• Journal of the Korean Society for Precision Engineering
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• v.30 no.3
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• pp.308-316
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• 2013

This paper proposes an observation model for a particle filter-based localization using a sonar grid map. The proposed model estimates a predicted observation by considering the properties of a sonar sensor which has a large angular uncertainty. The proposed model searches a grid which has the highest probability to reflect a sonar beam using the following procedures; (1) the reliable area of a single sonar data is determined using the footprint association model; (2) the detection probability of each grid cell in a sonar beam coverage in estimated. The proposed model was applied to the particle filter based localization, and was verified by experiments in indoor environments.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.8
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• pp.1021-1027
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• 2013

In this study, a prognostic technique for cavitation erosion that is applicable to centrifugal pumps is devised. To estimate the erosion states of pumps, damage rates are calculated based on cavitation noise measurements. The accumulated damage is predicted by using Miner's rule and the estimated damage undergone when coping with particular operating conditions. The remaining useful life (RUL) of the pump impellers is estimated according to the accumulated damage prediction and based on the assumption of future operating conditions. A Monte Carlo simulation is applied to obtain a prognostic uncertainty. The comparison of the prediction and the test results demonstrates that the developed method can be applied to predict cavitation erosion states and RUL estimates.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.2
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• pp.295-302
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• 2011

Almost half of New Zealand's greenhouse gas emissions arise from agriculture and enteric methane ($CH_4 $) emissions arising from ruminant animals constitute 30% of total $CO_2$-e emissions. Enteric $CH_4$ emissions have increased by 9% since 1990. Extensive research has been undertaken to develop reliable methods for measuring enteric $CH_4$ emissions. New Zealand studies using the SF6 tracer technique suggest that on average this technique yields similar values to the 'gold' standard of calorimetry, but with a larger variance. National inventory estimates based on results obtained using the $SF_6$ technique will therefore overestimate the uncertainty. Mitigating emissions can be achieved by changing feed type but there are practical and cost barriers to the use of alternative feeds. Forages containing condensed tannins do reduce emissions but are agronomically inferior to the forages currently used. Rumen additives have shown some success in-vitro but results from in-vivo trials with both monensin and fumaric acid have been disappointing. The development of methods for directly manipulating rumen microorganisms are at an early stage and work to develop vaccines that can inhibit methanogenesis has yielded mixed results. The successful identification of sheep with contrasting $CH_4$ yields raises the possibility that, in the long term, a breeding approach to $CH_4$ mitigation is feasible.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.2
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• pp.117-127
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• 1998

Power systems have uncertain dynamics due to a variety of effects such as lightning, severe storms and equipment failures. The variation of the effective reactance of a transmission line due to a fault is an example of uncertainty in power system dynamics. Hence, a robust controller to cope with these uncertainties is needed. Recently, fuzzy controllers are becoming quite popular for robust control due to its potential of dealing with uncertain systems. Thus in this paper we design an adaptive fuzzy controller based on an input-output linearization approach for the transient stabilization and voltage regulation of a power system under a sudden fault. Also this paper proposes a fuzzy system that estimates the upper bound of uncertain term in the system dynamics to guarantee the Lyapunov stability. Simulation results show that good performance is achieved by the proposed controller.

• Journal of the Korean Society for Railway
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• v.12 no.1
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• pp.135-143
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• 2009

The majority of development projects fail to meet their target schedule and cost, with the overrun typically between 40 and 200 percent. These overruns happen because the planners underestimate the work or do not consider the need to rework at project planning. Representative schedule planning/management techniques such as Gantt Chart, PERT/CPM etc. that are used in domestic project planning are unable to reflect rework. This paper proposes a method to consider rework to provide more realistic estimates at schedule planning. Additionally, to prevent the underestimation of the work this paper proposes a simulation method that calculates a probabilistic estimated schedule and the associated variance based on the random variable modeling of individual task completion dates.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.1
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• pp.43-48
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• 2012

This paper proposes a practical linear recursive robust motion deblurring filter using the inertial sensor measurements for strapdown image seekers. The angular rate information obtained from the gyro mounted on the missile is used to define the PSF(point spread function). Since the gyro output contains a unknown but bounded bias error. the motion blur image model can be expressed as the linear uncertain system. In consequence, the motion deblurring problem can be cast into the robust Kalman filtering which provides reliable state estimates even in the presence of the parametric uncertainty due to the gyro bias. Through the computer simulations using the actual IR scenes, it is verified that the proposed algorithm guarantees the robust motion deblurring performance.

• The Korean Journal of Applied Statistics
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• v.27 no.4
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• pp.655-665
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• 2014

An adequate understanding and response to natural hazards such as heat wave, heavy rainfall and severe drought is required. We apply extreme value theory to analyze these abnormal weather phenomena. It is common for extremes in climatic data to be nonstationary in space and time. In this paper, we analyze summer rainfall data in South Korea using exceedance values over thresholds estimated by quantile regression with location information and time as covariates. We group weather stations in South Korea into 5 clusters and t extreme value models to threshold exceedances for each cluster under the assumption of independence in space and time as well as estimates of uncertainty for spatial dependence as proposed in Northrop and Jonathan (2011).

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.129-141
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• 2023

Crop models have been used to predict yield under diverse environmental and cultivation conditions, which can be used to support decisions on the management of forage crop. Cultivar parameters are one of required inputs to crop models in order to represent genetic properties for a given forage cultivar. The objectives of this study were to compare calibration and ensemble approaches in order to minimize the uncertainty of crop yield estimates using the SIMPLE crop model. Cultivar parameters were calibrated using Log-likelihood (LL) and Generic Composite Similarity Measure (GCSM) as an objective function for Metropolis-Hastings (MH) algorithm. In total, 20 sets of cultivar parameters were generated for each method. Two types of ensemble approach. First type of ensemble approach was the average of model outputs (E_em), using individual parameters. The second ensemble approach was model output (E_pm) of cultivar parameter obtained by averaging given 20 sets of parameters. Comparison was done for each cultivar and for each error calculation methods. 'Jowoo' and 'Yeongwoo', which are forage rice cultivars used in Korea, were subject to the parameter calibration. Yield data were obtained from experiment fields at Suwon, Jeonju, Naju and I ksan. Data for 2013, 2014 and 2016 were used for parameter calibration. For validation, yield data reported from 2016 to 2018 at Suwon was used. Initial calibration indicated that genetic coefficients obtained by LL were distributed in a narrower range than coefficients obtained by GCSM. A two-sample t-test was performed to compare between different methods of ensemble approaches and no significant difference was found between them. Uncertainty of GCSM can be neutralized by adjusting the acceptance probability. The other ensemble method (E_pm) indicates that the uncertainty can be reduced with less computation using ensemble approach.

• Korean Journal of Construction Engineering and Management
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• v.21 no.6
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• pp.113-124
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• 2020

Social movements to improve the performance of buildings through remodeling of aging apartment houses are being captured. To this end, the remodeling construction cost analysis, structural analysis, and political institutional review have been conducted to suggest ways to activate the remodeling. However, although the method of analyzing construction cost for remodeling apartment houses is currently being proposed for research purposes, there are limitations in practical application possibilities. Specifically, In order to be used practically, it is applicable to cases that have already been completed or in progress, but cases that will occur in the future are also used for construction cost analysis, so the sustainability of the analysis method is lacking. For the purpose of this, we would like to suggest an automated estimating method. For the sustainability of construction cost estimates, Deep-Learning was introduced in the estimating procedure. Specifically, a method for automatically finding the relationship between design elements, work types, and cost increase factors that can occur in apartment remodeling was presented. In addition, Monte Carlo Simulation was included in the estimation procedure to compensate for the lack of uncertainty, which is the inherent limitation of the Deep Learning-based estimation. In order to present higher accuracy as cases are accumulated, a method of calculating higher accuracy by comparing the estimate result with the existing accumulated data was also suggested. In order to validate the sustainability of the automated estimates proposed in this study, 13 cases of learning procedures and an additional 2 cases of cumulative procedures were performed. As a result, a new construction cost estimating procedure was automatically presented that reflects the characteristics of the two additional projects. In this study, the method of estimate estimate was used using 15 cases, If the cases are accumulated and reflected, the effect of this study is expected to increase.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.1
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• pp.35-47
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• 2022

Expansion of potato production areas can improve the food security in North Korea because the given crop has less requirements for agricultural materials and facilities. The Global Agro-Ecological Zones (GAEZ) model, which was developed to evaluate climate suitability under different cultivation conditions, was used to identify potential areas for the potato production. The spatial estimates of crop suitability under low and high input management conditions were downloaded from the GAEZ data portal. The values of suitability were obtained at the potato occurrence sites retrieved from the Global Biodiversity Information Facility (GBIF) database. The suitable areas for the potato production were identified using a threshold value derived from the suitability estimates at the occurrence sites. It was found that 90% of the occurrence sites had the suitability index value >3,333, which was set to be the threshold value. The suitable areas in North Korea were summarized by province and county. Rice cultivation areas were excluded from the analysis. The reported relative acreage of potato production was better represented by the suitable areas under the low input management options than the high input conditions. The suitable areas also had a similar distribution to the reported acreage of potato production by county. These results indicated that the GAEZ model would be useful to identify the candidate production areas, which would facilitate the increases in potato production especially under future climate conditions. Furthermore, monthly maps of crop suitability can be used to design cropping systems that would improve crop production under the limited use of agricultural materials and facilities.