• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.29-45
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• 2015

Systematic theory, concepts, and methodology for the biological evolution have been developed while patterns and principles of the evolution have been actively studied in the past 200 years. Furthermore, they are applied to various fields such as evolutionary economics, evolutionary psychology, evolutionary linguistics, making significant progress in research. In addition, existing studies have applied main biological evolutionary models to artifacts although such methods do not fit to them. These models are also limited to generalize evolutionary patterns of artifacts because they are designed in terms of a subjective point of view of experts who know well about the artifacts. Unlike biological organisms, because artifacts are likely to reflect the imagination of the human will, it is known that the theory of biological evolution cannot be directly applied to artifacts. In this paper, beyond the individual's subjective, the aim of our research is to present evolutionary patterns of a given artifact based on peeping the idea of the public. For this, we propose a text mining approach that presents a systematic framework that can find out the evolutionary patterns of a given artifact and then visualize effectively. In particular, based on our proposal, we focus mainly on a case study of mobile phone that has emerged as an icon of innovation in recent years. We collect and analyze review posts on mobile phone available in the domestic market over the past decade, and discuss the detailed results about evolutionary patterns of the mobile phone. Moreover, this kind of task is a tedious work over a long period of time because a small number of experts carry out an extensive literature survey and summarize a huge number of materials to finally draw a diagram of evolutionary patterns of the mobile phone. However, in this work, to minimize the human efforts, we present a semi-automatic mining algorithm, and through this research we can understand how human creativity and imagination are implemented. In addition, it is a big help to predict the future trend of mobile phone in business and industries.

• Korean journal of applied entomology
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• v.57 no.3
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• pp.127-135
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• 2018

Climate change can affect variables related to the life cycle of insects, including growth, development, survival, reproduction and distribution. As it encourages alien insects to rapidly spread and settle, climate change is regarded as one of the direct causes of decreased biodiversity because it disturbed ecosystems and reduces the population of native species. Hypera postica caused a great deal of damage in the southern provinces of Korea after it was first identified on Jeju lsland in the 1990s. In recent years, the number of individuals moving to estivation sites has concerned scientists due to the crop damage and national proliferation. In this study, we examine how climate change could affect inhabitation of H. postica. The MaxEnt model was applied to estimate potential distributions of H. postica using future climate change scenarios, namely, representative concentration pathway (RCP) 4.5 and RCP 8.5. As variables of the model, this study used six bio-climates (bio3, bio6, bio10, bio12, bio14, and bio16) in consideration of the ecological characteristics of 66 areas where inhabitation of H. postica was confirmed from 2015 to 2017, and in consideration of the interrelation between prediction variables. The fitness of the model was measured at a considered potentially useful level of 0.765 on average, and the warmest quarter has a high contribution rate of 60-70%. Prediction models (RCP 4.5 and RCP 8.5) results for the year 2050 and 2070 indicated that H. postica habitats are projected to expand across the Korean peninsula due to increasing temperatures.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.19-43
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• 2016

This study examines the causes of the Asian exchange rate crisis and compares it to the European Monetary System crisis. In 1997, emerging countries in Asia experienced financial crises. Previously in 1992, currencies in the European Monetary System had undergone the same experience. This was followed by Mexico in 1994. The objective of this paper lies in the generation of useful insights from these crises. This research presents a comparison of South Korea, United Kingdom and Mexico, and then compares three different models for prediction. Previous studies of economic crisis focused largely on the manual construction of causal models using linear techniques. However, the weakness of such models stems from the prevalence of nonlinear factors in reality. This paper uses a structural equation model to analyze the causes, followed by a neural network model to circumvent the linear model's weaknesses. The models are examined in the context of predicting exchange rates In this paper, data were quarterly ones, and Consumer Price Index, Gross Domestic Product, Interest Rate, Stock Index, Current Account, Foreign Reserves were independent variables for the prediction. However, time periods of each country's data are different. Lisrel is an emerging method and as such requires a fresh approach to financial crisis prediction model design, along with the flexibility to accommodate unexpected change. This paper indicates the neural network model has the greater prediction performance in Korea, Mexico, and United Kingdom. However, in Korea, the multiple regression shows the better performance. In Mexico, the multiple regression is almost indifferent to the Lisrel. Although Lisrel doesn't show the significant performance, the refined model is expected to show the better result. The structural model in this paper should contain the psychological factor and other invisible areas in the future work. The reason of the low hit ratio is that the alternative model in this paper uses only the financial market data. Thus, we cannot consider the other important part. Korea's hit ratio is lower than that of United Kingdom. So, there must be the other construct that affects the financial market. So does Mexico. However, the United Kingdom's financial market is more influenced and explained by the financial factors than Korea and Mexico.

• Journal of Public Diplomacy
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• v.3 no.2
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• pp.35-52
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• 2023

Korea has developed as an influential country over Asia and all over the world based on remarkable economic development. And the background of this development was possible due to the existence of those who sacrificed precious lives and contributed to the nation's existence in the past crisis. Every year, Korea holds an annual commemorative event with people of national merit, Korean War veterans, and their families, expressing gratitude for sacrifices and contributions at home and abroad, and providing economic support. The tragedy of the Korean War and the pro-democracy movement in Korea over the past half century will one day become a history of the distant past over time. As generations change and the purpose and method of exchange by region change, the tragic situation that occurred earlier and the way people sacrificed for the country are expected to be different from before. In particular, it is true that the number of Korean War veterans and their families is gradually decreasing as they are now old. In addition, due to the outbreak of global infectious diseases such as COVID-19, it is difficult to plan and conduct face to face events as well as before. Currently, Korea's digital technology is introducing various methods. 5G communication networks, smart-phones, tablet PCs, and smart devices that can experience virtual reality are already used in our real lives. Business meetings are held in a metaverse environment, and concerts by famous singers are held in an online environment. Artificial intelligence technology has also been introduced in the field of human resource recruitment and customer response services, improving the work efficiency of companies. And it seems that this technology can be used in the field of veterans. In particular, there is a metaverse technology that can vividly show the situation during the Korean War, and a way to digitalize the voices and facial expressions of currently surviving veterans to convey their memories and lessons to future generations in the long run. If this digital technology method is realized on an online platform to hold a veterans' celebration event, veterans and their families on the other side of the world will be able to participate in the event more conveniently.

• Economic Analysis
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• v.26 no.1
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• pp.1-33
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• 2020

Recent discussions about a minimum wage increase (MWI) and its influence on the economy have mainly focused on the quantitative aspects, such as labor costs and employment. However, concerning the qualitative aspects, an MWI could have positive effects by enhancing firm productivity and crowding out marginal firms from the market. These positive effects of an MWI can offset, to some extent, its potential negative effects - increasing labor costs and decreasing employment, among others. In this regard we empirically examine the impact of an MWI on firm productivity (total factor productivity). Using firm level panel data from the manufacturing industry in Korea, we calculate the influence rates of a minimum wage by sector and by firm size (number of workers), and analyze its effects on firm productivity. In particular, the production functions of the firms are estimated by taking into account endogeneity among the input factors, in order to resolve the drawbacks of existing studies - underestimating the capital factor coefficient and overestimating the labor factor coefficient. This study finds that the influences of an MWI on wages, employment, and productivity are substantially different across sectors and firm sizes. While an MWI has shown to have positive influences on productivity growth in the manufacturing industry as a whole, each sector demonstrates a different direction of effect, and the degree of productivity change also varies by sector. The impacts of an MWI on firm productivity are generally estimated to be more negative for smaller firms, but in some sectors the effects are found to be positive. In addition, the wage increases resulting from an MWI seem to cause a productivity enhancement across all sectors in the manufacturing industry. The policy implications of this study are as follows. Considering the empirical findings that an MWI causes an increase in productivity in many sectors of the manufacturing industry, it would be desirable to take into consideration not only the negative side effects but also the positive effects of an MWI when designing any future minimum wage policy. Moreover, in spite of there being a uniform minimum wage, this study finds that the diverse influence rates of a minimum wage across firms have different impacts on wages, employment, and productivity across sectors or firm size. This finding could be conducive to discussions about differentiation among minimum wage schemes by sector or firm size.

• Journal of Climate Change Research
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• v.1 no.1
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• pp.31-50
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• 2010

The Arctic climate change for the Last Glacial Maximum(LGM) occurred at 21,000 years ago (21ka) was investigated using simulation results of atmosphere-ocean coupled models from the second phase of the Paleoclimate Modelling Intercomparison Program(PMIP2). In the analysis, we used seven models, the NCAR CCSM of USA, ECHAM3-MPIOM of German Max-Planxk Institute, HadCM3M2 of UK Met Office, IPSL-CM4 of France Laplace Institute, CNRM-CM3 of France Meteorological Institute, MIROC3.2 of Japan CCSR at University of Tokyo, and FGOALS of China Institute of Atmospheric Physics. All the seven models reproduces the Arctic climate features found in the present climate at 0ka(pre-industrial time) in a reasonable degree in comparison to observations. During the LGM, the atmospheric $CO_2$ concentration and other greenhouse gases were reduced, the ice sheets were expanded over North America and northern Europe, the sea level was lowered by about 120m, and orbital parameters were slightly different. These boundary conditions were implemented to simulated LGM climate. With the implemented LGM conditions, the biggest temperature reduction by more than $24^{\circ}C$ is found over North America and northern Europe owing to ice albedo feedback and the change in lapse rate by high elevation. Besides, the expansion of ice sheets leads to the marked temperature reduction by more then $10^{\circ}C$ over the Arctic Ocean. The temperature reduction in northern winter is larger than in summer around the Arctic and the annual mean temperature is reduced by about $14^{\circ}C$. Compared to low mid-latitudes, the temperature reduction is much larger in high northern altitudes in the LGM. This results mirror the larger warming around the Artic in recent century. We could draw some information for the future under global warming from the knowledge of the LGM.

• The Journal of Engineering Geology
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• v.27 no.3
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• pp.331-343
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• 2017

In this study to improve stability, workability and economics of the H-Pile+Earth plate or H-Pile+Earth plate+Cutoff grouting currently in use, we had developed HCS method belonging to the retaining wall which is consisting of a combination H-Pile, Plastic Sheet Pile and Steel Square Pipe for gap maintenance and reinforcement of flexible plastic Sheet Pile, and the behavior of each member composing HCS method is investigated by three-dimensional finite element analysis. To numerically analyze the behavior of the HCS method, we have performed extensive three-dimentional finite element analysis for three kinds of plastic Sheet Pile size, two kinds of H-Pile size and three kinds of H-Pile installation interval, one kinds of Steel Square Pipe and three kinds of Steel Square Pipe installation interval. After analyzing the numerical results, we found that the combinations of $P.S.P-460{\times}131.5{\times}7t$ (PS7) and H-Pile $250{\times}250{\times}9{\times}14$ (H250), $P.S.P473{\times}133.5{\times}9t$ (PS9) and H-Pile $300{\times}200{\times}9{\times}14$ (H300) is the most economical because these combinations are considered to have a stress ratio (=applied stress/allowable stress) close to that as the stiffness of H-Pile, plastic Sheet Pile and Steel Square Pipe composite increased, the horizontal displacement of the retaining wall and the vertical displacement of the upper ground decreased. Especially, due to the arching effects caused by the difference in stiffness between H-Pile and plastic Sheet Pile, a large part of the earth pressure acting on plastic Sheet Pile caused a stress transfer to H-Pile, and the stress and displacement of plastic Sheet Pile were small. Through this study, we can confirm the behavior of each member constituting the HCS method, and based on the confirmed results of this study, it can be used to apply HCS method in reasonable, stable and economical way in the future.

• Journal of Distribution Science
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• v.10 no.5
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• pp.37-44
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• 2012

In this paper, we investigate several factors that affect the locational decision of discount stores by using previous studies on the marketing area and the location of commercial facilities. We selected 21 primary variables that are expected to influence the decision of store location and, by factor analysis, grouped them into five underlying factors. Among these, the demographic factor, which shows the potential purchasing power level, had the greatest impact on the locational decision for the store. However, we found individual stores positioned according to unique locational characteristics in addition to the demographic factor. It means that we have to additionally consider if the vicinity of the market is based on any physical properties. Many previous studies proposed four decision factors for store location: the economic factor, the demographic factor, the land utilization factor, and traffic factor. However, the fivefold factors-our distinctive contribution-are more concrete and persuasive according to Korean reality. We show that location preference is based on the following criteria: (1) the area is densely populated, (2) houses stand close together, (3) residents have a high income level, (4) road traffic is developed and easy to access, and (5) public transportation is well developed. The demographic factor has the greatest impact on the location of a discount store. The number of households has a greater relevance to the demographic factor than does the individual consumer. Second, discount stores relatively prefer places where houses are located close together because such places offer easy access to the market. Third, a place whose residents have a high income level will be preferred, with its large cars and excellent traffic conditions. Fourth, a location would be highly rated if the roads around commercial facilities are well developed and their accessibility is good. Finally, discount stores must be located close to bus stops because female consumers, including housewives-the most important customers-evaluate stores based on distance. In this research, the variable of consumer attitude and preference was excluded, and the location factors of discount stores were analyzed according to a microscopic view through physical spatial data. In the future, the opening of new discount stores based on the five factors indicated above will require a comparatively shorter time from the first project feasibility analysis. In addition, the result of our study can be applied to the field of public policy for constructing and attracting large-scale distribution facilities.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.239-251
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• 2019

Statistical methods such as moving averages, Kalman filtering, exponential smoothing, regression analysis, and ARIMA (autoregressive integrated moving average) have been used for stock market predictions. However, these statistical methods have not produced superior performances. In recent years, machine learning techniques have been widely used in stock market predictions, including artificial neural network, SVM, and genetic algorithm. In particular, a case-based reasoning method, known as k-nearest neighbor is also widely used for stock price prediction. Case based reasoning retrieves several similar cases from previous cases when a new problem occurs, and combines the class labels of similar cases to create a classification for the new problem. However, case based reasoning has some problems. First, case based reasoning has a tendency to search for a fixed number of neighbors in the observation space and always selects the same number of neighbors rather than the best similar neighbors for the target case. So, case based reasoning may have to take into account more cases even when there are fewer cases applicable depending on the subject. Second, case based reasoning may select neighbors that are far away from the target case. Thus, case based reasoning does not guarantee an optimal pseudo-neighborhood for various target cases, and the predictability can be degraded due to a deviation from the desired similar neighbor. This paper examines how the size of learning data affects stock price predictability through k-nearest neighbor and compares the predictability of k-nearest neighbor with the random walk model according to the size of the learning data and the number of neighbors. In this study, Samsung electronics stock prices were predicted by dividing the learning dataset into two types. For the prediction of next day's closing price, we used four variables: opening value, daily high, daily low, and daily close. In the first experiment, data from January 1, 2000 to December 31, 2017 were used for the learning process. In the second experiment, data from January 1, 2015 to December 31, 2017 were used for the learning process. The test data is from January 1, 2018 to August 31, 2018 for both experiments. We compared the performance of k-NN with the random walk model using the two learning dataset. The mean absolute percentage error (MAPE) was 1.3497 for the random walk model and 1.3570 for the k-NN for the first experiment when the learning data was small. However, the mean absolute percentage error (MAPE) for the random walk model was 1.3497 and the k-NN was 1.2928 for the second experiment when the learning data was large. These results show that the prediction power when more learning data are used is higher than when less learning data are used. Also, this paper shows that k-NN generally produces a better predictive power than random walk model for larger learning datasets and does not when the learning dataset is relatively small. Future studies need to consider macroeconomic variables related to stock price forecasting including opening price, low price, high price, and closing price. Also, to produce better results, it is recommended that the k-nearest neighbor needs to find nearest neighbors using the second step filtering method considering fundamental economic variables as well as a sufficient amount of learning data.

• Journal of the Daesoon Academy of Sciences
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• v.44
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• pp.177-212
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• 2023

In this study, discussions of the suppression of cultural diversity in communities was conducted. First, based on the studies conducted so far and recent changes, the oppression that exists between the Chinese government and ethnic minorities was considered. The visible suppression mentioned was the expansion of Han Chinese Mandarin language education, sanctions on minority languages, and the expansion of higher education at the exclusion of minority identities. In terms of 'invisible' oppression, urbanization, urban development with modernization at the forefront, and the use of officials from minority ethnic groups educated by the central government were items that were discussed. Next, the case of Latin America was examined. In particular, attention was paid to the theory of resistance against Europeans and European culture. Based off of the worries and experiences of Latin American intellectuals who have underwent oppression as individuals from culturally diverse backgrounds, a mature theory was formulated that could be used to defend Chinese minorities in the future. There is a specificity to the problem of Chinese minority communities. However, from a large perspective, experience and self-critical exploration in Latin America serve as an opportunity to expand the specificity of Chinese minority communities. Their situation resembles previous situations in Latin America when native cultures were being culturally eroded by Europe. Thus, as Latin American scholars argue, a shift in perception is necessary. In addition to this, in the text, it is likewise necessary to reflect on diversity, freedom, and mutualistic respect. There are proposals advocating for the realization of Heyibutong (和而不同 harmony but not through sameness) based on the situation in China. In the process of this consideration, much thought was given about what the observed communities are like and what a hypothetically desirable community would be like. This extends not only to Chinese minority communities and native residents of Latin America, but also to Asians in the United States and foreigners in Korea. Through this, it is hoped that desirable communities characterized by cultural diversity can be skillfully pursued.