• Journal of KIISE:Databases
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• v.29 no.4
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• pp.262-273
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• 2002

MOLAP is a technology that accelerates multidimensional data analysis by storing data in a multidimensional array and accessing them using their position information. Depending on a mapping scheme of a multidimensional array onto disk, the sliced of MOLAP operations such as slice and dice varies significantly. [1] proposed a MOLAP cube storage scheme that divides a cube into small chunks with equal side length, compresses sparse chunks, and stores the chunks in row-major order of their chunk indexes. This type of cube storage scheme gives a fair chance to all dimensions of the input data. Here, we developed a variant of their cube storage scheme by placing chunks in a different order. Our scheme accelerates slice and dice operations by aligning chunks to physical disk block boundaries and clustering neighboring chunks. Z-indexing is used for chunk clustering. The efficiency of the proposed scheme is evaluated through experiments. We showed that the proposed scheme is efficient for 3~5 dimensional cubes that are frequently used to analyze business data.

• International Journal of Contents
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• v.5 no.2
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• pp.59-63
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• 2009

Since it is hard to use GPS for tracking mobile user in indoor environments, much research has focused on techniques using existing wireless local area network infrastructure. Signal strength received at a fixed location is not constant, so fingerprinting approach which use pattern matching is popular. But this approach has to pay additional costs to determine user location. This paper proposes a new approach to find user's location efficiently using an index scheme. After analyzing characteristics of RF signals, the paper suggests the data processing method how the signal strength values for each of the access points are recorded in a radio map. To reduce computational cost during the location determination phase, multidimensional indexes for radio map with the important information which is the order of the strongest access points are used.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.354-357
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• 2004

Data warehouse is subject-oriented, integrated, non-volatiled data, and it used for OLAP(On-Line Analytical Processing) the extraction of information from making decision processing. In the present, lots of study have been devoted to multidimensional modeling between OLAP operator and star schema. In this paper, the design of using the snowflake schema for object-oriented conceptual relation is more extended than using drill-across operator. The object-oriented relation schema which was not applicable has been improved through the design.

• Journal of Fisheries and Marine Sciences Education
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• v.29 no.2
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• pp.526-536
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• 2017

This study intended to understand similarity of image between games and position of image attribute perceived by consumers according to the games of marine sports using MDS (Multidimensional Scaling). Through the foregoing, this study aims to provide preliminary data for establishing marketing strategies for games of marine sports by accurately understanding images of marines sports perceived by consumers. For survey targets, this study selected students of K University located in Gyeonggi-do as a population, and extracted samples using convenience sampling out of non-probability sampling methods targeting 200 students who showed intention of participation in this study, and total 188 sheets of questionnaire were used as final data excepting 12 sheets that are filled up unfaithfully or considered unreliable. For data processing, this study conducted Frequency Analysis, Descriptive Statistical Analysis, Reliability Analysis, MDS (Multidimensional Scaling) and Multiple Regression Analysis, and study results show that water ski and wakeboard(.602) have the most similar image attribute, indicating that image attributes of scuba diving and water ski(2.031) are positioned farthest with each other. As for image attribute, image attribute of water ski has appearance and progressiveness, windsurfing has an image attribute of positive, scuba diving has an image attribute of negation, and marin rafting has an image attribute of friendliness.

• Bulletin of the Korean Chemical Society
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• v.29 no.10
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• pp.2017-2022
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• 2008

Of the experiments to shorten NMR measuring time by sparse sampling, non-uniform sampling (NUS) is advantageous. NUS miminizes systematic errors which arise due to the lack of samplings by randomization. In this study, I report the real-time acquisition of 3D NMR data using NUS and maximum-entropy (MaxEnt) data processing. The real-time acquisition combined with NUS can reduce NMR measuring time much more. Compared with multidimensional decomposition (MDD) method, which was originally suggested by Jaravine and Orekhov (JACS 2006, 13421-13426), MaxEnt is faster at least several times and more suitable for the realtime acquisition. The designed sampling schedule of current study makes all the spectra during acquisition have the comparable resulting resolutions by MaxEnt. Therefore, one can judge the quality of spectra easily by examining the intensities of peaks. I report two cases of 3D experiments as examples with the simulated subdataset from experimental data. In both cases, the spectra having good qualitie for data analysis could be obtained only with 3% of original data. Its corresponding NMR measuring time was 8 minutes for 3D HNCO of ubiquitin.

• Journal of the Korea Society of Computer and Information
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• v.23 no.3
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• pp.41-48
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• 2018

The recent sudden increase of big data has characteristics such as continuous generation of data, large amount, and unstructured format. The existing relational database technologies are inadequate to handle such big data due to the limited processing speed and the significant storage expansion cost. Current implemented solutions are mainly based on relational database that are no longer adapted to these data volume. NoSQL solutions allow us to consider new approaches for data warehousing, especially from the multidimensional data management point of view. In this paper, we develop and propose the integrated design methodology based on MongoDB for big data applications. The proposed methodology is more scalable than the existing methodology, so it is easy to handle big data.

• Proceedings of the IEEK Conference
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• 2003.07b
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• pp.1137-1140
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• 2003

The area of the prototype device is less than 80mm$^2$. Operating with a 60ns clock cycle, the device typically dissipates only 300mW. The full functionality was proven by using the methodical test programs based on typical image processing operations. Also, we realized the whole process from conventional gray image to color image. Format converters, implemented using multidimensional access memories, transfer the data between the processing element array and conventional bit-parallel components in real time. The completed system is fully functional and performs typical low-level image processing tasks at speed exceeding 30 frames of traditional TV system per second.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.1211-1214
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• 2011

OLAP(On-Line Analytical Processing) 툴은 조직 운영에서 발생하는 데이터의 양이 많아짐에 따라 분석 수요도 함께 급증하며 전문 분석가의 역량만으로는 처리할 수 없는 분석 요구 사항을 충족시키기 위한 툴이다. OLAP 에서는 다양한 사용자가 직접 데이터베이스에 접근하여 대화식으로 질의를 던지고 응답을 받아 분석 업무를 진행할 수 있다. 이렇게 많은 사용자들이 데이터베이스에 직접 접근을 하게 됨에 따라 조직의 민감한 데이터를 지키기 위한 보안 정책이 필수가 되었다. 하지만 기존 연구에서는 OLAP 의 기능적인 분석에 치중하여 MDX(Multidimensional Expressions)와 XMLA(XML for Analysis) 등의 기법으로 기능을 구현하는 것에 그치고 있다. 이에 본 연구에서는 OLAP 보안 관련 연구를 분석하고 보안 모듈을 설계하여 효율적인 정보 보호를 위한 데이터 접근 제어 방법을 제시한다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.2
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• pp.103-110
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• 2011

It is necessary to accurate and efficient management for measured digital data from sensors in u-health system. It is not efficient that sensor network process input stream data of mass storage stored in database the same time. We propose to improve the processing performance of multidimensional stream data continuous incoming from multiple sensor. We propose process query based on sliding window for efficient input stream and found multiple query plan to Mjoin method and we reduce stored data using backpropagation algorithm. As a result, we obtained to efficient result about 18.3% reduction rate of database using 14,324 data sets.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.137-145
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• 2010

Digital vessel have to accurate and efficient mange the digital data from various sensors in the digital vessel. But, In sensor network, it is difficult to transmit and analyze the entire stream data depending on limited networks, power and processor. Therefore it is suitable to use alternative stream data processing after classifying the continuous stream data. In this paper, We propose efficient processing method that arrange some sensors (temperature, humidity, lighting, voice) and process query based on sliding window for efficient input stream and pre-clustering using multiple Support Vector Machine(SVM) algorithm and manage hash table to summarized information. Processing performance improve as store and search and memory using hash table and usage reduced so maintain hash table in memory. We obtained to efficient result that accuracy rate and processing performance of proposal method using 35,912 data sets.