• Korean Journal of Social Welfare
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• v.59 no.1
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• pp.301-327
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• 2007

The purpose of this study is to examine the timing and the risk factors associated with the adoption of legally-free foster children. The sample of the study was drawn from foster care files of Adoption and Foster Care Analysis and Reporting System(AFCARS) in 32 states between October 1998 (FY 1999) and September 2002(FY 2002). The timing post-TPR to adoption was examined by plotting the Kaplan-Meier cumulative hazard function for adoption and by plotting the KM hazard functions stratified by child's race and child's age at TPR. Cox proportional-hazards regression analysis was used to identify risk factors for adoption of legally-free foster children after TPR. The hazard of adoption was very low immediately after TPR but increased steadily starting at 3 months and then declined after 20 months. The cumulative hazard functions for White non-Hispanic children and Black non-Hispanic children crossed over at 13 months after TPR. Racial minority status, older age, and disability were negatively associated with the hazard of adoption. Physical abuse, sexual abuse had the lower hazard for adoption compared by neglect. Caretaker's inability to cope had the slightly lower hazard for adoption whereas inadequate housing showed the slightly greater hazard for adoption. Characteristics of foster care services turned into be powerful predictors of adoption. Specifically, legally-free children placed in pre-adoptive homes, those who shared the same racial/ethnic background with their foster caretakers, and those who were placed in two-parent families have a greater likelihood of adoption. The findings highlight the importance of foster care service provisions after TPR to facilitate adoption of legally-free foster children. Furthermore, a more substantial resources and targeted support for foster children who experience physical abuse and sexual abuse in need of adoption should be provided for moving the foster children into permanency.

• Food Science and Preservation
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• v.23 no.7
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• pp.1065-1073
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• 2016

This study investigated the sensory attributes and quality characteristics of Fuji apples based on market commodity price to provide data for quality index of Fuji apples. Samples were purchased from the Garak market (Seoul Agro-Fisheries & Food Corporation) and divided into four groups depending on the price such as group A, B, C, D. There were no significant differences in their volume and weight among groups. In the soluble solid content and total free sugar, A and B group (high price) showed higher content than those of C and D (low price) group. And also, the A group and B, C, D group showed 386.29 mg% and 320.09~359.28 mg% in the total organic acid content, respectively. As an sensory evaluation results, A group and B group were evaluated higher score than those of C and D group in the uniformity of red color and glossiness of skin and unique apple sensory attributes using quantitative descriptive analysis. Consumer test showed similar to quantitative descriptive analysis results in the various sensory attributes. In the analysis results between quality characteristics and sensory attributes of Fuji apples, total acceptability was correlated positively with titratable acidity (r=0.58), soluble solid (r=0.89), soluble solid content/titratable acidity ratio (r=0.42), total free sugar (r=0.36) and total organic acid (r=0.38). Based on principal component analysis of apple's quality characteristics, apples were primary separated along the first principal component (pH, acidity, soluble solid content, total free sugar, organic acid), which accounted for 66.01% of total variance. In addition, principal component analysis of sensory evaluation revealed a total variance for the quantitative descriptive of 55. 65% and a total variance for the consumer test of 55.84%.

• Journal of Dental Rehabilitation and Applied Science
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• v.36 no.3
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• pp.183-195
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• 2020

Purpose: The purpose of this study is to compare the flexural strength of CAD/CAM denture base resins with conventional denture base resins based on their thicknesses. Materials and Methods: For the conventional denture base resins, Lucitone 199^® (C-LC) was used. DIOnavi - Denture (P-DO) and DENTCA Denture Base II (P-DC) were taken for the 3D printing denture base resins. For the prepolymerized PMMA resins, Vipi Block Gum (M-VP) and M-IVoBase^® CAD (M-IV) were used. The final dimensions of the specimens were 65.0 mm x 12.7 mm x 1.6 mm / 2.0 mm / 2.5 mm. The 3-point bend test was implemented to measure the flexural strength and flexural modulus. Microscopic evaluation of surface of fractured specimen was conducted by using a scanning electron microscope (SEM). After testing the normality of the data, one-way ANOVA was adopted to evaluate the differences among sample groups with a significance level of P = 0.05. The Tukey HSD test was performed for post hoc analysis. Results: Under the same thicknesses, there are significant differences in flexural strength between CAD/CAM denture base resins and conventional denture base resins except for P-DO and C-LC. M-VP showed higher flexural strength than conventional denture base resins, P-DC and M-IV displayed lower flexural strength than conventional denture base resins. Flexural modulus was highest in M-VP, followed by C-LC, P-DO, P-DC, M-IV, significant differences were found between all materials. In the comparison of flexural strength according to thickness, flexural strength of 2.5 mm was significantly higher than that of 1.6 mm in C-LC. Flexural strength of 2.5 mm and 2.0 mm was significantly higher than that of 1.6 mm in P-DC and M-VP. In M-IV, as the thickness increases, significant increase in flexural strength appeared. SEM analysis illustrates different fracture surfaces of the specimens. Conclusion: The flexural strength of different CAD/CAM denture base resins used in this study varied according to the composition and properties of each material. The flexural strength of CAD/CAM denture base resins was higher than the standard suggested by ISO 20795-1:2013 at a thickness of 1.6 mm or more though the thickness decreased. However, for clinical use of dentures with lower thickness, further researches should be done regarding other properties at lower thickness of denture base resins.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.64 no.4
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• pp.353-365
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• 2019

A near-infrared reflectance spectroscopy (NIRS) prediction model was set to establish a rapid analysis system of wheat germplasm and provide statistical information on the characteristics of protein contents. The variability index value (VIV) of calibration resources was 0.80, the average protein content was 13.2%, and the content range was from 7.0% to 13.2%. After measuring the near-infrared spectra of calibration resources, the NIRS prediction model was developed through a regression analysis between protein content and spectra data, and then optimized by excluding outliers. The standard error of calibration, R², and the slope of the optimized model were 0.132, 0.997, and 1.000 respectively, and those of external validation results were 0.994, 0.191, and 1.013, respectively. Based on these results, a developed NIRS model could be applied to the rapid analysis of protein in wheat. The distribution of NIRS protein content of 6,794 resources were analyzed using a normal distribution analysis. The VIV was 0.79, the average protein was 12.1%, and the content range of resources accounting for 42.1% and 68% of the total accessions were 10-13% and 9.5-14.6%, respectively. The composition of total resources was classified into breeding line (3,128), landrace (2,705), and variety (961). The VIV in breeding line was 0.80, the protein average was 11.8%, and the contents of 68% of total resources ranged from 9.2% to 14.5%. The VIV in landrace was 0.76, the protein average was 12.1%, and the content range of resources of 68% of total accessions was 9.8-14.4%. The VIV in variety was 0.80, the protein average was 12.8%, and the accessions representing 68% of total resources ranged from 10.2% to 15.4%. These results should be helpful to the related experts of wheat breeding.

• Journal of Korean Society of Environmental Engineers
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• v.36 no.6
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• pp.421-428
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• 2014

For the analysis of water supply network, demand-driven and pressure-driven analysis methods have been proposed. Of the two methods, demand-driven analysis (DDA) can only be used in a normal operation condition to evaluate hydraulic status of a pipe network. Under abnormal conditions, i.e., unexpected pipe destruction, or abnormal low pressure conditions, pressure-driven analysis (PDA) method should be used to estimate the suppliable flowrate at each node in a network. In order to carry out the pressure-driven analysis, head-outflow relationship (HOR), which estimates flowrate at a certain pressure at each node, should be first determined. Most previous studies empirically suggested that each node possesses its own characteristic head-outflow relationship, which, therefore, requires verification by using actual field data for proper application in PDA modeling. In this study, a model pipe network was constructed, and various operation scenarios of normal and abnormal conditions, which cannot be realized in real pipe networks, were established. Using the model network, data on pressure and flowrate at each node were obtained at each operation condition. Using the data obtained, previously proposed HOR equations were evaluated. In addition, head-outflow relationship at each node was analyzed especially under multiple pipe destruction events. By analyzing the experimental data obtained from the model network, it was found that flowrate reduction corresponding to a certain pressure drop (by pipe destruction at one or multiple points on the network) followed intrinsic head-outflow relationship of each node. By comparing the experimentally obtained head-outflow relationship with various HOR equations proposed by previous studies, the one proposed by Wagner et al. showed the best agreement with the exponential parameter, m of 3.0.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.2
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• pp.86-96
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• 2006

Ecoclimap-1, a new complete surface parameter global database at a 1-km resolution, was previously presented. It is intended to be used to initialize the soil-vegetation- atmosphere transfer schemes in meteorological and climate models. Surface parameters in the Ecoclimap-1 database are provided in the form of a per-class value by an ecoclimatic base map from a simple merging of land cover and climate maps. The principal objective of this ecoclimatic map is to consider intra-class variability of life cycle that the usual land cover map cannot describe. Although the ecoclimatic map considering land cover and climate is used, the intra-class variability was still too high inside some classes. In this study, a new strategy is defined; the idea is to use the information contained in S10 NDVI SPOT/VEGETATION profiles to split a land cover into more homogeneous sub-classes. This utilizes an intra-class unsupervised sub-clustering methodology instead of simple merging. This study was performed to provide a new ecolimatic map over Northeast Asia in the framework of Ecoclimap-2 global database construction for surface parameters. We used the University of Maryland's 1km Global Land Cover Database (UMD) and a climate map to determine the initial number of clusters for intra-class sub-clustering. An unsupervised classification process using six years of NDVI profiles allows the discrimination of different behavior for each land cover class. We checked the spatial coherence of the classes and, if necessary, carried out an aggregation step of the clusters having a similar NDVI time series profile. From the mapping system, 29 ecosystems resulted for the study area. In terms of climate-related studies, this new ecosystem map may be useful as a base map to construct an Ecoclimap-2 database and to improve the surface climatology quality in the climate model.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.121-145
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• 2010

University timetabling depending on the educational environments of universities is an NP-hard problem that the amount of computation required to find solutions increases exponentially with the problem size. For many years, there have been lots of studies on university timetabling from the necessity of automatic timetable generation for students' convenience and effective lesson, and for the effective allocation of subjects, lecturers, and classrooms. Timetables are classified into a course timetable and an examination timetable. This study focuses on the former. In general, a course timetable for liberal arts is scheduled by the office of academic affairs and a course timetable for major subjects is scheduled by each department of a university. We found several problems from the analysis of current course timetabling in departments. First, it is time-consuming and inefficient for each department to do the routine and repetitive timetabling work manually. Second, many classes are concentrated into several time slots in a timetable. This tendency decreases the effectiveness of students' classes. Third, several major subjects might overlap some required subjects in liberal arts at the same time slots in the timetable. In this case, it is required that students should choose only one from the overlapped subjects. Fourth, many subjects are lectured by same lecturers every year and most of lecturers prefer the same time slots for the subjects compared with last year. This means that it will be helpful if departments reuse the previous timetables. To solve such problems and support the effective course timetabling in each department, this study proposes a university timetabling support system based on two phases. In the first phase, each department generates a timetable template from the most similar timetable case, which is based on case-based reasoning. In the second phase, the department schedules a timetable with the help of interactive user interface under the timetabling criteria, which is based on rule-based approach. This study provides the illustrations of Hanshin University. We classified timetabling criteria into intrinsic and extrinsic criteria. In intrinsic criteria, there are three criteria related to lecturer, class, and classroom which are all hard constraints. In extrinsic criteria, there are four criteria related to 'the numbers of lesson hours' by the lecturer, 'prohibition of lecture allocation to specific day-hours' for committee members, 'the number of subjects in the same day-hour,' and 'the use of common classrooms.' In 'the numbers of lesson hours' by the lecturer, there are three kinds of criteria : 'minimum number of lesson hours per week,' 'maximum number of lesson hours per week,' 'maximum number of lesson hours per day.' Extrinsic criteria are also all hard constraints except for 'minimum number of lesson hours per week' considered as a soft constraint. In addition, we proposed two indices for measuring similarities between subjects of current semester and subjects of the previous timetables, and for evaluating distribution degrees of a scheduled timetable. Similarity is measured by comparison of two attributes-subject name and its lecturer-between current semester and a previous semester. The index of distribution degree, based on information entropy, indicates a distribution of subjects in the timetable. To show this study's viability, we implemented a prototype system and performed experiments with the real data of Hanshin University. Average similarity from the most similar cases of all departments was estimated as 41.72%. It means that a timetable template generated from the most similar case will be helpful. Through sensitivity analysis, the result shows that distribution degree will increase if we set 'the number of subjects in the same day-hour' to more than 90%.

• Korean Journal of Environmental Biology
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• v.35 no.4
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• pp.526-532
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• 2017

Development, survival, and reproduction of brown planthopper (BPH) Nilaparvata lugens $St{\aa}l$ (Hemiptera: Delphacidae), were studied in laboratory at $25{\pm}2^{\circ}C$, $65{\pm}5%$ RH and a 16L : 8D hours photoperiodism on five rice cultivars of: Dongjin 1ho, Chungchungbyeo, Jangseongbyeo, Chinnongbyeo and Jungmo 1045. BPH nymphs successfully survived on all rice cultivars, although survival rate was lowest on Jangseongbyeo (36.0%). Developmental time of immature stages ranged from $11.7{\pm}0.59d$ on Jungmo 1045 to $12.8{\pm}0.59d$ on Chinnongbyeo. Reproductive period and female longevity were longest on Dongjin 1ho, Chinnongbyeo and Jungmo 1045 while highest fecundity of N. lugens being observed on these three rice cultivars. Highest and lowest net reproductive rates were calculated on rice cultivars, Jungmo 1045 and Jangseongbyeo, respectively. Mean generation time was the longest on rice cultivar Dongjin 1ho. Respective descending order of intrinsic rates of population increase were on Jungmo 1045, Chinnongbyeo, Dongjin 1ho, Chungchungbyeo and Jangseongbyeo. These population parameters showed that N. lugens can successfully survive and reproduce on Chinnongbyeo and Jungmo 1045.

• Journal of IKEEE
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• v.25 no.3
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• pp.493-500
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• 2021

In this paper, we propose the development of deep learning structure to improve quality of polygonal containers. The deep learning structure consists of a convolution layer, a bottleneck layer, a fully connect layer, and a softmax layer. The convolution layer is a layer that obtains a feature image by performing a convolution 3x3 operation on the input image or the feature image of the previous layer with several feature filters. The bottleneck layer selects only the optimal features among the features on the feature image extracted through the convolution layer, reduces the channel to a convolution 1x1 ReLU, and performs a convolution 3x3 ReLU. The global average pooling operation performed after going through the bottleneck layer reduces the size of the feature image by selecting only the optimal features among the features of the feature image extracted through the convolution layer. The fully connect layer outputs the output data through 6 fully connect layers. The softmax layer multiplies and multiplies the value between the value of the input layer node and the target node to be calculated, and converts it into a value between 0 and 1 through an activation function. After the learning is completed, the recognition process classifies non-circular glass bottles by performing image acquisition using a camera, measuring position detection, and non-circular glass bottle classification using deep learning as in the learning process. In order to evaluate the performance of the deep learning structure to improve quality of polygonal containers, as a result of an experiment at an authorized testing institute, it was calculated to be at the same level as the world's highest level with 99% good/defective discrimination accuracy. Inspection time averaged 1.7 seconds, which was calculated within the operating time standards of production processes using non-circular machine vision systems. Therefore, the effectiveness of the performance of the deep learning structure to improve quality of polygonal containers proposed in this paper was proven.

• Knowledge Management Research
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• v.22 no.3
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• pp.273-293
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• 2021

Due to the COVID-19 pandemic, the size of the e-commerce has been increased rapidly. This pandemic, which made contact-less communication culture in everyday life made the e-commerce market to be opened even to the consumers who would hesitate to purchase and pay by electronic device without any personal contacts and seeing or touching the real products. Consumers who have experienced the easy access and convenience of the online purchase would continue to take those advantages even after the pandemic. During this time of transformation, however, the size of information source for the consumers has become even shrunk into a flat screen and limited to visual only. To provide differentiated and competitive information on products, companies are adopting AR/VR and steaming technologies but the reviews from the honest users need to be recognized as important in that it is regarded as strong as the well refined product information provided by marketing professionals of the company and companies may obtain useful insight for product development, marketing and sales strategies. Then from the consumer's point of view, if the ratings of reviews are widely diverged how consumers would process the review information before purchase? Are non-converged ratings always unreliable and worthless? In this study, we analyzed how consumer's regulatory focus moderate the attitude to process the diverged information. This experiment was designed as a 2x2 factorial study to see how the variance of product review ratings (high vs. low) for cosmetics affects product attitudes by the consumers' regulatory focus (prevention focus vs. improvement focus). As a result of the study, it was found that prevention-focused consumers showed high product attitude when the review variance was low, whereas promotion-focused consumers showed high product attitude when the review variance was high. With such a study, this thesis can explain that even if a product with exactly the same average rating, the converged or diverged review can be interpreted differently by customer's regulatory focus. This paper has a theoretical contribution to elucidate the mechanism of consumer's information process when the information is not converged. In practice, as reviews and sales records of each product are accumulated, as an one of applied knowledge management types with big data, companies may develop and provide even reinforced customer experience by providing personalized and optimized products and review information.