• KIPS Transactions on Software and Data Engineering
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• v.13 no.1
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• pp.1-16
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• 2024

Over recent years, 6 Sigma has become a key methodology in manufacturing for quality improvement and cost reduction. However, challenges have arisen due to the difficulty in analyzing large-scale data generated by smart factories and its traditional, formal application. To address these limitations, a big data-based 6 Sigma approach has been developed, integrating the strengths of 6 Sigma and big data analysis, including statistical verification, mathematical optimization, interpretability, and machine learning. Despite its potential, the practical impact of this big data-based 6 Sigma on manufacturing processes and management performance has not been adequately verified, leading to its limited reliability and underutilization in practice. This study investigates the efficiency impact of DX SS, a big data-based 6 Sigma, on manufacturing processes, and identifies key success policies for its effective introduction and implementation in enterprises. The study highlights the importance of involving all executives and employees and researching key success policies, as demonstrated by cases where methodology implementation failed due to incorrect policies. This research aims to assist manufacturing companies in achieving successful outcomes by actively adopting and utilizing the methodologies presented.

• Applied Chemistry for Engineering
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• v.35 no.3
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• pp.192-199
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• 2024

In this study, carbamazepine (CBZ) imprinted starch/PVA-based biomaterials were prepared by the casting method and UV irradiation, and their physicochemical properties, CBZ adsorption ability, and release properties were investigated. The surface properties of the prepared biomaterials were characterized using FE-SEM, while the stability of CBZ under UV irradiation and the functional groups of the biomaterials were characterized using FT-IR analysis. The adsorption properties of CBZ on the biomaterials were evaluated by binding isotherm and Scatchard plot. Results indicate that CBZ imprinted biomaterials possess a specific binding site of CBZ. To evaluate the applicability of the transdermal drug delivery system, the release properties of CBZ from prepared biomaterials using various pH buffers and artificial skin at 36.5 ℃ were investigated. Results indicated that the CBZ release at high pH was faster than at low pH. In addition, CBZ was released continuously for 12 h in the artificial skin test. The drug release mechanism of CBZ followed a pseudo-Fickian diffusion mechanism in buffer solution, whereas the release from artificial skin exhibited a non-Fickian diffusion mechanism.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.139-156
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• 2021

The biggest reason for using a deep learning model in image classification is that it is possible to consider the relationship between each region by extracting each region's features from the overall information of the image. However, the CNN model may not be suitable for emotional image data without the image's regional features. To solve the difficulty of classifying emotion images, many researchers each year propose a CNN-based architecture suitable for emotion images. Studies on the relationship between color and human emotion were also conducted, and results were derived that different emotions are induced according to color. In studies using deep learning, there have been studies that apply color information to image subtraction classification. The case where the image's color information is additionally used than the case where the classification model is trained with only the image improves the accuracy of classifying image emotions. This study proposes two ways to increase the accuracy by incorporating the result value after the model classifies an image's emotion. Both methods improve accuracy by modifying the result value based on statistics using the color of the picture. When performing the test by finding the two-color combinations most distributed for all training data, the two-color combinations most distributed for each test data image were found. The result values were corrected according to the color combination distribution. This method weights the result value obtained after the model classifies an image's emotion by creating an expression based on the log function and the exponential function. Emotion6, classified into six emotions, and Artphoto classified into eight categories were used for the image data. Densenet169, Mnasnet, Resnet101, Resnet152, and Vgg19 architectures were used for the CNN model, and the performance evaluation was compared before and after applying the two-stage learning to the CNN model. Inspired by color psychology, which deals with the relationship between colors and emotions, when creating a model that classifies an image's sentiment, we studied how to improve accuracy by modifying the result values based on color. Sixteen colors were used: red, orange, yellow, green, blue, indigo, purple, turquoise, pink, magenta, brown, gray, silver, gold, white, and black. It has meaning. Using Scikit-learn's Clustering, the seven colors that are primarily distributed in the image are checked. Then, the RGB coordinate values of the colors from the image are compared with the RGB coordinate values of the 16 colors presented in the above data. That is, it was converted to the closest color. Suppose three or more color combinations are selected. In that case, too many color combinations occur, resulting in a problem in which the distribution is scattered, so a situation fewer influences the result value. Therefore, to solve this problem, two-color combinations were found and weighted to the model. Before training, the most distributed color combinations were found for all training data images. The distribution of color combinations for each class was stored in a Python dictionary format to be used during testing. During the test, the two-color combinations that are most distributed for each test data image are found. After that, we checked how the color combinations were distributed in the training data and corrected the result. We devised several equations to weight the result value from the model based on the extracted color as described above. The data set was randomly divided by 80:20, and the model was verified using 20% of the data as a test set. After splitting the remaining 80% of the data into five divisions to perform 5-fold cross-validation, the model was trained five times using different verification datasets. Finally, the performance was checked using the test dataset that was previously separated. Adam was used as the activation function, and the learning rate was set to 0.01. The training was performed as much as 20 epochs, and if the validation loss value did not decrease during five epochs of learning, the experiment was stopped. Early tapping was set to load the model with the best validation loss value. The classification accuracy was better when the extracted information using color properties was used together than the case using only the CNN architecture.

• Journal of Korean Society of Forest Science
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• v.102 no.1
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• pp.82-89
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• 2013

Harvest is one of the major disturbances affecting the soil carbon (C) dynamics in forests. However, researches on the long-term impact of periodic harvest on the soil C dynamics are limited since they requires rigorous control of various factors. Therefore, we adopted a modeling approach to determine the long-term impacts of harvest interval, harvest intensity and post-harvest residue management on soil C dynamics by using the Korean Forest Soil Carbon model (KFSC model). The simulation was conducted on Pinus densiflora S. et Z. stands in central Korea, and twelve harvest scenarios were tested by altering harvest intervals (50, 80, and 100-year interval), intensities (partial-cut harvest: 30% and clear-cut harvest: 100% of stand volume), and the residue managements after harvest (collection: 0% and retention: 100% of aboveground residue). We simulated the soil carbon stock for 400 years for each scenario. As a result, the soil C stocks in depth of 30 cm after 400 years range from 50.3 to 55.8 Mg C $ha^{-1}$, corresponding to 98.1 to 108.9% of the C stock at present. The soil C stock under the scenarios with residue retention was 2.5-11.0% higher than that under scenarios with residue collection. However, there was no significant impact of harvest interval and intensity on the soil C stock. The soil C dynamics depended on the dead organic matter dynamics derived from the amount of dead organic matter and growth pattern after harvest.

• Journal of The Korean Association For Science Education
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• v.19 no.4
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• pp.604-621
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• 1999

We analyze the admission test problems used in 1998 at the Science Education Center for Gifted Youth at Kyungpook National University (SECGY, KNU). The test consists of two parts, an evaluation of the scientific thinking skills and an evaluation of the achievement for Mathematics and Sciences, the former of which includes evaluations of scientific process skills and logical thinking skills. The problems for the test of scientific thinking skills were developed and standardized by the Korea Education Development Center, while those of the achievement for Mathematics and Sciences were made at SECGY. We calculate the indices of the difficulty and discrimination for each problem to determine whether or not the test is appropriate to apply for selecting number of gifted students among the recommended students from 389 middle schools in Taegu-city and Kyungsang-pook-do Province. We find that both indices of most problems for the test of scientific thinking skills were out range of the appropriate level and. moreover, even those problems which fall into the appropriate range showed very low efficiencies for distractors. We, thus, conclude that the problems of the test of scientific thinking skills are inappropriate to use as a test for admission to SECGY. On the other hand, the problems of the achievement test showed extreme results; the Mathematics problems appeared to be too difficult, whereas the Physics problems appeared too easy. However, overall scores showed a normal distribution, indicating that those problems played crucial role in selecting gifted students. We finally propose several suggestions in developing the test problems and in selecting students at the SECGY.

• (The) Korean Journal of Educational Psychology
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• v.23 no.3
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• pp.645-663
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• 2009

The purpose of this study is to develop and verify a Korean Diagnostic Scale of Multiple Intelligence(MI), which will be an alternative test to avoid problems with former Shearer's MI test and to adopt H. Gardner's suggestions to develop MI assessment. The test is developed 5 types; kindergartner, elementary lower grader, elementary upper grader, middle schooler, high schooler test. A form of test is diversified with 3 types; multiple-choice items for accomplishment, true or false items for ability, and self-reported items with likert scale for interest and ability. According to H. Gardner's suggestions, we have tried to reanalyze key component of MI, analyze an overlapping or hierarchical relationship between intelligences, develop intelligences-fair items, diversify form of item. We have developed a final standardized test through a primary, secondary preliminary-test analysis, and sampled 5,585 students by age, gender, and regional groups. As a result of this sampling test, we can get a norm score and compare individuals with other's score relatively. To verify this test, we analyzed behavior observation, mean, standard deviation, a percentage of correct answers, reliability of each test type, correlation between intelligence scales, Kruskal-Wallis test of mean rank of career choice by intelligences. As a result of correlation analysis between sub-intelligence scales, we can conclude that this MI test is satisfied with intelligence independent assumption. Besides, as non-parametric statistics test(Kruskal-Wallis) of career choice by intelligences, we can identify that MI is related with domain of career choice. This test is not a linguistic and logical-mathematical biased test but a intelligences-fair test. It makes us compare individual's potential with a norm score. Besides, it could be useful as a means of educational prescription or counsel in comparison with ability, interest, and accomplishment of individual. But this test is limited to do factor or correlation analysis between types of sub-test, because items are minimized for a time-constraint and a heavy burden of test receiver. But if it could be tested with increased items by two sessions, further research could be expected to get over this constraints and do a further validation analysis.

• Journal of The Korean Association For Science Education
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• v.42 no.4
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• pp.417-428
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• 2022

This study analyzed the frequency and level of scientific practices presented in secondary science textbooks. A total of 1,378 student activities presented in 14 middle school science textbooks and 5 high school integrated science textbooks were analyzed, using the definition and level of scientific practice suggested in the NGSS. Findings show that most student activities focus on three practices. Compared to the textbooks for the previous science curriculum, the practice of 'obtaining, evaluating, and communicating information' was more emphasized, reflecting societal changes due to ICT development. However, the practice of 'asking a question', which can be an important element of student-led science learning, was still rarely found in textbooks, and 'developing and using models', 'using math and computational thinking' and 'arguing based on evidence' were not addressed much. The practices were mostly elementary school level except for the practice of 'constructing explanations'. Such repeated exposures to a few and low level of practices mean that many future citizens would be led to a naïve understanding of science. The findings imply that it is necessary to emphasize various practices tailored to the level of students. In the upcoming revision of the science curriculum, it is necessary to provide the definition of practices that are not currently specified and the expected level of each practice so that the curriculum can provide sufficient guidance for textbook writing. These efforts should be supported by benchmarking of overseas science curriculum and research that explore students' ability and teachers' understanding of scientific practices.

• Journal of Korean Home Economics Education Association
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• v.32 no.3
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• pp.81-96
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• 2020

This study aims to identify implications for the role of home economics in consumer education in middle schools focusing on building consumer competency. To this end, the content in middle school textbooks of home economics and other subjects, written according to the 2015 revised curriculum, were analyzed. This study examined consumer education content based on the consumer competency measurement index developed by the Korean Consumer Agency, and reviewed different foci presented by subjects. This study also investigated how the knowledge, attitude and practice, which are components of consumer competency, are presented. The major findings of this study can be summarized as follows: First, consumer competency content, presented in textbooks of home economics and other subjects, were comprised of citizenship competency(65.3%), transactional competency(27%), and financial competency(7.7%). Second, in terms of content on the consumer's citizenship competency, little attention was paid to consumer rights, revealing an imbalance between responsibilities and rights. Third, despite its importance, the "utilization of information and communications technology" in transaction competency, and "consumer participation" in citizenship competency are insufficiently covered in the home economics. Fourth, social studies was the subject that most extensively covered the content of consumer competency. In terms of scope, home economics dealt with most of the sub-fields. Fifth, even when the same content of consumer competency was covered, it was presented differently by subject. Sixth, there was a lack of connection between components of consumer competency-knowledge, attitude, and practice, with a disproportionately high emphasis on knowledge. In conclusion, this study concluded that consumer education content of middle school subjects is insufficient to enhance consumer competency.

• Journal of Food Hygiene and Safety
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• v.28 no.1
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• pp.7-12
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• 2013

This study presents the influence on growth properties determined using a novel predictive growth model of wild-type Salmonella spp. KSC 101 by variations in the temperature and time during cut packaging in cold, uncooked pork meat. The experiment performed for model development included an arrangement of different temperatures ($0^{\circ}C$, $5^{\circ}C$, $10^{\circ}C$, $15^{\circ}C$, and $20^{\circ}C$) and time durations (0, 1, 2, and 3 hours) that reflect actual pork-cut and packaging processes. No growth was observed at $0^{\circ}C$ and $5^{\circ}C$, whereas some growth was observed at $10^{\circ}C$, $15^{\circ}C$, and $20^{\circ}C$, with a mean increase of only 0.34 log CFU/g. The growth observed at $20^{\circ}C$ was more robust than that observed at $15^{\circ}C$, but the difference was not statistically significant (p > 0.05). However, compared with PMP (Pathogen Modeling Program), the wild-type Salmonella spp. KSC 101 showed a more rapid growth. We used the Gompertz 4 parameter equation as the primary model, and the exponential decay formula as the secondary model. The estimated $R^2$ values were 0.99 or higher. The developed model was evaluated by comparison of the experimental and predictive values, and the values were in agreement with the ${\pm}0.5$ log CFU/g, although the RMSE (Root mean square error) value was 0.103, which indicates a slight overestimation. Therefore, we suggest that the developed predictive growth model would be useful as a tool for evaluating sanitation criteria in pork cut-packaging processes.

• Korean Journal of Soil Science and Fertilizer
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• v.23 no.1
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• pp.8-14
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• 1990

Retardation and hydrodynamic dispersion coefficient necessary for model of water and solute movement in a soil were determined for horizontal soil column with different initial soil water conditions. The soil columns were compacted with sandy loam soil. The bulk density was $1,350+50kg/m^3$, and initial water contents were 0.05, 0.08 and 0.14. Advancement of 0.05% $CaSO_4$ solution was used as the standard and advancements of 0.5% KCl, $CaCl_2$ and $KH_2PO_4$ were compared. Retardation of non-reactive $Cl^-$ was related with the initial soil water content, ${\theta}n$, as ${\theta}/({\theta}-{\theta}n)$, and anion exclusion was ignored. Retardations of active $K^+$, $Ca^{{+}{+}}$ and $H_2PO_4{^-}$ were related as 1/(R+1) $^*{\theta}/({\theta}-{\theta}n)$, in which R was retardation coefficient. Measured R was 0.64 for $K^+$, 0.80 for $Ca^{{+}{+}}$ and 2.6 for $H_2PO_4{^-}$, respectively. Calculated R using Langmuir adsorption isotherm showed fair degree of applicability. Soil water diffusivity, $D({\theta}),m^2/sec$, calculated for different initial water content showed unique function as $$log(D({\theta}))=13.448{\theta}-9.288$$ Hydrodynamic dispersion coefficient of $Cl^-$ above soil water content 0.36 was similar to soil water diffusivity and decreased to near self diffusion coefficient at soil water content near 0.2. Those of $K^+$, $Ca^{{+}{+}}$ $H_2PO_4{^-}$ at soil water content of 0.38 were $5.5{\times}10^{-6}$, $2.4{\times}10^{-6}$ and $7.1{\times}10^{-7}m^2/sec$ and decreased rapidly with decreasing soil water content lower than 0.36.