• Proceedings of the Korea Institute of Applied Superconductivity and Cryogenics Conference
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• 2002.02a
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• pp.303-305
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• 2002

SSTF(Samsung Superconducting Test Facility) has been constructed at Samsung Advanced Institute of Technology to test the KSTAR(Korea Superconducting Tokamak Advanced Research) superconducting magnets and conductors. The SSTF DAC(Data Acquisition and Control) system basically consists of VME I/O modules, host PCs, and Ethernet links. VxWorks is used for the real-time OS of the VME IOC(Input/output Controller). EPICS (Experimental Physics and Industrial Control System) provides a software architecture for the communication between IOCs and host PCs. For the efficient management of measured data, the database management programs through NFS(Network File System) have been developed and successfully operated. In this paper, the current status of the SSTF DAC system, DBMS(DataBase Management System), recent test results, and future plans are presented.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.161-168
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• 2024

As the size of big data models grows, distributed training is emerging as an essential element for large-scale machine learning tasks. In this paper, we propose ParamHub for distributed data training. During the training process, this agent utilizes the provided data to adjust various conditions of the model's parameters, such as the model structure, learning algorithm, hyperparameters, and bias, aiming to minimize the error between the model's predictions and the actual values. Furthermore, it operates autonomously, collecting and updating data in a distributed environment, thereby reducing the burden of load balancing that occurs in a centralized system. And Through communication between agents, resource management and learning processes can be coordinated, enabling efficient management of distributed data and resources. This approach enhances the scalability and stability of distributed machine learning systems while providing flexibility to be applied in various learning environments.

• Journal of Advanced Navigation Technology
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• v.28 no.3
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• pp.348-355
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• 2024

A current source capable of stably supplying current as a measurement medium is required in order to measure and test important facilities that require large-scale measurement current, such as a control element drive mechanism control system(CEDMCS), in case of dismantling a nuclear power plant. However, it can provides only voltage power as a source, not current, although direct voltage controlled constant current source is essential to test major equipment. That kind of source is not available to supply stable constant current regardless of load variation. It is just voltage supplier. Developing current source is not easy other than voltage source. Very large-scale current source up to ampere class more than such ten times of normal current is inevitable to test above mentioned equipment. So, we developed large-scale current source which is controlled by input DC voltage and supplies constant stable current to object equipment according to this requirement. We measured and tested nuclear power plant equipment using given real site data for a long time and afforded long period load test, and then proved its validity and verification. The developed invetion will be used future installed important equipment measuring and testing.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1107-1116
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• 2016

Recent astronomical survey observations have produced substantial amounts of data as well as completely changed conventional methods of analyzing astronomical data. Both classical statistical inference and modern machine learning methods have been used in every step of data analysis that range from data calibration to inferences of physical models. We are seeing the growing popularity of using machine learning methods in classical problems of astronomical data analysis due to low-cost data acquisition using cheap large-scale detectors and fast computer networks that enable us to share large volumes of data. It is common to consider the effects of inhomogeneous spatial and temporal coverage in the analysis of big astronomical data. The growing size of the data requires us to use parallel distributed computing environments as well as machine learning algorithms. Distributed data analysis systems have not been adopted widely for the general analysis of massive astronomical data. Gathering adequate training data is expensive in observation and learning data are generally collected from multiple data sources in astronomy; therefore, semi-supervised and ensemble machine learning methods will become important for the analysis of big astronomical data.

• The Journal of the Korea Contents Association
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• v.8 no.11
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• pp.57-64
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• 2008

The data grid computing provides geographically distributed storage resources to solve computational problems with large-scale data. Unlike cache replacement policies in virtual memory or web-caching replacement, an optimal file replacement policy for data grids is the one of the important problems by the fact that file size is very large. The traditional file replacement policies such as LRU(Least Recently Used), LCB-K(Least Cost Beneficial based on K), EBR(Economic-based cache replacement), LVCT(Least Value-based on Caching Time) have the problem that they have to predict requests or need additional resources to file replacement. To solve theses problems, this paper propose SBR-k(Sized-based replacement-k) that replaces files based on file size. The proposed policy considers file size to reduce the number of files corresponding to a requested file rather than forecasting the uncertain future for replacement. The results of the simulation show that hit ratio was similar when the cache size was small, but the proposed policy was superior to traditional policies when the cache size was large.

• Korean Management Science Review
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• v.17 no.2
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• pp.135-150
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• 2000

Korean construction companies are recently facing stiff competition in free market economy, and construction projects tend to be complex and large-scale. Such an environment demands that construction companies ensure specialized subcontractors. This paper suggested a subcontractor evaluation model for selection of competent subcontractors which are equipped with operational, technical and productive ability. For designing a subcontractor model, AHP method as a group decision-marking method is applied in assigning weighting indices of evaluation elements. To verify this method, actual data collected in one of construction companies are analysed statistically.

• Explosives and Blasting
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• v.15 no.2
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• pp.53-72
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• 1997

It is impossible to precat the behavior of ground soil and structure accurately during underground construction in urban area or excavation in soft ground area because of difference between the assumed design condition and the actual site condition. Therefore, it must be managed by measuring system and correct the difference by real data. Large scale under ground construction in urban area like a seoul subway project has needed for Intelligent Construction technique, a field of the Engineering Contractor. The automated measuring system is developed for the technique. It is described that the procedure and the method of measuring work with application of the automated measuring system.

• Proceedings of the Korea Concrete Institute Conference
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• 1999.04a
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• pp.813-818
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• 1999

The construction of large scale civil and building structures which form the base of social economy has been grown greatly. As the increasing of aged and deteriorated structures, it is necessary to evaluate the safety of those structures. The deterioration, safety evaluation, repair and rehabilitation are important problems in the construction area that every country faces. This paper presents the general information on how to conduct a data analysis of long-term monitoring system and evaluate the characteristics of surveying methods.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.308-314
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• 2011

The research which sees, the parameters inputs and acoustic measurement result in simulation error most on a large scale concreteness of 3D models which affect number of effective surface. Therefore DATA of above the comparison which will listen, analyzed and investigated.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.5 no.2
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• pp.90-93
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• 1987

Relatively few papers are known to study the clustering the same kind of data records in a cylinder. In this article, I reviewed the clustering algorithms especially for the cellular list file which have been studied.