• Biotechnology and Bioprocess Engineering:BBE
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• 제10권6호
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• pp.535-539
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• 2005

The thermoacidophilic archaeon Thermoplasma acidophilum has long been known to utilize D-glucose via the non-phosphorylated Entner-Doudoroff (nED) pathway. We now report the identification of a gene encoding 2-keto-3-deoxy-D-gluconate (KDG) kinase. The discovery of this gene implies the presence of a glycolysis pathway, other than the nED pathway. It was found that Ta0122 in the T. acidophilum genome corresponded to KDG kinase. This enzyme shares no similarity with known KDG kinases, and belongs to a novel class of sugar kinases. Of the five sugars tested only KDG was utilized as a substrate.

• Structural Engineering and Mechanics
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• 제6권8호
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• pp.857-870
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• 1998

This paper deals with a special class of inverse problems in discrete structural plasticity involving the identification of elastic limits and hardening moduli on the basis of information on displacements. The governing equations lead naturally to a special and challenging optimization problem known as a Mathematical Program with Equilibrium Constraints (MPEC), a key feature of which is the orthogonality of two sign-constrained vectors or so-called "complementarity" condition. We investigate numerically the application of two simple algorithms, both based on the use of the general purpose nonlinear programming code CONOPT accessed via the GAMS modeling language, for solving the suitably reformulated problem. Application is illustrated by means of two numerical examples.

• International Journal of Advanced Culture Technology
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• 제11권2호
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• pp.30-35
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• 2023

This study is an example of a class of bibliotherapy through Lee Chung-joon's novel Snowy Road. Bibliotherapy proceeds through the process of identification, catharsis, output, insight, and application through reading. Through research, students objectively examine the situation of the character in the novel and compare it with their own situation. Students evaluate the situation of the character in the novel, experience the various life positions of the character in the novel by answering "What would you do if I were a character in the novel," and express their willingness to live differently from their lives. At the same time, I look into my relationship with my parents and seriously think about whether there is a problem and how to solve it if there is one. Through this process, students specifically suggest ways to think about and solve their emotions and problems. In the end, students' hurt feelings can be partially or sufficiently healed through reading. Through this study, it is expected that the method of bibliotherapy will be more concrete and develop in a positive direction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권6호
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• pp.2098-2114
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• 2021

Light intensity variation is one of the key factors which affect the accuracy of vehicle face re-identification, so in order to improve the robustness of vehicle face features to light intensity variation, a Nonnegative Matrix Factorization model with the constraint of image acquisition time difference is proposed. First, the original features vectors of all pairs of positive samples which are used for training are placed in two original feature matrices respectively, where the same columns of the two matrices represent the same vehicle; Then, the new features obtained after decomposition are divided into stable and variable features proportionally, where the constraints of intra-class similarity and inter-class difference are imposed on the stable feature, and the constraint of image acquisition time difference is imposed on the variable feature; At last, vehicle face matching is achieved through calculating the cosine distance of stable features. Experimental results show that the average False Reject Rate and the average False Accept Rate of the proposed algorithm can be reduced to 0.14 and 0.11 respectively on five different datasets, and even sometimes under the large difference of light intensities, the vehicle face image can be still recognized accurately, which verifies that the extracted features have good robustness to light variation.

• 과학교육연구지
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• 제36권2호
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• pp.251-262
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• 2012

본 연구에서는 중학교 학생들의 변인 판별 및 변인 통제 능력을 신장시킬 수 있는 15가지의 학습 프로그램을 개발하고, 이를 적용하여 수업효과를 분석하였다. 변인 판별 및 통제 학습 효과를 높이기 위하여 자신의 사고 과정을 모니터하고 인지 활동 결과에 대해 객관적으로 평가할 수 있도록 구성하였다. 이 프로그램의 수업 효과를 분석한 결과, 프로그램을 투입한 실험집단이 비교집단에 비해 변인 판별 점수가 높았으며, 변인통제 논리 형성정도도 증가하였는데, 특히 변인통제 논리 형성정도가 미형성 단계인 학생들에게 효과가 크게 나타났다. 이는 우리가 개발한 학습 프로그램을 통해 학생들의 변인 판별 및 통제 능력을 향상시키는 것이 가능함을 보여준다. 또한, 변인 통제 능력 점수와 메타 인지 수준 점수 간에 정(+)적인 상관관계를 보였다. 이는 메타인지 전략이 변인 통제 능력을 유의미하게 향상시키는 효과가 있다고 할 수 있다.

• 한국통신학회논문지
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• 제30권1B호
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• pp.17-26
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• 2005

RFID(Radio Frequency IDentification) 기술은 RF 신호를 사용하여 물품에 부착된 전자태그를 비접촉식으로 식별하는 자동인식기술이다. RFID 시스템 구축에 있어 식별영역 내에 다수의 태그가 존재할 경우, 다중태그 식별(multi-tag identification)을 위한 충돌방지(anti-collision) 알고리즘이 필수적으로 요구된다. 태그 충돌방지와 관련된 기존 연구들은 각각 고유한 형태의 코드체계를 기반으로 하고 있으며 태그 식별성능에 대한 비교연구도 부족한 상태이다. 본 논문에서는 저비용(low-cost) RFID 시스템 구축을 목표로 표준화가 진행되고 있는 96-비트 EPC(Electronic Product Code) 코드를 기반으로 기존 대표적인 충돌방지 알고리즘인 트리 기반 메모리래스(tree based memoryless) 충돌방지 알고리즘들과 슬롯 알로하 기반으로 (slot aloha based) 충돌방지 알고리즘들의 성능평가를 수행한다. 성능평가 결과 초당 평균 태그 식별개수에서 충돌 추적 트리(collision tracking tree) 알고리즘이 다른 알고리즘들보다 최소 2배에서 최대 50배 이상의 우수한 성능을 보여준다.

• Smart Structures and Systems
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• 제17권3호
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• pp.445-470
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• 2016

In this study, the Bayesian probabilistic framework is investigated for modal identification and modal identifiability based on the field measurements provided in the structural health monitoring benchmark problem of an instrumented cable-stayed bridge named Ting Kau Bridge (TKB). The comprehensive structural health monitoring system on the cable-stayed TKB has been operated for more than ten years and it is recognized as one of the best test-beds with readily available field measurements. The benchmark problem of the cable-stayed bridge is established to stimulate investigations on modal identifiability and the present paper addresses this benchmark problem from the Bayesian prospective. In contrast to deterministic approaches, an appealing feature of the Bayesian approach is that not only the optimal values of the modal parameters can be obtained but also the associated estimation uncertainty can be quantified in the form of probability distribution. The uncertainty quantification provides necessary information to evaluate the reliability of parametric identification results as well as modal identifiability. Herein, the Bayesian spectral density approach is conducted for output-only modal identification and the Bayesian model class selection approach is used to evaluate the significance of different modes in modal identification. Detailed analysis on the modal identification and modal identifiability based on the measurements of the bridge will be presented. Moreover, the advantages and potentials of Bayesian probabilistic framework on structural health monitoring will be discussed.

• 대한의용생체공학회:의공학회지
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• 제43권6호
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• pp.441-447
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• 2022

In this paper, we propose a pill identification model using engraved text feature and image feature such as shape and color, and compare it with an identification model that does not use engraved text feature to verify the possibility of improving identification performance by improving recognition rate of the engraved text. The data consisted of 100 classes and used 10 images per class. The engraved text feature was acquired through Keras OCR based on deep learning and 1D CNN, and the image feature was acquired through 2D CNN. According to the identification results, the accuracy of the text recognition model was 90%. The accuracy of the comparative model and the proposed model was 91.9% and 97.6%. The accuracy, precision, recall, and F1-score of the proposed model were better than those of the comparative model in terms of statistical significance. As a result, we confirmed that the expansion of the range of feature improved the performance of the identification model.

• 대한음성학회지:말소리
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• 제54호
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• pp.73-83
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• 2005

The goal of our research is to build a text-independent speaker identification system that can be used in any condition without any additional adaptation process. The performance of speaker recognition systems can be severely degraded in some unknown mismatched microphone and noise conditions. In this paper, we show that PCA(principal component analysis) can improve the performance in the situation. We also propose an augmented PCA process, which augments class discriminative information to the original feature vectors before PCA transformation and selects the best direction for each pair of highly confusable speakers. The proposed method reduced the relative recognition error by 21%.

• 대한수학회지
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• 제47권5호
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• pp.1077-1095
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• 2010

The paper considers the identifiability (i.e., the unique identification) of a composite string in the class of piecewise constant parameters. The 1-D string vibration is measured at finitely many observation points. The observations are processed to obtain the first eigenvalue and a constant multiple of the first eigenfunction at the observation points. It is shown that the identification by the Marching Algorithm is continuous with respect to the mean convergence in the admissible set. The result is based on the continuous dependence of eigenvalues, eigenfunctions, and the solutions on the parameters. A numerical algorithm for the identification in the presence of noise is proposed and implemented.