• Mycobiology
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• 제38권3호
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• pp.215-218
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• 2010

Azoles are currently the most widely used class of antifungal drugs clinically, and are effective for treating fungal infections. Target site of azoles is ergosterol biosynthesis in fungal cell membrane, which is absent in the mammalian host. However, the development of resistance to azole treatments in the fungal pathogen has become a significant challenge. Here, we report the identification and functional characterization of a UPC2 homolog in the human pathogen Cryptococcus neoformans. UPC2 plays roles in ergosterol biosynthesis, which is also affected by the availability of iron in Saccharomyces cerevisiae and Candida albicans. C. neoformans mutants lacking UPC2 were constructed, and a number of phenotypic characteristics, including antifungal susceptibility and iron utilization, were analyzed. No differences were found between the mutant phenotypes and wild type, suggesting that the role of C. neoformans UPC2 homolog may be different from those in S. cerevisiae and C. albicans, and that the gene may have a yet unknown function.

• 전기학회논문지
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• 제59권5호
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• pp.966-971
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• 2010

An adaptive state observer is presented for a class of LTI systems that have a sinusoidal disturbance in the measurement output. Adaptation rules are developed for identifying the unknown sinusoidal disturbance signal from the system output. For the application of the identification result to the state estimation problem, the sinusoidal signal with arbitrary initial phase has been considered in this paper. In order to test the performance of proposed algorithm, comparative computer simulations have been carried out with an existing robust observer. The simulation results show the effectiveness of the proposed method.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -3
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• pp.1674-1677
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• 2002

In this paper, the new method to extract the features of iris signals is proposed; Multiresolution ICA (M-ICA) provides good properties to represent signals with time-frequency. The conventional methods were to use the technique of filter bank analysis, while ICA is unsupervised learning algorithm using high-order statistics. M-ICA could make use of strengths of learn- ing method and multiresolution. Also, we performed comparative studies of different feature extraction techniques applied to personal identification using iris pat- tern. To measure goodness of methods, we use Fisher’s discriminant ratio to quantify the class-separability of features generated by various techniques.

• 한국음향학회지
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• 제21권4호
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• pp.415-420
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• 2002

라우드스피커의 선형 매개변수를 규명하는 두가지 방법을 기술하였다. 박스 법과 질량 추가 법을 이용하여 라우드스피커의 선형 매개변수를 규명하는 방법을 개발하였다. 상용 소프트웨어를 사용하여 구한 결과와 비교 검토하여 각 방법의 장단점을 비교하였다. 상용 소프트웨어인 라우드 소프트웨어에서 사용하는 박스 법을 사용하여 규명한 매개변수 결과는 본 논문에서 개발한 두가지 방법과는 큰 차이를 보이고 있으나, 개발한 두가지 방법의 매개 변수의 오차는 최대 4%이내였다. 박스 법을 이용하여 매개변수를 규명할 때에는 박스에 넣는 다공질 재료의 양에 따라 매개변수가 다르게 규명되는 현상도 기술하였다.

• Wind and Structures
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• 제15권4호
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• pp.285-299
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• 2012

This paper describes the development and calibration of a structural monitoring system installed in a 80 meters high steel wind tower supporting a 2.1 MW turbine Wind Class III IEC2a erected in the central part of Portugal. The several signals are measured at four different levels and include accelerations, strains on the tower wall and inside the connection bolts, inclinations and temperature. In order to correlate measurements with the wind velocity and direction and with the turbine operational parameters the corresponding signals are obtained directly from the turbine own monitoring system and are incorporated in the developed system. Results from the system calibration, the structural identification and the initial period of data acquisition are presented in this paper.

• 한국안전학회지
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• 제11권2호
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• pp.143-149
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• 1996

본 논문에서는 BPEJTC에 근거한 광-디지탈 지문인식 시스템을 구성하여 안전검증에 응용 가능함을 보였다. BPEJTC 시스템은 기존의 JTC에 비해 높은 상관 값을 가지므로 유사 지문 간의 상관이 발생하지 않으며, 입력에 여러개의 지문이 존재하는 경우에도 잘 적응할 수 있는 장점을 지닌다. 컴퓨터 시뮬레이션 및 실험을 통해 본 시스템이 변형된 동일인의 지문 혹은 여러종류의 다른지문으로부터 동일 지문을 인식할 수 있음을 보였다.

• Journal of Information Processing Systems
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• 제20권3호
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• pp.307-316
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• 2024

In the realm of large-scale identification deployments, the EPCglobal Class-1 Generation-2 (Gen2) standard serves as a cornerstone, facilitating rapid processing of numerous passive RFID tags. The Q-Algorithm has garnered considerable attention for its potential to markedly enhance the efficiency of Gen2-based RFID systems with minimal adjustments. This paper introduces a groundbreaking iteration of the Q-Algorithm, termed Time-Efficient Q-Algorithm (SwiftQ), specifically designed to push the boundaries of time efficiency within Gen2-based RFID systems. Through exhaustive simulations, our study substantiates that SwiftQ outperforms existing algorithms by a significant margin, demonstrating exceptional expediency that positions it as a formidable contender in the landscape of large-scale identification environments. By prioritizing time efficiency, SwiftQ offers a promising solution to meet the escalating demands of contemporary Internet of Things applications, underscoring its potential to catalyze advancements in RFID technology for diverse industrial and logistical contexts.

• Journal of Information Processing Systems
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• 제9권2호
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• pp.333-348
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• 2013

Mobile authentication/identification has grown into a priority issue nowadays because of its existing outdated mechanisms, such as PINs or passwords. In this paper, we introduce gait recognition by using a mobile accelerometer as not only effective but also as an implicit identification model. Unlike previous works, the gait recognition only performs well with a particular mobile specification (e.g., a fixed sampling rate). Our work focuses on constructing a unique adaptive mechanism that could be independently deployed with the specification of mobile devices. To do this, the impact of the sampling rate on the preprocessing steps, such as noise elimination, data segmentation, and feature extraction, is examined in depth. Moreover, the degrees of agreement between the gait features that were extracted from two different mobiles, including both the Average Error Rate (AER) and Intra-class Correlation Coefficients (ICC), are assessed to evaluate the possibility of constructing a device-independent mechanism. We achieved the classification accuracy approximately $91.33{\pm}0.67%$ for both devices, which showed that it is feasible and reliable to construct adaptive cross-device gait recognition on a mobile phone.

• 한국자동차공학회논문집
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• 제8권6호
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• pp.142-155
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• 2000

A MIMO model reference control scheme incorporating the variable structure theory for a vehicle four wheel steering system(4WS) is proposed and evaluated for a class of continuous-time nonlinear dynamics with known or unknown uncertainties. The scheme employs an neural network to identify the plant systems, where the neural network estimates the nonlinear dynamics of the plant. By the Lyapunov direct method, the algorithm is proven to be globally stable, with tracking errors converging to the neighborhood of zero. The merits of this scheme is that the global system stability is guaranteed and it is not necessary to know the exact structure of the system. With the resulting identification model which contains the neural networks, it does not need higher degrees of freedom vehicle model than 3 degree of freedom model. Th proposed scheme is applied to the active four wheel system and shows the validity is used to investigate vehicle handing performances. In simulation of the J-turn maneuver, the reduction of yaw rate overshoot of a typical mid-size car improved by 30% compared to a two wheel steering system(2WS) case, resulting that the proposed scheme gives faster yaw rate response and smaller side angle than the 2WS case.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 추계학술대회 학술발표 논문집 제14권 제2호
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• pp.211-216
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• 2004

In this thesis, we present the Takagi-Sugeno-Kang (TSK) fuzzy model based adaptive controller and adaptive identification for a general class of uncertain nonlinear dynamic systems. We use an estimated model for the unknown plant model and use this model for designing the controller. The hybrid adaptive control combined direct and indirect adaptive control based on TSK fuzzy model is constructed. The direct adaptive law can be showed by ignoring the identification errors and fails to achieve parameter convergence. Thus, we propose an TSK fuzzy model based hybrid adaptive (HA) law combined of the tracking error and the model ins error to adjust the parameters. Using a Lyapunov synthesis approach, the proposed hybrid adaptive control is proved. The hybrid adaptive law (HA) is better than the direct adaptive (DA) method without identifying the model ins error in terms of faster and improved tracking and parameter convergence. In order to show the applicability of the proposed method, it is applied to the inverted pendulum system and the performance is verified by some simulation results.