• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• Journal of The Korean Association For Science Education
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• v.42 no.3
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• pp.325-340
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• 2022

This study attempts to analyze the causes of low affective achievement of elementary, middle, and high school students in Korea in science. To this end, a total of 27 students, three to four students per grade, were interviewed by grade from the fourth grade of elementary school to the first grade of high school, and a total of nine teachers were interviewed by school level. In the interview, related questions were asked in five sub-areas of the 'Indicators of Positive Experiences about Science': 'Science Academic Emotion', 'Science-Related Self-Concept', 'Science Learning Motivation', 'Science-Related Career Aspiration', and 'Science-Related Attitude'. Interview contents were recorded, transcribed, and categorized. As a result of examining the causes of low science academic emotion, it was found that students experienced negative emotions when experiments are not carried out properly, scientific theories and terms are difficult, and recording the inquiry results is burdensome. In addition, students responded that science-related self-concept changed negatively due to poor science grades, difficult scientific terms, and a large amount of learning. The reasons for the decline in science learning motivation were the lack of awareness of relationship between science class content and daily life, difficulty in science class content, poor science grades, and lack of relevance to one's interest or career path. The main reason for the decline in science-related career aspirations was that they feel their career path was not related to science, and due to poor science performance. Science-related attitudes changed negatively due to difficulties in science classes or negative feelings about science classes, and high school students recognized the ambivalence of science on society. Based on the results of the interview, support for experiments and basic science education, improvement of elementary school supplementary textbook 'experiment & observation', development of teaching and learning materials, and provision of science-related career information were proposed.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.627-646
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• 2022

Recently, the seriousness of climate change-related problems caused by global warming is growing, and the average temperature is also rising. As a result, it is affecting the environment in which various temperature-sensitive creatures and creatures live, and changes in the ecosystem are also being detected. Seasons are one of the important factors influencing the types, distribution, and growth characteristics of creatures living in the area. Among the most popular and easily recognized plant seasonal phenomena among the indicators of the climate change impact evaluation, the blooming day of flower and the peak day of autumn leaves were modeled. The types of plants used in the modeling were forsythia and cherry trees, which can be seen as representative plants of spring, and maple and ginkgo, which can be seen as representative plants of autumn. Weather data used to perform modeling were temperature, precipitation, and solar radiation observed through the ASOS Observatory of the Korea Meteorological Administration. As satellite data, MODIS NDVI was used for modeling, and it has a correlation coefficient of about -0.2 for the flowering date and 0.3 for the autumn leaves peak date. As the model used, the model was established using multiple regression models, which are linear models, and Random Forest, which are nonlinear models. In addition, the predicted values estimated by each model were expressed as isopleth maps using spatial interpolation techniques to express the trend of plant seasonal changes from 2003 to 2020. It is believed that using NDVI with high spatio-temporal resolution in the future will increase the accuracy of plant phenology modeling.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.4
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• pp.63-76
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• 2022

This study was conducted to compare the perceptions of the park use status, importance, and satisfaction of users in the first implemented and completed Uijeongbu Jikdong Neighborhood Park among the private park special projects carried out as a countermeasure for long-term non-execution of urban parks. To this end, in the initiated project, apartment residents and non-residents were classified according to the promotion plan, and a questionnaire research on importance and satisfaction was conducted to analyze the park use status and IPA(importance-performance analysis). First, as a result of the analysis of the current situation in terms of locational characteristics that occur during the promotion of special projects for private parks, unlike the mountainous areas, the targeted site was close to flat land, indicating that users' satisfaction with the landscape was high. Second, the access of the apartment residents in the initiated project site was easy. Thus, the use rate of residents was relatively higher than that of the non-residents. Third, differences in perception by item were identified through the analysis of IPA and the establishment of strategies. In quadrant I, among the facilities and services, installing restrooms was the priority for residents, and parking facilities and rest facilities were the priority than installing restrooms for non-residents. In quadrant II, overall scores for residents and non-residents were similar, but the distance to the park was in quadrant III due to the low level of satisfaction among non-residents. In this study, the difference in perception between residents and non-residents may cause problems in access and facilities in managing the park in the future. Therefore, it would be necessary to find a way to improve it by establishing a management strategy that takes into account the difference in the perception of residents after construction. In addition, through the results of this study, it was judged that the purpose of park development, the selection of types of parks, and the selection of plans and management indicators for each kind would be significant in the promotion of initiated projects in the planning of park development.

• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.419-429
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• 2023

The objective of this study was to determine the management water level of an estuary reservoir considering three aspects: the water use, flood control and water quality, and to use a robust decision-making to consider uncertainty due to climate change. The watershed-reservoir linkage model was used to simulate changes in inflow due to climate change, and changes in reservoir water level and water quality. Five management level alternatives ranging from -1.7 El.m to 0.2 El.m were evaluated under the SSP1, 2, 3, and 5 scenariosof the ACCESS-CM2 Global Climate Model. Performance indicators based on period-reliability were calculated for robust decision-making considering the three aspects, and regret was used as a decision indicator to identify the alternatives with the minimum maximum regret. Flood control failure increased as the management level increased, while the probability of water use failure increased as the management level decreased. The highest number of failures occurred under the SSP5 scenario. In the water quality sector, the change in water quality was relatively small with an increase in the management level due to the increase in reservoir volume. Conversely, a decrease in the management level resulted in a more significant change in water quality. In the study area, the estuary reservoir was found to be problematic when the change in water quality was small, resulting in more failures.

• Korean Journal of Environmental Biology
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• v.41 no.1
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• pp.18-30
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• 2023

Forest destruction is an inevitable result of the development processes. According to the environmental impact assessment, over 10% of the destroyed trees need to be recycled and transplanted to minimize the impact of forest destruction. However, the rate of successful transplantation is low, leading to a high rate of tree death. This is attributable to a lack of consideration for environmental factors when choosing a temporary site for transplantation and inadequate management. To monitor transplanted trees, a field survey is essential; however, the spatio-temporal aspect is limited. This study evaluated the applicability of remote sensing for the effective monitoring of transplanted trees. Vegetation indices based on satellite remote sensing were derived to detect time-series changes in the status of the transplanted trees at three temporary transplantation sites. The mortality rate and vitality of transplanted trees before and after the transplant have a similar tendency to the changes in the vegetation indicators. The findings of this study showed that vegetation indices increased after transplantation of trees and decreased as the death rate increased and vitality decreased over time. This study presents a method for assessing newly transplanted trees using satellite images. The approach of utilizing satellite photos and the vegetation index is expected to detect changes in trees that have been transplanted across the country and help to manage tree transplantation for the environmental impact assessment.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.19-19
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• 2022

Hulled and naked oat is a perspective crop for the low input production systems due to its low requirements for soil quality and nutrition. Oats have good competitive ability against weeds and can provide appropriate yield in organic farming in comparison with other cereal species such as wheat or barley. It is a perspective crop from the point of view of use in the food industry too. The aim of our study was to compare the production and quality parameters of naked and hulled oat grown in both organic (OF) and conventional fields (CF). Small plot trials were conducted in two locations in the Czech Republic (České Budějovice, Prague) for four years (2018-2021) in two production systems (OF, and CF). We used four varieties of hulled oat (Korok, Kertag, Raven, Seldon) and one variety of naked oat (Patrik). During the vegetation, agronomically important data were recorded. After harvest samples were processed in the laboratory and analyzed selected quality parameters of grain dry matter (the protein content was determined by the Kjeldahl method, starch content in grain according to Ewers, fat content in grain dry matter by the modified method according to Soxhlet, and ash content in grain dry matter). The data were evaluated using the program STATISTICA version 13.2, StatSoft, Inc., California, USA. It is clear from the results that the number of panicles before the harvest was influenced by the location, cultivation system, year, and, to a lesser extent, the influence of the variety. The number of panicles in OF averaged 340 per square meter, which was 90% of the value of CF. For thousand grain weight (TGW), a significantly predominant effect of year was found. The independent effect of location on TGW was statistically not significant. Grain yield was predominantly influenced by cultivation system and location. In OF, it reached an average of 3.97 t.ha^-1, which was 75% of the yield of CF. As part of the evaluation of the basic grain quality indicators, the content of protein, starch, fat, and ash in the dry matter of the grain was evaluated. The content of protein in the dry matter of the grain was predominantly influenced by year, followed by the influence of the variety and a fairly comparable influence of the cultivation system and locality. On average, it achieved 16.05% in OF and 17.01% in CF. The starch content was then related to the protein content, where as a result of the lower protein content in the grain of OF oats, the content of starch and fat was on the contrary increased. The year turned out to be the most significant factor, affecting both the starch content in the dry matter of the grain and the fat content. This was followed again by a fairly comparable influence on the cultivation system and locality. The influence of the cultivation system and location was not statistically significantly applied in the case of ash content in dry matter. Based on our results we can propose both types of oat (hulled and naked) as perspective crops for OF. An organic farmer can expect to achieve stable yields which, in less favorable conditions for the production of cereals in the OF, may be close to the level of conventional yields. In the future, it will be important to change agrotechnology in OF and increase oat yield because this crop has a good potential to grow in areas with low nitrogen input or less fertile soil.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.655-667
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• 2023

Algal bloom outbreaks are frequently reported around the world, and serious water pollution problems arise every year in Korea. It is necessary to protect the aquatic ecosystem through continuous management and rapid response. Many studies using satellite images are being conducted to estimate the concentration of chlorophyll-a (Chl-a), an indicator of algal bloom occurrence. However, machine learning models have recently been used because it is difficult to accurately calculate Chl-a due to the spectral characteristics and atmospheric correction errors that change depending on the water system. It is necessary to consider the factors affecting algal bloom as well as the satellite spectral index. Therefore, this study constructed a dataset by considering water quality, hydrological and meteorological factors, and sentinel-2 images in combination. Representative ensemble models random forest and extreme gradient boosting (XGBoost) were used to predict the concentration of Chl-a in eight weirs located on the Nakdong river over the past five years. R-squared score (R²), root mean square errors (RMSE), and mean absolute errors (MAE) were used as model evaluation indicators, and it was confirmed that R² of XGBoost was 0.80, RMSE was 6.612, and MAE was 4.457. Shapley additive expansion analysis showed that water quality factors, suspended solids, biochemical oxygen demand, dissolved oxygen, and the band ratio using red edge bands were of high importance in both models. Various input data were confirmed to help improve model performance, and it seems that it can be applied to domestic and international algal bloom detection.

• Journal of Venture Innovation
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• v.6 no.4
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• pp.41-62
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• 2023

Given that SME workers are the driving force of national competitiveness and the basis and cornerstone of the industry, it is meaningful to study workers' job satisfaction and the factors that affect job satisfaction. In addition to variables related to corporate competitiveness and organizational justice, this study introduced variables such as environmental(E) activities, social(S) activities, and governance(G) activities, which th national government uses as major management evaluation indicators. Therefore, a literature study and empirical analysis were conducted on how self-efficacy affects job satisfaction when workers are faced with a changed work environment. To conduct this study, 300 copies of data were collected from workers in small and medium-sized enterprises and used for analysis. For data analysis, the SPSS statistical program (Ver. 25.0) was used. The study finds, first, that product or service quality and employee competency among corporate competitiveness had a significant positive(+) effect on job satisfaction. Secondly, among ESG management activities, social(S) activities and governance(G) activities were found to have a significant positive(+) effect on job satisfaction. Third, among organizational justice, distribution justice and procedural justice were found to have a positive(+) effect on job satisfaction. Fourth, self-efficacy was found to mediate the effect of product or service quality, employee competency, social(S) and governance(G) activities among ESG management activities, and procedural justice among organizational justice on job satisfaction. The academic value of this study is that it empirically analyzed the factors that ESG management activities affect workers' jobs,. As a result, it was confirmed that workers were satisfied with their jobs by actively showing interest in social(S) activities and governance(G) activities among ESG management activities and participating in corporate management. In addition, workers sensitive to changes in the external environment can become satisfied with their jobs through self-efficacy when SMEs actively enhance corporate competitiveness, execute ESG management activities, and provide a fair organizational culture. Finally, this study suggests that there's a possibility of improving the competitiveness of SMEs through a virtuous cycle created by a change in perception of job conversion and a decrease in turnover.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.37-50
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• 2023

Venture capital invests the necessary capital and supports management and technology in promising small and medium-sized venture companies in the early stages of start-up with promising technology and excellent manpower. It plays a role as a key player in the venture ecosystem that realizes profits by collecting the investment through various means after growth. Venture capital's job is to recruit various investors(LPs) to invest in small and medium-sized venture companies with growth potential through the formation of venture investment funds, and to collect investment as companies grow, distribute and reinvest. The main tasks of venture capitalists, which play the most important role in venture investment, are finding promising companies, corporate analysis and evaluation, investment screening, follow-up management, and investment recovery. Venture capital's success indicators are fund formation and return on investment, and venture capitalists are rewarded with annual salary, performance-based incentive, and promotion with work performance such as investment, exit, and fund formation. Compared to the recent rapidly growing venture investment market, investment manpower is insufficient, and venture capital is making great efforts to foster manpower and establish infrastructure and systems for long-term service, but research has been conducted mainly from a quantitative perspective. Accordingly, this study aims to empirically analyzed the impact of investment experience, delegation of authority, job fit, and peer relationships on fund formation and return on investment according to the characteristics of the venture capital industry. The results of these empirical studies suggested that future venture capital needs a job environment and manpower operation strategy so that venture capitalists with high job fit and investment experience can work for a long time.