• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.3
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• pp.278-284
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• 2016

Software reliability in the software development process is an important issue. In infinite failure NHPP software reliability models, the fault occurrence rates may have constant, monotonic increasing or monotonic decreasing pattern. In this paper, infinite failures NHPP models that the situation was reflected for the fault occurs in the repair time, were presented about comparing property. Commonly, the software model of the infinite failures using the linear hazard rate distribution software reliability based on intercept parameter was used in business economics and actuarial modeling, was presented for comparison problem. The result is that a relatively large intercept parameter was appeared effectively form. The parameters estimation using maximum likelihood estimation was conducted and model selection was performed using the mean square error and the coefficient of determination. The linear hazard rate distribution model is also efficient in terms of reliability because it (the coefficient of determination is 90% or more) in the field of the conventional model can be used as an alternative model could be confirmed. From this paper, the software developers have to consider intercept parameter of life distribution by prior knowledge of the software to identify failure modes which can be able to help.

• Journal of Korean Society of Transportation
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• v.33 no.6
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• pp.554-563
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• 2015

This study dealt with developing an accident model for rural signalized intersections with random parameter negative binomial method. The limitation of previous count models(especially, Poisson/Negative Binomial model) is not to explain the integrated variations in terms of time and the distinctive characters a specific point/segment has. This drawback of the traditional count models results in the underestimation of the standard error(t-value inflation) of the derived coefficient and finally affects the low-reliability of the whole model. To solve this problem, this study improves the limitation of traditional count models by suggesting the use of random parameter which takes account of heterogeneity of each point/segment. Through the analyses, it was found that the increase of traffic flow and pedestrian facilities on minor streets had positive effects on the increase of traffic accidents. Left turning lanes and median on major streets reduced the number of accidents. The analysis results show that the random parameter modeling is an effective method for investigating the influence on traffic accident from road geometries. However, this study could not analyze the effects of sequential changes of driving conditions including geometries and safety facilities.

• Journal of Veterinary Clinics
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• v.33 no.2
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• pp.107-112
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• 2016

The objective of this study was to determine potential contributing factors associated with biosecurity level of farrow-to-finish pig farms and to develop a classification tree model to explore how these factors related to each other based on prediction model. To this end, the author analyzed data (n = 193) extracted from a cross-sectional study of 344 farrow-to-finish farms which was conducted between March and September 2014 aimed to explore swine disease status at farm level. Standardized questionnaires with information about basic demographical data and management practices were collected in each farm by on-site visit of trained veterinarians. For the classification of the data sets regarding biosecurity level as a dependent variable and predictor variables, Chi-squared Automatic Interaction Detection (CHAID) algorithm was applied for modeling classification tree. The statistics of misclassification risk was used to evaluate the fitness of the model in terms of prediction results. Categorical multivariate input data (40 variables) was used to construct a classification tree, and the target variable was biosecurity level dichotomized into low versus high. In general, the level of biosecurity was lower in the majority of farms studied, mainly due to the limited implementation of on-farm basic biosecurity measures aimed at controlling the potential introduction and transmission of swine diseases. The CHAID model illustrated the relative importance of significant predictors in explaining the level of biosecurity; maintenance of medical records of treatment and vaccination, use of dedicated clothing to enter the farm, installing fence surrounding the farm perimeter, and periodic monitoring of the herd using written biosecurity plan in place. The misclassification risk estimate of the prediction model was 0.145 with the standard error of 0.025, indicating that 85.5% of the cases could be classified correctly by using the decision rule based on the current tree. Although CHAID approach could provide detailed information and insight about interactions among factors associated with biosecurity level, further evaluation of potential bias intervened in the course of data collection should be included in future studies. In addition, there is still need to validate findings through the external dataset with larger sample size to improve the external validity of the current model.

• Journal of Navigation and Port Research
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• v.32 no.6
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• pp.459-464
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• 2008

In this paper, we present the model-based fuzzy controller for container cranes which effectively performs set-point tracking control of trolley and anti-swaying control under system parameter and disturbance changes. The first part of this paper focuses on the development of Takagi-Sugeno (T-S) fuzzy modeling in a nonlinear container crane system. Parameters of the membership functions are adjusted by a RCGA to have same dynamic characteristics with nonlinear model of a container crane. In the second part, we present a design methodology of the model-based fuzzy controller. Sub-controllers are designed using LQ control theory for each subsystem in fuzzy model and then the proposed controller is performed with the combination of these sub-controllers by fuzzy IF-THEN rules. In the results of simulation, the fuzzy model showed almost similar dynamic characteristics compared to the outputs of the nonlinear container crane model. Also, the model-based fuzzy controller showed not only the fast settling time for the change in parameter and disturbance, but also stable and robust control performances without any steady-state error.

• Korean Journal of Remote Sensing
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• v.25 no.4
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• pp.311-320
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• 2009

This study was carried out to estimate forest biomass and to produce forest biomass thematic map for Muju county by combining field data from the 5$^{th}$ National Forest Inventory (2006-2007) and satellite data. For estimating forest biomass, two methods were examined using a Landsat TM-5(taken on April 28th, 2005) and field data: multi-variant regression modeling and t-Nearest Neighbor (k-NN) technique. Estimates of forest biomass by the two methods were compared by a cross-validation technique. The results showed that the two methods provide comparatively accurate estimation with similar RMSE (63.75$\sim$67.26ton/ha) and mean bias ($\pm$1ton/ha). However, it is concluded that the k-NN method for estimating forest biomass is superior in terms of estimation efficiency to the regression model. The total forest biomass of the study site is estimated 8.4 million ton, or 149 ton/ha by the k-NN technique.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.404-411
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• 2019

In this study, the HEC-HMS was applied to determine rainfall-runoff processes for the Gokgyuchun basin. Several sub-basins have large-scale reservoirs for agricultural needs and they store large amounts of initial runoff. Three infiltration methods were implemented to reflect the effect of initial loss by reservoirs: 'SCS-CN'(Scheme I), 'SCS-CN' with simple surface method(Scheme II), and 'Initial and Constant rate'(Scheme III). Modeling processes include incorporating three different methods for loss due to infiltration, Clark's UH model for transformation, exponential recession model for baseflow, and Muskingum model for channel routing. The parameters were calibrated using an optimization technique with trial and error method. Performance measures, such as NSE, RAR, and PBIAS, were adopted to aid in the calibration processes. The model performance for those methods was evaluated at Gangcheong station, which is the outlet of study site. Good accuracy in predicting runoff volume and peak flow, and peak time was obtained using the Scheme II and III, considering the initial loss, whereas Scheme I showed low reliability for storms. Scheme III did not show good matches between observed and simulated values for storms with multi peaks. Conclusively, Scheme II provided better results for both single and multi-peak storms. The results of this study can provide a useful tool for decision makers to determine master plans for regional flood control management.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.4
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• pp.267-277
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• 2019

Photogrammetry and computer vision are identical in determining the three-dimensional coordinates of images taken with a camera, but the two fields are not directly compatible with each other due to differences in camera lens distortion modeling methods and camera coordinate systems. In general, data processing of drone images is performed by bundle block adjustments using computer vision-based software, and then the plotting of the image is performed by photogrammetry-based software for mapping. In this case, we are faced with the problem of converting the model of camera lens distortions into the formula used in photogrammetry. Therefore, this study described the differences between the coordinate systems and lens distortion models used in photogrammetry and computer vision, and proposed a methodology for converting them. In order to verify the conversion formula of the camera lens distortion models, first, lens distortions were added to the virtual coordinates without lens distortions by using the computer vision-based lens distortion models. Then, the distortion coefficients were determined using photogrammetry-based lens distortion models, and the lens distortions were removed from the photo coordinates and compared with the virtual coordinates without the original distortions. The results showed that the root mean square distance was good within 0.5 pixels. In addition, epipolar images were generated to determine the accuracy by applying lens distortion coefficients for photogrammetry. The calculated root mean square error of y-parallax was found to be within 0.3 pixels.

• Journal of Korean Society of Forest Science
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• v.108 no.3
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• pp.364-371
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• 2019

This study was conducted to provide the basic information for a reasonable forest management plan and sustainable forest management by developing a dominant tree height growth model using diameter at breast height (DBH) and site index curves for Pinus densiflora and Chamaecyparis obtusa growing in Jeolla-do. The altitude, slope, orientation, soil type, height and DBH of a dominant tree, and the ages of trees were measured for 3055 Pinus densiflora trees (611 plots) and 3345 Chamaecyparis obtusa trees (699 plots), and these data were used to develop a customized afforestation map. In the dominant tree height growth model, the relationship to DBH was used in the Petterson, Michailow, and log equations. Also, a dominant tree height growth model in relationship to age used the Chapman-Richards, Schumacher, and Gompertz equations. The Petterson equation, which has a lower mean square error, was used to model dominant tree height growth in relationship to DBH. In the model of dominant tree height growth in relationship to age, three kinds of equations were considered to have little statistical difference. Therefore, the Chapman-Richards equation was chosen for modeling on the national level. Thirtyyears was used as the base age, which is an important factor for estimating the site index curves. In the results, a more varied range of site index family curves with 6-18 was developed for Pinus densiflora, and with 6-22 for Chamaecyparis obtusa. As the new site index curves indicated influences on growth of Pinus densiflora and Chamaecyparis obtusa, a reasonable forest management plan will be possible in the future for Jeolla-do.

• Food Science of Animal Resources
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• v.39 no.3
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• pp.371-378
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• 2019

The objective of this study was to develop mathematical models for describing the kinetic behavior of Staphylococcus aureus (S. aureus) in seasoned beef jerky. Seasoned beef jerky was cut into 10-g pieces. Next, 0.1 mL of S. aureus ATCC13565 was inoculated into the samples to obtain 3 Log CFU/g, and the samples were stored aerobically at $10^{\circ}C$, $20^{\circ}C$, $25^{\circ}C$, $30^{\circ}C$, and $35^{\circ}C$ for 600 h. S. aureus cell counts were enumerated on Baird Parker agar during storage. To develop a primary model, the Weibull model was fitted to the cell count data to calculate Delta (required time for the first decimal reduction) and ${\rho}$ (shape of curves). For secondary modeling, a polynomial model was fitted to the Delta values as a function of storage temperature. To evaluate the accuracy of the model prediction, the root mean square error (RMSE) was calculated by comparing the predicted data with the observed data. The surviving S. aureus cell counts were decreased at all storage temperatures. The Delta values were longer at $10^{\circ}C$, $20^{\circ}C$, and $25^{\circ}C$ than at $30^{\circ}C$ and $35^{\circ}C$. The secondary model well-described the temperature effect on Delta with an $R^2$ value of 0.920. In validation analysis, RMSE values of 0.325 suggested that the model performance was appropriate. S. aureus in beef jerky survives for a long period at low storage temperatures and that the model developed in this study is useful for describing the kinetic behavior of S. aureus in seasoned beef jerky.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.310-316
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• 2019

In automotive application, customers are demanding high efficiency and various functions for convenience. The demand for these automotive applications is steadily increasing. In this study, it has been studied the analysis of heat flow to improve the PCB(printed circuit board) heating performance of WPC (wireless power charger) recently developed for convenience. The charging performance of the wireless charger has been reduced due to power dissipation and thermal resistance of PCB. Therefore, it has been proposed optimal PCB design, layout and position of electronic parts through the simulation of heat flow analysis and PCB design was analyzed and decided at each design stage. Then, the experimental test is performed to verify the consistency of the analysis results under actual environmental conditions. In this paper, The PCB modeling and heat flow simulation in transient response were performed using HyperLynx Thermal and FloTHERM. In addition, the measurement was performed using infrared thermal imaging camera and used to verify the analysis results. In the final comparison, the error between analysis and experiment was found to be less than 10 % and the heating performance of PCB was also improved.