• Journal of the Korea Convergence Society
• /
• v.12 no.1
• /
• pp.99-104
• /
• 2021

In this paper, we propose health risk management using feature extraction and cluster analysis considering time flow. The proposed method proceeds in three steps. The first is the pre-processing and feature extraction step. It collects user's lifelog using a wearable device, removes incomplete data, errors, noise, and contradictory data, and processes missing values. Then, for feature extraction, important variables are selected through principal component analysis, and data similar to the relationship between the data are classified through correlation coefficient and covariance. In order to analyze the features extracted from the lifelog, dynamic clustering is performed through the K-means algorithm in consideration of the passage of time. The new data is clustered through the similarity distance measurement method based on the increment of the sum of squared errors. Next is to extract information about the cluster by considering the passage of time. Therefore, using the health decision-making system through feature clusters, risks able to managed through factors such as physical characteristics, lifestyle habits, disease status, health care event occurrence risk, and predictability. The performance evaluation compares the proposed method using Precision, Recall, and F-measure with the fuzzy and kernel-based clustering. As a result of the evaluation, the proposed method is excellently evaluated. Therefore, through the proposed method, it is possible to accurately predict and appropriately manage the user's potential health risk by using the similarity with the patient.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_1
• /
• pp.1301-1314
• /
• 2022

Normalized Difference Vegetation Index (NDVI) is utilized as an indicator to represent the vegetation condition on the land surface in various applications such as land cover, crop yield, agricultural drought, soil moisture, and forest disaster. However, satellite optical sensors for visible and infrared rays cannot see through the clouds, so the NDVI of the cloud pixel is not a valid value for the land surface. This study proposed a real-time correction of the underestimation noise for GEO-KOMPSAT-2A (GK2A) daily NDVI and made sure its feasibility through the quantitative comparisons with Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI and the qualitative interpretation of time-series changes. The underestimation noise was effectively corrected by the procedures such as the time-series correction considering vegetation phenology, the outlier removal using long-term climatology, and the gap filling using rigorous statistical methods. The correlation with MODIS NDVI was higher, and the difference was lower, showing a 32.7% improvement compared to the original NDVI product. The proposed method has an extensibility for use in other satellite products with some modification.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.19 no.1
• /
• pp.19-26
• /
• 2017

Surface air temperature ($T_{air}$) is a key variable for the meteorology and climatology, and is a fundamental factor of the terrestrial ecosystem functions. Satellite remote sensing from the Moderate Resolution Imaging Spectroradiometer (MODIS) provides an opportunity to monitor the $T_{air}$. However, the several problems such as frequent cloud cover and mountainous region can result in substantial retrieval error and signal loss in MODIS $T_{air}$. In this study, satellite-based $T_{air}$ was estimated under both clear and cloudy sky conditions in Gangwon Province using Aqua MODIS07 temperature profile product (MYD07_L2) and GCOM-W1 Advanced Microwave Scanning Radiometer 2 (AMSR2) brightness temperature ($T_b$) at 37 GHz frequency, and was compared with the measurements from the Automated Mountain Meteorology Stations (AMOS). The application of ambient temperature lapse rate was performed to improve the retrieval accuracy in mountainous region, which showed the improvement of estimation accuracy approximately 4% of RMSE. A simple pixel-wise regression method combining synergetic information from MYD07_L2 $T_{air}$ and AMSR2 $T_b$ was applied to estimate surface $T_{air}$ for all sky conditions. The $T_{air}$ retrievals showed favorable agreement in comparison with AMOS data (r=0.80, RMSE=7.9K), though the underestimation was appeared in winter season. Substantial $T_{air}$ retrievals were estimated 61.4% (n=2,657) for cloudy sky conditions. The results presented in this study indicate that the satellite remote sensing can produce the surface $T_{air}$ at the complex mountainous region for all sky conditions.

• Journal of the Korean Society of Hazard Mitigation
• /
• v.7 no.5
• /
• pp.73-78
• /
• 2007

It has been increasing that significant loss of life and property due to global wanning and extreme weather, and the climate and temperature changes in Korea Peninsula are now greater than the global averages. Climate information from regional climate models(RCM) at a finer resolution than that of global climate models(GCM) is required to predictclimate and weather variability, changes, and impacts. The new surface boundary conditions(SBCs) development is motivated by the limitations and inconsistencies of existing SBCs that have influence on model predictability. A critical prerequisite in constructing SBCs is that the raw data should be accurate with physical consistency across all relevant parameters and must be appropriately filled for missing data if any. The aim of this study is to construct appropriate SBCs for the RCM in Asia domain which will be used for the prevention of disasters due to climate changes. As all SBCs have constructed onto the 30km grid-mesh of the RCM suitable for Asia applications, they can be also used for other distributed models for climate and hydrologic studies.

• Journal of Korea Technology Innovation Society
• /
• v.18 no.3
• /
• pp.387-415
• /
• 2015

In this study, we have proposed an estimation model of domestic market size using the linking between standard statistical classification systems, and reviewed the practical applicability of the model. The results of the mining and manufacturing survey of Statistics Korea conducted on the basis of KSIC (Korea Standard Industrial Classification) and Korea trade statistics based on HS (The Harmonized Commodity Description and Coding System; Harmonized System) classification were linked for the model by using the correspondence tables provided by Statistics Korea and United Nations Statistics Division. The most serious problem to adopt the integrated KSIC-ISIC-HS correspondence table for the estimation of domestic market size is the complex multiple linkages among KSIC and HS codes. In this study, we have suggested the method to divide the amount of trade corresponding to the HS codes linked to more than two ISIC codes based on the ratio of shipments corresponding to the ISIC codes as the weight. Then, it is possible to analyze the domestic market size of 125 ISIC codes in the manufacturing industry and to forecast the market size in the near future by using the model. Although the model has some limitations such as the difficulty in analysis on more subdivided items than ISIC items, the impossibility of the analysis on items in industries except for manufacturing, errors in the shipment due to some missing data, this study has significance in the sense that it provided the analysis method of domestic market size by using the most objective, reliable and sustainably useful data.

• The Journal of the Korea Contents Association
• /
• v.16 no.9
• /
• pp.51-65
• /
• 2016

The purpose of this study was to examine whether authentic leadership influenced positive psychological capital and change-oriented organizational citizenship behavior(CO-OCB) in airline service context. Moreover, this study was designed to test the mediating effect of positive psychological capital between authentic leadership and CO-OCB to provide fundamental and practical information for airline industry. A convenience sample of 390 flight attendants was surveyed and a total of 377 usable questionnaires were analyzed. Then hypotheses were tested using structural equation modelling(SEM). The results were as follows. Firstly, authentic leadership was divided into 'self-awarenese', 'relational transparency', internalized moral perspective' and 'balanced process'. Secondly, 'self-awarenese' and 'internalized moral perspective' influenced positive psychological capital. Thirdly, positive psychological capital influenced CO-OCB. Fourtjly, positive psychological capital had mediating effects partially between authentic leadership and CO-OCB.

• Journal of the Korean Data and Information Science Society
• /
• v.27 no.3
• /
• pp.587-598
• /
• 2016

In predicting an outcome of election using a variety of methods ahead of the election, non-response is one of the major issues. Therefore, to address the non-response issue, a variety of methods of non-response imputation may be employed, but the result of forecasting tend to vary according to methods. In this study, in order to improve electoral forecasts, we studied a model based method of non-response imputation attempting to apply the Monte Carlo Expectation Maximization (MCEM) algorithm, introduced by Wei and Tanner (1990). The MCEM algorithm using maximum likelihood estimates (MLEs) is applied to solve the boundary solution problem under the non-ignorable non-response mechanism. We performed the simulation studies to compare estimation performance among MCEM, maximum likelihood estimation, and Bayesian estimation method. The results of simulation studies showed that MCEM method can be a reasonable candidate for non-response model estimation. We also applied MCEM method to the Korean presidential election exit poll data of 2012 and investigated prediction performance using modified within precinct error (MWPE) criterion (Bautista et al., 2007).

• Journal of the Korean Data and Information Science Society
• /
• v.28 no.1
• /
• pp.109-117
• /
• 2017

This study aims to identify the effect for exercise intensity on hypertension using propensity score based on the sixth Korea National Health and Nutrition Examination Survey data and to provide an evidence for the most effective exercise intensity for prevention or treatment of hypertension. Specifically, we select 3,486 subjects who aged between 18 and 65 years after excluding some subjects who are expected to have limited athletic ability. We estimate propensity scores for exercise intensity based on the confounders such as sex, age, smoking, drinking, and natrium intake. Considering the complex survey design, we conduct a descriptive analysis and multiple logistic regression for hypertension with propensity score as a covariate. Although the results of the study did not show statistically significant relationship between exercise intensity and hypertension, we expect that it can be used as a basis evidence that the appropriate exercise of moderate intensity may be more effective for the prevention and treatment of hypertension rather than strong intensity exercise and non-exercise.

• Journal of the Korean Data and Information Science Society
• /
• v.26 no.5
• /
• pp.1061-1069
• /
• 2015

Recently, transportation big data generated in the transportation sector has been widely used in the transportation policies making and efficient system management. Bus passengers' mobility patterns are useful insight for transportation policy maker to optimize bus lines and time intervals in a city. We propose a new methodology to discover mobility patterns by using transportation card data. We first estimate the bus stations where the passengers get-off because the transportation card data don't have the get-off information in most cities. We then applies LDA (Latent Dirichlet Allocation), the most representative topic modeling technique, to discover mobility patterns of bus passengers in Cheong-Ju city. To understand discovered patterns, we construct a data warehouse and perform multi-dimensional analysis by bus-route, region, time-period, and the mobility patterns (get-on/get-off station). In the case of Cheong Ju, we discovered mobility pattern 1 from suburban area to Cheong-Ju terminal, mobility pattern 2 from residential area to commercial area, mobility pattern 3 from school areas to commercial area.

• Culinary science and hospitality research
• /
• v.19 no.2
• /
• pp.149-166
• /
• 2013

The purpose of this study is to investigate what influence the external variables of the RFID system for eco-friendly agricultural products such as reliability, safety, effectiveness and innovation have on ease and usefulness, perceived value and behavioral intention. An empirical analysis were conducted to the general consumers over the age of 20 years who live in Seoul and Gyeonggi areas having experience of buying eco-friendly agricultural products in department stores, supermarkets and eco-friendly agricultural product specialty stores from November 10 to November 23, 2012, A total of 350 copies of questionnaire were distributed for this research and, excluding partial ones that were too concentrated on one side or found missing values, a total of 305 copies(87.1%) were used as the final statistical analysis data. The result shows that such external variables of the RFID system for eco-friendly agricultural products as liability, safety, effectiveness and innovation are useful enough as a theoretical basis for later study on RFID systems for eco-friendly agricultural products. Also, it reveals that, since all the process from production to sale of agricultural products can be seen, the products are provided safely for consumers, are objectively and rapidly investigated when problems occur, induce a positive attitude with their historical information, and are supplied through systematic management such as consumers' rights to know and choose and recall of unfit products.