• Journal of the Korean earth science society
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• v.40 no.3
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• pp.227-239
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• 2019

Heavy snowfall events frequently occur in the Gangwon province, and the snowfall amount significantly varies in space due to the complex terrain and topographical modulation of precipitation. Understanding the spatial characteristics of heavy snowfall and its prediction is particularly challenging during snowfall events in the easterly winds. The easterly wind produces a significantly different atmospheric condition. Hence, it brings different precipitation characteristics. In this study, we have investigated the microphysical characteristics of snowfall in the windward and leeward sides of the Taebaek mountain range in the easterly condition. The two snowfall events are selected in the easterly, and the snow particles size distributions (SSD) are observed in the four sites (two windward and two leeward sites) by the PARSIVEL distrometers. We compared the characteristic parameters of SSDs that come from leeward sites to that of windward sites. The results show that SSDs of windward sites have a relatively wide distribution with many small snow particles compared to those of leeward sites. This characteristic is clearly shown by the larger characteristic number concentration and characteristic diameter in the windward sites. Snowfall rate and ice water content of windward also are larger than those of leeward sites. The results indicate that a new generation of snowfall particles is dominant in the windward sites which is likely due to the orographic lifting. In addition, the windward sites show heavy aggregation particles by nearby zero ground temperature that is likely driven by the wet and warm condition near the ocean.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.199-230
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• 2021

Innovative new products and services are being launched through the convergence between heterogeneous industries, and social interest and investment in convergence industries such as AI, big data-based future cars, and robots are continuously increasing. However, in the process of commercialization of convergence new products and services, there are many cases where they do not conform to the existing regulatory and legal system, which causes many difficulties in companies launching their products and services into the market. In response to these industrial changes, the current government is promoting the improvement of existing regulatory mechanisms applied to the relevant industry along with the expansion of investment in new industries. This study, in these convergence industry trends, aimed to analysis the existing regulatory system that is an obstacle to market entry of innovative new products and services in order to preemptively predict regulatory issues that will arise in emerging industries. In addition, it was intended to establish a regulatory impact analysis system to evaluate adequacy and prepare improvement measures. The flow of this study is divided into three parts. In the first part, previous studies on regulatory impact analysis and evaluation systems are investigated. This was used as basic data for the development direction of the regulatory impact framework, indicators and items. In the second regulatory impact analysis framework development part, indicators and items are developed based on the previously investigated data, and these are applied to each stage of the framework. In the last part, a case study was presented to solve the regulatory issues faced by actual companies by applying the developed regulatory impact analysis framework. The case study included the autonomous/electric vehicle industry and the Internet of Things (IoT) industry, because it is one of the emerging industries that the Korean government is most interested in recently, and is judged to be most relevant to the realization of an intelligent information society. Specifically, the regulatory impact analysis framework proposed in this study consists of a total of five steps. The first step is to identify the industrial size of the target products and services, related policies, and regulatory issues. In the second stage, regulatory issues are discovered through review of regulatory improvement items for each stage of commercialization (planning, production, commercialization). In the next step, factors related to regulatory compliance costs are derived and costs incurred for existing regulatory compliance are calculated. In the fourth stage, an alternative is prepared by gathering opinions of the relevant industry and experts in the field, and the necessity, validity, and adequacy of the alternative are reviewed. Finally, in the final stage, the adopted alternatives are formulated so that they can be applied to the legislation, and the alternatives are reviewed by legal experts. The implications of this study are summarized as follows. From a theoretical point of view, it is meaningful in that it clearly presents a series of procedures for regulatory impact analysis as a framework. Although previous studies mainly discussed the importance and necessity of regulatory impact analysis, this study presented a systematic framework in consideration of the various factors required for regulatory impact analysis suggested by prior studies. From a practical point of view, this study has significance in that it was applied to actual regulatory issues based on the regulatory impact analysis framework proposed above. The results of this study show that proposals related to regulatory issues were submitted to government departments and finally the current law was revised, suggesting that the framework proposed in this study can be an effective way to resolve regulatory issues. It is expected that the regulatory impact analysis framework proposed in this study will be a meaningful guideline for technology policy researchers and policy makers in the future.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.157-173
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• 2021

With the development of information technology, the amount of available information increases daily. However, having access to so much information makes it difficult for users to easily find the information they seek. Users want a visualized system that reduces information retrieval and learning time, saving them from personally reading and judging all available information. As a result, recommendation systems are an increasingly important technologies that are essential to the business. Collaborative filtering is used in various fields with excellent performance because recommendations are made based on similar user interests and preferences. However, limitations do exist. Sparsity occurs when user-item preference information is insufficient, and is the main limitation of collaborative filtering. The evaluation value of the user item matrix may be distorted by the data depending on the popularity of the product, or there may be new users who have not yet evaluated the value. The lack of historical data to identify consumer preferences is referred to as data sparsity, and various methods have been studied to address these problems. However, most attempts to solve the sparsity problem are not optimal because they can only be applied when additional data such as users' personal information, social networks, or characteristics of items are included. Another problem is that real-world score data are mostly biased to high scores, resulting in severe imbalances. One cause of this imbalance distribution is the purchasing bias, in which only users with high product ratings purchase products, so those with low ratings are less likely to purchase products and thus do not leave negative product reviews. Due to these characteristics, unlike most users' actual preferences, reviews by users who purchase products are more likely to be positive. Therefore, the actual rating data is over-learned in many classes with high incidence due to its biased characteristics, distorting the market. Applying collaborative filtering to these imbalanced data leads to poor recommendation performance due to excessive learning of biased classes. Traditional oversampling techniques to address this problem are likely to cause overfitting because they repeat the same data, which acts as noise in learning, reducing recommendation performance. In addition, pre-processing methods for most existing data imbalance problems are designed and used for binary classes. Binary class imbalance techniques are difficult to apply to multi-class problems because they cannot model multi-class problems, such as objects at cross-class boundaries or objects overlapping multiple classes. To solve this problem, research has been conducted to convert and apply multi-class problems to binary class problems. However, simplification of multi-class problems can cause potential classification errors when combined with the results of classifiers learned from other sub-problems, resulting in loss of important information about relationships beyond the selected items. Therefore, it is necessary to develop more effective methods to address multi-class imbalance problems. We propose a collaborative filtering model using CGAN to generate realistic virtual data to populate the empty user-item matrix. Conditional vector y identify distributions for minority classes and generate data reflecting their characteristics. Collaborative filtering then maximizes the performance of the recommendation system via hyperparameter tuning. This process should improve the accuracy of the model by addressing the sparsity problem of collaborative filtering implementations while mitigating data imbalances arising from real data. Our model has superior recommendation performance over existing oversampling techniques and existing real-world data with data sparsity. SMOTE, Borderline SMOTE, SVM-SMOTE, ADASYN, and GAN were used as comparative models and we demonstrate the highest prediction accuracy on the RMSE and MAE evaluation scales. Through this study, oversampling based on deep learning will be able to further refine the performance of recommendation systems using actual data and be used to build business recommendation systems.

• Land and Housing Review
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• v.13 no.4
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• pp.55-71
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• 2022

Recently, the domestic department store industry is growing into a complex shopping cultural space, which is advanced and differentiated by changes in consumption patterns. In addition, competition is intensifying across 70 places operated by five large companies. This study investigates the determinants of the visits to department stores using the big data concept's automatic vehicle access system (pos) and proposes how to strengthen the competitiveness of the department store industry. We use a negative binomial regression test to predict the frequency of visits to 67 branches, except for three branches whose annual sales were incomplete due to the new opening in 2021. The results show that the demand for visiting department stores is positively associated with airport, terminal, and train stations, land areas, parking lots, VIP lounge numbers, luxury store ratio, F&B store numbers, non-commercial areas, and hotels. We suggest four strategies to enhance the competitiveness of domestic department stores. First, department store consumers have a high preference for luxury brands. Therefore, department stores need to form their own overseas buyer teams to discover and attract new luxury brands and attract customers who have a high demand for luxury brands. In addition, to attract consumers with high purchasing power and loyalty, it is necessary to provide more differentiated products and services for VIP customers than before. Second, it is desirable to focus on transportation hub areas such as train stations, airports, and terminals in Gyeonggi and Incheon. Third, department stores should attract tenants who can satisfy customers, given that key tenants are an important component of advanced shopping centers for department stores. Finally, the department store, a top-end shopping center, should be developed as a space with differentiated shopping, culture, dining out, and leisure services, such as "The Hyundai", which opened in 2021, to ensure future growth potential.

• Korean Journal of Environment and Ecology
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• v.34 no.6
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• pp.515-529
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• 2020

Constructed wetlands undergo biological and physical changes such as an increase in the proportion of arid plants due to the natural succession process after formation. It can adversely affect not only the purification function but also the habitat of species. As such, this study aims to identify environmental factors affecting biodiversity and propose management plans based on the monitoring results of physical environmental changes and the emergence of species in seven constructed wetlands selected based on the water depth and surrounding conditions among the lands purchased by the Nakdong River basin. We examined the environmental conditions and emergence of the Odonata, which is a wetland-dependent species, to predict the trend of changes in biodiversity and abundance. The results showed that the open water area decreased as the emergent plants spread to the deep water in 2015 compared to 2012 when they were initially restored to a depth of 0.2 to 1 m. While a total of 54 dragonfly species were observed, the habitat diversity, such as vegetation, water surface, and grassland, remained similar to the initial formation of the wetlands despite the expansion of the emergent plants. On the other hand, the number of Agrionidae species, which prefer areas with fewer aquatic plants, decreased between 2012 and 2015 due to the diminished water surface. The p-values of the differences in the number of species and population between wetlands by year were 2.568e-09 and 1.162e-08, respectively, indicating the statistically significant differences. The decrease in open water surface was found to have the greatest effect on the biodiversity and habitat density of dragonflies. The time-series survey of constructed wetlands confirmed that the spread of Phragmites communis, P. japonica, Typha orientalis, etc., caused a decrease in species diversity. It suggests that environmental management to maintain the open water surface area is necessary.

• Journal of Korean Society of Forest Science
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• v.100 no.1
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• pp.52-61
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• 2011

Whereas recent researches have elucidated the positive ecological roles of large wood (LW) in fishbearing channels, LW is also recognized as a negative factor of log-laden debris flows and floods in densely populated areas. However in Republic of Korea, no study has investigated longitudinal variations of LW distribution and dynamic along the stream corridor. Hence to elucidate 1) physical factors controlling longitudinal distribution of LW and 2) their effect on variation in LW load amount, we surveyed the amount of LW with respect to channel morphology in a mountain stream, originated from Mt. Ki-ryong in Inje, Gangwondo. Model selection in the Generalized Linear Model procedure revealed that number of boulder (greater than or equal to 1.0 m in diameter), bankfull channel width and their interaction were the best predictors explaining LW load volume per unit channel segment area (unit LW load). In general, boulders scattered within small mountain streams influence LW retention as flow obstructions. However, in this study, we found that the effect of the boulders vary with the channel width; that is, whereas the unit LW load in the segment with narrow channel width increased continuously with increasing boulder number, it in the segment with wide channel width did not depend on the boulder number. This should be because that, in two channels having different widths, the rates of channel widths reduced by boulders are different although boulder numbers are same. Our findings on LW load varying with physical factors (i.e., interaction of boulder number and channel width) along the stream corridor suggest understanding for longitudinal continuum of hydrogeomorphic and ecologic characteristics in stream environments, and these should be carefully applied into the erosion control works for systematic watershed management and subsequent disaster prevention.

• Journal of Korean Classical Literature and Education
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• no.39
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• pp.137-180
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• 2018

This article examines the constitutional characteristics of the works in the "Shinbi Apartment" (Mysterious Apartment) series produced by Tooniverse, a domestic animation channel, and considers the meaning of the contents of the ghoststory (鬼神談). The "Shinbi Apartment" series is a horror animation for children. It was produced for the first time in Korea and recorded high ratings. Additionally, it is different from Japanese horror animations that were dubbed and broadcast in Korea in terms of composition and narrative direction, and it succeeds in the form and direction of the traditional Korean ghost story. "Shinbi Apartment - The Secret of Ghost Ball" enriches narrative stories by embracing the structure of the "female ghost story" in traditional ghost stories while following the form of ghosts that suddenly pop up in the daily routines of contemporary ghost stories. The ghost's shape, which has a bizarre and unpredictable aspect, embodies the ghost as the object of fear that modern horror stories intend. However, it does not stop there, but puts the attention on the hero who focuses on the emerging ghost and listens and communicates with it, placing the emphasis of the story on communication, understanding, forgiveness, and reconciliation. The structure and contents of the unique story of "The Secret of Ghost Ball" contribute to the transformation of the ghost into a subject of friendliness and entertainment, not merely as one of shock, fear, and anxiety. Additionally, as the concept of "child" is being created, the custom of modernity, which deals with the story of ghosts in the dimension of teaching and edification, is also manifested in "The Secret of Ghost Ball." In other words, through the figure of the devil, it is to continue the lesson of the story by revealing the adventure, the courage necessary for the "child," and the boundaries for substance and appearance. The "Shinbi Apartment" series has also contributed to the success of ghosts as commercial contents. The structure of the story and its characters have been actively used as educational tools and toys for children. It can be said that ghost culture contributed to this popularization by establishing a base for enjoying ghosts for amusement and entertainment.

• Korean Chemical Engineering Research
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• v.60 no.1
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• pp.86-92
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• 2022

Recently, the bio-healthcare market is enlarging worldwide due to various reasons such as the COVID-19 pandemic. Among them, biometric measurement and analysis technology are expected to bring about future technological innovation and socio-economic ripple effect. Existing systems require a large-capacity battery to drive signal processing, wireless transmission part, and an operating system in the process. However, due to the limitation of the battery capacity, it causes a spatio-temporal limitation on the use of the device. This limitation can act as a cause for the disconnection of data required for the user's health care monitoring, so it is one of the major obstacles of the health care device. In this study, we report the concept of a standalone healthcare monitoring module, which is based on both triboelectric effects and electromagnetic effects, by converting biomechanical energy into suitable electric energy. The proposed system can be operated independently without an external power source. In particular, the wireless foot pressure measurement monitoring system, which is rationally designed triboelectric sensor (TES), can recognize the user's walking habits through foot pressure measurement. By applying the triboelectric effects to the contact-separation behavior that occurs during walking, an effective foot pressure sensor was made, the performance of the sensor was verified through an electrical output signal according to the pressure, and its dynamic behavior is measured through a signal processing circuit using a capacitor. In addition, the biomechanical energy dissipated during walking is harvested as electrical energy by using the electromagnetic induction effect to be used as a power source for wireless transmission and signal processing. Therefore, the proposed system has a great potential to reduce the inconvenience of charging caused by limited battery capacity and to overcome the problem of data disconnection.

• Journal of Korea Water Resources Association
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• v.55 no.1
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• pp.1-10
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• 2022

Irrigation water supplied to the paddy field is consumed in the amount of evapotranspiration, underground infiltration, and natural and artificial drainage from the paddy field. Irrigation return flow is defined as the excess of irrigation water that is not consumed by evapotranspiration and crop, and which returns to an aquifer by infiltration or drainage. The research on estimating the return flow play an important part in water circulation management of agricultural watershed. However, the return flow rate calculations are needs because the result of calculating return flow is different depending on irrigation channel water loss, analysis methods, and local characteristics. In this study, the irrigation return flow rate of agricultural watershed was estimated using the monitoring and SWMM (Storm Water Management Model) modeling from 2017 to 2020 for the Heungeop reservoir located in Wonju, Gangwon-do. SWMM modeling was performed by weather data and observation data, water of supply and drainage were estimated as the result of SWMM model analysis. The applicability of the SWMM model was verified using RMSE and R-square values. The result of analysis from 2017 to 2020, the average annual quick return flow rate was 53.1%. Based on these results, the analysis of water circulation characteristics can perform, it can be provided as basic data for integrated water management.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.41-54
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• 2021

It is very essential to estimate the water body area using remote exploration for water resource management, analysis and prediction of water disaster damage. Hydrophysical detection using satellites has been mainly performed on large satellites equipped with optical and SAR sensors. However, due to the long repeat cycle, there is a limitation that timely utilization is impossible in the event of a disaster/disaster. With the recent active development of Micro satellites, it has served as an opportunity to overcome the limitations of time resolution centered on existing large satellites. The Micro satellites currently in active operation are ICEYE in Finland and Capella satellites in the United States, and are operated in the form of clusters for earth observation purposes. Due to clustering operation, it has a short revisit cycle and high resolution and has the advantage of being able to observe regardless of weather or day and night with the SAR sensor mounted. In this study, the operation status and characteristics of micro satellites were described, and the water area estimation technology optimized for micro SAR satellite images was applied to the Daecheong Dam basin on the Korean Peninsula. In addition, accuracy verification was performed based on the reference value of the water generated from the optical satellite Sentinel-2 satellite as a reference. In the case of the Capella satellite, the smallest difference in area was shown, and it was confirmed that all three images showed high correlation. Through the results of this study, it was confirmed that despite the low NESZ of Micro satellites, it is possible to estimate the water area, and it is believed that the limitations of water resource/water disaster monitoring using existing large SAR satellites can be overcome.