• Journal of Home Health Care Nursing
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• v.31 no.1
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• pp.56-65
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• 2024

Purpose: This study aimed to explore the association between demographic characteristics, hospitalization-related characteristics, and the severity of long-term hospitalization in a high-level general hospital, and to analyze the factors influencing decisions of all patients. Methods: General and clinical characteristics of the participants were analyzed using frequency, percentage, mean, and standard deviation. Differences in these characteristics, contingent upon whether a power source was requested, were analyzed using independent t-Test and Chi-squared tests. Logistic regression analysis was used to identify the factors related to the presence or absence of power requests. Results: The factors impacting the decision to refer a dependent variable include medical treatment (neurosurgery) (B=2.118, SE=0.960, p-value=.027, OR=8.314, 95% CI=1.267-54.551), infection isolation (CRE) (B=1.336, SE=0.666, p-value=.045, OR=3.804, 95% CI=1.032-14.021), and the utilization of tertiary antibiotics (B=3.076, SE=1.362, p-value= .024, OR=21.663, 95% CI=1.502-312.530). Conclusion: This study found a significant association between medical treatment (neurosurgery), infection isolation (CRE), and the use of tertiary antibiotics as dependent variables. These findings indicate that continuous monitoring can contribute to a reduction in long-term financial burdens.

• Journal of Biosystems Engineering
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• v.43 no.2
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• pp.103-109
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• 2018

Purpose: This study has been conducted to develop a potato yield monitoring system, consisting of a segmentation algorithm to detect potatoes scattered on a soil surface and a counting system to count the number of potatoes and convert the data from two-dimensional images to masses. Methods: First, a segmentation algorithm was developed using top-hat filtering and processing a series of images, and its performance was evaluated in a stationary condition. Second, a counting system was developed to count the number of potatoes in a moving condition and calculate the mass of each using a mass estimation equation, where the volume of a potato was obtained from its two-dimensional image, and the potato density and a correction factor were obtained experimentally. Experiments were conducted to segment potatoes on a soil surface for different potato sizes. The counting system was tested 10 times for 20 randomly selected potatoes in a simulated field condition. Furthermore, the estimated total mass of the potatoes was compared with their actual mass. Results: For a $640{\times}480$ image size, it took 0.04 s for the segmentation algorithm to process one frame. The root mean squared deviation (RMSD) and average percentage error for the measured mass of potatoes using this counting system were 12.65 g and 7.13%, respectively, when the camera was stationary. The system performance while moving was the best in L1 (0.313 m/s), where the RMSD and percentage error were 6.92 g and 7.79%, respectively. For 20 newly prepared potatoes and 10 replication measurements, the counting system exhibited a percentage error in the mass estimation ranging from 10.17-13.24%. Conclusions: At a travel speed of 0.313 m/s, the average percentage error and standard deviation of the mass measurement using the counting system were 12.03% and 1.04%, respectively.

• Journal of the Korean Society of Costume
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• v.32
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• pp.21-30
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• 1997

Chogori the basic upper garment of korea costume occupies an important role in tra-ditional dressing and continues to be in use to the present days. Of course there has been changes in the length and line of Chogori with the flow of time based on the Ancient Yoo. This is a study of the 14 parts of Chgori based on statistical analysis by computing the practical measuements. Here the statistical analysis is a objective and quantitative of the stylistic changes in Chogori with time. In this study from the data the Mean and Standard deviation has been evaluated and periodic change is shown by graph to test the periodic change T-test Regressional analysis Index analysis has been used. The results are as follows: 1. The length of clothing has changed with time except the sleeve length. Here the length of clothing means all the other measurements ex-cept the sleeve Thus while the measurements of sleeve length has been uniquely unchanged the other measurements have influenced each other. 2. Generally the form of Chogori had the tendency towards smallness in the 19th cen-tury. But it tended to get larger in the 20th century. 3. Compared to other periods the mode of 19th and 20th century Chogori was widely ac-cepted as the Standard deviation of that period was very narrow. 4. The results seen from the regressional analysis of the Cho-sun period woman's Chogori satisfy the t-value and R-squared and thus support the regression formula presump-tion. 5. From the index analysis it is revealed that with decrease in the armhole measurement sleeve measurement and neckband; relatively same decrease in the wrist measurement; and very marked decrease in the sideline measurement.

• Science of Emotion and Sensibility
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• v.14 no.4
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• pp.653-662
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• 2011

As technology in 3D industry has rapidly advanced, a lot of studies primarily focusing on visual function and cognition have become vigorous. However, studies on effect of 3D visual fatigue on autonomic nervous system have not less been conducted. Thus, this study was to identify and determine the effect that might have a negative influence on sympathetic nervous system, parasympathetic nervous system, and cardiovascular system. Fifteen undergraduates (female: 9, mean age: $22.53{\pm}2.55$) participated and were sat on a comfortable chair, viewing a 3D content during about 1 hour. Cardiac responses like SDNN(standard deviation of RR intervals), RMS-SD(root mean squared successive difference), and HF/LF ratios extracted from the measured PPG(Photo-PlethysmoGram) before viewing 3D were compared to those after viewing 3D. The results showed that after subjects watched the 3D, responses in sympathetic nervous system and parasympathetic nervous system were activated and deactivated, respectively relative to those before watching the 3D. The results showed that HF/LF ratio, Ln(LF), and Ln(HF) after viewing 3D were significantly reduced relative to those before viewing 3D. No significant effects were observed in SDNN and RMS-SD. Results obtained in this study showed that visual fatigue induced by watching 3D adversely influenced autonomic nervous system, and thereby reduced heart rate variability causing sympathetic nervous acceleration.

• Journal of Korean Medicine Rehabilitation
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• v.19 no.2
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• pp.241-250
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• 2009

Objectives : To study autonomic nervous system dysfunction of Low Back Pain(LBP) patients, using spectral analysis of Heart Rate Variability(HRV). Methods : HRV of 190 patients was measured and seperated into two groups, those with LBP(n=95) and healthy controls(n=95). HRV was measured by SA-6000(Medicore, Korea) for 5 minutes after 5 minutes' resting. Results : 1. Mean heart rate(MHRT) of the experimental group was slightly higher than that of the control group, but did not show significant difference(P=0.428). The square root of the mean squared differences of successive normal-to-normal intervals(RMSSD), logarithmic very low frequency power(Ln VLF) and low frequency power/high frequency power ratio(LH/HF ratio) were not significantly low between experimental group and control group(P=0.16, 0.130, 0.537). 2. The standard deviation of all the normal-to-normal intervals(SDNN), logarithmic total power(Ln TP), logarithmic low frequency power(Ln LF) and logarithmic high frequency power(Ln HF) were significantly low between experimental group and control group(P=0.03, 0.005, 0.001, 0.007). 3. Ln LF of acute group was significantly low compared with those of chronic group(P= 0.039). Conclusions : This study suggests the activity and imbalance of autonomic nervous system in LBP is low. Also sympathetic nervous system of acute LBP is lower than that of chronic LBP. Further study of HRV related to LBP is needed in the clinical medicine.

• The Journal of Korean Obstetrics and Gynecology
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• v.28 no.3
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• pp.11-20
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• 2015

Objectives This study is performed to recognize the relationship between atrophic vaginitis and stress that have an affect on autonomic nervous system. Methods We studied 47 patients who visited Kangnam Kyunghee Korean Hospital Medical Examination Center from November, 2013 to June, 2014. They were devided into two groups, atrophic vaginitis group (AV, n=18) and non-atrophic vaginitis group (NAV, n=29). We compared the result of HRV between the two groups. Results The mean of The standard deviation of NN intervals (SDNN), the square root of the mean squared difference of successive NNs (RMSSD) in AV group was lower than NAV group, but there was no significant difference between the two groups. Total power (TP), low frequency (LF) and very low frequency (VLF) of AV group was significantly lower than NAV group. There was no significant difference in high frequency (HF). Conclusions Women with atrophic vaginitis is expected to have low adaptive capacity against stress.

• The Journal of Advanced Prosthodontics
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• v.13 no.6
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• pp.351-360
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• 2021

PURPOSE. The aim of this study was to evaluate the efficiency of occlusal and interproximal adjustments of single implant crowns (SIC), comparing a digital cast-free approach (CF) and a protocol using 3D printed casts (PC). MATERIALS AND METHODS. A titanium implant was inserted at position of lower right first molar in a typodont. The implant position was scanned using an intraoral scanner and SICs were fabricated accordingly. Ten crowns (CF; n = 10) were subject to a digital cast-free workflow without any labside occlusal and interproximal modifications. Ten other identical crowns (PC) were adjusted to 3D printed casts before delivery. All crowns were then adapted to the testing model, simulating chair-side adjustments during clinical placement. Adjustment time, quantity of adjustments, and contact relationship were assessed. Data were analyzed using SPSS software (P < .05). RESULTS. Median and interquartile range (IQR) of clinical adjustment time was 02:44 (IQR 00:45) minutes in group CF and 01:46 (IQR 00:21) minutes in group PC. Laboratory and clinical adjustment time in group PC was 04:25 (IQR 00:59) minutes in total. Mean and standard deviation (±SD) of root mean squared error (RMSE) of quantity of clinical adjustments was 45 ± 7 ㎛ in group CF and 34 ± 6 ㎛ in group PC. RMSE of total adjustments was 61 ± 11 ㎛ in group PC. Quality of occlusal contacts was better in group CF. CONCLUSION. Time effort for clinical adjustments was higher in the cast-free protocol, whereas quantity of modifications was lower, and the occlusal contact relationship was found more favourable.

• Wind and Structures
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• v.36 no.4
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• pp.237-247
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• 2023

The emergence of high-rise buildings has necessitated frequent structural health monitoring and maintenance for safety reasons. Wind causes damage and structural changes on tall structures; thus, safe structures should be designed. The pressure developed on tall buildings has been utilized in previous research studies to assess the impacts of wind on structures. The wind tunnel test is a primary research method commonly used to quantify the aerodynamic characteristics of high-rise buildings. Wind pressure is measured by placing pressure sensor taps at different locations on tall buildings, and the collected data are used for analysis. However, sensors may malfunction and produce erroneous data; these data losses make it difficult to analyze aerodynamic properties. Therefore, it is essential to generate missing data relative to the original data obtained from neighboring pressure sensor taps at various intervals. This study proposes a deep learning-based, deep convolutional generative adversarial network (DCGAN) to restore missing data associated with faulty pressure sensors installed on high-rise buildings. The performance of the proposed DCGAN is validated by using a standard imputation model known as the generative adversarial imputation network (GAIN). The average mean-square error (AMSE) and average R-squared (ARSE) are used as performance metrics. The calculated ARSE values by DCGAN on the building model's front, backside, left, and right sides are 0.970, 0.972, 0.984 and 0.978, respectively. The AMSE produced by DCGAN on four sides of the building model is 0.008, 0.010, 0.015 and 0.014. The average standard deviation of the actual measures of the pressure sensors on four sides of the model were 0.1738, 0.1758, 0.2234 and 0.2278. The average standard deviation of the pressure values generated by the proposed DCGAN imputation model was closer to that of the measured actual with values of 0.1736,0.1746,0.2191, and 0.2239 on four sides, respectively. In comparison, the standard deviation of the values predicted by GAIN are 0.1726,0.1735,0.2161, and 0.2209, which is far from actual values. The results demonstrate that DCGAN model fits better for data imputation than the GAIN model with improved accuracy and fewer error rates. Additionally, the DCGAN is utilized to estimate the wind pressure in regions of buildings where no pressure sensor taps are available; the model yielded greater prediction accuracy than GAIN.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Journal of Life Science
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• v.19 no.2
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• pp.271-276
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• 2009

The Purpose of this study was to examine the effects of boxing aerobic training on resting heart rate variability (HRV) in females. The subjects for this study were performed 16 female college students that aged 19-23. The subjects were divided into two groups; boxing aerobic exercise group (9 students) and control group (7 students). Boxing aerobic training program was performed three times a week for twelve weeks with $VO_{2max}$ 60-80% exercise intensity. The results of this study were following; 1. Mean HRT (mean heart rate) had no signigicant difference among the groups and exercise time. 2. SDNN (standard deviation of the normal to normal interval) had no significant difference among the group and exercise time. 3. RMS-SD (square root of the mean squared differences of successive normal to normal interval) had no significant difference among the groups and exercise time. 4. TP (total power) had no significant difference among the groups and exercise time. 5. LF (low frequency) had no significant difference among the groups and exercise time. 6. HF (high frequency) had no significant difference among the groups and exercise time. 7. LF/HF (low frequence/high frequency ratio) had no significant difference among the groups and exercise time. 8. VLF (very low frequency) had no significant difference among the groups and exercise time.