• 한국동물생명공학회지
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• 제34권4호
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• pp.280-291
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• 2019

Potential utility of 14 candidate housekeeping genes as normalization reference for RT-qPCR analysis with developmental samples (fertilized eggs to late veliger larvae) in Pacific abalone Haliotis discus hannai was evaluated using four different statistical algorithms (geNorm, NormFinder, BestKeeper and comparative ΔCT method). Different algorithms identified different genes as the best candidates, and geometric mean-based final ranking from the most to the least stable expression was as follow: RPL5, RPL4, RPS18, RPL8, RPL7, UBE2, RPL7A, GAPDH, RPL36, PPIB, EF1A, ACTB and B-TU. The findings were further validated via relative quantification of metallothionein (MT) transcripts using the stable and unstable reference genes, and expression levels of MT were greatly influenced according to the choice of reference genes. In overall, our data suggest that RPL5 and RPS18, either singly or in combination, are appropriate for normalizing gene expression in developmental samples of this abalone species, whereas ACTB, B-TU and EF1A are less stable and not recommended. In addition, our findings propose that standard deviations in geometric ranking as well as geometric mean itself should also be taken into account for the final selection of reference gene(s). This study could be a useful basis to facilitate the generation of accurate and reliable RT-qPCR data with developmental samples in this abalone species.

• 화약ㆍ발파
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• 제35권4호
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• pp.1-9
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• 2017

본 연구는 인공절리를 이용한 발파효과 검토를 위해 인공절리 수, 인공절리 간격, 인공절리 경사에 따른 발파속도의 영향 및 기여도를 평가 분석한 연구이다. 인공절리 상태 변화에 따른 발파속도는 동적해석 프로그램인 AUTODYN을 이용하여 획득하였다. 수치해석 결과에 대해 정규화 분석을 수행하였고, 각 인자의 기여도 분석을 위해 강건설계 실험계획법을 이용하여 설계 인자를 분석하였다. 각 인자는 3수준으로 설정하였고, 분석에 직교 배열표 $L_9(3^4)$를 사용하였다. 정규화 분석을 통해 수치해석 결과를 분석한 결과 인공절리 경사가 증가함에 따라 발파속도는 감소하는 경향을 보였다. 또한, 인공절리 간격과 인공절리 경사에 대해 발파속도를 분석한 결과 발파속도는 경사가 수직일 때 인공절리 간격이 증가함에 따라 감소는 경향을 보였다. 강건설계를 이용한 기여율 분석결과 발파속도에 가장 큰 영향을 미치는 것은 인공절리 경사이며, 이어서 인공절리 수, 인공절리 간격 순으로 기여율이 평가되었다.

• 대한두경부종양학회지
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• 제15권1호
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• pp.52-60
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• 1999

Objectives: For investigation of the differentiation between transient and permanent hypocalcemia, we focused on a postoperative calcium requirement and an interval of normalization in serum hypocalcemic level and studied for the causes of postoperative hypocalcemia. Material and Method: Postthyroidectomy hypocalcemia was studied in 193 patients who were admitted from January, 1991 to December, 1998 and underwent lobectomy, subtotal thyroidectomy or total thyroidectomy. We compared postoperative serum calcium, phosphate and ionized calcium levels among three groups which were lobectomy, subtotal thyroidectomy and total thyroidectomy, respectively. Result: All patients revealed postoperative decline in serum calcium and ionized calcium, especially, the lowest serum calcium level was seen in 48 hours after surgery. Serum calcium level was returned to normal in five to six postoperative days in most patients. But 24 patients required calcium supplementation due to symptomatic hypocalcemia. In this series, we discovered that the important period for monitoring of serum calcium level was 24 to 96 hours after surgery. If the calcium replacement therapy was not required in the first 72 hours after surgery, it would not be needed during the remainder of the patient's hospital course. Symptomatic transient hypocalcemia was 22 cases(11.4%) and permanent hypocalcemia was 2 cases(1%). Conclusion : We found that hypoalbuminemia, preoperative hyperthyroidism and impairment of blood supply to parathyroid were the main causes of postthyroidectomy hypocalcemia. We also thought that the interval from initial medication to normalization in serum calcium level, and the increase of requirement in calcium and vitamin D were the important factors for differentiation between transient and permanent hypocalcemia.

• Journal of Information Science Theory and Practice
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• 제4권1호
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• pp.21-29
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• 2016

Given the difference in research performance in various scientific fields, this study aims to weight and valuate current indicators used for evaluation of scientific productions (publications), in order to adjust these indicators in comparison to each other and make possible a more precise evaluation of scientific productions. This is a scientometrics study using documentary, evaluative, and survey techniques. The statistical population consisted of 106 top Iranian researchers, scientists, and scientific and research managers. Then their research résumé information was gathered and analyzed based on research questions. In order to compare values, the data gathered from research production performance of the population was weighted using Shannon entropy method. Also, the weights of each scientific production importance according to expert opinions (extracted from other works) was analyzed and after adjustment the final weight of each scientific production was determined. A pairwise matrix was used in order to determine the ratios. According to the results, in the area of engineering sciences, patents (0.142) in the area of science, international articles (0.074) in the area of humanities and social sciences, books (0.174), and in the area of medical sciences, international articles (0.111) had the highest weight compared to other information formats. By dividing the weights for each type of publication, the value of each scientific production compared to other scientific productions in the same field and productions of other fields was calculated. Validation of the results in the studied population resulted in very high credibility for all investigated indicators in all four fields. By using these values and normalized ratios of publication indicators it is possible to achieve precise and adjusted results, making it possible to feasibly use these results in realistic policy making.

• 한국멀티미디어학회논문지
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• 제6권2호
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• pp.247-258
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• 2003

얼굴인식 기술 분야에 있어서 Principal component analysis (PCA)기반 알고리즘은 많은 관련 알고리즘의 기초가 되고 있다. PCA는 매우 통계적인 접근이며 얼굴인식 분야에 응용하기 위해서는 많은 설계 결정요인 (design derision)을 필요로 한다. 본 논문에서는 일반적인 modular PCA알고리즘을 소개하면서 design decision을 얻는다. 얼굴인식 알고리즘 평가에 대한 표준 접근 방법인 September 1996 FERET evaluation protocol을 활용하여 각 모듈에 대한 서로 다른 구현방법을 실험하고 평가한다. 실험조건으로는 (1) 조도의 정규화 과정 을 변화 (2) JPEG과 wavelet compression 알고리즘 사용에 대한 성능효과를 분석 (3) 표현방법에서 eigenvectors의 수를 조절 (4) 분류과정에서 유사도 측정방법을 변경하는 등이다. 본 논문에서는 standard September 1996 FERET의 대용량 gallery image set에 대해 적용해 본 결과에 대해 정리하며, 100개의 무작위로 발생된 image set에 대해서도 알고리즘의 성능 변화를 평가한다.

• 문화기술의 융합
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• 제9권6호
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• pp.883-888
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• 2023

데이터센터는 24시간 365일 IT 서비스를 제공하는 곳이기 때문에, 2030년에는 데이터센터의 전력 소비량은 약 10%로 증가될 것으로 예측되고, 고밀도 IT장비들의 도입이 점차 증가하면서, IT장비가 안정적으로 운영될 수 있도록 냉방 에너지 절감 및 이를 위한 에너지 관리가 갖춰져야 하기에 다양한 연구가 요구되고 있는 상황이다. 본 연구는 데이터센터의 에너지 절약을 위해 다음과 같은 과정을 제안한다. 데이터센터를 CFD 모델링하고, 인공지능기반 열환경 예측 모델을 제안하였으며, 실측 데이터와 예측 모델 그리고 CFD 결과를 비교하여 최종적으로 데이터 센터의 열관리 성능을 평한 결과 전처리 방식은 정규화 방식으로 사용되었고, 정규화에 따른 RCI, RTI 및 PUE의 예측값 또한 유사한 것을 확인할 수 있다. 따라서 본 연구에서 제안하는 알고리즘으로 데이터센터에 적용될 열환경 예측 모델로 적용 및 제공할 수 있을 것으로 판단된다.

• International Journal of Stem Cells
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• 제17권2호
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• pp.194-203
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• 2024

Evaluating cell metabolism is crucial during pluripotent stem cell (PSC) differentiation and somatic cell reprogramming as it affects cell fate. As cultured stem cells are heterogeneous, a comparative analysis of relative metabolism using existing metabolic analysis methods is difficult, resulting in inaccuracies. In this study, we measured human PSC basal metabolic levels using a Seahorse analyzer. We used fibroblasts, human induced PSCs, and human embryonic stem cells to monitor changes in basal metabolic levels according to cell number and determine the number of cells suitable for analysis. We evaluated normalization methods using glucose and selected the most suitable for the metabolic analysis of heterogeneous PSCs during the reprogramming stage. The response of fibroblasts to glucose increased with starvation time, with oxygen consumption rate and extracellular acidification rate responding most effectively to glucose 4 hours after starvation and declining after 5 hours of starvation. Fibroblasts and PSCs achieved appropriate responses to glucose without damaging their metabolism 2~4 and 2~3 hours after starvation, respectively. We developed a novel method for comparing basal metabolic rates of fibroblasts and PSCs, focusing on quantitative analysis of glycolysis and oxidative phosphorylation using glucose without enzyme inhibitors. This protocol enables efficient comparison of energy metabolism among cell types, including undifferentiated PSCs, differentiated cells, and cells undergoing cellular reprogramming, and addresses critical issues, such as differences in basal metabolic levels and sensitivity to normalization, providing valuable insights into cellular energetics.

• 전기학회논문지
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• 제67권1호
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• pp.114-123
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• 2018

This paper concerns a design and learning method of softmax function neural networks based on K-means clustering. The partial discharge data Information is preliminarily processed through simulation using an Epoxy Mica Coupling sensor and an internal Phase Resolved Partial Discharge Analysis algorithm. The obtained information is processed according to the characteristics of the pattern using a Motor Insulation Monitoring System program. At this time, the processed data are total 4 types that void discharge, corona discharge, surface discharge and slot discharge. The partial discharge data with high dimensional input variables are secondarily processed by principal component analysis method and reduced with keeping the characteristics of pattern as low dimensional input variables. And therefore, the pattern classifier processing speed exhibits improved effects. In addition, in the process of extracting the partial discharge data through the MIMS program, the magnitude of amplitude is divided into the maximum value and the average value, and two pattern characteristics are set and compared and analyzed. In the first half of the proposed partial discharge pattern classifier, the input and hidden layers are classified by using the K-means clustering method and the output of the hidden layer is obtained. In the latter part, the cross entropy error function is used for parameter learning between the hidden layer and the output layer. The final output layer is output as a normalized probability value between 0 and 1 using the softmax function. The advantage of using the softmax function is that it allows access and application of multiple class problems and stochastic interpretation. First of all, there is an advantage that one output value affects the remaining output value and its accompanying learning is accelerated. Also, to solve the overfitting problem, L2-normalization is applied. To prove the superiority of the proposed pattern classifier, we compare and analyze the classification rate with conventional radial basis function neural networks.

• ETRI Journal
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• 제37권2호
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• pp.395-405
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• 2015

We address the problem of uncooperative person recognition through continuous monitoring. Multiple modalities, such as face, height, clothes color, and voice, can be used when attempting to recognize a person. In general, not all modalities are available for a given frame; furthermore, only some modalities will be useful as some frames in a video sequence are of a quality that is too low to be able to recognize a person. We propose a method that makes use of stochastic information updates of temporal modalities and environment estimators to improve person recognition performance. The environment estimators provide information on whether a given modality is reliable enough to be used in a particular instance; such indicators mean that we can easily identify and eliminate meaningless data, thus increasing the overall efficiency of the method. Our proposed method was tested using movie clips acquired under an unconstrained environment that included a wide variation of scale and rotation; illumination changes; uncontrolled distances from a camera to users (varying from 0.5 m to 5 m); and natural views of the human body with various types of noise. In this real and challenging scenario, our proposed method resulted in an outstanding performance.

• 한국게임학회 논문지
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• 제17권5호
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• pp.133-142
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• 2017

최근 스크린 클라이밍용 콘텐츠로 클라이밍 학습 프로그램과 스크린 클라이밍 게임이 등장하였으며, 특히 스크린 클라이밍 게임에 대한 연구가 활발히 진행되고 있다. 본 논문에서는 스크린 클라이밍 콘텐츠 구현의 핵심 기술인 자세 인식 성능의 개선을 위하여 등반자의 신체영역을 기반으로 하는 스켈레톤 보정 방법을 제안한다. 스켈레톤 보정 과정은 비정상적인 스켈레톤 정보를 걸러내는 스켈레톤 프레임 안정화와 신체 영역을 관절부위별로 나누어 각 관절부위의 중점을 보정위치로 하는 신체영역 기반 스켈레톤 수정 과정으로 이루어진다. 이렇게 보정한 스켈레톤 정보는 클라이밍 콘텐츠에서 등반자의 자세가 이상적인 자세와 얼마나 유사한지 판단하는 데 사용될 수 있다.