• Geophysics and Geophysical Exploration
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• v.19 no.4
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• pp.179-186
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• 2016

Data leveling utilizing baseline survey makes existing old data be smoothly compiled, and also keep characteristics of data, such as small high frequency anomaly information. The previously proposed leveling method may easily loose or damage the original characteristics of the data. This paper suggests a new leveling method. New method determines the leveling coefficients using regional field of the original data, which is composed by data on the grids point coincided with baseline survey grid, while existing method uses all grid data without any considerations. Results of new leveling method on test area shows that new method make two data sets compiled more smoothly and trends of data distribution expressed more clearly. And then, it also preserves high frequency information well.

• ETRI Journal
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• v.45 no.6
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• pp.1079-1089
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• 2023

Stroke is one of the leading causes of long-term disability worldwide, placing huge burdens on individuals and society. Further, automatic human activity recognition is a challenging task that is vital to the future of healthcare and physical therapy. Using a baseline long short-term memory recurrent neural network, this study provides a novel dataset of stretching, upward stretching, flinging motions, hand-to-mouth movements, swiping gestures, and pouring motions for improved model training and testing of stroke-affected patients. A MATLAB application is used to output textual and audible prediction results. A wearable sensor with a triaxial accelerometer is used to collect preprocessed real-time data. The model is trained with features extracted from the actual patient to recognize new actions, and the recognition accuracy provided by multiple datasets is compared based on the same baseline model. When training and testing using the new dataset, the baseline model shows recognition accuracy that is 11% higher than the Activity Daily Living dataset, 22% higher than the Activity Recognition Single Chest-Mounted Accelerometer dataset, and 10% higher than another real-world dataset.

• Culinary science and hospitality research
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• v.23 no.3
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• pp.257-270
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• 2017

The purpose of this study was to visualize the semantic network with big data related to food exhibition at convention center. For this, this study collected data containing 'coex food exhibition/bexco food exhibition' keywords from web pages and news on Google during one year from January 1 to December 31, 2016. Data were collected by using TEXTOM, a data collecting and processing program. From those data, degree centrality, closeness centrality, betweenness centrality and eigenvector centrality were analyzed by utilizing packaged NetDraw along with UCINET 6. The result showed that the web visibility of hospitality and destinations was high. In addition, the web visibility was also high for convention center programs, such as festival, exhibition, k-pop and event; hospitality related words, such as tourists, service, hotel, cruise, cuisine, travel. Convergence of iterated correlations showed 4 clustered named "Coex", "Bexco", "Nations" and "Hospitality". It is expected that this diagnosis on food exhibition at convention center according to changes in domestic environment by using these web information will be a foundation of baseline data useful for establishing convention marketing strategies.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.7
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• pp.104-115
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• 1999

This paper proposes an efficient method for 3D modeling of a human face from trinocular images by reconstructing face surface using range data. By using a trinocular camera system, we mitigated the tradeoff between the occlusion problem and the range resolution limitation which is the critical limitation in binocular camera system. We also propose an MPC_MBS (Matching Pixel Count Multiple Baseline Stereo) area-based matching method to reduce boundary overreach phenomenon and to improve both of accuracy and precision in matching. In this method, the computing time can be reduced significantly by removing the redundancies. In the model generation sub-pixel accurate surface data are achieved by 2D interpolation of disparity values, and are sampled to make regular triangular meshes. The data size of the triangular mesh model can be controlled by merging the vertices that lie on the same plane within user defined error threshold.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.4
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• pp.245-254
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• 2018

Impact of tropospheric correction techniques on accuracy of the GPS (Global Positioning System) derived ellipsoidal heights has been experimentally assessed in this paper. To this end, 247 baselines were constructed from a total of 88 CORS (Continuously Operating Reference Stations) in Korea. The GPS measurements for seven days, acquired from the so-called integrated GNSS (Global Navigation Satellite Systems) data center via internet connection, have been processed by two baseline processing software packages with an application of the empirical models, such as Hopfield, modified Hopfield and Saastamoinen, and the estimation techniques based on the DD (Double-Differenced) measurements and the PPP (Precise Point Positioning) technique; hence a total number of the baseline processed and tested was 8,645. Accuracy and precision of the estimated heights from the various correction schemes were analyzed about baseline lengths and height differences of the testing baselines. Details of these results are summarized with a view to hopefully providing an overall guideline of a suitable selection of the modeling scheme with respect to processing conditions, such as the baseline length and the height differences.

• Journal of Preventive Medicine and Public Health
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• v.37 no.4
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• pp.381-389
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• 2004

Objective : To compare the efficacy between SKI306X and Diclofenac by using generalized estimating equations (GEE) methodology in the analysis of correlated bivariate binary outcome data in Osteoarthritis (OA) diseases. Methods : A randomized, double-blind, active comparator-controlled, non-inferiority clinical trial was conducted at 5 institutions in Korea with the random assignment of 248 patients aged 35 to 75 years old with OA of the knee and clinical evidence of OA. Patients were enrolled in this study if they had at least moderate pain in the affected knee joint and a score larger than 35mm as assessed by VAS (Visual Analog Scale). The main exposure variable was treatment (SKI 306X vs. Diclofenac) and other covariates were age, sex, BMI, baseline VAS, center, operation history (Yes/No), NSAIDS (Y/N), acupuncture (Y/N), herbal medicine (Y/N), past history of musculoskeletal disease (Y/N), and previous therapy related with OA (Y/N). The main study outcome was the change of VAS pain scores from baseline to the 2nd and 4th weeks after treatment. Pain scores were obtained as baseline, 2nd and 4th weeks after treatment. We applied GEE approach with empirical covariance matrix and independent(or exchangeable) working correlation matrix to evaluate the relation of several risk factors to the change of VAS pain scores with correlated binary bivariate outcomes. Results : While baseline VAS, age, and acupuncture variables had protective effects for reducing the OA pain, its treatment (Joins/Diclofenac) was not statistically significant through GEE methodology (ITT:aOR=1.37, 95% CI=(0.8200, 2.26), PP:aOR=1.47, 95% CI=(0.73, 2.95)). The goodness-of-fit statistic for GEE (6.55, p=0.68) was computed to assess the adequacy of the fitted final model. Conclusions : Both ANCOVA and GEE methods yielded non statistical significance in the evaluation of non-inferiority of the efficacy between SKI306X and Diclofenac. While VAS outcome for each visit was applied in GEE, only VAS outcome for the fourth visit was applied in ANCOVA. So the GEE methodology is more accurate for the analysis of correlated outcomes.

• Journal of Radiation Protection and Research
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• v.46 no.3
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• pp.83-97
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• 2021

Background: The lifetime risk of lung cancer incidence due to radiation for nonsmokers is overestimated because of the use of the average cancer baseline risk among a mixed population, including smokers. In recent years, the generalized multiplicative (GM)-excess relative risk (ERR) model has been developed in the life span study of atomic bomb survivors to consider the joint effect of radiation and smoking. Based on this background, this paper discusses the issues of radiation risk assessment considering smoking in two parts. Materials and Methods: In Part 1, we proposed a simple method of estimating the baseline risk for nonsmokers using current smoking data. We performed sensitivity analysis on baseline risk estimation to discuss the birth cohort effects. In Part 2, we applied the GM-ERR model for Japanese smokers to calculate lifetime attributable risk (LAR). We also performed a sensitivity analysis using other ERR models (e.g., simple additive (SA)-ERR model). Results and Discussion: In Part 1, the lifetime baseline risk from mixed population including smokers to nonsmokers decreased by 54% (44%-60%) for males and 24% (18%-29%) for females. In Part 2, comparison of LAR between SA- and GM-ERR models showed that if the radiation dose was ≤200 mGy or less, the difference between these ERR models was within the standard deviation of LAR due to the uncertainty of smoking information. Conclusion: The use of mixed population for baseline risk assessment overestimates the risk for lung cancer due to low-dose radiation exposure in Japanese males.

• Journal of agricultural medicine and community health
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• v.18 no.2
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• pp.105-119
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• 1993

The purpose of this study was to evaluate the program for the control of acute respiratory infections(ARI) in children in a Korean rural area(Yonchon county). Evaluating the program, we focused on the pattern of prescription and appropriateness of antibiotics prescribed by the health personnel who had participated in the ARI Control Program. It was implemented at the primary health care setting in rural area, such as district hospital, health subcenters, and health posts. During six-months programme monitoring period, medical records were reviewed and collected data were analysed by the pediatrician, research coordinator of this study. The baseline data were collected from medical records of the same period(six months) of one year before the implementation of the ARI programme. The study results were as follow : 1. Common cold was the most prevalent disease(78.7%. 594 cases) among the all ARI cases (755 cases). The less frequent cases were bronchitis(11.9%), acute pharyngitis(5.2%), and pneumonia(1.8%). 2. Significant reduction in the use of antibiotics was observed after the programme implementation. Ninety three(15.7%) of 594 common cold cases were received antibiotics compared with 282(35.2%) of 802 in the baseline period. In the cases of bronchitis and acute pharyngitis, the reduction rates were 15.1% and 23.2% respectively compared to the baseline period. 3. Mean duration of antibiotics prescription was 1.81-1.75 days, similar to the baseline data. 4. The appropriateness rate of antibiotics prescriptions were 84.3%(common cold), 35.6% (bronchitis) and 28.2%(acute pharyngitis). In the case of pneumonia, the antibiotics prescription was compatible to the criteria developed. 5. Pediatrician prescribed antibiotics more appropriately for all cases than general practitioners in health sub-center, and nurse practitioners in health posts. 6. Antibiotics therapy was shown to be of no effect in the treatment of the all ARI cases. At the 5 and 10 days check-up of common cold cases after visits, proportion of improved patients were 58.3% in the antibiotics-used group and 51.4% in the control group. In the other cases of ARI, the patterns of response were similar to common cold. None of the differences in outcome between the antibiotics-used and control group was statistically significant. This ARI programme may have substantial a substantial impact on antibiotics use at the public health institutions(district hospital, health subcenters, health posts) which are of major domain for primary health care in Korean rural areas.

• Journal of Gastric Cancer
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• v.17 no.2
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• pp.132-144
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• 2017

Purpose: To identify baseline prognostic factors for survival in patients with disease progression, during or after chemotherapy for the treatment of advanced gastric or gastroesophageal junction (GEJ) cancer. Materials and Methods: We pooled data from patients randomized between 2009 and 2012 in 2 phase III, global double-blind studies of ramucirumab for the treatment of advanced gastric or GEJ adenocarcinoma following disease progression on first-line platinum- and/or fluoropyrimidine-containing therapy (REGARD and RAINBOW). Forty-one key baseline clinical and laboratory factors common in both studies were examined. Model building started with covariate screening using univariate Cox models (significance level=0.05). A stepwise multivariable Cox model identified the final prognostic factors (entry+exit significance level=0.01). Cox models were stratified by treatment and geographic region. The process was repeated to identify baseline prognostic quality of life (QoL) parameters. Results: Of 1,020 randomized patients, 953 (93%) patients without any missing covariates were included in the analysis. We identified 12 independent prognostic factors of poor survival: 1) peritoneal metastases; 2) Eastern Cooperative Oncology Group (ECOG) performance score 1; 3) the presence of a primary tumor; 4) time to progression since prior therapy <6 months; 5) poor/unknown tumor differentiation; abnormally low blood levels of 6) albumin, 7) sodium, and/or 8) lymphocytes; and abnormally high blood levels of 9) neutrophils, 10) aspartate aminotransferase (AST), 11) alkaline phosphatase (ALP), and/or 12) lactate dehydrogenase (LDH). Factors were used to devise a 4-tier prognostic index (median overall survival [OS] by risk [months]: high=3.4, moderate=6.4, medium=9.9, and low=14.5; Harrell's C-index=0.66; 95% confidence interval [CI], 0.64-0.68). Addition of QoL to the model identified patient-reported appetite loss as an independent prognostic factor. Conclusions: The identified prognostic factors and the reported prognostic index may help clinical decision-making, patient stratification, and planning of future clinical studies.

• Korean Journal of Psychosomatic Medicine
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• v.31 no.2
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• pp.149-154
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• 2023

Objectives : Far-infrared (FIR) lights have been investigated for sleep quality intervention. We sought to measure the advantageous effects of FIR in sleep using polysomnographic data as the objective outcomes. Methods : The ten healthy volunteers were enrolled in a single-center, prospective, patient-blind, single-arm trial. Individuals slept on a sham mattress and a FIR emitting mattress with polysomnography for one night each. Results : Sleep efficiency showed an increasing trend but was not statistically significant. PSQI-K significantly decreased (p=0.013). The latency to REM of the baseline was shorter than that of the intervention (p=0.008). Though there was no statistical significance, Stage N1 and N2 were shortened, and Stage N3 was prolonged after the intervention compared to the baseline. Conclusions : The FIR-emitting mattresses improved sleep quality on self-reported insomnia. We suggested the candidate for the markers altered by the FIR therapy, such as the normalization of REM latency and increased N3 sleep.