• Journal of Information Processing Systems
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• v.17 no.1
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• pp.136-150
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• 2021

The modern market is highly competitive. It has progressed from traditional competition between enterprises to competition between supply chains. To ensure that enterprise can form the best strategy consistently, it is necessary to evaluate the trust of other enterprises in the supply chain. First, this paper analyzes the background and significance of supply chain trust research, analyzes and expounds on the qualitative and quantitative methods of supply chain trust evaluation, and summarizes the research in this field. Analytic hierarchy process (AHP) is the most frequently used method in the literature to evaluate and rank criteria through data analysis. However, the input data for AHP analysis is based on human judgment, and hence there is every possibility that the data may be vague to some extent. Therefore, in view of the above problems, this study improves the global trust method based on chain iteration. The improved global trust evaluation method based on chain iteration is more flexible and practical, hence, it can more accurately evaluate supply chain trust. Finally, combined with an actual case of Zhaoxian Chengji Food Co. Ltd., the paper qualitatively analyzes the current situation of supply chain trust management and effectively strengthens the supervision of enterprises to cooperative enterprises. Thus, the company can identify problems on time and strategic adjustments can be implemented accordingly. The effectiveness of the evaluation method proposed in this paper is demonstrated through a quantitative evaluation of its trust in downstream enterprise A. Results suggest that the subjective preferences of and historical transactions together affect the final evaluation of trust.

• International Journal of Concrete Structures and Materials
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• v.6 no.2
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• pp.87-100
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• 2012

The process of selecting a repair material is a typical one of multi-criteria decision-making (MCDM) problems. In this study Analytical Hierarch Process was applied to solve this MCDM problem. Many factors affecting a process to select an optimal repair material can be classified into quantitative and qualitative requirements and this study handled only quantitative items. Quantitative requirements in the optimal selection model for repair material were divided into two parts, namely, the required chemical performance and the required physical performance. The former is composed of alkali-resistance, chloride permeability and electrical resistivity. The latter is composed of compressive strength, tensile strength, adhesive strength, drying shrinkage, elasticity and thermal expansion. The result of the study shows that this method is the useful and rational engineering approach in the problem concerning the selection of one out of many candidate repair materials even if this study was limited to repair material only for chloride-deteriorated concrete.

• Journal of Korean Tunnelling and Underground Space Association
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• v.14 no.1
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• pp.23-35
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• 2012

Due to the convenience, RMR has been widely applied in civil engineering works such as tunnel, slope, and so on. Many researchers have studied to suggest more simple and trustable RMR by modifying its parameters. However, those researches have just focused on looking for easy modified-RMRs by reducing number of parameters using various statistical analyses. Therefore, this research studied questions of modified-RMRs and gaps between RMR and its parameters. Approximately 2,000 parameters of 400 RMRs from various tunnel sites were normalized respectively and compared with one another to study their relations and divergences. The comparison results showed that there were common patterns among RMR and parameters. Data of uniaxial compressive strength and RQD, qualitative parameters, were located in upper side of RMR line. Discontinuity condition and ground water, quantitative oriented parameters, were opposite to them. It means if both qualitative and quantitative parameters can be properly combined then it can be easy to make simple and easy modified-RMRs without using difficult statistics. This results also show that the majority of field engineers used to estimate RMR conservatively when they did quantitative oriented parameters.

• Journal of Fashion Business
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• v.12 no.6
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• pp.34-45
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• 2008

This research was designed to find decision factors through color assortment planning process by Korean women's clothing merchandisers and to look for if there exists difference with American women's clothing merchandisers. A merchandise assortment is a collection of various quantities of styles, colors, sizes, and prices of related merchandise, usually grouped under one classification within a department. The subjects were 20 women's clothing merchandisers who work for clothing retail stores from 5 to 22 years in US and Korea. The authoring process was done for qualitative data analysis. The decision factors of color assortment planning were identified with four stages; information search, qualitative evaluation, quantitative evaluation, and selection. There were differences of color assortment decision factors due to different business types, business sizes, fashion-ability, sourcing ways, and merchandise turnover. Noticeable color assortment decision factor differences caused by country difference were not found except considering the target market ethnicity and skin color in US market. Korea merchandisers seem to be more sensitive to present sales data usages and spot order availability in color assortments because of more local production use than American merchandisers.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.25 no.6
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• pp.23-35
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• 2002

The problem of system reliability is very important issue in the digitalized nuclear power plant, because the failure of its system brings about extravagant economic loss, environment destruction, and fatal damage of human. Therefore the purpose of this study has developed the reliability evaluation model through the scoring model by the quantitative and qualitative factors in order to justify the evaluation considering the advanced safety factors in the Advanced Pressurized water Reactor 1400MWe(APR 1400MWe) under uncertainty. Especially, the qualitative factors considering the human, information control, and quality factors for the systematic and rational justification have been closely analyzed. The proposed model can be simply applied in real fields in order to minimize the industrial accidents in the digitalized nuclear power plant.

• Journal of Wetlands Research
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• v.17 no.3
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• pp.209-220
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• 2015

This study has improved the existed physical disturbance evaluation assessment technique in a river and analysed its applicability. The improvements are the quantitative evaluation items instead of qualitative one by providing the background and their evaluation equations, corresponding detailed itemization of evaluation score, and the direct input of hydraulic characteristics and geometrical changes by numerical simulation. In order to confirm the applicability of improved disturbance evaluation technique, the comparison and analysis between the evaluation results of existed and improved techniques have been carried out by applying to the 6 cases of natural, urban, and mountainous streams. Direct input of numerical simulation results of HEC-RAS enables the evaluation simple for 8 evaluation items excluding the items of habitat environment and bottom substrate. The improved disturbance evaluation technique, which evaluates the degree of disturbance sensitively by the quantitative and detailed itemized evaluations, has been confirmed the appropriate applicability by applying to river systems.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.909-914
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• 2024

This study suggests a quantitative evaluation of transfer learning, which is widely used in various AI fields, including image recognition for robot vision. Quantitative and qualitative analyses of results applying transfer learning are presented, but transfer learning itself is not discussed. Therefore, this study proposes a quantitative evaluation of transfer learning itself based on MNIST, a handwritten digit database. For the reference network, the change in recognition accuracy according to the depth of the transfer learning frozen layer and the ratio of transfer learning data and pre-training data is tracked. It is observed that when freezing up to the first layer and the ratio of transfer learning data is more than 3%, the recognition accuracy of more than 90% can be stably maintained. The transfer learning quantitative evaluation method of this study can be used to implement transfer learning optimized according to the network structure and type of data in the future, and will expand the scope of the use of robot vision and image analysis AI in various environments.

• Korean Journal of Soil Science and Fertilizer
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• v.33 no.4
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• pp.221-233
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• 2000

Evaluation method of soil fertility by application of geographic information system (GIS) which includes landscape characteristics and soil map data was investigated from productivities of red pepper and tobacco grown on the fields with no fertilization. Total 131 fields experiments, 64 fields of red pepper and 67 fields of tobacco were conducted from 22 and 23 fields for red pepper and tobacco, respectively, located at Cheangweon and Eumseong counties in 1996, from 20 and 25 fields at Boeun and Goesan counties in 1997, and 22 and 19 fields at Jincheon and Chungju counties in 1998. All the experimental sites were selected on the basis of wide range of distribution in landscape and soil attributes. Dry weights and nutrients (N, P and K) uptakes by red pepper plant and tobacco leaves were considered as basic fertility of the soil (BFS). The BFS was estimated by twenty-five independent variables including 13 chemical properties and 12 GIS data. Twenty-five independent variables were classified by two groups, 15 quantitative variables and 10 qualitative variables, and were analyzed by multiple linear regression (MLR) of REG and GLM models of SAS. Dry weight of red pepper (DWRP) and dry weight of tobacco leaves (DWTL) every year showed high variations by five times in difference plots with minimum yield and maximum yield indicating the diverse soil fertility among the experimental fields. Evaluation for the BFS by the MLR including independent variables was better than that by simple regression showing gradual improvement by adding chemical properties, quantitative variables, and qualitative variables of the GIS. However the evaluation for the BFS by the MLR showed the better result for tobacco than red pepper. For example the variability in the DWTL by MLR was explained 34.2% by only chemical properties, 35.0% by adding quantitative variables, and 72.5% by adding both the quantitative and qualitative variables of the GIS compared with 21.7% by simple regression with $NO_3-N$ content in soil. Consequently, it is assumed that this approach by the MLR including both the quantitative and qualitative variables was available as an evaluation model of soil fertility for upland field.

• International Journal of Air-Conditioning and Refrigeration
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• v.9 no.2
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• pp.62-68
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• 2001

It is a serous subject for energy conservation to prevent the energy loss caused by the mixture of heated and cooled air jets in perimeter and interior zone of a building operated with tow kinds of air-conditioning system simultaneously. The purpose of this paper is to clarify the quantitative and qualitative mechanisms of mixing loss and to propose a evaluation method for it. By using the dynamic heat load calculation, heat extraction load of a typical office building in Busan are calculated. According to the results, numerical simulations based on CFD(Computational Fluid Dynamics) were performed in order to evaluate mixing loss in the physical size of HVAC system. Then, the distributions of air temperature and airflow patterns according to the differences of set-point temperature are analyzed to grasp relations how to influence mixing loss.

• Journal of Biomedical Engineering Research
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• v.44 no.3
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• pp.182-189
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• 2023

CT is a medical device that acquires medical images based on Attenuation coefficient of human organs related to X-rays. In addition, using this theory, it can acquire sagittal and coronal planes and 3D images of the human body. Then, CT is essential device for universal diagnostic test. But Exposure of CT scan is so high that it is regulated and managed with special medical equipment. As the special medical equipment, CT must implement quality control. In detail of quality control, Spatial resolution of existing phantom imaging tests, Contrast resolution and clinical image evaluation are qualitative tests. These tests are not objective, so the reliability of the CT undermine trust. Therefore, by applying an artificial intelligence classification model, we wanted to confirm the possibility of quantitative evaluation of the qualitative evaluation part of the phantom test. We used intelligence classification models (VGG19, DenseNet201, EfficientNet B2, inception_resnet_v2, ResNet50V2, and Xception). And the fine-tuning process used for learning was additionally performed. As a result, in all classification models, the accuracy of spatial resolution was 0.9562 or higher, the precision was 0.9535, the recall was 1, the loss value was 0.1774, and the learning time was from a maximum of 14 minutes to a minimum of 8 minutes and 10 seconds. Through the experimental results, it was concluded that the artificial intelligence model can be applied to CT implements quality control in spatial resolution and contrast resolution.