• Explosives and Blasting
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• v.18 no.2
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• pp.7-13
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• 2000

Abstract The characteristics of bed rock in the study area was classified by means of the crack coefficient estimated from the seismic velocities of in-situ and intact rocks. Various statistical methods were investigated in order to minimize the possible errors in estimating the predictive equation of blasting vibration and to enhance the determination coefficient $R^2$, for more reliable estimation. The determination coefficient showed the highest in the analysis for those groups using weighting function with the number of samples. The analysis for the weighting function employed with standard coefficient and variance also enhanced the determination coefficients significantly compared to the others, but the reliability was slightly lower than results obtained former method. Therefore the most reliable predictive equation of blasting vibration was found to be obtained from a regression analysis of the mean vibration level using the weighting of same distance groups within 15m with the same explosive charge weight per delay. The coefficients, K and n 317.4 and -1.66, respectively, when using the square root scaling, and 209.9 and -1.66, respectively, when using the cube root scaling. The analysis also showed that the square root scaling may be used in the distance less than 31m form the blast source, and the cube root scaling in the distance more than 31m for safe design.

• Korean Journal of Applied Biomechanics
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• v.17 no.4
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• pp.115-125
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• 2007

Grould Reaction force(GRF) is important in human movements and GRF measurements are one of the most frequently used tool in biomechanical studies. In the studies of the golf swing motion, people refer to GRF as weight transfer. A successful golf swing motion requires many segments activation sequences which are controled by the nerve system. Due to the inter- and intra-individual variability of the human movement and the movement strategies, reliability of the measurements are important in human movement studies. Previous golf researches were based on group studies and certain events' values were analyzed. The purposes of this study were to determine the number of trials for the reliable golf swing GRF data collection, to reveal the variability level of the meaningful components of the golf swing GRF, and to classify the types of the golf swing GRF patterns. Twenty three male professional golfers($26.4{\pm}6.6$ years, $174.3{\pm}5.2\;cm$, $71.3{\pm}6.5\;kg$) signed an informed consent form prior to participation in this study. GRFs of driver swings were collected with Kistler 9285 force platform and 9865A amplifier, and calculated by the KwonGRF program(Visol, Korea). Sampling frequency was 1080 Hz. GRF data were trimmed from 1.5 s prior to the impact to 0.5 s after the impact. The number of trials for the reliable GRF collection was determined when the change in floating mean overs the 25 % of the standard deviation of that variable. Variabilities of the variables were determined by the coefficient of variation(CV) of 10 %. The types of GRF patterns were determined by visual inspection of the peak GRF shapes. The minimum number of trials for the reliable golf swing GRF data collection was five. Ten-trial seems more conservative. The value of the peak GRF was more reliable than the value of the impact GRF. The CV of the peak GRF and impact GRF were 7.4 %, 15.2 %, respectively. Because of the +/- sigh of the peak GRF appearance time, it was impossible to calculate CV of the peak GRF appearance time. Golf swing GRF patterns were classified as sing peak type, double peak type, and plateau peak type. This classification suggests the presence of the different golf swing weight transfer strategies.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1B
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• pp.15-30
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• 2000

The important considerations in the design of fiber-optic networks are reliability and survivability preparing against a failure. The SDH(Synchronous Digital Hierarchy), the international standard of optical transmission, offers several network reconfiguration methods that enable network to be automatically restored from failure. One of the methods is the SHR(Self Healing Ring), which is a ring topology system. Most network providers have constructed their backbone networks with SHR architecture since it can provide survivability economically. The network architecture has eventually evolved into a multi-ring network comprised of interconnected rings. This paper addresses multi-ring network design problems is to minimize ring-construction cost. This problem can be formulated with MIP(mixed integer programming) model. However, it is difficult to solve the model within reasonable computing time on a large scale network because the model is NP-complete. Furthermore, in practice we should consider the problem of routing demands on rings to minimize total cost. This routing problem involves multiplex bundling at the intermediate nodes. A family of heuristic algorithms is presented for this problem. These algorithms include gateway selection and routing of inter-ring demands as well as load balancing on single rings. The developed heuristic algorithms are applied to some network provider's regional and long-distance transmission networks. We show an example of ring design and compare it with another ring topology design. Finally, we analysis the effect bundling.

• Magazine of the Korean Society of Agricultural Engineers
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• v.22 no.3
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• pp.75-87
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• 1980

Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.

• International Journal of Highway Engineering
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• v.12 no.2
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• pp.9-16
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• 2010

Roughness is the most important factor to maintain the road performance, and affects greatly on the design life in Jointed Plain Concrete pavements. Also, the factors the evaluate pavement‘s commonality is the three method such as functionality, safety and structural performance. In evaluating function of road, representative factors is the roughness, which has been used to determine maintenance time as key standard. As research for roughness is absence in pavement design. Applied roughness-model had a low-reliability in Korea. Therefore, it is needed to develop reliable model in road roughness. In this research, uniform specific is applied to distribute them after selecting the concrete pavements. Concrete pavement is divided by sections of 238. Total length of this sections has 281km and account for 16% of total road length in korean concrete pavements for selected sections. Considering the korean roughness-model, the evaluation of roughness is performed for the freezing index, average annual rainfall, condition for the base, the amount of traffic as well as spalling(%), cracking(%), age(year) at the selected section at the selected section. Also, additional sections is selected to evaluate various age which affects on the roughness. As a result of the analysis, it showed that spalling(%), cracking(%), age(year), and the condition of the base affected road roughness. When the correlation with the road roughness was analyzed, the reliable model for road roughness was proposed, and the ratio that can explain road roughness was R2-68.8% and P value-0 which is statistically meaningful.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.5
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• pp.148-160
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• 2012

This study proposed more reasonable prediction models on compressive strength and carbonation of concrete structure and developed a more effective tunnel safety diagnosis and maintenance method through field application of the proposed prediction models. For this study, the Seoul Metro's Line 1 through Line 4 were selected as target structures because they were built more than 30 years ago and have accumulated numerous diagnosis and maintenance data for about 15 years. As a result of the analysis of compressive strength and carbonation, we were able to draw prediction models with accuracy of more than 80% and confirmed the prediction model's reliability by comparing it with the existing models. We've also confirmed field suitability of the prediction models by applying field, the average error of an estimate on compressive strength and carbonation depth was about 20%, which showed an accuracy of more than 80%. We developed a more effective maintenance method using durability prediction Map before field inspection. With the durability prediction Map, diagnostic engineers and structure managers can easily detect the vulnerable points, which might have failed to reach the standard of designed strength or have a high probability of corrosion due to carbonation, therefore, it is expected to make it possible for them to diagnose and maintain tunnels more effectively and efficiently.

• Journal of Korean Society of Disaster and Security
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• v.13 no.1
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• pp.25-39
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• 2020

Despite the global promotion of Smart City, there is currently no standard for smart water grid development, and it is not possible to judge the success of Smart City. There is a clear need to establish the requirements and goals of the Smart Water Grid and accurately diagnose and improve the limitations and problems of the existing Smart Water Grid. For this purpose, it is very important to use the index suitable for Smart Water Grid goals. In this study, we developed Smart Water Grid Index which can be used to evaluate the target measurement and attainment of Smart Water Grid and can be utilized based on the implementation plan for Smart Water Grid in the future. Through the development of the Smart Water Grid Key Performance Index (SWG KPI), we will lay the groundwork for continuous capacity evaluation of the Smart Water Grid and improve the reliability of the Index. It is expected that it will be possible to prepare and evaluate a Challenge Evaluation Card for the planned Smart Water Grid by providing an evaluation table for grid competency evaluation.

• Journal of Energy Engineering
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• v.24 no.4
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• pp.183-191
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• 2015

Studies on the environment-friendly and permanent low energy saving measure are and will continue to be an eternal challenge. However, the demand is high for the technologies that can save energy significantly in everyday life that produce tangible benefits for the users by applying saving factors and that anyone can access easily when it comes the related procedure. Government policies related to the improvement of energy effect in the existing building structure are characterized by complex procedure. Moreover, cost required and reliability issue emerge when request is made to an expert. Accordingly, this study seeks to present energy improvement plan that can be utilized simply and conveniently at any place, any time by enabling customized design according to individual taste by enabling energy change amount and grade prediction when the users select only the part that they want to replace by using a simple program.

• Journal of Food Hygiene and Safety
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• v.35 no.4
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• pp.398-410
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• 2020

In this study, the contents of soluble vitamins B₁ (thiamin), B₂ (riboflavin), and B₃ (niacin) in 13 kinds of rice, 11 kinds of noodles, and 15 kinds of sauces were identified. The limit of detection (LOD) and limit of quantification (LOQ) were checked to determine the reliability of the experimental results, and the accuracy of the results through the standard reference material (SRM 1849a) was verified to show excellent indicators. As for thiamin, japchaebab (stir-fried glass noodles with rice) was found to contain the highest content among rice dishes, makguksu (buckwheat noodles) among noodle dishes, and tomato spaghetti sauce among sauces. Riboflavin was identified as having the highest content in slightly spicy jajangbab (black-bean sauce with rice), bibimguksu (spicy noodles) for noodles, and spicy curry with turmeric for sauces. Niacin was highest in content in the deep and rich flavors of spicy chicken-fried rice, janchiguksu (banquet noodles), and black-bean sauce, respectively. As a result of checking the amount of recommended daily intake of water-soluble vitamins for Korean adult men and women, the highest content of riboflavin was 217.40% for men and 271.75% for women. Through this study, we are going to establish a database of nutrients for the water-soluble vitamins contained in rice, noodles, and sauces to provide the necessary dietary data concerning the content of the water-soluble vitamins contained in foods for daily recommended intake.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.366-372
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• 2019

The PRISM model has been used to estimate precipitation in South Korea where observation data are readily available at a large number of weather station. However, it is likely that the PRISM model would result in relatively low reliability of precipitation estimates in North Korea where weather data are available at a relatively small number of weather stations. Alternatively, a hybrid method has been developed to estimate the precipitation distribution in area where availability of climate data is relatively low. In the hybrid method, Regression coefficients between the precipitation-terrain relationships are applied to a low-resolution precipitation map produced using the PRISM. In the present study, a hybrid approach was applied to North Korea for estimation of precipitation distribution at a high spatial resolution. At first, the precipitation distribution map was produced at a low-resolution (2,430m) using the PRISM model. Secondly, a deviation map was prepared calculating difference between altitudes of synoptic stations and virtual terrains produced using 270m-resolution digital elevation map (DEM). Lastly, another deviation map of precipitation was obtained from the maps of virtual precipitation produced using observation data from the synoptic weather stations and both synoptic and automated weather station (AWS), respectively. The regression equation between precipitation and terrain was determined using these deviation maps. The high resolution map of precipitation distribution was obtained applying the regression equation to the low-resolution map. It was found that the hybrid approach resulted in better representation of the effects of the terrain. The precipitation distribution map for the hybrid approach had similar spatial pattern to that for the existing method. It was estimated that the mean annual cumulative precipitation of entire territory of North Korea was 1,195mm with a standard deviation of 253mm.