• Journal of the Korean Society of Environmental Restoration Technology
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• v.18 no.2
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• pp.79-88
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• 2015

Preparations need to be made for Korean pine(Pinus koraiensis) in anticipation of climate change because Korean pine is an endemic species of South Korea and the source of timber and pine nut. Therefore, climate change adaptation policy has been established to conduct an impact assessment on the distribution of Korean pine. Our objective was to predict the distribution of Korean pine while taking into account uncertainty and afforestation conditions. We used the 5th forest types map, a forest site map and BIOCLIM variables. The climate scenarios are RCP 4.5 and RCP 8.5 for uncertainty and the climate models are 5 regional climate models (HadGEM3RA, RegCM4, SNURCM, GRIMs, WRF). The base period for this study is 1971 to 2000. The target periods are the mid-21st century (2021-2050) and the end of the 21st century (2071-2100). This study used the MaxEnt model, and 50% of the presences were randomly set as training data. The remaining 50% were used as test data, and 10 cross-validated replicates were run. The selected variables were the annual mean temperature (Bio1), the precipitation of the wettest month (Bio13) and the precipitation of the driest month (Bio14). The test data's ROC curve of Korean pine was 0.689. The distribution of Korean pine in the mid-21st century decreased from 11.9% to 37.8% on RCP 4.5 and RCP 8.5. The area of Korean pine at an artificial plantation occupied from 32.1% to 45.4% on both RCPs. The areas at the end of the 21st century declined by 53.9% on RCP 4.5 and by 86.0% on RCP 8.5. The area of Korean pine at an artificial plantation occupied 23.8% on RCP 4.5 and 7.2% on RCP 8.5. Private forests showed more of a decrease than national forests for all subsequent periods. Our results may contribute to the establishment of climate change adaptation policies for considering various adaptation options.

• Journal of Korea Water Resources Association
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• v.42 no.5
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• pp.397-406
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• 2009

River is able to change by various environmental factors. In order to conduct restoration design of abandoned river channels, it is necessary to evaluate the river through the analysis of past and present river channels. River evaluation requires various data, such as geometry, hydraulic and hydrology, but there is a lot of difficulty to understand topographical information of river change on time and space due to a lack of past data by domestic conditions. This study analyzes the changes in past and present river channels and examines the applicability of river channel evaluation through image analysis using aerial photographs and 1918 year's map. Aerial photograph analysis was conducted by applying the image analysis method and GIS analysis method on Cheongmicheon. As a result of this analysis, we have quantitatively identified the form and size of abandoned channels, changes in the vertical-section and cross-section length of rivers, and micro-landform changes. More importantly, we verified that morphological changes in sandbars due to artificial straightening are important data in identifying the state of current river channels. In these results, although image analysis technique has limitations in two-dimensional information from aerial photographs, we were able to evaluate the changes in river channel morphology after artificial maintenance of the river.

• Journal of Mushroom
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• v.13 no.3
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• pp.151-156
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• 2015

Cordyceps militaris is being studied and cultivated as a medicinal mushroom having many valuable biological and pharmaceutical activities. In the breeding of new C. militaris mushroom, single ascospores were isolated and examined their mycelial growth, mycelial density, and production of stroma and perithecia. Among them selected isolates were crossed and hybrids were produced showing high quality fruiting bodies on artificial media. Mycelial growth rate of new strain 'Dowonhongcho' was higher than that of better on 'Yedang 3' on SDAY at $10-25^{\circ}C$. The stromata of new strain were club-shaped and bright orange-red. Its height was 6.1 cm and the cordycepin content was 0.34% on average. The new strain showed 9% higher yield than 'Yedang 3' with producing firmer fruit bodies. The optimum temperature for mycelial growth was $22{\sim}25^{\circ}C$ and the optimum temperature for stroma development was $18{\sim}22^{\circ}C$. Fruiting bodies were began to produce 45 days later after inoculation. This new cultivar may serve as a valuable one for artificial cultivation and industrial-scale production of C. militaris.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.821-832
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• 1998

This study investigates the prediction of daily water supply, which is a necessary for the efficient management of water distribution system. Fuzzy neuron, namely artificial intelligence, is a neural network into which fuzzy information is inputted and then processed. In this study, daily water supply was predicted through an adaptive learning method by which a membership function and fuzzy rules were adapted for daily water supply prediction. This study was investigated methods for predicting water supply based on data about the amount of water supplied to the city of Kwangju. For variables choice, four analyses of input data were conducted: correlation analysis, autocorrelation analysis, partial autocorrelation analysis, and cross-correlation analysis. Input variables were (a) the amount of water supplied (b) the mean temperature, and (c)the population of the area supplied with water. Variables were combined in an integrated model. Data of the amount of daily water supply only was modelled and its validity was verified in the case that the meteorological office of weather forecast is not always reliable. Proposed models include accidental cases such as a suspension of water supply. The maximum error rate between the estimation of the model and the actual measurement was 18.35% and the average error was lower than 2.36%. The model is expected to be a real-time estimation of the operational control of water works and water/drain pipes.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.5
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• pp.525-534
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• 2016

In South Korea, paddy rice has been consumed over the entire region and it is the main source of income for farmers, thus mathematical model for the estimation of rice yield is required for such decision-making processes in agriculture. The objectives of our study are to: (1) develop rice yield estimation model using Convolutional Neural Networks(CNN), (2) choose hyper-parameters for the model which show the best performance and (3) investigate whether CNN model can effectively predict the rice yield by the comparison with the model using Artificial Neural Networks(ANN). Weather and MODIS(The MOderate Resolution Imaging Spectroradiometer) products from April to September in year 2000~2013 were used for the rice yield estimation models and cross-validation was implemented for the accuracy assessment. The CNN and ANN models showed Root Mean Square Error(RMSE) of 36.10kg/10a, 48.61kg/10a based on rice points, respectively and 31.30kg/10a, 39.31kg/10a based on 'Si-Gun-Gu' districts, respectively. The CNN models outperformed ANN models and its possibility of application for the field of rice yield estimation in South Korea was proved.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.235-243
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• 2019

Universities are opening related majors and subjects to nurture the problem-solving fusion that businesses want. The time has come when rapid technological. On this thesis, we analyzed three years (2017-2019) of survey result of Women University students in order to figuring out and dealing with the change in 4th industrial revolution and intellectual information technology. It turns out that 1) there was an increase of interest in 4th industrial revolution from 59% in 2017 to 80% in 2019, 2) IoT, ICT, Artificial Intelligence, and Education Research System became top priority in technical strategy, 3)the prime keyword is AI, robot, job, 4)the expectation on increasing of the opportunity and the number of jobs in science technology field was 50%, 5)the importance of universities and companies was 50%, 80% each, 6) the information needed for science technology were educational discipline, change in future science, prospective future information in order, and 7)the most needed education were education on creativity, coding, cross-subject, engineering in order. In the era of the fourth industrial revolution, it is essential to expand the SW manpower base in various fields. University education, which should provide connectivity for super-fusion, should provide curriculum optimized for industrial demands such as, fusion and connected education, creative thinking, self-directed problem solving and etc.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.97-117
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• 2021

Predicting term deposit subscriptions is one of representative financial marketing in banks, and banks can build a prediction model using various customer information. In order to improve the classification accuracy for term deposit subscriptions, many studies have been conducted based on machine learning techniques. However, even if these models can achieve satisfactory performance, utilizing them is not an easy task in the industry when their decision-making process is not adequately explained. To address this issue, this paper proposes an explainable scheme for term deposit subscription forecasting. For this, we first construct several classification models using decision tree-based ensemble learning methods, which yield excellent performance in tabular data, such as random forest, gradient boosting machine (GBM), extreme gradient boosting (XGB), and light gradient boosting machine (LightGBM). We then analyze their classification performance in depth through 10-fold cross-validation. After that, we provide the rationale for interpreting the influence of customer information and the decision-making process by applying Shapley additive explanation (SHAP), an explainable artificial intelligence technique, to the best classification model. To verify the practicality and validity of our scheme, experiments were conducted with the bank marketing dataset provided by Kaggle; we applied the SHAP to the GBM and LightGBM models, respectively, according to different dataset configurations and then performed their analysis and visualization for explainable term deposit subscriptions.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.7-15
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• 2022

With the aim of an intelligent world in the age of individual customization through decentralization of information and technology, sharing/opening, and connection, we often see a tendency to cross expectations and concerns in the technological discourse and interest in artificial intelligence more than ever. Recently, it is easy to find claims by futurists that AI singularity will appear before and after 2045. Now, as part of preparations to create a paradigm of coexistence that coexists and prosper with AI in the coming age of artificial intelligence, a standard framework for setting up more correct AI ethics and regulations is required. This is because excluding the risk of omission of setting major guidelines and methods for evaluating reasonable and more reasonable guideline items and evaluation standards are increasingly becoming major research issues. In order to solve these research problems and at the same time to develop continuous experiences and learning effects on AI ethics and regulation setting, we collect guideline data on AI ethics and regulation of international organizations / countries / companies, and research and suggest ways to set up a standard framework (SF: Standard Framework) through a setting research model and text mining exploratory analysis. The results of this study can be contributed as basic prior research data for more advanced AI ethics and regulatory guidelines item setting and evaluation methods in the future.

• Applied Chemistry for Engineering
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• v.33 no.2
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• pp.195-201
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• 2022

The main objective of this work is to prepare Rehmannia glutinosa extract (RE) incorporated functional chitosan (CH) based biomaterials and evaluate their physical properties, RE release properties, inhibitory effect of melanogenesis, and antioxidant and elastase inhibitory activities. RE incorporated CH based biomaterials were synthesized by a casting method and UV curing process. The surface and cross sections of prepared biomaterials were characterized by a field emission scanning electron microscope (FE-SEM). The physical properties such as tensile strength and elongation at break were also investigated. To apply the transdermal drug delivery system, RE release properties were examined with pH 4.5, 5.5, and 6.5 buffer solutions and artificial skin test at 36.5 ℃. Results indicated that RE release of RE incorporated biomaterials with/without the addition of plasticizers [glycerol (GL) and citric acid (CA)] at pH 6.5 was about 1.10 times higher than that of at pH 4.5. In addition, results of the artificial skin test verified that RE was released constantly for 6 h. To verify the applicability of the prepared biomaterials, tyrosinase, 2,2-diphenyl-1-picrylhydrazyl (DPPH), and elastase assays were investigated. Results indicated that RE incorporated biomaterials added CA exhibited tyrosinase activation, DPPH radical scavenging activity rate, and elastase activation of 45.12, 89.40, and 59.94%, respectively.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.8
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• pp.315-324
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• 2022

In this paper, we propose KoEPT, a Transformer-based generative model for automatic math word problems solving. A math word problem written in human language which describes everyday situations in a mathematical form. Math word problem solving requires an artificial intelligence model to understand the implied logic within the problem. Therefore, it is being studied variously across the world to improve the language understanding ability of artificial intelligence. In the case of the Korean language, studies so far have mainly attempted to solve problems by classifying them into templates, but there is a limitation in that these techniques are difficult to apply to datasets with high classification difficulty. To solve this problem, this paper used the KoEPT model which uses 'expression' tokens and pointer networks. To measure the performance of this model, the classification difficulty scores of IL, CC, and ALG514, which are existing Korean mathematical sentence problem datasets, were measured, and then the performance of KoEPT was evaluated using 5-fold cross-validation. For the Korean datasets used for evaluation, KoEPT obtained the state-of-the-art(SOTA) performance with 99.1% in CC, which is comparable to the existing SOTA performance, and 89.3% and 80.5% in IL and ALG514, respectively. In addition, as a result of evaluation, KoEPT showed a relatively improved performance for datasets with high classification difficulty. Through an ablation study, we uncovered that the use of the 'expression' tokens and pointer networks contributed to KoEPT's state of being less affected by classification difficulty while obtaining good performance.