• KOREAN JOURNAL OF CROP SCIENCE
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• v.65 no.3
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• pp.172-181
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• 2020

Koshihikari has been one of the most popular rice cultivars with good eating quality since the 1960s despite its susceptibility to blast disease and lodging. To map the genes controlling blast resistance and to develop promising blast-resistant breeding lines inheriting Koshihikari's high eating quality, a recombinant inbred line (RIL) population was developed from a cross between Koshihikari and a blast resistance donor with early maturity, Baegilmi. A total of 394 Koshihikari × Baegilmi RILs (KBRIL), and the two parents, were evaluated for blast resistance and major agronomic traits including heading date, culm length, panicle length, and tiller number. A linkage map encompassing 1,272.7 cM was constructed from a subset of the KBRIL (n = 142) using 130 single nucleotide polymorphisms. Two quantitative trait loci (QTL) for blast resistance, qBL1.1 harboring Pish/Pi35 and qBL2.1 harboring Pib, were mapped onto chromosomes 1 and 2, respectively. qBL1.1 was detected in both of the experimental sites, Namwon and Jeonju, while qBL2.1 was only detected in Namwon. qBL1.1 and qBL2.1 did not affect agronomic traits, including heading date, culm length, panicle length, and tiller number. From the 394 KBRILs, lines that were phenotypically similar to Koshihikari were selected according to heading date and culm length and were further divided into the following two groups based on blast resistance: Koshishikari-type blast resistant lines (KR, n = 15) and Koshishikari-type blast susceptible lines (KS, n = 15). Although no significant differences were observed in the major agronomic traits between the two groups, the KR group produced a greater mean head rice ratio than the KS group. The present study provides useful materials for developing blast-resistant cultivars that inherit both Koshihikari's high eating quality and Baegilmi's blast resistance.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.2
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• pp.132-140
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• 2005

This study was conducted to develop regional site index equations for main tree species in Gangwon, Gyunggi-Chungcheong, Gyungsang, and Jeolla area of Korea, using environmental and soil factors obtained from a digital forest site map. Using the large data set obtained from the digital forest map, a total of 28 environmental and soil factors were regressed on site index by tree species for developing the best site index equations for each of the regions. The selected main tree species were Larix 1eptolepis, Pinus koraiensis, Pinus densiflora, Pinus thunbergii, and Quercus acutissima. Finally, four to five environmental and soil factors by species were chosen as independent variables in defining the best regional site index equations with the highest coefficients of determination $(R^2)$. For those site index equations, three evaluation statistics such as mean difference, standard deviation of difference and standard error of difference were applied to the data sets independently collected from fields within the region. According to the evaluation statistics, it was found that the regional site index equations by species developed in this study conformed well to the independent data set, having relatively low bias and variation. It was concluded that the regional site index equations by species had sufficient capability for the estimation of site productivity.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.73-82
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• 2021

Rural roads are the significant infrastructure for developing and managing the rural areas, hence the utilization of the remote sensing datasets for managing the rural roads is necessary for expanding the rural transportation infrastructure and improving the life quality of the rural residents. In this research, the two different methods such as image classification and image segmentation were compared for mapping the rural road based on the given high-resolution satellite image acquired in the rural areas. In the image classification method, the deep learning with the multiple neural networks was employed to the given high-resolution satellite image for generating the object classification map, then the rural roads were mapped by extracting the road objects from the generated object classification map. In the image segmentation method, the multiresolution segmentation was employed to the same satellite image for generating the segment image, then the rural roads were mapped by merging the road objects located on the rural roads on the satellite image. We used the 100 checkpoints for assessing the accuracy of the two rural roads mapped by the different methods and drew the following conclusions. The image segmentation method had the better performance than the image classification method for mapping the rural roads using the give satellite image, because some of the rural roads mapped by the image classification method were not identified due to the miclassification errors occurred in the object classification map, while all of the rural roads mapped by the image segmentation method were identified. However some of the rural roads mapped by the image segmentation method also had the miclassfication errors due to some rural road segments including the non-rural road objects. In future research the object-oriented classification or the convolutional neural networks widely used for detecting the precise objects from the image sources would be used for improving the accuracy of the rural roads using the high-resolution satellite image.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.2
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• pp.88-99
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• 2019

This study aims to conduct a depth analysis of motivation and value of local residents and tourists based on means-end chain theory. The sampling of the study was conducted on local residents living near downtown area of Gyeong-ju City, and tourists through soft laddering and hard laddering methods. A mutual correlation model in relation with Hierarchical Value Map (HVM) for each group by conducting the analysis of factor loading (attributes, consequences, value) and cognitive structure (the correlations among attributes, consequences and value) was proposed and the comparisons of HVM for each group was also conducted. The structured questionnaires using Association Pattern Technique (APT) of hard laddering were utilized to analyze the means and end of value chain structures in terms of the attributes, consequences, value of Gyeong-ju Ancient Tombs. The findings propose that local residents are visiting Ancient Tombs Gyeong-ju City Center for 'Rest and take a walk' as the means, which results in 'Relieving stress' and eventually leads to the 'Improvement of historic and cultural cultivation' as the end. On the other hand, tourists also 'Rest and take a walk' as the mean, which also leads to 'Relieving stress'. However, unlike local residents, it eventually leads to 'Self-reflection and healing' as the end. It is expected that the findings of this study not only recommend us to consider preserving and managing cultural heritages and value of ancient tombs in developing "Ancient Tomb Park in Gyoneg-ju City Center" but also provides baseline data for the establishment of reasonable plans of utilizing tombs, historical and cultural heritages.

• Journal of Global Scholars of Marketing Science
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• v.19 no.3
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• pp.49-61
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• 2009

This article provides training exercises for executives into interpreting subroutine maps of executives' thinking in processing business and industrial marketing problems and opportunities. This study builds on premises that Schank proposes about learning and teaching including (1) learning occurs by experiencing and the best instruction offers learners opportunities to distill their knowledge and skills from interactive stories in the form of goal.based scenarios, team projects, and understanding stories from experts. Also, (2) telling does not lead to learning because learning requires action-training environments should emphasize active engagement with stories, cases, and projects. Each training case study includes executive exposure to decision system analysis (DSA). The training case requires the executive to write a "Briefing Report" of a DSA map. Instructions to the executive trainee in writing the briefing report include coverage in the briefing report of (1) details of the essence of the DSA map and (2) a statement of warnings and opportunities that the executive map reader interprets within the DSA map. The length maximum for a briefing report is 500 words-an arbitrary rule that works well in executive training programs. Following this introduction, section two of the article briefly summarizes relevant literature on how humans think within contexts in response to problems and opportunities. Section three illustrates the creation and interpreting of DSA maps using a training exercise in pricing a chemical product to different OEM (original equipment manufacturer) customers. Section four presents a training exercise in pricing decisions by a petroleum manufacturing firm. Section five presents a training exercise in marketing strategies by an office furniture distributer along with buying strategies by business customers. Each of the three training exercises is based on research into information processing and decision making of executives operating in marketing contexts. Section six concludes the article with suggestions for use of this training case and for developing additional training cases for honing executives' decision-making skills. Todd and Gigerenzer propose that humans use simple heuristics because they enable adaptive behavior by exploiting the structure of information in natural decision environments. "Simplicity is a virtue, rather than a curse". Bounded rationality theorists emphasize the centrality of Simon's proposition, "Human rational behavior is shaped by a scissors whose blades are the structure of the task environments and the computational capabilities of the actor". Gigerenzer's view is relevant to Simon's environmental blade and to the environmental structures in the three cases in this article, "The term environment, here, does not refer to a description of the total physical and biological environment, but only to that part important to an organism, given its needs and goals." The present article directs attention to research that combines reports on the structure of task environments with the use of adaptive toolbox heuristics of actors. The DSA mapping approach here concerns the match between strategy and an environment-the development and understanding of ecological rationality theory. Aspiration adaptation theory is central to this approach. Aspiration adaptation theory models decision making as a multi-goal problem without aggregation of the goals into a complete preference order over all decision alternatives. The three case studies in this article permit the learner to apply propositions in aspiration level rules in reaching a decision. Aspiration adaptation takes the form of a sequence of adjustment steps. An adjustment step shifts the current aspiration level to a neighboring point on an aspiration grid by a change in only one goal variable. An upward adjustment step is an increase and a downward adjustment step is a decrease of a goal variable. Creating and using aspiration adaptation levels is integral to bounded rationality theory. The present article increases understanding and expertise of both aspiration adaptation and bounded rationality theories by providing learner experiences and practice in using propositions in both theories. Practice in ranking CTSs and writing TOP gists from DSA maps serves to clarify and deepen Selten's view, "Clearly, aspiration adaptation must enter the picture as an integrated part of the search for a solution." The body of "direct research" by Mintzberg, Gladwin's ethnographic decision tree modeling, and Huff's work on mapping strategic thought are suggestions on where to look for research that considers both the structure of the environment and the computational capabilities of the actors making decisions in these environments. Such research on bounded rationality permits both further development of theory in how and why decisions are made in real life and the development of learning exercises in the use of heuristics occurring in natural environments. The exercises in the present article encourage learning skills and principles of using fast and frugal heuristics in contexts of their intended use. The exercises respond to Schank's wisdom, "In a deep sense, education isn't about knowledge or getting students to know what has happened. It is about getting them to feel what has happened. This is not easy to do. Education, as it is in schools today, is emotionless. This is a huge problem." The three cases and accompanying set of exercise questions adhere to Schank's view, "Processes are best taught by actually engaging in them, which can often mean, for mental processing, active discussion."

• Journal of the Korean Society of Environmental Restoration Technology
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• v.17 no.5
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• pp.29-41
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• 2014

Ecosystem services provide various benefits to human beings, but are considered to be free of cost. To protect ecosystems in an economically sustainable way, several developing countries have adopted a policy known as the Payment for Ecosystem Services (PES) that compensates upstream services with monetary incentives collected from service users. Vietnam is one of the countries that have enacted a nationwide PES policy. However, the policy in Vietnam requires further development in order to evaluate the spatial priority zones based on the quantification of ecosystem services. To obtain a recent and high-quality land cover map, we first classified the land cover in the Da River basin, in northern Vietnam, using Landsat dataset. We then applied a water balance theory and an USLE equation to assess hydrological ecosystem services concerning water supply and sediment retention. Following the assessment, we identified the priority areas for hydrological ecosystem services exclusively for forest environments. We found that the quantity and distribution of services from forests varied, due to the topography, climate, and land cover. According to a quantile distribution, Mt. Phu Luong, Mt. Fansipan, and Hoang Lien National Park were evaluated as high service areas in terms of both water yield and sediment retention. As a result, this assessment method can help construct spatial priority zones concerning ecosystem service distribution, and can also contribute to benefit sharing by indicating which forest and landowners require compensation.

• Journal of Korean Society of Forest Science
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• v.98 no.4
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• pp.409-416
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• 2009

Forest biomass estimation is essential for greenhouse gas inventories and terrestrial carbon accounting. Remote sensing allows for estimating forest biomass over a large area. This study was conducted to estimate forest biomass and to produce a forest biomass map for Muju county using forest biomass conversion table developed by field plot data from the 5th National Forest Inventory and Landsat TM-5. Correlation analysis was carried out to select suitable independent variables for developing regression models. It was resulted that the height class, crown closure density, and age class were highly correlated with forest biomass. Six regression models were used with the combination of these three stand variables and verified by validation statistics such as root mean square error (RMSE) and mean bias. It was found that a regression model with crown closure density and height class (Model V) was better than others for estimating forest biomass. A biomass conversion table by model V was produced and then used for estimating forest biomass in the study site. The total forest biomass of the Muju county was estimated about 8.8 million ton, or 128.3 ton/ha by the conversion table.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.1
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• pp.125-137
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• 2008

This research aims to produce basic data for developing habitat suitability models on the breeding sites of Oriental White Storks(Ciconia boyciana) which will be reintroduced to the wild in the future. The habitat characteristics of ten historical nesting sites of the Oriental White Storks at Gyeonggi and Chungcheong provinces in South Korea were analyzed with 1970's land use maps and Landsat MSS. The range of altitude on nesting sites was 40~116.38m. The mean distance from nesting sites to rice fields, to 30m wider river, and to reservoirs was $54.8{\pm}84.48m$, $869.8{\pm}708.01m$, and $1721.2{\pm}906.05m$ respectively. Historical nesting sites were located close to human settlements, and the mean distance of nesting sites to human settlements was $144.1{\pm}182.97m$. The land types within 5km radius from ten historical nesting sites consisted of 53.7% forest, 28.3% rice fields, 16.7% grasslands, 0.8% water bodies, and 0.6% human settlements. The composition of four land types(forest, rice fields, grasslands, and human settlements) was significantly differed between 93 random points and 10 historical nesting sites.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.3B
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• pp.193-201
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• 2012

In the last decade, heavy rainfall induced debris flow events have been remarkably occurred in Korea. Consequently, debris flow is becoming one of the most dangerous natural phenomena in mountainous area. Understanding and correct predicting of the runout distance of debris flow is an essential prerequisite for developing debris flow hazard map and prevention technology. Based on the simple and widely used sled model, in this study, we analyse the net efficiency of debris flows which is a dimensionless constant (=1/R) and defined by the ratio of the horizontal runout distance L from the debris flow source to deposit and the vertical elevation H of the source above the deposit. The analysis of field data observed in total 238 debris flow events occurred from 2002 to 2011 reveals that the representative value of the net efficiency of debris flows in Korea is 4.3. The data observed in Gangwon province where is the most debris flow-prone area in Korea shows that debris flows in Inje area have the runout distance longer than those in Pyongchang and Gangneung. Overall features of the net efficiency of debris flows observed in the central Korea are similar to those in the southern Korea. The estimation based on aerial photographs and available depositional conditions appears to overestimate the net efficiency compared to estimation based on the field observations, which indicates that appropriate depositional conditions need to be developed for debris flows in Korea.