. Ways of performance improvement are classified as multiple machine learning structure modeling, $+{\alpha}$ machine learning structure modeling, and so forth.