• 한국지구과학회지
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• 제40권5호
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• pp.487-501
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• 2019

In this study, steric height variability in the East Asian Seas (EAS) has been analyzed by using ocean reanalysis intercomparison project (ORA-IP) data. Results show that there are significant correlations between ocean reanalysis and satellite data except the phase of annual cycle and interannual signals of the Yellow Sea. Reanalysis ensemble derived from 15-different assimilation systems depicts higher correlation (0.706) than objective analysis ensemble (0.296) in the EAS. This correlation coefficient is also much higher than that of the global ocean (0.441). For the long-term variability of the thermosteric sea level during 1993-2010, a significant warming trend is found in the East/Japan Sea, while cooling trend is shown around the Kuroshio extension area. For the halosteric sea level, a dominant freshening trend is found in the EAS. However, below 300 m depth around this area, the signal-to-noise ratio of the linear trend is generally less than one, which is related to the low density of observation data.

• 한국농공학회지
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• 제19권3호
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• pp.4472-4482
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• 1977

In order to estimate furture consumtive use, some statistical characteristics of 22-year pan evaporation data at four selected stations were calculated in this study. Districal distribution, trend analysis and time-series, statistical and periodic analysis for annual, monethly and ten-day values were performed in the statistical analysis. The stations are Seoul, Taeku, Jeonju and Mokpo for monthly data, and Suweon data are compared to the reported Penman values. The results are as followed: 1. Annual evaporation ranged to 990-1,375mm varying with the locations of the stations. The Districal distribution of evaporation in the Republic is shown in Fig. 1. 2. The trend analysis for annual evaporation resulted in detail in Table 2 and Fig. 2, through simple moving average methods. The results show relatively short-period data of about 10 years would be acceptable for field use. 3. The means and dispersions of monthly evaporation at four stations are detailed in Table 3. 4. The monthly evaporation approached to the trend of normal distribution Fig. 3 showed the examples of normal distribution for each typical monthly data. 5. The correlograms detailed in Fig. 4, shows the time-series characteristics of monthly evaporation, whose periodic term should be twelve months. 6. The periodic analysis for monthly evapolation results in Table 4. Fig. 5 shows the comparison of estimated values to actual and the trend approaches Shuster's periodic trend. 7. A periodic description of days after March 1 for irrigation periods was developed to predict ten-day evaporation in Fig. 6. The ten-day etraporation is different in the distribution form and occurence period of maximum values from the reported Penman's man's evapotranspiration.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2017년도 학술발표회
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• pp.424-424
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• 2017

Several studies of the world have analyzed the regional rainfall trends in large data sets. However, it reported that the long-term behavior of rainfall was different on spatial and temporal scales. The objective of this study is to determine the local trends of rainfall indices in the Yom River Basin, Thailand. The rainfall indices consist of the annual total precipitation (PRCTPOP), number of heavy rainfall days ($R_{10}$), number of very heavy rainfall days ($R_{20}$), consecutive of dry days (CDD), consecutive of wet days (CWD), daily maximum rainfall ($R_{x1}$), five-days maximum rainfall ($R_{x5}$), and total of annual rainy day ($R_{annual}$). The rainfall data from twelve hydrological stations during the period 1965-2015 were used to analysis rainfall trend. The Mann-Kendall test, which is non-parametric test was adopted to detect trend at 95 percent confident level. The results of these data were found that there is only one station an increasing significantly trend in PRCTPOP index. CWD, which the index is expresses longest annual wet days, was exhibited significant negative trend in three locations. Meanwhile, the significant positive trend of CDD that represents longest annual dry spell was exhibited four locations. Three out of thirteen stations had significant decreasing trend in $R_{annual}$ index. In contrast, there is a station statistically significant increasing trend. The analysis of $R_{x1}$ was showed a station significant decreasing trend at located in the middle of basin, while the $R_{x5}$ of the most locations an insignificant decreasing trend. The heavy rainfall index indicated significant decreasing trend in two rainfall stations, whereas was not notice the increase or decrease trends in very heavy rainfall index. The results of this study suggest that the trend signal in the Yom River Basin in the half twentieth century showed the decreasing tendency in both of intensity and frequency of rainfall.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2000년도 추계학술발표논문집
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• pp.299-306
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• 2000

General definition of data mining is the knowledge discovery or is to extract hidden necessary information from large databases. Its technique can be applied into decision making, prediction, and information analysis through analyzing of relationship and pattern among data. One of the most important work is to find association rules in data mining. The objective of this paper is to find customer's trend using association rule from analysis of database and the result can be used as fundamental data for CRM(Customer Relationship Management). This paper uses Apriori algorithm and FoodMart data in order to find association rules.

• 융합보안논문지
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• 제8권2호
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• pp.35-40
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• 2008

소트프웨어 고장 시간은 테스팅 시간과 관계없이 일정하거나, 단조 증가 혹은 단조 감소 추세를 가지고 있다. 이러한 소프트웨어 신뢰모형들을 분석하기 위한 자료척도로 자료에 대한 추세 검정이 개발되어 있다. 추세 분석에는 산술평균 검정과 라플라스 추세 검정 등이 있다. 추세분석들은 전체적인 자료의 개요의 정보만 제공한다. 본 논문에서는 고장시간을 측정하다가 시간절단이 될 경우에 미래의 고장 시간 예측에 관하여 연구되었다. 고장 시간 예측에 사용된 고장시간자료는 소프트웨어 고장 시간 분포에 널리 사용되는 와이블 분포에서 형상모수가 1이고 척도모수가 0.5를 가진 난수를 발생된 모의 자료를 이용 하였다. 이 자료를 이용하여 시계열 분석에 이용되는 ARIMA 모형 중에서 AR(1) 모형과 모의실험을 통한 예측 방법을 제안하였다. 이 방법에서 ARIMA 모형을 이용한 예측방법이 효율적임을 입증 하였다.

• 한국실내디자인학회논문집
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• 제15권6호
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• pp.238-246
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• 2006

Recent trends of interior design have a focus on creation of more various meanings rather than past ideology which sought after the compatibility to the function of modem design. These trends requires integral understanding of social and cultural ideologies with a sens of values for a certain periods. In addition, they also require creativity which able to read, find and solve consumer's diverse demand and desire. Considering the effort of trend forecasting in Korea is still heavily rely on the foreign trend shows, it is natural to attempt to study the analytical forecasting methodology based upon more systematic principles which lead to more objective outcome, when the understanding, forcasting and analysis of interior decoration trend are required. In this thesis, the analysis and forecasting of interior decoration trend are studied by means of verbal image code process which involves the induction of design concept through data extraction, classification and analysis, in order to understanding and satisfying the diversified consumer's demand and trend. The coding process of verbal image is understanding as general concept. by extracting common elements from abstract and individual image, and/or specific concept. Therefore, it is proposed that the database building and data mining process of verbal Image, and subsequent development of programming skill can be applied as more efficient tool for various verbal image process.

• 노동경제논집
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• 제32권2호
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• pp.95-124
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• 2009

본 연구는 외환위기 이후 상장제조기업의 생산성 추이 및 교육훈련효과를 분석하였다. 분석 결과, 외환위기 이후 상장제조기업은 시간이 흐를수록 저 생산성 국면에 빠지게 되었으며, 그 과정에서 상장제조기업의 고용 없는 성장, 물적 투자 없는 성장, 인적자본투자 없는 성장 현상이 관찰되었다. 그리고 생산성이 높은 기업의 고용비중이 늘고, 낮은 기업의 고용비중이 주는 효율적인 노동시장이 거의 작동하지 않았다. 또한 교육훈련이 생산성에 미치는 영향을 분석해 보기 위해 동적 패널 분석을 실시할 경우 교육훈련의 과소투자가 발생하고 있음에도 불구하고 교육훈련의 생산성에 대한 지나치게 높은 긍정적 효과가 나타나는 모순적 현상이 상당 부분 해결되었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권8호
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• pp.4133-4145
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• 2017

Advances in science and technology are driving us to the better life but also forcing us to make more investment at the same time. Therefore, the government has provided the investment to carry on the promising futuristic technology successfully. Indeed, a lot of resources from the government have supported into the science and technology R&D projects for several decades. However, the performance of the public investments remains unclear in many ways, so thus it is required that planning and evaluation about the new investment should be on data driven decision with fact based evidence. In this regard, the government wanted to know the trend and issue of the science and technology with evidences, and has accumulated an amount of database about the science and technology such as research papers, patents, project reports, and R&D information. Nowadays, the database is supporting to various activities such as planning policy, budget allocation, and investment evaluation for the science and technology but the information quality is not reached to the expectation because of limitations of text mining to drill out the information from the unstructured data like the reports and papers. To solve the problem, this study proposes a practical text mining methodology for the science and technology trend analysis, in case of aerospace technology, and conduct text mining methods such as ontology development, topic analysis, network analysis and their visualization.

• 한국정보시스템학회지:정보시스템연구
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• 제30권3호
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• pp.201-216
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• 2021

Purpose The purpose of this study is to analyze the trend of patent technology in textile materials using text mining methodology based on Dynamic Embedded Topic Model and Structural Topic Model. It is expected that this study will have positive impact on revitalizing and developing textile materials industry as finding out technology trends. Design/methodology/approach The data used in this study is 866 domestic patent text data in textile material from 1974 to 2020. In order to analyze technology trends from various aspect, Dynamic Embedded Topic Model and Structural Topic Model mechanism were used. The word embedding technique used in DETM is the GloVe technique. For Stable learning of topic modeling, amortized variational inference was performed based on the Recurrent Neural Network. Findings As a result of this analysis, it was found that 'manufacture' topics had the largest share among the six topics. Keyword trend analysis found the fact that natural and nanotechnology have recently been attracting attention. The metadata analysis results showed that manufacture technologies could have a high probability of patent registration in entire time series, but the analysis results in recent years showed that the trend of elasticity and safety technology is increasing.

• 대한가정학회지
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• 제38권1호
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• pp.139-154
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• 2000

The purpose of this study was to identify the changes in transportation expenditure patterns of urban households during 1985-19o8. The data were drawn from 'Annual Report on the family Income and Expenditure Survey' by National Statistical Office, Republic of Korea. For data analysis, frequency, percentile, mean, and multiple regression analysis were utilized by the SAS window program. The results of this study were as follows; Frist, the levels of public transportation expenditure showed increasing trend, whereas the portions of public transportation expenditure have showed decreasing trend during 1985-1998. And both the level and the portion of private transportation expenditure showed increasing trends during 1985-1998. Second, the marginal propensities to consume of public transportation have decreased, whereas the marginal propensities to consume of private transportation have increased during 1985-1998. Third, income elasticities of public transportation showed decreasing trend during 1985-1998, impling that consumers have less demand public transportation with increasing income. And income elasticities of private transportation showed increasing trend till 1993, and then showed decreasing trend till 1998, impling that consumers have perceived the car as one of necessary goods rather than luxury goods gradually since 1993.