• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.3
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• pp.133-139
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• 2023

This paper proposes a two-stage Water Shield Automation System (WSAS) to predict the possibility of river overflow and vehicle flooding due to sudden rainfall. The WSAS uses a two-stage Deep Neural Network (DNN) model. First, a river overflow prediction module is designed with LSTM to decide whether the river is flooded by predicting the river's water level rise. Second, a vehicle flooding prediction module predicts flooding of underground parking lots by detecting flooded tires with YOLOv5 from CCTV images. Finally, the WSAS automatically installs the water barrier whenever the river overflow and vehicle flooding events happen in the underground parking lots. The only constraint to implementing is that collecting training data for flooded vehicle tires is challenging. This paper exploits the Image C&S data augmentation technique to synthesize flooded tire images. Experimental results validate the superiority of WSAS by showing that the river overflow prediction module can reduce RMSE by three times compared with the previous method, and the vehicle flooding detection module can increase mAP by 20% compared with the naive detection method, respectively.

• Asian-Australasian Journal of Animal Sciences
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• v.14 no.11
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• pp.1511-1515
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• 2001

A prediction of 305 d milk production from early records using an empirical Bayes method (EBM) was performed. The EBM was compared with the best predicted estimation (BPE), test interval method (TIM), and the linearized Wood's model (LWM). Daily milk yields were obtained from 606 first lactation Japanese Holstein cows in three herds. From each file of 305 daily records, 10 random test day records with an interval of approximately one month were taken. The accuracies of these methods were compared using the absolute difference (AD) and the standard deviation (SD) of the differences between the actual and the estimated 305 d milk production. The results showed that in the early stage of the lactation, EBM was superior in obtaining the prediction with high accuracy. When all the herds were analyzed jointly, the AD during the first 5 test day records were on average 373, 590, 917 and 1,042 kg for EBM, BPE, TIM, and LWM, respectively. Corresponding SD for EBM, BPE, TIM, and LWM were on average 488, 733, 747 and 1,605 kg. When the herds were analyzed separately, the EBM predictions retained high accuracy. When more information on the actual lactation was added to the prediction, TIM and LWM gradually achieved better accuracies. Finally, in the last period of the lactation, the accuracy of both of the methods exceeded EBM and BPM. The AD for the last 2 samples analyzing all the herds jointly were on average 141, 142, 164, and 214 kg for LWM, TIM, EBM, and BPE, respectively. In the current practices of collecting monthly records, early prediction of future milk production may be more accurate using EBM. Alternatively, if enough information of the actual lactation is accumulated, TIM may obtain better accuracy in the latter stage of lactation.

• Journal of ILASS-Korea
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• v.27 no.2
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• pp.57-65
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• 2022

The purpose of this study is to use machine learning to build a model capable of predicting the flash boiling spray characteristics. In this study, the flash boiling spray was visualized using Shadowgraph visualization technology, and then the spray image was processed with MATLAB to obtain quantitative data of spray characteristics. The experimental conditions were used as input, and the spray characteristics were used as output to train the machine learning model. For the machine learning model, the XGB (extreme gradient boosting) algorithm was used. Finally, the performance of machine learning model was evaluated using R² and RMSE (root mean square error). In order to have enough data to train the machine learning model, this study used 12 injectors with different design parameters, and set various fuel temperatures and ambient pressures, resulting in about 12,000 data. By comparing the performance of the model with different amounts of training data, it was found that the number of training data must reach at least 7,000 before the model can show optimal performance. The model showed different prediction performances for different spray characteristics. Compared with the upstream spray angle and the downstream spray angle, the model had the best prediction performance for the spray tip penetration. In addition, the prediction performance of the model showed a relatively poor trend in the initial stage of injection and the final stage of injection. The model performance is expired to be further enhanced by optimizing the hyper-parameters input into the model.

• Genomics & Informatics
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• v.20 no.2
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• pp.23.1-23.9
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• 2022

A survival prediction model has recently been developed to evaluate the prognosis of resected nonmetastatic pancreatic ductal adenocarcinoma based on a Cox model using two nationwide databases: Surveillance, Epidemiology and End Results (SEER) and Korea Tumor Registry System-Biliary Pancreas (KOTUS-BP). In this study, we applied two machine learning methods-random survival forests (RSF) and support vector machines (SVM)-for survival analysis and compared their prediction performance using the SEER and KOTUS-BP datasets. Three schemes were used for model development and evaluation. First, we utilized data from SEER for model development and used data from KOTUS-BP for external evaluation. Second, these two datasets were swapped by taking data from KOTUS-BP for model development and data from SEER for external evaluation. Finally, we mixed these two datasets half and half and utilized the mixed datasets for model development and validation. We used 9,624 patients from SEER and 3,281 patients from KOTUS-BP to construct a prediction model with seven covariates: age, sex, histologic differentiation, adjuvant treatment, resection margin status, and the American Joint Committee on Cancer 8th edition T-stage and N-stage. Comparing the three schemes, the performance of the Cox model, RSF, and SVM was better when using the mixed datasets than when using the unmixed datasets. When using the mixed datasets, the C-index, 1-year, 2-year, and 3-year time-dependent areas under the curve for the Cox model were 0.644, 0.698, 0.680, and 0.687, respectively. The Cox model performed slightly better than RSF and SVM.

• Journal of Ocean Engineering and Technology
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• v.23 no.2
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• pp.87-91
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• 2009

The welding distortion of a hull structure in the shipbuilding industry is inevitable at each assembly stage. The geometric inaccuracy caused by welding distortion tends to preclude the introduction of automation and mechanization and requires additional man-hours for adjustment work during the following assembly stage. To overcome this problem, a distortion control method should be applied. For this purpose, it is necessary to develop an accurate prediction method that can explicitly account for the influence of various factors on the welding distortion. The validity of this prediction method must also be clarified through experiments. For the purpose of reducing the weld-induced bending deflection, this paper proposes the plastic counter-deforming method (PCDM), which uses line heating as the optimum distortion control method. The validity of this method was substantiated by a number of numerical simulations and actual measurements.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.1
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• pp.116-124
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• 2006

A model test was carried out, in order to verify the hydrodynamic performances of public 30 feet class sailing yacht. In the initial design stage, the performances and the running attitude of sail yacht including the hull form and sail plan, appendages were estimated by VPP, from which made the representative test conditions. A new experiment system such as captive model device was composed because the running attitude could be changed by wind conditions. The test results show that the minimum resistance is generated in the heeling 20 degree. which was expected in the initial design stage. It is thought to be the useful informations that the keel has an effects on hydrodynamic forces and resistance differences between the upwind and the downwind condition. Also this paper is associated with the state-of-the-art of calculating sailing yacht performance as this is performed in velocity Prediction program (VPP) The VPP results shows a typical shape of a sailing yacht and the designed yacht has the best performance at 120 degree angle of true wind with 20 knots.

• Journal of Welding and Joining
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• v.21 no.4
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• pp.75-79
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• 2003

The welding distortion of a hull structure in the shipbuilding industry is inevitable at each assembly stage. This geometric inaccuracy caused by the welding distortion tends to preclude the introduction of automation and mechanization and needs the additional man-hours for the adjusting work at the following assembly stage. To overcome this problem, a distortion control method should be applied. For this purpose, it is necessary to develop an accurate prediction method which can explicitly account for the influence of various factors on the welding distortion. The validity of the prediction method must be also clarified through experiments. For the purpose of reducing the weld-induced bending deflection, this paper proposes the plastic counter-deforming method (PCDM) using the line heating as the optimum distortion control method. The validity of this method has been substantiated by a number of numerical simulations and actual measurements.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.12
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• pp.3357-3368
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• 1994

Total pressure losses required to calculate the total-to-total efficiency are estimated by integrating empirical loss coefficients of four loss mechanisms along the mean-line of blades as follows; blade profile loss, secondary flow loss, end wall loss and tip clearance loss. The off-design points are obtained on the basis of Howell's off-design performance of a compressor cascade. Also, inlet-outlet air angles and camber angle are obtained from semi-empirical relations of transonic airfoils' minimum loss incidence and deviation angles. And nominal point is replaced by the design point. It is concluded that relatively simple loss models and Howell's off-design data permit us to calculate the off-design performance with satisfactory accuracy. And this method can be easily extended for off-design performance prediction of multi-stage compressors.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.700-705
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• 2002

The welding distortion of a hull structure in the shipbuilding industry is inevitable at each assembly stage. The geometric inaccuracy caused by the distortion tends to preclude the introduction of automation and mechanization and needs the additional man-hours for the adjusting work at the following assembly stage. To overcome this problem, a distortion control method should be applied. For this purpose, it is necessary to develop an accurate prediction method which can explicitly account for the influence of various factors on the welding distortion. In order to minimize the weld-induced angular distortion in thick weldments, this paper proposes the optimum groove design for various plate thicknesses as the distortion control method. The validity of this method has been substantiated by a number of numerical simulations and experiments.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.06a
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• pp.824-831
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• 2005

A model test was carried out, in order to verify the hydrodynamic performances of public 30 feet class sailing yacht. In the initial design stage, the performances and the running attitude of sail yacht including the hull form and sail plan, appendages were estimated by VPP, from which made the representative test conditions. A new experiment system such as captive model device was composed because the running attitude could be changed by wind conditions. The test results show that the minimum resistance is generated in the heeling 20 degree, which was expected in the initial design stage. It is thought to be the useful informations that the keel has an effects on hydrodynamic forces and resistance differences between the upwind and the downwind condition. Also this paper is associated with the state-of-the-art of calculating sailing yacht performance as this is performed in velocity prediction program (VPP). The VPP results shows a typical shape of a sailing yacht and the designed yacht has the best performance at 120 degree angle of true wind with 20 knots.