Journal of Korean Society for Geospatial Information Science
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v.11
no.3
s.26
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pp.23-34
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2003
Currently, the efficiency of GPS has been increased in the various precise survey like as the control survey and the navigation etc. Also, it is widely used in the deformation analysis of the structure, the measurement of the marine tides, the measurement of the river level and the topographic monitoring of seabed or riverbed by combined the measurement equipment for depth. In this study, we intend to increase in efficiency of the topographic monitoring of seabed or riverbed by combined with DGPS, RTK GPS and echo sounder. For this study, we defined the error correction of the echo sounder with the experiment of water tank which is considered the characteristic of estuary riverbed and then we developed the s/w for 3-dimensional monitoring of estuary riverbed and applied the s/w to field test and improved the various problems. On analyzing topography of estuary riverbed by combined GPS with echo sounder, the draught error which is yielded to change of length from the water surface by the movement of survey vessel to the end of the transducer was eliminated by geometrical rearrangement and we defined the correction formula $z=BM+SAH-DBR_{(i)}-DRT-ED$. The sounding error about the echo sounder and characteristic of estuary riverbed was found by understanding the relation of average diameter ind residual error and we defined correction formula, $Y=0.00474{\ast}ln(X)-0.0045$ by the regression analysis. and then we verified applicability of correction formula.
In this paper, we propose FPGA design technique for rotating LED display device which is capable of displaying videos with the use of the afterimage effect. The proposed technique is made up of image data correction process based on inverse gamma correction and error diffusion, block interleaving process, and data serial output process. The data correction process based on inverse gamma correction and error diffusion is an image data correction step in which image data received are corrected by inverse gamma correction process to convert the data into linear brightness characteristics, and by error diffusion process to reduce the brightness reduction phenomenon in low-gray-level which is caused by inverse gamma correction. In the block interleaving process, the data of the frames entered transversely are first saved in accordance with entrance order, and then only the longitudinal image data are read. The data serial output process is applied to convert the parallel data in a rotating location into serial data and send them to LED Driver IC, in order to send data which will be displayed on high-speedy rotating LED Bar. To evaluate the accuracy of the proposed FPGA design technique, this paper used XC6SLX45-FG484, a Spartan 6 family of Xilinx, as FPGA, and ISE 14.5 as a design tool. According to the evaluation analysis, it was found that goal values were consistent with simulation values in terms of accurate operation of inverse gamma and error diffusion correction, block interleaving operation, and serialized operation of image data.
Traffic volumes are fundamental data widely used in various traffic analysis, such as origin-and-destination establishment, total traveled kilometer distance calculation, congestion evaluation, and so on. The low number of links collecting the traffic-volume data in a large urban highway network has weakened the quality of the analyses in practice. This study proposes a method to estimate the traffic volume data on a highway link where no collection device is available by introducing a spatial statistic technique with (1) the traffic-volume data from TOPIS, and National Transport Information Center in the Ministry of Land, Infrastructure, and (2) the navigation data from private navigation. Two different component models were prepared for the interrupted and the uninterrupted flows respectively, due to their different traffic-flow characteristics: the piecewise constant function and the regression kriging. The comparison of the traffic volumes estimated by the proposed method against the ones counted in the field showed that the level of error includes 6.26% in MAPE and 5,410 in RMSE, and thus the prediction error is 20.3% in MAPE.
In P300-based concealed information test (P300 CIT), it evaluates whether the P300 amplitude for the probe is significantly greater than that of the irrelevant to determine if the suspect is telling a lie. An independent sample t-test or a bootstrap method can be used as a statistical test to make that decision. Rosenfeld et al. (2004) used the bootstrap method, claiming that "t tests on single sweeps are too insensitive to use to compare mean probe and irrelevant P300s within individuals" and their method has been accepted to date. The purpose of the study is to evaluate whether the power of t-test is lower than that of the bootstrap method in the P300 CIT. The Monte Carlo study was conducted by using EEG collected from 39 participants. The results showed that the type I error rates of the t-test and the percentile bootstrap method were similar and the power of the percentile bootstrap method was slightly higher than that of the t-test. The type I error rates of the t-test and the percentile bootstrap method were slightly lower than the significance level and the powers of the two tests were also slightly lower than that of the theoretical t-test. On the other hand, the type I error rate and power of the standard error Bootstrap method were the same as those of the theoretical t-test and its power was .012 ~ .081 higher than that of t-test depending on experimental conditions.
As the role of water distribution networks (WDNs) becomes more important, identifying abnormal events (e.g., pipe burst) rapidly and accurately is required. Since existing approaches such as field equipment-based detection methods have several limitations, model-based methods (e.g., machine learning based detection model) that identify abnormal events using hydraulic simulation models have been developed. However, no previous work has examined the impact of data uncertainties on the results. Thus, this study compares the effects of measurement error-induced pressure data uncertainty in WDNs. An artificial neural network (ANN) is used to predict nodal pressures and measurement errors are generated by using cumulative density function inverse sampling method that follows Gaussian distribution. Total of nine conditions (3 input datasets × 3 output datasets) are considered in the ANN model to investigate the impact of measurement error size on the prediction results. The results have shown that higher data uncertainty decreased ANN model's prediction accuracy. Also, the measurement error of output data had more impact on the model performance than input data that for a same measurement error size on the input and output data, the prediction accuracy was 72.25% and 38.61%, respectively. Thus, to increase ANN models prediction performance, reducing the magnitude of measurement errors of the output pressure node is considered to be more important than input node.
Minjee Kang;Cheong-Hee Lee;Kyu-Bok Lee;So-Yeun Kim;Du-Hyeong Lee
Journal of Dental Rehabilitation and Applied Science
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v.40
no.3
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pp.142-148
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2024
Purpose: The purpose of this study was to investigate the accuracy of digital mounting with occlusal scans in the interocclusal record for a full-mouth fixed prosthetic treatment condition. Materials and Methods: The entire maxillary teeth were prepared in a dentiform model and attached to an articulator in maximum intercuspation. Temporary crowns were fabricated and occlusion was adjusted. After scanning the arch with tooth preparation, digital mounting was performed using an occlusion scan of the anterior or posterior teeth areas. The accuracy of the positioned jaw relation was evaluated three-dimensionally through positional deviation and angular error of the occlusal plane. Afterwards, the same procedure was repeated on the partially edentulous model to evaluate the accuracy of digital interocclusal record. Kruskal-Wallis test and Mann-Whitney U test were used for statistical analysis, and the significance level was set at 0.05. Results: There was no significant difference in the positional error at the center of the arch in the digitally established jaw relation depending on the scan area used and remaining tooth conditions (P = 0.53). The angular error of the occlusal plane was larger when the anterior teeth were used as the overlapping area, and a smaller error value was observed when both posterior teeth were used as the overlapping area (P < 0.001). Conclusion: The use of bilateral posterior occlusal scans is recommended when digitally mounting the jaw relation established with temporary teeth during full-mouth fixed prosthetic treatment.
Ahn, So Ra;Lee, Ji Wan;Jang, Sun Sook;Kim, Seong Joon
Journal of The Korean Society of Agricultural Engineers
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v.58
no.4
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pp.21-35
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2016
This study is to evaluate the applicability of SWAT (Soil and Water Assessment Tool) model for multi-purpose dams and multi-function weirs operation in Namhan river basin ($12,577km^2$) of South Korea. The SWAT was calibrated (2005 ~ 2009) and validated (2010 ~ 2014) considering of 4 multi-purpose dams and 3 multi-function weirs using daily observed dam inflow and storage, evapotranspiration, soil moisture, and groundwater level data. Firstly, the dam inflow was calibrated by the five steps; (step 1) the physical rate between total runoff and evapotranspiration was controlled by ESCO, (step 2) the peak runoff was calibrated by CN, OV_N, and CH_N, (step 3) the baseflow was calibrated by GW_DELAY, (step 4) the recession curve of baseflow was calibrated by ALPHA_BF, (step 5) the flux between lateral flow and return flow was controlled by SOL_AWC and SOL_K, and (step 6) the flux between reevaporation and return flow was controlled by REVAPMN and GW_REVAP. Secondly, for the storage water level calibration, the SWAT emergency and principle spillway were applied for water level from design flood level to restricted water level for dam and from maximum to management water level for weir respectively. Finally, the parameters for evapotranspiration (ESCO), soil water (SOL_AWC) and groundwater level fluctuation (GWQMN, ALPHA_BF) were repeatedly adjusted by trial error method. For the dam inflow, the determination coefficient $R^2$ was above 0.80. The average Nash-Sutcliffe efficiency (NSE) was from 0.59 to 0.88 and the RMSE was from 3.3 mm/day to 8.6 mm/day respectively. For the water balance performance, the PBIAS was between 9.4 and 21.4 %. For the dam storage volume, the $R^2$ was above 0.63 and the PBIAS was between 6.3 and 13.5 % respectively. The average $R^2$ for evapotranspiration and soil moisture at CM (Cheongmicheon) site was 0.72 and 0.78, and the average $R^2$ for groundwater level was 0.59 and 0.60 at 2 YP (Yangpyeong) sites.
This study investigated the effect of protection of property right on foreign direct investment. With the US. multinational corporations over the periods from 2000 to 2008, this study used the FEM and system GMM, and found that the change of protection of property right level positively affects attracting foreign direct investment while protection of property right level itself does not. In the analyses on high income and low income countries(by income level), only the change of protection of property right level positively affects attracting foreign direct investment in low income countries. In considering the problem of heteroscedasticity on the error term, this study used FGLS and PCSE estimation methods. It is reported that the change of protection of property right level positively affects attracting foreign direct investment while protection of property right level itself does not. And only the change of protection of property right level positively affects attracting foreign direct investment in low income countries. This result means the change of protection of property right level is a key determinant to attract foreign direct investment.
The objectives of this study are to produce level 3 type LULC map and analysis of phenological features of North Korea, ISODATA clustering of the 88scenes of MVC of MODIS NDVI in 2008 and 8scenes in 2009 was carried out. Analysis of phenological phases based mapping method was conducted, In level 2 type map, the confusion matrix was summarized and Kappa coefficient was calculated. Total of 27 typical habitat types that represent the dominant species or vegetation density that cover land surface of North Korea in 2008 were made. The total of 27 classes includes the 17 forest biotopes, 7 different croplands, 2 built up types and one water body. Dormancy phase of winter (${\sigma}^2$ = 0.348) and green up phase in spring (${\sigma}^2$ = 0.347) displays phenological dynamics when much vegetation growth changes take place. Overall accuracy is (851/955) 85.85% and Kappa coefficient is 0.84. Phenological phase based mapping method was possible to minimize classification error when analyzing the inaccessible land of North Korea.
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.
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