• Journal of Distribution Science
• /
• v.20 no.10
• /
• pp.61-66
• /
• 2022

Purpose: Predicting the financial distress distribution of an enterprise is important to warn enterprises about their future. Predicting the possibility of financial distress helps companies have action plans to avoid the possibility of bankruptcy. In this study, the author conducted a forecast of the financial distress distribution of enterprises. Research design, data and methodology: The forecasting method is based on Logit and Discriminant analysis models. The data was collected from companies listed on Vietnam Stock Exchange from 2012 to 2020. In which there are both companies suffer from financial distress and non-financial distress. Results: The forecast analysis results show that the Logistic model has better predictability than the Discriminant analysis model. At the same time, the results also indicate three main factors affecting the financial distress of enterprises at all three research stages: (1) Liquidity, (2) Interest payment, and (3) firm size. In addition, at each stage, the impact of factors on financial distress differs. Conclusions: From the results of this study, the author also made several recommendations to help companies better control company operations to avoid falling into financial distress. Adjustments to current assets, debt, and company expansion considerations are the most important factors for companies.

• Journal of the Korean earth science society
• /
• v.44 no.2
• /
• pp.119-134
• /
• 2023

The synoptic, thermodynamic, and dynamic characteristics of a snowfall event that occurred in the Yeongdong region on March 1-2, 2021, were investigated. Surface weather charts, ERA5 reanalysis data, rawinsonde data, GK-2A satellite data, and WISSDOM data were used for analysis. The snow depth, exceeding 10 cm, was observed at four weather stations during the analysis period. The maximum snow depth (37.4 cm) occurred at Bukgangneung. According to the analysis of the weather charts, old and dry air was trapped within relatively warm, humid air in the upper atmosphere over the East Sea and adjacent Yeongdong region. This caused unstable atmospheric conditions that led to developing convective clouds and snowfall over Bukgangneung. In particular, based on the thermodynamic and kinematic vertical analysis, we suggest that strong winds attributable to the vertical gradient of potential temperature in the low layer and the development of convective instability due to cold advection played a significant role in the occurrence of snowfall in the Yeongdong region. These results were confirmed from the vertical analysis of the rawinsonde data.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.12 no.2
• /
• pp.1-10
• /
• 2009

Recently the large scale of forest disaster such as landslide and forest fire gives a very bad impact on not only forest ecosystem but also farm business so that it has became the main issue of environmental problems. In this study, the landslide hazard area forecast method was developed by considering not only the topographic thematic maps based on GIS and satellite images but also amount of rainfall data, which are very important factors of landslide. Uljin-gun was selected as the study area and the GIS weight score and overlay analysis were applied to topographical map and meteorological observation map. Finally the landslide area distribution map was constructed by considering the evaluation criteria. Also, the accuracy could be acquired by comparing the landslide hazard area forecast map and real damaged area extracted from satellite image.

• Atmosphere
• /
• v.31 no.4
• /
• pp.461-472
• /
• 2021

Yeongdong has frequently suffered from severe snowstorms, which generally give rise to societal and economic damages to the region in winter. In order to understand its mechanism, there has been a long-term measurement campaign, based on the rawinsonde measurements for every snowfall event at Gangneung since 2014. The previous observations showed that a typical heavy snowfall is generally accompanied with northerly or northeasterly flow below the snow clouds, generated by cold air outbreak over the relatively warmer East Sea. An intensive and multi-institutional measurement campaign has been launched in 2019 mainly in collaboration with Gangwon Regional Office of Meteorology and National Institute of Meteorological Studies of Korean Meteorological Administration, with a special emphasis on winter snowfall and spring windstorm altogether. The experiment spanned largely from February to April with comprehensive measurements of frequent rawinsonde measurements at a super site (Gangneung) with continuous remote sensings of wind profiler, microwave radiometers and weather radar etc. Additional measurements were added to the campaign, such as aircraft dropsonde measurements and shipboard rawinsonde soundings. One of the fruitful outcomes is, so far, to identify a couple of cold air damming occurrences, featuring lowest temperature below 1 km, which hamper the convergence zone and snow clouds from penetrating inland, and eventually make it harder to forecast snowfall in terms of its location and timing. This kind of comprehensive observation campaign with continuous remote sensings and intensive additional measurement platforms should be conducted to understand various orographic precipitation in the complex terrain like Yeongdong.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.1
• /
• pp.8-14
• /
• 2020

The human impact of particulate matter are revealed and demand for improved forecast accuracy is increasing. Recently, efforts is made to improve the accuracy of PM10 predictions by using machine learning, but prediction performance is decreasing due to the particulate matter data with a large rate of low concentration occurrence. In this paper, separation prediction model by concentration is proposed to improve the accuracy of PM10 particulate matter forecast. The low and high concentration prediction model was designed using the weather and air pollution factors in Cheonan, and the performance comparison with the prediction models was performed. As a result of experiments with RMSE, MAPE, correlation coefficient, and AQI accuracy, it was confirmed that the predictive performance was improved, and that 20.62% of the AQI high-concentration prediction performance was improved.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.63-63
• /
• 2022

기상 예보자료는 발생 가능한 재난의 예방 및 대비 차원에서 매우 중요한 자료로 활용되고 있다. 우리나라 기상청에서는 동네예보를 통해 5km 공간해상도의 1시간 간격 초단기예보와, 6시간 간격 정량강우예보(Quantitative Precipitation Forecast, QPF)의 단기예보 정보를 제공하고 있다. 그러나 이와 같은 예보자료는 강우량의 시·공간변화가 큰 집중호우와 같은 기상자료를 활용한 수문학적인 해석에는 한계가 있다. 예보자료를 수문학에 활용하기 위한 시·공간적 해상도 개선뿐만 아니라 방대한 기상 및 기후 자료의 예측성능을 개선하기 위한 다양한 연구가 진행되고 있다. 본 연구에서는 기상청이 제공하는 지역 앙상블 예측 시스템(Local ENsemble prediction System, LENS)와 종관기상관측시스템(ASOS) 및 방재기상관측시스템(AWS) 관측 데이터 및 동네예보에 기계학습 방법을 적용하여 수문학적 정량적 강수량 예측(Hydrological Quantitative Precipitation Forecast, HQPF) 정보를 생산하였다. 전처리 과정을 통해 모든 데이터의 시간해상도와 공간해상도를 동일한 해상도로 변환하였으며, 예측 변수의 인자 분석을 통해 기계학습의 예측 변수를 도출하였다. 기계학습 방법으로는 처리속도와 확장성을 고려하여 XGBoost(eXtreme Gradient Boosting) 방식을 적용하였으며, 집중호우에서의 예측정확도를 높이기 위해 확률매칭(PM) 방식을 적용하였다. 생산된 HQPF의 성능을 평가하기 위해 2020년에 발생한 14건의 호우 사상을 대상으로 태풍형과 비태풍형으로 구분하여 검증을 수행하였다.

• The Journal of the Acoustical Society of Korea
• /
• v.28 no.1E
• /
• pp.23-28
• /
• 2009

At the crossings of turnout systems, noise is generated by the impact of train on the connection points. However, rapid movement changes between rail and wheels on connection point are inevitable on existing turnout section which may cause safety concern as well as noise problem caused by repeated impact load by passing train. And given the turnout is a complicated system which combines various functions such as rolling stock, trackbed, signaling, communication and electrical system, it's very difficult to expect to improve the overall performance of the turnout in such a way of optimizing only particular part of such integrated system. Since the turnout is the only movable section among the integrated parts and has complicated structure that inevitably brings about quick and sudden movement, safety has been still put on the top of the list. This study was aimed at comparing and analyzing the noise data obtained around the turnout of existing railway, by categorizing them into tilting train, high speed train and traditional train, and by distance, speed and type of turnout. And based on the data measured, the forecast of noise level when tilting train accelerates around a turnout was conducted in the study.

• Korean System Dynamics Review
• /
• v.13 no.2
• /
• pp.25-45
• /
• 2012

The purpose of this study is to estimate the effects of healthy city policies on residents' walking. In order to estimate promotion of walking rates by healthy cities policies, it developed System dynamics(SD)-based model which showed causal relationships among urban design, public health policies, and walking levels. SD technique is useful for future forecast and policy impact assessment. The spatial units of the SD-based system for policy impact assessment included 66 cities, counties, and communities in Seoul Metropolitan Area. The system simulation was planned to be run for 21 years from 2009 to 2030. For this study, 3 alternatives were proposed with combinations of length of bike lanes, number of bus routes, crime rates, self-reported good health status rates, and obesity rates. As a result of simulations, residents' participation rates for walking were increased from 1.00% to 9.98%. This study contributes to better understanding the benefits of healthy cities that are associated with individual walking. It further provided useful insights into planners' role in promoting health. The paper concluded with a discussion on future research opportunities and implications for public policies in urban and transportation and public health.

• Atmosphere
• /
• v.34 no.2
• /
• pp.107-121
• /
• 2024

In this study, we empirically analyzed the impact of physical risks due to climate change on the soundness and operational performance of the financial industry by combining economics and climatology. Particularly, unlike previous studies, we employed the Seasonal-Trend decomposition using LOESS (STL) method to extract trends of climate-related risk variables and economic-financial variables, conducting a two-stage empirical analysis. In the first stage estimation, we found that the delinquency rate and the Bank for International Settlement (BIS) ratio of commercial banks have significant negative effects on the damage caused by natural disasters, frequency of heavy rainfall, average temperature, and number of typhoons. On the other hand, for insurance companies, the damage from natural disasters, frequency of heavy rainfall, frequency of heavy snowfall, and annual average temperature have significant negative effects on return on assets (ROA) and the risk-based capital ratio (RBC). In the second stage estimation, based on the first stage results, we predicted the soundness and operational performance indicators of commercial banks and insurance companies until 2035. According to the forecast results, the delinquency rate of commercial banks is expected to increase steadily until 2035 under assumption that recent years' trend continues until 2035. It indicates that banks' managerial risk can be seriously worsened from climate change. Also the BIS ratio is expected to decrease which also indicates weakening safety buffer against climate risks over time. Additionally, the ROA of insurance companies is expected to decrease, followed by an increase in the RBC, and then a subsequent decrease.

• Atmosphere
• /
• v.31 no.4
• /
• pp.445-459
• /
• 2021

This study uses a cloud-resolving storm simulator (CReSS) to understand the individual effect of determinant meteorological factors on snowfall characteristics in the Yeongdong region based on the rawinsonde soundings for two snowfall cases that occurred on 23 February (Episode 1) and 13 December (Episode 2) 2016; one has a single-layered cloud and the other has two-layered cloud structure. The observed cloud and precipitation (snow crystal) features were well represented by a CReSS model. The first ideal experiment with a decrease in low-level temperature for Episode 1 indicates that total precipitation amount was decreased by 19% (26~27% in graupel and 53~67% in snow) compared with the control experiment. In the ideal experiment that the upper-level wind direction was changed from westerly to easterly, although total precipitation was decreased for Episode 1, precipitation was intensified over the southwestern side (specifically in terrain experiment) of the sounding point (128.855°E, 37.805°N). In contrast, the precipitation for Episode 2 was increased by 2.3 times greater than the control experiment under terrain condition. The experimental results imply that the low-level temperature and upper-level dynamics could change the location and characteristics of precipitation in the Yeongdong region. However, the difference in precipitation between the single-layered experiment and control (two-layered) experiment for Episode 2 was negligible to attribute it to the effect of upper-level cloud. The current results could be used for the development of guidance of snowfall forecast in this region.