• 한방재활의학과학회지
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• 제19권2호
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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.

• 대한치과기공학회지
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• 제39권1호
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• pp.17-24
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• 2017

Purpose: The purpose of this study was to evaluate the internal fitness of the resin coping that was fabricated by the traditional and Digital manufacturing methods through 3-dimensional analysis. Methods: maxillary right second molar was chosen implant master model. Custom-built impression trays were manufactured. After screwing the pick-up impression coping onto the master cast, impressions were made with silicone impression. The Working model was then made with type IV stone. The coping was fabricated: SLAC group (n=8), APPC group (n=8), LAPC group (n=8) Resin coping data was measured by using a three-dimensional evaluation program. Internal fitness was calculated by RMS (Root Mean Square).It measures mean and Standard Deviation (SD). Results: Three groups are measured $47.11{\pm}(3.08){\mu}m$ total RMS of SLAC group, $48.35({\pm}1.55{\mu}m)$ for total RMS of LAPC group, $43.45{\pm}2.09{\mu}m$ for total RMS of APPC group. Measured value is gradually increased. Followed by autopolymerized pattern resin; Stereolithography resin, Light-activated pattern resin But there were no differences stastically(P>0.321). Conclusion: Evaluation of internal fitness on Resin copings was fabricated by three-ways methods showed that no differences statistically significant and clinically acceptable results.

• 대한원격탐사학회지
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• 제14권2호
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• pp.149-164
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• 1998

본 연구에서는 지구자원탐사용 인공위성 화상데이터중에서 공간해상력이 우수한 RS-1C PAN 데이터와 Landsat TM 데이터를 중합(merging)하는데 있어서, 어떤 중합방법이 유효한지를 밝히고자 하였다. 각기 다른 두 화상데이터를 중합하기 위하여 IHS, PCA, HPF, ratio enhanoement 및 LUT방법을 적용하였으며, 이 방법들에 의하여 얻어진 화상들의 평가에 있어서는, 분광반사특성 보존성부분과 공간해상력 부분으로 나누어서 평가하였다. 그 결과 ratio enhancement방법이 분광반사특성의 보존성에 있어서 가장 좋은 결과를 나타내었다. 전체적인 화상의 시각적 판독평가에 있어서는 PCA방법이 다른 방법에 비하여 공간해상력이 우수한 것으로 파악되었으며 다음으로 HPF, ratio enhancement, IHS, LUT방법의 순으로 나타났다.

• 한국건설순환자원학회논문집
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• 제7권3호
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• pp.216-223
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• 2019

이 연구의 목적은 바텀애시 골재와 기포를 융합한 경량 콘크리트(bottom ash based lightweight concrete, LWC-BF)의 압축 응력-변형률 모델 제시이다. Yang 등이 제시한 응력-변형률 곡선식에서 LWC-BF 9 배합의 실험으로부터 얻은 탄성계수, 최대응력 시 변형률 그리고 최대응력 이후 최대응력의 50% 응력 시 변형률 값들을 이용하여 상승부와 하강부의 기울기를 결정하였다. 제시된 모델은 기포 혼입율의 증가와 함께 감소되는 초기 강성 및 증가되는 하강부 기울기를 잘 반영하면서 실험결과와 잘 일치하였다. 제시된 모델의 예측값과 실험값의 평균제곱근 오차로부터 결정된 평균값과 표준편차는 각각 0.19와 0.08로서 각각 1.23과 0.47 값을 보이는 fib 2010 모델에 비해 현저히 낮았다.

• 대한한방부인과학회지
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• 제28권3호
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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.

• Safety and Health at Work
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• 제7권2호
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• pp.124-129
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• 2016

Background: Work-related fatigue has a strong impact on performance and safety but so far, no agreed upon method exists to detect and quantify it. It has been suggested that work-related fatigue cannot be quantified with just one test alone, possibly because fatigue is not a uniform construct. The purpose of this study is therefore to measure work-related fatigue with multiple tests and then to determine the underlying factorial structure. Methods: Twenty-eight employees (mean: 36.11; standard deviation 13.17) participated in five common fatigue tests, namely, posturography, heart rate variability, distributed attention, simple reaction time, and subjective fatigue before and after work. To evaluate changes from morning to afternoon, t tests were conducted. For further data analysis, the differences between afternoon and morning scores for each outcome measure and participant (${\Delta}$ scores) were submitted to factor analysis with varimax rotation and each factor with the highest-loading outcome measure was selected. The ${\Delta}$ scores from tests with single and multiple outcome measures were submitted for a further factor analysis with varimax rotation. Results: The statistical analysis of the multiple tests determine a factorial structure with three factors: The first factor is best represented by center of pressure (COP) path length, COP confidence area, and simple reaction time. The second factor is associated with root mean square of successive difference and useful field of view (UFOV). The third factor is represented by the single ${\Delta}$ score of subjective fatigue. Conclusion: Work-related fatigue is a multidimensional phenomenon that should be assessed by multiple tests. Based on data structure and practicability, we recommend carrying out further studies to assess work-related fatigue with manual reaction time and UFOV Subtest 2.

• 한방재활의학과학회지
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• 제31권2호
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• pp.81-97
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• 2021

Objectives This study was designed to identify the changes of autonomic nervous system (ANS) which was induced by acupuncture at the field of the auricular branch of the vagus nerve. Methods 30 healthy adults were selected and classified into two groups; experimental group, control group. After providing mental stress, acupuncture was applied at external ear in experimental group and no treatment executed in control group. The evaluation of ANS function was measured by heart rate variability (HRV). We statically analyzed the difference of HRV parameters which include mean heart rate (MHRT), standard deviation of all N-N intervals (SDNN), square root of the mean of the sum of the squares of differences between adjacent N-N intervals (RMSSD), total power (TP), low frequency power (LF), high frequency power (HF), LF/HF ratio. Results All subjects showed significant increase in SDNN, LF after stress stimulation (p<0.05). Immediately after intervention, MHRT was significantly decreased (p<0.001) and RMSSD, HF were significantly increased in experimental group (p<0.05). After the end of intervention, SDNN, HF, RMSSD, TP, LF were significantly increased in experimental group (p<0.01, p<0.05). And when comparing baseline HRV, SDNN, LF were significantly increased in control group (p<0.01) and SDNN, RMSSD, TP, LF were significantly increased in experimental group (p<0.05). In the subgroup analysis, normal balance of ANS group showed significant increase in TP, LF, SDNN, HF (p<0.01, p<0.05). Conclusions We suggested that acupuncture at external ear, region of the vagus nerve distribution could increase parasympathetic activity and cause changes and reregulation of the ANS.

• 한국전문물리치료학회지
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• 제28권2호
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• pp.123-131
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• 2021

Background: Only 2% of falls in older adults result in serious injuries (i.e., hip fracture). Therefore, it is important to differentiate injurious versus non-injurious falls, which is critical to develop effective interventions for injury prevention. Objects: The purpose of this study was to a. extract the best features of surface electromyography (sEMG) for classification of injurious falls, and b. find a best model provided by data mining techniques using the extracted features. Methods: Twenty young adults self-initiated falls and landed sideways. Falling trials were consisted of three initial fall directions (forward, sideways, or backward) and three knee positions at the time of hip impact (the impacting-side knee contacted the other knee ("knee together") or the mat ("knee on mat"), or neither the other knee nor the mat was contacted by the impacting-side knee ("free knee"). Falls involved "backward initial fall direction" or "free knee" were defined as "injurious falls" as suggested from previous studies. Nine features were extracted from sEMG signals of four hip muscles during a fall, including integral of absolute value (IAV), Wilson amplitude (WAMP), zero crossing (ZC), number of turns (NT), mean of amplitude (MA), root mean square (RMS), average amplitude change (AAC), difference absolute standard deviation value (DASDV). The decision tree and support vector machine (SVM) were used to classify the injurious falls. Results: For the initial fall direction, accuracy of the best model (SVM with a DASDV) was 48%. For the knee position, accuracy of the best model (SVM with an AAC) was 49%. Furthermore, there was no model that has sensitivity and specificity of 80% or greater. Conclusion: Our results suggest that the classification model built upon the sEMG features of the four hip muscles are not effective to classify injurious falls. Future studies should consider other data mining techniques with different muscles.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권8호
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• pp.2068-2082
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• 2023

With the rapid development of deep learning, Depth Map Super-Resolution (DMSR) method has achieved more advanced performances. However, when the upsampling rate is very large, it is difficult to capture the structural consistency between color features and depth features by these DMSR methods. Therefore, we propose a color-image guided DMSR method based on iterative depth feature enhancement. Considering the feature difference between high-quality color features and low-quality depth features, we propose to decompose the depth features into High-Frequency (HF) and Low-Frequency (LF) components. Due to structural homogeneity of depth HF components and HF color features, only HF color features are used to enhance the depth HF features without using the LF color features. Before the HF and LF depth feature decomposition, the LF component of the previous depth decomposition and the updated HF component are combined together. After decomposing and reorganizing recursively-updated features, we combine all the depth LF features with the final updated depth HF features to obtain the enhanced-depth features. Next, the enhanced-depth features are input into the multistage depth map fusion reconstruction block, in which the cross enhancement module is introduced into the reconstruction block to fully mine the spatial correlation of depth map by interleaving various features between different convolution groups. Experimental results can show that the two objective assessments of root mean square error and mean absolute deviation of the proposed method are superior to those of many latest DMSR methods.

• Geomechanics and Engineering
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• 제34권6호
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• pp.697-726
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• 2023

Brittleness as an important property of rock plays a crucial role both in the failure process of intact rock and rock mass response to excavation in engineering geological and geotechnical projects. Generally, rock brittleness indices are calculated from the mechanical properties of rocks such as uniaxial compressive strength, tensile strength and modulus of elasticity. These properties are generally determined from complicated, expensive and time-consuming tests in laboratory. For this reason, in the present research, an attempt has been made to predict the rock brittleness indices from simple, inexpensive, and quick laboratory test results namely dry unit weight, porosity, slake-durability index, P-wave velocity, Schmidt rebound hardness, and point load strength index using multiple linear regression, exponential regression, support vector machine (SVM) with various kernels, generating fuzzy inference system, and regression tree ensemble (RTE) with boosting framework. So, this could be considered as an innovation for the present research. For this purpose, the number of 39 rock samples including five igneous, twenty-six sedimentary, and eight metamorphic were collected from different regions of Iran. Mineralogical, physical and mechanical properties as well as five well known rock brittleness indices (i.e., B₁, B₂, B₃, B₄, and B₅) were measured for the selected rock samples before application of the above-mentioned machine learning techniques. The performance of the developed models was evaluated based on several statistical metrics such as mean square error, relative absolute error, root relative absolute error, determination coefficients, variance account for, mean absolute percentage error and standard deviation of the error. The comparison of the obtained results revealed that among the studied methods, SVM is the most suitable one for predicting B₁, B₂ and B₅, while RTE predicts B₃ and B₄ better than other methods.