• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.99-107
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• 2021

We live in a myriad of data. Various data are created in all situations in which we work, and we discover the meaning of data through big data technology. Many efforts are underway to find meaningful data. This paper introduces an analysis technique that enables humans to make better choices through the trend and prediction of time series data as a principal component analysis technique. Principal component analysis constructs covariance through the input data and presents eigenvectors and eigenvalues that can infer the direction of the data. The proposed method computes a reference axis in a time series data set having a similar directionality. It predicts the directionality of data in the next section through the angle between the directionality of each time series data constituting the data set and the reference axis. In this paper, we compare and verify the accuracy of the proposed algorithm with LSTM (Long Short-Term Memory) through cryptocurrency trends. As a result of comparative verification, the proposed method recorded relatively few transactions and high returns(112%) compared to LSTM in data with high volatility. It can mean that the signal was analyzed and predicted relatively accurately, and it is expected that better results can be derived through a more accurate threshold setting.

• Journal of Distribution Science
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• v.12 no.2
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• pp.105-112
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• 2014

Purpose - This research undertakes to understand the trade structures of both China and Japan to strengthen Sino-Japan economic cooperation and examines impediments to trade between the 2 countries to analyze causes which affect trade and to examine improvements in these areas to find out ways of trade expansion. Through this survey of a defined period of time, we can identify the structural factors of trade dependence in the relationship between China and Japan. Research design, data, methodology - The data were collected from Korea Traders Association, Korea Customs Office and UN Comtrade, from which whole table indexes are calculated by author. This research methodology uses trade related indexes to focus on analyzing comparative advantages based on time-series analysis statistics data (2000~2012), by using the analysis index of Trade Intensity Index (TII), Revealed Comparative Advantage Index (RCA) and Trade Specialization Index (TSI). Results - The export ratio for China against Japan was a little higher in 2000 at 2.867 and the export ratio for China against Japan was sustained in 2005. However, it diminished gradually and reached 1.263 in 2012. During the whole period of 2000~2012, the indexes were maintained without any significant change. However, they are still moving closer to -1. Especially, in 2012 it is the closest it has been to -1. Therefore, Japan has a comparative advantage toward export specialization. On the other hand, China has a comparative advantage toward import specialization. For the whole research period, all indexes were much smaller than 1, which means that China has comprehensively had a comparative disadvantage against Japan for the past 10 years when compared to other industries, even though it had improved in 2000. Conclusions - The summary of conclusions based on empirical analysis research are as follows: First, per the Trade Intensity Index of industries between the 2 countries, we can conclude that export ratio index is 2.867, based on the formula, in 2000, which means the export ratio of China against Japan is a little bit higher. Furthermore, the ratios of 2.259 and 1.263 are indicated in 2005 and 2012 respectively which mean the export ratio of China against Japan was maintained in 2005 but was diminishing gradually as the index is 1.263 in 2012. Second, per the Trade Specialization Index of the shipping industry between China and Japan, -0.379 is indicated in 2000, -0.368 in 2005 and -0.568 in 2012. Looking at the whole period of 2000~2012, the indexes were maintained without any significant change. However, they are still moving closer to -1. Especially, in 2012 it is the closest it has been to -1. Third, per the Revealed Comparative Advantage Index of the automobile industry between China and Japan, the RCA indexes in 2005 and 2012 are 0.246 and 0.306 respectively which are still far from 1 even though the index is improved compared to 2000's value of 0.0001. Therefore, the Chinese automobile industry is very much at a comparative disadvantage to that of the Japanese automobile industry.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.5
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• pp.41-50
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• 2024

An increasing pattern of extreme rainfall recently affected the rural infrastructures with catastrophic damage, especially the overtopping of a fill dam embankment in the Republic of Korea. The overtopping was caused by the sudden increase in reservoir water level over the dam crest level, and it was not easy work to predict a priori because of its non-linear behavior. Fuzzy time series (FTS) is a fuzzy-logic inference procedure and is suited to apply to non-linear prediction methods such as machine learning. This study used the Wangshin reservoir and Goesan-dam cases, which experienced overtopping in 2023 and 2022, respectively. Wangshin Reservoir was a typical agricultural fill dam and needed to stack more available data, with only the daily storage rate (water level) of 7 years, starting on 2 May 2016. Therefore, we used Goesan-dam data to select appropriate variables and compare the analysis result, which was stacked with about 17 years of records. The analyses adapted LSTM to compare with FTS. As a result, the reservoir water level was applied to predict the overtopping water level, and it was shown that the FTS method could predict the actual water levels effectively according to the result of comparison with LSTM. Then, the FTS method was expected to predict reservoir water level a priori to make appropriate countermeasures on overtopping events as one of the alternatives.

• Journal of the Korean Society for Heat Treatment
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• v.36 no.6
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• pp.374-381
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• 2023

This study develops and evaluates a deep learning model for predicting oxide and nitride layers based on plasma process data. We introduce a novel deep learning-based Varying Coefficient Regressor (VCR) by adapting the VCR, which previously relied on an existing unique function. This model is employed to forecast the oxide and nitride layers within the plasma. Through comparative experiments, the proposed VCR-based model exhibits superior performance compared to Long Short-Term Memory, Random Forest, and other methods, showcasing its excellence in predicting time series data. This study indicates the potential for advancing prediction models through deep learning in the domain of plasma processing and highlights its application prospects in industrial settings.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.516-520
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• 1991

This paper presents a comparative analysis of two inverter power supply topologies for induction heating and melting applications. The comparison is based on criteria such as resonant condition, component ratings, minimum and maximum operating frequencies, operation under varying load conditions, inverter starting current, and diode reverse recovery time. The voltage source series/parallel resonant inverters are found to offer the best overall performance with respect to converter utilization.

• SUVANNABHUMI
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• v.16 no.1
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• pp.125-143
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• 2024

Korean dramas, commonly referred to as Koreanovelas or K-Dramas in the Philippines, have significantly influenced and reshaped Philippine television culture since the early 2000s. Their impact persists in contemporary television programming, reflecting the transnational flow of media texts across borders. As media content transcends geographical boundaries, local media companies have adopted the practice of producing adaptations of foreign television series for their audiences. This paper examines the adaptation of the Koreanovela The World of the Married into the Philippine series The Broken Marriage Vow, both of which are adaptations derived from the British show Doctor Foster. Through this comparative analysis, I argue that the process of localizing these television shows to suit the preferences of the target audience serves as a tangible manifestation of transnational adaptation. Particularly in an era of globalization, where entertainment is still a thriving enterprise, thus traversing international borders, this phenomenon demonstrates the evolving nature of television content as it adapts and caters to diverse cultural contexts let alone a profitable means to generate an ailing entertainment industry, especially in the time of the pandemic.

• New & Renewable Energy
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• v.6 no.2
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• pp.5-11
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• 2010

This paper reviews three commercial softwares for wind climate data analysis in wind resource assessment; WAsP/Observed Wind Climate, WindRose and Windographer. Windographer is evaluated as the best software because of its variety of input data format, analysis functions, easiness of user interface, etc. For a quantitative understanding of uncertainty depending on software selection, a benchmark is carried out with the met-mast observation dataset at the Gimnyeong Wind Turbine Performance Test Site. It is found that Weibull parameter calculation and air density correction have a dependency on the software so that such uncertainty should be considered when an analysis software is selected. It is confirmed that annual energy production calculated by WAsP using a statistical table of frequency of occurrence may have some error compared to a time-series calculation method used by the other softwares.

• Journal of Distribution Science
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• v.13 no.7
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• pp.11-18
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• 2015

Purpose - This paper reviews the changes in the ship export and import structure between Korea and China. It utilizes the comparative advantage trade theory to analyze time-series statistical data from the market share index, revealed comparative advantage index (RCA), and trade specialization index(TSI). Research design, data, and methodology - Based on their economic phases, both Korea and China have similar country characteristics. The purpose of this research is to understand the two country's trade structures to fortify the Korea-Sino economic relationship including verifying what is working and what is not. Results - Based on the analysis, bilateral economic activity to achieve a plus trade stimulus environment should be realized in the long run. Both countries should establish guarantee-free trade negotiations and boundaries instead of various non-tariff barriers. Conclusion - Reviewing the research, a sound competitive relationship can be grown for mutual benefit including export market diversification in the near future. The review of the Korea-Sino ship industry is keenly important and investigative research about it is timely because it is a major industry in each country.

• Korean Journal of Construction Engineering and Management
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• v.12 no.2
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• pp.111-120
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• 2011

High-rise buildings have recently increased over the residential, commercial and office facilities, thus an understanding of construction cost for high-rise building projects has been a fundamental issue due to enormous construction cost as well as unpredictable market conditions and fluctuations in the rate of inflation by long-term construction periods of high-rise projects. Especially, recent violent fluctuations of construction material prices add to problems in construction cost forecasting. This research, therefore, develops a time-series model with the Box-Jenkins methodologies and material prices time-series data in Korea in order to forecast future trends of unit prices of required materials. BIM (Building Information Modeling) approaches are also used to analyze injection time of construction resources and to conduct quantity takeoff so that total material price can be forecasted. Comparative analysis of Predictability of tentative ARIMA (Autoregressive Integrated Moving Average) models was conducted to determine optimal time-series model for forecasting future price trends. Proposed BIM based time series forecasting model can help to deal with sudden changes in economic conditions by estimating future material prices.

• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.7-13
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• 2021

This study develops an artificial intelligence prediction system for Fine particulate Matter(PM2.5) based on the deep learning algorithm GAN model. The experimental data are closely related to the changes in temperature, humidity, wind speed, and atmospheric pressure generated by the time series axis and the concentration of air pollutants such as SO2, CO, O3, NO2, and PM10. Due to the characteristics of the data, since the concentration at the current time is affected by the concentration at the previous time, a predictive model for recursive supervised learning was applied. For comparative analysis of the accuracy of the existing models, CNN and LSTM, the difference between observation value and prediction value was analyzed and visualized. As a result of performance analysis, it was confirmed that the proposed GAN improved to 15.8%, 10.9%, and 5.5% in the evaluation items RMSE, MAPE, and IOA compared to LSTM, respectively.