• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.23-46
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• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.187-204
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• 2016

Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.

• Journal of Korea Port Economic Association
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• v.31 no.4
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• pp.75-89
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• 2015

This study examines 31 import and export cargo items handled in each port to investigate which items face the most competition among the ports and how many of them are transited to other ports. The study aims to suggest implications for the future port policy of Incheon Port. It was found that the volume concentration in the Western Coast region from 2005 to 2014 became increasingly decentralized. The decentralization began in earnest in 2009 in particular, and the value was 0.448 in 2014, indicating fierce competition among the regions. According to the static and dynamic positioning analyses results for Incheon Port, Pyeongtaek and Dangjin Port, and Gunsan Port, using BCG Matrix, the static positioning analysis showed that Incheon Port belongs to the 3rd quadrant (Cash Cows), Pyeongtaek and Dangjin Port belongs to the 2nd quadrant (Question Marks), and Gunsan Port belongs to the (Dogs) group. This implies that Incheon Port has maintained its position with large shares compared to those of other ports, despite its low growth rate. However, the market position and growth rate of Incheon Port decreased according to the dynamic positioning analysis results. The shift-share analysis results indicated that the volumes of Incheon Port and Gunsan Port were shifting to Pyeongtaek and Dangjin Port. Moreover, the ratio of absolute growth to potential growth of Incheon Port and Gunsan Port turned out to be significantly lower than that of Pyeongtaek and Dangjin Port, implying that Incheon Port and Gunsan Port are declining as compared to Pyeongtaek Port and Dangjin Port. According to the LQ index analysis results, specialized items from Incheon Port that do not overlap with other ports included the following ten items: meat, fish and crustaceans, bituminous coals, crude oil and petroleum, petroleum-refined products, plastic rubber and products, textiles, nonferrous metal and products, electric machinery, and aircrafts and ships. In particular, it was confirmed that the bulk cargo of Incheon Port was actually shifting to Pyeongtaek and Dangjin Port following the policy of re-establishing port functions.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.679-692
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• 2020

We coupled a CFD model to the WRF-Chem model (WRF-CFD model) and investigated the characteristics of flows and carbon monoxide (CO) distributions in a building-congested district. We validated the simulated results against the measured wind speeds, wind directions, and CO concentrations. The WRF-Chem model simulated the winds from southwesterly to southeasterly, overestimating the measured wind speeds. The statistical validation showed that the WRF-CFD model simulated the measured wind speeds more realistically than the WRF-Chem model. The WRF-Chem model significantly underestimated the measured CO concentrations, and the WRF-CFD model improved the CO concentration prediction. Based on the statistical validation results, the WRF-CFD model improved the performance in predicting the CO concentrations by taking complicatedly distributed buildings and mobiles sources of CO into account. At 04 KST on May 22, there was a downdraft around the AQMS, and airflow with a relatively low CO concentration was advected from the upper layer. Resultantly, the CO concentration was lower at the AQMS than the surrounding area. At 15 KST on May 22, there was an updraft around the AQMS. This resulted in a slightly higher CO concentration than the surroundings. The WRF-CFD model transported CO emitted from the mobile sources to the AQMS measurement altitude, well reproducing the measured CO concentration. At 18 KST on May 22, the WRF-CFD model simulated high CO concentrations because of high CO emission, broad updraft area, and an increase in turbulent diffusion cause by wind-shear increase near the ground.

• Korean Journal of Ecology and Environment
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• v.46 no.4
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• pp.524-540
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• 2013

After the construction of the Geum River estuary dam, we investigated the ecological property of phytoplankton community with physicochemical property in 9 stations of Geum River estuary 4 times seasonally in 2010 about the environmental changes through the change of phytoplankton. Physicochemical property seems to show eutrophication which developed from the tendency of accruing of the nutrients (those involved in intermittency of freshwater which flows from the dike and the surrounding cities), caused by the changing of tidal flow, the decreasing of the inflow of seawater after the construction of the Geum River estuary dam (dike). A total of 233 species of species composition of phytoplankton emerged, showing a highly increased result compared to that of the former research. The reason for the increase in number is considered as a phenomenon resulting from the mix of blackish and freshwater marine species in the flow of intermittency of freshwater discharge. Also, the standing crops of phytoplankton considerably increased compared to when the dike had not yet been built. Highly affected by the discharge of occasional freshwater, the diatoms of blackish water zone dominated in spring and winter, while freshwater species appeared to dominate in summer and autumn. The species diversity showed over 2.0 except in winter season. After a cluster analysis, the result showed that the Geum River estuary was influenced by runoff from cities like Gunsan, the sewage which flows from Gyeongpo River, and the intermittency of freshwater discharge from the Geum River estuary dam.

• Journal of Soil and Groundwater Environment
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• v.12 no.5
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• pp.19-32
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• 2007

In Korea, there have been various methods of estimating groundwater recharge which generally can be subdivided into three types: baseflow separation method by means of groundwater recession curve, water budget analysis based on lumped conceptual model in watershed, and water table fluctuation method (WTF) by using the data from groundwater monitoring wells. However, groundwater recharge rate shows the spatial-temporal variability due to climatic condition, land use and hydrogeological heterogeneity, so these methods have various limits to deal with these characteristics. To overcome these limitations, we present a new method of estimating recharge based on water balance components from the SWAT-MODFLOW which is an integrated surface-ground water model. Groundwater levels in the interest area close to the stream have dynamics similar to stream flow, whereas levels further upslope respond to precipitation with a delay. As these behaviours are related to the physical process of recharge, it is needed to account for the time delay in aquifer recharge once the water exits the soil profile to represent these features. In SWAT, a single linear reservoir storage module with an exponential decay weighting function is used to compute the recharge from soil to aquifer on a given day. However, this module has some limitations expressing recharge variation when the delay time is too long and transient recharge trend does not match to the groundwater table time series, the multi-reservoir storage routing module which represents more realistic time delay through vadose zone is newly suggested in this study. In this module, the parameter related to the delay time should be optimized by checking the correlation between simulated recharge and observed groundwater levels. The final step of this procedure is to compare simulated groundwater table with observed one as well as to compare simulated watershed runoff with observed one. This method is applied to Mihocheon watershed in Korea for the purpose of testing the procedure of proper estimation of spatio-temporal groundwater recharge distribution. As the newly suggested method of estimating recharge has the advantages of effectiveness of watershed model as well as the accuracy of WTF method, the estimated daily recharge rate would be an advanced quantity reflecting the heterogeneity of hydrogeology, climatic condition, land use as well as physical behaviour of water in soil layers and aquifers.

• Economic and Environmental Geology
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• v.41 no.3
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• pp.299-314
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• 2008

The NE-trending Honam shear zone is a broad, dextral strike-slip fault zone between the southern margin of the Okcheon Belt and the Precambrian Yeongnam Massif in South Korea and is parallel to the trend of Sinian deformation that is conspicuous in Far East Asia. In this paper, we report geochemical and isotopic(Sr and Nd) data of mylonitic quartz-muscovite Precambrian gneisses and surrounding foliated hornblende-biotite granitoids near the Myeongho area in the Yecheon Shear Zone, a representative segment of the Honam Shear Zone. Foliated hornblende-biotite granitoids commonly plot in the granodiorite field($SiO_2=61.9-67.1\;wt%$ and $Na_2O+K_2O=5.21-6.99\;wt%$) on $SiO_2$ vs. $Na_2O+K_2O$ discrimination diagram, whereas quartz-muscovite Precambrian orthogneisses plot in the granite field. The foliated hornblende-biotite granitoids are mostly calcic and calc-alkalic and are dominantly magnesian in a modified alkali-lime index(MALI) and Fe# [$=FeO_{total}(FeO_{total}+MgO)$] versus $SiO_2$ diagrams, which correspond with geochemical characteristics of Cordilleran Mesozoic batholiths. The foliated hornblende-biotite granitoids have molar ratios of $Al_2O_3/(CaO+Na_2O+K_2O)$ ranging from 0.89 to 1.10 and are metaluminous to weakly peraluminous, indicating I type. In contrast, Paleoproterozoic orthogneisses have peraluminous compositions, with molar ratios of $Al_2O_3/(CaO+Na_2O+K_2O)$ ranging from 1.11 to 1.22. On trace element spider diagrams normalized to the primitive mantle, the large ion lithophile element(LILE) enrichments(Rb, Ba, Th and U) and negative Ta-Nb-P-Ti anomalies of foliated hornblende-biotite granitoids and mylonitized quartz-muscovite gneisses in the Yecheon Shear Zone are features common to subduction-related granitoids and are also found in granitoids from a crustal source derived from the arc crust of active continental margin. ${\varepsilon}_{Nd}(T)$ and initial Sr-ratio ratios of foliated hornblende-biotite granitoids with suggest the involvement of upper crust-derived melts in granitoid petrogenesis. Foliated hornblende-biotite granitoids in the study area, together with the Yeongju Batholith, show not changing contents of specific elements(Ti, P, Zr, V and Y) from shear zone to the area near the shear zone. These results suggest that no volume changes and geochemical alterations in fluid-rich foliated hornblende-biotite granitoids may occur during deformation, which mass transfer by fluid flow into the shear zone is equal to the mass transfer out of the shear zone.

• Korean Journal of Environmental Biology
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• v.23 no.3 s.59
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• pp.257-268
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• 2005

Meiofauna community was surveyed in the Arctic Ocean. Sediment samples were collected from six stations in the east Barents Sea and from five stations in Kongsfjorden, Svalbard during summer 2002. Eight taxa of meiofauna were identified in the Barents Sea. Meiofauna abundance ranged from 245 to 906 indiv.10 $cm^{-2}$ (mean 580 indiv.10 $cm^{-2}$) and total biomass varied from 23 and 404 ${\mu}gC10cm^{-2}$ (mean 184 ${\mug}C10cm^{-2}$) in the Barent Sea. Nematode predominated in meiofauna comprising $95.2\%$ of total abundance and $66.4\%$ of biomass. Copepods, polycheats and sarcomastigophonans were also dominant in the study area. Nine taxa of meiofauna were identified in Kongsfiorden. Meiofauna abundance ranged from 103 to 513 indiv.10 $cm^{-2}$ (mean 292 indiv.10 $cm^{-2}$) and biomass varied from 13 and 196{\mu}gC10\;cm^{-2}$ (mean 94{\mu}gC10\;cm^{-2}$) in the Kongsfiorden. Nematodes predominated in meiofauna, comprising $64.1\%$ of abundance and $64.3\%$ biomass. Copepods, polychaets, and kinorhyncha were also dominant in the study area. The meiofauna abundances from both the study areas well match with the previous reports from the various regions including the temperate areas. However the occurred taxa in the present study are only a half comparing with the reports from temperate zone. Meiofauna abundance, biomass, diversity index and species richness were much higher than in the coastal which were strongly affected by fresh water run off in the Barents Sea. The stations affected by chlorophyll had high abundance and biomass, but low diversity index and spices richness in Kongsfiorden.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.45-67
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• 2016

Given the recent development of smart devices, users are producing, sharing, and acquiring a variety of information via the Internet and social network services (SNSs). Because users tend to use multiple media simultaneously according to their goals and preferences, domestic SNS users use around 2.09 media concurrently on average. Since the information provided by such media is usually textually represented, recent studies have been actively conducting textual analysis in order to understand users more deeply. Earlier studies using textual analysis focused on analyzing a document's contents without substantive consideration of the diverse characteristics of the source medium. However, current studies argue that analytical and interpretive approaches should be applied differently according to the characteristics of a document's source. Documents can be classified into the following types: informative documents for delivering information, expressive documents for expressing emotions and aesthetics, operational documents for inducing the recipient's behavior, and audiovisual media documents for supplementing the above three functions through images and music. Further, documents can be classified according to their contents, which comprise facts, concepts, procedures, principles, rules, stories, opinions, and descriptions. Documents have unique characteristics according to the source media by which they are distributed. In terms of newspapers, only highly trained people tend to write articles for public dissemination. In contrast, with SNSs, various types of users can freely write any message and such messages are distributed in an unpredictable way. Again, in the case of newspapers, each article exists independently and does not tend to have any relation to other articles. However, messages (original tweets) on Twitter, for example, are highly organized and regularly duplicated and repeated through replies and retweets. There have been many studies focusing on the different characteristics between newspapers and SNSs. However, it is difficult to find a study that focuses on the difference between the two media from the perspective of supply and demand. We can regard the articles of newspapers as a kind of information supply, whereas messages on various SNSs represent a demand for information. By investigating traditional newspapers and SNSs from the perspective of supply and demand of information, we can explore and explain the information dilemma more clearly. For example, there may be superfluous issues that are heavily reported in newspaper articles despite the fact that users seldom have much interest in these issues. Such overproduced information is not only a waste of media resources but also makes it difficult to find valuable, in-demand information. Further, some issues that are covered by only a few newspapers may be of high interest to SNS users. To alleviate the deleterious effects of information asymmetries, it is necessary to analyze the supply and demand of each information source and, accordingly, provide information flexibly. Such an approach would allow the value of information to be explored and approximated on the basis of the supply-demand balance. Conceptually, this is very similar to the price of goods or services being determined by the supply-demand relationship. Adopting this concept, media companies could focus on the production of highly in-demand issues that are in short supply. In this study, we selected Internet news sites and Twitter as representative media for investigating information supply and demand, respectively. We present the notion of News Value Index (NVI), which evaluates the value of news information in terms of the magnitude of Twitter messages associated with it. In addition, we visualize the change of information value over time using the NVI. We conducted an analysis using 387,014 news articles and 31,674,795 Twitter messages. The analysis results revealed interesting patterns: most issues show lower NVI than average of the whole issue, whereas a few issues show steadily higher NVI than the average.

• Journal of Bio-Environment Control
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• v.31 no.3
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• pp.246-254
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• 2022

Domestic facility agriculture grows rapidly, such as modernization and large-scale. And the production scale increases significantly compared to the area, accounting for about 60% of the total agricultural production. Greenhouses require energy input to create an appropriate environment for stable mass production throughout the year, but the energy load per unit area is large because of low insulation properties. Through the rooftop greenhouse, one of the types of urban agriculture, energy that is not discarded or utilized in the building can be used in the rooftop greenhouse. And the cooling and heating load of the building can be reduced through optimal greenhouse operation. Dynamic energy analysis for various environmental conditions should be preceded for efficient operation of rooftop greenhouses, and about 40% of the solar energy introduced in the greenhouse is energy exchange for crops, so it should be considered essential. A major analysis is needed for each sensible heat and latent heat load by leaf surface temperature and evapotranspiration, dominant in energy flow. Therefore, an experiment was conducted in a rooftop greenhouse located at the Korea Institute of Machinery and Materials to analyze the energy exchange according to the growth stage of crops. A micro-meteorological and nutrient solution environment and growth survey were conducted around the crops. Finally, a regression model of leaf temperature and evapotranspiration according to the growth stage of leafy vegetables was developed, and using this, the dynamic energy model of the rooftop greenhouse considering heat transfer between crops and the surrounding air can be analyzed.