• Journal of Biosystems Engineering
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• v.43 no.2
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• pp.103-109
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• 2018

Purpose: This study has been conducted to develop a potato yield monitoring system, consisting of a segmentation algorithm to detect potatoes scattered on a soil surface and a counting system to count the number of potatoes and convert the data from two-dimensional images to masses. Methods: First, a segmentation algorithm was developed using top-hat filtering and processing a series of images, and its performance was evaluated in a stationary condition. Second, a counting system was developed to count the number of potatoes in a moving condition and calculate the mass of each using a mass estimation equation, where the volume of a potato was obtained from its two-dimensional image, and the potato density and a correction factor were obtained experimentally. Experiments were conducted to segment potatoes on a soil surface for different potato sizes. The counting system was tested 10 times for 20 randomly selected potatoes in a simulated field condition. Furthermore, the estimated total mass of the potatoes was compared with their actual mass. Results: For a $640{\times}480$ image size, it took 0.04 s for the segmentation algorithm to process one frame. The root mean squared deviation (RMSD) and average percentage error for the measured mass of potatoes using this counting system were 12.65 g and 7.13%, respectively, when the camera was stationary. The system performance while moving was the best in L1 (0.313 m/s), where the RMSD and percentage error were 6.92 g and 7.79%, respectively. For 20 newly prepared potatoes and 10 replication measurements, the counting system exhibited a percentage error in the mass estimation ranging from 10.17-13.24%. Conclusions: At a travel speed of 0.313 m/s, the average percentage error and standard deviation of the mass measurement using the counting system were 12.03% and 1.04%, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.8
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• pp.2793-2800
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• 2010

In this paper, we propose a quadratic (nonlinear) regression model that forecasts daily demands of electric power in summer. For cost-effective production (and/or procurement) of electric power, forecasting demands of electric power with accuracy is important, especially in summer when temperature is high. In the literature, temperature and daily demands of preceding days are typically employed to construct forecasting models. While, we consider another factor, day of the week, together with temperature and daily demands of preceding days. For validating the proposed model, we demonstrate the forecasting accuracy in terms of MAPE(Mean Absolute Percentage Error) and MPE(Maximum Percentage Error) using field data from KEPCO(Korea Electric Power Corporation) in comparison with two forecasting models in the literature. When compared with the two benchmarks, the proposed forecasting model performs far better providing MAPE and MPE not exceeding 3.08% and 8.99%, respectively, in summer from 2005 to 2009.

• Geomechanics and Engineering
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• v.30 no.5
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• pp.437-448
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• 2022

Alluvial soil is challenging to work with due to its high compressibility. Thus, consolidation settlement of this type of soil should be accurately estimated. Accurate estimation of the consolidation settlement of alluvial soil requires accurate prediction of compressibility parameters. Geotechnical engineers usually use empirical correlations to estimate these compressibility parameters. However, no attempts have been made to develop correlations to estimate compressibility parameters of alluvial soil. Thus, this paper aims to develop new models to predict the compression and recompression indices (Cc and Cr) of alluvial soils. As part of the study, geotechnical laboratory tests have been conducted on large number of undisturbed samples of local alluvial soil. The obtained results from these tests in addition to available results from the literature from different parts in the world have been compiled to form the database of this study. This database is then employed to examine the accuracy of the available empirical correlations of the compressibility parameters and to develop the new models to estimate the compressibility parameters using the nonlinear regression analysis. The accuracy of the new models has been accessed using mean absolute error, root mean square error, mean, percentage of predictions with error range of ±20%, percentage of predictions with error range of ±30%, and coefficient of determination. It was found that the new models outperform the available correlations. Thus, these models can be used by geotechnical engineers with more confidence to predict Cc and Cr.

• Journal of Korean Society of Forest Science
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• v.3 no.1
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• pp.28-31
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• 1963

Recognizing shortcomings and unreasonable points of the usual methods of measurement of the standing-tree volume, author contrived measurement formula of standing-tree volume which is based on stem-curve equation, $y^2=2px$, resulted from the analysises and experiments on stem-curve by differentiation & integration. The results of this study are as follows ; (1) The following is the formula. $V=1/2g_{1.2}$(h+1.2) V=volume of tree $g_{1.2}$ = sectional area at breast heigh h = height of tree (2) So plain is the form of this formula that this formula is more convenient than usual formulas in measuring. (3) The percentage error of this formula is negative and it is remarkably superior to usual formulas except Pressler's formula, in other words, the higher the tree that is measured is, the more inaccurate become pressler's formula, and the percentage error of the breast-height form factor method is direct proportion to the grossness of the tree that is measured, but the higher the tree that is measured, the lower become percentage error of this formula in geometrical progression.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.487-500
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• 1999

We propose a class of hierarchical Bayes estimators of the error variance under the relative squared error loss in balanced fixed-effects two-way analysis of variance models. Also we provide analytic expressions for the risk improvement of the hierarchical Bayes estimators over multiples of the error sum of squares. Using these expressions we identify a subclass of the hierarchical Bayes estimators each member of which dominates the best multiple of the error sum of squares which is known to be minimax. Numerical values of the percentage risk improvement are given in some special cases.

• Geosystem Engineering
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• v.21 no.5
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• pp.273-281
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• 2018

In this study, the activated red mud was used as a new and appropriate adsorbent for the removal of ferrocyanide and ferricyanide from aqueous solution. Predicting the removal percentage and adsorption capacity of ferro-ferricyanide by activated red mud during the adsorption process is necessary which has been done by modeling and simulation. The artificial neural network (ANN) was used to develop new models for the predictions. A back propagation algorithm model was trained to develop a predictive model. The effective variables including pH, absorbent amount, absorbent type, ionic strength, stirring rate, time, adsorbate type, and adsorbate dosage were considered as inputs of the models. The correlation coefficient value ($R^2$) and root mean square error (RMSE) values of the testing data for the removal percentage and adsorption capacity using ANN models were 0.8560, 12.5667, 0.9329, and 10.8117, respectively. The results showed that the proposed ANN models can be used to predict the removal percentage and adsorption capacity of activated red mud for the removal of ferrocyanide and ferricyanide with reasonable error.

• Journal of Korean Society of Forest Science
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• v.6 no.1
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• pp.1-5
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• 1967

We studied on the bark Percentage of red pine (Pinus denssiflora S & Z) and tarch (Larix Kaemdferi sargent) and obtained the results as follows: (1) For diameter classes from 8 to 38 cm in red pine. the linear equation adopts the relation of the bark percentage to the diameter more accurately than the logarithmic equation. (2) The difference between the regression equation of the bark percentage between red pine and Larch is significant and the correlation cofficient in red Pine is high so that standard error of red Pine is lower than its value of Larch. We established, therefore the tables of bark percentage for each species by applying the following regression equations. red Pine Y=10.08205-0.08794x Larch Y=10.3527-0.17071x.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.628-632
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• 2007

The purpose of study is to confirm a acceptable range of data errors in data collecting. To examine a acceptable range of data errors, emission level is calculated for a vehicle flow and heavy vehicle percentage as a function of small-sized velocity. According to road selected, noise level of detail influence road noise calculations. It can be concluded that a vehicle flow raised an error less than 5000(veh/h) for a maximum error in emission level of 3.01dB, and the more a heavy vehicle percentage have a low value, the more emission level is a slight difference. This analysis gives insight regarding the accuracy of traffic flow data that is needed to reach a certain level of accuracy for the resulting noise level.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.1B
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• pp.21-27
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• 2011

When execute runoff forecasting, can not remove perfectly uncertainty of forecasting results. But, reduce uncertainty by various techniques analysis. This study applied various forecasting techniques for runoff prediction's accuracy elevation in Gongju basin. statics techniques is ESP, Period Average & Moving average, Exponential Smoothing, Winters, Auto regressive moving average process. Authoritativeness estimation with results of runoff forecasting by each techniques used MAE (Mean Absolute Error), RMSE (Root Mean Squared Error), RRMSE (Relative Root Mean Squared Error), Mean Absolute Percentage Error (MAPE), TIC (Theil Inequality Coefficient). Result that use MAE, RMSE, RRMSE, MAPE, TIC and confirm improvement effect of runoff forecasting, ESP techniques than the others displayed the best result.

• Korean Journal of Digital Imaging in Medicine
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• v.13 no.1
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• pp.33-38
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• 2011

Now a days, there's many change over for PACS among the most of hospital and it standard for DICOM 3.0. These kind of using of DICOM 3.0 improves increasing of medical imaging exchange and service for patient. However, there's some problems of compatibility caused during carry out CD and DVD from hospital. For this reason, this thesis analyzed patients image targeting those storages requested to hospitals in Seoul by using Validation Toolkit which is recommended from KFDA. The analyze type is like this. Make 100 data, total 500, each of MRI CT Plain x-ray Ultrasound PET-CT images and analyzed type of error occurred and loyalty of information. If express percentage of error occurred statistically, we can get a result as follows MRI 5%, Plain x-ray 11%, CT 18%, US 25%, PET-CT 30%. The reson why percentage of error occurred in PET-CT is because of imperfective support and we could notice that we weren't devoted to information. Even though, PET-CT showed highest percentage of error occurred, currently DICOM data improved a lot compare to past. Moreover, it should be devoted to rule of IHE TOOL or DICOM. In conclusion, we can help radiographer to analyze information of image by providing clues for solving primary problem and further more, each of PACS company or equipment company can enhance fidelity for following standard of image information through realizing the actual problem during transfer of image information.