• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.4
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• pp.349-358
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• 2019

This paper aimed at collecting sensor signals to extract characteristic parameter of the rotor. A vibration test rig has been developed to perform model tests. Signal characteristics were analyzed when driving normally. Envelope FFT Analysis is used to extract vibration components caused by periodic impacts from other vibration factors. Signal analysis was performed when load changes were given to speed sensors and vibration test rigs that show low frequency characteristics of the rotor and signal analysis according to rotational speed. The acceleration signal measured in the bearing housing has a small amplitude and produces only the rotational frequency component and harmonic component of the motor. As the number of rotations increases, the amplitude of acceleration can be seen. As the rotational speed increases, it can be seen that there is a difference in the shape of the original data and compared with the acceleration FFT graph, it can be seen that the noise is strong at low frequencies and the corresponding rotational frequency components are clearly represented. It can be seen that changing the load does not increase the main rotational frequency component.

• Atmosphere
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• v.31 no.1
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• pp.29-43
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• 2021

In this study, two-step statistical approach including Principal Component Analysis (PCA) and Multiple Linear Regression (MLR) was employed, and main meteorological factors explaining the high-PM2.5 episodes were identified in two regions: Seoul and Busan. We first performed PCA to isolate the Principal Component (PC) that is linear combination of the meteorological variables observed at two levels: surface and 850 hPa level. The employed variables at surface are: temperature (T2m), wind speed, sea level pressure, south-north and west-east wind component and those at 850 hPa upper level variables are: south-north (v850) and west-east (u850) wind component and vertical stability. Secondly we carried out MLR analysis and verified the relationships between PM2.5 daily mean concentration and meteorological PCs. Our two-step statistical approach revealed that in Seoul, dominant factors for influencing the high PM2.5 days are mainly composed of upper wind characteristics in winter including positive u850 and negative v850, indicating that continental (or Siberian) anticyclone had a strong influence. In Busan, however, the dominant factors in explanaining in high PM2.5 concentrations were associated with high T2m and negative u850 in summer. This is suggesting that marine anticyclone had a considerable effect on Busan's high PM2.5 with high temperature which is relevant to the vigorous photochemical secondary generation. Our results of both differences and similarities between two regions derived from only statistical approaches imply the high-PM2.5 episodes in Korea show their own unique characteristics and seasonality which are mostly explainable by two layer (surface and upper) mesoscale meteorological variables.

• Journal of Korea Spatial Information System Society
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• v.4 no.2 s.8
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• pp.65-74
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• 2002

The CBD(component based development) method has recently been on the rise as the main current among all fields of developing Information Systems. The developing system by building and integrating of components is encouraged in GIS sphere. Business domain which considerably identifies components occupies GIS shpere rather then any other sphere. Arithmetic function is quite needed in GIS sphere but non-arithmetic functions are also used in GIS sphere as well as in enterprise sphere. Component is characterized by ensuring the reuse of itself. The efficiency of reusing component is promoted as the component is functionally simple and is packed to a minimum. The GIS Component Extraction Method has already been presented in several studies but this study is about the GIS Component Extraction by the Affinity Analysis Method. CBD uses UML on a basis and the core of the UML is consisted of the use case and the class. The purpose of the Affinity Analysis is a study how relate between the use case and the class in a certain business domain and then the results identify the component. The Affinity Analysis is useful not only in GIS but also in every business domain and is considered to be popular as the procedure of this method is not complex at all.

• Journal of Korean Association for Spatial Structures
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• v.7 no.3 s.25
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• pp.125-132
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• 2007

The purpose of this study is to investigate the functions and formations of the component units as aesthetic components in the spatial grid. The main subject covered here is the presentation of the morphological method of shaping spatial grid by application of 3-dimensional units satisfying the suitable form of polyhedra, tensegrity and hybrid structure. In accordance with the subject, the definition of the spatial grid and 3-dimensional nit, the relationship between them, and then the functions of those units are reviewed. And the formations of polyhedral units, tensegrity units and hybrid units are generated by means of the modules of the simplest type or pattern. And also the overall appearance of the spatial grid shaped by several basic methods in which one unit can be joined to another and arranged are depicted.

• Environmental Engineering Research
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• v.15 no.3
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• pp.135-140
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• 2010

With the various urban characteristics of each city, the existing water demand prediction, which uses average liter per capita day, cannot be used to achieve an accurate prediction as it fails to consider several variables. Thus, this study considered social and industrial factors of 164 local cities, in addition to population and other directly influential factors, and used main substance and cluster analyses to develop a more efficient water demand prediction model that considers unique localities of each city. After clustering, a multiple regression model was developed that proved that the $R^2$ value of the inclusive multiple regression model was 0.59; whereas, those of Clusters A and B were 0.62 and 0.74, respectively. Thus, the multiple regression model was considered more reasonable and valid than the inclusive multiple regression model. In summary, the water demand prediction model using principal component and cluster analyses as the standards to classify localities has a better modification coefficient than that of the inclusive multiple regression model, which does not consider localities.

• Journal of Korea Multimedia Society
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• v.23 no.10
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• pp.1339-1347
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• 2020

This study is a preliminary study to design a character automation system that considers the facial characteristics of mammals. The experimental data of this study was conducted on dogs (dog breeds) and humans, which were designed to be used in many contents. First, data was extracted from 100 types of dogs and 100 human data. Second, the criteria for measuring the ratio of important parts of the dog and human face were suggested. In addition, a comparative analysis of the face of a dog and a human face is conducted. Lastly, by analyzing the main component(PCA), the most characteristic elements in the faces of dogs and humans were analyzed. As a result, it was confirmed that the length of the face, the size of the eyes, the length of the glabellar, and the length of the glabellar and other parts are important. Through this study, the features of the dog's face that are different from humans are expected to contribute to the animal character automation.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.30 no.2
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• pp.13-23
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• 1998

Two major cellulase components purified with sephadex G-75 and DEAE sepharose were applied to bleached kraft pulp to inverstigate the change of fiber properties. Cellulose viscosity was very sensitive to $C_x$ component treatment (more than 15% drop was observed) while being little influenced by $C_1$, component (only 2% drop). Fiber fraction longer than 2mm was reduced by $C_x$ treatment while short fiber fraction was increased greatly by more than 15%. There was little change in fiber length distribution by combined treatment of $C_1$ 1 and $C_x$ at equal. In this case, fine contents increased by more than 2.5% at equivalent refining time. WRV and Density were increased as the amount of $C_1$ or $C_x$ treatment was increased. $C_{x}$ was main cause for increasing them. But the effect fell as enzyme dosage.

• Korean Journal of Remote Sensing
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• v.33 no.4
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• pp.445-454
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• 2017

The performance of spatial downscaling models depends on the quality of input coarse scale products. Thus, the impact of intrinsic errors contained in coarse scale satellite products on predictive performance should be properly assessed in parallel with the development of advanced downscaling models. Such an assessment is the main objective of this paper. Based on a synthetic satellite precipitation product at a coarse scale generated from rain gauge data, two synthetic precipitation products with different amounts of error were generated and used as inputs for spatial downscaling. Geographically weighted regression, which typically has very high explanatory power, was selected as the trend component estimation model, and area-to-point kriging was applied for residual correction in the spatial downscaling experiment. When errors in the coarse scale product were greater, the trend component estimates were much more susceptible to errors. But residual correction could reduce the impact of the erroneous trend component estimates, which improved the predictive performance. However, residual correction could not improve predictive performance significantly when substantial errors were contained in the input coarse scale data. Therefore, the development of advanced spatial downscaling models should be focused on correction of intrinsic errors in the coarse scale satellite product if a priori error information could be available, rather than on the application of advanced regression models with high explanatory power.

• International Journal of Contents
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• v.13 no.3
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• pp.1-8
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• 2017

Rice plant numbers and density are key factors for yield and quality of rice grains. Precise and properly estimated rice plant numbers and density can assure high yield from rice fields. The main objective of this study was to automatically detect and count rice plants using images of usual field condition from an unmanned aerial vehicle (UAV). We proposed an automatic image processing method based on morphological operation and boundaries of the connected component to count rice plant numbers after transplanting. We converted RGB images to binary images and applied adaptive median filter to remove distortion and noises. Then we applied a morphological operation to the binary image and draw boundaries to the connected component to count rice plants using those images. The result reveals the algorithm can conduct a performance of 89% by the F-measure, corresponding to a Precision of 87% and a Recall of 91%. The best fit image gives a performance of 93% by the F-measure, corresponding to a Precision of 91% and a Recall of 96%. Comparison between the numbers of rice plants detected and counted by the naked eye and the numbers of rice plants found by the proposed method provided viable and acceptable results. The $R^2$ value was approximately 0.893.

• Journal of the Korean Society of Systems Engineering
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• v.13 no.1
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• pp.25-31
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• 2017

This paper aims to evaluate the conservatism in the design of APR1400 (Advanced Pressurized water Reactor 1400 designed by KHNP) reactor internals component, the LSS (Lower Support Structure). Re-engineering of the LSS is done based on the system design condition data and applicable ASME code that was used for the original APR1400 design. Systems engineering approach is applied to design the LSS of APR1400 without refering APR1400 LSS dimensional parameters and tries to verify important design parameters of APR1400 LSS as well as the validity of the re-engineering design process as independent verification method of reactor component design. Systems engineering approach applied in this study following V-model approach. The re-engineered LSS design showed more than enough conservatism for static loading case. The maximum deflection of LSS is under 1mm (calculated value is 0.25mm) from 4000 mm diameter of LSS. Hence the deflection can be ignored in other reactor internals for structural integrity assessment. Especially the effect of LSS deflection on fuel assembly can be minimized and which is one of the main requirements of LSS design. It also showed that the maximum stress intensity is 2.36MPa for the allowable stress intensity of 60.1 MPa. The stress resulted from the static load is also very small compared to the maximum allowable stress intensity, hence there is more than enough conservatism in the LSS design.