• Korean Journal of Food Science and Technology
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• v.53 no.4
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• pp.501-508
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• 2021

The purpose of this study was to evaluate the application of ATP bioluminescence assay for effect assessment of hygiene visiting education on children's foodservice facilities in the local small town. The sanitary inspection results of the hygiene visiting education showed significant improvement in all items except 'To regularly disinfect cooking facilities, storage rooms, etc.' ATP bioluminescence analysis was performed on cooking utensils to evaluate the educational effect, and the results showed a correlation with the effect in most items. In the case of knives and cutting boards, all facilities showed a value of 20 RLU/cm² or less after the educational support, and in particular, it was approximately 10 RLU/cm² or less in national/public, corporation and private facilities. Correlation analysis between the post-education sanitary inspection results and ATP values for three items related to knives and cutting boards showed that they have a negative and high correlations.

• Korean Journal of Remote Sensing
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• v.32 no.2
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• pp.105-118
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• 2016

The purpose of this study is to improve the classification system of sub-divided land cover map among the land cover maps provided by the Ministry of Environment. To accomplish the purpose, first, the overseas country land cover map classification items were examined in priority. Second, the area ratio of each item established by applying the previous sub-divided classification system was analyzed. Third, the survey on the improvement of classification system targeting the users (experts and general public) who actually used the sub-divided land cover map was carried out. Fourth, a new classification system which improved the previous system by reclassifying 41 classification items into 33 items was finally established. Fifth, the established land cover classification items were applied on study area, and the land cover classification result according to the improvement method was compared with the previous classification system. Ilsan area in Goyang city where there are diverse geographic features with various land surface characteristics such as the urbanization area and agricultural land were distributed evenly were selected as the study area. The basic images used in this study were 0.25 m aerial ortho-photographs captured by the National Geographic Information Institute (NGII), and digital topographic map, detailed stock map plan, land registration map and administrative area map were used as the relevant reference data. As a result of applying the improved classification system into the study area, the area of culture-sports, leisure facilities was $1.84km^2$ which was approximately more than twice larger in comparison to the previous classification system. Other areas such as transportation and communication system and educational administration facilities were not classified. The result of this study has meaningful significance that it reflects the efficiency for the establishment and renewal of sub-divided land cover map in the future and actual users' needs.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.343-350
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• 2024

Since the release of Meta's Segment Anything Model (SAM), a large-scale vision transformer generation model with rapid image segmentation capabilities, several studies have been conducted to apply this technology in various fields. In this study, we aimed to investigate the applicability of SAM for water bodies detection and extraction using the QGIS Geo-SAM plugin, which enables the use of SAM with satellite imagery. The experimental data consisted of Compact Advanced Satellite 500 (CAS500)-1 images. The results obtained by applying SAM to these data were compared with manually digitized water objects, Open Street Map (OSM), and water body data from the National Geographic Information Institute (NGII)-based hydrological digital map. The mean Intersection over Union (mIoU) calculated for all features extracted using SAM and these three-comparison data were 0.7490, 0.5905, and 0.4921, respectively. For features commonly appeared or extracted in all datasets, the results were 0.9189, 0.8779, and 0.7715, respectively. Based on analysis of the spatial consistency between SAM results and other comparison data, SAM showed limitations in detecting small-scale or poorly defined streams but provided meaningful segmentation results for water body classification.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.139-147
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• 2023

As heavy precipitation rates have increased due to climate change, the risk of landslides has also become greater. Studies in the field of disaster risk assessment predominantly focus on evaluating intrinsic importance represented by the use or role of facilities. This work, however, focused on evaluating risks according to the external conditions of facilities, which were presented via debris flow simulation. A random walk model (RWM) was partially improved and used for the debris flow simulation. The existing RWM algorithm contained the problem of the simulation results being overly concentrated on the maximum slope line. To improve the model, the center cell height was adjusted and the inertia application method was modified. Facility information was collected from a digital topographic map layer. The risk level of each object was evaluated by combining the simulation result and the digital topographic map layer. A risk assessment technique suitable for the polygon and polyline layers was applied, respectively. Finally, by combining the evaluated risk with the attribute table of the layer, a system was prepared that could create a list of objects expected to be damaged, derive various statistics, and express the risk of each facility on a map. In short, we used an easy-to-understand simulation algorithm and proposed a technique to express detailed risk information on a map. This work will aid in the user-friendly development of a debris flow risk assessment system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.687-693
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• 2006

Image co-registration is the process of overlaying two images of the same scene, one of which represents a reference image, while the other is geometrically transformed to the one. In order to improve efficiency and effectiveness of the co-registration approach, the author proposed a pre-qualified area matching algorithm which is composed of feature extraction with canny operator and area matching algorithm with cross correlation coefficient. For refining matching points, outlier detection using studentized residual was used and iteratively removes outliers at the level of three standard deviation. Throughout the pre-qualification and the refining processes, the computation time was significantly improved and the registration accuracy is enhanced. A prototype of the proposed algorithm was implemented and the performance test of 3 Landsat images of Korea. showed: (1) average RMSE error of the approach was 0.435 pixel; (2) the average number of matching points was over 25,573; (3) the average processing time was 4.2 min per image with a regular workstation equipped with a 3 GHz Intel Pentium 4 CPU and 1 Gbytes Ram. The proposed approach achieved robustness, full automation, and time efficiency.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.11
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• pp.357-366
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• 2017

This study was conducted to identify the diabetes self-care (DSM) knowledge, DSM competence, DSM behavior, and quality of life according to HbA1c control in diabetic elderly. The participants were 205 diabetes elderly who visited the citizen health promotion center located in D city, Korea. Data were collected from April, 4 to August 31 2015, and were analyzed by the t-test and chi-squared test using IBM SPSS 23.0. The mean scores of DSM knowledge, DSM competence, DSM behavior and quality of life were $50.61{\pm}16.39$, $71.27{\pm}10.21$, $62.78{\pm}1.29$ and $0.86{\pm}0.11$, respectively. Additionally, DSM behavior (t=2.17, p=0.031), education level (t=11.80, p=0.0019) l, BMI (t=0.001, p=0.012), and number of visits to citizen health center (t=16.497, p=0.001) differed significantly between the controlled HbA1c group and uncontrolled HbA1C group. However, ANCOVA revealed that the level of HbA1c did not affect the DSM behaviors. Therefore, it is necessary to develop and apply a DSM education program that reflects the characteristics knowledge level of the elderly. In addition, healthcare institutions with high accessibility in terms of distance and cost to guide and manage desirable diabetic self-care behaviors should be provided everywhere.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.2
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• pp.57-68
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• 2004

Recently in order to more effectively and scientifically process forest official tasks, which have been focused on documents and inventories, they should be applied with the up-to-date spatial information technologies. Especially, the forest resource information management based on GIS(geographic information system) and aerial orthophoto is expected not only to play an important role as DSS(decision support system) for domestic forest conservation policy and forestry development industry but also to service forest resource information toward people such as the owners of a mountain rapidly. In this study, the important forest information such as digital topography map, digital forest type map, digital forest cadastral map, digital aerial photographs and attribute data were first reprocessed and constructed in DBMS(data base management system). In addition, forest officials could analyze and retrieve forest information by using detail sub-application systems such as forest cadastral retrieval, forest land development information management, reserved forest information management and forest resource information retrieval. For this, the user interface is developed by using Visual Basic 6.0 and MapObjects 2.1 of ESRI based on CBD(component based development) technology. The result of developing this system will not only perform constructing economical forest and better environment but also be the foundation of domestic spatial technology for forest resource management.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.194-205
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• 2006

The purpose of this study is to develop a pedestrian multi-agent model and simulation system using multi-agent theory, which may be utilized as a planning support system for building a comfort and safe environment of pedestrian street. Differing from existing pedestrian models, however, every single pedestrian was regarded as an individual agent in the model. Multiple agents like multiple pedestrians in the street then maintain their own characteristics and respond to surrounding environment. In addition their moving behavior are made by their own decision rules that they have or had acquired through the interactive communications or learning between agents like real world. After verifying the model validation, as the $R^2$ between the predicted value and observed value was up to 0.781, the developed model was applied to Gazwa district within Gyeongsang university village. The simulation system was developed by Flash MX action scripts and the physical environment of the streets was configured with the digital map and ArcGis within computer virtual space. The attribute data of buildings such as type and size of commercial business were collected through the field survey and combined with physical features. Then the effect of the variation of building attractiveness and the occurrence of street events to pedestrian environment were simulated. Through the experiments this study could make suggestions to improve pedestrian environment.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.4 no.1
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• pp.83-91
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• 2001

Purpose: The aim of this study was to investigate the current prevalence of protein-energy malnutrition (PEM) and the nutritional status of hospitalized pediatric patients. Methods: We evaluated the nutritional status of the 200 patients from February to July 1994 and the 233 patients from February to July 1999 admitted to Pediatric Department of Chosun University Hospital. Nutritional status was assessed by anthropometric and laboratory data. The nutritional status was classified according to based on the Waterlow criteria and using the laboratory data obtained between 3 days to 5 days after admission. Results: 1) The prevalence of acute PEM (weight for height) was as follows: severe, 0.5%; moderate, 7%; mild, 18%; and none, 74.5% in 1994 and severe, 2.24%; moderate, 3.59%; mild, 19.73%; and none, 74.4% in 1999. 2) The prevalence of chronic PEM (height for age) was as follows: severe, 5%; moderate, 5.5%; mild, 25.5%; and none, 64% in 1994 and severe, 2.24%; moderate, 4.04%; mild, 22.87%; and none, 70.85% in 1999. There was not a statistically significant difference between 1994 and 1999. 3) The prevalence of PEM according to age group, all age group had in general higher prevalence of mild PEM. 4) Values for hemoglobin and albumin were below than total lymphocyte values in PEM. Conclusion: The prevalence of acute or chronic PEM was common in hospitalized children. Therefore, the assessment of nutritional status may an important role to establish effective nutritional support and to improve their subsequent hospital course in hospitalized pediatric patient.

• Korean Journal of Remote Sensing
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• v.36 no.5_4
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• pp.1179-1194
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• 2020

This study investigates the feasibility of three algorithms, K-Nearest Neighbors (K-NN), Random Forest (RF) and Neural Network (NN), for estimating the air temperature of an unobserved area where the weather station is not installed. The satellite image were obtained from Landsat-8 and MODIS Aqua/Terra acquired in 2019, and the meteorological ground weather data were from AWS/ASOS data of Korea Meteorological Administration and Korea Forest Service. In addition, in order to improve the estimation accuracy, a digital surface model, solar radiation, aspect and slope were used. The accuracy assessment of machine learning methods was performed by calculating the statistics of R² (determination coefficient) and Root Mean Square Error (RMSE) through 10-fold cross-validation and the estimated values were compared for each target area. As a result, the neural network algorithm showed the most stable result among the three algorithms with R² = 0.805 and RMSE = 0.508. The neural network algorithm was applied to each data set on Landsat imagery scene. It was possible to generate an mean air temperature map from June to September 2019 and confirmed that detailed air temperature information could be estimated. The result is expected to be utilized for national disaster safety management such as heat wave response policies and heat island mitigation research.