• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.1
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• pp.24-30
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• 2024

The gas-gun test is a experimental approach employed to validate the operational or structural stability when subjected to the impact energy encountered during launch or target collision. Predicting the outcomes of the gas-gun test has traditionally relied on empirical knowledge, due to numerous factors such as the bird assembly's shape, weight, material, and flight velocity. However, due to the nonlinearity and complex interactions between these variables, numerous tests are necessary to identify the necessary requirements, resulting in significant expense and time consumption during the process. The objective of this study is to forecast the variations in impact energy in future tests by developing a numerical model and analysis that aligns with the test outcomes, utilizing the ABAQUS Explicit. The outcome of the numerical analysis produced a framework that anticipates the peak g and the duration of the actual gas-sun test results, throughout post-processing techniques using FFT and LPF filters.

• Asia-Pacific Journal of Business
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• v.14 no.4
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• pp.343-356
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• 2023

Purpose - This study attempted to predict short-term transportation demand using trains and getting off at Gangchon Station. Through this, we present numerical data necessary for future tourist inflow policies in the Gangchon area of Chuncheon and present related implications. Design/methodology/approach - This study collected and analyzed transportation demand data from Gangchon Station using the Gyeongchun Line and ITX-Cheongchun Train from January 2014 to August 2023. Winters exponential smoothing model and ARIMA model were used to reflect the trend and seasonality of the raw data. Findings - First, transportation demand using trains to get off at Gangchon Station in Chuncheon City is expected to show a continuous increase from 2020 until the forecast period is 2024. Second, the number of passengers getting off at Gangchon Station was found to be highest in May and October. Research implications or Originality - As transportation networks are improving nationwide and people's leisure culture is changing, the number of tourists visiting the Gangchon area in Chuncheon City is continuously decreasing. Therefore, in this study, a time series model was used to predict short-term transportation demand alighting at Gangchon Station. In order to calculate more accurate forecasts, we compared models to find an appropriate model and presented forecasts.

• Korean Journal of Artificial Intelligence
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• v.12 no.1
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• pp.17-24
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• 2024

This paper introduces a novel approach to time-series estimation for energy load forecasting within Virtual Power Plant (VPP) systems, leveraging advanced artificial intelligence (AI) algorithms, namely Long Short-Term Memory (LSTM) and Seasonal Autoregressive Integrated Moving Average (SARIMA). Virtual power plants, which integrate diverse microgrids managed by Energy Management Systems (EMS), require precise forecasting techniques to balance energy supply and demand efficiently. The paper introduces a hybrid-method forecasting model combining a parametric-based statistical technique and an AI algorithm. The LSTM algorithm is particularly employed to discern pattern correlations over fixed intervals, crucial for predicting accurate future energy loads. SARIMA is applied to generate time-series forecasts, accounting for non-stationary and seasonal variations. The forecasting model incorporates a broad spectrum of distributed energy resources, including renewable energy sources and conventional power plants. Data spanning a decade, sourced from the Korea Power Exchange (KPX) Electrical Power Statistical Information System (EPSIS), were utilized to validate the model. The proposed hybrid LSTM-SARIMA model with parameter sets (1, 1, 1, 12) and (2, 1, 1, 12) demonstrated a high fidelity to the actual observed data. Thus, it is concluded that the optimized system notably surpasses traditional forecasting methods, indicating that this model offers a viable solution for EMS to enhance short-term load forecasting.

• Journal of Korea Water Resources Association
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• v.54 no.9
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• pp.731-745
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• 2021

In this study, the monthly temperature of the Han River basin was predicted by statistical multiple regression models that use global climate indices and weather data of the target region as predictors. The optimal predictors were selected through teleconnection analysis between the monthly temperature and the preceding patterns of each climate index, and forecast models capable of predicting up to 12 months in advance were constructed by combining the selected predictors and cross-validating the past period. Fore each target month, 1000 optimized models were derived and forecast ranges were presented. As a result of analyzing the predictability of monthly temperature from January 1992 to December 2020, PBIAS was -1.4 to -0.7%, RSR was 0.15 to 0.16, NSE was 0.98, and r was 0.99, indicating a high goodness-of-fit. The probability of each monthly observation being included in the forecast range was about 64.4% on average, and by month, the predictability was relatively high in September, December, February, and January, and low in April, August, and March. The predicted range and median were in good agreement with the observations, except for some periods when temperature was dramatically lower or higher than in normal years. The quantitative temperature forecast information derived from this study will be useful not only for forecasting changes in temperature in the future period (1 to 12 months in advance), but also in predicting changes in the hydro-ecological environment, including evapotranspiration highly correlated with temperature.

• Archives of design research
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• v.13 no.4
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• pp.85-93
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• 2000

Design becomes a source of new competitive power in the boundless global market so-called globalization. The competitive power in business was lied in the technology in 70's and the design was understood as a styling or graphic means. However, the design has become more important means to get the competitive power in business since 1980. World businesses have found the fact that it has a super competitive power to make the product's performance as well as its dignity rather than it is to determine the product's external view or color. The change of design policy in Phillips, one of the world's leading producers of electronic products, is not much different. Design manager's power was limited until 70's. However, Phillips has focused its business strategy on the higher competitive power since 1980 and they welcomed Robert Blaich, vice president of design and development at Herman Miller Inc., to be a member of the company, expanding the importance of design along with restructure while working on the globalization. Meanwhile, Stefano Marzano, a Senior Director in 90's, established a high design concept, working on the strategic futures to get customer-oriented and for successful commercialization. The vision of the future developed over 3 years until 1996 was to forecast 10 years coming up and create a new value while achieving the business target through the design as an innovative design in bracing for the information network era.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.1
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• pp.108-126
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• 2013

Recently, it becomes essential for firms or nations to forecast the future and identify emerging technologies in order to improve R&D efficiency and gain a competitive advantage. Particularly, the mobile communications industry is characterized by rapid advance and wide application of its technology and thus identifying emerging technologies is more important in the industry than in others. Nevertheless, few attempts have been made to explore its emerging technologies. Therefore, this research aims to develop a methodology to identify the future and emerging technologies especially for the industry and applied it to list top ten emerging technologies for 2020 in the industry. For this purpose, firstly, we focused the key issues in the future targeting 2020 and identified user needs relating to them. Then, candidates of emerging technologies were defined from a set of technologies to meet the needs, for which technological and economic feasibility is assessed to determine their priorities. Finally, the top ten most important technologies were selected and verified. This research is distinct from the previous studies in that it takes a market-pull approach instead of a technology-push approach. The research results are expected to provide valuable information to support strategy- and policy-makings in the mobile communications industry.

• Journal of Korea Water Resources Association
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• v.43 no.3
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• pp.309-323
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• 2010

As climate changes and abnormal climates have drawn research interest recently, many countries utilize the GCM, which is based on SRES suggested by IPCC, to obtain more accurate forecast for future climate changes. Especially, many research attempts have been made to simulate localized geographical characteristics by using RCM with the high resolution data globally. To evaluate the impacts of climate and landuse change on water resources in the Han-river basin, we carried out the procedure consisting of the CA-Markov Chain, the Multi-Regression equation using two independent variables of temperature and rainfall, the downscaling technique based on the RegCM3 RCM, and SLURP. From the CA-Markov Chain, the future landuse change is forecasted and the future NDVI is predicted by the Multi-Regression equation. Also, RegCM3 RCM 50 sets were generated by the downscaling technique based on the RegCM3 RCM provided by KMA. With them, 90 year runoff scenarios whose period is from 2001 to 2090 are simulated for the Han-river basin by SLURP. Finally, the 90-year simulated monthly runoffs are compared with the historical monthly runoffs for each dam in the basin. At Paldang dam, the runoffs in September show higher increase than the ones in August which is due to the change of rainfall pattern in future. Additionally, after exploring the impact of the climate change on the structure of water circulation, we find that water management will become more difficult by the changes in the water circulation factors such as precipitation, evaporation, transpiration, and runoff in the Han-river basin.

• Journal of the Korea Society for Simulation
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• v.31 no.3
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• pp.35-44
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• 2022

In this study, we analyze and forecast quantum computer technology trends. Previous research has been mainly focused on application fields centered on technology for quantum computer technology trends analysis. Therefore, this paper analyzes important quantum computer technologies and performs future signal detection and prediction, for a more market driven technical analysis and prediction. As analyzing words used in news articles to identify rapidly changing market changes and public interest. This paper extends conference presentation of Cha & Chang (2022). The research is conducted by collecting domestic news articles from 2019 to 2021. First, we organize the main keywords through text mining. Next, we explore future quantum computer technologies through analysis of Term Frequency - Inverse Document Frequency(TF-IDF), Key Issue Map(KIM), and Key Emergence Map (KEM). Finally, the relationship between future technologies and supply and demand is identified through random forests, decision trees, and correlation analysis. As results of the study, the interest in artificial intelligence was the highest in frequency analysis, keyword diffusion and visibility analysis. In terms of cyber-security, the rate of mention in news articles is getting overwhelmingly higher than that of other technologies. Quantum communication, resistant cryptography, and augmented reality also showed a high rate of increase in interest. These results show that the expectation is high for applying trend technology in the market. The results of this study can be applied to identifying areas of interest in the quantum computer market and establishing a response system related to technology investment.

• Atmosphere
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• v.25 no.2
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• pp.221-233
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• 2015

Pollen is closely related to health issues such as allergenic rhinitis and asthma as well as intensifying atopic syndrome. Information on current and future spatio-temporal distribution of allergenic pollen is needed to address such issues. In this study, the Community Multiscale Air Quality Modeling (CMAQ) was utilized as a base modeling system to forecast pollen dispersal from oak trees. Pollen emission is one of the most important parts in the dispersal modeling system. Areal emission factor was determined from gridded areal fraction of oak trees, which was produced by the analysis of the tree type maps (1:5000) obtained from the Korea Forest Service. Daily total pollen production was estimated by a robust multiple regression model of weather conditions and pollen concentration. Hourly emission factor was determined from wind speed and friction velocity. Hourly pollen emission was then calculated by multiplying areal emission factor, daily total pollen production, and hourly emission factor. Forecast data from the KMA UM LDAPS (Korea Meteorological Administration Unified Model Local Data Assimilation and Prediction System) was utilized as input. For the verification of the model, daily observed pollen concentration from 12 sites in Korea during the pollen season of 2014. Although the model showed a tendency of over-estimation in terms of the seasonal and daily mean concentrations, overall concentration was similar to the observation. Comparison at the hourly output showed distinctive delay of the peak hours by the model at the 'Pocheon' site. It was speculated that the constant release of hourly number of pollen in the modeling framework caused the delay.

• Journal of the Korean Society of Costume
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• v.18
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• pp.321-337
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• 1992

Fashions are constantly subject to change, so that forecasting trends in fashion is very difficult and the forecasting is very important. The reason is that forecasting is identifying a hot trend for the next days' business and projecting the future. The purpose of this study is to suggest the realistic forecasting theory identify fashion trends at present, further forecast fashion trends to 1995. For this study, historical models (th historical resurrection model, the historical continuity model) and the art movement model among the behavioral science models which was suggested in 1986 by Geoge B.Sproles were selected. According to this study, was exhibited. This curve was resulted from relation between 1980s fashion trends and the behavioral science models of fashion. Fashion trends to 1995 through will be followings; 1. Body Conscious look as one of the characteristics of modern fashion will bi continued throughout 1990s' fashion trends. 2. The attraction of Mini style was started from the middle of 1980s, recently gets near micro mini and super shouts, These are representative of the historical continuity model. 3. Mini look as revivals of '60s in early 1990s fashion trends. This phenomenon identifies that "Fashion is repetition" 4. When Mini look and super shorts reach, will not progress any more. In this time, will bi seen transfer of style be using classic style. Tat is modern classic will be appeared. also this condition is same from late 1960s to early 1970s. In view of the historical base, the action of the varieted pants will be prominent. 5. Fashion trends which passed through this process will transfer from young look to elegant look. In this time, designers will retrospect '30s and '50s fashion trends, and then will design modern feminine look. 6. Ethnic look, the fashion trend after that condition will be accelated feminine look. This look with the feminine look will reveal rich, colorful, elegance feminine image. 7. In 1980s, activity and function in clothes were demanded. The clothes which are considered these condition will be demanded continuously. 8. The variety of fashion will appear as mixmode and new coordinate look in a clothes simultaneously in fashion of '90s. And these looks will creat mixed beauty. 9. Pop art, op art, graphic art will be not only development of textile but also movement of fashion soul in 1990s. The fashion behavior will be continuously scientificated.