• Journal of Intelligence and Information Systems
• /
• v.18 no.2
• /
• pp.143-156
• /
• 2012

People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
• /
• 2001.04a
• /
• pp.98-103
• /
• 2001

In order to understand the characteristics of leachate at the Seokdae municipal waste landfill in the Pusan city, the correlation between leachate pollution loading and volume of gas production. concentration of gas and subsidence of ground, the characteristical methos, geochemical analyses and laboratory column tests using samples of gases, leachate and surface soil of Seokdae waste landfill area. Through the analysis of water balance, leachate flow rate and pollution loading were estimated. Geistatistical analysis of four gas components ( $O_2$, C $H_4$, $H_2$S and CO) shows the possibility of ground subsidence around the group of a site with high concentration of gas. From geochemical analyses of leachate, EC and Total-Alkalinity of ground subsidence around the group of a site with high concentration of gas. From geochemical analysis of leachate, Ec and Total-Alkalinity were increased, and Cl, Cr, Mn, Cu, Zn, Cd and Pb were decreassed comparing to the part, and the type of water quality was Na-HC $O_3$ in trilinear diagram. It shows that biodecomposition of municipal wastes continues actively. From the analysis of water balance, the total leachate flow rate is about 465.11㎥/day and pure pollution loading of Cl, Mn and Fe are estimated to 223.8kg/day, 0.2kg/day, 0.3kg/day, respectively. The laboratory column test of residual soil and landfill soil shows 0.206cm and 0.019cm for linear velocity(equation omitted), 0.234 $\textrm{cm}^2$/min and 0.018$\textrm{cm}^2$/min for diffusion coefficient ( $D_{ι}$), and 1.136cm and 0.095cm longitudinal dispersion index ($\alpha$$_{ι}$), respective]y. It demonstrates that the delay time of contamination for residual soil is shorter than that of landfill soil.

• Journal of Korean Society of Forest Science
• /
• v.112 no.1
• /
• pp.71-82
• /
• 2023

Forest biomass is used as a representative indicator of forest size, maturity, and productivity. Therefore, quantitative evaluation is important for management and harvest as well as the evaluation of ecosystem functions and services including CO₂ absorption. The allometric equation is a widely used method for estimating the value of each component through the relative growth rate of plants. Recently, studies indicated that the relative growth of trees is changing because of the increased CO₂ concentration in the atmosphere and the resulting climate change, raising the need to review the previously developed relative growth models and coefficients. In this study, the height-diameter at breast height (DBH) relationships of four major tree species in Korea [(Pinus densiflora (PD), Larix kaempferi (LK), Quercus variabilis (QV), and Quercus mongolica (QM)] were analyzed using the 5th-7th National Forest Inventory (NFI) data. Furthermore, these results were compared with the present yield table from the National Institute for Forest Science. This analysis revealed that the expected height for the same DBH increased as the NFI progressed. For example, in model analysis, the expected heights for PD, LK, QV, and QM for DBH of 25 cm were 12.48, 19.17, 14.47, and 13.19 m, respectively, in the 5th NFI data. In the 7th NFI data, these values were estimated as 13.61 (+9.1%), 21.58 (+12.7%), 15.76 (+8.9%), and 13.93 m (+5.6%), respectively. These results indicate that the major tree species in South Korean forests currently are more vigorous in height growth than in diameter growth when compared to the height-DBH development trends by tree species identified through past survey data.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.19 no.3
• /
• pp.93-101
• /
• 2017

The distribution of inter-annual variation in temperature would help evaluate the likelihood of a climatic risk and assess suitable zones of crops under climate change. In this study, we evaluated two methods to estimate the standard deviation of temperature in the areas where weather information is limited. We calculated the monthly standard deviation of temperature by collecting temperature at 0600 and 1500 local standard time from 10 automated weather stations (AWS). These weather stations were installed in the range of 8 to 1,073m above sea level within a mountainous catchment for 2011-2015. The observed values were compared with estimates, which were calculated using a geospatial correction scheme to derive the site-specific temperature. Those estimates explained 88 and 86% of the temperature variations at 0600 and 1500 LST, respectively. However, it often underestimated the temperatures. In the spring and fall, it tended to had different variance (e.g., increasing or decreasing pattern) from lower to higher elevation with the observed values. A regression analysis was also conducted to quantify the relationship between the standard deviation in temperature and the topography. The regression equation explained a relatively large variation of the monthly standard deviation when lapse-rate corrected temperature, basic topographical variables (e.g., slope, and aspect) and topographical variables related to temperature (e.g., thermal belt, cold air drainage, and brightness index) were used. The coefficient of determination for the regression analysis ranged between 0.46 and 0.98. It was expected that the regression model could account for 70% of the spatial variation of the standard deviation when the monthly standard deviation was predicted by using the minimum-maximum effective range of topographical variables for the area.

• Korean Journal of Environment and Ecology
• /
• v.1 no.1
• /
• pp.46-65
• /
• 1987

This study was excuted to measure the user's impact area of the Bukhan Mountain National Park. Eighteen sites of the campsite and the picnic area were sample to measure the impact rating of soil and vegetation. And three belt transects were sampled to analyze soil properties and vegetational change by the user's impact. Also user's psychology was investigated through questionnaires with the visitor and 726 answers were collected from May to June in 1987. The regression equation was significant between the distance and the soil hardness. individual number per 100$m^2$, herb coverage and similarity index from the center of picnic area to the non-use site. The tolerant tree against user's impact are Lespedza maximowiczii. Stephanandra insica, Actinidia arguta Symplocos chinensis for. pilosa and the sensitive trees were Fraxinus rhy chophylla Sorbus alnifolia. and Rhodadendron mucronulatun. The facilities factor and social factor are the most affecting factors to User's psychology by the varimax rotated factor analysis. The carrying capacity of the picnic area was 25$m^2$ per man by the degree of psychological satisfaction.

• Korean Journal of Environment and Ecology
• /
• v.18 no.1
• /
• pp.53-60
• /
• 2004

This study was carried out to investigate the effect of green area in apartment complexes to variation of temperature. The inside temperature of each site was estimated by analyzing Landsat ETM＋ image data. The factors on variation of temperature were landcover type, building density, and Normalised Difference Vegetation Index(NDVI). The results of correlation between inside temperature of apartment complex and land cover type showed that the green area ratio had negative(－) correlation and impermeable pavement ratio had positive(＋) correlation. Building-to-land ratio was not significant with inside temperature. A coefficient of correlation between the temperature value and the value of permeable pavement ratio added up green area ratio was higher than a coefficient of correlation between the temperature value and the value of permeable pavement ratio added up impermeable pavement ratio. Thus we may define that permeable pavement area decrease urban temperature with green area in apartment complex. Floor area ratio had no significant correlation with inside temperature. Inside temperature was decreased as the NDVI was increased. To establish the temperature distribution model in a development apartment complex, As the result of regression analysis between inside temperature as dependent variable and permeable pave ratio+green area ratio, green area ratio, building-to-land ratio and NDIT as independent variables, only permeable pavement ratio added up green area ratio of the independent variables was accepted fur regression equation in both two seasons and adjusted coefficient of determination was 41.4 on September, 2000 and 40.4 on June,2001.

• Journal of Environmental Policy
• /
• v.9 no.3
• /
• pp.69-114
• /
• 2010

This study investigates the voluntary corporate disclosure of environmental information via stand-alone environmental reports or company web-sites. Quality of disclosure was assessed using the content analysis index proposed by Clarkson et al. (2008) based on GRI guidelines. Descriptive statistics on disclosure scores by category suggest that the level of disclosure is low relative to the expectation implied by the GRI reporting guidelines, and points to the need for improvement in the future. Specific areas where improvement is required include the disclosure of environmental performance indicators. Corporate environmental performance was measured in terms of the percentage of toxic wastes that was treated or processed by each firm and economic performance, by industry-adjusted annual return, which was subject to a series of association tests designed to explore the interrelations among environmental disclosure, environmental performance, and economic performance. The individual equation approach based on OLS procedures suggests a positive association between environmental performance and the level of discretionary environmental disclosures, which is not the case between environmental and economic performance. An integrated analysis using simultaneous equations approach does not indicate any significant relationships among three constructs, suggesting the lack of endogeneity, inconsistent with Al-Tuwaijri et al. (2004). Additional analysis assesses the level of environmental disclosure made in footnotes to the audited annual reports, which suggests that the quality of disclosure is very low and that footnote disclosure does not serve as a meaningful channel for the provision of corporate environmental information.

• Journal of Bio-Environment Control
• /
• v.30 no.4
• /
• pp.419-428
• /
• 2021

In order to develope a mobile-based greenhouse energy calculation program, firstly, the overall thermal transmittance of 10 types of major covers and 16 types of insulation materials were measured. In addition, to estimate the overall thermal transmittance when the cover and insulation materials were installed in double or triple layers, 24 combinations of double installations and 59 combinations of triple installations were measured using the hotbox. Also, the overall thermal transmittance value for a single material and the thermal resistance value were used to calculate the overall thermal transmittance value at the time of multi-layer installation of covering and insulating materials, and the linear regression equation was derived to correct the error with the measured values. As a result of developing the model for estimating thermal transmittance when installing multiple layers of coverings and insulating materials based on the value of overall thermal transmittance of a single-material, the model evaluation index was 0.90 (good when it is 0.5 or more), indicating that the estimated value was very close to the actual value. In addition, as a result of the on-site test, it was evaluated that the estimated heat saving rate was smaller than the actual value with a relative error of 2%. Based on these results, a mobile-based greenhouse energy calculation program was developed that was implemented as an HTML5 standard web-based mobile web application and was designed to work with various mobile device and PC browsers with N-Screen support. It had functions to provides the overall thermal transmittance(heating load coefficient) for each combination of greenhouse coverings and thermal insulation materials and to evaluate the energy consumption during a specific period of the target greenhouse. It was estimated that an energy-saving greenhouse design would be possible with the optimal selection of coverings and insulation materials according to the region and shape of the greenhouse.

• Asia Marketing Journal
• /
• v.14 no.1
• /
• pp.25-51
• /
• 2012

Researches about the relationship between SST(Self Service Technology) and TRI(Technology Readiness Index) have been carried out after TRI was developed by Parasuraman and his colleagues(2000). We hypothesize Consumer Readiness can also influence consumer's motivation, attitude, and intent to use SST. Currently, there has been no research on this subject. In this study, we investigated the relationship between TR, Consumer Readiness and SST Core Attitudinal Model which Dabholkar & Bagozzi(1994) proposed. The researchers also investigated moderating effects of consumer traits and situational factors to verify the acceptance of such forms of service delivery by all kinds of consumers and under different situational contexts. Self consciousness, the need for interaction with an employee, and the technology anxiety were used as consumer trait variables. Perceived waiting time and perceived crowding were used as situational variables. 380 questionnaires were distributed to a sample group of people in their 20's and 30's, and the data were analyzed with structural equation model using AMOS 18.0 program. All of Cronbach's alpha values representing reliabilities were satisfactory. The values of Composite Reliability(CR) and Average Variance Extracted(AVE) also showed the above criteria, thus providing evidence of convergent validity. To confirm discriminant validity among the constructs, confirmatory factor analysis and correlations among all the variables were examined. The results were satisfactory. The results of this study are summarized as follows. 1. Optimism and innovativeness of TR partially influenced the motivation to use SST. People who tend to be optimistic use SST because of ease of use and fun. The innovative however, usually use SST due to its performance. However, consumer readiness of role clarity, ability and self-efficacy influence all the components of motivation to use SST, ease of use, performance and fun. The relative effect of consumer readiness on the motivation to use SST was much stronger and more significant than that of TR. No other previous studies have examined the effects of Consumer Readiness on SST usage motivation, attitude and intention. It is academically meaningful that the researchers verified that Consumer Readiness is the important precedent construct influencing the self service technology core Attitudinal Model. Our findings suggest that marketers should consider fun and ease of use attributes to promote the use of self service technology. In addition, the SST usage frequency will rise rapidly when role clarity, ability, and self-efficacy which anybody can easily handle SST is assured. If the SST usage rate is increased, waiting times for customers could be decreased. Shorter waiting time could lead to higher customer satisfaction. It may also result in making a long-term profit owing to the reduced number of employees. Thus, presentation of using SST by employees or videos showing how to use it will promote the usage attitude and intent. 2. In SST core attitudinal model, performance and fun factors among SST usage motivation affected attitudes of using SST. The attitude of using SST highly influenced intent to use SST. This result is consistent with previous researches that dealt with the relationship between motivation, attitude and intention. Expectation of using SST could result in good performance just like the effect of ordering menu to service employees and to have fun since fun during its use could promote more SST usage rate. 3. In the relationship among motivation, attitude and intent in SST core attitudinal model, the moderating effect of consumer traits(self-consciousness, need for interaction with service employees and technology anxiety) and situational factors(perceived crowding and perceived waiting time) were tested. The results also supported the hypothesized moderating effects except perceived crowding. The highly self-conscious tended to form attitudes to use SST because of its fun compared to those who were less self-conscious because of its performance. People who had a high need for interaction with service employees tended to use SST for its performance. This result indicates that if ordering results are assured, SST is easily accessible to even consumers who have a high need for interaction with a service employee. When SST is easy to use, attitudes strengthen intent among people who had a high level of anxiety of technology. People who had low technology anxiety formed attitudes to use SST because of its performance. Service firms must ensure their self service technology is designed to be easy to use for those who have a high level of technology anxiety. Shorter perceived waiting times strengthened the attitude to use self service technology because of its fun. If the fun aspect is assured, people willing to use self service technology even perceive waiting time to be shorter than it actually is. Greater perceived waiting times form higher level of intent to use self service technology than those of shorter perceived waiting times. This implies that people view self service technology as a faster alternative to ordering service employees. The fun aspect of self service technology will attract a higher rate of usage for self service technology. 4. It has been proven that ease of use, performance and fun aspects are very important factors in motivation to form attitudes and intent to use self service technology regardless of the amount of perceived waiting time, self-consciousness, need for interaction with service employees, and technology anxiety. Service firms must consider these motivation aspects(ease of use, performance and fun)strongly in their promotion to use self service technology. Ease of use, assuring absolute performance compared to interaction with service employees', and adding a fun aspect will positively strengthen consumers' attitudes and intent to use self service technology. Summarizing the moderating effects, fun is the most valuable factor triggering SST usage attitude and intention. Therefore, designing self service technology to be fun will be the key to its success. This study focused on the touch screen self service technology in fast food restaurant. Although it has its limits due to the fact that it is hard to generalize the results to any other self service technology, the conceptual framework of this study can be applied to future research of any other service site.