• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.51-60
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• 2021

Due to the growth of digital media technology, there is increasing demand of personalized education based on context data of learners throughout overall education area. For music education, several studies have been conducted for providing appropriate educational contents to learners by considering some factors such as the proficiency, the amount of practice, and their capability. In this paper, a technique has been defined to recommend the appropriate music scores to learners by extracting and analyzing the practice data and chord data. Concretely, several meaningful relationships among chords patterns and learners were analyzed and visualized by constructing the learners' profiles of proficiency, extracting the chord sequences from music scores. In addition, we showed the potential for use in personalized education by analyzing music similarity, learner's proficiency similarity, learner's proficiency of music and chord, mastered chords and chords sequence patterns. After that, the chord practice programs can be effectively generated considering various music scores using the synthetically summarized chord sequence graphs for the music scores that the learners selected.

• Journal of Information Management
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• v.19 no.1
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• pp.50-72
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• 1988

The data base is a basis for the Management Information Systems (MIS) and Technical Data Packages(TDPs) are one of the key factors in the research and development activities. Most research institutes has been developed their own MIS and also MIS for the IDP has been advanced and applied in the various area. However, MIS and it's operation of the drawings and TDPs generated from researches and developments should be developed further more. In this study, we studied on the creation of data base of MIS related to the drawings, specifications and TDPs based on general concepts and priciple of MIS and data base. And finally, mentioned a design of data base consisting of drawing, specifications and related TDPs which are applied to MIS. To help to understand this system, it is presented, that three master files and six variable files were created, as a experimental data base, according to the "TOTAL" of CYBER computer system and two other user programs and it's outputs after computer run. It is expected that results of this study could be useful for TDP MIS enhancement through improvement of this study and new user program development.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.445-452
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• 2019

In this study, parallel processing codes of k-means clustering algorithm were developed and implemented in a PC-cluster for unsupervised classification of large satellite images. We implemented intra-node code using multicores of CPU (Central Processing Unit) based on OpenMP (Open Multi-Processing), inter-nodes code using a PC-cluster based on message passing interface, and hybrid code using both. The PC-cluster consists of one master node and eight slave nodes, and each node is equipped with eight multicores. Two operating systems, Microsoft Windows and Canonical Ubuntu, were installed in the PC-cluster in turn and tested to compare parallel processing performance. Two multispectral satellite images were tested, which are a medium-capacity LANDSAT 8 OLI (Operational Land Imager) image and a high-capacity Sentinel 2A image. To evaluate the performance of parallel processing, speedup and efficiency were measured. Overall, the speedup was over N / 2 and the efficiency was over 0.5. From the comparison of the two operating systems, the Ubuntu system showed two to three times faster performance. To confirm that the results of the sequential and parallel processing coincide with the other, the center value of each band and the number of classified pixels were compared, and result images were examined by pixel to pixel comparison. It was found that care should be taken to avoid false sharing of OpenMP in intra-node implementation. To process large satellite images in a PC-cluster, code and hardware should be designed to reduce performance degradation caused by file I / O. Also, it was found that performance can differ depending on the operating system installed in a PC-cluster.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.669-678
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• 2018

This study developed information technology infrastructures for building a driving environment analysis platform using various big data, such as vehicle sensing data, public data, etc. First, a small platform server with a parallel structure for big data distribution processing was developed with H/W technology. Next, programs for big data collection/storage, processing/analysis, and information visualization were developed with S/W technology. The collection S/W was developed as a collection interface using Kafka, Flume, and Sqoop. The storage S/W was developed to be divided into a Hadoop distributed file system and Cassandra DB according to the utilization of data. Processing S/W was developed for spatial unit matching and time interval interpolation/aggregation of the collected data by applying the grid index method. An analysis S/W was developed as an analytical tool based on the Zeppelin notebook for the application and evaluation of a development algorithm. Finally, Information Visualization S/W was developed as a Web GIS engine program for providing various driving environment information and visualization. As a result of the performance evaluation, the number of executors, the optimal memory capacity, and number of cores for the development server were derived, and the computation performance was superior to that of the other cloud computing.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.2
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• pp.67-76
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• 2017

In industrial site in various fields it will be generated in combination with large amounts of data have a correlation. It is able to collect a variety of data in types of industry process, but they are unable to integrate each other's association between each process. For the data of the existing industry, the set values of the molding condition table are input by the operator as an arbitrary value When a problem occurs in the work process. In this paper, design the fusion and analysis processing model of data collected for each industrial type, Prediction Case(Automobile Connect), a through for corporate earnings improvement and process manufacturing industries such as master data through standard molding condition table and the production history file comparison collected during the manufacturing process and reduced failure rate with a new molding condition table digitized by arbitrary value for worker, a new pattern analysis and reinterpreted for various malfunction factors and exceptions, increased productivity, process improvement, the cost savings. It can be designed in a variety of data analysis and model validation. In addition, to secure manufacturing process of objectivity, consistency and optimization by standard set values analyzed and verified and may be optimized to support the industry type, fits optimization(standard setting) techniques through various pattern types.