• Asian-Australasian Journal of Animal Sciences
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• v.16 no.12
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• pp.1705-1710
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• 2003

A small body size of Brown Tsaiya laying duck is desirable to reduce maintenance requirements, so the body weight at 40 weeks of age (BW40) has to be maintained at its current level. Egg weight has to be maintained at around 65 g to meet market requirements. Eggshell strength at 40 weeks of age (ES40) must to be increased in order to maintain a low incidence of broken eggs. Thus, number of eggs laid up to 52 weeks of age (EN52) has to be increased without negative correlated response on ES40. A new linear genetic selection index was used: $I_g=a_0{\times}GEW40\;(g)+a_1{\times}GBW40\;(g)+a_2{\times}GES40\;(kg/cm^2)+a_3{\times}GEN52\;(eggs)$ where GEW40, GBW40, GES40 and GEN52 were the multitrait best linear unbiased prediction (MT-BLUP) animal model predictors of the breeding values respectively of egg weight and body weight at 40 weeks of age (EW40, BW40), ES40 and EN52. The coefficients $a_0$, $a_1$, $a_2$ and $a_3$ were calculated with constraints of 0.0 g, 0.0 g and $0.013kg/cm^2$ for expected genetic gains in EW40, BW40 and ES40 respectively and maximum gain in EN52. Since 1997, the drakes and the ducks were selected according to their own indexes, with this new genetic selection index. From G0 to G4, the average per generation predicted genetic responses in female duck were +0.05 g for EW40, +0.92 g for BW40, $+0.035kg/cm^2$ for ES40 and +2.13 eggs for EN52. Which represented respectively 0.07%, 0.06%, 0.67% and 1.0% of the means of the EW40, BW40, ES40 and EN52. For ES40 and EN52, it represented also respectively 16.1% and 21.6% of the additive genetic standard deviation of these traits. Thevse results indicated that selection of laying Brown Tsaiya by a restricted genetic selection index and with MT-BLUP animal model could be an efficient tool for improving the efficiency of egg production, increasing egg shell strength and egg number while holding egg weight and body weight constants.

• Journal of Internet Computing and Services
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• v.14 no.4
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• pp.63-72
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• 2013

Business Process Intelligence (BPI) is one of the emerging technologies in the knowledge discovery and analysis area. BPI deals with a series of techniques from discovering knowledge to analyzing the discovered knowledge in BPM-supported organizations. By means of the BPI technology, we are able to provide the full functionality of control, monitoring, prediction, and optimization of process-supported organizational knowledge. Particularly, we focus on the focal organizational knowledge, which is so-called the BPM activity-performer affiliation networking knowledge that represents the affiliated relationships between performers and activities in enacting a specific business process model. That is, in this paper we devise a statistical analysis method to be applied to the BPM activity-performer affiliation networking knowledge, and dubbed it the activity-performer correspondence analysis method. The devised method consists of a series of pipelined phases from the generation of a bipartite matrix to the visualization of the analysis result, and through the method we are eventually able to analyze the degree of correspondences between a group of performers and a group of activities involved in a business process model or a package of business process models. Conclusively, we strongly expect the effectiveness and efficiency of the human resources allotments, and the improvement of the correlational degree between business activities and performers, in planning and designing business process models and packages for the BPM-supported organization, through the activity-performer correspondence analysis method.

• Information Systems Review
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• v.16 no.3
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• pp.113-134
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• 2014

Since a movie is an experience goods, purchase can be decided upon preliminary information and evaluation. There are ongoing researches on what impact online reviews might have on movie revenues. Whereas research in the past was focused on the effect of online reviews. The influence of online reviews appears to be significant in products like a movie because it is difficult to evaluate the feature prior to "consuming" the product. Since an online review is regarded to be objective, consumers find it more trustworthy. Contrary to prior research focused on movie review ratings and volume, we focus moves on movie features related specific reviews. This research proposes a predictive model for movie revenue generation. We decided 15 criteria to classify movie features collected from online reviews through the online review mining and made up feature keyword list each criterion. In addition, we performed data preprocessing and dimensional reduction for data mining through factor analysis. We suggest the movie revenue predictive model is tested using discriminant analysis. Following the discriminant analysis, we found that online review factors can be used to predict movie popularity and revenue stream. We also expect using this predictive model, marketers and strategic decision makers can allocate their resources in more parsimonious fashion.

• Journal of Broadcast Engineering
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• v.18 no.2
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• pp.178-184
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• 2013

In this paper, we propose an efficient parallelization technique of PU-level motion estimation (ME) in the next generation video coding standard, high efficiency video coding (HEVC) to reduce the time complexity of video encoding. It is difficult to encode video in real-time because ME has significant complexity (i.e., 80 percent at the encoder). In order to solve this problem, various techniques have been studied, and among them is the parallelization, which is carefully concerned in algorithm-level ME design. In this regard, merge estimation method using merge estimation region (MER) that enables ME to be designed in parallel has been proposed; but, parallel ME based on MER has still unconsidered problems to be implemented ideally in HEVC test model (HM). Therefore, we propose two strategies to implement stable parallel ME using MER in HM. Through experimental results, the excellence of our proposed methods is shown; the encoding time using the proposed method is reduced by 25.64 percent on average of that of HM which uses sequential ME.

• Journal of Korean Society of Disaster and Security
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• v.13 no.2
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• pp.39-51
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• 2020

Recently, flood damage has been increasing in Korea due to frequent local torrential rains caused by abnormal weather conditions. According to the calculation of the recurrence period of torrential rain that occurred in North Chungcheong Province on July 16, 2017, it was estimated that the rainfall frequency in the upper are of Goessan Dam was around 1,524 years, and the highest level of Goesan Dam rose to EL.137.60 meters, leaving only 5 cm of margin until the height of the dam floor (EL.137.65 meters). The Goesan Dam, which operated for 62 years since 1957, needs to be prepared to cope with the increase of floodgate volume in the basin, the development of a single purpose dam for power generation only, and there are no measurement facilities for flood control, so efficient operation methods are needed to secure the safety of residents in upper and lower regions. In this study, a method of dam operation was proposed by constructing a rain matrix for quick decision making in flood prediction, calculating the highest level of dam for each condition in advance, and preparing a survey table, and quickly finding the level corresponding to the conditions in case of a situation.

• Journal of Korean Society of Transportation
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• v.17 no.1
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• pp.173-185
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• 1999

The purpose of this study is to develope a forecasting model to implement short-term Congestion Management Program (CMP) based on TDM strategies in Seoul. The CMP is composed of three elements: 1) setting a goal of short-term traffic management. 2) developing a model to forecast the impacts of TDM alternatives, and 3) finding TDM measures to achieve the goal To Predict the impacts of TDM alternatives, a model called SECOMM (SEoul COngestion Management Model) is developed. The model assumes that trip generation and distribution are not changing in a short term, and that only mode split and traffic assignment are affected by TDM. The model includes the parameter values calibrated by a discrete mode choice model, and roadway and transit networks with 1,020 zones. As a TDM measure implement, it affects mode choice behavior first and then the speeds of roadway network. The chanced speed again affects the mode choice behavior and the roadway speeds. These steps continue until the network is equilibrated. The study recommends that CMP be introduced in Seoul, and that road way conditions be monitored regularly to secure the prediction accuracy of SECOMM. Also, TDM should be the major Policy tools in removing short-term congestion problems in a big city.

• Journal of Korean Society on Water Environment
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• v.28 no.3
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• pp.375-383
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• 2012

Soil erosion has been emphasized as serious environmental problem affecting water quality in the receiving waterbodies. Recently, Best Management Practices (BMPs) have been applied at a field to reduce soil erosion and its effectiveness in soil erosion reduction has been monitored with various methods. Although monitoring at fields/watershed outlets would be accurate way for these ends, it is not possible at some fields/watersheds due to various limitations in direct monitoring. Thus modeling has been suggested as an alternative way to evaluate effects of the BMPs. Most models, which have been used in evaluating hydrology and water quality at a watershed, could not reflect rainfall intensity in runoff generation and soil erosion processes. In addition, source codes of these models are not always public for modification/enhancement. Thus, runoff-sediment evaluation system using hourly rainfall data and vegetated filter strip (VFS) evaluation module at field level were developed using open source MapWindow GIS component in this study. This evaluation system was applied to Bangdongri, Chuncheonsi to evaluate its prediction ability and VFS module in this study. The NSE and $R^2$ values for runoff estimation were 0.86 and 0.91, respectively, and measured and simulated sediment yield were 15.2 kg and 16.5 kg indicating this system, developed in this study, can be used to simulate runoff and sediment yield with acceptable accuracies. Nine VFS scenarios were evaluated for effectiveness of soil erosion reduction. Reduction efficiency of the VFS was high when sediment inflow was small. As shown in this study, this evaluation system can be used for evaluation BMPs with local rainfall intensity and variations considered with ease-of-use GIS interface.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.7
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• pp.967-972
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• 2017

Objective: Two experiments were conducted to determine the effects of forage-to-concentrate (F:C) ratio on the nutrient digestibility and enteric methane ($CH_4$) emission in growing goats and Sika deer. Methods: Three male growing goats (body weight $[BW]=19.0{\pm}0.7kg$) and three male growing deer ($BW=19.3{\pm}1.2kg$) were respectively allotted to a $3{\times}3$ Latin square design with an adaptation period of 7 d and a data collection period of 3 d. Respiration-metabolism chambers were used for measuring the enteric $CH_4$ emission. Treatments of low (25:75), moderate (50:50), and high (73:27) F:C ratios were given to both goats and Sika deer. Results: Dry matter (DM) and organic matter (OM) digestibility decreased linearly with increasing F:C ratio in both goats and Sika deer. In both goats and Sika deer, the $CH_4$ emissions expressed as g/d, g/kg $BW^{0.75}$, % of gross energy intake, g/kg DM intake (DMI), and g/kg OM intake (OMI) decreased linearly as the F:C ratio increased, however, the $CH_4$ emissions expressed as g/kg digested DMI and OMI were not affected by the F:C ratio. Eight equations were derived for predicting the enteric $CH_4$ emission from goats and Sika deer. For goat, equation 1 was found to be of the highest accuracy: $CH_4(g/d)=3.36+4.71{\times}DMI(kg/d)-0.0036{\times}neutral$ detergent fiber concentrate (NDFC,g/kg)+$0.01563{\times}dry$ matter digestibility (DMD,g/kg)-$0.0108{\times}neutral$ detergent fiber digestibility (NDFD, g/kg). For Sika deer, equation 5 was found to be of the highest accuracy: $CH_4(g/d)=66.3+27.7{\times}DMI(kg/d)-5.91{\times}NDFC(g/kg)-7.11{\times}DMD(g/kg)+0.0809{\times}NDFD(g/kg)$. Conclusion: Digested nutrient intake could be considered when determining the $CH_4$ generation factor in goats and Sika deer. Finally, the enteric $CH_4$ prediction model for goats and Sika deer were estimated.

• Korean Journal of Food Science and Technology
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• v.37 no.6
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• pp.1012-1017
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• 2005

Predictive growth model of putrefactive bacteria of surimi-based imitation crab in the modified surimi-based imitation crab (MIC) broth was investigated. The growth curves of putrefactive bacteria were obtained by measuring cell number in MIC broth under different conditions (Initial cell number, $1.0{\times}10^2,\;1.0{\times}10^3$ and $1.0{\times}10^4$ colony forming unit (CFU)/mL; temperature, $15^{\circ}C,\;20^{\circ}C\;and\;25^{\circ}C$) and applied them to Gompertz model. The microbial growth indicators, maximum specific growth rate constant (k), lag time (LT) and generation time (GT), were calculated from Gompertz model. Maximum specific growth rate (k) of putrefactive bacteria was become fast with rising temperature and fastest at $25^{\circ}C$. LT and GT were become short with rising temperature and shortest at $25^{\circ}C$. There were not significant differences in k, LT and GT by initial cell number (p>0.05). Polynomial model, $k=-0.2160+0.0241T-0.0199A_0$, and square root model, $\sqrt{k}=0.02669$ (T-3.5689), were developed to express the combination effects of temperature and initial cell number, The relative coefficient of experimental k and predicted k of polynomial model was 0.87 from response surface model. The relative coefficient of experimental k and predicted k of square root model was 0.88. From above results, we found that the growth of putrefactive bacteria was mainly affected by temperature and the square root model was more credible than the polynomial model for the prediction of the growth of putrefactive bacteria.

• Journal of Environmental Science International
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• v.15 no.8
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• pp.775-784
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• 2006

In this study, CN value was estimated by using detailed soil map and land cover characteristic against upper basin of Kumho watermark located on the upper basin of Kumho river and the hydrologic morphological characteristic factors were extracted from the basin by using the DEM document. Also the runoff analysis was conducted by the WMS model in order to study how the assumed CN value affects the runoff characteristic. First of all, as a result of studying the soil type in this study area, mostly D type soil was Identified by the application of the 1987 classification criteria. However, by that in 1995, B type soil and C type soil were distributed more widely in that area. When CN value was classified by the 1995 classification criteria, it was estimated lower than in 1987, as a result of comparing the estimated CNs by those standars. Also it was assumed that CN value was underestimated when the plan for Geum-ho river maintenance was drawn up. As a result of the analysis of runoff characteristic, the pattern of generation of the classification criteria of soil groups appeared to be similar, but in the case of the application of the classification criteria in 1995, the peak rate of runoff was found to be smaller on the whole than in the case of the application of the classification criteria in 1987. Also when the statistical data such as the prediction errors, the mean squared errors, the coefficient of determination and other data emerging from the analysis, was looked over in total, it seemed appropriate to apply the 1995 classification criteria when hydrological soil classification group was applied. As the result of this study, however, the difference of the result of the statistical dat was somewhat small. In future study, it is necessary to follow up evidence about soil application On many more watersheds and in heavy rain.