• 대한본초학회지
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• 제36권1호
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• pp.77-85
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• 2021

Objective : This study was designed to investigate effect of immature fruits from Citrus unshiu Markovich to mature them on antioxidative and antiaging-related enzyme activities in vitro. Methods : Fruits from Open field-cultivated C. unshiu Markovich (ripe and unripe fruits of Citri) made a purchase in Jeju island. We measured total polyphenol and flavonoid contents in mature C. unshiu Markovich (MC) and immature C. unshiu Markovich (IMC) 70% ethanol extract. DPPH free radical, ABTS radical, and hydroxyl radical scavenging activities in both extracts were determined. Also, reducing power, SOD-like activities, elastase inhibition, and collagenase inhibition activities of these extract were assayed at 5, 1, 0.5, and 0.1 mg/㎖. Results : The total polyphenol contents in the ethanol extract of IMC were higher than those of MC (26.99 ± 0.89 mg/TAEg). And total flavonoid contents in them were very similar to both extract (MC; 7.25 ± 0.4 mg/RUEg and IMC; 7.44 ± 0.18 mg/RUEg). DPPH free radical scavenging activities, ABTS radical scavenging capacity, reducing power, and SOD-like activities of IMC-treated group showed significant increase compared to those of MC group in all treated concentrations. Particularly, DPPH free radical scavenging and elastase inhibition activities in IMC-treated group at 5 mg/㎖ showed similar with positive control group. Besides, IMC extract at 5 mg/㎖ concentration surpassed positive control (BHA or Vit. C) in SOD-like activities and ABTS radical scavenging capacity. Conclusion : These results suggest that IMC ethanol extract may be used as a natural antioxidant and a antiaging material for development of functional foods and cosmeceuticals.

• 한국정보전자통신기술학회논문지
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• 제15권1호
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• pp.62-68
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• 2022

의술과 경제적 발전으로 인해 예쁘고 건강한 치아를 복원 또는 유지하기 위해 다양한 치료 방법들이 연구되고 있으며 특히 치아의 손실을 복원하는 보철치료, 미백과 같은 심미 치료 시술에 대한 관심이 증가하고 있다. 보철 및 심미 치료 분야에 있어 중요한 것 중 하나가 치아의 정확한 색상을 결정하는 것인데 이는 자연치와의 조화가 심미 보철물의 완성도를 결정 짓는 중요한 요소이기 때문이다. 본 연구는 스마트폰을 카메라를 활용하여 치아 측색 위한 측색 애플리케이션 개발에 대한내용으로서, 측색 애플리케이션 UI를 설계하고, 측색 알고리즘을 도출하여 애플리케이션을 구현하였으며, 구현된 애플리케이션에 대한 테스트를 통해 유효성에 대한 검증을 진행했다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권7호
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• pp.2390-2406
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• 2022

Scene text recognition has important application value and attracted the interest of plenty of researchers. At present, many methods have achieved good results, but most of the existing approaches attempt to improve the performance of scene text recognition from the image level. They have a good effect on reading regular scene texts. However, there are still many obstacles to recognizing text on low-quality images such as curved, occlusion, and blur. This exacerbates the difficulty of feature extraction because the image quality is uneven. In addition, the results of model testing are highly dependent on training data, so there is still room for improvement in scene text recognition methods. In this work, we present a natural scene text recognizer to improve the recognition performance from the feature level, which contains feature representation and feature enhancement. In terms of feature representation, we propose an efficient feature extractor combined with Representative Batch Normalization and ResNet. It reduces the dependence of the model on training data and improves the feature representation ability of different instances. In terms of feature enhancement, we use a feature enhancement network to expand the receptive field of feature maps, so that feature maps contain rich feature information. Enhanced feature representation capability helps to improve the recognition performance of the model. We conducted experiments on 7 benchmarks, which shows that this method is highly competitive in recognizing both regular and irregular texts. The method achieved top1 recognition accuracy on four benchmarks of IC03, IC13, IC15, and SVTP.

• Journal of Ginseng Research
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• 제46권4호
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• pp.543-549
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• 2022

Background: In physical activity or labor, the human body is in a state of high intensity stress, and all parts or physiological functions of the body respond positively to maintain or balance the need for movement. The human body has many physiological changes in the process of movement, and fatigue is the external manifestation of various complex changes inside the human body. Fatigue is also a physiological mechanism of self-protection after the body reaches a certain level of activity, which can prevent the occurrence of life-threatening excessive functional failure. The generation of fatigue is a very complex process, and its mechanism has not been concluded yet. Therefore, it is an important work to search and screen the effective components of natural plants that have anti-fatigue effect and to explore their mechanism. Methods: This was a 8-week, randomized, double-blind, placebo-controlled clinical trial. A total of 110 subjects who passed physical examination were included according to the scheme design, and randomly divided into a test group which was given KRG and a placebo control group. The calculation is carried out according to the standard of sub-high-intensity exercise test. Results: There was no adverse effect on safety index of subjects after taking red ginseng capsule. After KRG treatment, subjective strength grade is significant lower than placebo treatment. Blood lactic acid content is significantly get lower after trial in KRG group, and significant lower than placebo group. Creatine phosphokinase(CK) content is significantly get lower after trial in KRG group, and significant lower than placebo group. Conclusion: According to the criterion in the test scheme, the result shows that KRG is helpful on relieving physical fatigue.

• 한국추진공학회지
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• 제25권2호
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• pp.119-143
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• 2021

최근 발사체 개발의 큰 흐름을 살펴보면, 친환경, 저비용, 재사용, 심우주 탐사를 위한 저장성, 외부행성에서의 추진제 확보 가능성 등의 이유로 액체 메탄이 로켓 연료로 각광 받기 시작했다. 재사용 발사체 기술의 보편화, 국제적인 엔진개발 추세에 발맞춰 미래의 경쟁력과 임무 유연성을 확보하려면 엔진 개발 기간 등을 고려해서 가능한 빨리 메탄엔진 개발을 추진해야 하며, 제작 및 시험 인프라, 활용성, 개발 비용 등을 종합적으로 고려하면 부스터 엔진보다 저추력 엔진을 선행 개발하는 것이 더 적절한 것으로 판단된다.

• 한국음향학회지
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• 제40권6호
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• pp.671-677
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• 2021

본 연구의 목적은 마감모르타르의 물결합재비가 공동주택 바닥충격음에 미치는 영향을 조사하는 것이다. 이를 위하여 동일한 동탄성계수를 지닌 Expanded Polystyrene(EPS) 완충재와 52 %, 66 %, 72 % 의 물결합재비를 가진 모르타르를 활용하여 뜬바닥구조를 시공하였으며, 표준실험동에서 바닥충격음을 측정하였다. 실험결과, 경량충격음에 있어서는 물결합재비 52 % 일 때, 밀도가 높은 관계로 경량충격음 전달특성이 높게 나타났다. 마감모르타르의 물결합재비가 높아지면 완충재 상부층 질량이 낮아지고, 이로 인해 뜬바닥구조의 고유진동수가 63 Hz 대역으로 이동하게 되면서 중량충격음의 음압레벨이 높게 나타났다. 이를 통하여 마감모르타르의 물결합재비가 중량충격음에 미치는 특성을 규명하였다.

• Imaging Science in Dentistry
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• 제52권4호
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• pp.383-391
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• 2022

Purpose: Periodontitis, the most prevalent chronic inflammatory condition affecting teeth-supporting tissues, is diagnosed and classified through clinical and radiographic examinations. The staging of periodontitis using panoramic radiographs provides information for designing computer-assisted diagnostic systems. Performing image segmentation in periodontitis is required for image processing in diagnostic applications. This study evaluated image segmentation for periodontitis staging based on deep learning approaches. Materials and Methods: Multi-Label U-Net and Mask R-CNN models were compared for image segmentation to detect periodontitis using 100 digital panoramic radiographs. Normal conditions and 4 stages of periodontitis were annotated on these panoramic radiographs. A total of 1100 original and augmented images were then randomly divided into a training (75%) dataset to produce segmentation models and a testing (25%) dataset to determine the evaluation metrics of the segmentation models. Results: The performance of the segmentation models against the radiographic diagnosis of periodontitis conducted by a dentist was described by evaluation metrics(i.e., dice coefficient and intersection-over-union [IoU] score). MultiLabel U-Net achieved a dice coefficient of 0.96 and an IoU score of 0.97. Meanwhile, Mask R-CNN attained a dice coefficient of 0.87 and an IoU score of 0.74. U-Net showed the characteristic of semantic segmentation, and Mask R-CNN performed instance segmentation with accuracy, precision, recall, and F1-score values of 95%, 85.6%, 88.2%, and 86.6%, respectively. Conclusion: Multi-Label U-Net produced superior image segmentation to that of Mask R-CNN. The authors recommend integrating it with other techniques to develop hybrid models for automatic periodontitis detection.

• 한국지반공학회논문집
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• 제23권3호
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• pp.101-109
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• 2007

국내 풍화토사면의 경우 순수 균질 사면보다는 대부분 점토 및 세립분이 섞인 비균질 상태로 존재하며 이러한 함유비율은 풍화도 및 지역에 따라 다르다. 따라서 세립분함량 변화에 따른 불포화사면에의 분석을 위해, 화강풍화토(SW)에 일정비율의 세립분(CH)을 섞어 성형한 시료를 통해 GCTS pressure plates을 이용한 함수특성곡선 실험을 수행하였다. 실험 및 침투해석결과 강우지속시간에 따른 포화깊이의 증가율은 세립분이 증가할수록 또한 상대밀도가 증가할수록 작아졌다. 또한 침투해석과 포화 및 불포화강도정수를 이용한 사면 안정성 해석결과(SLOPE/W), 전반적으로 세립분함량 $10\sim15%$의 범위까지는 침투깊이 증가에 따른 흡수력 변화가 안전율에 지대한 영향을 미치는 반면 이를 초과하는 경우(>15%)에는 오히려 세립분함량 증가에 따른 강도정수의 변화가 크게 영향을 미침을 알 수 있었다.

• 디자인융복합연구
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• 제17권3호
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• pp.1-19
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• 2018

수부재활훈련도구는 저하된 수부 기능 회복 및 전체적인 수부 기능 향상을 필요로 하는 환자와 사용자들을 위해 병원 및 가정에서 치료와 함께 병행한다. 이에 따라 다양한 목적의 수부재활훈련도구의 개발 또한 함께 이루어 지고 있으며, 많은 도구가 보급되어 각 병원에서 규정한 프로세스로 재활훈련을 진행하고 있다. 그러나 현재 병원에서 활용하는 훈련도구들은 점진적인 시스템으로 구성되어 있지 않고 일정 시간동안 단순반복성 동작을 유도한다. 따라서 재활훈련을 하는 환자들이 무료함을 느끼며 재활에 대한 동기부여를 갖지 못하므로 지속적이고 효과적인 훈련이 어렵다. 또한, 훈련에 활용되는 도구들은 고가인 경우가 대부분이며, 공간적 제한성으로 인해 환자의 자발적 재활훈련을 어렵게 한다. 이는 환자의 경제적 부담을 가중시킴과 동시에 올바른 신체적 향상을 가져오지 못하는 문제로 이어질 수 있다. 이러한 논점을 바탕으로 본 연구는 놀이요소 중 하나인 실뜨기를 접목해 과제를 통한 효과적 재활훈련이 이루어질 수 있도록 하고, 경제적이며 자유로운 재활이 이루어질 수 있도록 하고자 한다. 이를 위해 도구의 특성과 사용자 환경을 조사한 후 실뜨기 놀이와, 훈련도구와의 관련성 및 지속적인 재활이 가능한지에 대한 타당성을 확인하고 전문가 인터뷰를 통해 디자인 요소를 도출하였다. 이후 디자인 가이드라인 및 프로토타입을 제작해 사용성 테스트 및 디자인요소 평가를 진행하여 문제점을 보완하였다.

• Computers and Concrete
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• 제32권2호
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• pp.149-163
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• 2023

One of the main design parameters traditionally utilized in projects of geotechnical engineering is the uniaxial compressive strength. The present paper employed three artificial intelligence methods, i.e., the stochastic fractal search (SFS), the multi-verse optimization (MVO), and the vortex search algorithm (VSA), in order to determine the compressive strength of concrete (CSC). For the same reason, 1030 concrete specimens were subjected to compressive strength tests. According to the obtained laboratory results, the fly ash, cement, water, slag, coarse aggregates, fine aggregates, and SP were subjected to tests as the input parameters of the model in order to decide the optimum input configuration for the estimation of the compressive strength. The performance was evaluated by employing three criteria, i.e., the root mean square error (RMSE), mean absolute error (MAE), and the determination coefficient (R²). The evaluation of the error criteria and the determination coefficient obtained from the above three techniques indicates that the SFS-MLP technique outperformed the MVO-MLP and VSA-MLP methods. The developed artificial neural network models exhibit higher amounts of errors and lower correlation coefficients in comparison with other models. Nonetheless, the use of the stochastic fractal search algorithm has resulted in considerable enhancement in precision and accuracy of the evaluations conducted through the artificial neural network and has enhanced its performance. According to the results, the utilized SFS-MLP technique showed a better performance in the estimation of the compressive strength of concrete (R²=0.99932 and 0.99942, and RMSE=0.32611 and 0.24922). The novelty of our study is the use of a large dataset composed of 1030 entries and optimization of the learning scheme of the neural prediction model via a data distribution of a 20:80 testing-to-training ratio.