• Journal of Industrial Convergence
• /
• v.21 no.1
• /
• pp.87-93
• /
• 2023

Determining the timing of buying and selling in stock investment is one of the most important factors to increase the return on stock investment. Buying low and selling high makes a profit, but buying high and selling low makes a loss. The price is determined by the quantity of buying and selling, which determines the price of a stock, and buying and selling is also related to corporate performance and economic indicators. The fear and greed index provided by CNN uses seven factors, and by assigning weights to each element, the weighted average defined as greed and fear is calculated on a scale between 0 and 100 and published every day. When the index is close to 0, the stock market sentiment is fearful, and when the index is close to 100, it is greedy. Therefore, we analyze the trading criteria that generate the maximum return when buying and selling the US S&P 500 index according to CNN fear and greed index, suggesting the optimal buying and selling timing to suggest a way to increase the return on stock investment.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2023.05a
• /
• pp.163-163
• /
• 2023

Flooding has become an increasing event which is one of the major natural disasters responsible for direct economic damage in South Korea. Driven by climate change, precipitation extremes play significant role on the flood damage and its further increase is expected to exacerbate the socioeconomic impact in the country. However, the empirical evidence associating changes in precipitation extremes to the historical flood damage is limited. Thus, there is a need to assess the causal relationship between changes in precipitation extremes and flood damage, especially in agricultural region like Chungcheong region in South Korea. The spatial and temporal changes of precipitation extremes from 10 synoptic stations based on daily precipitation data were analyzed using the ClimPACT2 tool and Mann-Kendall test. The four precipitation extreme indices consisting of consecutive wet days (CWD), number of very heavy precipitation wet days (R30 mm), maximum 1-day precipitation amount (Rx1day), and simple daily precipitation intensity (SDII), which represent changes in intensity, frequency, and duration, respectively, and the time series data on flooded area and flood damage from 1985 to 2020 were used to investigate the causal relationship in the ARDL-ECM framework and pairwise Granger causality analysis. The trend results showed that majority of the precipitation indices indicated positive trends, however, CWD showed no significant changes. ARDL-ECM framework showed that there was a long-run relationship among the variables. Further analysis on the empirical results showed that flooded area and Rx1day have significant positive impacts on the flood damage in both short and long-runs while R30 mm only indicated significant positive impact in the short-run, both in the current period, which implies that an increase in flooded area, Rx1day, and R30 mm will cause an increase in the flood damage. The pairwise Granger analysis showed unidirectional causality from the flooded area, R30 mm, Rx1day, and SDII to flood damage. Thus, these precipitation indices could be useful as indicators of pluvial flood damage in Chungcheong region of South Korea.

• Journal of Industrial Convergence
• /
• v.21 no.1
• /
• pp.167-173
• /
• 2023

As research has been published to predict future data using regression analysis or artificial intelligence as a method of analyzing economic indicators. In this study, we designed a system that predicts prospective futures prices using artificial intelligence that utilizes topic probability data obtained from past news articles using topic modeling. Topic probability distribution data for each news article were obtained using the Latent Dirichlet Allocation (LDA) method that can extract the topic of a document from past news articles via unsupervised learning. Further, the topic probability distribution data were used as the input for a Long Short-Term Memory (LSTM) network, a derivative of Recurrent Neural Networks (RNN) in artificial intelligence, in order to predict prospective futures prices. The method proposed in this study was able to predict the trend of futures prices. Later, this method will also be able to predict the trend of prices for derivative products like options. However, because statistical errors occurred for certain data; further research is required to improve accuracy.

• 한국노년학
• /
• v.31 no.2
• /
• pp.419-437
• /
• 2011

The purpose of this study is to compare on the productive activities and life satisfaction between rural and urban elderly. Economic activities and caring labor activity had a negative effect on life satisfaction. but, community participation had a positive effect. In other words, the concept of productive activities in life satisfaction has multidimensionality. Therefore, using multiple indicators to measure is inappropriate. And, according to Chow test, coefficients that describe the structure of life satisfaction were different between the elderly living in rural and urban. The self-actualization needs of the elderly can be interpreted as due to be implemented differently, because of the different cultures of urban and rural areas. And, In life satisfaction, we have found that individual volunteer activity is more effective than volunteer through groups.

• The Journal of Engineering Geology
• /
• v.34 no.1
• /
• pp.107-115
• /
• 2024

This study assesses forest fire susceptibility in Gangwon-do, South Korea, which hosts the largest forested area in the nation and constitutes ~21% of the country's forested land. With 81% of its terrain forested, Gangwon-do is particularly susceptible to wildfires, as evidenced by the fact that seven out of the ten most extensive wildfires in Korea have occurred in this region, with significant ecological and economic implications. Here, we analyze 480 historical wildfire occurrences in Gangwon-do between 2003 and 2019 using 17 predictor variables of wildfire occurrence. We utilized three machine learning algorithms—random forest, logistic regression, and support vector machine—to construct wildfire susceptibility prediction models and identify the best-performing model for Gangwon-do. Forest and soil map data were integrated as important indicators of wildfire susceptibility and enhanced the precision of the three models in identifying areas at high risk of wildfires. Of the three models examined, the random forest model showed the best predictive performance, with an area-under-the-curve value of 0.936. The findings of this study, especially the maps generated by the models, are expected to offer important guidance to local governments in formulating effective management and conservation strategies. These strategies aim to ensure the sustainable preservation of forest resources and to enhance the well-being of communities situated in areas adjacent to forests. Furthermore, the outcomes of this study are anticipated to contribute to the safeguarding of forest resources and biodiversity and to the development of comprehensive plans for forest resource protection, biodiversity conservation, and environmental management.

• Journal of Korea Water Resources Association
• /
• v.57 no.6
• /
• pp.371-383
• /
• 2024

The quantification methods and definitions of resilience vary and are studied across many fields. However, this diversity can lead to gaps in interpretation regarding the meaning and indicators of resilience, potentially having a negative impact on resilience assessments. Therefore, uniform standards for defining and quantifying resilience are essential. This study presented a definition of resilience and socio-structural evaluation methods of resilience through network analysis. Furthermore, through analyzing various definitions of resilience, the definition of resilience in the context of urban flooding was presented. Distinguishing between static and dynamic resilience, an evaluation method based on common attributes was proposed. Lastly, the economic effects of introducing resilience were analyzed using an inundation trace map. Future research on the secondary effects through standardized resilience assessments is expected to be widely utilized in decision-making stages within urban flood policies.

• Journal of Korean Society for Quality Management
• /
• v.51 no.4
• /
• pp.515-530
• /
• 2023

Purpose : This research aims to develop a data-driven inspection policy for radio stations utilizing the KS Q ISO 2859-1 sampling method, addressing potential regulatory relaxations and impending management challenges. Methods : Using radio station inspection big data from the past six years, we established a simulation model to evaluate the current policy. A new inspection sampling policy framework was designed based on the KS Q ISO 2859-1 method. The study compares the performance of the current and proposed inspection systems, offering insights for an improved inspection strategy. Results : This study introduced a simulation model for inspection system based on the KS Q ISO 2859-1 sampling method. Through various experimental designs, key performance indicators such as non-detection rate and sample proportion were derived, providing foundational data for the new inspection policy. Conclusion : Using big data from radio station inspections, we evaluated current inspection systems and quantitatively compared a new system across diverse scenarios. Our simulation model effectively verified the feasibility and efficiency of the proposed framework. For practical implementation, essential factors such as lot size, inspection cycle, and AQL standards need precise definition and consideration. Enhancing radio station inspections requires a policy-driven approach that factors in socio-economic impacts and solicits feedback from industry participants. Future study should also explore various perspectives related to legislative, institutional, and operational aspects of inspection organizations.

• Journal of Digital Convergence
• /
• v.16 no.9
• /
• pp.107-114
• /
• 2018

Since China's economic reform in 1978, international trade has enormously flourished and the port industry is reckoned as a key factor contributing to this growth. This study examines the Bohai Rim port group in the scope of top three largest ports Qingdao, Dalian and Tianjin. By utilizing indicators including concentration ratio (CR), Herfindahl-Hirschman index (HHI), the Gini coefficient and the Lorenz curve as well as shift-share analysis (SSA), the concentration level of this port group in the period 2004-2016 is discussed. As a results, CR demonstrates a decrease during the studied period with a minor fluctuation, and HHI index shows a trend of deconcentration with Bohai Rim port group. In addition, SSA indicates that during the period 2004-2016, the overall shift index of Qingdao port was -1.371 meanwhile with Tianjin and Dalian port were 0.118 and 1.252 in turn. These results suggest that the growth in regional influence of Tianjin and Dalian ports would motivate to the deconcentration pattern in Bohai Rim region. The findings assist decision makers and scholars to obtain knowledge about the port development this region. Considering the geographic position of these three ports as the gate of northeast China, it is suggested that these three ports could explore their advantages and cooperate with the small ports in the surrounding area to enhance their influences in the future study.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.39 no.6
• /
• pp.903-911
• /
• 2019

The multi-utility tunnel is one of the essential social infrastructures, but it is difficult to establish the multi-utility tunnel due to the scale of the National Land Planning and Utilization Act (2 million square meters). In this paper, we analyze the feasibility of establishing the multi-utility tunnel in the existing city in order to activate the multi-utility tunnel installation. For the feasibility analysis, the scale was classified into four categories based on related laws, and related indicators were selected and evaluated using feasibility and economic analysis. Three kinds/four kinds of suitable multi-utility tunnel for the scale of the existing city were shown, and five kinds of multi-utility tunnel were considered suitable for the new city over 2 million square meters. The results of the overall score evaluation of the tunnel type of the existing city and the open type of the new city of 2 million square meters or more, which is the obligation to install the multi-utility tunnel, do not show much difference and suggest the validity of the installation of the multi-utility tunnel in various scale of the existing city.

• Economic and Environmental Geology
• /
• v.52 no.6
• /
• pp.573-586
• /
• 2019

A seismic hazard map based on spatial analysis of various sources of geologic seismic information was developed and assessed for regional seismic vulnerability in South Korea. The indicators for assessment were selected in consideration of the geological characteristics affecting the seismic damage. Probabilistic seismic hazard and fault information were used to be associated with the seismic activity hazard and bedrock depth related with the seismic damage hazard was also included. Each indicator was constructed of spatial information using GIS and geostatistical techniques such as ordinary kriging, line density mapping and simple kriging with local varying means. Three spatial information constructed were integrated by assigning weights according to the research purpose, data resolution and accuracy. In the case of probabilistic seismic hazard and fault line density, since the data uncertainty was relatively high, only the trend was intended to be reflected firstly. Finally, the seismic activity hazard was calculated and then integrated with the bedrock depth distribution as seismic damage hazard indicator. As a result, a seismic hazard map was proposed based on the analysis of three spatial data and the southeast and northwest regions of South Korea were assessed as having high seismic hazard. The results of this study are expected to be used as basic data for constructing seismic risk management systems to minimize earthquake disasters.