• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권3호
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• pp.1243-1263
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• 2018

The two-stage linear discrimination analysis (TSLDA) is a feature extraction technique to solve the small size sample problem in the field of image recognition. The TSLDA has retained all subspace information of the between-class scatter and within-class scatter. However, the feature information in the four subspaces may not be entirely beneficial for classification, and the regularization procedure for eliminating singular metrics in TSLDA has higher time complexity. In order to address these drawbacks, this paper proposes an improved two-stage linear discriminant analysis (Improved TSLDA). The Improved TSLDA proposes a selection and compression method to extract superior feature information from the four subspaces to constitute optimal projection space, where it defines a single Fisher criterion to measure the importance of single feature vector. Meanwhile, Improved TSLDA also applies an approximation matrix method to eliminate the singular matrices and reduce its time complexity. This paper presents comparative experiments on five face databases and one handwritten digit database to validate the effectiveness of the Improved TSLDA.

• International Journal of Reliability and Applications
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• 제13권1호
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• pp.19-35
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• 2012

This paper presents an optimum design of step-stress partially accelerated life test (PALT) plan which allows the test condition to be changed from use to accelerated condition on the occurrence of fixed number of failures. Various life distribution models such as exponential, Weibull, log-logistic, Burr type-Xii, etc have been used in the literature to analyze the PALT data. The need of different life distribution models is necessitated as in the presence of a limited source of data as typically occurs with modern devices having high reliability, the use of correct life distribution model helps in preventing the choice of unnecessary and expensive planned replacements. Truncated distributions arise when sample selection is not possible in some sub-region of sample space. In this paper it is assumed that the lifetimes of the items follow Truncated Logistic distribution truncated at point zero since time to failure of an item cannot be negative. Optimum step-stress PALT plan that finds the optimal proportion of units failed at normal use condition is determined by using the D-optimality criterion. The method developed has been explained using a numerical example. Sensitivity analysis and comparative study have also been carried out.

• Smart Structures and Systems
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• 제12권3_4호
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• pp.235-250
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• 2013

Optimal sensor placement (OSP) technique plays a key role in the structural health monitoring (SHM) of large-scale structures. According to the mathematical background and implicit assumptions made in the triaxial effective independence (EfI) method, this paper presents a novel multi-dimensional OSP method for the Canton Tower focusing on application demands. In contrast to existing methods, the presented method renders the corresponding target mode shape partitions as linearly independent as possible and, at the same time, maintains the stability of the modal matrix in the iteration process. The modal assurance criterion (MAC), determinant of the Fisher Information Matrix (FIM) and condition number of the FIM have been taken as the optimal criteria, respectively, to demonstrate the feasibility and effectiveness of the proposed method. Numerical investigations suggest that the proposed method outperforms the original EfI method in all instances as expected, which is looked forward to be even more pronounced should it be used for other multi-dimensional optimization problems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권11호
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• pp.5496-5521
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• 2018

Object detection and tracking is the basic capability of mobile robots to achieve natural human-robot interaction. In this paper, an object tracking system of mobile robot is designed and validated using improved multiple instance learning algorithm. The improved multiple instance learning algorithm which prevents model drift significantly. Secondly, in order to improve the capability of classifiers, an active sample selection strategy is proposed by optimizing a bag Fisher information function instead of the bag likelihood function, which dynamically chooses most discriminative samples for classifier training. Furthermore, we integrate the co-training criterion into algorithm to update the appearance model accurately and avoid error accumulation. Finally, we evaluate our system on challenging sequences and an indoor environment in a laboratory. And the experiment results demonstrate that the proposed methods can stably and robustly track moving object.

• ETRI Journal
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• 제44권3호
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• pp.462-475
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• 2022

Although researchers have proposed numerous techniques for speech emotion recognition, its performance remains unsatisfactory in many application scenarios. In this study, we propose a speech emotion recognition model based on a genetic algorithm (GA)-decision tree (DT) fusion of deep and acoustic features. To more comprehensively express speech emotional information, first, frame-level deep and acoustic features are extracted from a speech signal. Next, five kinds of statistic variables of these features are calculated to obtain utterance-level features. The Fisher feature selection criterion is employed to select high-performance features, removing redundant information. In the feature fusion stage, the GA is is used to adaptively search for the best feature fusion weight. Finally, using the fused feature, the proposed speech emotion recognition model based on a DT support vector machine model is realized. Experimental results on the Berlin speech emotion database and the Chinese emotion speech database indicate that the proposed model outperforms an average weight fusion method.

• Journal of Trauma and Injury
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• 제24권2호
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• pp.89-94
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• 2011

Purpose: A few studies have assessed the factors affecting the prognoses for major trauma patients and those improving the circumstances when dealing with the trauma system. In that light, we analyzed factors, such as pre-hospital factors, the time to admission, the length of stay in the emergency department (ED) and emergency operation, influencing the outcomes for trauma patients. Methods: The patients who visited our emergency department from April 1, 2009, to February 29, 2011, due to major trauma were enrolled in the study. The inclusion criterion was a revised trauma score (RTS) < 7 or injury severity score (ISS) ${\geq}$ 16. We used reviews of medical records, to analyze each step of emergency medical care with respect to patients' sex, age, visit time and visit date. Continuous variables were described as a median with an interquartile range, and we compared the variables between the survival and the mortality groups by using the Mann-Whitney U test. Fisher's exact test was used for nominal variables. Using the variables that showed statistical significance in univariate comparisons, we performed a logistic regression analysis, and we tested the model's adequacy by the using the Hosmer-Lemeshow method. Results: A total of 261 patients with major trauma satisfied either the RTS score criterion or the ISS score criterion. Excluding 12 patients with missing data, 249 patients were included in this study. The overall mortality rate was 16.9%. Time to ED arrival, time to admission, time of ED stay, RTS, ISS, and visit date being a holiday showed statistically significant differences between the survival and the mortality groups in the univariate analysis. RTS, ISS, length of ED stay, and visit date being a holiday showed statistical significance in the multivariate analysis. Conclusion: The mortality rate did not show a significant relationship with the time to ED arrival, use of 119, on time to admission. Rather, it elicited a quite significant correlation with the trauma scoring system (RTS and ISS), the time of ED stay, and the visit date being a holiday.

• 생물정신의학
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• 제11권2호
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• pp.165-172
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• 2004

Objective:Although polymorphism of dopamine transporter gene(DAT1) has been considered to be implicated in the pathogenesis of social phobia, previous investigations have been inconsistent and controversial. The authors investigated the relationship between DAT1 polymorphism and social phobia in Koreans. Methods:DAT1 and alleles of fifty subjects who met DSM-IV criterion of social phobia, and those of age- & sex- matched fifty normal controls in Korea were compared. Additionally, patients were grouped into generalized(33) and nongeneralized(17) types and DAT1 polymorphism was compared with that of age- & sex- matched controls. DAT1 with variable number of tandem repeats(VNTR) were determined by using polymerase chain reaction. To compare the distribution of the DAT1 polymorphism between different groups, Fisher's exact test was used. Results:There were no significant differences in either genotypic(p=0.451) or allelic(p=0.452) distributions between the social phobia patients and the controls. There also were no differences in genotypic distribution between subtypes of social phobia patients and the controls. Conclusion:We couldn't find any association between DAT1 polymorphism and social phobia. Further studies including larger number of samples and diverse clinical variables should be conducted to elucidate the present findings.

• 전자공학회논문지CI
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• 제42권4호
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• pp.33-42
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• 2005

본 논문에서는 소속 함수와 신경망을 이용한 유전자 발현 정보의 분류 기법을 제안한다. 유전자 발현은 유전자가 mRNA와 생체의 기능을 일으키게 하는 단백질을 만들어내는 과정이다. 유전자 발현에 대한 정보는 유전자의 기능을 밝히고 유전자간의 상관 관계를 알아내는데 중요한 역할을 한다. 이러한 유전자 발현 연구를 위한 정보를 대량으로 신속하게 얻을 수 있는 도구가 DNA 칩이다. DNA 칩으로 얻은 수백$\~$수천개의 데이터는 그 데이터만으로는 의미를 갖지 못한다. 따라서 유전자 발현정도에 따라 수치적으로 획득된 데이터에서 의미적인 특성을 찾아내기 위해서는 클러스터링 방법이 필요하다. 본 논문에서는 수많은 유전자 데이터 중에서 주요 정보를 포함한 것으로 판단되는 유전자 데이터를 피셔 기준에 의하여 선택한다. 이때 선택된 데이터들이 클러스터링에 효과적인 데이터라고 보장할 수 없으므로, 클러스터링 성능을 저해하는 유전자 데이터의 영향력을 감소시키기 위해서 소속 함수를 이용하여 특징값을 계산하고, 계산된 특징값으로 얻은 특징 벡터들을 적용하여 역전파 신경망 학습을 수행한다. 본 논문에서 제안한 유전자 발현 정보의 분류 결과로 얻은 클러스터링의 성능은 기존의 연구 결과와 비교했을 때 다양한 유전자 데이터에 대하여 향상된 인식율을 보이는 것을 확인할 수 있었다.

• 대한전자공학회논문지SP
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• 제47권5호
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• pp.183-191
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• 2010

생체인식은 개인의 유일하면서 변화하지 않는 생체의 특징을 이용하여 개인의 본인 여부를 판별하는 방법으로써 널리 사용되어 왔다. 생체정보의 고유 불변한 특징을 저장하는 것은 개인정보의 노출에 따른 보안상의 문제점을 갖고 있으며 이를 해결하기 위해 제안된 방법이 가변생체인식 (cancelable biometrics)이다. 가변생체인식은 생체정보의 도난이나 도용으로부터 강인하며 재생성 가능한 생체템플릿을 제공하는 생체 인식방법이다. 본 논문에서는 변환 생체인식의 한 가지 방법으로써 얼굴 생체정보의 새로운 이진화 방법을 제안한다. 얼굴 생체정보의 이진화를 위한 특징추출은 얼굴정보의 부분적 변화에 강인한 영역기반 주성분 분석(Subpattern-based PCA)을 이용하였으며 이로부터 얻어진 특징을 보조정보에 기반한 방법으로 이진화 하였다. 획득된 이진비트열은 영역기반 주성분 분석의 사용으로 여러 얼굴 영역의 고려와 함께, 선택된 주성분 개수만큼의 계수들에 대한 이진화 값들을 포함하고 있다. 이러한 서로 다른 얼굴영역의 여러 주성분들에서 추출된 이진비트열중 구분력이 좋은 비트 값들을 선택하였으며, 선택된 비트 값들은 이진화를 위한 보조 정보가 노출된 경우에서도 원 얼굴특징벡터보다 향상된 인식성능을 보여준다.

• Journal of Trauma and Injury
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• 제25권4호
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• pp.247-253
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• 2012

Purpose: Hemorrhage is a main cause of death in trauma patients. The goal of this study is to describe the characteristics of trauma patients with massive bleeding and to evaluate the prognostic factors concerning their survival. Methods: This study was performed retrospectively and included trauma patients with massive bleeding who had been treated from March 2007 to August 2012. The inclusion criterion was patients who received more than 10 U of packed red blood cells within the first 24 hours after visiting the emergency department. Based on their medical records, we collected data in terms of demographic findings, mechanisms of injury, initial clinical and laboratory findings, methods for hemostasis (emergency surgery and/or angioembolization), transfusion, injury severity score (ISS), revised trauma score (RTS) and trauma and injury severity score (TRISS). We used the Mann-Whitney U test and Fisher's exact test to compare the variables between the patients that survived and those that did not. We performed a logistic regression analysis with the significant variables from the univariate test. Results: Thirty-two(32) patients were enrolled. The main mechanisms of injury were falls and motor vehicle accidents. The mean transfusion amount of packed red blood cells (PRBC) was 17.4 U. The mean elapsed time for the first hemostasis (surgery or embolization) was 3.5 hours. The initial technical success rates were 83.3%(15/18) in angioembolization and 66.7%(8/12) in surgery. The overall mortality rate was 34.4%(11/32). The causes of death were bleeding, brain swelling and multiple organ failure. The ISS(25.5 vs 46.3, p=0.000), TRISS(73.6 vs 45.1, p=0.034) and base excess(<-12 mmol/L, p=0.020) were significantly different between the patients who survived and those who did not. Conclusion: The ISS was a prognostic factor for trauma patients with massive bleeding.