• Steel and Composite Structures
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• v.49 no.1
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• pp.91-107
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• 2023

An effective approach to promoting sustainability within the construction industry is the use of recycled aggregate concrete (RAC) as a substitute for natural aggregates. Ensuring the frost resilience of RAC technologies is crucial to facilitate their adoption in regions characterized by cold temperatures. The main aim of this study was to use the Random Forests (RF) approach to forecast the frost durability of RAC in cold locations, with a focus on the durability factor (DF) value. Herein, three optimization algorithms named Sine-cosine optimization algorithm (SCA), Black widow optimization algorithm (BWOA), and Equilibrium optimizer (EO) were considered for determing optimal values of RF hyperparameters. The findings show that all developed systems faithfully represented the DF, with an R² for the train and test data phases of better than 0.9539 and 0.9777, respectively. In two assessment and learning stages, EO - RF is found to be superior than BWOA - RF and SCA - RF. The outperformed model's performance (EO - RF) was superior to that of ANN (from literature) by raising the values of R² and reducing the RMSE values. Considering the justifications, as well as the comparisons from metrics and Taylor diagram's findings, it could be found out that, although other RF models were equally reliable in predicting the the frost durability of RAC based on the durability factor (DF) value in cold climates, the developed EO - RF strategy excelled them all.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.4
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• pp.163-169
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• 2016

This study is to analyze factors affecting a growth of online community with perspectives of social network. Particularly this study tries to explore structural phenomenon built by interactions between users in a certain of free board belonging to the online community, in which focuses on one's writing a comments responding on those of others. With using SNA(Social Network Analysis), the social network data calculated from users' interaction shown as their comments were collected to draw out each individual's centrality value representing the structure of the online community and also we estimated duration time and the number of each comments as a proxy variable representing growth of the online community. And then cause-and-effect relationship between individual's centrality value and the duration time and the number of each comment were analyzed. As a result of the analysis, Core-Periphery, Centralization and Reciprocity have significant effects on the duration time and the number of each comment, therefore those significant values representing online structure will give an implication to manage, to promote the online community, to forecast its evolution path and to build critical policies.

• KIEAE Journal
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• v.16 no.3
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• pp.129-135
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• 2016

Purpose: Building figuration is imperative to perceive the its value, environmental clean status and form. Therefore, maintenance activities of the building exterior are required to keep the housing condition and value. Each household should pay the repair cost which is brought out in the future. For this repair cost, the estimation model would needed to forecast and provide the required cost. This study aimed at providing the estimation model of the repair cost, using the repair survey data between the 2011 and 2014 in Seoul. Method: For these, it took various estimation function of repair cost such as 1st function, inverse function and so on. These above functions would be applied into the building exterior and outdoor facilities which figure the building shape and characteristics. Result: Results of this study are shown ; First, among 11 estimation models, the power function has a better statistics and goodness-of-fit than any other models. Second, the estimation model with a variable of household has a pattern in upward to the right. On the contrary, the model with management area is little downward to the right. Both of them are depended on the estimated parameter of the power function and the parameter smaller than 1.

• Asian Journal of Innovation and Policy
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• v.9 no.2
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• pp.133-144
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• 2020

Korean economy has experienced a very rapid growth largely due to the change of the innovation system since the last half century. The recent outbreak of COVID-19 impacts the global economy as well as Korea's innovation system. In order to understand the influence of the shock to the Korean technological system, we have forecast the future of the system combining qualitative and quantitative techniques such as expert panel, cross impact analysis, and scenario planning. According to the results, we have identified 39 driving forces influencing the change of Korea's technological innovation system. Four scenarios have been suggested based on the predetermined factors and core uncertainties. In other words, uncertainties of emergence of the regions and global value chains generate four scenarios: regional growth, unstable hope, returning to the past, and regional conflicts. The 'regional growth' scenario is regarded as the most preferable, whereas the 'regional conflicts' scenario is unavoidable. In conclusion, we put forward some policy implications to boost the regional innovation system by exploiting the weakened global value chains in order to move on to the most preferable scenario away from the return to the past regime.

• Asia pacific journal of information systems
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• v.30 no.1
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• pp.31-52
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• 2020

Stock markets are popular investment avenues to people who plan to receive premium returns compared to other financial instruments, but they are highly volatile and risky due to the complex financial dynamics and poor understanding of the market forces involved in the price determination. A system that can forecast, predict the stock prices and automatically create a portfolio of top performing stocks is of great value to individual investors who do not have sufficient knowledge to understand the complex dynamics involved in evaluating and predicting stock prices. In this paper the authors propose a Stock prediction, Portfolio Generation and Selection model based on Machine learning algorithms, Artificial neural networks (ANNs) are used for stock price prediction, Mathematical and Statistical techniques are used for Portfolio generation and Un-Supervised Machine learning based on K-Means Clustering algorithms are used for Portfolio Evaluation and Selection which take in to account the Portfolio Return and Risk in to consideration. The model presented here is limited to predicting stock prices on a long term basis as the inputs to the model are based on fundamental attributes and intrinsic value of the stock. The results of this study are quite encouraging as the stock prediction models are able predict stock prices at least a financial quarter in advance with an accuracy of around 90 percent and the portfolio selection classifiers are giving returns in excess of average market returns.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.3
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• pp.396-402
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• 2018

Earned Value Management(EVM) has been used to manage and forecast defense project schedule and cost over the last two decades in the world. However to support the lacking ability of schedule analysis in traditional EVM, earned schedule(ES) has been introduced as a tool to more accurately estimate schedule performance. This paper compares which method EVM or ES, provides more accurate schedule predictors in 32 Korean defense research and development projects. As a result of comparison, the ES method can predict the future schedule more reliably than the EVM method. We also analyze early warning function of schedule performance index considering project duration extension point. Through the analysis results, we confirm that both the EVM and the ES method lack the ability of the early warning in terms of the current schedule management criterion.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.387-393
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• 2022

The article reflects short-term perspectives on the use of information and communication technologies in the training of teachers for higher education. Education is characterized by conservatism, so aspects of systematic development of the industry are relevant to this cluster of social activity. Therefore, forecasting the introduction of innovative elements of ICT training is in demand for the educational environment. Forecasting educational trends are most relevant exactly in the issues of training future teachers of higher education because these specialists are actually the first to implement the acquired professional skills in pedagogical activities. The article aims to consider the existing potential of ICT-based learning, its implementation in the coming years, and promising innovative educational elements that may become relevant for the educational space in the future. The tasks of scientific exploration are to show the optimal formats of synergy between traditional and innovative models of learning. Based on already existing experience, extrapolation of conditions of educational process organization with modeling realities of using information and communication technologies in various learning dimensions should be carried out. Educational trends for the next 3 years are a rather tentative forecast because, as demonstrated by the events associated with the COVID-19 pandemic, the socio-cultural space is very changeable. Consequently, the dynamism of the educational environment dictates the need for a value-based awareness of the information society and the practical use of technological advances. Thus, information and communication technologies are a manifestation of innovative educational strategies of today and become an important component along with traditional aspects of educational process organization. Future higher education teachers should develop a training strategy taking into account the expediency of the ICT component.

• Korean Institute of Interior Design Journal
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• no.10
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• pp.77-81
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• 1997

The study is for interior design and planning of new c conceptual modern shop(called "Value Conscious Store") t through the history of retail store, and its process is based on m most great cites in USA. The Value Conscious Store has c come into existence for consumer and retailer who have had v various lifestyles and characters. From analysis of new l lifestyle consumer to retailer's strategy. we could find i interesting design solutions and, forecast next concerns for d designing store. Store has been designed up-scaled and opened to give pleasure and comfort and made by a theme to m make unique and strong impact for customers. Also it uses M Multi-Media for excitment, and is designed as exhibition of m museum to lead constomers to new culture and trend. From t these interior trends will go on to next generation with new c concepts : environment and nature, senses and sensibility. T These words will be the new solution for creative and s successful store design by the designer who has environm mentally conscious and social responsibility in his mind. his mind.

• Journal of Korea Trade
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• v.24 no.1
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• pp.131-145
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• 2020

Purpose - The recent growth of South Korean products in the international market is the benchmark for both developed as well as developing countries. According to the development index, the role of international trade is indeed crucial for the development of the national economy. However, the visualization of the international trade profile of the country is the prerequisite of governmental policy decision-makers and guidance for forecasting of foreign trade. Design/methodology - We have utilized data visualization techniques in order to visualize the import & export product space and trade partners of South Korea. Economic Complexity Index (ECI) and Revealed Comparative Advantage (RCA) were used to identify the Korean international trade diversification, whereas the time series approach is used to forecast the economy and foreign trade variables. Findings - Our results show that Chine, U.S, Vietnam, Hong Kong, and Japan are the leading trade partners of Korea. Overall, the ECI of South Korea is growing significantly as compared to China, Hong Kong, and other developed countries of the world. The expected values of total import and export volume of South Korea are approximately US$535.21 and US$ 781.23B, with the balance of trade US$ 254.02B in 2025. It was also observed from our analysis that imports & exports are equally substantial to the GDP of Korea and have a significant correlation with GDP, GDP per capita, and ECI. Originality/value - To maintain the growth rate of international trade and efficient competitor for the trade partners, we have visualized the South Korea trade profile, which provides the information of significant export and import products as well as main trade partners and forecasting.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.2
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• pp.51.2-51.2
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• 2010

We have investigated 63 intense geomagnetic storms (Dst $\leq$ -100 nT) that occurred from 1998 to 2006. Using these events, we compared Dst forecast models: Burton et al. (1975), Fenrich and Luhmann (1998), O'Brien and McPherron (2000a), Wang et al. (2003), and Temerin and Li (2002, 2006) models. For comparison, we examined a linear correlation coefficient, RMS error, the difference of Dst minimum value (${\Delta}$peak), and the difference of Dst minimum time (${\Delta}$peak_time) between the observed and the predicted during geomagnetic storm period. As a result, we found that Temerin and Li model is mostly much better than other models. The model produces a linear correlation coefficient of 0.94, a RMS (Root Mean Square) error of 14.89 nT, a MAD (Mean Absolute Deviation) of ${\Delta}$peak of 12.54 nT, and a MAD of ${\Delta}$peak_time of 1.44 hour. Also, we classified storm events as five groups according to their interplanetary origin structures: 17 sMC events (IP shock and MC), 18 SH events (sheath field), 10 SH+MC events (Sheath field and MC), 8 CIR events, and 10 nonMC events (non-MC type ICME). We found that Temerin and Li model is also best for all structures. The RMS error and MAD of ${\Delta}$peak of their model depend on their associated interplanetary structures like; 19.1 nT and 16.7 nT for sMC, 12.5 nT and 7.8 nT for SH, 17.6 nT and 15.8 nT for SH+MC, 11.8 nT and 8.6 nT for CIR, and 11.9 nT and 10.5 nT for nonMC. One interesting thing is that MC-associated storms produce larger errors than the other-associated ones. Especially, the values of RMS error and MAD of ${\Delta}$peak of SH structure of Temerin and Li model are very lower than those of other models.