• The KIPS Transactions:PartA
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• v.19A no.3
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• pp.129-138
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• 2012

In distributed memory architectures like clusters, each node stores a portion of data. How data is distributed across nodes influences the performance of such systems. The data distribution scheme is the strategy to distribute data across nodes and realize parallel data processing. Due to various reasons such as maintenance, scale up, upgrade, etc., the performance of nodes in a cluster can often become non-identical. In such clusters, data distribution without considering performance cannot efficiently distribute data on nodes. In this paper, we propose a new data distribution scheme based on the number of cores in nodes. We use the number of cores as the performance factor. In our data distribution scheme, each node is allocated an amount of data proportional to the number of cores in it. We implement our data distribution scheme using the Chapel language. To show our data distribution is effective in reducing the execution time of parallel applications, we implement Mandelbrot Set and ${\pi}$-Calculation programs with our data distribution scheme, and compare the execution times on a cluster. Based on experimental results on clusters of 8-core and 16-core nodes, we demonstrate that data distribution based on the number of cores can contribute to a reduction in the execution times of parallel programs on clusters.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.4
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• pp.129-134
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• 2018

Recently, the artificial neural network (ANN) model is a promising technique in the prediction, numerical control, robot control and pattern recognition. We predicted the outside temperature of greenhouse using ANN and utilized the model in greenhouse control. The performance of ANN model was evaluated and compared with multiple regression model(MRM) and support vector machine (SVM) model. The 10-fold cross validation was used as the evaluation method. In order to improve the prediction performance, the data reduction was performed by correlation analysis and new factor were extracted from measured data to improve the reliability of training data. The backpropagation algorithm was used for constructing ANN, multiple regression model was constructed by M5 method. And SVM model was constructed by epsilon-SVM method. As the result showed that the RMSE (Root Mean Squared Error) value of ANN, MRM and SVM were 0.9256, 1.8503 and 7.5521 respectively. In addition, by applying the prediction model to greenhouse heating load calculation, it can increase the income by reducing the energy cost in the greenhouse. The heating load of the experimented greenhouse was 3326.4kcal/h and the fuel consumption was estimated to be 453.8L as the total heating time is $10000^{\circ}C/h$. Therefore, data mining technology of ANN can be applied to various agricultural fields such as precise greenhouse control, cultivation techniques, and harvest prediction, thereby contributing to the development of smart agriculture.

• Journal of the Korean Institute of Gas
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• v.2 no.2
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• pp.18-25
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• 1998

According to the requirements of ANSI B3l.8, the pipe thickness is determined with hoop stress resulted from internal pressure. And the other loads induced by soil, vehicle, thermal expansion, ground subsidence, etc shall be evaluated rationally. There are two ways of calculating stress of buried gas pipeline. The first is FEM. FEM can calculate the stress regardless of the complexity of pipeline shape and boundary conditions. But it needs high cost and long time. The second is the way to use equation. The reliable equations to calculate the stress of buried gas pipeline was developed and have been used in designing pipeline and evaluating pipeline safety, But these equation are very difficult to understand and use for non-specialist. For easy calculation of non-specialist, the new computer program to calculate stress of buried natural gas pipeline have been developed. The stress is calculated by the equations and extrapolation of the graph resulted from FEM. The full paper is consist of series I and II. In this paper, series I, the calculating equation of the program is explained in detail.

• Journal of Educational Research in Mathematics
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• v.26 no.3
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• pp.489-508
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• 2016

Number and operation is the most basic and crucial part in elementary mathematics but is also well known as a part that students have lots of difficulties. A lot of researches have been done in various ways to solve this problem but it can't be solved fundamentally by emphasizing calculation method and skill. So we need to go over it in terms of relevant arithmetical thinking. This study aims to diagnose the cause of an underachiever's difficulties about arithmetic and finds a prescription for her by analyzing her level of arithmetical thinking based on Guberman(2014) and understanding about arithmetic. To achieve this goal, we chose an 6th grader who's having a hard time particularly in number and operation among mathematics strands and conducted a case study carrying out arithmetical thinking level tests on two separate occasions and analyzing her responses. As a result of analyzing data, her arithmetical thinking corresponded to Guberman's first level and it is also turned out that student is suffering from some arithmetic concepts. We suggest several implications for teaching of arithmetic at elementary school in terms of the development of arithmetical thinking based on analysis result and discussion about it.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.15 no.1
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• pp.1-10
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• 2003

In this paper, the laboratory test results with middle-sired ,soil box test in modeling the in-situ installing of horizontal drains are discussed the estimation of the optimum negative pressure. The test was carried out in the different vacuum pressure conditions together with the measurement for the settlement and volume change of drained water by the installed drains during the consolidation process. After the test, the water content was measured to both directions of lateral distance from the drain and depth of the soil, to find out the distribution of ground improvement and strength enhancement. From the analysis on the distribution of water content, the gradual application of vacuum pressure to higher level by pre-determined stages starting from low vacuum pressure is found to be effective and desirable. In the comparison of the degrees of consolidation with elapsed time, the calculated value by the prediction method based on the Barren's conventional theory showed a good agreement with the measured value. With this, It is positively considered that the applicability of the prediction method based on Barren's theory to the practical design of horizontal drains can be justified such as in the calculation of drain spacing and consolidation period.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.2
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• pp.68-76
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• 2006

A thermal time-based two-step phenological model was used to project flowering dates of Japanese cherry in South Korea from 1941 to 2100. The model consists of two sequential periods: the rest period described by chilling requirement and the forcing period described by heating requirement. Daily maximum and minimum temperature are used to calculate daily chill units until a pre-determined chilling requirement for rest release is met. After the projected rest release date, daily heat units (growing degree days) are accumulated until a pre-determined heating requirement for flowering is achieved. Model calculations using daily temperature data at 18 synoptic stations during 1955-2004 were compared with the observed blooming dates and resulted in 3.9 days mean absolute error, 5.1 days root mean squared error, and a correlation coefficient of 0.86. Considering that the phonology observation has never been fully standardized in Korea, this result seems reasonable. Gridded data sets of daily maximum and minimum temperature with a 270 m grid spacing were prepared for the climatological years 1941-1970 and 1971-2000 from observations at 56 synoptic stations by using a spatial interpolation scheme for correcting urban heat island effect as well as elevation effect. A 25km-resolution temperature data set covering the Korean Peninsula, prepared by the Meteorological Research Institute of Korea Meteorological Administration under the condition of Inter-governmental Panel on Climate Change-Special Report on Emission Scenarios A2, was converted to 270 m gridded data for the climatological years 2011-2040, 2041-2070 and 2071-2100. The model was run by the gridded daily maximum and minimum temperature data sets, each representing a climatological normal year for 1941-1970, 1971-2000, 2011-2040, 2041-2070, and 2071-2100. According to the model calculation, the spatially averaged flowering date for the 1971-2000 normal is shorter than that for 1941-1970 by 5.2 days. Compared with the current normal (1971-2000), flowering of Japanese cherry is expected to be earlier by 9, 21, and 29 days in the future normal years 2011-2040, 2041-2070, and 2071-2100, respectively. Southern coastal areas might experience springs with incomplete or even no Japanese cherry flowering caused by insufficient chilling for breaking bud dormancy.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.6
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• pp.609-616
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• 2017

In this paper, we propose an algorithm to obtain more stable and high recognition rate by using left and right rotation information of input image in order to obtain a stable recognition rate in face recognition. The proposed algorithm uses the facial image as the input information in the web camera environment to reduce the size of the image and normalize the information about the brightness and color to obtain the improved recognition rate. We apply Principal Component Analysis (PCA) to the detected candidate regions to obtain feature vectors and classify faces. Also, In order to reduce the error rate range of the recognition rate, a set of data with the left and right $45^{\circ}$ rotation information is constructed considering the directionality of the input face image, and each feature vector is obtained with PCA. In order to obtain a stable recognition rate with the obtained feature vector, it is after scattered in the eigenspace and the final face is recognized by comparing euclidean distant distances to each feature. The PCA-based feature vector is low-dimensional data, but there is no problem in expressing the face, and the recognition speed can be fast because of the small amount of calculation. The method proposed in this paper can improve the safety and accuracy of recognition and recognition rate faster than other algorithms, and can be used for real-time recognition system.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.276-276
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• 2010

Localized surface plasmon resonance (LSPR) has been explored recently as a promising approach to increase energy conversion efficiency in photovoltaic devices, particularly for thin film hydrogenated amorphous silicon (a-Si:H) solar cells. The LSPR is frequently excited via an electromagnetic (EM) radiation in proximate metallic nanostructures and its primary con sequences are selective photon extinction and local EM enhancement which gives rise to improved photogeneration of electron-hole (e-h) pairs, and consequently increases photocurrent. In this work, high-dielectric-constant (k) $ZrO_2$ (refractive index n=2.22, dielectric constant $\varepsilon=4.93$ at the wavelength of 550 nm) is proposed as spacing layer to enhance the LSPR for application to the thin film silicon solar cells. Compared to excitation of the LSPR using $SiO_2$ (n=1.46, $\varepsilon=2.13$ at the wavelength of 546.1 nm) spacing layer with Au nanoparticles of the radius of 45nm, that using $ZrO_2$ dielectric shows the advantages of(i) ~2.5 times greater polarizability, (ii) ~3.5 times larger scattering cross-section and ~1.5 times larger absorption cross-section, (iii) 4.5% higher transmission coefficient of the same thickness and (iv) 7.8% greater transmitted electric filed intensity at the same depth. All those results are calculated by Mie theory and Fresnel equations, and simulated by finite-difference time-domain (FDTD) calculations with proper boundary conditions. Red-shifting of the LSPR wavelength using high-k $ZrO_2$ dielectric is also observed according to location of the peak and this is consistent with the other's report. Finally, our experimental results show that variation of short-circuit current density ($J_{sc}$) of the LSPR enhanced a-Si:H solar cell by using the $ZrO_2$ spacing layer is 45.4% higher than that using the $SiO_2$ spacing layer, supporting our calculation and theory.

• Journal of Wetlands Research
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• v.17 no.2
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• pp.203-208
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• 2015

To identify the effect of fallen cherry blossom on the artificial pond ecosystem, microcosm experiment was conducted into the aquatic decomposition of Prunus species petals. Petals were put in $1mm^2$ mesh nylon litter bags. For treatment group, one flower litter bag was placed into each pot microcosm ($27{\times}20{\times}8cm^3$) filled with influent water from the artificial pond, whereas control group microcosm contained pond water only. Decomposition time were set differently (4, 8, 12, 16 days) among treatment groups. At the end of experiment, most petals were decomposed and only 32.3% of initial dry weight remained with the decay rate (k) of $7.06{\times}10^{-2}day^{-1}$. $NO_3-N$ concentration of microcosm water decreased sharply from 1.90 mg/L at first to 0.02 mg/L, whereas $NH_4-N$ concentration increased from 0.03 mg/L to 2.85 mg/L continually. $PO_4-P$ concentration was 0.03 mg/L at first and increased to 2.39 mg/L by decomposition. Therefore, available phosphorus seems to have leached with higher rate than nitrogen from the petals litter. Increase about 0.02 mg/L in $PO_4-P$ concentration could be estimated in artificial pond from the calculation on the total quantity of fallen blossoms. This result suggests that available phosphorus from the decomposed Prunus petals could cause eutrophication in the artificial pond.

• Journal of Wetlands Research
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• v.15 no.3
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• pp.367-380
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• 2013

In this study, sub-indicators, and thematic mid-indexes to evaluate the water use characteristics were selected through historical data analysis and factor analysis, and consisted of the subject approach framework. And the integrated index was developed to evaluate water use characteristics of the watershed. Using developed index, the water use characteristics were assessed for 812 standard basins with the exception for North Korea using data of 1990 to 2007 from the relevant agencies. A sensitivity analysis is conducted for this study to determine the proper way through various normalization and weighting methods. To increase the objectivity of developed index, the history of the damage indicators are excluded in the analysis. In addition, in order to ensure its reliability, results from index with and without consideration of the damage history were compared. Also, the index is also applied to real data for 2008 Gangwon region to verify its field applicability. Through the validation process this index confirmed the adequacy for the indicators selection and calculation method. The results of this study were analyzed based on the spatial and time vulnerability of the basin's water use, which can be applied to various parts such as priority decision-making for water business or policy, mitigations for the vulnerable components of the basin, and supporting measures to establishment by providing relevant information about it.