• 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 Applied Science and Technology
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• v.38 no.1
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• pp.318-331
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• 2021

This study was conducted on the assumption that bone age would be more effective when it comes to physique and physical fitness assessment for adolescents, and the purpose of this study was to identify the differences in physique and physical fitness for students in their adolescence through bone age and chronological age in order to contribute to the well-balanced physique and physical fitness development in adolescents and the health improvement in students. Total 874 adolescents(483 males, 391 females) aged 11~16 were selected as subjects out of the total population of 1100 adolescents aged 6~16 based on the PAPS(Physical Activity Promotion System) and age standards of the TW3 method; and skeletal maturation, which symbolize the indicators of biological maturation, were evaluated by using the TW3(Tanner-Whitehouse 3) method after hand-wrist radiographs, and birth date was used for chronological age. A stadiometer and InBody 270 (Biospace, Korea) were used to measure 2 components in physique. A total of 7 components in physical fitness, which included muscular strength, muscular endurance, flexibility, power, cardiovascular endurance, balance, agility, were measured as well. A independent samples t-test was conducted for data processing using SPSS 25.0, and the significance level was set at p< .05. The study results are as follows. First, bone age and chronological age used for physique comparison in males aged 11 and 12, height and weight showed significant difference; in males aged 13, weight showed signicant difference. Weight and height in females aged 11, and height in females aged 12 showed significant difference. Second, bone age and chronological age used for physical fitness comparison in males aged 11, muscular strength, power, flexibility, cardiovascular endurance showed significant difference; in males aged 12, muscular strength. power, cardiovascular endurance; in males aged 13, flexibility showed significant difference. Muscular strength, power, flexibility, muscular endurance, cardiovascular endurance in females aged 11, and flexibility in females aged 14 showed significant difference. As a result, this study concluded that in a period of rapid skeletal growth, evaluating physique and physical fitness based on bone age is more accurate than evaluating based on chronological age.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.26 no.3
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• pp.263-276
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• 2021

Marine benthic organisms have been used as the indicators for the environment assessment and recently considered as a very important component in the biodiversity and ecosystem restoration. In Korean waters, the quantitative data on marine benthos was used as one of major components for the marine pollution assessment for 50 years since 1970s. The species identification which is an important factor for the quantitative biological data was mainly performed by the marine benthic ecologists. This leads to the deterioration of the data quality on marine benthos from the misidentication of major taxonomic groups due to the lack of taxonomic expertise in Korea. This taxonomic problem has not been solved until now and remains in most data from national research projects on the marine ecosystems in Korean waters. Here we introduce the quality assurance and control (QA/QC) system for the marine biological data in UK, that is, NMBAQC (Northeast Atlantic Marine Biological Analytic and Quality Control) Scheme which has been performed by private companies to solve similar species identification problems in UK. This scheme asks for all marine laboratories which want to participate to any national monitoring programs in UK to keep their identification potency at high level by the internal quality assurance systems and provides a series of taxonomic workshops and literature to increase their capability. They also performs the external quality control for the marine laboratories by performing the Ring Test using standard specimens on various faunal groups. In the case of Korea, there are few taxonomic expertise in two existing national institutions and so they can't solve the taxonomic problems in marine benthic fauna data. We would like to provide a few necessary suggestions to solve the taxonomic problems in Korean marine biological data in short-terms and long-terms: (1) the identification of all dominant species in marine biological data should be confirmed by taxonomic expertise, (2) all the national research programs should include taxonomic experts, and (3) establishing a private company, like the Korea marine organism identification association (KMOIA), which can perform the QA/QC system on the marine organisms and support all Korean marine laboratories by providing taxonomic literature and species identification workshops to enhance their potency. The last suggestion needs more efforts and time for the establishment of that taxonomic company by gathering the detailed contents and related opinions from diverse stakeholders in Korea.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.265-282
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• 2022

Sea surface temperature (SST) is a factor that greatly influences ocean circulation and ecosystems in the Earth system. As global warming causes changes in the SST near the Korean Peninsula, abnormal water temperature phenomena (high water temperature, low water temperature) occurs, causing continuous damage to the marine ecosystem and the fishery industry. Therefore, this study proposes a methodology to predict the SST near the Korean Peninsula and prevent damage by predicting abnormal water temperature phenomena. The study area was set near the Korean Peninsula, and ERA5 data from the European Center for Medium-Range Weather Forecasts (ECMWF) was used to utilize SST data at the same time period. As a research method, Long Short-Term Memory (LSTM) algorithm specialized for time series data prediction among deep learning models was used in consideration of the time series characteristics of SST data. The prediction model predicts the SST near the Korean Peninsula after 1- to 7-days and predicts the high water temperature or low water temperature phenomenon. To evaluate the accuracy of SST prediction, Coefficient of determination (R²), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) indicators were used. The summer (JAS) 1-day prediction result of the prediction model, R²=0.996, RMSE=0.119℃, MAPE=0.352% and the winter (JFM) 1-day prediction result is R²=0.999, RMSE=0.063℃, MAPE=0.646%. Using the predicted SST, the accuracy of abnormal sea surface temperature prediction was evaluated with an F1 Score (F1 Score=0.98 for high water temperature prediction in summer (2021/08/05), F1 Score=1.0 for low water temperature prediction in winter (2021/02/19)). As the prediction period increased, the prediction model showed a tendency to underestimate the SST, which also reduced the accuracy of the abnormal water temperature prediction. Therefore, it is judged that it is necessary to analyze the cause of underestimation of the predictive model in the future and study to improve the prediction accuracy.

• 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.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.40 no.1
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• pp.74-80
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• 2022

The vegetation of historical sites has been a form of vegetation that has remained since some years ago, but in modern times, vegetation and terrain have been deformed or damaged due to urban development, which was followed by an industrialization. As a solution to this, it is necessary to establish a plan for restoration and management by referring to the vegetation and landscape remaining in the historic site as indicators. This study was conducted to provide basic data for vegetation and landscape management of Baekje Historic Sites in Seoul by comparing and analyzing location characteristics, existing vegetation, and remaining vegetation of past substitutional vegetation for Pungnaptoseong and Mongchontoseong, Baekje Historic Sites in Seoul. As a result of the study, Pungnaptoseong and Mongchontoseong are located near the main stream of the Han River, Pungnaptoseong is located on a flat land consisting of natural embankments and floodplains, and Mongchontoseong is located on a hilly area. In the case of existing vegetation, it has been confirmed that Pungnaptoseong mainly has ornamental trees planting sites, while Mongchontoseong has a distribution of residual species from the past that grow in villages and hilly lowlands. The Substitutional vegetation of Pungnaptoseong and Mongchontoseong was synthesized based on the location characteristics and actual vegetation, it is estimated that the hilly areas may have been divided into "Quercus aliena Blume.", "Quercus mongolica Fisch. ex Ledeb." and so on, "Pinus densiflora Siebold & Zucc." on dry land,"Salix koreensis Andersson.", "Juglans mandshurica Maxim.", "Alnus japonica (Thunb.) Steud." in rivers and tributaries, "Quercus acutissima Carruth." in the main part of the forest, "Pinus densiflora Siebold & Zucc.", "Salix koreensis Andersson.", "Zelkova serrata (Thunb.) Makino." as a divine tree in the beginning of the village. Since the 1960s, all substitutional vegetation in the past has disappeared due to the introduction of foreign species and the creation of urban areas in Pungnaptoseong and Mongchontoseong, and the landscape has also been damaged. Fortunately, the substitutional vegetation was estimated in consideration of the species of residual trees distributed along the walls, climate, location characteristics, and times, but this study was conducted based on literature and existing vegetation surveys. Therefore, it is necessary to supplement the past target vegetation in Baekje historical sites in Seoul through quantitative experiments such as plant relic analysis in the future.

• Journal of the Korean Orthopaedic Association
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• v.56 no.4
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• pp.334-340
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• 2021

Purpose: This study analyzed the bone mineral densities of the lumbar vertebrae and femurs of patients with ankle fractures to determine the correlation between ankle fractures and osteoporosis. Materials and Methods: From April 2002 to July 2014, one hundred consecutive ankle fracture patients with bone mineral density tests performed within post-traumatic one year were enrolled. The patients were divided into three age groups according to their age at the time of injury (group 1: <50, group 2: 50-69, group 3: ≥70). The types of ankle fractures were classified into unimalleolar, bimalleolar and trimalleolar fractures. The bone mineral density was analyzed using the T score, Z score, absolute value (g/cm²) of the lumbar spine (L1-L4), femur neck, femur intertrochanter, and total femur. Results: There were 3.2 times more females with ankle fractures than males, and the prevalence of osteoporosis according to age group was 0% in the group under 50 years, 24.2% in the 50 to 69-year-old group, and 15% in the group over 70 years. Osteoporosis was found in 30% of patients with a trimalleolar fracture in the 50 to 69-year-old group. In all patient groups, a lower age indicated a higher frequency of unimalleolar fractures. The relationship between the bone mineral density and the type of fracture is that the frequency of trimalleolar fracture increased with decreasing T score of the lumbar vertebrae and the absolute value of bone mineral density (g/cm²) and the Z score of the femur neck, but there were no other indicators. Conclusion: Among the 100 patients with ankle fractures, females were more common than males, because osteoporosis was less severe in males. The incidence of unimalleolar fracture was higher than that of trimalleolar fracture. On the other hand, the correlation between the ankle fractures and the bone mineral density of the femur and lumbar spine was not significant.

• 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.

• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.179-193
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• 2021

This study examines the use of satellite images for river classification and determination of stream reach, which is the first priority in the river environment assessment system. In the river environment assessment system used in South Korea, it is proposed to set a stream reach by using 10 or 25 times the width of the river based on the result of river classification. First, river classification for the main stream section of Cheongmi stream was performed using various river-related data. The maximum likelihood method was applied for land cover classification. In this study, Sentinel-2 satellite imagery, which is an open data technology with a resolution of 10 m, was used. A total of four satellite images from 2018 was used to consider various flow conditions: February 2 (daily discharge = 2.39 m³/s), May 23 (daily discharge = 15.51 m³/s), June 2 (daily discharge = 3.88 m³/s), and July 7 (daily discharge = 33.61 m³/s). The river widths were estimated from the result of land cover classification to determine stream reach. The results of the assessment reach classification were evaluated using indicators of stream physical environments, including pool diversity, channel sinuosity, and river crossing shape and structure. It is concluded that appropriate flow conditions need to be considered when using satellite images to set up assessment segments for the river environment assessment system.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.101-119
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• 2022

Existing algal bloom monitoring is based on field sampling, and there is a limit to understanding the spatial distribution of algal blooms, such as the occurrence and spread of algae, due to local investigations. In this study, algal bloom monitoring was performed using an unmanned aerial vehicle and multispectral sensor, and data on the distribution of algae were provided. For the algal bloom monitoring site, data were acquired from the Mulgeum·Mae-ri site located in the lower part of the Nakdong River, which is the areas with frequent algal bloom. The Chlorophyll-a(Chl-a) value of field-collected samples and the Chl-a estimation formula derived from the correlation between the spectral indices were comparatively analyzed. As a result, among the spectral indices, Maximum Chlorophyll Index (MCI) showed the highest statistical significance(R²=0.91, RMSE=8.1mg/m³). As a result of mapping the distribution of algae by applying MCI to the image of August 05, 2021 with the highest Chl-a concentration, the river area was 1.7km², the Warning area among the indicators of the algal bloom warning system was 1.03km²(60.56%) and the Algal Bloom area occupied 0.67km²(39.43%). In addition, as a result of calculating the number of occurrence days in the area corresponding to the "Warning" in the images during the study period (July 01, 2021~November 01, 2021), the Chl-a concentration above the "Warning" level was observed in the entire river section from 12 to 19 times. The algal bloom monitoring method proposed in this study can supplement the limitations of the existing algal bloom warning system and can be used to provide information on a point-by-point basis as well as information on a spatial range of the algal bloom warning area.