• The Journal of Sustainable Design and Educational Environment Research
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• v.19 no.2
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• pp.11-20
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• 2020

The goal of this study was to investigate the implementation and related issues of the school space innovation issued by key Korean mass media using text mining. To accomplish this goal, this study collected 519 news articles associated with the school space innovation issued by 54 Korean mass media companies. Based on this data, this study performed the frequency analysis and network analysis regarding the keywords. Based on the findings, the characteristics of school space innovation are summarized as follows: First, school space innovation has progressed in response to future education. Second, users are actively participating in school space innovation. Third, experts are supporting the innovation of school space by establishing a cooperative system. Fourth, the community is actively considering the innovation of school space. Fifth, the main projects of the Ministry of Education and the Provincial Offices of Education are actively conducted in a mix of top-down and bottom-up approaches. The findings of this study will contribute to providing a clear direction for contemporary school space innovation and implications for future research agenda and implementation.

• The KIPS Transactions:PartD
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• v.16D no.1
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• pp.113-122
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• 2009

Since the traditional pattern mining methods only probe unspecified moving patterns that seem to satisfy users' requests among diverse patterns within the limited scopes of time and space, they are not applicable to problems involving the mining of optimal moving patterns, which contain complex time and space constraints, such as 1) searching the optimal path between two specific points, and 2) scheduling a path within the specified time. Therefore, in this paper, we illustrate some problems on mining the optimal moving patterns with complex time and space constraints from a vast set of historical data of numerous moving objects, and suggest a new moving pattern mining method that can be used to search patterns of an optimal moving path as a location-based service. The proposed method, which determines the optimal path(most frequently used path) using pattern frequency retrieved from historical data of moving objects between two specific points, can efficiently carry out pattern mining tasks using by space generalization at the minimum level on the moving object's location attribute in consideration of topological relationship between the object's location and spatial scope. Testing the efficiency of this algorithm was done by comparing the operation processing time with Dijkstra algorithm and $A^*$ algorithm which are generally used for searching the optimal path. As a result, although there were some differences according to heuristic weight on $A^*$ algorithm, it showed that the proposed method is more efficient than the other methods mentioned.

• ETRI Journal
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• v.29 no.3
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• pp.336-352
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• 2007

Sequential pattern mining has become an essential task with broad applications. Most sequential pattern mining algorithms use a minimum support threshold to prune the combinatorial search space. This strategy provides basic pruning; however, it cannot mine correlated sequential patterns with similar support and/or weight levels. If the minimum support is low, many spurious patterns having items with different support levels are found; if the minimum support is high, meaningful sequential patterns with low support levels may be missed. We present a new algorithm, weighted interesting sequential (WIS) pattern mining based on a pattern growth method in which new measures, sequential s-confidence and w-confidence, are suggested. Using these measures, weighted interesting sequential patterns with similar levels of support and/or weight are mined. The WIS algorithm gives a balance between the measures of support and weight, and considers correlation between items within sequential patterns. A performance analysis shows that WIS is efficient and scalable in weighted sequential pattern mining.

• Journal of Internet Computing and Services
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• v.10 no.5
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• pp.49-63
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• 2009

The performance of spatio-temporal moving pattern mining depends on how to analyze and process the huge set of spatio-temporal data due to the nature of it. The several method was presented in order to solve the problems in which existing spatio-temporal moving pattern mining methods[1-10] have, such as increasing execution time and required memory size during the pattern mining, but they did not solve properly yet. Thus, we proposed the STMP/MST method[11] as a preceding research in order to extract effectively sequential and/or periodical frequent occurrence moving patterns from the huge set of spatio-temporal moving data. The proposed method reduces patterns mining execution time, using the moving sequence tree based on hash tree. And also, to minimize the required memory space, it generalizes detailed historical data including spatio-temporal attributes into the real world scopes of space and time by using spatio-temporal concept hierarchy. In this paper, in order to verify the effectiveness of the STMP/MST method, we compared and analyzed performance with existing spatio-temporal moving pattern mining methods based on the quantity of mining data and minimum support factor.

• International Journal of Aeronautical and Space Sciences
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• v.8 no.2
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• pp.28-36
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• 2007

A multi-objective design exploration for a three-element airfoil consisted of a slat, a main wing, and a flap was carried out. The lift curve improvement is important to design high-lift system, thus design has to be performed with considered multi-angle. The objective functions considered here are to maximize the lift coefficient at landing and near stall conditions simultaneously. Kriging surrogate model which was constructed based on several sample designs is introduced. The solution space was explored based on the maximization of Expected Improvement (EI) value corresponding to objective functions on the Krigingmodels. The improvement of the model and the exploration of the optimum can be advanced at the same time by maximizing EI value. In this study, a total of 90 sample points are evaluated using the Reynolds averaged Navier-Stokes simulation(RANS) for the construction of the Kriging model. In order to obtain the information of the design space, two data mining techniques are applied to design result. One is functional Analysis of Variance(ANOVA) which can show quantitative information and the other is Self-Organizing Map(SOM) which can show qualitative information.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.1
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• pp.49-55
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• 2006

Two data mining techniques, analysis of variance (ANOVA) and self-organizing map (SOM), are applied to knowledge discovery in aerodynamic design space. These methods make it possible to identify the effect of each design variable on the objective functions. Furthermore, ANOVA shows the effect of interaction between design variables on the objective function and SOM visualizes the trade-off among objective functions. Present methods are applied to the result of the supersonic wing design which includes 72 design variables and 4 objective functions.

• Journal of Information Technology Applications and Management
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• v.19 no.1
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• pp.85-100
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• 2012

The development of technology causes a lot of change. Many researchers have insisted that the proliferation of cyber space changes the physical space. Their insistences have been accumulated into three aspects. Firstly, the proliferation of cyber space brings out the concentration in the physical space, secondly the decentralization and lastly both at the same time. In Korea, the concentration of plastic surgery clinics has taken place in Kangnam-gu area at similar period of the Internet proliferation. In this research, we execute empirical study of whether the concentration of plastic surgery in specific areas correlates with the proliferation of cyber space or not. In order to do this, we verified homogeneity of plastic surgery websites between Kangnam-gu and Non-Kangnam-gu areas. Also, we used three statistical and data-mining techniques which are Multi-discriminant analysis, Decision tree analysis and artificial neural network analysis. As a result, there was homogeneity between two different area plastic surgery clinics websites, but there was not big heterogeneity as well. Therefore, in this case of concentration of plastic surgery in Korea, the proliferation of cyber space restrictively correlates with the concentration of physical space.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.231-242
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• 2007

The existing pattern mining methods[1,2,3,4,5,6,11,12,13] do not use location generalization method on the set of location history data of moving object, but even so they simply do extract only frequent patterns which have no spatio-temporal constraint in moving patterns on specific space. Therefore, it is difficult for those methods to apply to frequent pattern mining which has spatio-temporal constraint such as optimal moving or scheduling paths among the specific points. And also, those methods are required more large memory space due to using pattern tree on memory for reducing repeated scan database. Therefore, more effective pattern mining technique is required for solving these problems. In this paper, in order to develop more effective pattern mining technique, we propose new location generalization method that converts data of detailed level into meaningful spatial information for reducing the processing time for pattern mining of a massive history data set of moving object and space saving. The proposed method can lead the efficient spatial moving pattern mining of moving object using by creating moving sequences through generalizing the location attributes of moving object into 2D spatial area based on $R^*$-Tree and Area Grid Hash Table(AGHT) in preprocessing stage of pattern mining.

• The Journal of the Korea Contents Association
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• v.8 no.9
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• pp.19-26
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• 2008

With the development of ubiquitous computing and the construction of infrastructure for one-to-one personalized services, the importance of context-aware services based on user's situation and environment is being spotlighted. The smart home technology connects real space and virtual space, and converts situations in reality into information in a virtual space, and provides user-oriented intelligent services using this information. In this paper, we proposed the discovery of the behavior sequence pattern using the mining in the smart home. We discovered the behavior sequence pattern by using mining to add time variation to the association rule between locations that occur in location transactions. We can predict the path or behavior of user according to the recognized time sequence and provide services accordingly. To evaluate the performance of behavior consequence pattern using mining, we conducted sample t-tests so as to verify usefulness. This evaluation found that the difference of satisfaction by service was statistically meaningful, and showed high satisfaction.

• Tunnel and Underground Space
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• v.32 no.3
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• pp.173-193
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• 2022

In this study, international standardization trend of smart mining technology was analyzed focusing on the guidelines developed by GMG (Global Mining Guidelines Group). GMG is a non-profit organization that unites the global mining community. It was established to promote mining safety, innovation and sustainability. Currently, GMG's working group consists of artificial intelligence, asset management, autonomous mining, cybersecurity, data access and usage/interoperability, the electric mine, mineral processing, underground mining, and sustainability. Guideline development projects related to smart mining technology are being conducted in artificial intelligence, autonomous mining, cybersecurity, data access and usage/interoperability, and underground mining. As of April 2022, eight types of smart mining-related guidelines have been published through pre-launch, launch, guideline definition, contents generation, technical editing/layout/final review, and voting process. It is judged that the GMG guidelines can be an important reference for the development of domestic smart mining technology standards.