• Korean Journal of Childcare and Education
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• v.9 no.2
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• pp.173-189
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• 2013

The purpose of this study was to examine the relationship between children's information processing ability and basic learning abilities. To collect the data, two tests were given to 99 children. The Korean K-ABC(Moon & Byun, 1997) and Pictorial Basic Learning Abilities for Children(Kim, 2011) were used to examine the relationship between children's information processing and basic learning abilities. The collected data were analyzed by correlation analysis and multiple regression analysis. According to the results of this study, there was a significant positive correlation between information processing(sequential processing, simultaneous processing) and basic learning abilities including reading, writing, and basic mathematics. And information processing significantly affected basic learning abilities. Namely, simultaneous processing explained 22% of basic learning abilities and by adding sequential processing, the explanation was increased to 25%. In conclusion, the results of this study suggest various implications about children's basic learning abilities. These implications will help teachers and parents to understand their children's learning.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.73-78
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• 2003

In this research, we implement Realtime Air Diffusion Prediction System which is a parallel Fortran model running on distributed-memory parallel computers. The system is designed for air diffusion simulations with four-dimensional data assimilation. For regional air quality forecasting a series of dynamic downscaling technique is adopted using the NCAR/Penn. State MM5 model which is an atmospheric model. The realtime initial data have been provided daily from the KMA (Korean Meteorological Administration) global spectral model output. It takes huge resources of computation to get 24 hour air quality forecast with this four step dynamic downscaling (27km, 9km, 3km, and lkm). Parallel implementation of the realtime system is imperative to achieve increased throughput since the realtime system have to be performed which correct timing behavior and the sequential code requires a large amount of CPU time for typical simulations. The parallel system uses MPI (Message Passing Interface), a standard library to support high-level routines for message passing. We validate the parallel model by comparing it with the sequential model. For realtime running, we implement a cluster computer which is a distributed-memory parallel computer that links high-performance PCs with high-speed interconnection networks. We use 32 2-CPU nodes and a Myrinet network for the cluster. Since cluster computers more cost effective than conventional distributed parallel computers, we can build a dedicated realtime computer. The system also includes web based Gill (Graphic User Interface) for convenient system management and performance monitoring so that end-users can restart the system easily when the system faults. Performance of the parallel model is analyzed by comparing its execution time with the sequential model, and by calculating communication overhead and load imbalance, which are common problems in parallel processing. Performance analysis is carried out on our cluster which has 32 2-CPU nodes.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.1027-1038
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• 2006

There are many technical problems in the recommendation system based on very large database(VLDB). So, it is necessary to study the recommendation system' structure and the data-mining technique suitable for the large scale Internet shopping mail. Thus we design and implement the product recommendation system using k-means clustering algorithm and sequential pattern technique which can be used in large scale Internet shopping mall. This paper processes user information by batch processing, defines the various categories by hierarchical structure, and uses a sequential pattern mining technique for the search engine. For predictive modeling and experiment, we use the real data(user's interest and preference of given category) extracted from log file of the major Internet shopping mall in Korea during 30 days. And we define PRP(Predictive Recommend Precision), PRR(Predictive Recommend Recall), and PF1(Predictive Factor One-measure) for evaluation. In the result of experiments, the best recommendation time and the best learning time of our system are much as O(N) and the values of measures are very excellent.

• The KIPS Transactions:PartD
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• v.10D no.7
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• pp.1093-1102
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• 2003

As the use of internet is growing, the amount of information is increasing rapidly and XML that is a standard of the web data has the property of flexibility of data representation. Therefore electronic document systems based on web, such as EDMS (Electronic Document Management System), ebXML (e-business extensible Markup Language), have been adopting XML as the method for exchange and standard of documents. So research on the method which can manage and search structural XML documents in an effective wav is required. In this paper we propose the clustering method based on structural similarity among the many XML documents, using typical structures extracted from each document by sequential pattern mining in pre-clustering process. The proposed algorithm improves the accuracy of clustering by computing cost considering cluster cohesion and inter-cluster similarity.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.4
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• pp.2818-2827
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• 2015

The spatial patterns and characteristics of these sequential earthquakes and ground motions induced by the earthquakes are examined by contours of peak ground velocity (PGV) and geometric mean peak ground velocity (GMPGV) using both ordinary kriging in geographical information system (GIS) and data, the records obtained from strong motion stations, acquired after recent sequential earthquakes in Canterbury, New Zealand (NZ). The performance of underground water pipeline system is examined by using data acquired after earthquakes. The spatial distribution of GMPGV is superimposed on water pipeline repairs throughout the water distribution system in areas affected principally by transient ground motion using GIS and then water pipeline repair rates, expressed as repairs/km, for different types of pipe are evaluated relative to the estimated GMPGV outside liquefaction areas. The earthquake performance of underground water pipeline systems is summarized in this study.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.8
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• pp.565-570
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• 2013

Previous researches on mining sequential patterns mainly focused on discovering patterns from the point-based event. Interval events with a time interval occur in the real world that have the start and end point. Existing interval pattern mining methods that discover relationships among interval events based on the Allen operators have some problems. These are that interval patterns having three or more interval events can be interpreted as several meanings. In this paper, we propose the I_TPrefixSpan algorithm, which is an efficient sequence pattern mining technique for removing ambiguity in the Interval Patterns Mining. The proposed algorithm generates event sequences that have no ambiguity. Therefore, the size of generated candidate set can be minimized by searching sequential pattern mining entries that exist only in the event sequence. The performance evaluation shows that the proposed method is more efficient than existing methods.

• The Transactions of the Korea Information Processing Society
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• v.5 no.8
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• pp.1997-2012
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• 1998

It is necessary to find out the parallelism in tlle sequential Java program to execute it on the parallel machine. The loop is a fundamental source to exploit parallelism as it process a large portion of total execution time in sequential Java program on the parallel machine. However, a complete parallel execution can hardly be achieved due to data dependence. This paper proposes the method of exploiting the implicit parallelism by structuring a dependence graph through the analysis of data dependence in the existing Java programming language having a nested loop structure. The parallel code generation method through the restructuring compiler and also the translation method of Java source program into multithread statement. which is supported by the Java programming language itself, are proposed here. The perforance evaluatlun of the program translaed into the thread statement is conducted using the trip cunt of loop and the trip Count of luop and the thread count as parameters The resttucturing compiler provides efficient way of exploiting parallelism by reducing manual overhead conveliing sequential Java program into parallel code. The execution time for the Java program as a result can be reduced un the parallel machine.

• The Journal of Information Systems
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• v.22 no.3
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• pp.25-42
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• 2013

Recently various kinds of Information Technology services are created and the quantities of the data flow are increase rapidly. Not only that, but the data patterns that we deal with also slowly becoming diversity. As a result, the demand of discover the meaningful knowledge/information through the various mining analysis such as linkage analysis, sequencing analysis, classification and prediction, has been steadily increasing. However, solving the business problems using data mining analysis does not always concerning, one of the major causes of these limitations is there are some analyzed data can't accurately reflect the real world phenomenon. For example, although the time gap of purchasing the two products is very short, by using the traditional sequencing analysis, the precedence relationship of the two products is clearly reflected. But in the real world, with the very short time interval, the precedence relationship of the two purchases might not be defined. What was worse, the sequence of the purchase intention and the sequence of the purchase realization of the two products might be mutually be reversed. Therefore, in this study, an expanded sequencing analysis methodology has been proposed in order to reflect this situation. In this proposed methodology, the purchases that being made in a very short time interval among the purchase order which might not important will be notice, and the analysis which included the original sequence and reversed sequence will be used to extend the analysis of the data. Also, to some extent a very short time interval can be defined as the time interval, so an experiment were carried out to determine the varying based on the time interval for the actual data.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.5
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• pp.293-299
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• 2007

Intelligent pipeline inspection gauges (PIGs) are inspection vehicles that move along within a (gas or oil) pipeline and acquire signals (also called sensor data) from their surrounding rings of sensors. By analyzing the signals captured in intelligent PIGs, we can detect pipeline defects, such as holes and curvatures and other potential causes of gas explosions. There are two major data access patterns apparent when an analyzer accesses the pipeline signal data. The first is a sequential pattern where an analyst reads the sensor data one time only in a sequential fashion. The second is the repetitive pattern where an analyzer repeatedly reads the signal data within a fixed range; this is the dominant pattern in analyzing the signal data. The existing PIG software reads signal data directly from the server at every user#s request, requiring network transfer and disk access cost. It works well only for the sequential pattern, but not for the more dominant repetitive pattern. This problem becomes very serious in a client/server environment where several analysts analyze the signal data concurrently. To tackle this problem, we devise a fast in-memory cache manager, called T-Cache, by considering pipeline sensor data as multiple time-series data and by efficiently caching the time-series data at T-Cache. To the best of the authors# knowledge, this is the first research on caching pipeline signals on the client-side. We propose a new concept of the signal cache line as a caching unit, which is a set of time-series signal data for a fixed distance. We also provide the various data structures including smart cursors and algorithms used in T-Cache. Experimental results show that T-Cache performs much better for the repetitive pattern in terms of disk I/Os and the elapsed time. Even with the sequential pattern, T-Cache shows almost the same performance as a system that does not use any caching, indicating the caching overhead in T-Cache is negligible.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.65-70
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• 1989

Lately, at an epock of a full-scale satellite launching plan of Korea, T.T.C(Tracking, Telemetery & Command) is a indispensable part. In this paper, particular attention is given to orbit determination problem of the role of T.T.C. A near-earth satellite is modeled, batch and extended sequential estimation algorithm (ESEA) are compared using range data. As a result, ESEA show effectiveness.