• Journal of KIISE:Information Networking
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• v.32 no.3
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• pp.370-381
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• 2005

Mobile IP provides an efficient and scalable mechanism for host mobility within the Internet. Using Mobile If, mobile nodes may change their point of attachment to the Internet without changing their If address. However, it would result in a high signaling cost. To reduce the signaling cost, we factor in the fact that mobile users will not be actively communicating much of the time. In fact, there Is no necessity to send a binding update message to the home agent when an mobile node does not communicates with others while moving. From this point of view, we propose a lazy update strategy for minimizing signaling cost using the forwarding pointer in hierarchical Mobile IPv6. In our proposal, binding updates are sent only when a mobile node is in a busy mode. If an mobile node is in a dormant mode, binding update messages are delayed until busy mode using the forwarding pointer. As a result, our proposal can reduce the total signaling cost by eliminating unnecessary binding update messages when a mobile node Is in a dormant mode. In addition to, our proposal reduces unnecessary location update cost resulting from ping-pong effect under mobile node's dormant mode. Analysis results using the discrete analytic model presented in this paper shows that our proposal can has superior performance than hierarchical Mobile nv6 when the call-to-mobility ratio is low and the length of the forwarding pointer chain K is low.

• Journal of the Economic Geographical Society of Korea
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• v.17 no.1
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• pp.129-146
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• 2014

This paper investigates how industrial diversity affects unemployment and employment instability from the perspective of the regional economy. Through this analysis, we examine how the industry-specific policy to promote some industry strategically in most of areas affects the stability of the regional economy. We measure Herfindahl indexes using the 1993-2010 data of 16 regions in Korea, and use panel regression model for empirical analysis. The main results from this empirical analysis are summarized as follows. First, we confirm that the industrial structure of most regions has been changed to the direction of specialization in 1990s and to the direction of diversification in 2000s through analyzing the changes in the values of Herfindahl indexes during the given period. Second, we find from the estimation results of panel regression model that the higher industrial diversity in most of regions is, the lower the unemployment rate is. However, a statistically significant relationship between industrial diversity and employment instability only partially confirmed. Third, there exist high unemployment rate and employment instability in most metropolitan areas, but it is hard to say that this relationship is highly statistically significant. From the results of the empirical analysis, it is likely that the industry-specific policies such as the regional strategic industry development policies unlike policy goals make the unemployment rate to rise and economic instability to increase. From the viewpoint of employment aspects, the strategies to increase industrial diversity would be desirable rather than those to specialize in the industrial structure.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.5_6
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• pp.273-279
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• 2003

Hypercube multicomputers have been drawing considerable attention from many researchers due to their regular structure and short diameter. One of keys to the performance of Hypercube is the efficiency of communication among processors. Among several communication patterns, multicast is important, which is found in a variety of applications as data replication and signal processing. As the number of processors increases, the probability of occurrences of fault components also increases. So it would be desirable to design an efficient scheme that multicasts messages in the presence of faulty component. In fault-tolerant routing and multicast, there are local information based scheme, global information based scheme and limited information based scheme in terms of information. In general, limited information is easy to obtain and maintain by compressing information in a concise format. In this paper, we propose a new routing scheme and a new multicast scheme using recently proposed fully reachability information scheme and new local information scheme. The proposed multicast scheme increases multicast success possibility and reduce deroute cases. Experiments show that multicast success possibility can increase at least 15% compared to previous method.

• Journal of the Korean School Mathematics Society
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• v.24 no.1
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• pp.59-81
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• 2021

This study aimed to investigate how the learners' mathematics learning processes change with repeatedly reading mathematical text. As a way to teach and learn mathematics, we also wanted to examine the effect of repeated reading and to explore the implications for a more efficient teaching and learning strategy. To help us with this study, we mainly used eye tracking and heart rate (HR) measurement. There were four cycles in a cycle of repeated reading, and the number of repeated readings for all cycles was fixed to three times. Eight prospective mathematics teachers in the Department of Mathematics Education of a National University in South Korea participated. Data were analyzed in five aspects: (1) the total reading time per round, the total reading time per slide; (2) the change trends of total reading time per round and slide; (3) the order of slides read; (4) the change trends of HR per round. We found that most participants read in a similar pattern in the first reading, but the second and third reading patterns appeared more diverse for each learner. Also, the first reading required the most time regardless of the repeat cycle, and the time it took to repeatedly read afterward varied depending on the individual. Based on the findings of this study, the most primary conclusion is that self-directed mathematics learning by using repeated reading is effective regardless of cycle. In addition, we suggested four strategies to improve the efficiency of this teaching and learning method.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.2
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• pp.51-78
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• 2021

Followed by 'start-up', the theme of 'scale-up' has been considered as an important agenda in both corporate and policy spheres. In particular, although it is a term commonly used in industry and policy fields, even a conceptual definition has not been achieved from the academic perspective. "Corporate Growth" in the academic aspect and "Business Growth" in the practical management field have different understandings (Achtenhagen et al., 2010). Previous research on corporate growth has not departed from Penrose(1959)'s "Firm as a bundle of resources" and "the role of managers". Based on the theory and background of economics, existing research has mainly examined factors that contribute to firms' growth and their growth patterns. Comparatively, we lack knowledge on the firms' growth with a focus on 'annual revenue growth rate'. In the early stage of the firms, they tend to exhibit a high growth rate as it started with a lower level of annual revenue. However, when the firms reach annual revenue of more than 100 billion KRW, a threshold to be classified as a 'middle-standing enterprise' by Korean standards, they are unlikely to reach a high level of revenue growth rate. In our study, we used our sample of 333 companies (6.7% out of 5,000 'fastest-growing' companies) which reached 15% of the compound annual growth rate in the last three years with more than USD 100 million. It shows that sustaining 'high-growth' above a certain firm size is difficult. The study focuses on firms with annual revenue of more than $100 billion (approximately 120 billion KRW) from the 'Inc. 2020 fast-growing companies 5,000' list. The companies have been categorized into 1) Fast-growing companies (revenue CAGR 15%~40% between 2016 and 2019), 2) Hyper-growing companies (40%~99.9%), and 3) Super-growing (100% or more) with in-depth analysis of each group's characteristics. Also, the relationship between the revenue growth rate, individual company's strategy choice (market orientation, generic strategy, growth strategy, pioneer strategy), industry/market environment, and firm age is investigated with a quantitative approach. Through conducting the study, it aims to provide a reference to the 'Hyper-Growing Model' that combines the paths and factors of growth strategies. For policymakers, our study intends to provide a reference to which factors or environmental variables should be considered for 'optimal effective combinations' to promote firms' growth.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.67-88
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• 2019

Webtoon is a Korean-style digital comics platform that distributes comics content produced using the characteristic elements of the Internet in a form that can be consumed online. With the recent rapid growth of the webtoon industry and the exponential increase in the supply of webtoon content, the need for effective webtoon content recommendation measures is growing. Webtoons are digital content products that combine pictorial, literary and digital elements. Therefore, webtoons stimulate consumer sentiment by making readers have fun and engaging and empathizing with the situations in which webtoons are produced. In this context, it can be expected that the sentiment that webtoons evoke to consumers will serve as an important criterion for consumers' choice of webtoons. However, there is a lack of research to improve webtoons' recommendation performance by utilizing consumer sentiment. This study is aimed at developing consumer sentiment pattern maps that can support effective recommendations of webtoon content, focusing on consumer sentiments that have not been fully discussed previously. Metadata and consumer sentiments data were collected for 200 works serviced on the Korean webtoon platform 'Naver Webtoon' to conduct this study. 488 sentiment terms were collected for 127 works, excluding those that did not meet the purpose of the analysis. Next, similar or duplicate terms were combined or abstracted in accordance with the bottom-up approach. As a result, we have built webtoons specialized sentiment-index, which are reduced to a total of 63 emotive adjectives. By performing exploratory factor analysis on the constructed sentiment-index, we have derived three important dimensions for classifying webtoon types. The exploratory factor analysis was performed through the Principal Component Analysis (PCA) using varimax factor rotation. The three dimensions were named 'Immersion', 'Touch' and 'Irritant' respectively. Based on this, K-Means clustering was performed and the entire webtoons were classified into four types. Each type was named 'Snack', 'Drama', 'Irritant', and 'Romance'. For each type of webtoon, we wrote webtoon-sentiment 2-Mode network graphs and looked at the characteristics of the sentiment pattern appearing for each type. In addition, through profiling analysis, we were able to derive meaningful strategic implications for each type of webtoon. First, The 'Snack' cluster is a collection of webtoons that are fast-paced and highly entertaining. Many consumers are interested in these webtoons, but they don't rate them well. Also, consumers mostly use simple expressions of sentiment when talking about these webtoons. Webtoons belonging to 'Snack' are expected to appeal to modern people who want to consume content easily and quickly during short travel time, such as commuting time. Secondly, webtoons belonging to 'Drama' are expected to evoke realistic and everyday sentiments rather than exaggerated and light comic ones. When consumers talk about webtoons belonging to a 'Drama' cluster in online, they are found to express a variety of sentiments. It is appropriate to establish an OSMU(One source multi-use) strategy to extend these webtoons to other content such as movies and TV series. Third, the sentiment pattern map of 'Irritant' shows the sentiments that discourage customer interest by stimulating discomfort. Webtoons that evoke these sentiments are hard to get public attention. Artists should pay attention to these sentiments that cause inconvenience to consumers in creating webtoons. Finally, Webtoons belonging to 'Romance' do not evoke a variety of consumer sentiments, but they are interpreted as touching consumers. They are expected to be consumed as 'healing content' targeted at consumers with high levels of stress or mental fatigue in their lives. The results of this study are meaningful in that it identifies the applicability of consumer sentiment in the areas of recommendation and classification of webtoons, and provides guidelines to help members of webtoons' ecosystem better understand consumers and formulate strategies.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.119-133
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• 2020

Fama asserted that in an efficient market, we can't make a trading rule that consistently outperforms the average stock market returns. This study aims to suggest a machine learning algorithm to improve the trading performance of an intraday short volatility strategy applying asymmetric volatility spillover effect, and analyze its trading performance improvement. Generally stock market volatility has a negative relation with stock market return and the Korean stock market volatility is influenced by the US stock market volatility. This volatility spillover effect is asymmetric. The asymmetric volatility spillover effect refers to the phenomenon that the US stock market volatility up and down differently influence the next day's volatility of the Korean stock market. We collected the S&P 500 index, VIX, KOSPI 200 index, and V-KOSPI 200 from 2008 to 2018. We found the negative relation between the S&P 500 and VIX, and the KOSPI 200 and V-KOSPI 200. We also documented the strong volatility spillover effect from the VIX to the V-KOSPI 200. Interestingly, the asymmetric volatility spillover was also found. Whereas the VIX up is fully reflected in the opening volatility of the V-KOSPI 200, the VIX down influences partially in the opening volatility and its influence lasts to the Korean market close. If the stock market is efficient, there is no reason why there exists the asymmetric volatility spillover effect. It is a counter example of the efficient market hypothesis. To utilize this type of anomalous volatility spillover pattern, we analyzed the intraday volatility selling strategy. This strategy sells short the Korean volatility market in the morning after the US stock market volatility closes down and takes no position in the volatility market after the VIX closes up. It produced profit every year between 2008 and 2018 and the percent profitable is 68%. The trading performance showed the higher average annual return of 129% relative to the benchmark average annual return of 33%. The maximum draw down, MDD, is -41%, which is lower than that of benchmark -101%. The Sharpe ratio 0.32 of SVS strategy is much greater than the Sharpe ratio 0.08 of the Benchmark strategy. The Sharpe ratio simultaneously considers return and risk and is calculated as return divided by risk. Therefore, high Sharpe ratio means high performance when comparing different strategies with different risk and return structure. Real world trading gives rise to the trading costs including brokerage cost and slippage cost. When the trading cost is considered, the performance difference between 76% and -10% average annual returns becomes clear. To improve the performance of the suggested volatility trading strategy, we used the well-known SVM algorithm. Input variables include the VIX close to close return at day t-1, the VIX open to close return at day t-1, the VK open return at day t, and output is the up and down classification of the VK open to close return at day t. The training period is from 2008 to 2014 and the testing period is from 2015 to 2018. The kernel functions are linear function, radial basis function, and polynomial function. We suggested the modified-short volatility strategy that sells the VK in the morning when the SVM output is Down and takes no position when the SVM output is Up. The trading performance was remarkably improved. The 5-year testing period trading results of the m-SVS strategy showed very high profit and low risk relative to the benchmark SVS strategy. The annual return of the m-SVS strategy is 123% and it is higher than that of SVS strategy. The risk factor, MDD, was also significantly improved from -41% to -29%.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.1-23
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• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.3
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• pp.119-129
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• 2013

This study was conducted to predict the changes in forest biomass in different ecoprovinces and forest types under climate change scenario based on cumulative data (i.e., digital forest site and climate maps, National Forest Inventory data) and various prediction models. The results from this study showed that predicted changes over time in biomass varied according to ecoprovince and forest type in Korea. A reduction in biomass was predicted for all forest types associated with the mountain, southeastern hilly, and southwestern hilly ecoprovinces. On the other hand, the biomass was predicted to increase for the coniferous forest and mixed-forest types in the central hilly ecoprovince. Furthermore, increases in biomass are predicted for all forest types, except coniferous forests, in the coastal ecoprovince. The results from this study provide a basis for developing technology to predict forest impacts due to climate change by predicting changes in forest biomass based on the estimation of site index.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.9
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• pp.146-156
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• 2017

In this study, the causal relationship between the main factors influencing the import of agricultural products and the changes in agricultural imports was investigated. In addition, we compared the magnitude of the impact of each factor on the changes in agricultural imports. It was found that the import liberalization rate, which represents the FTA factors and reflects the per capita GDP, the conditions of supply and demand of agricultural products in exporting countries and the changes in exchange rates, affects the changes of the agricultural products imports. However, the factors affecting the change of the imports by agricultural product category and the magnitude of the influence by each factor were different. This shows that various factors, other than the FTA factors, are compounding the changes in the agricultural imports. In the future, the market openings due to the implementation of the FTA will be further enlarged and the economic territory of the FTA will be further expanded, due to the implementation of additional FTAs, and the changes in the imports of agricultural products will cause damage to the domestic agricultural sector.