• 한국비블리아학회지
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• 제24권1호
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• pp.25-44
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• 2013

본 연구는 1986년부터 2011년까지 한국문헌정보학회지, 한국도서관 정보학회지, 정보관리학회지, 한국비블리아학회지, 서지학연구에 실린 논문 205편을 대상으로 분류에 관한 국내 연구 동향을 분석하였다. 이를 위해 하위주제, 연구방법, 자료수집 및 분석방법의 측면에서 개별 논문들을 분석하고 분류 관련 연구의 특성들을 도출하였다. 그 결과 논문의 양은 점차 증가하는 양상으로, 활용에 초점이 맞추어져 있었으며, 새로운 분류 방안을 제안하거나 기존 분류체계의 수정전개방안을 제안하는 형태의 논문들이 대부분이었고, 이러한 경우 문헌연구를 활용한 분류체계 비교연구가 압도적으로 많았다. 연구자 측면에서 교수와 강사, 학생은 문헌연구를 선호하였으나 연구원은 주로 사례연구와 시스템 분석/설계방법을 활용하였다. 가장 높은 생산성을 보인 저자 9명은 교수나 강사였고, 소수의 타학문분야 기반 저자들은 대부분이 컴퓨터학 전공자들이었다. 이와 같은 결과는 분류 관련 연구에 다양한 연구주제에 대한 접근, 연구방법의 다양한 시도, 타학문분야와의 연계가 보다 더 필요함을 보여주는 것이다.

• Earthquakes and Structures
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• 제15권1호
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• pp.1-8
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• 2018

A new site classification system and site coefficients based on local site conditions in Korea were developed and implemented as a part of minimum design load requirements for general seismic design. The new site classification system adopted bedrock depth and average shear wave velocity of soil above the bedrock as parameters for site classification. These code provisions were passed through a public hearing process before it was enacted. The public hearing process recommended to modify the naming of site classes and adjust the amplification factors so that the level of short-period amplification is suitable for economical seismic design. In this paper, the new code provisions were assessed using dynamic centrifuge tests and by comparing the design response spectra (DRS) with records from 2016 Gyeongju earthquake, the largest earthquake in history of instrumental seismic observation in Korea. The dynamic centrifuge tests were performed to simulate the representative Korean site conditions, such as shallow depth to bedrock and short-period amplification characteristics, and the results corroborated with the new DRS. The Gyeongju earthquake records also showed good agreement with the DRS. In summary, the new code provisions are reliable for representing the site amplification characteristic of shallow bedrock condition in Korea.

• 대한지구과학교육학회지
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• 제4권2호
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• pp.151-165
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• 2011

Following a microgenetic design, this study was analysed the characteristic and the change of classification strategy that appear in college students' classification activity. The 4 tasks were developed for classification activity; a shell as a familiar real things, an animal fossil as a unfamiliar real things, a snow flake as a familiar picture cards and galaxy as a unfamiliar picture card. Achieved study to 6 college students who major in elementary education. Data were collected by interview with subjects, subject's classification schema, investigator's observation of subject's activity, and videotaped that record subject's subject classification process over an extended period of 6 times. Result proved in this study is as following. In the 6 times of the data collection procedures, a strategy F identifying concrete attribution of classification objects and a more detailed strategy X3 combining qualitative, spatial and dimensional attribution were found and more frequently used in both groups of college students which reported a classification process and did not report the process. While discovery and absorption of both a concrete classification strategy and a detailed classification strategy were rapidly developed in the reporting group, they were gradually developed in the non-reporting group. In addition to this, as the data collection procedures were progressing, the college students were familiar with change factors of classification tasks and in the case of pictures the classification strategy showed more desirable changes.

• 디지털산업정보학회논문지
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• 제15권4호
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• pp.197-212
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• 2019

The purpose of this study is to identify the maturity stages of venture firms through classification analysis, which is widely used as a big data technique. Venture companies should develop a competitive advantage in the market. And the maturity stage of a company can be classified into five stages. I will analyze a difference in the growth stage of venture firms between the survey response and the statistical classification methods. The firm growth level distinguished five stages and was divided into the period of start-up and declines. A classification method of big data uses popularly k-mean cluster analysis, hierarchical cluster analysis, artificial neural network, and decision tree analysis. I used variables that asset increase, capital increase, sales increase, operating profit increase, R&D investment increase, operation period and retirement number. The research results, each big data analysis technique showed a large difference of samples sized in the group. In particular, the decision tree and neural networks' methods were classified as three groups rather than five groups. The groups size of all classification analysis was all different by the big data analysis methods. Furthermore, according to the variables' selection and the sample size may be dissimilar results. Also, each classed group showed a number of competitive differences. The research implication is that an analysts need to interpret statistics through management theory in order to interpret classification of big data results correctly. In addition, the choice of classification analysis should be determined by considering not only management theory but also practical experience. Finally, the growth of venture firms needs to be examined by time-series analysis and closely monitored by individual firms. And, future research will need to include significant variables of the company's maturity stages.

• 한국도서관정보학회지
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• 제36권2호
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• pp.165-178
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• 2005

본 연구는 대학도서관의 단행본에 대한 분류검색 환경을 조사${\cdot}$분석함으로써, 그 실태를 파악하기 위한 것이다. 조사내용은 분류검색 제공여부, 접근방법, 검색수준 등에 중점을 두었다. 데이터 수집은 계통추출법에 의해 표집된 100개 도서관 중, 조사기간 동안 URL 연결이 가능한 97개 도서관을 대상으로 이루어졌다. 그 결과, 97개 도서관 중, $92.8\%$가 분류검색을 제공하고 있었으나, 이중 $52.2\%$가 분류기호만을 통해, $47.8\%$가 분류기호와 분류 디렉터리를 통해 접근이 가능한 것으로 나타났다. 따라서, 분류검색을 활성화하기 위해서는 분류기호만을 통해 접근이 가능한 도서관에 대한 검색환경 개선이 시급한 것으로 파악되었다.

• 아시안잔디학회지
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• 제2권1호
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• pp.59-64
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• 1988

This study was carried out to investigate the classification and the growing charicteristics of weed species in a newly formed lawngrass land. The results obtained are summarized as follows: 1)Weed population in a newly formed lawn field consisted of 30% of Gramineae, 15% of Compositae, and 12% of Leguminosae family. 2)Percentage of weed emergence between April and May was 39.4%. The same amount of weed emergence was observed at the period of September and October, where as the percentage was 21.2% at the period of March and April. 3)The population ratio of flowering date of weed species was in order of 48.5% July and August, 30.3% in May and July, 12.1% in March and April, and 9.1% in September and October. 4)Weed classification by life cycle showed 39.4% of biennials, 33.3% of annuals, and 27.3% of perennials. 5)Weed species were grouped according to the plant height. The ratios of each group were 33.3% of 20~40cm group, 27.3% of 40~60cm group, 24.2% of shorter than 20cm group, and 15.2% of taller than 60cm group.

• Journal of Astronomy and Space Sciences
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• 제20권2호
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• pp.101-108
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• 2003

This study reports one approach for the classification of magnetic storms into recurrent patterns. A storm event is defined as a local minimum of Dst index. The analysis of Dst index for the period of year 1957 through year 2000 has demonstrated that a large portion of the storm events can be classified into a set of recurrent patterns. In our approach, the classification is performed by seeking a categorization that minimizes thermodynamic free energy which is defined as the sum of classification errors and entropy. The error is calculated as the squared sum of the value differences between events. The classification depends on the noise parameter T that represents the strength of the intrinsic error in the observation and classification process. The classification results would be applicable in space weather forecasting.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제3권3호
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• pp.285-307
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• 2009

This paper introduces DICE, a Domain-Independent text Classification Engine. DICE is robust, efficient, and domain-independent in terms of software and architecture. Each module of the system is clearly modularized and encapsulated for extensibility. The clear modular architecture allows for simple and continuous verification and facilitates changes in multiple cycles, even after its major development period is complete. Those who want to make use of DICE can easily implement their ideas on this test bed and optimize it for a particular domain by simply adjusting the configuration file. Unlike other publically available tool kits or development environments targeted at general purpose classification models, DICE specializes in text classification with a number of useful functions specific to it. This paper focuses on the ways to locate the optimal states of a practical text classification framework by using various adaptation methods provided by the system such as feature selection, lemmatization, and classification models.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2005년도 지반공학 공동 학술발표회
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• pp.154-162
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• 2005

In this paper, site response analyses were performed based on equivalent linear technique using the shear wave velocity profiles of 162 sites collected around the Korean peninsula. The site characteristics, particularly the shear wave velocities and the depth to the bedrock, are compared to those in the western United States. The results show that the site-response coefficients based on the mean shear velocity of the top 30m ($V_{S30}$) suggested in the current code underestimates the motion in short-period ranges and overestimates the motion in mid-period ranges. Also the current Korean code based on UBC is required to be modified considering site characteristics in Korea for the reliable estimation of site amplification. From the results of numerical estimations, new regression curves were derived between site coefficients ($F_a$ and $F_v$) and the fundamental site periods, and site coefficients were grouped based on site periods in the regions of shallow bedrock. The standard deviations of the proposed method was reasonable compared to site classification based on $V_{S30}$. Finally, new site classification system is recommended based on site periods for regions of shallow bedrock depth in Korea.

• 대기
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• 제16권3호
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• pp.235-246
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• 2006

Remote sensing techniques using satellites or the scanning weather radars depend mostly on the presence of clouds or precipitation, and leave the extensive regions of clear air unobserved. But wind profilers provide the most direct measurements of mesoscale vertical air motion in the troposphere, even in the context of heavy precipitation. In this paper, the precipitation events during the Changma period was classified into 4 precipitation types - stratiform, mixed stratiform/ convective, deep convective, and shallow convective. The parameters for the classification of analysis are the vertical structure of reflectivity, Doppler velocity, and spectral width measured with the wind profiler at Haenam for a three-year period (2003-2005). In addition, the synoptic fields and total amount of precipitation were analyzed using the Global Final Analyses (FNL) data and the Global Precipitation Climatology Project (GPCP) data. During the Changma period, the results show that the stratiform type was dominant under the moist-neutral atmosphere in 2003, whereas the deep convective type was under the moist unstable condition in 2004. The stratiform type was no less popular than the deep convective type among four seasons because the moist neutral layer was formed by the convergence between the upper-level jet and the low-level jet, and by the moisture transport along the western rim of the North Pacific subtropical anticyclone.