• Spatial Information Research
• /
• v.10 no.2
• /
• pp.301-316
• /
• 2002

Soil Loss by outflow of water or rainfall has caused many environmental problems as declining agricultural productivity, damaging pasture and preventing flow of water. Also, validity pondage of reservoir or dam is decreased by rivers inflow of eroded soil. Revised Universal Soil Loss Equation(RUSLE) is mainly used to presume soil loss amount of basin using GIS. But, because comparison with survey data is difficult, it is no large meaning that estimate calculated soil loss amount as quantitative. This research used unit sediment deposit survey data of Bo-seong basin for quantitative conclusion of soil loss amount that calculate on RUSLE. Through comparison examination with unit sediment yield that calculate on RUSLE and unit sediment deposit survey data, we can estimate resolution far RUSLE Model. As a result, cell size of 150m was estimated by thing which is most suitable.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.16 no.1
• /
• pp.77-82
• /
• 2003

The ac loss is an important issue in the design of high-Tc superconducting power devices such as transformers and cables. In these devices many Bi-2223 tapes are closely stacked together and exposed to alternating magnetic fields that can have different orientations with respect to a tape. In such arrangement the magnetization loss is influenced by the screening current induced in adjacent tapes and thus different from that in a single tape. This stacking effect was experimentally investigated by measuring the magnetization loss in a stack, which consists of a number of tapes. First the magnetization loss in the single tape was measured in order to confirm the reliability of the loss data measured in the stack. The results for the single tape coincide well will the loss characteristics described in other previous works. For the stack In parallel and longitudinal magnetic fields the measured loss is Independent of both the number of tapes and stacking type. The longitudinal magnetization loss Is well explained rather by the slab model for decoupled filaments. For the tall stack in perpendicular field the measured loss at low fields is greatly decreased, compared to the loss of the single tape. However the loss at high fields is unaffected. These loss behaviors in the tall stack are well described by the slab model for full coupling.

• The Korean Journal of Applied Statistics
• /
• v.25 no.1
• /
• pp.101-114
• /
• 2012

In car insurance, the loss ratio is the ratio of total losses paid out in claims divided by the total earned premiums. In order to minimize the loss to the insurance company, estimating extreme quantiles of loss ratio distribution is necessary because the loss ratio has essential prot and loss information. Like other types of insurance related datasets, the distribution of the loss ratio has heavy-tailed distribution. The Peaks over Threshold(POT) and the Hill estimator are commonly used to estimate extreme quantiles for heavy-tailed distribution. This article compares and analyzes the performances of various kinds of parameter estimating methods by using a simulation and the real loss ratio of car insurance data. In addition, we estimate extreme quantiles using the Hill estimator. As a result, the simulation and the loss ratio data applications demonstrate that the POT method estimates quantiles more accurately than the Hill estimation method in most cases. Moreover, MLE, Zhang, NLS-2 methods show the best performances among the methods of the GPD parameters estimation.

• Nutrition Research and Practice
• /
• v.16 no.2
• /
• pp.205-216
• /
• 2022

BACKGROUND/OBJECTIVES: While many obesity studies have pointed out the importance of meal regularity, few have conducted empirical analyses using data from food diaries. We examined the association between meal regularity (i.e., meal time regularity [MTR] and calorie intake regularity [CIR]) and weight loss. SUBJECTS/METHODS: We collected food diary data from 637 women who had participated in commercial weight loss programs for 28-168 days (4-24 weeks). This study defined "meal regularity" in terms of two concepts: MTR and CIR. MTR refers to how regularly people eat their meals (i.e., at certain times each day), whereas CIR refers to how regularly people consume a certain amount of calories at each meal. We conducted multiple regression analyses. RESULTS: MTR (model 1: β = -2,576.526, P < 0.001; model 2: β = -1511.447, P < 0.05; model 3: β = -1,721.428, P < 0.05) and CIR (model 1: β = -1,231.551, P < 0.01; model 2: β = -2,082.353, P < 0.001; model 3: β = -1,343.490, P < 0.01) turned out to be significant determinants of the amount of weight loss in breakfast, lunch, and dinner contexts. While meal regularity (i.e., MTR and CIR) was significantly associated with weight loss, daily calorie intake from meals was not significantly associated with the amount of weight loss (model 1: β = 0.13, P > 0.05; model 2: β = 0.11, P > 0.05; model 3: β = 0.14, P > 0.05). Subjects who consumed an equal amount of calories per meal throughout the day lost more weight than those who did not (model 4: β = -3,675.51, P < 0.001). CONCLUSIONS: Eating each meal (i.e., breakfast, lunch, and dinner) at a certain time every day may increase weight loss success. Also, consuming the same amount of calories at each meal may help weight loss success.

• The Journal of the Acoustical Society of Korea
• /
• v.41 no.6
• /
• pp.647-654
• /
• 2022

Although the fields in which is utilized children's speech recognition is on the rise, the lack of quality data is an obstacle to improving children's speech recognition performance. This paper proposes a new method for improving children's speech recognition performance by additionally using adult speech data. The proposed method is a transformer based domain adversarial training using dynamically weighted loss to effectively address the data imbalance gap between age that grows as the amount of adult training data increases. Specifically, the degree of class imbalance in the mini-batch during training was quantified, and the loss function was defined and used so that the smaller the data, the greater the weight. Experiments validate the utility of proposed domain adversarial training following asymmetry between adults and children training data. Experiments show that the proposed method has higher children's speech recognition performance than traditional domain adversarial training method under all conditions in which asymmetry between age occurs in the training data.

• International Journal of Fluid Machinery and Systems
• /
• v.10 no.1
• /
• pp.63-75
• /
• 2017

Many axial fans have circular arc blades with constant thickness. It is still a challenging task to calculate their performance, i.e. to predict how large their pressure rise and pressure losses are. For this task a need for cascade data exists. Therefore, the designer needs a method which works quickly for design purposes. In the present contribution a design method for such cascades consisting of circular arc blades with constant thickness is described. It is based on a singularity method which is combined with a CFD-data-based flow loss model. The flow loss model uses CFD-data to predict the total pressure losses. An interpolation method for the CFD-data are applied and described in detail. Data of measurements are used to validate the CFD-data and parameter variations are conducted. The parameter variations include the variation of the camber angle, pitch chord ratio and the Reynolds number. Additionally, flow patterns of two dimensional cascades consisting of circular arc blades with constant thickness are shown.

• Transactions of Materials Processing
• /
• v.31 no.4
• /
• pp.229-239
• /
• 2022

Convolution Neural Network(CNN) is a class of deep learning algorithms and can be used for image analysis. In particular, it has excellent performance in finding the pattern of images. Therefore, CNN is commonly applied for recognizing, learning and classifying images. In this study, the surface defect classification performance of Al 6061 extruded material using CNN-based algorithms were compared and evaluated. First, the data collection criteria were suggested and a total of 2,024 datasets were prepared. And they were randomly classified into 1,417 learning data and 607 evaluation data. After that, the size and quality of the training data set were improved using data augmentation techniques to increase the performance of deep learning. The CNN-based algorithms used in this study were VGGNet-16, VGGNet-19, ResNet-50 and DenseNet-121. The evaluation of the defect classification performance was made by comparing the accuracy, loss, and learning speed using verification data. The DenseNet-121 algorithm showed better performance than other algorithms with an accuracy of 99.13% and a loss value of 0.037. This was due to the structural characteristics of the DenseNet model, and the information loss was reduced by acquiring information from all previous layers for image identification in this algorithm. Based on the above results, the possibility of machine vision application of CNN-based model for the surface defect classification of Al extruded materials was also discussed.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.20 no.8
• /
• pp.703-709
• /
• 2010

An analysis tool for predicting transmission loss in high speed trains based on combined use of the statistical energy analysis and the finite element methods has been proposed. The analysis utilizes a commercially available numerical solver VA ONE with imbedded NASTRAN module. The proposed analysis tool is first verified by comparing numerically predicted transmission loss of a light rail transport(LRT) structure with experimental results. The comparison shows that the numerically predicted transmission loss is similar to the experimental data. The analysis tool is then applied to the prediction of transmission loss in the high speed train(HST) currently under development. Various sub-structures such as the floor, side panel and ceiling have been numerically analyzed to predict their transmission losses. The results obtained here can be used as input data for predicting the interior noise level of the HST at design stage.

• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.9
• /
• pp.305-314
• /
• 2020

This paper investigates the impact of profit and loss sharing (PLS) contracts on non-performing financing of Islamic rural banks as Islamic small banks focus on small and medium enterprises at province level across country. Our study employs panel data, consisting of 142 Islamic rural banks and using quarterly data from 2013Q1 to 2018Q4, and splits them based on the bank's size and geographical area. Both static and dynamic panel regressions are then applied. The results obviously indicate that a high proportion of profit and loss sharing contracts leads to high financing risk. The large Islamic banks encounter a higher non-performing financing stemming from profit and loss contracts compared to small Islamic banks. Profit and loss contracts also produce higher financing risk for Islamic banks outside Java, as those areas are less developed areas than Java itself. A more efficient Islamic bank is less financing risk. Income diversification lessens the impaired financing and, more particularly, large Islamic banks and Islamic banks located in Java much benefit by diversifying income and financing to lower financing risk. Our study suggests that Islamic rural banks may consider the optimal level of profit and loss sharing contracts to minimize financing risk.

• Management Science and Financial Engineering
• /
• v.11 no.3
• /
• pp.95-107
• /
• 2005

As online shopping malls have emerged as a substantial shopping channel, they have used various sales promotion strategies to acquire new customers. Most of these strategies have been applied by offline malls for years. One, loss-leader pricing, is a type of promotional pricing in which stores sell well known products below their marginal cost, in order to attract customers and induce them to purchase more goods through impulse buying. This strategy is based on the expectation that customers will factor transaction costs into their purchasing decisions. However, its application to online malls fails to recognize that transaction costs are lower online, and that customers will behave differently as a result. Our study predicts that loss-leader pricing will not work online because online malls entail lower searching and moving costs than offline malls The study examines the effectiveness of loss-leader pricing with empirical data from a survey as well as log data from a Korean online shopping mall. The results show that while loss-leader pricing does attract customers to online shopping malls, it encourages cherry-picking rather than impulse purchases of regular-price goods.