• 조명전기설비학회논문지
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• 제25권9호
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• pp.1-7
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• 2011

A performance delivers the contents and feeling through human bodies and stage settings in the limited space of a stage. Among the stage settings, the lighting creates overall atmospheres effectively according to the situations of the performance such as a time flow, a change of seasons, an expression of the mental state of the performer. As the LED lighting is used more widely, the number and the size of the lighting is being decreased, which makes it possible for various devices to be used. However, just as conventional lighting devices, most of them are fixed. So it is difficult to use them at a blind spot and to replace them. To solve this problem, this article suggests a system which replaces lighting automatically and moves. As it can moved to a spot we want on a rail, and the lighting system can be replaced by itself, it can have various lighting effects, increasing the effectiveness of the performance. Additionally, it can also decrease the danger of a worker operating the lighting device located at a high place. At the mock-up experiment, its mobility and stability on a rail were tested using the wheel of the Modular Robot.

• Structural Monitoring and Maintenance
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• 제2권4호
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• pp.399-418
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• 2015

Automated damage detection through Structural Health Monitoring (SHM) techniques has become an active area of research in the bridge engineering community but widespread implementation on in-service infrastructure still presents some challenges. In the meantime, visual inspection remains as the most common method for condition assessment even though collected information is highly subjective and certain types of damage can be overlooked by the inspector. In this article, a Frequency Response Functions-based model updating algorithm is evaluated using experimentally collected data from the University of Central Florida (UCF)-Benchmark Structure. A protocol for measurement selection and a regularization technique are presented in this work in order to provide the most well-conditioned model updating scenario for the target structure. The proposed technique is composed of two main stages. First, the initial finite element model (FEM) is calibrated through model updating so that it captures the dynamic signature of the UCF Benchmark Structure in its healthy condition. Second, based upon collected data from the damaged condition, the updating process is repeated on the baseline (healthy) FEM. The difference between the updated parameters from subsequent stages revealed both location and extent of damage in a "blind" scenario, without any previous information about type and location of damage.

• 대한소아치과학회지
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• 제33권1호
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• pp.53-61
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• 2006

미다졸람은 소아 환자의 진정시 흔히 사용되는 약물로서 안전성이 뛰어나고 사용이 편리하며 투여 방법이 다양하다. 여러 투여 방법 중, 주로 사용되는 근육내 투여 방법은 동통을 유발하기 때문에 어린이의 치과에 대한 공포를 가중시킬 수 있다. 따라서 근육내 투여의 이런 단점을 완화할 수 있도록 용량에 따른 미다졸람 경구 투여의 진정 효과를 근육내 투여시의 진정 효과와 비교 평가하고자 하였다. 총 12명의 환자를 실험대상으로 하였으며 이중 맹검법에 의해 두 번의 내원중 임의로 한 번은 Midazolam 0.75 mg/kg을 경구 투여하고, 한 번은 미다졸람 0.3mg/kg을 근육내 투여하여 치료하였으며, 치료과정 동안 환자의 생징후(말초 동맥혈 산소 포화도, 심박수)와 행동양상을 Ohio State University Behavior rating scale과 Automated Counting System을 사용하여 평가하였다. 생징후의 경우 양 군 모두 정상범위 내에서 안정된 양상을 보였으며, 임상적으로 바람직한 행동양상(Q:Quiet)의 비율이양 군에서 대부분 높게 나타났으며 양군간에 유의 한 차이를 보이지 않았다(p>0.05). 본 연구에서 미다졸람을 근육내 투여한 군과 경구 투여한 군 모두 진정 효과가 양호한 결과를 보였으며 양군간에 유의한 차이를 보이지 않았다(pgt;0.05).

• 대한원격탐사학회지
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• 제37권5_1호
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• pp.1149-1161
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• 2021

컴퓨터 비전 기술이 위성영상에 적용되면서, 최근 들어 딥러닝 영상인식을 이용한 구름 탐지가 관심을 끌고 있다. 본연구에서는 SPARCS (Spatial Procedures for Automated Removal of Cloud and Shadow) Cloud Dataset과 영상자료증대 기법을 활용하여 U-Net 구름탐지 모델링을 수행하고, 10폴드 교차검증을 통해 객관적인 정확도 평가를 수행하였다. 512×512 화소로 구성된 1800장의 학습자료에 대한 암맹평가 결과, Accuracy 0.821, Precision 0.847, Recall 0.821, F1-score 0.831, IoU (Intersection over Union) 0.723의 비교적 높은 정확도를 나타냈다. 그러나 구름그림자 중 14.5%, 구름 중 19.7% 정도가 땅으로 잘못 예측되기도 했는데, 이는 학습자료의 양과 질을 보다 더 향상시킴으로써 개선 가능할 것으로 보인다. 또한 최근 각광받고 있는 DeepLab V3+ 모델이나 NAS(Neural Architecture Search) 최적화 기법을 통해 차세대중형위성 1, 2, 4호 등의 구름탐지에 활용 가능할 것으로 기대한다.

• The Korean Journal of Pain
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• 제10권2호
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• pp.170-178
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• 1997

Background: The analgesic efficacy and safety of propacetamol, an injectable prodrug of acetoaminophen, in combination with intravenous morphine PCA were studied in 40 patients after gynecological surgery requiring lower abdominal incision. Methods: Using a double-blind, randomized, parallel-group design, the effects of four(every 6 hr) intravenous injections of 2 g propacetamol(=1 g acetoaminophen) were compared with four injections of placebo(PL) immediately after surgery. Efficacy of cumulative dose of morphine and number of boluses requested was assessed over 24 hours by automated recording on the PCA device. It was assessed on pain scores rated on a ten-point verbal scale along with vital signs, $K^+$, glucose, BUN, creatinine, PT and PTT were measured along with stress hormones(epinephrine, norepinephrine and cortisol). Results: There were no differences in demographic data between two groups. Propacetamol group demonstrated approximately 21% morphine sparing effect compared to placebo group($33.1{\pm}10.4$ mg vs $41.4{\pm}8.0$ mg). No significant differences noted in $K^+$, glucose, BUN, Creatinine, PT and PTT levels. There were significant increases in norepinephrine and cortisol in placebo group postoperatively, compared to preoperative values. At the same time, propacetamol group also showed significant changes in these hormones. Both group revealed high degree of patient satisfaction. Conclusion: Propacetamol showed significant morphine sparing effect to some degree. Side effects were much less in propacetamol group with subsequently high patient satisfaction. The secretion of stress hormone were not blocked by postoperative propacetamol injections. Authors concluded that propacetamol should be considered as an excellent adjuvant analgesics in postoperative pain control in opioid patient controlled analgesia.

• Smart Structures and Systems
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• 제29권1호
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• pp.77-91
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• 2022

Various monitoring systems have been implemented in civil infrastructure to ensure structural safety and integrity. In long-term monitoring, these systems generate a large amount of data, where anomalies are not unusual and can pose unique challenges for structural health monitoring applications, such as system identification and damage detection. Therefore, developing efficient techniques is quite essential to recognize the anomalies in monitoring data. In this study, several machine learning techniques are explored and implemented to detect and classify various types of data anomalies. A field dataset, which consists of one month long acceleration data obtained from a long-span cable-stayed bridge in China, is employed to examine the machine learning techniques for automated data anomaly detection. These techniques include the statistic-based pattern recognition network, spectrogram-based convolutional neural network, image-based time history convolutional neural network, image-based time-frequency hybrid convolution neural network (GoogLeNet), and proposed ensemble neural network model. The ensemble model deliberately combines different machine learning models to enhance anomaly classification performance. The results show that all these techniques can successfully detect and classify six types of data anomalies (i.e., missing, minor, outlier, square, trend, drift). Moreover, both image-based time history convolutional neural network and GoogLeNet are further investigated for the capability of autonomous online anomaly classification and found to effectively classify anomalies with decent performance. As seen in comparison with accuracy, the proposed ensemble neural network model outperforms the other three machine learning techniques. This study also evaluates the proposed ensemble neural network model to a blind test dataset. As found in the results, this ensemble model is effective for data anomaly detection and applicable for the signal characteristics changing over time.

• Journal of Ginseng Research
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• 제47권6호
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• pp.766-772
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• 2023

Background: Korean Red Ginseng (KRG) is an effective anti-stress treatment. In this study, we investigated the therapeutic potential effects of KRG on relieving stress in a general population using transcriptome analysis. Methods: We conducted an 8-week clinical pilot study on 90 healthy men who reported stress. The study was completed by 43 participants in the KRG group and 44 participants in the placebo group. Participants were randomized 1:1 to the KRG and placebo groups. We evaluated the stress by stress response inventory (SRI) at baseline and 8 weeks. The main outcomes were changes in the levels of neurotransmitters (NTs) and NT-related gene expression. NTs were analyzed using automated (GC) content, and levels of gene expression were measured by reads per kilobase of transcript per million mapped reads (RPKM). Results: The KRG group showed significantly preserved epinephrine decrease compared with placebo group at 8 weeks (changes in epinephrine, KRG vs. placebo; -1623.2 ± 46101.5 vs. -35116.3 ± 86288.2, p = 0012). Among subjects who higher SRI score, meaning stress increased compared to baseline, the KRG group showed a smaller decrease in serotonin than the placebo group (changes in serotonin, KRG vs. placebo; -2627.5 ± 5859.1 vs, -8087.4 ± 7162.4, p = 0.005) and a smaller increase in cortisol than the placebo group (changes in cortisol, KRG vs. placebo; 1912.7 ± 10097.75 vs. 8046.2 ± 8050.6 , p = 0.019) in subgroup analysis. Transcriptome findings indicated that KRG intake affects gene expression related with metabolism of choline, adrenalin, and monoamine. Conclusion: These findings suggest that KRG has beneficial effects on the amelioration of stress response in NTs, and this effect is more prominent in stressful situations. Further clinical studies are required to confirm the anti-stress effect of KRG.

• 대한소아치과학회지
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• 제32권3호
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• pp.416-426
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• 2005

소아환자는 치과치료시 다양한 방법의 진정요법이 요구된다. 정맥내 투여방법은 약효의 발현이 빠르고, 진정의 심도 및 시간을 술자의 의도대로 조절할 수 있다는 장점이 있다. Midazolam은 현재 의과 및 치과영역에서 성인의 진정요법에 가장 널리 쓰이며, 심혈관계와 호흡계에 대한 영향이 적은 진정 약제이다. 그러나 midazolam을 이용한 정맥내 진정요법의 소아치과에서의 사용에 대한 연구와 보고는 적은 편으로, 이에 본 연구에서는 소아환자에서의 midazolam을 이용한 정맥내 투여시 효과적이고 안전한 초기 투여용량에 관한 연구를 하고자 한다. 진정요법으로 2회 이상의 구치부 치료가 필요한 건강하고 비협조적인 행동을 보이는 16명의 환자를 대상으로 하였으며 평균연령은 $54.7{\pm}10.7$개월, 평균 몸무게는 $18.1{\pm}3.0kg$이었다. 술전 투약으로 0.3mg/kg, 최대 5mg의 midazolam을 근육내 투여 후 30~50%의 $N_2O-O_2$를 병용투여한다. 이중 맹검법에 의해 모든 환자는 두 번의 내원 중 임의로 한번은 0.1mg/kg(I군)을, 다른 한번은 0.2mg/kg(II군)의 초기 용량의 midazolam을 정맥내 투여하여 치료하였고, 추가투여시에는 초기용량의 1/2을 투여하였다. 치료시 환자의 생징후를 측정하였고, 행동양상은 Ohio State University Behavioral Rating Scale과 Automated Counting System을 사용하여 평가하였다. 술자는 Houpt가 제시한 기준을 응용하여 임상적 치료의 성공과 실패를 평가하였다. 몸무게에 대한 총 투여용량은 I군에서 0.16mg/kg, 2군에서 0.24 mg/kg 이었다. 생징후의 경우 두 군 모두 정상범위 내에서 안정된 상태를 보였고, 통계적으로 유의한 차이를 보이지 않았다(p>0.05). 행동양상평가에서 II군에서 바람직한 행동양상(Quiet)의 비율이 높았고, 임상적 성공률은 II군에서 높았으나, 두 군간 통계학적 유의차는 보이지 않았다(p>0.05). 작용 발현시간은 II군에서, 회복시간은 I군에서 빨랐고, 약물 투여 횟수는 I군에서 많았으나, 두 군간 통계학적으로 유의한 차이를 보이지 않았다(p>0.05).