• Journal of Korean Society of Forest Science
• /
• v.102 no.4
• /
• pp.515-521
• /
• 2013

The objective of this study was to estimate the changes of stand structure before and after applying the three different silvicultural treatments such as selection cutting system, two-storied system, and shelterwood system. This study has been conducted in the natural deciduous forests in Pyeongchang of Gangwon Province, Korea. Nine permanent sampling plots of 0.09 ha were established in the forests and each of the three silvicultural treatments was applied to three sampling points. Some tree variables were measured in each stand before and after the silvicultural treatments were applied. With these data, stand attributes were estimated in each stand before and after applying the silvicultural treatments. In this study, a competition index was used to analyze the differences among structures of stands managed by three different silvicultural treatments. Hegyi's distance-dependent competition index was estimated and compared to analyze the differences of stand structures among the stands before and after silvicultural treatments. A method using a height angle $50^{\circ}$ from the base of the subject tree was adopted as the selection method of competitor trees. Duncan's multiple range test and t-test were then employed to statistically analyze the difference of stand structure among the stands. The results revealed that competition status among trees in the stand seems to be improved after applying the silvicultural treatments. There are significant differences in the competition index between before and after silvicultural treatments for each stand. According to the evaluation of competition index, it was confirmed that spatial structure of the stands was improved by applying the silvicultural treatments.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.5
• /
• pp.47-56
• /
• 2020

The stock index is used not only as an economic indicator for a country, but also as an indicator for investment judgment, which is why research into predicting the stock index is ongoing. The task of predicting the stock price index involves technical, basic, and psychological factors, and it is also necessary to consider complex factors for prediction accuracy. Therefore, it is necessary to study the model for predicting the stock price index by selecting and reflecting technical and auxiliary factors that affect the fluctuation of the stock price according to the stock price. Most of the existing studies related to this are forecasting studies that use news information or macroeconomic indicators that create market fluctuations, or reflect only a few combinations of indicators. In this paper, this we propose to present an effective combination of the news information sentiment analysis and various macroeconomic indicators in order to predict the US Dow Jones Index. After Crawling more than 93,000 business news from the New York Times for two years, the sentiment results analyzed using the latest natural language processing techniques BERT and NLTK, along with five macroeconomic indicators, gold prices, oil prices, and five foreign exchange rates affecting the US economy Combination was applied to the prediction algorithm LSTM, which is known to be the most suitable for combining numeric and text information. As a result of experimenting with various combinations, the combination of DJI, NLTK, BERT, OIL, GOLD, and EURUSD in the DJI index prediction yielded the smallest MSE value.

• Journal of the Korean Society for information Management
• /
• v.39 no.4
• /
• pp.269-306
• /
• 2022

This study aimed to develop indicators that can measure the digital transformation performance of science and technology information construction and sharing systems by utilizing the Digital Curation Maturity Models. For digital transformation, it is necessary to consider not only simple service improvement but also organizational and business changes. In this study, we aimed to develop a model for measuring the digital transformation of KISTI, Korea's representative science and technology information service organization. KISTI has already carried out BPR work for digital transformation and borrowed the concept of a maturity model. However, in BPR, there is no method to measure the result. Therefore, in this paper, we developed an index to measure digital transformation based on the maturity model. Indicator development was carried out in two ways: model development and evaluation. Cases for model construction were made through a comprehensive review of existing KISTI and various domestic and foreign cases. The models before verification were technology (37), data (45), strategy (18), organization (36), and (social)influence (14) based on the major categories. After verification using confirmatory factor analysis, the model is classified as technology (20 / 17 indicators dropped), data (36 / 9 indicators dropped), strategy (18 / maintenance), organization(30 / 6 indicators dropped), and (social) influence (13 indicators / 1 indicator dropped).

• The Korean Journal of Food And Nutrition
• /
• v.16 no.4
• /
• pp.397-405
• /
• 2003

The cleanness of Korean(n=292), Chinese(n=46), Japanese(n=114) and Western(n=74) styles restaurants in 25 districts in Seoul was evaluated in terms of kitchen area(6 criteria), handling of raw materials(3 criteria), hygiene practice for cook(1 criteria), treatment of wastes(2 criteria) and hall(2 criteria). The western-style restaurants were scored the highest points in all criteria. The other three restaurants were poorly evaluated compared with western-style ones in kitchen area, including cleanness of inside of the kitchen, hygiene practice, ventilation and working environment, drainage, and storage of utensils. The most critical criterion which represents the overall evaluation was the ventilation and working environment of the kitchen for Chinese, Japanese and Western-style restaurants, and was the cleanness of inside the kitchen for Korean-style restaurants.

• Journal of Food Hygiene and Safety
• /
• v.31 no.4
• /
• pp.264-271
• /
• 2016

The purpose of this study was to investigate contamination sources of baby leafy vegetables by assessing microbial loads on baby leafy vegetables and agricultural inputs contacted with the vegetables. To estimate microbial loads, fecal indicators (coliform and Escherichia coli) and foodborne pathogens (E. coli O157:H7, Salmonella spp., Staphylococcus aureus, Listeria monocytogenes, and Bacillus cereus) were examined. A total of 126 samples including eleven kinds of leafy vegetables, irrigation water, media, and tools were tested, resulting in coliform contamination observed from most of samples. For E. coli, 10.3% (13/126) of the samples were positive including irrigation water, knife, handler, media, tools, and three kinds of leafy vegetables. B. cereus was detected from 38% (48/126) of the samples including media, tools and three kinds of leafy vegetables. No E. coli O157:H7, Salmonella spp., and L. monocytogenes was detected. This result implies that contacting with agricultural inputs could explain microbial load of baby leafy vegetables.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.6 no.4
• /
• pp.16-23
• /
• 2003

In this study, for the application of land resource evaluation using GIS map overlay method, I have considered about the process that can draw out right results from the problems involving multiple hierarchical indicators and weights. The assumption of this research is that there are two processes in the application of analytic hierarchy process(AHP) and the different results will appear. The two processes are as follows; (1) calculate directly the comprehensive weights to the indicators and overlay the layers(Method I) and (2) repeat the process of map overlay and standardization(Method II). The two precesses are applied on the study site based on the envirosystem in Bong-Hwa, and then some differences were found in the results and it was suggested that the Method II is more reasonable.

• Information Systems Review
• /
• v.4 no.1
• /
• pp.69-87
• /
• 2002

As the society of knowledge becomes, the most competitive resource for corporations is knowledge. Furthermore corporations may evaluate and improve latent knowledge of `Intellectual Capital' (IC), which will be directly related with the existence of corporation in the future. Although it has been researched and proposed to evaluate IC value that is ignored relatively to tangible asset, the indexes of evaluating IC have never been examined and have been adopted by many corporations. Furthermore, as there is no systematic model to evaluate IC value, each corporation should re-evaluate IC valuation model. Economic wastes have been created under this situation. Therefore this study intends to develop a synthetic and systematic model for IC valuation. Consequently the model is consisted of 3 dimensions, 10 factors, 22 evaluation criteria, and 82 indexes, which was necessary for IC valuation. This model will be practically applied to IC valuation of corporations.

• Journal of Intelligence and Information Systems
• /
• v.14 no.4
• /
• pp.69-87
• /
• 2008

The Web is evolving toward the Semantic Web. Ontologies are considered as a crucial component of the Semantic Web since it is the backbone of knowledge representation for this Web. However, most of these ontologies are still built manually. Manual building of an ontology is time-consuming activity which requires many resources. Consequently, the need for automatic ontology extraction tools has been increased for the last decade, and many tools have been developed for this purpose. Yet, there is no comprehensive framework for evaluating such tools. In this paper, we proposed a set of criteria for evaluating ontology extraction tools and carried out an experiment on four popular ontology extraction tools (i.e., OntoLT, Text-To-Onto, TERMINAE, and OntoBuilder) using our proposed evaluation framework. The proposed framework can be applied as a useful benchmark when developers want to develop ontology extraction tools.

• Explosives and Blasting
• /
• v.33 no.4
• /
• pp.14-24
• /
• 2015

We conducted test blasting in 3 sites to identify the effect on safety of the earth retaining wall by near blasting vibration. As a test result, we confirm that underground structures(earth anchor et al.) are relatively safer than surface structures as the underground vibration is 10~52% of surface vibration at a same distance. We derived surface and underground vibration prediction equations by regression analysis of measured 3 sites' surface and underground vibration PPV. Also we calculated minimum separation distance by blasting pattern about underground and surface curing concrete. Unless any discontinuity which are unsafe on the earth retaining wall appear, blasting work using under 2.4kg per delay is not meaningful to the earth retaining wall's safety as the result of measuring near blasting vibration, confirming change the earth retaining wall's instrument, and observation of structural deformation.

• The Journal of the Korea Contents Association
• /
• v.18 no.11
• /
• pp.135-145
• /
• 2018

In online communities, users use comments to exchange their opinions and feelings on various subjects. Communication based on comments is quick and convenient, but sometimes this light-weight characteristic makes users use impolite and aggressive words, which leads to an online conflict. Therefore, it is important to analyze and classify users according to their characteristics in order to predict and take action for this kind of troubles. In this paper, we present several quantitative measures for describing the structures of comments trees based on the assumption that the user characteristics be observed as a form of some structural feature in comment trees of articles in which they posted comments. We examine the distribution of the proposed measures over article posters and commenters, and in addition, we show the effectiveness of the presented structural features by conducting experiments to classify users who have received warnings of the administrator from benign users.