• Bulletin of the Korean Mathematical Society
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• v.55 no.6
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• pp.1791-1809
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• 2018

Let T be the singular integral operator with nonsmooth kernel which was introduced by Duong and McIntosh, and $T_q(q{\in}(1,{\infty}))$ be the vector-valued operator defined by $T_qf(x)=({\sum}_{k=1}^{\infty}{\mid}T\;f_k(x){\mid}^q)^{1/q}$. In this paper, by proving certain weak type endpoint estimate of L log L type for the grand maximal operator of T, the author establishes some quantitative weighted bounds for $T_q$ and the corresponding vector-valued maximal singular integral operator.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.616-623
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• 2002

This paper proposes a new DFA methodology that ran estimate the standard assembly time and evaluate the assemblability of parts for small-sized product. We deride some determining and influencing factors related with assembly process and measure the assembly time using notion analysis to estimate of assemblability. We deduce quantitative store of assemblability through analysis of a correlation between determining factors and grade of influencing factors.

• 한국IT서비스학회:학술대회논문집
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• 2005.11a
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• pp.345-355
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• 2005

As the portion of information systems(IS) budget to the total government budget becomes greater, the cost estimation of IS development and maintenance projects is recognized as one of the most important problems to be resolved for quantitative and efficient management of IS budget. The primary concern in the cost estimation of IS projects is to estimate software development cost. In this paper, we propose a new method to estimate software cost using support vector regression(SVR), which has attracted considerable attention because of its good performance and theoretical clearness. The paper is the first study which apply SVR to software cost estimation.

• Earthquakes and Structures
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• v.26 no.6
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• pp.433-447
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• 2024

During earthquakes, regular buildings perform better than irregular buildings. In general, seismic design codes define a regular building using estimates of Storey Stiffness and Storey Strength. At present, seismic design codes do not recommend a specific method to estimate these parameters. Consequently, any method described in the literature can be applied to estimate the aforementioned parameters. Nevertheless, research has demonstrated that storey stiffness and storey strength vary depending on the estimation method employed. As a result, the same building can be regular or irregular, depending on the method employed to estimate storey stiffness and storey strength. Hence, there is a need to identify the best method to estimate storey stiffness and storey strength. For this purpose, the study presents a qualitative and quantitative evaluation of nine approaches used to determine storey stiffness. Similarly, the study compares six approaches for estimating storey strength. Subsequently, the study identifies the best method to estimate storey stiffness and storey strength using results of 350 linear time history analyses and 245 nonlinear time history analyses, respectively. Based on the comparison, it is concluded that the Fundamental Lateral Translational Mode Shape Method and Isolated Storey Method - A Particular Case are the best methods to estimate storey stiffness and storey strength of low-to-mid rise buildings, respectively.

• Journal of Biomedical Engineering Research
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• v.35 no.1
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• pp.1-7
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• 2014

Among semi-quantitative or fully quantitative lateral flow assay readers, an image sensor-based instrument has been widely used because of its simple setup, cheap sensor price, and compact equipment size. For all previous approaches, monochrome CCD or CMOS cameras were used for lateral flow assay imaging in which the overall intensities of all colors were taken into consideration to estimate the analyte content, although the analyte related color information is only limited to a narrow wavelength range. In the present work, we introduced a color CCD camera as a sensor and a color decomposition method to improve the sensitivity of the quantitative biosensor system which utilizes the lateral flow assay successfully. The proposed setup and image processing method were applied to achieve the quantification of imitatively dispensed particles on the surface of a porous membrane first, and the measurement result was then compared with that using a monochrome CCD. The compensation method was proposed in different illumination conditions. Eventually, the color decomposition method was introduced to the commercially available lateral flow immunochromatographic assay for the diagnosis of myocardial infarction. The measurement sensitivity utilizing the color image sensor is significantly improved since the slopes of the linear curve fit are enhanced from 0.0026 to 0.0040 and from 0.0802 to 0.1141 for myoglobin and creatine kinase (CK)-MB detection, respectively.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.183-183
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• 2020

Accurate quantitative precipitation estimation plays an important role in hydrological modelling and prediction. Instantaneous quantitative precipitation estimation (QPE) by utilizing the weather radar data is a great applicability for operational hydrology in a catchment. Previously, regression technique performed between reflectivity (Z) and rain intensity (R) is used commonly to obtain radar QPEs. A novel, recent approaching method which might be applied in hydrological area for QPE is Long Short-Term Memory (LSTM) Networks. LSTM networks is a development and evolution of Recurrent Neuron Networks (RNNs) method that overcomes the limited memory capacity of RNNs and allows learning of long-term input-output dependencies. The advantages of LSTM compare to RNN technique is proven by previous works. In this study, LSTM networks is used to estimate the quantitative precipitation from weather radar for an urban catchment in South Korea. Radar information and rain-gauge data are used to evaluate and verify the estimation. The estimation results figure out that LSTM approaching method shows the accuracy and outperformance compared to Z-R relationship method. This study gives us the high potential of LSTM and its applications in urban hydrology.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1830-1835
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• 2005

It is important to estimate the distribution of intensity of a magnetic field for application of magnetic method to industrial nondestructive evaluation. Magnetic camera provides the distribution of a quantitative magnetic field with homogeneous lift-off and same spatial resolution. And it is possible to interpret the distribution of the magnetic field when the dipole model is introduced. This study introduces the numerical and experimental considering of the quantitative evaluation of several size and shapes of the cracks using the magnetic field images of the scan type magnetic camera.

• Journal of Forest and Environmental Science
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• v.31 no.2
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• pp.73-77
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• 2015

Acquiring accurate quantitative and qualitative information is necessary for the technical and scientific management of forest stands. In this study, stratification and systematic random sampling methods were used to estimation of quantitative characteristics in study area. The estimator ($((E%)^2xT)$) was used to compare the systematic random and stratified sampling methods. 100 percent inventory was carried out in an area of 400 hectares; characteristics as: tree density, crown cover (canopy), and basal area were measured. Tree density of stands was compared through systemic random and stratified sampling methods. Findings of the study reveal that stratified sampling method gives a better representation of estimates than systematic random sampling.

• Journal of Korea Multimedia Society
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• v.17 no.12
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• pp.1494-1502
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• 2014

Since smartphones are utilized in the ranges from personal usages to governmental data exchanges, known but not patched vulnerabilities in smartphone operating systems are considered as major threats to the public. To minimize potential security breaches on smartphones, it is necessary to estimate possible security threats. So far, there have been numerous studies conducted to evaluate the security risks caused by mobile devices qualitatively, but there are few quantitative manners. For a large scale risk evaluation, a qualitative assessment is a never ending task. In this paper, we try to calculate relative risk levels triggered by software vulnerabilities from unsecured smartphone operating systems (Android and iOS) among 51 Asian countries. The proposed method combines widely accepted risk representation in both theory and industrial fields. When policy makers need to make a strategic decision on mobile security related agendas, they might find the presented approach useful.

• Journal of Information Technology Services
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• v.8 no.1
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• pp.113-124
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• 2009

Value-based requirements engineering process, called The ViRE(Value-Innovative Requirement Engineering) was suggested to create an uncontested market using ERRC(Eliminate, Reduce, Raise, Create) requirements analysis. But ViRE did not provides a quantitative data analysis method for ERRC decision so as to make objective decisions for customers. In this paper, to solve this problem, we suggest a quantitative ERRC analysis method by estimating requirements cost. Our method defines user requirements and decides their weight. Then, it makes quality level table for all the identified requirements and function modules and estimate implementation cost based on their quality levels. Finally, assess each requirement's impact and then evaluate ERRC value. We could get the more objective ERRC values by evaluate the requirement weight. functional module weight, and implementation cost. And we proved the efficiency of our model by a case study, smart student ID system.