• Journal of Information Processing Systems
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• 제19권5호
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• pp.641-651
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• 2023

Malicious hate speech and gender bias comments are common in online communities, causing social problems in our society. Gender bias and hate speech detection has been investigated. However, it is difficult because there are diverse ways to express them in words. To solve this problem, we attempted to detect malicious comments in a Korean hate speech dataset constructed in 2020. We explored bidirectional encoder representations from transformers (BERT)-based deep learning models utilizing hyperparameter tuning, data sampling, and logits ensembles with a label distribution. We evaluated our model in Kaggle competitions for gender bias, general bias, and hate speech detection. For gender bias detection, an F1-score of 0.7711 was achieved using an ensemble of the Soongsil-BERT and KcELECTRA models. The general bias task included the gender bias task, and the ensemble model achieved the best F1-score of 0.7166.

• Progress in Superconductivity
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• 제14권2호
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• pp.96-98
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• 2012

Bias current dependence of a superconducting strip photon detector is studied in the wavelength range of 405 to 1310 nm. The detector is made of an $MgB_2$ meander pattern with the line width of 135 nm and thickness of 10 nm. At 1310 nm, the detection efficiency exponentially decreases as the bias current decreases. While at 405 nm, the detection efficiency almost saturates in the high bias current region. These features suggest that the intrinsic detection efficiency of the $MgB_2$ detector is high at 405 nm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.554-557
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• 1992

In this paper the normalized innovations squared of a Kalman filter is used to detect a bias level in prediction errors due to target accelerations. The probability density function of the normalized innovation squared is obtained for a steady state Kalman filter, and it is used to calculate the detection probability of the bias level. A typical example is given to compute the detection probability.

• 대한전기학회논문지
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• 제36권9호
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• pp.678-684
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• 1987

The identification problem of instrument faults in PWR pressurizer is considered. The instrument failure detection technique in this paper consists of two filters, a normal-mode Kalman filter which estimates plant states in normal operation and a bias estimator which estimates the magnitudes and directions of bias faults. The concept of threshold based on the residual of a Kalman filter in normal operation is introduced. The bias estimator is driven when the absolute value of residual exceeds the threshold. The suggested failure detection algorithm is applied to a PWR pressurizer. Computer simulations show that the prompt detection of bias fault can be performed very successfully when there exist instrument faults.

• 한국전자파학회:학술대회논문집
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• 한국전자파학회 2005년도 종합학술발표회 논문집 Vol.15 No.1
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• pp.97-100
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• 2005

This paper proposes a linearization method that is to control the operating point of a class AB amplifier according to its output power. The proposed linearization method is presented in this paper and the performance test results using two-tone signal are presented also.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.86.5-86
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• 2002

The measurement sensor may contain unknown bias in addition to the white noise in the measurement sequence. In this paper, fault detection and diagnosis scheme for the measurement sensor is developed based on the adaptive estimator. The proposed scheme consists of a parallel bank of Kalman-type filters each matched to a set of different possible biases, a mode probability evaluator, an estimate combiner at the outputs of the filters, a bias estimator, and a fault detection and diagnosis logic. Monte Carlo simulations for the PWR steam generator in the nuclear power plant are provided to illustrate the effectiveness of the proposed scheme.

• Journal of Information Processing Systems
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• 제9권4호
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• pp.538-547
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• 2013

In this paper, we propose a bias detection method that is based on personal and social opinions that express contrasting views on competing topics on Twitter. We used unsupervised polarity classification is conducted for learning social opinions on targets. The $tf{\cdot}idf$ algorithm is applied to extract targets to reflect sentiments and features of tweets. Our method addresses there being a lack of a sentiment lexicon when learning social opinions. To evaluate the effectiveness of our method, experiments were conducted on four issues using Twitter test collection. The proposed method achieved significant improvements over the baselines.

• 센서학회지
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• 제2권1호
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• pp.57-64
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• 1993

이 논문에서는 목표의 가속에서 비롯된 예측오차의 바이어스 레벨을 검출하기 위해서 Kalman 필터의 정규화된 이노베이션 제곱을 검출함수로 사용하고 그 검출함수의 바이어스 레벨 검출확률을 구했다. 여기서 이 확률의 효율적 표현을 위해서 재정의된 상태변수를 사용하였고, 이 상태변수의 Singer 모델에 대한 정상상태 Kalman 필터의 정규화된 이노베이션 제곱의 확률밀도함수를 구했다. 그리고 이 확률밀도함수를 이용하여 예측오차의 바이어스 레벨 검출확률 및 기동 검출기 동작특성곡선을 구했다.

• 한국항공우주학회지
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• 제32권9호
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• pp.88-93
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• 2004

본 논문에서는 기저선 제한조건을 이용하여 GPS 반송파 측정값에 바이어스 존재 여부를 보다 정확하게 판단하는 방법을 확인하고, 시뮬레이션을 통하여 이를 분석하였다. 기저선 제한조건은 추가적인 측정값으로 사용되며, 기존의 GPS 반송파 측정 방정식을 확장하는 형태로 사용된다. GPS 반송파 측정값만을 사용하는 경우와 기저선 제한조건을 함께 사용하는 경우에 대하여, 각각 검출확률(Detection Probability)를 계산하고 기저선 제한조건을 사용하는 경우 검출확률이 향상되는 것을 보이게 된다. 기저선 제한조건을 사용하는 것에 대한 장점을 통계적으로 증명하고 시뮬레이션을 통하여 수치적인 결과를 확인한다.

• 제어로봇시스템학회논문지
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• 제6권4호
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• pp.254-260
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• 2000

This paper deals with the development of fault tolerant control for a nonlinear boiler system with noise and disturbance. The MCMBPC(Multivariable Constrained Model Based Predictive Control) is adopted for the control of the specific boiler turbin model. The fault detection and diagnosis are accomplished with the Kalman filter and two bias estimators. Once a fault is detected, two Bias estimators are driven to estimate the fault and to discriminate Process fault and sensor fault. In this paper, a fault tolerant control scheme combining MCMBPC with a fault compensation method based on the bias estimator is proposed. The proposed scheme has been applied to the nonlinear boiler system and shown a satisfactory performance through some simulations.