• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.665-673
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• 2010

The role of remote sensing in phenological studies is increasingly regarded as a key in understanding large area seasonal phenomena. This paper describes the application of Moderate Resolution Imaging Spectroradiometer (MODIS) time series data for vegetation classification using seasonal variation patterns. The vegetation seasonal variation phase of Seoul and provinces in Korea was inferred using 8 day composite MODIS NDVI (Normalized Difference Vegetation Index) dataset of 2006. The seasonal vegetation classification approach is performed with reclassification of 4 categories as urban, crop land, broad-leaf and needle-leaf forest area. The BISE (Best Index Slope Extraction) filtering algorithm was applied for a smoothing processing of MODIS NDVI time series data and fuzzy classification method was used for vegetation classification. The overall accuracy of classification was 77.5% and the kappa coefficient was 0.61%, thus suggesting overall high classification accuracy.

• Journal of the Korean Dietetic Association
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• v.13 no.4
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• pp.331-344
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• 2007

This study was performed to improve the hospital food service in quality and customer satisfaction by using 6-sigma strategy which was processed by DMAIC methods. The research procedure was as follows; analyzing the main causes of customer dissatisfaction of food service by using numerical method, and then finding out the standardized problem solving methods, and finally reforming food service process. The effectiveness of 6-sigma activity was measured by ‘food service quality index’, ‘customer satisfaction index’ and ‘total food service satisfaction index’. Food service quality index was calculated by adding grade of soup temperature, food service, delivery time, and setting accuracy. Statistical data analyses were completed by using the Minitab Ver. 14. By performing 6 sigma activity, food service quality index was increased from 67 to 79 points (p<0.05) and customer satisfaction index also rise from 73 to 79points (p<0.05). Satisfaction of meals’ taste, diverse menu, food setting accuracy, remove of food service, overall food service were significantly improved(p<0.05). The results of capability analysis in food service quality index, customer satisfaction index, and total food service satisfaction index were improved 2.11$\sigma$ to 2.49$\sigma$, 1.88$\sigma$ to 2.43$\sigma$, and 2.04$\sigma$ to 2.47$\sigma$ respectively (p<0.05). Therefore this study showed that subjective food service improving process could be measured by objective numerical value which might be used for financial value in hospital management.

• Journal of the Korean Data and Information Science Society
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• v.10 no.2
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• pp.341-357
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• 1999

Greenwich and Jahr-Schaffrath(1995) considered a new process incapability index(PII) $C_{pp}$, which modified the useful index $C^{\ast}_{pm}{$ for detecting assignable causes. The new index $C_{pp}$ provides an uncontaminated separation between information concerning the process accuracy and precision while this kind of information separation is not available with the $C^{\ast}_{pm}$ index. In this paper, we will study about the index $C_{pp}$ based on the bootstrap. First, we will prove the consistency of bootstrap deriving the bootstrap asymptotic distribution for our index $C_{pp}$. Moreover, with the consistency of bootstrap, we will construct six bootstrap confidence intervals and compare their performances. Some simulation results, comparison and analysis are provided. In particular, two STUD and ABC bootstrap methods perform significantly better.

• Journal of the Korean Society of Physical Medicine
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• v.18 no.1
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• pp.77-86
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• 2023

PURPOSE: This study developed an experimental algorithm, which is similar or identical to semantic linking for KCF codes, even if it converted existing semantic code linking methods to morphological code extraction methods. The purpose of this study was to verify the applicability of the system. METHODS: An experimental algorithm was developed as a morphological extraction method using code-specific words in the KCF code descriptions. The algorithm was designed in five stages that extracted KCF code using natural language paragraphs. For verification, 80 clinical natural language experimental cases were defined. Data acquisition for the study was conducted with the deliberation and approval of the bioethics committee of the relevant institution. Each case was linked by experts and was extracted through the System. The linking accuracy index model was used to compare the KCF code linking by experts with those extracted from the system. RESULTS: The accuracy was checked using the linking accuracy index model for each case. The analysis was divided into five sections using the accuracy range. The section with less than 25% was compared; the first experimental accuracy was 61.24%. In the second, the accuracy was 42.50%. The accuracy was improved to 30.59% in the section by only a weight adjustment. The accuracy can be improved by adjusting several independent variables applied to the system. CONCLUSION: This paper suggested and verified a way to easily extract and utilize KCF codes even if they are not experts. KCF requires the system for utilization, and additional study will be needed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.11a
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• pp.7-8
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• 2008

• Proceedings of the Korea Contents Association Conference
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• 2014.06a
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• pp.487-488
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• 2014

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.2
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• pp.21-35
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• 2020

Vegetation information is a very important factor used in various fields such as urban planning, landscaping, water resources, and the environment. Vegetation varies according to canopy density or chlorophyll content, but vegetation vitality is not considered when classifying vegetation areas in previous studies. In this study, in order to satisfy various applied studies, a study was conducted to set a threshold value of vegetation index considering vegetation vitality. First, an eBee fixed-wing drone was equipped with a multi-spectral camera to construct optical and near-infrared orthomosaic images. Then, GIS calculation was performed for each orthomosaic image to calculate the NDVI, GNDVI, SAVI, and MSAVI vegetation index. In addition, the vegetation position of the target site was investigated through VRS survey, and the accuracy of each vegetation index was evaluated using vegetation vitality. As a result, the scenario in which the vegetation vitality point was selected as the vegetation area was higher in the classification accuracy of the vegetation index than the scenario in which the vegetation vitality point was slightly insufficient. In addition, the Kappa coefficient for each vegetation index calculated by overlapping with each site survey point was used to select the best threshold value of vegetation index for classifying vegetation by scenario. Therefore, the evaluation of vegetation index accuracy considering the vegetation vitality suggested in this study is expected to provide useful information for decision-making support in various business fields such as city planning in the future.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.4
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• pp.522-528
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• 1986

Based on the modified effective index method, analysis of dielectric rectangular waveguides and directional couplers are presented. Aside from the effective index concept of channel region, the equivalent index concept of cladding region is proposed. The error problem of eigenvalues, which has been experienced when the effective index method is used, is improved. Our approxiamtions give similar accuracy when compared with the results of other regorous approxiamtion techiniques. The advantage of the modified effective index methods is utilized by replacing the directional coupler with the equivalent slab guides, and the coupling constant is calculated by the coupled mode theory. The effectiveness of the equivalent index concept is positively confirmed.

• Atmosphere
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• v.23 no.1
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• pp.113-121
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• 2013

The objective of this study is to develop and evaluate the system to produce the real-time ensemble drought prediction data. Ensemble drought prediction consists of 3 processes (meteorological outlook using the multi-initial conditions, hydrological analysis and drought index calculation) therefore, more processing time and data is required than that of single member. For ensemble drought prediction, data process time is optimized and hardware of existing system is upgraded. Ensemble drought data is estimated for year 2012 and to evaluate the accuracy of drought prediction data by using ROC (Relative Operating Characteristics) analysis. We obtained 5 ensembles as optimal number and predicted drought condition for every tenth day i.e. 5th, 15th and 25th of each month. The drought indices used are SPI (Standard Precipitation Index), SRI (Standard Runoff Index), SSI (Standard Soil moisture Index). Drought conditions were determined based on results obtained for each ensemble member. Overall the results showed higher accuracy using ensemble members as compared to single. The ROC score of SRI and SSI showed significant improvement in drought period however SPI was higher in the demise period. The proposed ensemble drought prediction system can be contributed to drought forecasting techniques in Korea.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.12
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• pp.5001-5004
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• 2015

The Reid colposcopic index (RCI) helps physicians for interpret the results of colposcopic examination. To compare the accuracy of RCI in colposcopic evaluation between general and oncologic gynecologists, this prospective trial was conducted by invited women over 20 years of age who were scheduled for a colposcopy at Chiang Mai University Hospital between August, 2008 and May, 2014 to participate. Pregnant patients or those having a history of hysterectomy or conization were excluded. During the colposcopy, all patients were simultaneously evaluated by general and oncologic gynecologists utilizing the RCI. Further management with either a biopsy or LEEP in each patient was dependent on the decision of the attending oncologic gynecologist. The accuracy of the RCI in diagnosing HSIL or more was calculated by the comparison with the final histology. Finally, 135 patients were recruited into this study. The sensitivity, specificity, PPV, NPV, and accuracy of RCI in diagnosing HSIL or more in general gynecologists were 45.2%, 80.7%, 41.1%, 83.2% and 72.6% while in the oncologic gynecologists were 51.6%, 85.6%, 51.6%, 85.6% and 77.8%, respectively. The difference in accuracy between evaluator groups was not significant (p-value=0.28). Of 3 patients with invasive cervical cancer, all were undetected by the general gynecologists using RCI while only 1 invasive cervical cancer was missed via RCI by the oncologic gynecologists. We conclude that RCI could be used by general gynecologists in provincial hospitals with major concerns about missing invasive cervical cancer. A short training period regarding colposcopy might help to resolve this problem.