• Journal of Positioning, Navigation, and Timing
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• v.5 no.2
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• pp.75-85
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• 2016

The performance of up-to-date mapping functions and various mean temperature equations were analyzed to derive optimal mapping function and mean temperature equation when GNSS precipitable water vapor (PWV) was investigated in the Korean Peninsula. Bernese GNSS Software 5.2, which can perform high precision GNSS data processing, was used for accurate analysis, and zenith total delay (ZTD) required to calculate PWV was estimated via the Precise Point Positioning (PPP) method. GNSS, radiosonde, and meteorological data from 2009 to 2014 were acquired from Sokcho Observatory and used. ZTDs estimated by applying the global mapping function (GMF) and Vienna mapping function 1 (VMF1) were compared with each other in order to evaluate the performance of the mapping functions. To assess the performance of mean temperature equations, GNSS PWV was calculated by using six mean temperature equations and a difference with radiosonde PWV was investigated. Conclusively, accuracy of data processing was improved more when using VMF1 than using GMF. A mean temperature equation proposed by Wu (2003) had the smallest difference with that in the radiosonde in the analysis including all seasons. In summer, a mean temperature equation proposed by Song & Grejner-Brzezinska (2009) had the closest results with that of radiosonde. In winter, a mean temperature equation proposed by Song (2009) showed the closest results with that of radiosonde.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.11 no.4
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• pp.227-236
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• 1986

In this paper, an integrated voice/data packet network with window flow control is modeled by a colsed multichain queueing system, and its performance is analyzed by the mean value analysis method. Particularly, for the analysis of a packet network having various kinds of messages with different priority classes, we introduce an approach based on the mean value analysis and the concept of effective capacity. By the mathematical analysis and computer simulation, we obtain the following network statistics in the steady state: Mean buffer occupancy at each node, utilization of link throughput of a virtual channel, and mean delay time of each message. Our iterative analysis method can predict the link data status in most cases within about 10 percent of accurady, and the statistics of voice messages and external data within 5 percent as compared to simulation results.

• The Journal of Internal Korean Medicine
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• v.29 no.3
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• pp.535-542
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• 2008

Objectives : Ryodoraku, which is a physiological function test using electric current, is closely related to skin sympathetic tone. Pulse analysis is known to reflect cardiovascular reactivity. Refer to the previous researches Ryodoraku and pulse analysis have value as tools for diagnosing respiratory diseases. In this study we examined the diagnostic values of Ryodoraku and pulse analysis for respiratory disease patients. Methods : For this study. we conducted Ryodoraku and pulse analysis on 114 people, including 83 respiratory disease outpatients and 31 volunteers who did not have any respiratory symptoms or disease history. The respiratory patients were divided into three subgroups according to their symptoms: rhinorrhea group, cough-sputum group and wheezing-dyspnea group. Then we compared the disease groups with the control group. Results : When all experimental groups were compared with the control group, mean Ryodoraku was significantly lower. Mean H2, mean H3 and mean H6 were significantly lower in the rhinorrhea group (P<0.05), all the test results of Ryodoraku were evidently lower in the cough-sputum group (P<0.01), and most results of Ryodoraku were evidently lower in the wheezing-dyspnea group except H1 (P<0.01). Compared with the control group on pulse analysis, mean YP+/YP- was significantly lower in the wheezing-dyspnea group (P<0.05). Conclusion : Ryodoraku and pulse analysis were found to have a high value as quantitative diagnosis tools reflecting individuals' weakness and firmness. Nevertheless, more research is needed to find the further values.

• Composites Research
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• v.36 no.5
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• pp.329-334
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• 2023

The classical multiscale finite element (FE² ) method involves iterative calculations of micro-boundary value problems for representative volume elements at every integration point in macro scale, making it a computationally time and data storage space. To overcome this, we developed the data-driven multiscale analysis method based on the mean-field homogenization (MFH). Data-driven computational mechanics (DDCM) analysis is a model-free approach that directly utilizes strain-stress datasets. For performing multiscale analysis, we efficiently construct a strain-stress database for the microstructure of composite materials using mean-field homogenization and conduct data-driven computational mechanics simulations based on this database. In this paper, we apply the developed multiscale analysis framework to an example, confirming the results of data-driven computational mechanics simulations considering the microstructure of a hyperelastic composite material. Therefore, the application of data-driven computational mechanics approach in multiscale analysis can be applied to various materials and structures, opening up new possibilities for multiscale analysis research and applications.

• Research in Mathematical Education
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• v.12 no.1
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• pp.49-66
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• 2008

In this paper we present a cognitive developmental analysis of the arithmetic mean concept. This analysis leads us to a hierarchical classification at different levels of understanding of the responses of 227 students to a questionnaire which combines open-ended and multiple-choice questions. The SOLO theoretical framework is used for this analysis and we find five levels of students' responses. These responses confirm different types of difficulties encountered by students regarding their conceptualization of the arithmetic mean. Also we have observed that there are no significant differences between secondary school and university students' responses.

• Journal of Bio-Environment Control
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• v.17 no.2
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• pp.124-131
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• 2008

To investigate main air temperature factors correlated to difference of fruit characteristics according to cultivating areas, fruit and air temperature characteristics of eight cultivating areas of 'Fuyu' persimmon were analyzed by principle components and multiple regression analysis. The first principal components extracted from 16 air temperature factors was annual mean temperature, mean temperature during October, annual mean minimum extreme temperature, mean temperature during growing period, and so forth. The second principal components was mean temperature during May and June and so forth. And cumulative contribution was 91.4%. The five of eight cultivating area had clearly the difference of main factors or the correlated direction among cultivating areas. In multiple regression analysis between the extracted main factors and fruit characteristics, fruit hight were highly correlated with mean temperature during growing period ($X_8$) and cumulative temperature ($X_6$), and the regression equation was $Y=150.55-5.375X_8+ 0.014X_6(r^2=0.843)$. Also this regression equation was affected by mean minimum temperature during growing period, cumulative temperature, and mean temperature during August. Fruit diameter was negatively correlated with mean temperature during growing period, flesh browning rate and Hunter a value of peel color were positively correlated with mean minimum temperature during growing period and annual minimum air temperature, respectively.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.58
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• pp.113-118
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• 2000

Estimation of the process deviation is an important problem in statistical process control, especially in the control chart, process capability analysis or measurement system analysis. In this paper we suggest the use of the Gini's mean difference for the estimation of the c, the measure of the process deviation through a lots of simulations in various types of distributions. The Gini's mean difference uses the differences of all possible pairs of data. This point will improve the efficiency of estimation. In various classes of distributions, the Gini's mean difference shows good performance, in sense of bias of estimates or mean squared errors.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.10 no.1
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• pp.108-117
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• 1998

This study was performed to analyze the fluid flow characteristics and the temperature distribution of the aquarium for fish breeding. In this study, the finite volume method and turbulence k-$\varepsilon$ model with the SIMPLE computational algorithm are used to study the water flow in the aquarium. The calculation parameters are the circulating flow rate and the basin depth, and the experiments were carried out for the water flow visualization This numerical analysis gives reasonable velocity distributions in good agreement with the experimental data. As the results of the three dimmentional simulations, the sectional mean velocity increased as the sectional mean temperature increases for constant basin depth, and the mean velocity increased more rapidly for small basin depth than that of large basin depth, The mean velocity and temperature can be expressed as the function of the circulating flow rates and the basin depth.

• The Journal of Fisheries Business Administration
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• v.42 no.3
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• pp.79-93
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• 2011

Water temperature of Oliver flounder farm affects Oliver flounder growth and mortality rate. In laboratory experimental tanks, optimal water temperature was $22.5^{\circ}C$($21{\sim}24^{\circ}C$) and cultivatable water temperature was $12{\sim}28^{\circ}C$. The purpose of this study is to identify applicable and useful water temperature of Oliver flounder farm in case of actual farming. The data applied in the analysis was collected from Jeju island. In the study, various analytical methods including productivity analysis, regression analysis, statistical analysis were conducted for 13 Oliver flounder culture farms. The result of analysis can be summarized as follows : First, growth rate on the Oliver flounder culture farms was related to mean of water temperature, variation of water temperature and low water temperature. Second, survival rate on the Oliver flounder culture farms was related to mean of water temperature. In case of including Oliver flounder stocking density, defined as the surface area of Oliver flounder per $m^2$ of water surface area, survival rate strongly related to mean of water temperature, variation of water temperature, cultivating capability and stocking density. Third, production weight per $m^2$ of water surface area was strongly related to mean of water temperature, low water temperature and cultivating capability. Growth rate and survival rate was analyzed into mediate variable character.

• Journal of Korean Society for Quality Management
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• v.29 no.3
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• pp.79-85
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• 2001

Estimation of the process deviation is an important problem in statistical process control, especially in the control chart, process capability analysis or measurement system analysis. In this paper we suggest the use of the Gini's mean difference for the estimation of the process deviation when we design the control limits in construction of the control charts. The efficiency of the Gini's mean difference was well explained in Nam, Lee and Jung(2000). In this paper we propose an $\overline{X}$ control chart which use the control limits based on the Gini's mean difference. In various classes of distributions, the proposed control chart shows food performance.