• Journal of the Korean Data and Information Science Society
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• v.21 no.3
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• pp.605-619
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• 2010

Caching of frequently accessed data in multi-hop ad hoc environment is a technique that can improve data access performance and availability. Cooperative caching, which allows sharing and coordination of cached data among several clients, can further en-hance the potential of caching techniques. In this paper, we propose a fuzzy cooperative caching scheme in mobile ad hoc networks. The cache management of the proposed caching scheme not only uses adaptively CacheData or CachePath based on data sim-ilarity and data utility, but also uses the replacement manager based on data pro t. Also, the proposed caching scheme uses a prefetch manager. When the TTL of the cached data expires, the prefetch manager evaluates the popularity index of the data. If the popularity index is larger than a threshold, the data is prefetched. Otherwise, its space is released. The performance of the proposed scheme is evaluated analytically and is compared to that of other cooperative caching schemes.

• Genomics & Informatics
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• v.1 no.2
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• pp.65-74
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• 2003

Data mining differs primarily from traditional data analysis on an important dimension, namely the scale of the data. That is the reason why not only statistical but also computer science principles are needed to extract information from large data sets. In this paper we briefly review data mining, its characteristics, typical data mining algorithms, and potential and ongoing applications of data mining at biopharmaceutical industries. The distinguishing characteristics of data mining lie in its understandability, scalability, its problem driven nature, and its analysis of retrospective or observational data in contrast to experimentally designed data. At a high level one can identify three types of problems for which data mining is useful: description, prediction and search. Brief review of data mining algorithms include decision trees and rules, nonlinear classification methods, memory-based methods, model-based clustering, and graphical dependency models. Application areas covered are discovery compound libraries, clinical trial and disease management data, genomics and proteomics, structural databases for candidate drug compounds, and other applications of pharmaceutical relevance.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.73-77
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• 2021

As the big data analysis technologies has been developed worldwide, the importance of asset management for electric power facilities based data analysis is increasing. It is essential to secure quality of data that will determine the performance of the RISK evaluation algorithm for asset management. To improve reliability of asset management, asset data must be preprocessed. In particular, the process of cleaning dirty data is required, and it is also urgent to develop an algorithm to reduce time and improve accuracy for data treatment. In this paper, the result of the development of an automatic cleaning algorithm specialized in overhead transmission asset data is presented. A data cleaning algorithm was developed to enable data clean by analyzing quality and overall pattern of raw data.

• Journal of Korea Multimedia Society
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• v.25 no.9
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• pp.1291-1306
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• 2022

The dual image-based reversible data hiding scheme embeds secret data into two images to increase the embedding capacity of secret data. The dual image-based reversible data hiding scheme can transmit a lot of secret data. Therefore, various schemes have been proposed until recently. In 2021, Chen and Hong proposed a dual image-based reversible data hiding scheme that embeds a large amount of secret data using a reference matrix, secret data, and bit values. However, in this paper, more secret data can be embedded than Chen and Hong's scheme. To achieve this goal, the proposed scheme generates polynomials and shared values using secret sharing scheme, and embeds secret data using reference matrix and septenary number, and random value. Experimental results show that the proposed scheme can transmit more secret data to the receiver while maintaining the image quality similar to other dual image-based reversible data hiding schemes.

• Publications of The Korean Astronomical Society
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• v.29 no.3
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• pp.45-52
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• 2014

This paper describes the development of algorithm for direct data transmission between Raw VLBI Data Buffer (RVDB) and Huge Capacity Data Server (HCDS) operated in Korea-Japan Correlation Center (KJCC). The transmitted data is the VLBI observation data, which is recorded at each radio telescope site, and the data transmitting rate is varying from 1 Gbps, in usual case, upto 8 Gbps. The developed algorithm for data transmission enables the direct data transmission between RVDB and HCDS through 10 Gbps optical network using VLBI Data Interchange Format (VDIF). Proposed method adopts the conventional UDP/IP protocol, but in order to prevent the loss of data during data transmission, the packet error monitoring and data re-transmission functions are newly designed. The VDIF specification and VDIFCP (VDIF Control Protocol) are used for the direct data transmission between RVDB and HCDS. To validate the developed algorithm for data transmission, we conducted the data transmission from RVDB to HCDS, and compared to the transmitted data with the original data bit by bit. We confirmed that the transmitted data is identical to the original data without any loss and it has been recovered well even if there were some packet losses.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1993-1998
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• 2004

This paper proposes a new framework for control system design, called the data-based control approach or data space approach, in which the input and output data of a dynamical system is directly and solely used to analyze or design a control system without the employment of any mathematical models like transfer functions, state space equations, and kernel representations. Since, in this approach, most of the analysis and design processes are carried out in the domain of the data space, we introduce some notions of geometrical objects, e.g., the openloop and closed-loop data spaces, which serve as the system representations in the data space. In addition, we establish a relationship between the open-loop and closed-loop data spaces that the closed-loop data space is contained in the open-loop data space as one of its subspaces. By using this relationship, we can derive the data-based stabilization condition for a linear time-invariant discrete-time system, which leads to a linear matrix inequality with a rank constraint.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.927-935
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• 2007

Currently, Gyeongnam province is executing the social index survey every year to the provincials. But, this survey has the limit of the analysis as execution of the different survey per 3 year cycles. The solution of this problem is data fusion. Data fusion is the process of combining multiple data in order to provide information of tactical value to the user. But, data fusion doesn#t mean the ultimate result. Therefore, efficient analysis for the data fusion is also important. In this study, we present data fusion method of statistical survey data. Also, we suggest application methodology of association rule mining by clustering through data fusion of statistical survey data.

• Journal of Platform Technology
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• v.8 no.2
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• pp.3-9
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• 2020

Big Data is a new concept in the global and local area. This field has gained tremendous momentum in the recent years and has attracted attention of several researchers. Big Data is a data analysis methodology enabled by recent advances in information and communications technology. However, big data analysis requires a huge amount of computing resources making adoption costs of big data technology. Therefore, it is not affordable for many small and medium enterprises. We survey the concepts and characteristics of Big Data along with a number of tools like HADOOP, HPCC for managing Big Data. It also presents an overview of big data like Characteristics of Big data, big data technology, big data management tools etc. We have also highlighted on some challenges and opportunities related to the fields of big data.

• New & Renewable Energy
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• v.20 no.1
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• pp.95-101
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• 2024

Since 1990, the Renewable Big Data Research Lab at the Korea Institute of Energy Technology has been observing solar radiation at 16 sites across South Korea. Serving as the National Reference Standard Data Center for Renewable Energy since 2012, it produces essential data for the sector. By 2020, it standardized meteorological year data from 22 sites. Despite user demand for data from approximately 260 sites, equivalent to South Korea's municipalities, this need exceeds the capability of measurement-based data. In response, our team developed a method to derive solar radiation data from satellite images, covering South Korea in 400,000 grids of 500 m × 500 m each. Utilizing satellite-derived data and ERA5-Land reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF), we produced standard meteorological year data for 1,000 sites. Our research also focused on data measurement traceability and uncertainty estimation, ensuring the reliability of our model data and the traceability of existing measurement-based data.

• Informatization Policy
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• v.28 no.4
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• pp.54-75
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• 2021

The right to data portability needs to be introduced to strengthen the self-control of data subjects and promote personal data use. However, the right to data portability constitutes a high risk of invasion of privacy of data subjects and may infringe on the property rights of data controllers, so careful and thorough design is warranted. The right to data portability can intensify the concentration and monopoly of personal data, result in problems of overseas transfer of personal data held by public institutions, and enrich only the profits of giant platforms by burdening the data subject with high transfer cost. By contrast, SMEs are more likely to endure a personal data deprivation. From the proposed amendment to the Personal Data Protection Act are raised various legal issues such as. i) Whether to include inferred/derived data, personal data held by public institutions, activity data, sensitive data, and personal data of third parties within the scope of data portability; ii) whether SMEs are included in the data porting organization; iii) whether to exclude SMEs or large platforms from the scope of the data receiving organization; iv) Whether to allow the right to transmit to other data controllers, v) Whether to allow the overseas transfer of personal data held by public institutions, vi) How to safely exercise the right to data portability, vii) the scope of responsibility and immunity of a data porting organization, etc. The purpose of this paper is to propose the direction for legislative action based on various legal issues related to data portability.