• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.43.2-43.2
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• 2019

In many astrophysical systems, smooth large-scale variations coexist with small-scale fluctuations. For example, a large-scale velocity or density gradient can exist in molecular clouds that have small-scale fluctuations by turbulence. In redshifted 21cm observations, we also have two types of signals - the Galactic foreground emissions that change smoothly and the redshifted 21cm signals that fluctuate fast in frequency space. In many cases, the large-scale variations make it difficult to extract information on small-scale fluctuations. We propose a simple technique to remove smooth large-scale variations. Our technique relies on multi-point structure functions and can obtain the magnitudes of small-scale fluctuations. It can also be used to design filters that can remove large-scale variations and retrieve small-scale data. We discuss how to apply our technique to irregularly spaced data, such as rotation measure observations toward extragalactic radio point sources.

• Nuclear Engineering and Technology
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• v.56 no.9
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• pp.3594-3601
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• 2024

It is difficult to detect a small-scale leakage in a nuclear power plant (NPP) quickly and take appropriate action. Delaying these procedures can have adverse effects on NPPs. In this paper, we propose leak flow rate prediction using the bidirectional gated recurrent unit (Bi-GRU) method to detect leakage quickly and accurately in small-scale leakage situations because large-scale leak rates are known to be predicted accurately. The data were acquired by simulating small loss-of-coolant accidents (LOCA) or small-scale leakage situations using the modular accident analysis program (MAAP) code. In addition, to improve prediction performance, data were collected by distinguishing the break sizes in more detail. In addition, the prediction accuracy was improved by performing both LOCA diagnosis and leak flow rate prediction in small LOCA situations. The prediction model developed using the Bi-GRU showed a superior prediction performance compared with other artificial intelligence methods. Accordingly, the accurate and effective prediction model for small-scale leakage situations proposed herein is expected to support operators in decision-making and taking actions.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.268-273
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• 2021

In this paper, we propose a sentiment analysis model that improves performance on small-scale data. A sentiment analysis model for small-scale data is proposed and verified through experiments. To this end, we propose Bagging-Bi-GRU, which combines Bi-GRU, which learns GRU, which is a variant of LSTM (Long Short-Term Memory) with excellent performance on sequential data, in both directions and the bagging technique, which is one of the ensembles learning methods. In order to verify the performance of the proposed model, it is applied to small-scale data and large-scale data. And by comparing and analyzing it with the existing machine learning algorithm, Bi-GRU, it shows that the performance of the proposed model is improved not only for small data but also for large data.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1203-1209
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• 2010

Internet addiction is a serious social problem in information society. The purpose of this study is to develope a small diagnostic scale in order to detect internet addiction easily. The reliability and validity of K-scale and Kimberly Young-scale is investigated. Five small diagnostic scale is suggested by factor analysis and regression. The comparision of these small scale is established by correlation coefficient, chi-square test, gamma value of concordance in contingency table. In view of reliability and validity, we suggest a small diagnostic scale. The results of this study may be useful to detect internet addiction by oneself.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.6190-6213
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• 2019

For small-scale vector data, restrictions on watermark scheme capacity and robustness limit the use of copyright protection. A watermarking scheme based on robust geometric features and capacity maximization strategy that simultaneously improves capacity and robustness is presented in this paper. The distance ratio and angle of adjacent vertices are chosen as the watermark domain due to their resistance to vertex and geometric attacks. Regarding watermark embedding and extraction, a capacity-improved strategy based on quantization index modulation, which divides more intervals to carry sufficient watermark bits, is proposed. By considering the error tolerance of the vector map and the numerical accuracy, the optimization of the capacity-improved strategy is studied to maximize the embedded watermark bits for each vertex. The experimental results demonstrated that the map distortion caused by watermarks is small and much lower than the map tolerance. Additionally, the proposed scheme can embed a copyright image of 1024 bits into vector data of 150 vertices, which reaches capacity at approximately 14 bits/vertex, and shows prominent robustness against vertex and geometric attacks for small-scale vector data.

• 한국벤처창업학회:학술대회논문집
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• 2006.11a
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• pp.275-299
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• 2006

This study aims at examining the early-stage financing scale for entrepreneur to build small & medium business. The data was collected from the DART (Data Analysis, Retrieval and Transfer System) of Korean Financial Supervisory Service(FSS) in the main. The results of this study show that small & medium business needs equipment & operation financing for about 37 months extent to reach Break-Even Point. The limitations of this study are data collections from registered firms on Korean FSS primarily and no showing about the early stage financing scale for building small & Medium Business concretely. Small & Medium business entrepreneur have to make a early stage finance plan according to a necessary equipment and operating cost in their business field for 37 months extent.

• Steel and Composite Structures
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• v.20 no.5
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• pp.1119-1131
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• 2016

As a first attempt, an inverse hybrid numerical method for small scale parameter estimation of functionally graded (FG) nanobeams using measured frequencies is presented. The governing equations are obtained with the Eringen's nonlocal elasticity assumptions and the first-order shear deformation theory (FSDT). The equations are discretized by using the differential quadrature method (DQM). The discretized equations are transferred from temporal domain to frequency domain and frequencies of the nanobeam are obtained. By applying random error to these frequencies, measured frequencies are generated. The measured frequencies are considered as input data and inversely, the small scale parameter of the beam is obtained by minimizing a defined functional. The functional is defined as root mean square error between the measured frequencies and calculated frequencies by the DQM. Then, the conjugate gradient (CG) optimization method is employed to minimize the functional and the small scale parameter is obtained. Efficiency, convergence and accuracy of the presented hybrid method for small scale parameter estimation of the beams for different applied random error, boundary conditions, length-to-thickness ratio and volume fraction coefficients are demonstrated.

• Journal of the Korean Society of Safety
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• v.29 no.4
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• pp.42-47
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• 2014

This paper is aimed to investigate and analyze of characteristic for electrical equipment and work environment for the small-scale site. In order to investigate and analyze electrical equipment and work environment for preventing electric shock disaster in construction sites, 50 small-scale construction sites and 12 large-scale construction sites are selected. This paper completed site investigations of low-voltage equipment and the portable electric machine and equipment in 12 large-scale construction sites and 50 small-scale construction sites. The findings were about the electric shock environment relevant to the ground-relevant equipment, the panel board, the protection tools, the sockets, the temporary wiring system, the portable and movable electric machines and equipments in small-scale construction sites. Finally, this study analyzed the domestic and foreign relevant standards and regulations and these findings can be utilized as educational data warning electric shock risk caused by electric equipment in small-scale construction site.

• Proceedings of the KSME Conference
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• 2008.11b
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• pp.2548-2553
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• 2008

Prediction of the rotor blade performance is important for determining design factors such as weight and size in development of a small-scale helicopter. Generally, prediction of helicopter performance means the estimation of the power required for a given flight condition. However, due to lack of test data and analyzed results for small-scale rotor blade operated at low Reynolds numbers ($Re{\approx}10^5$), this is not an easy task. As an initial research, this work performs a modeling of a single rotor configuration with FLIGHTLAB and a experimental research with rotor test bed. In this process, we performed small-scale isolated single rotor by experimental and numerical method and achieved good agreement of the hover performance on the test data and simulation results.

• Korean Journal of Occupational Health Nursing
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• v.9 no.1
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• pp.56-61
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• 2000

This study was done in an attempt to reveal those factors interfering with the observation study. Three trained research assistants collected data by observing the two occupational health nurses working in the small scale enterprises on the 3rd and 10th of February, 1999. The first observation was performed on the 3rd of February without observation guidance. Guidance was given during the second observation on the 10th of February. These data were compared between reporters in nursing services of 'Workplace visiting', 'Health counselling' and 'Blood pressure checking' according to nursing time and frequency. These areas were chosen because these activities were regarded as clearly identifiable by observers in contrast to the other performances. The data showed inconsistency between reporters. However, they were reduced when reporters observed nurses with guidance, although there were still minor differences between data in time and frequency. Discussions were carried out to find possible reasons for these differences. The causes were mainly attributed to the difficulty in workplace conditions to observe, the work specificity of nurses visiting each workplace and the delicate situation between nurses and observers when reporters were travelling in the nurse's car. Therefore, the results suggest that the observation method applied to the nursing service research at small-scale enterprises should be more concerned about the selection of appropriate workplace and operational definition of nursing activity in order to more precisely measure nurses' attitudes.