• 전기의세계
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• 제20권4호
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• pp.23-30
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• 1971

The photovoltaic behaviors ahve been observed with a sandwich-type cell, consisting of a junction between .betha.-carotene and stannic oxide conducting layer to provide a junction electrode. In the stannic oxide and .betha.-carotene junction it was found that its electromotive forse decreased to a value smaller than the original one. This is due to a space charge formation. Photovoltage reached approximately 40mV with an irradiation energy of 250Kcal/M$^{2}$hr. It appeared that a magnitude of the photovoltaic response was proportional to the logarithm of irradiance. The time constant of the photovoltaic effect was shown to be approximately 0.7 sec. The wavelength dependence of the photovoltaic behavior was very anomalous. It is assumed that such an anomalous photoresponse depends on a internal capacitance due to some bubble during process to make a cell.

• 한국위성정보통신학회논문지
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• 제12권3호
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• pp.35-40
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• 2017

위성의 상태를 파악하기 위해 기존에는 OOL(Out-Of-Limit) 방식을 많이 사용하여 왔다. OOL은 특정 텔레메트리의 상위, 하위 문턱 값을 지정하여 해당 값을 벗어날 경우 문제가 발생한 것으로 인식 하는 방식이다. 이 방법은 파라미터의 특성을 파악하여 각각의 문턱 값을 정확히 설정해야 하는 전문 지식과 노력이 필요하고 텔레메트리 값이 문턱값 내에서 비정상적으로 변할 경우는 검출할 수 없다는 문제점이 있다. 이러한 문제를 극복하기 위해 본 논문에서는 위성이 정상 상태일 때 텔레메트리의 통계적 특징 중 러프집합을 이용하여 중요한 것을 선택, 적용하여 퍼지 모델을 구축하고 이상 상태를 구분하는 시스템을 제안한다. 정상 상태의 데이터만 이용하여 모델을 구축하기 때문에 출력값을 비교 하여 사전에 정의되지 않은 비정상 상태의 구분이 가능 하며 다양한 통계 값을 이용하기 때문에 전문 지식 필요 없이 문턱값 내에서 비정상적으로 변하는 텔레메트리를 검출할 수 있다. 제안한 시스템의 동작 확인을 위해 실제 저궤도 관측위성의 배터리 온도 텔레메트리를 적용하여 시험을 수행 하였고 비정규적 운영 상태에 대한 검출이 성공적으로 이루어 졌다.

• Bulletin of the Korean Chemical Society
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• 제5권2호
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• pp.82-86
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• 1984

The anomalous behaviors of supercooled water are explained by using a two-solid-like structure model in which an equilibrium is assumed between open structures and closed structures. Besides these structures, small fraction of monomer exists in liquid water. The anomalies of liquid water are classified into two groups: structural and energetic. The structural anomalies appear in enlarged fashions in a supercooled state where the free volume is small.

• Journal of Information Processing Systems
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• 제20권2호
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• pp.159-172
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• 2024

The number of healthcare products available for pets has increased in recent times, which has prompted active research into wearable devices for pets. However, the data collected through such devices are limited by outliers and missing values owing to the anomalous and irregular characteristics of pets. Hence, we propose pet behavior recognition based on a hybrid one-dimensional convolutional neural network (CNN) and long short- term memory (LSTM) model using pet wearable devices. An Arduino-based pet wearable device was first fabricated to collect data for behavior recognition, where gyroscope and accelerometer values were collected using the device. Then, data augmentation was performed after replacing any missing values and outliers via preprocessing. At this time, the behaviors were classified into five types. To prevent bias from specific actions in the data augmentation, the number of datasets was compared and balanced, and CNN-LSTM-based deep learning was performed. The five subdivided behaviors and overall performance were then evaluated, and the overall accuracy of behavior recognition was found to be about 88.76%.

• Transactions on Electrical and Electronic Materials
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• 제7권3호
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• pp.149-153
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• 2006

An attempting to produce a p-type diluted magnetic semiconductor (DMS) using $Ti_{1-x}Co_xO_{2-\delta}-based$ thin films was made by suitable control of the deposition parameters including deposition temperature, deposition pressure, and doping level using a pulsed laser deposition method. T$Ti_{0.97}Co_{0.03}O_{2-\delta}-based$ (TCO) films deposited at $500^{\circ}C$ at a pressure of $5\times10^{-6}$ Torr showed an anomalous Hall effect with p-type characteristics. On the other hand, films deposited at $700^{\circ}C$ at $5\times10^{-6}$ Torr showed n-type behaviors by a decreased solubility of cobalt. The charge carrier concentration in the p-type TCO films was approximately $7.9\times10^{22}/cm^3$ at 300 K and the anomalous Hall effect in the p-type TCO films was controlled by a side-jump scattering mechanism. The magnetoresistance (MR), measured at 5 K in p-type TCO films showed a positive behavior in an applied magnetic field and the MR ratio was approximately 3.5 %. The successful preparation of p-type DMS using the TCO films has the potential for use in magnetic tunneling junction devices.

• 대한전자공학회논문지SD
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• 제41권3호
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• pp.1-8
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• 2004

본 연구에서는 소오스와 드레인 근처에 포켓형상으로 이온이 주입되어 halo구조를 갖고 있는 MOSFET 소자의 1/f 잡음 특성에 대하여 고찰하였다. 채널 방향으로 전도도가 균일하지 않은 MOSFET 소자가 선형영역에서 동작할 때, 영역구분 근사기법(regional approach)을 근간으로 논의된 기존의 1/f 잡음모델을 영역별로 서로 다른 전기적 성질이 정의될 수 있는 halo MOSFET 소자에 적용하여 그 타당성을 조사하였다. 잡음모델의 검증을 위하여 기존의 모델에서와 같이 영역구분 근사를 사용하여 보다 넓은 동작범위에서 적용될 수 있도록 기존의 모델식을 개선하였다. 개선된 잡음식은 선형영역에서 기존에 보고된 잡음식에 수렴한다. 실험적으로 측정된 1/f 잡음 특성과의 비교에서 영역구분 근사기법으로 정리된 잡음식은 게이트 전압이 비교적 큰 경우에 한해서 적용될 수 있음을 보였다.

• 한국재료학회지
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• 제13권10호
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• pp.673-676
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• 2003

We have investigated $Al_{x}$ $Ga_{l-x}$ N/GaN epilayers (x = 0.08, 0.15) grown by metal organic vapor phase epitaxy on sapphire with photoluminescence(PL), and persistent photoconductivity(PPC) experiments. An anomalous S-shaped shift behavior of temperature dependencies of PL peak energy is observed for the x = 0.15 sample. In PPC measurement, showed that the dark current recovery time of $Al_{x}$$Ga_{l-x}$ N/GaN epilayers mainly depends on the Al content. These behaviors are usually attributed to the presence of carrier localization states. All these phenomena are explained based on the alloy compositional fluctuations in the $Al_{x}$ /$Ga_{l-x}$ N/ epilayers. The photocurrent quenching observed in PPC measurements for $Al_{x}$ $Ga_{l-x}$ N/ epilayers less than 0.2 $\mu\textrm{m}$ thickness indicates that the presence of metastable state in the bandgap of GaN layer, and that the excess holes in the valence band recombine with free electrons.

• Journal of Information Processing Systems
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• 제16권3호
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• pp.612-628
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• 2020

This paper presents a new approach for detecting abnormal behaviors in complex surveillance scenes where anomalies are subtle and difficult to distinguish due to the intricate correlations among multiple objects' behaviors. Specifically, a cascaded probabilistic topic model was put forward for learning the spatial context of local behavior and the temporal context of global behavior in two different stages. In the first stage of topic modeling, unlike the existing approaches using either optical flows or complete trajectories, spatio-temporal correlations between the trajectory fragments in video clips were modeled by the latent Dirichlet allocation (LDA) topic model based on Markov random fields to obtain the spatial context of local behavior in each video clip. The local behavior topic categories were then obtained by exploiting the spectral clustering algorithm. Based on the construction of a dictionary through the process of local behavior topic clustering, the second phase of the LDA topic model learns the correlations of global behaviors and temporal context. In particular, an abnormal behavior recognition method was developed based on the learned spatio-temporal context of behaviors. The specific identification method adopts a top-down strategy and consists of two stages: anomaly recognition of video clip and anomalous behavior recognition within each video clip. Evaluation was performed using the validity of spatio-temporal context learning for local behavior topics and abnormal behavior recognition. Furthermore, the performance of the proposed approach in abnormal behavior recognition improved effectively and significantly in complex surveillance scenes.

• 사물인터넷융복합논문지
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• 제5권2호
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• pp.95-101
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• 2019

4차 산업혁명시대와 사물인터넷의 시대로 접어들면서 다양한 서비스가 빠르게 성장하고 있으며 관련된 다양한 연구가 활발히 진행중에 있다. 그중에서도 사물인터넷에서 사용이 되고 있는 다양한 디바이스에 대한 비정상행위에 대한 연구도 진행이 되고 있다. 초연결의 사회에서 하나의 잘못된 디바이스로 인한 피해가 발생하면 다양하게 연결되어 있는 시스템에 심각한 영향을 줄 수 밖에 없다. 본 논문에서는 이러한 사물인터넷 환경에서 디바이스에 대한 안전성을 높일 수 있는 방법과 안전하게 디바이스와 서비스를 이용하 수 있는 방법에 대하여 안티디버깅 기법, 이상 프로세스 탐지 기법, 백도어 탐지 기법 등 여러 가지 비정상적인 행위로 인한 위협요소에 대응하기 위한 기법을 제안한다.

• 정보보호학회지
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• 제5권2호
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• pp.32-48
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• 1995

Our paper describes an Intrusion Detection Parallel System(IDPS) which detects an anomaly activity corresponding to the actions that interaction between near detection events. IDES uses parallel inductive approaches regarding the problem of real-time anomaly behavior detection on rule-based system. This approach uses sequential rule that describes user's behavior and characteristics dependent on time. and that audits user's activities by using rule base as data base to store user's behavior pattern. When user's activity deviates significantly from expected behavior described in rule base. anomaly behaviors are recorded. Observed behavior is flagged as a potential intrusion if it deviates significantly from the expected behavior or if it triggers a rule in the parallel inductive system.