• Journal of the Korea Society of Computer and Information
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• v.19 no.1
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• pp.191-201
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• 2014

The purpose of this study is to propose strategies of puzzle-based learning for Informatics gifted education through analyzing Informatics gifted elementary students' computational problem solving approaches in puzzle-based learning contexts. Six types of educational puzzles, which are constraints, optimization, probability, statistically speaking, pattern recognition, and strategy, were used in teaching 14 Informatics gifted students for 8 sessions. The results of pre and post test and each students' answers were analyzed to identify why students were not able to solve the puzzles. We also analysed what essential computational strategies are needed to solve each type of puzzles, and what students did not know in solving puzzle problems. We identified some problems caused by puzzle representation methods, and various students' intuitions that disturb puzzle solving. Also, we identified essential computational strategies to solve puzzles: backtracking, dynamic programming, abstraction, modeling, and reduction of big problem. However, students had difficulties in applying these strategies to solve their puzzle problems. We proposed the revised puzzle-based learning strategies, which is based on the improved problem representation, just-in-time cognitive feedbacks, and web-based learning system.

• The KIPS Transactions:PartB
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• v.14B no.4
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• pp.287-294
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• 2007

Many classification algorithms for real world data suffer from a data class imbalance problem. To solve this problem, various methods have been proposed such as altering the training balance and designing better sampling strategies. The previous methods are not satisfy in the distribution of the input data and the constraint. In this paper, we propose a focused sampling method which is more superior than previous methods. To solve the problem, we must select some useful data set from all training sets. To get useful data set, the proposed method devide the region according to scores which are computed based on the distribution of SOM over the input data. The scores are sorted in ascending order. They represent the distribution or the input data, which may in turn represent the characteristics or the whole data. A new training dataset is obtained by eliminating unuseful data which are located in the region between an upper bound and a lower bound. The proposed method gives a better or at least similar performance compare to classification accuracy of previous approaches. Besides, it also gives several benefits : ratio reduction of class imbalance; size reduction of training sets; prevention of over-fitting. The proposed method has been tested with kNN classifier. An experimental result in ecoli data set shows that this method achieves the precision up to 2.27 times than the other methods.

• Cartoon and Animation Studies
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• s.18
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• pp.37-56
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• 2010

This paper focalizes on the 'evolution' of monster animation and . Actually, Many characters' 'Evolution' is a very powerful convention of Japanese genre animation. Lots of young people feel a huge pleasure about character's evolution. It is a fantastic spectacle to boys and girls. The first characteristic point of characters' evolution is growing-up body to an adult. For example, magical girls genre shows a woman's sexy body. This scene gives a sexual fantasy to young girl spectators, a voyeuristic visual pleasure to young boy spectators. The second point is that a transforming-body gains some super power or magical power. The third point is that a great many characters is in one text. In , characters' numbers go on increasing through 6 ways-hybrid type, mutant-reiteration type, metamorphosis type, simple-grownup type, narrative type, multiple evolution type. The evolution of has to pay attention to only one transforming way. Most Digimon characters are becoming to a human-weapons cyborg. In my opinion, this is very dangerous phenomenon with a political ideology.

• Journal of Korean Society of Transportation
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• v.28 no.1
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• pp.39-49
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• 2010

Although many studies have been carried out on the pattern of behavior of drivers which result from the provision of traffic information, there have been few detailed studies on the composition of message, method for message expression, timing of provision, point of provision, media for provision, changes by traffic condition, etc. This study was intended to provide an insight into the changes in the characteristics related to the provision of information by analyzing how the patterns of information utilization change depending on the traffic condition and reclassifying such patterns according to the characteristics of media. Unlike the existing studies, this study adopted the traffic condition, using rate of information media, and the correlation coefficient label as the basis for information media classification, and categorized them into passive utilization media, active utilization media, and past experience in order to ensure the statistical reasonability. The categorized using rate of information media and traffic condition was found to have a positive(+) correlation with the travel speed in the case of passive utilization media during both consecutive holidays(Korea's traditional Thanksgiving day) and weekends, but had a negative(-) correlation with the positive utilization media and past experience. The rate of decision to take a detour based on the past experience was high at the condition of congestion or slow during both consecutive holidays and weekends, but the rate of decision to take a detour through passive utilization media was high in a smooth traffic. In other words, if the traffic condition worsens, using rate of passive utilization media would be low while the diversion rate would be high which uses the active utilization media and past experience. Therefore, it should be established to suit the traffic condition and media characteristics for strategies of traffic distribution through drivers' diversion behavior on weekends and consecutive holidays.

• Journal of KIISE:Software and Applications
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• v.35 no.2
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• pp.70-80
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• 2008

Today, businesses have to respond with flexibility and speed to ever-changing customer demand and market opportunities. Service-oriented architecture (SOA) is the best methodology for minimizing the complexity and the cost of enterprise-level infrastructure and for maximizing the productivity and the flexibility of an enterprise. Most of the enterprise-level SOA delivery strategies deal with the top-down approach, which organization has to define the business processes, to model business services, and to find the required services or to develop new services. However, a lot of peoples want to maximally reuse legacy component-based systems as well as to deliver SOA into their organizations. In this paper, we propose a bottom-up approach for identifying business services with proper granularity. It can improve the reusability and maintenance of services by considering not data I/O of components of legacy applications but GUI event patterns. Our proposed method is applied to MIS with 129 GUIs and 13 components. As a result, the valiance of the coupling value of components is increased five times and three business services are distinctly exposed. It also provides a 49% improvement in reducing the relationship problems between services over a service identification method using only partitioning information of components.

• Journal of Intelligence and Information Systems
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• v.9 no.3
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• pp.23-47
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• 2003

Traditional studies for customer relationship management (CRM) generally focus on static CRM in a specific time frame. The static CRM and customer behavior knowledge derived could help marketers to redirect marketing resources fur profit gain at that given point in time. However, as time goes, the static knowledge becomes obsolete. Therefore, application of CRM to an online retailer should be done dynamically in time. Customer-based analysis should observe the past purchase behavior of customers to understand their current and likely future purchase patterns in consumer markets, and to divide a market into distinct subsets of customers, any of which may conceivably be selected as a market target to be reached with a distinct marketing mix. Though the concept of buying-behavior-based CRM was advanced several decades ago, virtually little application of the dynamic CRM has been reported to date. In this paper, we propose a dynamic CRM model utilizing data mining and a Monitoring Agent System (MAS) to extract longitudinal knowledge from the customer data and to analyze customer behavior patterns over time for the Internet retailer. The proposed model includes an extensive analysis about a customer career path that observes behaviors of segment shifts of each customer: prediction of customer careers, identification of dominant career paths that most customers show and their managerial implications, and about the evolution of customer segments over time. furthermore, we show that dynamic CRM could be useful for solving several managerial problems which any retailers may face.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.2
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• pp.987-994
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• 2015

This study examines how single-person household expenditure patterns are different with respect to age and income groups using Tobit model. The expenditure data of the national household survey from 2006 to 2012 were used. The results show that income elasticities of all items are greater than 1 except for food & beverage, housing, water, electricity & gas, and Communication. Income elasticities are significantly different among consuming items. Additionally the income elasticities are also different between various age and income groups of single-person households. Therefore governments and businesses have to take this into account when devising their policies or strategies regarding single-person households. Especially, businesses need to adopt a strategy targeted at single-person households with high income and buying power such as unmarried professional people. As the number of single-person household increases the proportion of expenditures on necessities such as beverage, food, and energy is expected to decrease while that on services increases. Consequently policy responses are required to prepare for the expansion of service industries such as health, hospital, and housekeeping services.

• Journal of Korea Multimedia Society
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• v.6 no.2
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• pp.194-207
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• 2003

This paper presents an optimal design methodology for the multidimensional nested attribute index (MD-NAI) that uses a multidimensional index structure for indexing the nested attributes in object databases. The MD-NAI efficiently supports complex queries involving both nested attributes and class hierarchies, which are not supported by the nested attribute index using one-dimensional index structure such as $B^+$-tree. However, the performance of the MD-NAI is very degraded in some cases of user's query types. In this paper, for the performance enhancement of the MD-NAI, we first determine the optimal shape of index page region by using the query information about the nested predicates, and then construct an optimal MD NAI by applying a region splitting strategy that makes the shape of the page regions of the MD-NAI as close as possible to the predetermined optimal one. For performance evaluation, we perform extensive experiments with the MD-NAI using various types of nested predicates and object distribution. The results indicate that our proposed method builds optimal MD-NAI regardless of the query types and object distributions. When the interval ratio of a three-dimensional query region is 1:16:236, the performance of the proposed method is enhanced by as much as 5.5 times over that of the conventional method employing the cyclic splitting strategy.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.304-316
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• 2021

The purpose of this study is to analyze the records of 8 people with mental disabilities who had participated in Research and Mutual Help of Bethel's House and to investigate the occurrence of mental crisis and process of self-help by using the grounded theory method. As a result of axial coding, the central phenomenon of crisis experience of the people with mental disabilities was derived as 'being overwhelmed by hardships in the life related to their symptoms'. In the self-help process of overcoming the crisis, Action-interaction strategies were derived as 'talking about the hardships', 'researching and practicing with peers', 'participating in various groups', etc. through the intervening conditions such as 'understanding patterns and meanings of hardships led by the person' and 'finding ways to overcome the hardships with the person'. These strategies were analyzed as a process in which the person with mental disabilities leads his/her life reassuming control over his/her crisis. The result of this study shows that it is necessary to expand the political crisis concept in the support system for the mental crisis of people with mental disabilities, and the self-help approach in which the persons participate autonomously can be useful.

• Journal of Korean Society of Forest Science
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• v.108 no.1
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• pp.116-126
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• 2019

The production volume and amount of non-timber forest products in Korea has been on the increase for the past five years. In particular, the production amount of wild vegetables (edible mountain plants) is approximately KRW 400 billion as of 2017, accounting for 14 % of the total production amount of non-timber forest products. Among wild vegetables, especially the production volumes and amounts of bracken, saw-wort (Saussurea), and thistle have grown steadily. Nevertheless, severe price competition with cheap imports and little changes in the pattern of wild vegetable consumption may negatively affect the prices of domestic wild vegetables. This, in turn, can decrease the overall consumption of wild vegetables. Recently, however, consumers have preferred healthy food with increases in their income and interest in health. Therefore, now is a crucial time for the wild vegetable market. Accordingly, this study analyzed consumers' purchase and consumption behavior related to wild vegetables through a consumer survey to contribute to establishing various strategies and policies for promoting the consumption of these vegetables. Also, this study identified consumers' awareness and intention regarding wild vegetables by analyzing social big data. Different from previous studies, this study investigated consumers' awareness and intention by analyzing SNS social big data, as well as conducting a survey. The results of the study will help prioritize strategies and policies for boosting the consumption of wild vegetables.