• Horticultural Science & Technology
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• v.29 no.5
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• pp.420-432
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• 2011

Population dynamics of greenhouse whitefly, Trialeurodes vaporariorum (Westwood), were modeled and simulated to compare the temperature effects of air and tomato leaf inside greenhouse using DYMEX model simulator (pre-programed module based simulation program developed by CSIRO, Australia). The DYMEX model simulator consisted of temperature dependent development and oviposition modules. The normalized cumulative frequency distributions of the developmental period for immature and oviposition frequency rate and survival rate for adult of greenhouse whitefly were fitted to two-parameter Weibull function. Leaf temperature on reversed side of cherry tomato leafs (Lycopersicon esculentum cv. Koko) was monitored according to three tomato plant positions (top, > 1.6 m above the ground level; middle, 0.9 - 1.2 m; bottom, 0.3 - 0.5 m) using an infrared temperature gun. Air temperature was monitored at same three positions using a Hobo self-contained temperature logger. The leaf temperatures from three plant positions were described as a function of the air temperatures with 3-parameter exponential and sigmoidal models. Data sets of observed air temperature and predicted leaf temperatures were prepared, and incorporated into the DYMEX simulator to compare the effects of air and leaf temperature on population dynamics of greenhouse whitefly. The number of greenhouse whitefly immatures was counted by visual inspection in three tomato plant positions to verify the performance of DYMEX simulation in cherry tomato greenhouse where air and leaf temperatures were monitored. The egg stage of greenhouse whitefly was not counted due to its small size. A significant positive correlation between the observed and the predicted numbers of immature and adults were found when the leaf temperatures were incorporated into DYMEX simulation, but no significant correlation was observed with the air temperatures. This study demonstrated that the population dynamics of greenhouse whitefly was affected greatly by the leaf temperatures, rather than air temperatures, and thus the leaf surface temperature should be considered for management of greenhouse whitefly in cherry tomato grown in greenhouses.

• Korean Journal of Ecology and Environment
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• v.40 no.1
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• pp.130-142
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• 2007

This study was to examine impacts of turbid water on fish community in the downstream of Yongdam Dam during the period from June to October 2006. For the research, we selected six sampling sites in the field: two sites were controls with no influences of turbid water from the dam and other remaining four sites were the stations for an assessment of potential turbid effects. We evaluated integrative health conditions throughout applications of various models such as necropsy-based fish health assessment model (FHA), Index of Biological Integrity (IBI) using fish assemblages, and Qualitative Habitat Evaluation Index (QHEI). Laboratory tests on fish exposure under 400 NTU were performed to find out impact of turbid water using scanning electron microscope (SEM). Results showed that fine solid particles were clogging in the gill in the treatments, while particles were not found in the control. This results indicate that when inorganic turbidity increases abruptedly, fish may have a mechanical abrasion or respiratory blocking. The stream health condition, based on the IBI values, ranged between 38 and 48 (average: 42), indicating a "excellent" or "good" condition after the criteria of US EPA (1993). In the mean time, physical habitat condition, based on the QHEI, ranged 97 to 187 (average 154), indicating a "suboptimal condition". These biological outcomes were compared with chemical dataset: IBI values were more correlated (r=0.526, p<0.05, n=18) with QHEI rather than chemical water quality, based on turbidity (r=0.260, p>0.05, n=18). Analysis of the FHA showed that the individual health indicated "excellent condition", while QHEI showed no habitat disturbances (especially bottom substrate and embeddeness), food-web, and spawning place. Consequently, we concluded that the ecological health in downstream of Yongdam Dam was not impacted by the turbid water.

• Korean Journal of Food Science and Technology
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• v.37 no.3
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• pp.484-491
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• 2005

Quantitative microbial risk assessment (QMRA) analyzes potential hazard of microorganisms on public health and offers structured approach to assess risks associated with microorganisms in foods. This paper addresses specific risk management questions associated with Staphylococcus aureus in kimbab and improvement and dissemination of QMRA methodology, QMRA model was developed by constructing four nodes from retail to table pathway. Predictive microbial growth model and survey data were combined with probabilistic modeling to simulate levels of S. aureus in kimbab at time of consumption, Due to lack of dose-response models, final level of S. aureus in kimbeb was used as proxy for potential hazard level, based on which possibility of contamination over this level and consumption level of S. aureus through kimbab were estimated as 30.7% and 3.67 log cfu/g, respectively. Regression sensitivity results showed time-temperature during storage at selling was the most significant factor. These results suggested temperature control under $10^{\circ}C$ was critical control point for kimbab production to prevent growth of S. aureus and showed QMRA was useful for evaluation of factors influencing potential risk and could be applied directly to risk management.

• Korean Journal of Soil Science and Fertilizer
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• v.41 no.6
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• pp.393-398
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• 2008

Several researchers have proposed models or equations to predict soil $CO_2$ flux from more readily available biotic and abiotic measurement. Tree commonly used abiotic variables were N mineral and soil temperature and soil water content. This study was conducted to determine $CO_2$ emission to mineral N, soil water content and soil temperature with clay loam and sandy loam in pepper cultivation in 2004~2005. $CO_2$ flux in the upland with different levels of soil water potential was measured at least once in two weeks during the cropping period in the pepper cultivation plots. Soil water potential in the clay loam and sandy loam soils was established at -30kPa and -50kPa by measuring the soil gravimetric water content with two replications. $CO_2$ emission rate from the differently managed plots was highly correlation coefficient to between the mineral N ($R=0.830^{**}$, $0.876^{**}$) and soil temperature ($r^2=0.793^{**}$, $0.804^{**}$) in the clay loam and sandy loam, respectively. However, the relationships between $CO_2$ emission and soil water content were non-significant. $CO_2$ emissions at sandy loam soils was lower to 21~37% than at clay loam soils for both soil water conditions without differences in yield. At difference levels of soil water conditions, $CO_2$ emission at -50kPa decreased to 37.5% in comparison with that at -30kPa. From the path analysis as to contribution factors of GHGs, it appeared that contribution rate was in the order of soil temperature (54.9%), mineral N (32.7%), and soil moisture content (12.4%).

• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.749-758
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• 2004

In this paper, we propose a new method utilizing only raw corpus without additional human effort for disambiguation of target word selection in English-Korean machine translation. We use two data-driven techniques; one is the Latent Semantic Analysis(LSA) and the other the Probabilistic Latent Semantic Analysis(PLSA). These two techniques can represent complex semantic structures in given contexts like text passages. We construct linguistic semantic knowledge by using the two techniques and use the knowledge for target word selection in English-Korean machine translation. For target word selection, we utilize a grammatical relationship stored in a dictionary. We use k- nearest neighbor learning algorithm for the resolution of data sparseness Problem in target word selection and estimate the distance between instances based on these models. In experiments, we use TREC data of AP news for construction of latent semantic space and Wail Street Journal corpus for evaluation of target word selection. Through the Latent Semantic Analysis methods, the accuracy of target word selection has improved over 10% and PLSA has showed better accuracy than LSA method. finally we have showed the relatedness between the accuracy and two important factors ; one is dimensionality of latent space and k value of k-NT learning by using correlation calculation.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.5 no.4
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• pp.1-34
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• 2010

Recently, failure rates of Kosdaq IPO firms are increasing and their survival rates tend to be very low, and when these firms do fail, often times backed by a number of governmental financial supports, they may inflict severe financial damage to investors, let alone economy as a whole. To ensure investors' confidence in Kosdaq and foster promising and healthy businesses, it is necessary to precisely assess their intrinsic values and survivability. This study investigates what contributed to the failure of IPO firms and analyzed how these elements are factored into corresponding firms' stock returns. Failure risks are assessed at the time of IPO. This paper considers factors reflecting IPO characteristics, a firm's underwriter prestige, auditor's quality, IPO offer price, firm's age, and IPO proceeds. The study further went on to examine how, if at all, these failure risks involved during IPO led to post-IPO stock prices. Sample firms used in this study include 98 Kosdaq firms that have failed and 569 healthy firms that are classified into the same business categories, and Logit models are used in estimate the probability of failure. Empirical results indicate that auditor's quality, IPO offer price, firm's age, and IPO proceeds shown significant relevance to failure risks at the time of IPO. Of other variables, firm's size and ROA, previously deemed significantly related to failure risks, in fact do not show significant relevance to those risks, whereas financial leverage does. This illustrates the efficacy of a model that appropriately reflects the attributes of IPO firms. Also, even though R&D expenditures were believed to be value relevant by previous studies, this study reveals that R&D is not a significant factor related to failure risks. In examing the relation between failure risks and stock prices, this study finds that failure risks are negatively related to 1 or 2 year size-adjusted abnormal returns after IPO. The results of this study may provide useful knowledge for government regulatory officials in contemplating pertinent policy and for credit analysts in their proper evaluation of a firm's credit standing.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.4
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• pp.145-159
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• 2013

The purpose of this study is to analyze the structural relationship as to how learning flow and self-directed learning are linked to learning motives and academic self-efficacy in the learning setting of high school students. To accomplish such purpose, based on theoretical backgrounds and preceding research findings evaluation models were put to verification for a valid research model for this study. The initial hypothetical model was that self-directed learning ability would have a direct influence on learning motive, academic efficacy and learning flow, while having an indirect influence on learning flow with learning motive and self-efficacy acting as a mediating variable. But the hypothetical model showed low significance level between self-directed learning and learning motive, and learning motive and learning flow. Therefore, links were adjusted to create the final model within the scope that the adequacy of the model might not be compromised. To verify the model, 900 high school students in Seoul were surveyed and the collected data were statistically analyzed using AMOS v21.0 and SPSS v21.0 But 815 surveys were excluded because they were not sufficiently answered. From the analysis, it was found that self-directed learning and academic efficacy have a direct influence on learning flow while self-directed learning and academic efficacy have an indirect leaning motive and learning flow. This finding means that, in the relationship of self-directed learning and learning flow, learning motive and learning efficacy are positive factors that help high school students experience learning flow. Thus, in order to enhance the experience of self-directed learning ability of high school students, various educational endeavors are needed to draw the experience of learning flow during the regular course of study. In addition, customized educational methods and environments are required to increase academic efficacy of the students.

• Journal of Animal Science and Technology
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• v.45 no.4
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• pp.509-516
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• 2003

Growth curves were estimated for 1083 female Korean cattle raised in Daekwanryeong branch, National Livestock Research Institute (NLRI). Comparisons were made among various growth curve models for goodness of fit for the growth of the cows. Estimated growth curve functions were $W_t=370.2e^{-2.208e^{-0.00327t}$ for Gompertz model, for von Bertalanffy model, and $W_t=341.2(1+5.652e^{-0.00524t})^{-1}$ for Logistic model. Ages at inflection estimated from Gompertz model, von Bertalanffy model and Logistic model were 242.2 days, 191.5 days, and 330.5 days respectively, body weight at inflection were 136kg, 115kg, and 170kg, and daily gain at inflection were 0.445kg, 0.451kg, and 0.446kg. The predicted weights by ages from Gompertz model, von Bertalanffy model, and Logistic model were onsistently overestimated at birth weight and underestimated at 36 month weight. The von Bertalanffy model which had a variable point of inflection fit the data best.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.43-57
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• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.

• Journal of Korean Home Economics Education Association
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• v.28 no.1
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• pp.19-39
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• 2016

The purpose of this study was to develop the safety theme-based integrated teaching learning process plans for the middle school Home Economics(HE) Instruction and ultimately to contribute for the middle school students to live their safe lives. To achieve the goals of this study, HE curriculum documents from the 1st to the 2015 revision were analyzed and a survey was conducted to identify the middle school students' current status of safety accidents and needs on the HE safety education. The respondents of the survey were the 512 students of one ${\bigcirc}{\bigcirc}$ Girls' Middle School in Busan. And then, the seven integrated themes were selected, each seven integrated theme-networks were formed, and safety theme-based Home Economics curriculum and learning materials were developed. The results of this study were as the follows. The safety education content has continually been included from the first HE curriculum of 1954 to the 2015 revised HE curriculum. The middle school student respondents highly needed the content of 'the methods to deal with sexual violence and prostitution prevention', 'suicide prevention', and 'bullying net' for the HE safety education. All the 42 items were needed for the HE safety education by the respondents. The safety theme-based HE teaching learning process plans developed finally included the seven integrated themes, which were (1) dietary life safety, (2) adolescents' sex and safety, (3) adolescents' relationships with friends and safety, (4) family life and safety, (5) dwelling life and safety, (6) adolescents' egos and safety, and (7) social environment and safety. Each integrated theme consisted of three to six small themes, which amounted to total 28(for 35 lessons). Each small theme was presented with learning objectives and particular goals. The total 157 learning materials including the Home Economics curriculum were developed, which offered learning objectives and content for each safety theme, total 28 teaching and learning plans(for 35 lessons) were developed, which offered specific instructions for the easy implementation of the curriculum in the classroom, 28 PPTs, 25 film materials, four reading materials, 61 workbooks, 14 activity sheets, 16 evaluation sheets, 3 test sheets, 2 reference materials, and 4 learning material models(the refrigerator model, traffic lights for discussions, food tray model and stickers, and food mileage card). In this study, the safety education themes of 'clothing life and safety', 'conflict and safety', 'professional life and safety', and 'consumer and safety' were not addressed because these theme were not needed highly by the respondents. Therefore, for the further development of the teaching learning process plans for the HE safety education, it is necessary to develop and evaluate the teaching learning process plans to address the themes of 'clothing life and safety', 'conflict and safety', 'professional life and safety', and 'consumer and safety'.