• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.41-47
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• 2008

Cluster based fuzzy model tree has certain drawbacks to decrease performance of testinB data when over-fitting of training data exists. To reduce the sensitivity of performance due to over-fitting problem, we proposed a modified cluster based fuzzy model tree with node information. To construct model tree, cluster centers are calculated by fuzzy clustering method using all input and output attributes in advance. And then, linear models are constructed at internal nodes with fuzzy membership values between centers and input attributes. In the prediction step, membership values are calculated by using fuzzy distance between input attributes and all centers that passing the nodes from root to leaf nodes. Finally, data prediction is performed by the weighted average method with the linear models and fuzzy membership values. To show the effectiveness of the proposed method, we have applied our method to various dataset. Under various experiments, our proposed method shows better performance than conventional cluster based fuzzy model tree.

• Animal Bioscience
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• v.37 no.6
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• pp.1065-1076
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• 2024

Objective: This study aimed to assess the effects of dietary mulberry leaves on the growth, production performance, gut microbiota, and immunological parameters of poultry and livestock. Methods: The PubMed, Embase, and Scopus databases were systematically analyzed to identify pertinent studies up to December 2022. The effects of mulberry leaf diet was assessed using the weighted mean difference, and the 95% confidence interval was calculated using a random-effects model. Results: In total, 18 studies that sampled 2,335 poultry and livestock were selected for analysis. Mulberry leaves improved the average daily gain and reduced the feed/meat ratio in finishing pigs, and the average daily gain and average daily feed intake in chicken. In production performance, mulberry leaves lowered the half carcass weight, slaughter rate, and loin eye area in pigs, and the slaughter rate in chickens. Regarding meat quality in pigs, mulberry leaves reduced the cooked meat percentage, shear force, crude protein, and crude ash, and increased the 24 h pH and water content. In chickens, it increased the drip loss, shear force, 45 min and 24 h pH, crude protein, and crude ash. Mulberry leaves also affect the abundances of gut microbiota, including Bacteroides, Prevotella, Megamonas, Escherichia-Shigella, Butyricicoccus, unclassified Ruminococcaceae, Bifidobacterium, Lactobacillus, and Escherichia coli in poultry and livestock. Mulberry leaves at different doses were associated with changes in antioxidant capacity in chickens, and immune organ indexes in pigs. With respect to egg quality, mulberry leaves at different doses improved the shell strength, yolk color, eggshell thickness, and eggshell weight. However, moderate doses diminished the egg yolk ratio and the egg yolk moisture content. Conclusion: In general, dietary mulberry leaves improved the growth, production performance, and immunological parameters in poultry and livestock, although the effects varied at different doses.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.165-179
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• 2024

It is crucial to have a comprehensive understanding of inundation and water cycle in urban areas for mitigating flood risks and sustainable water resources management. In this study, we developed a Cellular Automata-based integrated Water cycle model (CAW). A comparative analysis with physics-based and conventional cellular automata-based models was performed in an urban watershed in Portland, USA, to evaluate the adequacy of spatiotemporal inundation simulation in the context of a high-resolution setup. A high similarity was found in the maximum inundation maps by CAW and Weighted Cellular Automata 2 Dimension (WCA2D) model presumably due to the same diffuse wave assumption, showing an average Root-Mean-Square-Error (RMSE) value of 1.3 cm and high scores of binary pattern indices (HR 0.91, FAR 0.02, CSI 0.90). Furthermore, through multiple simulation experiments estimating the effects of land cover and soil conditions on inundation and infiltration, as the impermeability rate increased by 41%, the infiltration decreased by 54% (4.16 mm/m²) while the maximum inundation depth increased by 10% (2.19 mm/m²). It was expected that high-resolution integrated inundation and water cycle analysis considering various land cover and soil conditions in urban areas would be feasible using CAW.

• The Journal of Korean Association of Computer Education
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• v.7 no.1
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• pp.79-88
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• 2004

Since computer integrated technology was introduced to the field of education, it has offered an expanding range of interactive possibilities which are remarkably powerful and helpful for the learners, especially constructing the cyber learning environments. Interactivity, the critical element in cyber learning, is categorized into three dimensions: student-to-contents, student-to-student and student-to-instructors. Six surrogate variables are introduced, and two quantitative model are developed for evaluating the degree of interactivity. The first model, which is called Data Envelopment Analysis model, is a linear programming based technique for measuring the relative performance of organizational units where the presence of multiple inputs and outputs makes comparison difficult. DEA model allows each unit to adopt a set of weight that shows it in the most favorable light in comparison to the other unit. The Second model employes the weighted average of standardized input variables for evaluation. Actual data have been collected from the Cyber IT university and these two models are applied for comparison. The analysis shows that the results from these two models are very much similar to each other, and are highly correlated to the level of class satisfaction.

• Korean Journal of Construction Engineering and Management
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• v.17 no.1
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• pp.3-9
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• 2016

This study proposes a approximate cost estimation system based on Excel with VBA using weighted CBR(Case Based Reasoning). One characteristic of this system is that it generates the sheet automatically as many as the number of similar case and new estimation when it performs a case learning and a new estimate and cell formula is automatically entered into each sheet. User can be free to compose a combination of attribute factors because they can select up to ten attribute factors. This paper presents an applicability of estimation model for estimating the soil remediation cost when it use a landfarming method. When compared to a estimation model by using average unit cost and optimum multiple regression, this model shows a better result. This study was aimed at landfarming method, but it is expected that a cost estimation model using CBR will be more likely to apply in soil remediation technologies which various remediation technologies and pollutant species exist.

• Journal of the Korea Safety Management & Science
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• v.16 no.3
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• pp.451-469
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• 2014

The purpose of this study is to implement and develop the integrated Economic Value Added (EVA) and Time-Driven Activity-Based Costing (TDABC) model to seek both improvement of Net Operating Profit Less Adjusted Tax (NOPLAT) and reduction of Capital Charge (CC). Net Operating Profit Less Adjusted Tax (NOPLAT) can be maximized by reducing the indirect cost of an unused resource capacity increased by Cost Capacity Ratio (CCR) of TDABC. On the other hand, Capital Charge (CC) can be minimized by improving the efficiency of Invested Capital (IC) considered by Weighted Average Cost of Capital (WACC) of EVA. In addition, the integrated system of TDABC using Balance Scorecard (BSC) and EVA is developed by linking between the lagging indicators and the three leading indicators. The three leading indicators include customer, internal process and growth and learning perspectives whereas the lagging indicator includes NOPLAT and CC in terms of financial perspective. When the Critical Success Factor (CSF) of BSC is cascading as a cause and an effect relationship, time driver of TDABC and capital driver of EVA can be used efficiently as Key Performance Indicator (KPI) of BSC. For a better understanding of the proposed EVA/TDABC model and BSC/EVA/TDABC model, numerical examples are derived from this paper. From the proposed model, the time driver of TDABC and the capital driver of EVA are known to lessen indirect cost from comprehensive income statement when increasing the efficiency of operating IC from the statement of financial position with unified KPI cascading of aligned BSC CSFs.

• Animal Bioscience
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• v.34 no.9
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• pp.1451-1459
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• 2021

Objective: The objectives of the study were to evaluate reproductive performance and selection response through genetic trend of community-based breeding programs (CBBPs) of Bonga sheep. Methods: Reproduction traits data were collected between 2012 and 2018 from Bonga sheep CBBPs. Phenotypic performance was analyzed using the general linear model procedures of Statistical Analysis System. Genetic parameters were estimated by univariate animal model for age at first lambing (AFL) and repeatability models for lambing interval (LI), litter size (LS), and annual reproductive rate (ARR) traits using restricted maximum likelihood method of WOMBAT. For correlations bivariate animal model was used. Best model was chosen based on likelihood ratio test. The genetic trends were estimated by the weighted regression of the average breeding value of the animals on the year of birth/lambing. Results: The overall least squares mean±standard error of AFL, LI, LS, and ARR were 375±12.5, 284±9.9, 1.45±0.010, and 2.31±0.050, respectively. Direct heritability estimates for AFL, LI, LS, and ARR were 0.07±0.190, 0.06±0.120, 0.18±0.070, and 0.25±0.203, respectively. The low heritability for both AFL and LI showed that these traits respond little to selection programs but rather highly depend on animal management options. The annual genetic gains were -0.0281 days, -0.016 days, -0.0002 lambs and 0.0003 lambs for AFL, LI, LS, and ARR, respectively. Conclusion: Implications of the result to future improvement programs were improving management of animals, conservation of prolific flocks and out scaling the CBBP to get better results.

• Journal of Korea Water Resources Association
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• v.43 no.12
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• pp.1083-1091
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• 2010

Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. However, widely used estimation schemes fail to describe the realistic variability of daily precipitation field. We compare and contrast the performance of statistical methods for the spatial estimation of precipitation in two hydrologically different basins, and propose a two-step process for effective daily precipitation estimation. The methods assessed are: (1) Inverse Distance Weighted Average (IDW); (2) Multiple Linear Regression (MLR); (3) Climatological MLR; and (4) Locally Weighted Polynomial Regression (LWP). In the suggested simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before applying IDW scheme (one of the local scheme) to estimate the amount of precipitation separately on wet days. As the results, the suggested method shows the better performance of daily rainfall interpolation which has spatial differences compared with conventional methods. And this technique can be used for streamflow forecasting and downscaling of atmospheric circulation model effectively.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.40 no.1
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• pp.29-36
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• 2004

This study deals with an analysis on the sinking resistance for the model purse seine, in the case of different netting material and sinkers. The experiment was carried out using rune simplified model seines of knotless nettings. Dimension of model seines 420cm for corkline and 85cm for seine depth, three groups of models rigged 25, 45 and 60g with the same weighted sinkers in water were used. These were named PP-25, PA-25, PES-25, PP-45, PA-45, PES-45, PP-60, PA-60 and PES-60 seine. The densitie($\rho$) of netting materials were 0.91g/cm$cm^3$, 1.14g/cm$cm^3$ and 1.38g/cm$m^3$. Experiments carried out in the observation channel in a flume tank under still water conditions. Sinking motion was recorded by the one set of TV-camera for VTR, and reading coordinate carried out by the video digitization system. Differential equations were derived from the conservation of momenta of the model purse seines and used to determine the sinking speeds of the depths of leadline and the other portions of the seines. An analysis carried out by simultaneous differential equations for numerical method by sub-routine Runge-Kutta-Gill The results obtained were as follows : 1. Average sinking speed of leadline for the model seines rigged 60g with the same weighted sinkers in water was fastest for 12.2cm/sec of PES seine, followed by 11.4cm/sec of PA and 10.7cm/sec of PP seines. 2. The coefficient of resistance for netting of seine was estimated to be $K_D=0.09(\frac{\rho}{\rho_w})^4$ 3. The coefficient of resistance for netting bundle of seine was estimated to be $C_R=0.91(\frac{\rho}{\rho_w})$ 4. In all seines, the calculated depths of leadline closely agreed with the measured ones, each 25g, 45g, 60g of weighted sinkers were put into formulas meas.=1.04cal., meas.=0.99cal. and meas.=0.98 cal.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.2
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• pp.92-98
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• 2017

Generally, image contains geometrical and radiometric errors. Census transform can solve the stereo mismatching problem caused by the radiometric distortion. Since the general census transform compares center of window pixel value with neighbor pixel value, it is hard to obtain an accurate matching result when the difference of pixel value is not large. To solve that problem, we propose a census transform method that applies different 4-step weight for each pixel value difference by applying an assistance window inside the window kernel. If the current pixel value is larger than the average of assistance window pixel value, a high weight value is given. Otherwise, a low weight value is assigned to perform a differential census transform. After generating an initial disparity map using a weighted census transform and input images, the gradient information is additionally used to model a cost function for generating a final disparity map. In order to find an optimal cost value, we use guided filtering. Since the filtering is performed using the input image and the disparity image, the object boundary region can be preserved. From the experimental results, we confirm that the performance of the proposed stereo matching method is improved compare to the conventional method.