• Korean Journal of Community Nutrition
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• v.27 no.3
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• pp.223-244
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• 2022

Objectives: This study was designed to investigate the relationship between metabolic risk factors, Index of Nutrition Quality, and the dietary quality index score of Korean adults. Methods: The subjects were 18,652 Korean adults aged 19 years or older (7,899 males, 10,753 females) who participated in the 2016-2019 Korea National Health and Nutrition Examination Survey. Subjects were divided into normal, pre-metabolic syndrome, and metabolic syndrome (MetS) groups according to the number of their metabolic risk factors. Data were analyzed using the SPSS program. Results: About 44.7% of men in the MetS group were at least college graduates (P < 0.001), whereas 52.0% of women in the MetS group were middle school graduates or lower (P < 0.001). The frequency of fruit and dairy products intake tended to decrease as the number of metabolic risk factors increased in both men and women (P for trend < 0.001). As the number of metabolic risk factors decreased, the frequency of grain intake tended to decrease in men (P for trend < 0.001) while the frequency of intake of red meat (P for trend = 0.001), poultry (P for trend < 0.001), and eggs (P for trend < 0.001) decreased in women. The total scores of Diet Quality Index-International (DQI-I) (men P < 0.001, women P < 0.01) and Korean Healthy Eating Index (KHEI) (men and women P < 0.001) were significantly lower in the MetS group compared to the other groups, and the total score of DQI-I and KHEI tended to decrease as the number of metabolic risk factors increased. Conclusions: Dietary quality evaluation using various indices can provide more information on the dietary problems related to metabolic risk factors. Nutrients and foods that have been confirmed to be related to metabolic risk factors can be used to develop dietary guidelines for the nutritional management of metabolic diseases.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.55-58
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• 2024

In this paper, we propose a design and implementation of big data-based fine dust anomaly detection machine learning system. The proposed is system that classifies the fine dust air quality index through meteorological information composed of fine dust and big data. This system classifies fine dust through the design of an anomaly detection algorithm according to the outliers for each air quality index classification categories based on machine learning. Depth data of the image collected from the camera collects images according to the level of fine dust, and then creates a fine dust visibility mask. And, with a learning-based fingerprinting technique through a mono depth estimation algorithm, the fine dust level is derived by inferring the visibility distance of fine dust collected from the monoscope camera. For experimentation and analysis of this method, after creating learning data by matching the fine dust level data and CCTV image data by region and time, a model is created and tested in a real environment.

• Journal of Korean Society on Water Environment
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• v.27 no.6
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• pp.794-803
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• 2011

Self Organizing Map (SOM) was applied for pattern classification of hydrological and water quality data measured at Jangseong Reservoir on a monthly basis. The primary objective of the present study is to understand better data characteristics and relationship between the data. For the purpose, two SOMs were configured by a methodologically systematic approach with appropriate methods for data transformation, determination of map size and side lengths of the map. The SOMs constructed at the respective measurement stations for water quality data (JSD1 and JSD2) commonly classified the respective datasets into five clusters by Davies-Bouldin Index (DBI). The trained SOMs were fine-tuned by Ward's method of a hierarchical cluster analysis. On the one hand, the patterns with high values of standardized reference vectors for hydrological variables revealed the high possibility of eutrophication by TN or TP in the reservoir, in general. On the other hand, the clusters with low values of standardized reference vectors for hydrological variables showed the patterns with high COD concentration. In particular, Clsuter1 at JSD1 and Cluster5 at JSD2 represented the worst condition of water quality with high reference vectors for rainfall and storage in the reservoir. Consequently, SOM is applicable to identify the patterns of potential eutrophication in reservoirs according to the better understanding of data characteristics and their relationship.

• Journal of Korean Society on Water Environment
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• v.35 no.5
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• pp.425-431
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• 2019

Recently, people have been attracting attention to the good quality of water resources as well as water welfare. to improve the quality of life. This study is a papers on the prediction of benthic macroinvertebrate index (BMI), which is a aquatic ecological health, using the machine learning based CFS (Correlation-based Feature Selection) method and the random forest model to compare the measured and predicted values of the BMI. The data collected from the Han River's branch for 10 years are extracted and utilized in 1312 data. Through the utilized data, Pearson correlation analysis showed a lack of correlation between single factor and BMI. The CFS method for multiple regression analysis was introduced. This study calculated 10 factors(water temperature, DO, electrical conductivity, turbidity, BOD, $NH_3-N$, T-N, $PO_4-P$, T-P, Average flow rate) that are considered to be related to the BMI. The random forest model was used based on the ten factors. In order to prove the validity of the model, $R^2$, %Difference, NSE (Nash-Sutcliffe Efficiency) and RMSE (Root Mean Square Error) were used. Each factor was 0.9438, -0.997, and 0,992, and accuracy rate was 71.6% level. As a result, These results can suggest the future direction of water resource management and Pre-review function for water ecological prediction.

• Korean Journal of Artificial Intelligence
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• v.7 no.1
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• pp.23-59
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• 2019

The purpose of this study is to develop a measure of service quality in the traditional market by examining previous research on the service quality of the traditional market studied so far. After defining basic concepts through definition of traditional market and existing studies, 5 categories of configuration items for SERVQUAL measurement in traditional market were made up based on existing researches related to definition of service quality and service quality of traditional market. A survey was conducted on the items that fit the intention of this study and various statistical analyzes were conducted. Statistical analysis was performed using SPSS 22.0 and AMOS 22.0. The reliability of the items was measured by the reliability test, and the predictability and accuracy of the items were examined. The validity of the measured variables was verified through confirmatory factor analysis. Reliability, empathy, responsiveness, certainty, and tangibility were the most important factors in this study. Responsiveness factors include communication, time reduction, real time, promptness. Assurance factors include the assurance of delivery, prompt answers, product knowledge items. Tangibility factors include, convenient device systems, location information, presence as a fact, and as a result, the latest modern items are adopted. The quality of service in the traditional market developed in this study was found to be good in reliability and validity test. Confirmatory factor analysis result using structural equation model also met the conformity index standard. If service satisfaction is measured based on this research, basic data can be presented to policy makers who implement policies on traditional markets to make the right decisions. In addition, it will be able to provide traditional market operators with operational strategy and marketing data. In the future, based on the traditional market service quality scale developed in this study, it is necessary to grasp the factors to be continuously managed to improve the service quality of the traditional market, user satisfaction, and intention to use.

• The Journal of Industrial Distribution & Business
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• v.9 no.11
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• pp.7-15
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• 2018

Purpose - This study surveys factors such as lifestyles, nutritional status, physical indicators, and physical fitness levels that affect the health of seniors over the age of 65 and based on the collected data attempts to create a senior health index model that provides health service information, help support seniors' successful aging, and improve their quality of life. Research design, data, and methodology - This paper conducted the development for senior health index model and the cross validity verification to examine the status of senior health level, and aimed at setting the health status evaluation criteria. Seniors 384 usable data were analyzed. Results - As an attempt to segment the senior health service market, I divided the results of this study based on measurability, accessibility, disparity between groups, and the size of the potential client base. I divided the senior market into five subgroups: very healthy, healthy, normal, weak, and very weak. Conclusions - The findings of this study may prove useful in preparing for the forthcoming super-aged society through segmentation of the senior market, understanding differences between groups with different health conditions, and discovering effective marketing strategies that meet the demands of different senior groups.

• Asia pacific journal of information systems
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• v.13 no.2
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• pp.23-46
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• 2003

This paper proposes an analysis methodology that enables the establishment of improved customer satisfaction via decision support system using customer satisfaction index data and customer database of a company. The proposed methodology establishes rational future goal of a company by applying DEA, finds potential customers which correspond to demographic features of the previous target group, and improve quality factors which distinguish the quality-satisfaction-group from the quality-dissatisfaction-group through the use of machine learning tools, SOM and C4.5. Finally, we illustrate the effectiveness of our research methodology using actual data of a camera company.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.134-140
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• 2021

Big data has recently been used in various industries such as tourism, medical care, distribution, and marketing. And it is evolving to the stage of collecting real-time information or analyzing correlations and predicting the future. In the tourism industry, big data can be used to identify the size and shape of the tourism market, and by building and utilizing a large-capacity database, it is possible to establish an efficient marketing strategy and provide customized tourism services for tourists. This paper has begun with anticipation of the effects that would occur when big data is actively used in the tourism field. Because the method of use must have applicability and practicality, the spatial scope will be limited to Seosan, Chungcheongnam-do, and research will be conducted. In this paper, to improve the quality of tourism courses by collecting and analyzing the number of mention data and sentiment index data on social media, which reflect the tourist's interest, preference and satisfaction. Therefore, it is used as basic data necessary for the development of new local tourism courses in the future. In addition, the development of tourism courses will be able to promote tourism growth and also revitalizing the local economy.

• Korean Journal of Ecology and Environment
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• v.41 no.4
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• pp.490-498
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• 2008

This study was to analyze fish composition and ecological indicator characteristics from eight sampling sites of Geum River, October 2007. Total number of family and species sampled were 9 and 40. The most dominant family was Cyprinidae (27 species, 85%), and then followed by Cobitidae, Odomtobutidae, and Gobiidae. Constancy values of Zacco platypus and Zacco temminckii were 1.00 and 0.30, respectively, and the relative abundance of Acheilognathus koreensis and Pseudogobio esocinus were greater than 5% of the total. The number of Korean endemic species sampled in this Geum River study was 7 family 19 species, which is 47.5% of total 40 species, and endangered species of Pseudopungtungia nigra and Gobiobotia brevibarba were only 0.5% of the total and these species were only distributed within the upstream regions. Exotic species, Micropterus salmoides, which is known as large-mouth bass, were observed in two sites of G3 and G7. Analytical results of fish community showed that community dominance index was 0.19, which is low, and the species evenness index (0.74), diversity index (2.03), and richness index (3.00) appeared high. These results indicate that structure of fish community is stable in the Geum River. According to various guilds analysis, the relative abundance of tolerant and omnivores at all sites were 40% and 47% of the total, respectively. This monitoring data may contribute changes of fish fauna and compositions in relation to habitat modifications and chemical water quality degradations in the future.

• Earthquakes and Structures
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• v.11 no.4
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• pp.629-648
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• 2016

This paper deals with 111 buildings built between 1962 and 1987, from various parts of the city of Osijek, for which, through the collection of documentation, a database is created. The aim of this paper is to provide the first steps in assessing seismic risk in Osijek applying method based on vulnerability index. This index uses collected information of parameters of the building: the structural system, the construction year, plan, the height, i.e., the number of stories, the type of foundation, the structural and non-structural elements, the type and the quality of main construction material, the position in the block and built-up area. According to this method defining five damage states, the action is expressed in terms of the macroseismic intensity and the seismic quality of the buildings by means of a vulnerability index. The value of the vulnerability index can be changed depending on the structural systems, quality of construction, etc., by introducing behavior and regional modifiers based on expert judgments. Since there is no available data of damaged buildings under earthquake loading in our country, we will propose behavior modifiers based on values suggested by earlier works and on judgment based on available project documentation of the considered buildings. Depending on the proposed modifiers, the seismic vulnerability of existing buildings in the city of Osijek will be assessed. The resulting vulnerability of the considered residential buildings provides necessary insight for emergency planning and for identification of critical objects vulnerable to seismic loading.