• Journal of the Korean GEO-environmental Society
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• v.4 no.4
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• pp.61-71
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• 2003

On the soft soil consisted of silty clay, the compulsion replacement method is useful for revetment and its safety is very much affected by compulsion replacement depth. Usual method calculating the compulsion replacement depth on silty clay is considered the bearing capacity of soft soil with undrained shear strength increase from ground surface and weight of revetment. But according to soil deposit, there are some cases of soft soil with inter sand layer or clayed silt, which affect the compulsion replacement depth. In this paper, the compulsion replacement depth on soft soil with inter sand layer is analyzed by layered weighted average bearing capacity considering influence effect of Perloff et al.(1967) and compared with numerical method(FLAC). In the result, the calculated depth from numerical method is nearest to layered weighted average bearing capacity in case that contact width under revetment is $0.2B_o$(soft soil with inter sand layer), $0.5B_o$(only soft soil) and the effect of contact width under revetment is less than undrained shear strength, thickness and location of inter sand layer. Also the compulsion replacement depth is as much as the inter sand thickness($d_2/B_o$) is thinner, the inter sand layer location($d_1/B_o$) is farther, and undrained shear strength is less.

• Korean Journal of Materials Research
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• v.33 no.2
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• pp.54-62
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• 2023

The most comprehensive and particularly reliable method for non-destructively measuring the residual stress of the surface layer of metals is the sin²ψ method. When X-rays were used the relationship of ε_φψ-sin²ψ measured on the surface layer of the processing metal did not show linearity when the sin²ψ method was used. In this case, since the effective penetration depth changes according to the changing direction of the incident X-ray, σ_φ becomes a sin²ψ function. Since σ_φ cannot be used as a constant, the relationship in ε_φψ-sin²ψ cannot be linear. Therefore, in this paper, the orthogonal function method according to Warren's diffraction theory and the basic profile of normal distribution were synthesized, and the X-ray diffraction profile was calculated and reviewed when there was a linear strain (stress) gradient on the surface. When there is a strain gradient, the X-ray diffraction profile becomes asymmetric, and as a result, the peak position, the position of half-maximum, and the centroid position show different values. The difference between the peak position and the centroid position appeared more clearly as the strain (stress) gradient became larger, and the basic profile width was smaller. The weighted average strain enables stress analysis when there is a strain (stress) gradient, based on the strain value corresponding to the centroid position of the diffracted X-rays. At the 1/5 I_max max height of X-ray diffraction, the position where the diffracted X-ray is divided into two by drawing a straight line parallel to the background, corresponds approximately to the centroid position.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.3
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• pp.145-150
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• 2014

This paper presents an effective vision based method for LED traffic light detection at the daytime. First, the proposed method calculates horizontal coordinates to set region of interest (ROI) on input sequence images. Second, the proposed uses color segmentation method to extract region of green and red traffic light. Next, to classify traffic light and another noise, shape filter and haar-like feature value are used. Finally, temporal delay filter with weight is applied to remove blinking effect of LED traffic light, and state and weight of traffic light detection are used to classify types of traffic light. For simulations, the proposed method is implemented through Intel Core CPU with 2.80 GHz and 4 GB RAM, and tested on the urban and rural road video. Average detection rate of traffic light is 94.50 % and average recognition rate of traffic type is 90.24 %. Average computing time of the proposed method is 11 ms.

• Journal of Forest and Environmental Science
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• v.28 no.3
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• pp.170-178
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• 2012

Dipterocarps or Dipterocarpaceae is a commercially important timber producing and dominant keystone tree family in the rain forests of Borneo. Borneo's landscape is changing at an unprecedented rate in recent years which affects this important biodiversity. This paper attempts to model the natural occurrence (distribution including those areas with natural forests before being converted to other land uses as opposed to current distribution) of dipterocarp species in Sarawak which is important for forest biodiversity conservation and management. Local modeling method of Inverse Distance Weighting was compared with commonly used statistical method (Binary Logistic Regression) to build the best natural distribution models for three genera (12 species) of dipterocarps. Database of species occurrence data and pseudoabsence data were constructed and divided into two halves for model building and validation. For logistic regression modeling, climatic, topographical and edaphic parameters were used. Proxy variables were used to represent the parameters which were highly (p>0.75) correlated to avoid over-fitting. The results show that Inverse Distance Weighting produced the best and consistent prediction with an average accuracy of over 80%. This study demonstrates that local interpolation method can be used for the modeling of natural distribution of dipterocarp species. The Inverse Distance Weighted was proven a better method and the possible reasons are discussed.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.4
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• pp.247-252
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• 2013

Korea gas corporation (KOGAS) is responsible for the whole sale of natural gas in the domestic market. It is important to forecast the daily demand of city gas for supply and demand control, and delivery management. Since there is the autoregressive characteristic in the daily gas demand, we introduce a modified autoregressive model as the first step. The daily gas demand also has a close connection with the outdoor temperature. Accordingly, our second proposed model is a temperature-based model. Those two models, however, do not meet the requirement for forecasting performances. To produce acceptable forecasting performances, we develop a weighted average model which compounds the autoregressive model and the temperature model. To examine our proposed methods, the forecasting results are provided. We confirm that our method can forecast the daily city gas demand accurately with reasonable performances.

• Journal of the Korea Safety Management & Science
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• v.3 no.4
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• pp.135-144
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• 2001

The capital cost of the company is one that must be paid to the money owner as the price by using the money. The capital cost according to the source of money supply can be estimated by the expected profit rate undertaken by the use of the capital. But in the area of pre-existent economic evaluation, the evaluation of the company investment has been treated by the profit rate of the capital after considering the repayment conditions of the other's money or the interest. Thus in this study, in case the company makes an investment on various kinds of the capital at the same time, not make use of the capital as a one source, the economic evaluation of an investment should be handled by taking the weighted average cost of capital into consideration in proportion to the constitution of the capital cost by the sources of money supply, Especially, as the cost of the private money is very much connected with the profit rate through the stock market, the Capital Asset Pricing Model (CAPM) will be applied. This kind of economic evaluation method can be said to have much to do with the Economic Value Added : EVA) as well as to be highly thought as a standard to estimate the company' value recently To certify the usefulness of this approach, the case study of the output of the capital cost will be made for the purse of the economic evaluation of the alternative investment by using the financial statements of a motor company H.

• Journal of Information Technology Applications and Management
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• v.29 no.3
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• pp.43-55
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• 2022

In this study, with the goal of developing a deep learning-based product recommendation model for effective matching of influencers and products, a deep learning model with a collaborative filtering model combined with generalized matrix decomposition(GMF), a collaborative filtering model based on multi-layer perceptron (MLP), and neural collaborative filtering and generalized matrix Factorization (NeuMF), a hybrid model combining GMP and MLP was developed and tested. In particular, we utilize one-class problem free boosting (OCF-B) method to solve the one-class problem that occurs when training is performed only on positive cases using implicit feedback in the deep learning-based collaborative filtering recommendation model. In relation to model selection based on overall experimental results, the MLP model showed highest performance with weighted average precision, weighted average recall, and f1 score were 0.85 in the model (n=3,000, term=15). This study is meaningful in practice as it attempted to commercialize a deep learning-based recommendation system where influencer's promotion data is being accumulated, pactical personalized recommendation service is not yet commercially applied yet.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1171-1180
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• 2010

It is well known that the asymptotic convergence rates of nonparametric regression estimator gets worse as the dimension of covariates gets larger. One possible way to overcome this problem is reducing the dimension of covariates by using single index models. Two coefficient estimation methods in single index models are introduced. One is semiparametric least square estimation method, which tries to find approximate solution by using iterative computation. The other one is weighted average derivative estimation method, which is non-iterative method. Both of these methods offer the parametric convergence rate to normal distribution. However, practical comparison of these two methods has not been done yet. In this article, we compare these methods by examining the variances of estimators in various models.

• Journal of Advanced Marine Engineering and Technology
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• v.25 no.3
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• pp.623-630
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• 2001

The conventional control techniques based a mathematical model are not well suited for dealing with ill-defined and uncertain system like a linear quadratic control. Recently, fuzzy control has been successfully applied to a wide variety of practical problems such as robot, water purification, automatic train operation system etc. In this paper, a design technique of robust Fuzzy-LQ controller for each subsystem is designed. Secondly , all the subsystem controllers are combined by fuzzy weighted averaging method. Finally the effectiveness of the proposed controller is verified through a series of computer simulations for an inverted pole system.

• Journal of Communications and Networks
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• v.8 no.1
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• pp.28-37
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• 2006

State-dependent call admission control (SDCAC) is proposed to make efficient use of scarce wireless resource in a hierarchical wireless network with heterogeneous traffic. With SDCAC, new calls are accepted according to an acceptance probability taking account of not only cell dwell time but also call holding time and system state (i.e., occupied bandwidth). An analytical method is developed to calculate performance measures of interest, e.g., new call blocking probability, forced termination probability, over. all weighted blocking probability. Numerical results with not only stationary but nonstationary traffic loads are presented to show the robustness of SDCAC. It is shown that SDCAC performs much better than the other considered schemes under nonstationary traffic load.