• Asian-Australasian Journal of Animal Sciences
• /
• 제27권7호
• /
• pp.1013-1018
• /
• 2014

In this study, we developed kinetic models to predict the growth of pathogenic Escherichia coli on cheeses during storage at constant and changing temperatures. A five-strain mixture of pathogenic E. coli was inoculated onto natural cheeses (Brie and Camembert) and processed cheeses (sliced Mozzarella and sliced Cheddar) at 3 to 4 log CFU/g. The inoculated cheeses were stored at 4, 10, 15, 25, and $30^{\circ}C$ for 1 to 320 h, with a different storage time being used for each temperature. Total bacteria and E. coli cells were enumerated on tryptic soy agar and MacConkey sorbitol agar, respectively. E. coli growth data were fitted to the Baranyi model to calculate the maximum specific growth rate (${\mu}_{max}$; log CFU/g/h), lag phase duration (LPD; h), lower asymptote (log CFU/g), and upper asymptote (log CFU/g). The kinetic parameters were then analyzed as a function of storage temperature, using the square root model, polynomial equation, and linear equation. A dynamic model was also developed for varying temperature. The model performance was evaluated against observed data, and the root mean square error (RMSE) was calculated. At $4^{\circ}C$, E. coli cell growth was not observed on any cheese. However, E. coli growth was observed at $10{\circ}C$ to $30^{\circ}C$C with a ${\mu}_{max}$ of 0.01 to 1.03 log CFU/g/h, depending on the cheese. The ${\mu}_{max}$ values increased as temperature increased, while LPD values decreased, and ${\mu}_{max}$ and LPD values were different among the four types of cheese. The developed models showed adequate performance (RMSE = 0.176-0.337), indicating that these models should be useful for describing the growth kinetics of E. coli on various cheeses.

• Communications for Statistical Applications and Methods
• /
• 제29권2호
• /
• pp.251-261
• /
• 2022

As AI has a wide range of influence on human social life, issues of transparency and ethics of AI are emerging. In particular, it is widely known that due to the existence of historical bias in data against ethics or regulatory frameworks for fairness, trained AI models based on such biased data could also impose bias or unfairness against a certain sensitive group (e.g., non-white, women). Demographic disparities due to AI, which refer to socially unacceptable bias that an AI model favors certain groups (e.g., white, men) over other groups (e.g., black, women), have been observed frequently in many applications of AI and many studies have been done recently to develop AI algorithms which remove or alleviate such demographic disparities in trained AI models. In this paper, we consider a problem of using the information in the sensitive variable for fair prediction when using the sensitive variable as a part of input variables is prohibitive by laws or regulations to avoid unfairness. As a way of reflecting the information in the sensitive variable to prediction, we consider a two-stage procedure. First, the sensitive variable is fully included in the learning phase to have a prediction model depending on the sensitive variable, and then an imputed sensitive variable is used in the prediction phase. The aim of this paper is to evaluate this procedure by analyzing several benchmark datasets. We illustrate that using an imputed sensitive variable is helpful to improve prediction accuracies without hampering the degree of fairness much.

• 한국문헌정보학회지
• /
• 제50권1호
• /
• pp.533-553
• /
• 2016

1998년부터 2010년에 걸쳐 발표되었던 'FRBR family' 모형은 2016년에 'FRBR 도서관 참조모형'(FRBR LRM)이라는 새로운 이름으로 재구조화될 예정이다. FRBR LRM은 기존의 개념 모형인 FRBR, FRAD, FRSAD을 포함하여, 온톨로지 형식의 FRBRCore 및 FaBio, 박물관 분야와의 협력을 위한 FRBRoo와의 연계도 고려한 통합모형이다. 이에 본 연구에서는 FRBR LRM의 개발 배경과 통합모형으로서의 특징을 이용자 과업, 개체, 속성, 관계 측면에서 분석하고, LRM의 개체와 관계를 $prot{\acute{e}}g{\acute{e}}$에 적용하여 검토하였다. 이를 통해 초기 FRBR 모형과 LRM의 차이점을 살펴보았으며, FRBR 모형이 시맨틱웹과 같은 다양한 분야에 응용될 수 있음을 확인하였다. 앞으로 FRBR 모형을 적용할 때는, 단일한 구현방식만을 규정할 것이 아니라, 다양한 FRBR 응용 모형을 함께 검토하고, 그 중에서 국가별이나 기관별로 가장 적합한 모형을 선정한 뒤, 필요한 경우 기존의 모형을 변형하거나 통합할 수 있어야 할 것이다.

• 한국해안해양공학회:학술대회논문집
• /
• 한국해안해양공학회 2003년도 한국해안해양공학발표논문집
• /
• pp.164-169
• /
• 2003

The need fur higher grid resolution in climate models is often discussed (e.g. McAvaney et al.,2001) because a number of important oceanic processes are not resolved by the current generation of coupled models, e.g., boundary currents, mesoscale eddy fluxes, sill through flows. McClean et al., (1997) and Bryan and Smith (1998) have compared simulated mesoscale variability in simulations at several eddy-resolving resolutions to TOPEX/Poseidon and similar data. (omitted)

• 한국의류학회지
• /
• 제38권3호
• /
• pp.347-354
• /
• 2014

The color appearance of a yarn-dyed woven fabric depends on the color of the yarn as well as on the weave structure. Predicting the final color appearance or formulating the recipe is a difficult task, considering the interference of colored yarns and structure variations. In a modern fabric design process, the intended color appearance is attained through a digital color methodology based on numerous color data and color mixing recipes (i.e., color prediction models, accumulated in CAD systems). For successful color reproduction, accurate color prediction models should be devised and equipped for the systems. In this study, the final colors of yarn-dyed woven fabrics were predicted using six geometric-color mixing models (i.e., simple K/S model, log K/S model, D-G model, S-N model, modified S-N model, and W-O model). The color differences between the measured and the predicted colors were calculated to evaluate the accuracy of various color models used for different weave structures. The log K/S model, D-G model, and W-O model were found to be more accurate in color prediction of the woven fabrics used. Among these three models, the W-O model was found to be the best one as it gave the least color difference between the measured and the predicted colors.

• 한국정보디스플레이학회:학술대회논문집
• /
• 한국정보디스플레이학회 2004년도 Asia Display / IMID 04
• /
• pp.365-368
• /
• 2004

We present a family of elaborate numerical models for simulation and systematic optimization of complex LCDs for demanding applications (e.g. LCD-TV). These numerical models comprise modules for solving LCD-related problems in one, two and three dimensions. The three modules feature an intuitive graphical user surface for a jump-start into modeling, a common database for a range of materials and components as well as sophisticated and proven algorithms with more than 15 years of reliable performance in the LCD-industry. Methods for obtaining data required for the modeling of key components are presented.

• 통상정보연구
• /
• 제8권2호
• /
• pp.119-139
• /
• 2006

The purpose of this research is to analyze four models of global e-trade implementation which was suggested at the advance research of implementation global e-Trade with major trading countries. The main outcomes of this empirical study are as follows. For realizing global e-trade of G-Networking model country we have to implement e-trade in the field of "import & logistics". And for realizing global e-trade of P-Networking model country, it need to try in "settlement & clearance". Furthermore, for realizing global e-Trade of G-Penetration model country, we have known that the field of "import & logistics" would be implemented. Finally for realizing global e-Trade of P-Penetration model country, "settlement & clearance" could be implemented. Also, this study suggests that we have to do negotiation with China and Japan at first, and to try the area of settlement & clearance to implement the global e-Trade with Korea's 10 major trading countries.

• Journal of Periodontal and Implant Science
• /
• 제45권1호
• /
• pp.2-7
• /
• 2015

A fundamental problem in analyzing complex multilevel-structured periodontal data is the violation of independency among the observations, which is an assumption in traditional statistical models (e.g., analysis of variance and ordinary least squares regression). In many cases, aggregation (i.e., mean or sum scores) has been employed to overcome this problem. However, the aggregation approach still exhibits certain limitations, such as a loss of power and detailed information, no cross-level relationship analysis, and the potential for creating an ecological fallacy. In order to handle multilevel-structured data appropriately, mixed effects models have been introduced and employed in dental research using periodontal data. The use of mixed effects models might account for the potential bias due to the violation of the independency assumption as well as provide accurate estimates.

• 천문학회지
• /
• 제44권5호
• /
• pp.195-200
• /
• 2011

We have revisited the ACS Virgo Cluster Survey (ACSVCS), a Hubble Space Telescope program to obtain ACS/WFC g and z bands imaging for a sample of 100 early-type galaxies in the Virgo Cluster. In this study, we examine 51 nucleated early-type galaxies in the ACSVCS in order to look into the relationship between the photometric and structural properties of stellar nuclei and their host galaxies. We morphologically dissect galaxies into five classes. We note that (1) the stellar nuclei of dwarf early-type galaxies (dS0, dE, and dE,N) are generally fainter and bluer with g > 18.95 and (g-z) < 1.40 compared to some brighter and redder counterparts of the ellipticals (E) and lenticular galaxies (S0), (2) the g-band half-light radii of stellar nuclei of all dwarf early-type galaxies (dS0, dE, and dE,N) are smaller than 20 pc and their average is about 4 pc, and (3) the colors of red stellar nuclei with (g - z) > 1.40 in bright ellipticals and lenticular galaxies are bluer than their host galaxies colors. We also show that most of the unusually "red" stellar nuclei with (g-z) > 1.54 in the ACSVCS are the central parts of bright ellipticals and lenticular galaxies. Furthermore, we present multi photometric band color - color plots that can be used to break the age-metallicity degeneracy particularly by inclusion of the thermally pulsing-asymptotic giant branch (TP-AGB) phases of stellar evolution in the stellar population models.

• 대한건축학회논문집:구조계
• /
• 제35권2호
• /
• pp.45-52
• /
• 2019

BEMS(Building Energy Management Systems) have been applied to office buildings and collect relevant building energy data, e.g. temperatures, mass flow rates and energy consumptions of building mechanical systems and indoor spaces. The aforementioned measured data can be beneficially utilized for developing data-driven machine learning models which can be then used as part of MPC(Model Predictive Control) and/or optimal control strategies. In this study, the authors developed ANN(Artificial Neural Network) models of an AHU (Air Handling Unit) and a chiller for a real-life office building using BEMS data. Based on the ANN models, the authors developed optimal control strategies, e.g. daily operation schedule with regard to optimal start and stop of the AHU and the chiller (500 RT). It was found that due to the optimal start and stop of the AHU and the chiller, 4.5% and 16.4% of operation hours of the AHU and the chiller could be saved, compared to an existing operation.