Because the thickness and depth of consolidation layer vary at every location, the consolidation settlement and time have to be evaluated spatially. Also, for a rational evaluation of the uncertainty of the spatial distribution of consolidation settlement and time, it is necessary to adopt a probabilistic method. In this study, mean and standard deviation of consolidation settlement and time of whole analysis region are evaluated by using the spatial distribution of consolidation layer which is estimated from ordinary kriging and statistics of soil properties. Using these results and probabilistic method, the area that needs adopting the prefabricated vertical drain as well as raising the ground level for balancing the final design ground level is determined. It is observed that such areas are influenced by the variability of soil properties. The design procedure and method presented in this paper can be used in the decision making process for a geotechnical engineering design.
Purpose: A fully digital approach to oral prosthodontic rehabilitation requires the possibility of combining (i.e., registering) digital documentation from different sources. This becomes more complex in an edentulous jaw, as fixed dental markers to perform reliable registration are lacking. This validation study aimed to evaluate the reproducibility of 1) intraoral scanning and 2) soft tissue-based registration of an intraoral scan with a cone-beam computed tomography (CBCT) scan for a fully edentulous upper jaw. Materials and Methods: Two observers independently performed intraoral scans of the upper jaw in 14 fully edentulous patients. The palatal vault of both surface models was aligned, and the inter-observer variability was assessed by calculating the mean inter-surface distance at the level of the alveolar crest. Additionally, a CBCT scan of all patients was obtained and a soft tissue surface model was generated using patient-specific gray values. This CBCT soft tissue model was registered with the intraoral scans of both observers, and the intraclass correlation coefficient(ICC) was calculated to evaluate the reproducibility of the registration method. Results: The mean inter-observer deviation when performing an intraoral scan of the fully edentulous upper jaw was 0.10±0.09 mm. The inter-observer agreement for the soft tissue-based registration method was excellent(ICC=0.94; 95% confidence interval, 0.81-0.98). Conclusion: Even when teeth are lacking, intraoral scanning of the jaw and soft tissue-based registration of an intraoral scan with a CBCT scan can be performed with a high degree of precision.
Proceedings of the Korea Water Resources Association Conference
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2020.06a
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pp.125-125
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2020
European Space Agency's Sentinel-1 has an improved spatial and temporal resolution, as compared to previous satellite data such as Envisat Advanced SAR (ASAR) or Advanced Scatterometer (ASCAT). Thus, the assumption used for low-resolution retrieval algorithms used by ENVISAT ASAR or ASCAT is not applicable to Sentinel-1, because a higher degree of land surface heterogeneity should be considered for retrieval. The assumption of homogeneity over land surface is not valid any more. In this study, considering that soil roughness is one of the key parameters sensitive to soil moisture retrievals, various approaches are discussed. First, soil roughness is spatially inverted from Sentinel-1 backscattering over Yanco sites in Australia. Based upon this, Artificial Neural Networks data (feedforward multiplayer perception, MLP, Levenberg-Marquadt algorithm) are compared with Fractal approach (brownian fractal, Hurst exponent of 0.5). When using ANNs, training data are achieved from theoretical forward scattering models, Integral Equation Model (IEM). and Sentinel-1 measurements. The network is trained by 20 neurons and one hidden layer, and one input layer. On the other hand, fractal surface roughness is generated by fitting 1D power spectrum model with roughness spectra. Fractal roughness profile is produced by a stochastic process describing probability between two points, and Hurst exponent, as well as rms heights (a standard deviation of surface height). Main interest of this study is to estimate a spatial variability of roughness without the need of local measurements. This non-local approach is significant, because we operationally have to be independent from local stations, due to its few spatial coverage at the global level. More fundamentally, SAR roughness is much different from local measurements, Remote sensing data are influenced by incidence angle, large scale topography, or a mixing regime of sensors, although probe deployed in the field indicate point data. Finally, demerit and merit of these approaches will be discussed.
This study investigated the effects of continuous Singing Bowl healing on brainwaves and autonomic nervous system responses. The variations in brainwaves were measured during 45-minute sessions in eight participants, before and after Singing Bowl healing sessions to assess the changes in brainwaves before and after five weeks of Singing Bowl healing treatment. BioBrain BIOS-S8 was used to obtain brainwave measurements. Electrodes were placed on six channels: F3, F4, T3, T4, P3, and P4. A standard limb lead I with electrodes was used for electrocardiogram (ECG) measurements. Using the collected brainwave data, changes in brain waves were observed before and after five weeks of Singing Bowl healing. Beta waves, alpha waves, and sensorimotor rhythm were found to have reduced, while theta waves, delta waves, and the standard deviation of normal-to-normal intervals in heart rate variability had increased. These results indicate that continuous Singing Bowl healing over five weeks can stabilize brainwaves, activate the autonomic nervous system, and increase the relaxation-inducing effects of the parasympathetic nervous system.
In the livestock industry, detecting environmental outliers and predicting data are crucial tasks. Outliers in livestock environment data, typically gathered through time-series methods, can signal rapid changes in the environment and potential unexpected epidemics. Prompt detection and response to these outliers are essential to minimize stress in livestock and reduce economic losses for farmers by early detection of epidemic conditions. This study employs two methods to experiment and compare performances in setting thresholds that define outliers in livestock environment data outlier detection. The first method is an outlier detection using Mean Squared Error (MSE), and the second is an outlier detection using a Dynamic Threshold, which analyzes variability against the average value of previous data to identify outliers. The MSE-based method demonstrated a 94.98% accuracy rate, while the Dynamic Threshold method, which uses standard deviation, showed superior performance with 99.66% accuracy.
Dae Hyeok Lee;Wonjun Yang;Ji Seop Kim;Hoseok Sul;Jee Woong Choi;Su-Uk Son
The Journal of the Acoustical Society of Korea
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v.43
no.3
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pp.285-292
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2024
When calculating sonar detection probability, underwater acoustic uncertainty is assumed to be normal distributed with a standard deviation of 8 dB to 9 dB. However, due to the variability in experimental areas and ocean environmental conditions, predicting detection performance requires accounting for underwater acoustic uncertainty based on ocean experimental data. In this study, underwater acoustic uncertainty was determined using measured mid-frequency (2.3 kHz, 3 kHz) noise level and transmission loss data collected in the shallow water of the East Sea. After calculating the predictable probability of detection reflecting underwater acoustic uncertainty based on ocean experimental data, we compared it with the conventional detection probability results, as well as the predictable probability of detection results considering the uncertainty of the Rayleigh distribution and a negatively skewed distribution. As a result, we confirmed that differences in the detection area occur depending on each underwater acoustic uncertainty.
Purpose: Nuclear medicine manufacturers provide various softwares which shorten imaging time using their own image processing techniques such as UlatraSPECT, ASTONISH, Flash3D, Evolution, and nSPEED. Seoul National University Hospital has introduced softwares from Siemens and Philips, but it was still hard to understand algorithm difference between those two softwares. Thus, the purpose of this study was to figure out the difference of two softwares in planar images and research the possibility of application to images produced with high energy isotopes. Materials and Methods: First, a phantom study was performed to understand the difference of softwares in static studies. Various amounts of count were acquired and the images were analyzed quantitatively after application of PIXON, Siemens and ASTONISH, Philips, respectively. Then, we applied them to some applicable static studies and searched for merits and demerits. And also, they have been applied to images produced with high energy isotopes. Finally, A blind test was conducted by nuclear medicine doctors except phantom images. Results: There was nearly no difference between pre and post processing image with PIXON for FWHM test using capillary source whereas ASTONISH was improved. But, both of standard deviation(SD) and variance were decreased for PIXON while ASTONISH was highly increased. And in background variability comparison test using IEC phantom, PIXON has been decreased over all while ASTONISH has shown to be somewhat increased. Contrast ratio in each spheres has also been increased for both methods. For image scale, window width has been increased for 4~5 times after processing with PIXON while ASTONISH showed nearly no difference. After phantom test analysis, ASTONISH seemed to be applicable for some studies which needs quantitative analysis or high contrast, and PIXON seemed to be applicable for insufficient counts studies or long time studies. Conclusion: Quantitative values used for usual analysis were generally improved after application of the two softwares, however it seems that it's hard to maintain the consistency for all of nuclear medicine studies because result images can not be the same due to the difference of algorithm characteristic rather than the difference of gamma cameras. And also, it's hard to expect high image quality with the time shortening method such as whole body scan. But it will be possible to apply to static studies considering the algorithm characteristic or we can expect a change of image quality through application to high energy isotope images.
Objectives: Sahyangsohapwon (SS) is a herbal medication that has been widely used with circulatory and neural diseases. This study was conducted to assess the effect of SS on the autonomic nervous system by using heart rate variability measurement. Methods: The eligible subjects were enrolled from the healthy male group of ages 20 to 35 years. They were divided into two groups, the SS group (n=26) and the control (n=24). We monitored the ECG of subjects from the time period 14:00 to 18:00. In the SS group, subjects were administered with a dose of SS at the time 15:00, whereas the control group had none. For each hour HRV measurement was monitored every 15 minutes for 512 seconds from the time period 14:00 to 18:00. The mean value, which was calculated using the 4 values during each hour (i.e. 14:00, 14:15, 14:30, 14:45), was used as the representative value for each individual hour. For the measurement values, RR-interval and SDNN (standard deviation of the NN intervals) were used as time domain analysis, and HF (high frequency), LF (low frequency), and LF/HF ratio were used as frequency domain analysis. Results: The LF value showed an increase after one hour of SS administration and showed gradual diminution for each and every hour. The repeated measures of ANOVA for the comparison of the LF value between the SS group and the control group showed significant differences. While, RR interval, SDNN, HF, and LF/HF ratio values showed no significant differences between the two groups. Conclusions: We suggest that the SS might be useful for stabilizing autonomic nervous system by inhibiting sympathetic nerve activation in healthy people.
Jeong, Young Ae;Jang, Dong Cheol;Kwon, Jin Kyung;Kim, Dae Hyun;Choi, Eun Young
Journal of Bio-Environment Control
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v.31
no.3
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pp.221-229
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2022
This study was aimed to investigate spatial and vertical characteristics of greenhouse environments according to the location of the environmental sensors, and to investigate the correlations between temperature, light intensity, and carbon dioxide (CO2) concentration according to the type of greenhouse. Temperature, relative humidity (RH), CO2, and light sensors were installed in the four-different vertical positions of the whole canopy as well as ground and roof space at the five spatial locations of the Venlo greenhouse. Also, correlations between temperature, light intensity, and CO2 concentration in Venlo and semi-closed greenhouses were analyzed using the Curve Expert Professional program. The deviations among the spatial locations were larger in the CO2 concentration than other environmental factors in the Venlo greenhouse. The average CO2 concentration ranged from 465 to 761 µmol·mol-1 with the highest value (646 µmol·mol-1) at the Middle End (4ME) close to the main pipe (50Ø) of the liquefied CO2 gas supply and lowest (436 µmol·mol-1) at the Left Middle (5LM). The deviation among the vertical positions was greater in temperature and relative humidity than other environments. The time zone with the largest deviation in average temperature was 2 p.m. with the highest temperature (26.51℃) at the Upper Air (UA) and the lowest temperature (25.62℃) at the Lower Canopy (LC). The time zone with the largest deviation in average RH was 1 p.m. with the highest RH (76.90%) at the LC and the lowest RH (71.74%) at the UA. The highest average CO2 concentration at each hour was Roof Air (RF) and Ground (GD). The coefficient of correlations between temperature, light intensity, and CO2 concentration were 0.07 for semi-closed greenhouse and 0.66 for Venlo greenhouse. All the results indicate that while the CO2 concentration in the greenhouse needs to be analyzed in the spatial locations, temperature and humidity needs to be analyzed in the vertical positions of canopy. The target CO2 fertilization concentration for the semi-closed greenhouse with low ventilation rate should be different from that of general greenhouses.
KSCE Journal of Civil and Environmental Engineering Research
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v.40
no.1
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pp.119-126
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2020
This study analyzed the effects of future climate change on water resources in the Gyeongan-cheon watershed of the Han River. Considering the uncertainties of GCM climate data, future data using 16 GCMs and SQM downscaling method are used. And SWAT model was applied to simulate the hydrological changes from the past to the future. The maximum to minimum difference according to GCM for the future period (2010-2099) was about 1,500 mm of annual precipitation, 150 mm of evapotranspiration, 1,380 mm of runoff, and the deviation from the mean was -40 % to +60 % of precipitation, ±15 % of evapotranspiration, -60 % to +90 % of runoff, which means that the variability is very high according to GCM. The impacts of climate change over the three future periods showed that precipitation, evapotranspiration, and runoff were expected to increase gradually toward the far future (2070-2099), and would be relatively larger under the RCP 8.5 scenario. On a monthly basis, it was analyzed that precipitation and runoff increased in July to September, while the evapotranspiration decreased in July and August, and increased in September and October. The results of this study are expected to be helpful in understanding the future climate impacts of various GCM data and the uncertainties associated with GCMs.
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