• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2007년도 추계 종합학술대회 논문집
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• pp.282-285
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• 2007

스폰서십의 효과를 결정짓는 여러 요인 중 기업이 스폰서하는 공동체(community)의 구성원들이 어떤 태도를 가지고 있는가 하는 점이 가장 중요한 요인이라 할 수 있다. 공동체 구성원의 태도를 이해하는데 매우 중요한 이론으로 동일시(identification) 혹은 일체감 이론을 생각할 수 있다. 공동체 구성원이 자신이 속한 공동체에 어느 정도의 일체감을 느끼는가에 따라 공동체에 대한 행동과 공동체에 스폰서하는 기업에 대한 태도가 달라질 수 있다. 본 연구에서는 공동체의식 개념을 적용하여 공동체 일체감의 주요 선행요인을 확인하고, 공동체 일체감과 기업의 스폰서십에 대한 반응 간의 관계를 살펴보고자 하였다. 연구결과 공동체 의식이 공동체 일체감과 공동체에 대한 충성도에 영향을 미치는 것을 알 수 있었다. 공동체 의식의 세부 요소별로 보면, 욕구의 충족, 소속감, 정서적 유대감은 공동체 일체감과 공동체 충성도에 모두 긍정적 영향을 미치며, 영향력은 공동체 충성도에만 영향을 미치는 것을 알 수 있었다. 또한 공동체 일체감이 높을수록 공동체 충성도가 높아지며, 공동체 충성도가 높아지면 스폰서에 대한 태도가 개선되는 반응이 나타남을 확인할 수 있었다.

• Journal of the Korean Wood Science and Technology
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• 제45권6호
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• pp.797-808
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• 2017

Automatic wood species identification systems have enabled fast and accurate identification of wood species outside of specialized laboratories with well-trained experts on wood species identification. Conventional automatic wood species identification systems consist of two major parts: a feature extractor and a classifier. Feature extractors require hand-engineering to obtain optimal features to quantify the content of an image. A Convolutional Neural Network (CNN), which is one of the Deep Learning methods, trained for wood species can extract intrinsic feature representations and classify them correctly. It usually outperforms classifiers built on top of extracted features with a hand-tuning process. We developed an automatic wood species identification system utilizing CNN models such as LeNet, MiniVGGNet, and their variants. A smartphone camera was used for obtaining macroscopic images of rough sawn surfaces from cross sections of woods. Five Korean softwood species (cedar, cypress, Korean pine, Korean red pine, and larch) were under classification by the CNN models. The highest and most stable CNN model was LeNet3 that is two additional layers added to the original LeNet architecture. The accuracy of species identification by LeNet3 architecture for the five Korean softwood species was 99.3%. The result showed the automatic wood species identification system is sufficiently fast and accurate as well as small to be deployed to a mobile device such as a smartphone.

• 대한한방내과학회지
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• 제36권2호
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• pp.122-152
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• 2015

Objectives: This study was designed to develop a standard tool for pattern identification of gastroesophageal reflux disease (GERD) patients. Methods: Korean and Chinese literature was selected that mentioned pattern identification of GERD. We gathered the pattern identification and their symptoms and a Chinese medical doctor proficient in Korean translated the Chinese characters into Korean. A Korean linguist then confirmed the translation results to develop a draft of the standard tool for pattern identification of gastroesophageal reflux disease (PIGERD). The final PIGERD was developed after assessment by an expert committee composed of professors from the Korean Medicine University, using the following items: inclusion of the pattern identification and its symptoms, importance of items, and validity of translation. Results: Six pattern identifications and 94 symptoms were selected from 45 references and translated into Korean. Four pattern identifications [pattern/syndrome of liver qi invading the stomach (肝胃不和), spleen-stomach weakness (脾胃虛弱), spleen-stomach dampness-heat (脾胃濕熱), and stomach yin deficiency (胃陰不足)] and 49 symptoms were then selected through the Delphi method by the expert committee. The final standard PIGERD tool was completed after the assessment of translation validity and reflection of individual opinions by the expert committee. This tool consists of 40 items including tongue and pulse diagnosis. The weighted value was also computed from assessment of the importance of items. Conclusions: We developed a standard tool for pattern identification of gastroesophageal reflux disease (PIGERD) to clarify the pattern identification of patients with gastroesophageal reflux disease for standardized diagnosis.

• 대한예방한의학회지
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• 제23권2호
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• pp.101-115
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• 2019

Objective : This study is aimed to application possibility and status of pattern identification in middle and high school students. Method : This study was cross-sectional study. We recruited 277 students through school doctor program of Seongnam city in 2017. Male students are 66 in middle school, 32 in high school. Female students are 117 in middle school, 62 in high school. For pattern identification, we used the tool of Qui Xui Shui pattern identification in students. Students fill questionnaires in inquiry of pattern identification and Korean medicine doctor diagnosis inspection and palpation of students. Results : Among 277 students, no pattern identification were 114(41.2%). It appeared in the order of phlegm, blood deficinecy, qi deficiency, qi stagnation and qi reversal. Qi deficiency, qi stagnation, qi reversal, blood deficiency and phlegm pattern are statistically significant by gender except blood stagnation. of 277 students, 105 (37.9%) had one more pattern identification. Conclusions : This study showed possibility of Qui Xui Shui pattern for student health management. In the future, large scale follow up study will be needed to clarify the relationship of pattern identification and student's health.

• 동의생리병리학회지
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• 제34권6호
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• pp.362-371
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• 2020

In order to find out the relationship between the Eight Principle Pattern Identification of Yin-Yang, Exterior-Interior and the Sasang constitution, we analyzed the clinical data from 500 women with menstrual pain and women without menstrual pain. In the previous study, the subject's information of Typology Complexion Pulse and Symptom was collected, and Eight Principle Pattern Identification was executed based on this. Later, The relationship between the Sasang constitution and the Eight Principle Pattern Identification was statistically analyzed. The obvious difference between the experimental group and the control group in the patterns of Yin-Yang and Exterior-Interior is that patients who complain of menstrual pain do not maintain harmony with the yin-yang ratio, it can be said that the patterns of Yin-Yang and Exterior-Interior can be a identification standard that significantly obscures the condition of the disease. There was a significant difference between the Sasang constitution and the Eight Principle Pattern Identification of Yin-Yang. There was no significant difference between the Sasang constitution and the Eight Principle Pattern Identification of Exterior-Interior. It is assumed that the relationship between the Eight Principle Pattern Identification and the Sasang constitution has changed depending on the difference a view of emotional Qi and pathogenic Qi.

• 대한치과교정학회지
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• 제51권2호
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• pp.77-85
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• 2021

Objective: To evaluate the accuracy of a multi-stage convolutional neural network (CNN) model-based automated identification system for posteroanterior (PA) cephalometric landmarks. Methods: The multi-stage CNN model was implemented with a personal computer. A total of 430 PA-cephalograms synthesized from cone-beam computed tomography scans (CBCT-PA) were selected as samples. Twenty-three landmarks used for Tweemac analysis were manually identified on all CBCT-PA images by a single examiner. Intra-examiner reproducibility was confirmed by repeating the identification on 85 randomly selected images, which were subsequently set as test data, with a two-week interval before training. For initial learning stage of the multi-stage CNN model, the data from 345 of 430 CBCT-PA images were used, after which the multi-stage CNN model was tested with previous 85 images. The first manual identification on these 85 images was set as a truth ground. The mean radial error (MRE) and successful detection rate (SDR) were calculated to evaluate the errors in manual identification and artificial intelligence (AI) prediction. Results: The AI showed an average MRE of 2.23 ± 2.02 mm with an SDR of 60.88% for errors of 2 mm or lower. However, in a comparison of the repetitive task, the AI predicted landmarks at the same position, while the MRE for the repeated manual identification was 1.31 ± 0.94 mm. Conclusions: Automated identification for CBCT-synthesized PA cephalometric landmarks did not sufficiently achieve the clinically favorable error range of less than 2 mm. However, AI landmark identification on PA cephalograms showed better consistency than manual identification.

• 한국빅데이터학회지
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• 제5권2호
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• pp.43-52
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• 2020

빅데이터 활용 기술의 발전으로 데이터의 저장 및 공유가 늘어나면서 그에 따른 프라이버시 침해가 일어나게 되었다. 이 문제를 해결하기 위해 비식별 기술이 도입되었지만 비식별된 데이터에 대해서도 재식별이 가능하다는 것이 여러 차례 증명되었다. 재식별 가능성이 존재하기 때문에 완전히 안전할 수 없지만 그럼에도 불구하고 충분한 비식별처리가 이루어져야 하는데, 현재 법령이나 규제는 어느 정도로 비식별 처리를 해야 하는지 정량적으로 규정하고 있지 않다. 본 논문에서는 재식별 작업을 할 때 소요되는 시간을 고려하여 적절한 비식별 기준을 제시하려고 한다. 다양한 비식별 평가 모델 중에서 k-익명성 모델에 대해 집중적으로 연구하였으며 어느 정도의 k값이 적절한 지 판단하였다. 본 연구의 결과를 일반화시킬 수 있다면 각종 법률 및 규제에서 적절한 비식별 강도를 규정하는 데 사용할 수 있을 것이다.

• 한국심리학회지:학교
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• 제18권2호
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• pp.221-247
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• 2021

본 연구에서는 전문상담교사의 역할정체성 혼란이 소진 및 직무 만족에 미치는 효과를 살펴 보았다. 전문상담교사의 역할정체성 혼란이 소진 및 직무 만족에 영향을 미치는 경로를 설명하는 매개변인으로 역할갈등을, 이러한 매개효과를 조절하는 변인으로 직무의미창조를 설정하였다. 설문조사를 통해 전문상담교사 총 150명의 응답을 수집하여 분석한 결과, 역할정체성 혼란은 역할갈등 및 소진과 정적 상관, 직무 만족과 부적 상관이 있는 것으로 나타났다. 또한 역할갈등이 역할정체성 혼란과 소진 및 직무 만족의 관계를 매개하는 것으로 나타나, 역할정체성 혼란이 소진 및 직무 만족에 직접적으로 영향을 미치기보다는 역할갈등을 통해 간접적으로 영향을 미치는 것으로 나타났다. 한편 변인들의 경로에서 직무의미창조에 의한 조절된 매개효과는 없는 것으로 나타났다. 논의에서는 연구 결과의 함의와 연구의 한계에 대해 기술하였다.

• 대한중풍순환신경학회지
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• 제9권1호
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• pp.8-13
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• 2008

Objectives : This study was to investigated the correlation between average temperature & precipitation and pattern identification of the patients with stroke. Methods : 115 stroke patients within 30days of onset were registered during the study period. Pattern identification of stroke was classified into Fire and heat, Turbid phlegm and others. We took the mean of average temperature according to pattern identification and analyzed pattern identification into two groups according to climatological normal of average temperature in Seoul. We also analyzed pattern identification into two groups according to existence of precipitation. Results : Heat and fire, and other type of pattern identification had high frequency when average temperature was higher than 12.2℃. And there was no correlation between precipitation and pattern identification of stroke.

• Smart Structures and Systems
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• 제31권3호
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• pp.229-245
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• 2023

The absence of excitation measurements may pose a big challenge in the application of structural damage identification owing to the fact that substantial effort is needed to reconstruct or identify unknown input force. To address this issue, in this paper, an iterative strategy, a synergy of Tikhonov regularization method for force identification and modified Jaya algorithm (M-Jaya) for stiffness parameter identification, is developed for damage identification with partial output-only responses. On the one hand, the probabilistic clustering learning technique and nonlinear updating equation are introduced to improve the performance of standard Jaya algorithm. On the other hand, to deal with the difficulty of selection the appropriate regularization parameters in traditional Tikhonov regularization, an improved L-curve method based on B-spline interpolation function is presented. The applicability and effectiveness of the iterative strategy for simultaneous identification of structural damages and unknown input excitation is validated by numerical simulation on a 21-bar truss structure subjected to ambient excitation under noise free and contaminated measurements cases, as well as a series of experimental tests on a five-floor steel frame structure excited by sinusoidal force. The results from these numerical and experimental studies demonstrate that the proposed identification strategy can accurately and effectively identify damage locations and extents without the requirement of force measurements. The proposed M-Jaya algorithm provides more satisfactory performance than genetic algorithm, Gaussian bare-bones artificial bee colony and Jaya algorithm.