• Animal Bioscience
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• v.34 no.10
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• pp.1623-1631
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• 2021

Objective: This study aimed to validate and evaluate the dry matter (DM) intake prediction model of the Korean feeding standards for dairy cattle (KFSD). Methods: The KFSD DM intake (DMI) model was developed using a database containing the data from the Journal of Dairy Science from 2006 to 2011 (1,065 observations 287 studies). The development (458 observations from 103 studies) and evaluation databases (168 observations from 74 studies) were constructed from the database. The body weight (kg; BW), metabolic BW (BW^0.75, MBW), 4% fat-corrected milk (FCM), forage as a percentage of dietary DM, and the dietary content of nutrients (% DM) were chosen as possible explanatory variables. A random coefficient model with the study as a random variable and a linear model without the random effect was used to select model variables and estimate parameters, respectively, during the model development. The best-fit equation was compared to published equations, and sensitivity analysis of the prediction equation was conducted. The KFSD model was also evaluated using in vivo feeding trial data. Results: The KFSD DMI equation is 4.103 (±2.994)+0.112 (±0.022)×MBW+0.284 (±0.020)×FCM-0.119 (±0.028)×neutral detergent fiber (NDF), explaining 47% of the variation in the evaluation dataset with no mean nor slope bias (p>0.05). The root mean square prediction error was 2.70 kg/d, best among the tested equations. The sensitivity analysis showed that the model is the most sensitive to FCM, followed by MBW and NDF. With the in vivo data, the KFSD equation showed slightly higher precision (R² = 0.39) than the NRC equation (R² = 0.37), with a mean bias of 1.19 kg and no slope bias (p>0.05). Conclusion: The KFSD DMI model is suitable for predicting the DMI of lactating dairy cows in practical situations in Korea.

• Korean Journal of Cognitive Science
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• v.34 no.3
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• pp.197-226
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• 2023

Generative Text Summarization is one of the Natural Language Processing tasks. It generates a short abbreviated summary while preserving the content of the long text. ROUGE is a widely used lexical-overlap based metric for text summarization models in generative summarization benchmarks. Although it shows very high performance, the studies report that 30% of the generated summary and the text are still inconsistent. This paper proposes a methodology for evaluating the performance of the summary model without using the correct summary. AggreFACT is a human-annotated dataset that classifies the types of errors in neural text summarization models. Among all the test candidates, the two cases, generation summary, and when errors occurred throughout the summary showed the highest correlation results. We observed that the proposed evaluation score showed a high correlation with models finetuned with BART and PEGASUS, which is pretrained with a large-scale Transformer structure.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.2
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• pp.108-121
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• 2016

The purpose of this study is to explore the issues and implications for landscape design education in Korean landscape architecture by analyzing the National Exhibition of Korean Landscape Architecture(NEKLA). This study analyzed the suggested topics and selected site as well as the commentary that appeared in the NEKLA's award-winning book published from 2004 to 2014. Results of the study are as follows: First, topics of NEKLA are not only competition guidelines but related to exploring new area and role of Korean landscape architecture. Second, most dealing with site is 'industrial heritage and regeneration space' and 'green infrastructure'. In more recent years, a larger variety of sites were addressed. Third, site locations are concentrated in metropolitan areas, and awards and participation of the non-metropolitan universities was very low. Fourth, seven criteria can be applied in a general landscape design competition such as 'newness of the concept(idea)', 'logicality of the design process', 'selection of site fidelity of analysis(interpretation)', 'presentation and completion of the master plan', 'consistency with the theme', 'linkage of concepts and results' and 'feasibility'. The evaluation criteria are increasing the sophistication of the design language to provide useful suggestions on how to find design education methods. Its implications are as follows: First, training is essential to derive innovative ideas, but it should avoid excessive concept-oriented education. Second, design education may include instruction on how to define the problems related with the site. Third, more emphasis on design logic is essential to transform the innovative concept to actual results. Fourth, 'slick images' unrelated to design should be suppressed. Fifth, practice is needed to solve the topics addressed in the design process of education. Sixth, 'feasibility' and 'creative thinking' are necessary to recognize a reciprocal relationship that is helpful to one another. This study uses direct quote commentary to minimize the subjectivity of the researcher and to trace issues of the contemporary landscape architecture more directly and vividly. This study is a record waiting for another review as meta-criticism. In this regard this study, the landscape architect of the next times will have a mean that historical records to review the current thinking of the landscape theory and design.

• Journal of Food Hygiene and Safety
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• v.29 no.4
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• pp.305-311
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• 2014

Minimum infective dose (MID) data has been recognized as an important and absolutely needed in quantitative microbiological assessment (QMRA). In this study, we performed a comprehensive literature review and meta-analysis to better quantify this association. The meta-analysis applied a final selection of 82 published papers for total 12 species foodborne disease pathogens (bacteria 9, virus 2, and parasite 1 species) which were identified and classified based on the dose-response models related to QMRA studies from PubMed, ScienceDirect database and internet websites during 1980-2012. The main search keywords used the combination "food", "foodborne disease pathogen", "minimum infective dose", and "quantitative microbiological risk assessment". The appropriate minimum infective dose for B. cereus, C. jejuni, Cl. perfringens, Pathogenic E. coli (EHEC, ETEC, EPEC, EIEC), L. monocytogenes, Salmonella spp., Shigella spp., S. aureus, V. parahaemolyticus, Hepatitis A virus, Noro virus, and C. pavum were $10^5cells/g$ (fi = 0.32), 500 cells/g (fi = 0.57), $10^7cells/g$ (fi = 0.56), 10 cells/g (fi = 0.47) / $10^8cells/g$ (fi = 0.71) / $10^6cells/g$ (fi = 0.70) / $10^6cells/g$ (fi = 0.60), $10^2{\sim}10^3cells/g$ (fi = 0.23), 10 cells/g (fi = 0.30), 100 cells/g (fi = 0.32), $10^5cells/g$ (fi = 0.45), $10^6cells/g$ (fi = 0.64), $10{\sim}10^2particles/g$ (fi = 0.33), 10 particles/g (fi = 0.71), and $10{\sim}10^2oocyst/g$ (fi = 0.33), respectively. Therefore, these results provide the preliminary data necessary for the development of foodborne pathogens QMRA.

• Journal of Food Hygiene and Safety
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• v.29 no.4
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• pp.299-304
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• 2014

The dose-response models are important for the quantitative microbiological risk assessment (QMRA) because they would enable prediction of infection risk to humans from foodborne pathogens. In this study, we performed a comprehensive literature review and meta-analysis to better quantify this association. The meta-analysis applied a final selection of 193 published papers for total 43 species foodborne disease pathogens (bacteria 26, virus 9, and parasite 8 species) which were identified and classified based on the dose-response models related to QMRA studies from PubMed, ScienceDirect database and internet websites during 1980-2012. The main search keywords used the combination "food", "foodborne disease pathogen", "dose-response model", and "quantitative microbiological risk assessment". The appropriate dose-response models for Campylobacter jejuni, pathogenic E. coli O157:H7 (EHEC / EPEC / ETEC), Listeria monocytogenes, Salmonella spp., Shigella spp., Staphylococcus aureus, Vibrio parahaemolyticus, Vibrio cholera, Rota virus, and Cryptosporidium pavum were beta-poisson (${\alpha}=0.15$, ${\beta}=7.59$, fi = 0.72), beta-poisson (${\alpha}=0.49$, ${\beta}=1.81{\times}10^5$, fi = 0.67) / beta-poisson (${\alpha}=0.22$, ${\beta}=8.70{\times}10^3$, fi = 0.40) / beta-poisson (${\alpha}=0.18$, ${\beta}=8.60{\times}10^7$, fi = 0.60), exponential (r=$1.18{\times}10^{-10}$, fi = 0.14), beta-poisson (${\alpha}=0.11$, ${\beta}=6,097$, fi = 0.09), beta-poisson (${\alpha}=0.21$, ${\beta}=1,120$, fi = 0.15), exponential ($r=7.64{\times}10^{-8}$, fi = 1.00), betapoisson (${\alpha}=0.17$, ${\beta}=1.18{\times}10^5$, fi = 1.00), beta-poisson (${\alpha}=0.25$, ${\beta}=16.2$, fi = 0.57), exponential ($r=1.73{\times}10{-2}$, fi = 1.00), and exponential ($r=1.73{\times}10^{-2}$, fi = 0.17), respectively. Therefore, these results provide the preliminary data necessary for the development of foodborne pathogens QMRA.

• Journal of vocational education research
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• v.37 no.2
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• pp.39-75
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• 2018

The purpose of this study is to verify the general characteristics in the previous studies and the magnitude of the correlation between the learner's satisfaction and the academic achievement in the education and training program. To do this, we searched relevant literature from 2000 to 2016, and conducted a systematic review of the literature on the final 31 studies through the selection criteria and quality evaluation. Among them, 27 meta-analysis of the literature was conducted. The finding of the study were as follows. First, a total of 31 studies were conducted from 2000 to 2016, and more than half of them(16) were conducted for the last 4 years(2009~2012). In terms of education and training students, there are 18 college students, 9 workers, and 4 elementary students in order of study. In terms of methods, 15 collective education, 14 distance education, 2 blended education. In terms of learner's participation, 22 the general participation, 9 the active participation. Second, as a result of the meta-analysis, the magnitude of the correlation between satisfaction and achievement was moderate(ZCOR=.297, 95%: CI .210~.383). Third, as a result of verifying the difference in the magnitude of the correlation effect between satisfaction and achievement according to the characteristics of the education and training program, there was no difference between the groups in the student object and education method, but there was a difference in the magnitude of the correlation effect depending on the participant type(Q=15.40, df=1, p<.0001). The active participation showed a correlation effect size larger(ZCOR=.588, 95%: CI .422~.754). The effect size of the general participation was lower than the median(ZCOR=.211, 95%: CI .12 ~.300).

• The Journal of Pediatrics of Korean Medicine
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• v.34 no.1
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• pp.26-36
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• 2020

Objectives The purpose of this study is to assess the reporting quality and methodological quality of systematic reviews from the Journal of Pediatrics of Korean Medicine. Methods Systematic reviews were selected from the Journal of Pediatrics of Korean Medicine (JPKM) by utilizing Oriental Medicine Advanced Searching Integrated System (OASIS) and JPKM homepage. Two independent researchers assessed the reporting quality through Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline checklist, and assessed the methodological quality of systematic review through Assessment of Multiple Systematic Reviews (AMSTAR) 2 tool checklist. Results Four systematic reviews were finally selected for the assessment. When assessed by PRISMA, three literatures were little insufficient, and one literature was sufficient. When assessed by AMSTAR 2, three literatures were moderate quality, and one literature was critically low quality. Also, all of the reviews had no information about 'Protocol and registration', 'publication bias', and 'conflicts of interest'. Conclusions Systematic review is important for Journal of Pediatrics of Korean Medicine and Korean Medicine Society. Efforts are needed to improve the reporting and methodological quality of the systematic reviews through PRISMA and AMSTAR 2.

• IE interfaces
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• v.17 no.4
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• pp.426-439
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• 2004

This research discusses knowledge contents needed to build an OLAP system for medical sector, OLAP functionalities from past studies, and a medical intelligence system which is a kind of OLAP. The knowledge requirements which consist of nine contents and OLAP fundamental functionalities are applied to the system. Most past studies have focused on developing a medical data warehouse rather than OLAP. The medical intelligence system supplies health care providers (i.e., doctors, clinicians, researchers and nurses) and non-providers (i.e., managers and business analysts) with multidimensional OLAP functionalities. The system can be used to gain a deeper understanding of specific medical issues. In this research, we focus not on medical data warehouse, but on the technical challenges of designing and implementing an effective medical intelligence system for health care information. An architecture is applied to developing the medical intelligence system for a medical center in order to illustrate its practical usage. Six packages in the developed system are discussed in this research: Explorer, Analyzer, Reporter, Statistician, Visualizer, and Meta Administrator packages. Evaluation of the system and ongoing research directions conclude the research.

• Journal of Electrical Engineering and Technology
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• v.3 no.1
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• pp.52-59
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• 2008

This paper describes the secant method for solving the economic dispatch (ED) problem with generator constraints and transmission losses. The ED problem is an important optimization problem in the economic operation of a power system. The proposed algorithm involves selection of minimum and maximum incremental costs (lambda values) and then the evaluation of optimal lambda at required power demand is done by secant method. The proposed algorithm has been tested on a power system having 6, 15, and 40 generating units. Studies have been made on the proposed method to solve the ED problem by taking 120 and 200 units with generator constraints. Simulation results of the proposed approach were compared in terms of solution quality, convergence characteristics, and computation efficiency with conventional methods such as lambda iterative method, heuristic methods such as genetic algorithm, and meta-heuristic methods like particle swarm optimization. It is observed from different case studies that the proposed method provides qualitative solutions with less computational time compared to various methods available in the literature.

• Journal of Advanced Navigation Technology
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• v.13 no.5
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• pp.781-786
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• 2009

The cloud computing environment is a new trend of web based application parts. It can be IT business model that is able to easily support learning service and allocate resources through the internet to users. U-learning also is a maximal model with efficiency of the internet based learning. Thus, in this research, we proposed a design of u-learning's teaching and learning model that is applying the internet based learning. Proposal method is to fit u-learning and has 7 steps: Preparing, planning, gathering, learning process, analysis and evaluation, and feedback. We make a cloud u-learning server and cloud LMS to process and manage the service. And We also make a mobile devices meta data to aware the model.