• Journal of the Korean Recycled Construction Resources Institute
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• v.8 no.3
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• pp.276-285
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• 2020

In this study, accelerated chloride diffusion tests were performed on OPC(Ordinary Portland Cement) and FA(Fly Ash) concrete considering three levels o f W/B(Water to Binder) ratio o n 1,095 curing days. The accelerated chloride diffusion coefficient and the passed charge were evaluated in accordance with Tang's method and ASTM C 1202, and the resistance performance to chloride attack improved over time. FA concrete showed excellent resistance performance against chloride penetration with help of pozzolanic reaction. As the result of the passed charge, FA concrete showed durability improvement, "low" grade to "very low" grade, but OPC concrete changed "moderate" grade to "low" grade at 1,095 curing days. After assuming the design variables used for durability design as normal distribution functions, the service life of each case was evaluated by the probabilistic analysis method based on MCS(Monte Carlo Simulation). In FA concrete, the increase of probability of durability failure was lower than that of OPC concrete with increasing time, because the time-dependent coefficient of FA concrete was up to 3.2 times higher than OPC concrete. In addition, the service life by probabilistic analysis was evaluated lower than the service life by deterministic analysis, since the target probability of durability failure was set to 10%. It is considered that more economical durability design will be possible if the mo re suitable target probability of durability failure is set for various structures through researches on actual conditions and indoor tests under various circumstances.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.10 no.16
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• pp.101-106
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• 1987

Statistical control charts are useful tools to monitor and control the manufacturing processes and are widely used in most Korean industries. Many Korean companies, however, do not always obtain desired results from the traditional control charts by Shewhart such as the $\bar{X}$-chart, $\bar{X}$-chart, $\bar{X}$-chart, etc. This is partly because the quality charterstics of the process are not distributed normally but are skewed due to the intermittent production, small lot size, etc. In Shewhart $\bar{X}$-chart. which is the most widely used one in Kora, such skewed distributions make the plots to be inclined below or above the central line or outside the control limits although no assignable causes can be found. To overcome such shortcomings in nonnormally distributed processes, a distribution-free type of confidence interval can be used, which should be based on order statistics. This thesis is concerned with the design of control chart based on a sample median which is easy to use in practical situation and therefore properties for nonnormal distributions may be easily analyzed. Control limits and central lines are given for the more famous nonnormal distributions, such as Gamma, Beta, Lognormal, Weibull, Pareto, Truncated-normal distributions. Robustness of the proposed median control chart is compared with that of the $\bar{X}$-chart; the former tends to be superior to the latter as the probability distribution of the process becomes more skewed. The average run length to detect the assignable cause is also compared when the process has a Normal or a Gamma distribution for which the properties of X are easy to verify, the proposed chart is slightly worse than the $\bar{X}$-chart for the normally distributed product but much better for Gamma-distributed products. Average Run Lengths of the other distributions are also computed. To use the proposed control chart, the probability distribution of the process should be known or estimated. If it is not possible, the results of comparison of the robustness force us to use the proposed median control chart based oh a normal distribution. To estimate the distribution of the process, Sturge's formula is used to graph the histogram and the method of probability plotting, $\chi$$^2$-goodness of fit test and Kolmogorov-Smirnov test, are discussed with real case examples. A comparison of the proposed median chart and the $\bar{X}$ chart was also performed with these examples and the median chart turned out to be superior to the $\bar{X}$-chart.

• Journal of Korea Water Resources Association
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• v.36 no.4
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• pp.533-545
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• 2003

This study analyzed several storm events observed in the Seolma-chun basin to derive the characteristic velocity of GIUH (Geomophological Instantaneous Unit Hydrograph) as well as its variability. Especially, this study focused on the variation of characteristic velocity due to the change of rainfall characteristics. The IUH of the Seolma-chun basin was derived using the HEC-1, whose peak discharge and time were then compared with those of the GIUH to derive the characteristic velocities. The characteristics velocities were analyzed by comparing with the GcIUH (Geomorphoclimatic IUH) as well as the characteristics of rainfall. Results are summarized as follows. (1) The characteristic velocity of GIUH was estimated higher with higher variability than the GcIUH, but their trends were found similar (2) Total amount of effective rainfall (or, mean effective rainfall) well explains the characteristic velocity of GIUH. This could be assured by the regression analysis, whose coefficient of determination was estimated about 0.6. (3) The duration and the maximum intensity of rainfall were found not to affect significantly on the characteristic velocity of GIUH. The coefficients of determination were estimated less than 0.3 for all cases considered. (4) For the rainfall events used in this study, the characteristic velocities of GIUH were found to follow the Gaussian distribution with its mean and the standard deviation 0.402 m/s and 0.173 m/s, respectively. Most of the values are within the range of 0.4∼0.5 m/s, and its coefficient of variation was estimated to be 0.43, much less than that of the runoff itself (about 1.0).

• Water for future
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• v.14 no.4
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• pp.35-52
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• 1981

This study is to evaluate the areal precipitation from the basic data groups of monthly, seasonal, and annual rainfalls over all ma in stations in Korea. The evaluating pocesses are performed through the point and regional frequency analysis from the basic data. The basic data groups are divided into two periods-the first(1916-1944) and the second (1960-1979)-which are compared with each other. In the point frequecny analysis, the variable transformation method is applied to the best fitting distribution, and the normal fittings are established by using the Chisquare test method. In the regional frequency analysis, the geomorphologic factors and hydrometeorological factors are taken into consideration when dividing into five zones and Thiessen method and the Isohyetal method are applied. The results of this study are as follows: 1)The areal precipitation values of the first period are about 70-80mm less than that of the second period for the whole of Korea. Therefore, a new precipitation value of 1180mm is considered more suitable than the value of 1159mm, which has been up till now. 2)As the annual areal precipitiation values areevaluated over the five divide zones, it tis noticed that the difference between the values of the first period and the second is the largest in spring (to the extent of 5 times that in the other seasonas). Thereform it is considered that this result is necessary for the establishment of a timely insurance plan for the water resources. 3)The application of the Isohyetal method through the division of Korea into five zones is considered to be a reasonable procedure in the analysis of areal precipitation.

• Korean Journal of Weed Science
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• v.13 no.1
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• pp.62-70
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• 1993

There was intraspecific variation in Echinochloa crus-galli var, crus-galli in response to quinclorac, showing that plan height and dry weight of a locally collected barnyardgrass(Chinjupi) from Chinju were 90.5 and 37.8% of the untreated control, while those of a locally collected one(Iripi) from Iri showed 19.1 and 14.4%, respectively. The normal distribution curve was obtained from frequency distribution of 89 rice cultivars as affected by the application rates of quinclorac at 30, 300, and 3,000g ai/ha. Protein patterns(SDS-PAGE) of two barnyardgrasses belonging to E, crus-galli var. crus-galli such as Iripi and Chinjupi were not affected by the quinclorac application, indicating that inhibition of enzyme and/or protein biosynthesis seems to be not the primary action target of quinclorac. Electronmicroscopic observation on the injured leaf of Iripi which is considered as a susceptible one showed prominent membrane disruption. Chuchungbyeo(rice variety) resulted in a greater inhibition of tomato growth than those from Chinjupi or Iripi, indicating a great amount of quinclorac discharged from rice root, Chinjupi which is relatively tolerant to quinclorac than Iripi, discharged more quinclorac causing a greater inhibition of tomato growth.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.10
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• pp.465-472
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• 2017

In the past, researchers mainly used the supervised learning technique of machine learning to analyze power data and investigated the identification of patterns through the data mining technique. Data analysis research, however, faces its limitations with the old data classification and analysis techniques today when the size of electric power data has increased with the possible real-time provision of data. This study thus set out to propose a clustering architecture to analyze large-sized electric power data. The clustering process proposed in the study supplements the K-means algorithm, an unsupervised learning technique, for its problems and is capable of automating the entire process from the collection of electric power data to their analysis. In the present study, power data were categorized and analyzed in total three levels, which include the row data level, clustering level, and user interface level. In addition, the investigator identified K, the ideal number of clusters, based on principal component analysis and normal distribution and proposed an altered K-means algorithm to reduce data that would be categorized as ideal points in order to increase the efficiency of clustering.

• Korean Journal of Remote Sensing
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• v.13 no.1
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• pp.47-56
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• 1997

In this paper, remote sensing is used to estimate trophic state which is primary concern in a lake. In using remote sensing, this study estimated trophic state not with conventional method such as regression equations but with classification methods. As europhication is caused by the extraodinary proliferation of the algae, chlorophyll a and transparency are applied to remote sensing data.. Maximum Likelihood Classification and Minimum Distance Classification which are kinds of classification methods enabled trophic state to be confirmed in a lake. These are obtained as the result of applying remote sensing to classify trophic state in a lake. Firest, when we evaluate tropic state in a large area of water body, the application of remote sensing data can obtain more than 70% accuracies just in using basic classification methods. Second, in the aspect of classification, the accuracy of Minimum Distance Classification is usually better than that of Maximum Likelihood Classification. This result is caused that samples have normal distribution, but their numbers are a few to apply statistical method. Therefore, classification method is required such as artificial neural networks which are not influenced by statistical distribution. Third, this study enables the trophic state of water body to be analyzed and evaluated rapidly, periodically and visibly. Also, this study is good for forming proper countermeasure accompanying with trophic state progress extent in a lake and is useful for basic-data.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1317-1328
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• 2021

This study analyzes the early satellite mission marine fog detection results from Geostationary Ocean Color Imager-II (GOCI-II). We investigate optical characteristics of the GOCI-II spectral bands for marine fog between October 2020 and March 2021 during the overlapping mission period of Geostationary Ocean Color Imager (GOCI) and GOCI-II. For Rayleigh-corrected reflection (R_rc) at 412 nm band available for the input of the GOCI-II marine fog algorithm, the inter-comparison between GOCI and GOCI-II data showed a small Root Mean Square Error (RMSE) value (0.01) with a high correlation coefficient (0.988). Another input variable, Normalized Localization Standard (NLSD), also shows a reasonable correlation (0.798) between the GOCI and GOCI-II data with a small RMSE value (0.007). We also found distinctive optical characteristics between marine fog and clouds by the GOCI-II observations, showing the narrower distribution of all bands' R_rc values centered at high values for cloud compared to marine fog. The GOCI-II marine fog detection distribution for actual cases is similar to the GOCI but more detailed due to the improved spatial resolution from 500 m to 250 m. The validation with the automated synoptic observing system (ASOS) visibility data confirms the initial reliability of the GOCI-II marine fog detection. Also, it is expected to improve the performance of the GOCI-II marine fog detection algorithm by adding sufficient samples to verify stable performance, improving the post-processing process by replacing real-time available cloud input data and reducing false alarm by adding aerosol information.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.1-9
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• 2021

Traditionally, most malicious codes have been analyzed using feature information extracted by domain experts. However, this feature-based analysis method depends on the analyst's capabilities and has limitations in detecting variant malicious codes that have modified existing malicious codes. In this study, we propose a ResNet-Variational AutoEncder-based variant malware classification method that can classify a family of variant malware without domain expert intervention. The Variational AutoEncoder network has the characteristics of creating new data within a normal distribution and understanding the characteristics of the data well in the learning process of training data provided as input values. In this study, important features of malicious code could be extracted by extracting latent variables in the learning process of Variational AutoEncoder. In addition, transfer learning was performed to better learn the characteristics of the training data and increase the efficiency of learning. The learning parameters of the ResNet-152 model pre-trained with the ImageNet Dataset were transferred to the learning parameters of the Encoder Network. The ResNet-Variational AutoEncoder that performed transfer learning showed higher performance than the existing Variational AutoEncoder and provided learning efficiency. Meanwhile, an ensemble model, Stacking Classifier, was used as a method for classifying variant malicious codes. As a result of learning the Stacking Classifier based on the characteristic data of the variant malware extracted by the Encoder Network of the ResNet-VAE model, an accuracy of 98.66% and an F1-Score of 98.68 were obtained.

• 한국사회정책
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• v.23 no.3
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• pp.17-47
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• 2016

This paper aims to analysis working-time of Korea focusing on "the difference and the distribution" by a stratum. Classifying working-time into four categories including marginal part-time, part-time work, standard-time work and long-time working, it compares the relative distribution by income quintile. The outcome is as following : 20% of low-ranking income quintile are (marginal) part-time working, 60% from income quintile 2 to 4 are in long-time working and 20% of top-ranking income quintile are in the standard-time working in overall. Working-time classes can be divided up into three: short time-low income of type 1, long time-medium income of type 2 and standard time-high income of type 3. Analysing working time type, the low wage-short time, medium wage-long time and high wage-standard time by the wage per month and low wage-very long time, medium wage-long time and high wage-standard time by the wage per hours are confirmed. Also, stratification of working-time has been intensified in terms of age, jobs and work status. Policy implication from this study is that the increase of minimum wage to the lowest income class and creation of employment by the reduction of working-time to the medium income class could be effective policies.