• Journal of Nutrition and Health
• /
• v.53 no.6
• /
• pp.688-701
• /
• 2020

Purpose: This study was performed to evaluate the importance and satisfaction of the selective attributes of delivery food and to analyze the factors affecting customer satisfaction. Methods: A total of 574 responses were collected from customers who had ordered delivery food for data analysis. Statistical analyses were conducted using the SPSS program (ver. 25.0) for frequency analysis, χ2 tests, t-test, factor analysis, Pearson correlation, multiple regression analysis, and Importance-Performance Analysis (IPA). Results: The importance of delivery food selection attributes was higher in the order of 'hygiene control level (4.72)', 'taste of food (4.64)', and 'delivery accuracy (4.40)'. Satisfaction assessment was higher in the order of 'taste of food (4.32)', 'delivery accuracy (4.26)', and 'convenience of using the delivery app (4.21)'. According to the results of IPA, items that were priorities for improvement were charges for delivery, discount offers, sufficient description of the menu, and rapid handling of customer complaints. On an average, overall customer satisfaction score of delivery food was 4.01 out of 5 points. Additionally, five satisfaction factors were extracted by exploratory factor analysis. According to the results of multiple regression analysis, quality of delivery platform (p < 0.001), quality of delivery service (p < 0.001), convenience and diversity (p < 0.001), quality of delivery food (p < 0.001), and health and safety (p < 0.001) had significant positive effects on overall customer satisfaction. Conclusion: To increase customer satisfaction among delivery food customers, restaurant or delivery platform managers should consistently improve not only the quality of the delivery platform but also the quality of the delivery food and service.

• The Journal of Bigdata
• /
• v.5 no.2
• /
• pp.53-67
• /
• 2020

This study employees a supervised learning prediction model to detect nonconformity in advance of processed food manufacturing and processing businesses. The study was conducted according to the standard procedure of machine learning, such as definition of objective function, data preprocessing and feature engineering and model selection and evaluation. The dependent variable was set as the number of supervised inspection detections over the past five years from 2014 to 2018, and the objective function was to maximize the probability of detecting the nonconforming companies. The data was preprocessed by reflecting not only basic attributes such as revenues, operating duration, number of employees, but also the inspections track records and extraneous climate data. After applying the feature variable extraction method, the machine learning algorithm was applied to the data by deriving the company's risk, item risk, environmental risk, and past violation history as feature variables that affect the determination of nonconformity. The f1-score of the decision tree, one of ensemble models, was much higher than those of other models. Based on the results of this study, it is expected that the official food control for food safety management will be enhanced and geared into the data-evidence based management as well as scientific administrative system.

• Journal of Food Hygiene and Safety
• /
• v.35 no.6
• /
• pp.607-617
• /
• 2020

Human bio-monitoring (HBM) data is a very important resource for tracking total exposure and concentrations of a parent chemical or its metabolites in human biomarkers. However, until now, it was difficult to execute the integration of different types of HBM data due to incompatibility problems caused by gaps in study design, chemical description and coding system between different sources in Korea. In this study, we presented a standardized code system and HBM knowledge model (KM) based on relational database modeling methodology. For this purpose, we used 11 raw datasets collected from the Ministry of Food and Drug Safety (MFDS) between 2006 and 2018. We then constructed the HBM database (DB) using a total of 205,491 concentration-related data points for 18,870 participants and 86 chemicals. In addition, we developed a summary report-type statistical analysis program to verify the inputted HBM datasets. This study will contribute to promoting the sustainable creation and versatile utilization of big-data for HBM results at the MFDS.

• Journal of the Korean Institute of Traditional Landscape Architecture
• /
• v.41 no.1
• /
• pp.21-34
• /
• 2023

This study identified the materials and construction methods of 'Old Wall' in 13 villages which were designated as National Registered Cultural Heritage at the time of designation and examined the their structural changes based on field survey. The results are as follows: First, the 'Old Wall' consisted of 10 Soil-Stone Wall and 5 Stone Wall. At the time of designation, Stone Wall, which was built irregularly by dry-construction of natural stones, is similar in shape, but Soil-Stone Wall showed difference by the construction method of making used stones, joints, and faces. Second, the study extracted the changes of 'Old Wall' by repair and examined the changes of construction methods as well as the substitution and addition of materials of structure. The wall-roof was built with cement roof-tile and asbestos slate which have the advantage improve durability and cost-effectiveness. In addition, tile-mouth soil was added to korean traditional roof-tile to prevent rainwater from flowing in. Besides, to improve constructional convenience, the natural stone of the wall-body was replaced with blast stone, float stone and cut stone. Cement block, cement brick and cement mortar were frequently used to repair as well. As Soil-Stone Wall was transformed from irregular pattern-construction to comb pattern-construction and wet-construction was changed to dry-construction, it caused landscape and structural problems. Also, the layer of cement mortar applied to wall-foundation blocked the flow of rainwater that was induced by dry-construction of natural stones. Third, the study regarded that the problem with the repair of 'Old Wall' may occur as it is located in living space, because the owner of the wall could repair for the minor damages without technical knowledge. In addition, it is difficult for repair companies in charge of maintenance of Cultural Heritage to supply local materials, and it is differential construction specifications are not applied.

• Design Convergence Study
• /
• v.15 no.2
• /
• pp.347-368
• /
• 2016

Recently, researches for the word of mouth(WOM) imply that consumers use WOM informations of products in their purchase process. This study suggests methods using opinion mining and visualization to understand consumers' opinion of each goods and each markets. For this study we conduct research that includes developing domain ontology based on reviews confined to "movie" category because people who want to have watching movie refer other's movie reviews recently, and it is analyzed by opinion mining and visualization. It has differences comparing other researches as conducting attribution classification of evaluation factors and comprising verbal dictionary about evaluation factors when we conduct ontology process for analyzing. We want to prove through the result if research method will be valid. Results derived from this study can be largely divided into three. First, This research explains methods of developing domain ontology using keyword extraction and topic modeling. Second, We visualize reviews of each movie to understand overall audiences' opinion about specific movies. Third, We find clusters that consist of products which evaluated similar assessments in accordance with the evaluation results for the product. Case study of this research largely shows three clusters containing 130 movies that are used according to audiences'opinion.

• Design Convergence Study
• /
• v.15 no.5
• /
• pp.71-83
• /
• 2016

Interior panels are usually used in finishing of interior walls for not only decorative effects but also information transfer. According to designer's design placing interior panels may need repetitive tasks and the emphasis of this paper is to support an automation of these tasks. Considering the utilization characteristics of interior panels, we propose three method to present patterns by using bitmap image pixels and interior panels' shape changes, based on the theoretical consideration. In addition, in order to approve the possibility of the proposed methods, we have implemented the BIM based interior panels auto layout tool which applied one of the three methods to present patterns by using bitmap image pixel values and panel identification attributes. This tool also supports auto generation of quantity and panel arrangement sequence information that will be used in future construction phase. We expect that this approach will also be used in other decorative objects which require repetition of the basic units, such as floor tiles.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.1D
• /
• pp.145-151
• /
• 2009

Recently, the rapid development of GIS technology has made it possible to handle a various data associated with spatially hydrological parameters with their attribute information. Therefore, there has been a shift in focus from lumped runoff models to distributed runoff models, as the latter can consider temporal and spatial variations of discharge. This research is to evaluate the feasibility of GIS based distributed model using radar rainfall which can express temporal and spatial distribution in actual dam watershed during flood runoff period. K-DRUM (K-water hydrologic & hydaulic Distributed flood RUnoff Model) which was developed to calculate flood discharge connected to radar rainfall based on long-term runoff model developed by Kyoto- University DPRI (Disaster Prevention Research Institute), and Yondam-Dam watershed ($930km^2$) was applied as study site. Distributed rainfall according to grid resolution was generated by using preprocess program of radar rainfall, from JIN radar. Also, GIS hydrological parameters were extracted from basic GIS data such as DEM, land cover and soil map, and used as input data of distributed model (K-DRUM). Results of this research can provide a base for building of real-time short-term rainfall runoff forecast system according to flash flood in near future.

• Journal of Korean Historical Folklife
• /
• no.57
• /
• pp.197-228
• /
• 2019

This study was conducted under the judgement that there was a need to make several mentions by reference to studies about the spatial composition of the traditional village. The judgement was not about the dimension that there was a problem about the spatial composition of the existing village but that it would be effective to make a fresh reorganization of it in a little more detail. As a result, this study presented seven spaces in the spatial composition of the traditional village. It attempted to analyze it by dividing it into four spaces such as ① natural space, ② residential space and work space, ③ moving space and boundary space and ④ play space and ritual space to fit its basic nature. First of all, it made a pictorial presentation of the basic form of the spatial composition of the traditional farming village in the late Joseon Dynasty which was most general and whose form has been handed down up to the present. And it described the composition of each space accordingly. It was not intended for a specific village. So it presented the historical change, the behavior of the members surrounding the village and a difference according to the nature of the village, which were judged to be very important in explaining the items of the composition of each space. As a result, it was found that the spatial composition of the traditiona Korean village well embodied the framework of their life in terms of their view of nature, lifestyle and worldview. The view of nature acted on the spatial composition of the village as a whole and is well reflected in the natural space in particular. Their lifestyle is reflected in the residential space, farming space, moving space and play space, and their worldview is spcifically mirrored in the boundary space and ritual space. In particular, this study focused on how to take a look at the element of Feng-Shui in discussing the spatial composition of the village.

• Journal of Internet Computing and Services
• /
• v.24 no.5
• /
• pp.17-27
• /
• 2023

Today, as AI (Artificial Intelligence) technology develops and its practicality increases, it is widely used in various application fields in real life. At this time, the AI model is basically learned based on various statistical properties of the learning data and then distributed to the system, but unexpected changes in the data in a rapidly changing data situation cause a decrease in the model's performance. In particular, as it becomes important to find drift signals of deployed models in order to respond to new and unknown attacks that are constantly created in the security field, the need for lifecycle management of the entire model is gradually emerging. In general, it can be detected through performance changes in the model's accuracy and error rate (loss), but there are limitations in the usage environment in that an actual label for the model prediction result is required, and the detection of the point where the actual drift occurs is uncertain. there is. This is because the model's error rate is greatly influenced by various external environmental factors, model selection and parameter settings, and new input data, so it is necessary to precisely determine when actual drift in the data occurs based only on the corresponding value. There are limits to this. Therefore, this paper proposes a method to detect when actual drift occurs through an Anomaly analysis technique based on XAI (eXplainable Artificial Intelligence). As a result of testing a classification model that detects DGA (Domain Generation Algorithm), anomaly scores were extracted through the SHAP(Shapley Additive exPlanations) Value of the data after distribution, and as a result, it was confirmed that efficient drift point detection was possible.

• Journal of Family Resource Management and Policy Review
• /
• v.27 no.3
• /
• pp.67-75
• /
• 2023

This study will examine the changing nature of housework by analyzing participation in domestic work among 30-somethings according to generational and life cycle characteristics. To this end, 2,687 men and women in their 30s were taken from the 2020 Family Status Survey data, and a latent class analysis was conducted to categorize their participation in housework. The subjects were categorized into three groups: overall non-participation (18.05%), overall participation (59.96%), and intensive cleaning participation (21.99%). Gender, employment status, family life cycle, and attitudes about gender roles were significantly related to participation in housework. Men were more likely to be in the overall non-participation group, while women were more likely to be in the overall participation group. Individuals in the pre-formative period of the family life cycle were more likely to be in the overall non-participation group, while those in the formative and expanding periods were more likely to be in the overall participation group. The results of this study suggest that gender inequality in housework is common in the younger generation; the results also show that, in the same generation, individual participation in housework differs according to family life cycle.