• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.81-96
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• 2016

As the internet has become widespread and easy to access everywhere, it is common for people to search information via online search engines such as Google and Naver in everyday life. Recent studies have used online search volume of specific keyword as a measure of the internet users' attention in order to predict disease outbreaks such as flu and cancer, an unemployment rate, and an index of a nation's economic condition, and etc. For stock traders, web search is also one of major information resources to obtain data about individual stock items. Therefore, search volume of a stock item can reflect the amount of investors' attention on it. The investor attention has been regarded as a crucial factor influencing on stock price but it has been measured by indirect proxies such as market capitalization, trading volume, advertising expense, and etc. It has been theoretically and empirically proved that an increase of investors' attention on a stock item brings temporary increase of the stock price and the price recovers in the long run. Recent development of internet environment enables to measure the investor attention directly by the internet search volume of individual stock item, which has been used to show the attention-induced price pressure. Previous studies focus mainly on Dow Jones and NASDAQ market in the United States. In this paper, we investigate the relationship between the individual investors' attention measured by the internet search volumes and stock price changes of individual stock items in the KOSDAQ market in Korea, where the proportion of the trades by individual investors are about 90% of the total. In addition, we examine the difference between industries in the influence of investors' attention on stock return. The internet search volume of stocks were gathered from "Naver Trend" service weekly between January 2007 and June 2015. The regression model with the error term with AR(1) covariance structure is used to analyze the data since the weekly prices in a stock item are systematically correlated. The market capitalization, trading volume, the increment of trading volume, and the month in which each trade occurs are included in the model as control variables. The fitted model shows that an abnormal increase of search volume of a stock item has a positive influence on the stock return and the amount of the influence varies among the industry. The stock items in IT software, construction, and distribution industries have shown to be more influenced by the abnormally large internet search volume than the average across the industries. On the other hand, the stock items in IT hardware, manufacturing, entertainment, finance, and communication industries are less influenced by the abnormal search volume than the average. In order to verify price pressure caused by investors' attention in KOSDAQ, the stock return of the current week is modelled using the abnormal search volume observed one to four weeks ahead. On average, the abnormally large increment of the search volume increased the stock return of the current week and one week later, and it decreased the stock return in two and three weeks later. There is no significant relationship with the stock return after 4 weeks. This relationship differs among the industries. An abnormal search volume brings particularly severe price reversal on the stocks in the IT software industry, which are often to be targets of irrational investments by individual investors. An abnormal search volume caused less severe price reversal on the stocks in the manufacturing and IT hardware industries than on average across the industries. The price reversal was not observed in the communication, finance, entertainment, and transportation industries, which are known to be influenced largely by macro-economic factors such as oil price and currency exchange rate. The result of this study can be utilized to construct an intelligent trading system based on the big data gathered from web search engines, social network services, and internet communities. Particularly, the difference of price reversal effect between industries may provide useful information to make a portfolio and build an investment strategy.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.2
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• pp.103-119
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• 2023

Since the Korean government has decided to apply the policy of BIM (Building Information Modeling) to the entire construction industry, it has experienced a positive trend in adoption and utilization. BIM can reduce workloads by building model objects into libraries that conform to standards and enable consistent quality, data integrity, and compatibility. In the domestic architecture, civil engineering, and the overseas landscape architecture sectors, many BIM library standardization studies have been conducted, and guidelines have been established based on them. Currently, basic research and attempts to introduce BIM are being made in Korean landscape architecture field, but the diffusion has been delayed due to difficulties in application. This can be addressed by enhancing the efficiency of BIM work using standardized libraries. Therefore, this study aims to provide a starting point for discussions and present a classification system for objects and attribute information that can be referred to when creating landscape libraries in practice. The standardization of landscape BIM library was explored from two directions: object classification and attribute information items. First, the Korean construction information classification system, product inventory classification system, landscape design and construction standards, and BIM object classification of the NLA (Norwegian Association of Landscape Architects) were referred to classify landscape objects. As a result, the objects were divided into 12 subcategories, including 'trees', 'shrubs', 'ground cover and others', 'outdoor installation', 'outdoor lighting facility', 'stairs and ramp', 'outdoor wall', 'outdoor structure', 'pavement', 'curb', 'irrigation', and 'drainage' under five major categories: 'landscape plant', 'landscape facility', 'landscape structure', 'landscape pavement', and 'irrigation and drainage'. Next, the attribute information for the objects was extracted and structured. To do this, the common attribute information items of the KBIMS (Korean BIM Standard) were included, and the object attribute information items that vary according to the type of objects were included by referring to the PDT (Product Data Template) of the LI (UK Landscape Institute). As a result, the common attributes included information on 'identification', 'distribution', 'classification', and 'manufacture and supply' information, while the object attributes included information on 'naming', 'specifications', 'installation or construction', 'performance', 'sustainability', and 'operations and maintenance'. The significance of this study lies in establishing the foundation for the introduction of landscape BIM through the standardization of library objects, which will enhance the efficiency of modeling tasks and improve the data consistency of BIM models across various disciplines in the construction industry.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.337-357
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• 2021

Because the growth of paddy rice is affected by meteorological factors, the selection of appropriate meteorological variables is essential to build a rice yield prediction model. This paper examines the suitability of multiple meteorological datasets for the rice yield modeling in South Korea, 1996-2019, and a hindcast experiment for rice yield using a machine learning method by considering the nonlinear relationships between meteorological variables and the rice yield. In addition to the ASOS in-situ observations, we used CRU-JRA ver. 2.1 and ERA5 reanalysis. From the multiple meteorological datasets, we extracted the four common variables (air temperature, relative humidity, solar radiation, and precipitation) and analyzed the characteristics of each data and the associations with rice yields. CRU-JRA ver. 2.1 showed an overall agreement with the other datasets. While relative humidity had a rare relationship with rice yields, solar radiation showed a somewhat high correlation with rice yields. Using the air temperature, solar radiation, and precipitation of July, August, and September, we built a random forest model for the hindcast experiments of rice yields. The model with CRU-JRA ver. 2.1 showed the best performance with a correlation coefficient of 0.772. The solar radiation in the prediction model had the most significant importance among the variables, which is in accordance with the generic agricultural knowledge. This paper has an implication for selecting from multiple meteorological datasets for rice yield modeling.

• International Journal of Highway Engineering
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• v.13 no.3
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• pp.157-165
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• 2011

With respect to the trend of highway traffic accident, highway accident is in decline, whileas, the fatality is on an increasing trend. Thus, many efforts to decrease highway traffic accidents and improve the safety, are required. In particular, in case of highway, the management standard by grade for accident black spot is designated. Thus, investing the effect factors by grade for highway traffic accident is required in detail. Thus, in this study, the factors affecting the traffic accidents among the environmental factors based on the graded data for the accident black spot in the applicable section targeting the Seoul-Pusan Express Highway, were reviewed; accident forecasting model which would analyze the characteristics of the accidents for determining the accident grade, was developed. As a result of establishing a model by using Quantification Theory of Type II, considering the characteristics of the dependent and independent variables based on the geometric structure, 'the fixed variable' among the variables relating to the accident, for the variables influencing over the accident grade, 'the type of vans, a chassis and people', 'the trailers, special vehicles and chassis people' and 'the negligence of watching and cloudy weather' were analyzed as common factors, in case of 'horizontal alignment', 'longitudinal slope' and, 'barricade' respectively.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.3
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• pp.33-41
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• 2007

Owing to the development of multimedia and communication technologies, multimedia data become a common feature of the information systems and are on the increase. This has led to the need of 3D shape retrieval systems that, given a query object, retrieve similar 3D objects. Therefore, shape descriptor required to describe a 3D object effectively and efficiently. In this paper, a new descriptor for 3D model retrieval based on shape information is proposed. The proposed descriptor utilizes the curvedness together with the shape index that provides local geometry information. The existing 3D Shape Spectrum Descriptor (3D SSD), which is defined as the histogram of shape index values, represents the characteristics of local shapes of the 3D surface. However, it does not properly represent the local shape characteristics, because many points with different curvedness may have the same shape index value. Therefore, we add a new feature that represents the degree of curvedness, thereby improving the discriminating power of the shape descriptor. We evaluate the performance of the proposed method, compared with the previous method. The experimental results have shown that the performance of retrieval has been improved by 23.6%.

• Journal of Korean Society of Environmental Engineers
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• v.31 no.9
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• pp.825-830
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• 2009

Pharmaceutical compounds enter the water environment through the diverse pathways. Because their concentration in the water environment was frequently detected in the level of ppt to ppb, the monitoring system should be optimized as much as possible for finding appropriate management policies and technical solutions. One Factor At a Time (OFAT) approach approximating the response with a single variable has been preferred for the optimization of LC-MS/MS operational conditions. However, it is common that variables in analytical instruments are interdependent. Therefore, the best condition could be found by using the statistical optimization method changing multiple variables at a time. In this research, response surface analysis (RSA) was applied to the LC-MS/MS analysis of emerging antibiotic compound, sulfamethoxazole, for the best sensitivity. In the screening test, fragmentation energy and collision voltage were selected as independent variables. They were changed simultaneously for the statistical optimization and a polynomial equation was fit to the data set. The correlation coefficient, $R^2$ valuerepresented 0.9947 and the error between the predicted and observed value showed only 3.41% at the random condition, fragmentation energy of 60 and collision voltage of 17 eV. Therefore, it was concluded that the model derived by RSA successfully predict the response. The optimal conditions identified by the model were fragmentation energy of 116.6 and collision voltage of 10.9 eV. This RSA can be extensively utilized for optimizing conditions of solid-phase extraction and liquid chromatography.

• Journal of Environmental Impact Assessment
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• v.23 no.6
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• pp.453-465
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• 2014

Hotspots are top sites in terms of species diversity as the most threatened and most diverse sites which have been used to select priority areas for reserves. The purpose of this paper is to identify biodiversity hotspots through analyzing nationwide spatial patterns of species richness and rarity of Korean mammals. Four endangered mammals and eleven common mammals were selected as target species. Environmental variables as model input data were consisted of topography, distance, and vegetation structure etc. and Maxent was used to develop species distribution models for target species. Species richness and rarity were used as index of biodiversity. The results of this study were as follows. Firstly, hotspots of species richness for endangered mammals were in high elevation and steep mountain areas. However, species richness for whole mammals were high in low elevation of mountains. Secondly, distribution pattern of species rarity for endangered mammals were similar as richness. However, hotspots of species rarity for whole mammals were a little different from species richness. Species rarity was high in both low and high elevation of mountain areas. This study will provide the useful information for a biodiversity assessment, a habitat conservation, a national ecological network plan, and the management of protected areas.

• Journal of Information Technology Applications and Management
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• v.16 no.2
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• pp.1-21
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• 2009

The balanced scorecard(BSC) framework is a tool for strategic decision making and task support that aims for efficiency in performance management and strategy execution. BSC evolved from an old performance management practice, which tended to be limited to a finance-only perspective, to a new system of corporate management looking at corporate tasks from a multi-dimensional, future-inclined value perspective. This form of BSC amounts to a framework capable of driving management innovation and renewing the ways in which companies conceive their strategy and perform their operations. Since BSC draws integrally on user participation, it can be expected that users' satisfaction with BSC systems is an important factor in systems' success or failure. However, previous studies of the BSC system have not yet considered it as a theoretical model, specifically examining BSC system and task characteristics. To date, only a few studies have put forward plans for the implementation and use of BSC systems, and these studies have the common limitation of failing to consider the circumstances or theoretical structure of the companies for which a BSC system is being proposed. This paper then begins to fill some of this gap by characterizing the BSC system from the perspective of contingency theories. Contingency theories can be particularly useful in the Korean context in exploring how different companies use the BSC system in ways determined by their unique environmental characteristics, which may also determine the performance factors behind the application of a company's particular BSC system. In order to provide concrete suggestions for implanting and using the BSC system from a contingency theory perspective, this study sets out to determine the relationships between the contingency variables affecting BSC system performance and BSC system property variables(in given cases) through an empirical analysis. The study takes into account the perspective from which contingency theory is to be applied in individual cases, sets contingency and BSC property variables with reference to the BSC system user's environment and BSC system's character, and frames initial hypotheses concerning corporate structure and environmental variables and BSC system performance variables with reference to previous studies. A survey was then conducted on users in Korean companies that have implemented the BSC system in order to verify the research model and understand results.

• Journal of Korean society of Dental Hygiene
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• v.3 no.1
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• pp.59-72
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• 2003

The purpose of this study was to examine what the role of denial hygienist was. The subjects were 751 dental hygienists from dental clinics, dental hospitals, general hospitals, public dental clinics and their branches throughout the nation. After a survey was conducted, the collected data were analyzed with SPSS WIN 10.0, and variance analysis and post-analysis were implemented. And Forgarty's 8th integrated model, out of 10 ones, was selected to delve into the practical role of dental hygienist in detail. The findings of this study were as follows: 1. The three age groups had a significantly different opinion on the significance of individual subjects. The dental hygienists of thirty six and over found the basic and preventive public dental care courses most important, and the 31~35 age group placed most stock in education and research. Overall, the post-analysis results showed that prevention and clinical courses were considered most vital, followed by education and fundamental courses. 2. There was a significant gap between four groups from the different work places in their view of the weight of the individual subjects. According to the post-analysis, the dental hygienists from the general hospitals, public dental clinics and their branches gave more weight to fundamental, education and research areas. Those who were with the dental clinics, dental hospitals and general hospitals put higher value on clinical course than the dental hygienists from the public dental clinics and their branches. 3. Two groups with a different career also had a different outlook on the importance of the individual subjects. The post-analysis results illustrated that the dental hygienists who had worked for three years or more put higher stress on the fundamental course than those with a less career, and the dental hygienists with a five-year or higher career attached more importance to the education and research field than those with a smaller career. 4. There was a significant difference between the three age groups in their clinical role. The post-analysis results indicated thai the younger dental hygienists were more of assistants than of professionals, as they chiefly took X-ray photograph, handled treatment materials or performed treatment-related works. Overall, handling treatment materials was most common. 5. The three groups from the different work places significantly varied in their clinical role. According to the post-analysis, those from the dental clinics and dental hospitals took more x-ray photographs, handled more treatment materials and performed more relevant works, compared to those from the general hospitals, public dental clinics and their branches. 6. The two groups with a different career differed significantly in their clinical role. The post-analysis results suggested that the dental hygienists with a less career played an assistant role more, which handled treatment materials or carried out other relevant works. 7. The fundamental courses (I) and (II), preventive class (I) and (II) and its practice course were regarded as integrated subjects that they should take 10 offer preventive treatment, which was one of the dental hygienist missions. What's needed to act as dental-care educators was the basic courses (I) and (II), dental hygiene education and its practice. Finally, integrated clinical courses (I) and (II) and clinical practice were viewed as necessary for their role performance as dental treatment collaborators.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.829-839
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• 2013

This study is a descriptive research study with the purpose of predicting and comparing factors of depression affecting residents in a metropolitan city by using logistic regression analysis and decision-making tree analysis. The subjects for the study were 462 residents ($20{\leq}aged{\angle}65$) in a metropolitan city. This study collected data between October 7, 2011 and October 21, 2011 and analyzed them with frequency analysis, percentage, the mean and standard deviation, ${\chi}^2$-test, t-test, logistic regression analysis, roc curve, and a decision-making tree by using SPSS 18.0 program. The common predicting variables of depression in community residents were social dysfunction, perceived physical symptom, and family support. The specialty and sensitivity of logistic regression explained 93.8% and 42.5%. The receiver operating characteristic (roc) curve was used to determine an optimal model. The AUC (area under the curve) was .84. Roc curve was found to be statistically significant (p=<.001). The specialty and sensitivity of decision-making tree analysis were 98.3% and 20.8% respectively. As for the whole classification accuracy, the logistic regression explained 82.0% and the decision making tree analysis explained 80.5%. From the results of this study, it is believed that the sensitivity, the classification accuracy, and the logistics regression analysis as shown in a higher degree may be useful materials to establish a depression prediction model for the community residents.