• Communications for Statistical Applications and Methods
• /
• 제29권2호
• /
• pp.251-261
• /
• 2022

As AI has a wide range of influence on human social life, issues of transparency and ethics of AI are emerging. In particular, it is widely known that due to the existence of historical bias in data against ethics or regulatory frameworks for fairness, trained AI models based on such biased data could also impose bias or unfairness against a certain sensitive group (e.g., non-white, women). Demographic disparities due to AI, which refer to socially unacceptable bias that an AI model favors certain groups (e.g., white, men) over other groups (e.g., black, women), have been observed frequently in many applications of AI and many studies have been done recently to develop AI algorithms which remove or alleviate such demographic disparities in trained AI models. In this paper, we consider a problem of using the information in the sensitive variable for fair prediction when using the sensitive variable as a part of input variables is prohibitive by laws or regulations to avoid unfairness. As a way of reflecting the information in the sensitive variable to prediction, we consider a two-stage procedure. First, the sensitive variable is fully included in the learning phase to have a prediction model depending on the sensitive variable, and then an imputed sensitive variable is used in the prediction phase. The aim of this paper is to evaluate this procedure by analyzing several benchmark datasets. We illustrate that using an imputed sensitive variable is helpful to improve prediction accuracies without hampering the degree of fairness much.

• Asian-Australasian Journal of Animal Sciences
• /
• 제18권8호
• /
• pp.1088-1097
• /
• 2005

Main objectives of this study were to investigate accuracy, bias and power of linear and threshold model segregation analysis methods for detection of major genes in categorical traits in farm animals. Maximum Likelihood Linear Model (MLLM), Bayesian Linear Model (BALM) and Bayesian Threshold Model (BATM) were applied to simulated data on normal, categorical and binary scales as well as to disease data in pigs. Simulated data on the underlying normally distributed liability (NDL) were used to create categorical and binary data. MLLM method was applied to data on all scales (Normal, categorical and binary) and BATM method was developed and applied only to binary data. The MLLM analyses underestimated parameters for binary as well as categorical traits compared to normal traits; with the bias being very severe for binary traits. The accuracy of major gene and polygene parameter estimates was also very low for binary data compared with those for categorical data; the later gave results similar to normal data. When disease incidence (on binary scale) is close to 50%, segregation analysis has more accuracy and lesser bias, compared to diseases with rare incidences. NDL data were always better than categorical data. Under the MLLM method, the test statistics for categorical and binary data were consistently unusually very high (while the opposite is expected due to loss of information in categorical data), indicating high false discovery rates of major genes if linear models are applied to categorical traits. With Bayesian segregation analysis, 95% highest probability density regions of major gene variances were checked if they included the value of zero (boundary parameter); by nature of this difference between likelihood and Bayesian approaches, the Bayesian methods are likely to be more reliable for categorical data. The BATM segregation analysis of binary data also showed a significant advantage over MLLM in terms of higher accuracy. Based on the results, threshold models are recommended when the trait distributions are discontinuous. Further, segregation analysis could be used in an initial scan of the data for evidence of major genes before embarking on molecular genome mapping.

• 한국측량학회지
• /
• 제37권2호
• /
• pp.55-62
• /
• 2019

The stereo geometry establishment based on the precise sensor modeling is prerequisite for accurate stereo data processing. Ground control points are generally required for the accurate sensor modeling though it is not possible over the area where the accessibility is limited or reference data is not available. For the areas, the relative orientation should be carried out to improve the geometric consistency between the stereo data though it does not improve the absolute positional accuracy. The relative orientation requires conjugate points that are well distributed over the entire image region. Therefore the automatic conjugate point extraction is required because the manual operation is labor-intensive. In this study, we applied the method consisting of the key point extraction, the search space minimization based on the epipolar line, and the rigorous outlier detection based on the RPCs (Rational Polynomial Coefficients) bias compensation modeling. We tested different parameters of window sizes for Kompsat-2 across track stereo data and analyzed the RPCs precision after the bias compensation for the cases whether the epipolar line information is used or not. The experimental results showed that matching outliers were inevitable for the different matching parameterization but they were successfully detected and removed with the rigorous method for sub-pixel level of stereo RPCs precision.

• 한국산학기술학회논문지
• /
• 제17권9호
• /
• pp.141-155
• /
• 2016

본 연구는 중년기 성인의 뇌졸중 관련 건강지식, 낙관적 편견 및 건강증진 생활양식 정도와 관계를 파악하고, 건강증진 생활양식에 미치는 효과를 파악하기 위한 서술적 조사연구이다. 연구기간은 2015년 7월 15일부터 8월 15일이며, 연구대상자는 40세 이상 60세 미만의 성인 191명이며, 자료 수집은 구조화된 설문지를 이용한 자가 보고식으로 이루어졌다. 자료분석은 PASW Statistics 21.0과 AMOS 21.0 프로그램을 사용하였으며, 분산분석, 상관성분석, 구조방정식 모형 분석 등을 실시하였다. 중년기 성인은 뇌졸중 위험요인으로 흡연과 고혈압을 당뇨병보다 높게 인식하였으며, 뇌졸중에 대한 낙관적 편견은 미미하였다. 뇌졸중 관련 건강지식은 낙관적 편견(r=-.143, p=.048), 건강증진 생활양식(r=.268, p=<.001)과 상관관계가 있었고, 낙관적 편견은 건강증진 생활양식의 대인관계 및 스트레스 행위(r=.177, p=.014)와 상관관계가 있었다. 또한 뇌졸중 관련 건강지식이 낙관적 편견보다 건강증진 생활양식에 더 큰 영향을 미치는 것으로 확인하였다. 결론적으로 중년기 성인의 뇌졸중에 관한 능동적인 정보획득과 건강 지식, 낙관적 편견이 뇌졸중 관련 건강증진 생황양식에 중요한 요인임을 알 수 있었다. 그러므로 중년기 성인의 뇌졸중 관련 건강증진 생활양식을 향상시키기 위한 교육 프로그램에는 뇌졸중 관련 건강지식을 높이고, 낙관적 편견을 감소시킬 수 있는 방안이 고려되어야 할 것이다.

• Journal of Astronomy and Space Sciences
• /
• 제28권4호
• /
• pp.267-271
• /
• 2011

I developed an enhanced correction method for Ricean bias which occurs in linear polarization measurement. Two known methods for Ricean bias correction are reviewed. In low signal-to-noise area, the method based on the mode of the equation gives better representation of the fractional polarization. But a caution should be given that the accurate estimation of noise level, i.e. ${\sigma}$ of the polarized flux, is important. The maximum likelihood method is better choice for high signal-to-noise area. I suggest a hybrid method which uses the mode of the equation at the low signal-to-noise area and takes the maximum likelihood method at the high signal-to-noise area. A modified correction coefficient for the mode solution is proposed. The impact on the depolarization measure analysis is discussed.

• 한국항공우주학회지
• /
• 제33권12호
• /
• pp.61-67
• /
• 2005

본 논문에서는 GPS 신호가 자주 단절되는 환경하에서도 안정한 위치 해를 제공하는 반송파 DGPS 방법을 제안한다. 시계 바이어스 변화율을 이용하여 큰 오차가 포함된 측정치 채널을 제거함으로써 더욱 정확한 위치 해를 제공하는 알고리듬을 구현하였다. 가시위성의 앙각과 시계 바이어스 변화율의 관계를 살펴보고, 적절한 임계치를 제안하였으며, 구현된 알고리듬이 실데이터에서도 성능이 우수함을 상용프로그램과 비교하여 보였다.

• 한국정보시스템학회지:정보시스템연구
• /
• 제23권3호
• /
• pp.143-164
• /
• 2014

This study draws on status quo bias theoretic perspective as a meta-theoretic lens to explain why individuals have resists to adopt smart devices for their tasks. More specifically, we attempted to examine the relationships among user's resist, perceived usefulness and individual productivity in the smart work context. By employing the status quo bias theoretic perspective, we develop and test our research model by using a survey data from 235 individual users. We demonstrate that satisfaction on the current state influence users' resist, and also the users' resist is mediated by perceived usefulness on individual productivity. From the status quo bias view, this study presents an alternative meta-theoretical lens in order to understand individuals' resist in the smartwork context.

• Applied Science and Convergence Technology
• /
• 제23권3호
• /
• pp.145-150
• /
• 2014

MgO thin films were deposited by internal ICP-assisted reactive-magnetron sputtering with bipolar pulse bias on a substrate to suppress random arcs. Mg is reactively sputtered by a bipolar pulsed DC power of 100 kHz into ICP generated by a dielectrically shielded internal antenna. At a mass flow ratio of $Ar/O_2$ = 10 : 2 and an ICP/sputter power ratio of 1 : 1, optimal film properties were obtained (a powder-like crystal orientation distribution and a RMS surface roughness of approximately 0.42 nm). A bipolar pulse substrate bias at a proper frequency (~a few kHz) prevented random arc events. The crystalline preferred orientations varied between the (111), (200) and (220) orientations. By optimizing the plasma conditions, films having similar bulk crystallinity characteristics (JCPDS data) were successfully obtained.

• 한국항공우주학회지
• /
• 제31권1호
• /
• pp.58-66
• /
• 2003

본 논문에서는 무궁화위성을 대상으로 추적 안테나의 바이어스를 추정하기 위한 방안들을 제시하고 있다. 먼저 거리, 방위각, 앙각에 이어 선회시선거리를 포함하는 배치필터를 구성하였으며 시뮬레이션을 통하여 바이어스 추정성능 변화를 분석하였다. 또한 결과를 보완하기 위하여 정밀하게 보정된 타 추적 안테나의 정보를 이용하여 대상 안테나의 바이어스를 정확하게 예측하기 위한 방안을 제시하였다. 마지막으로 안테나 바이어스 추정 결과를 분석하고 평가할 수 있도록 안테나 바이어스간의 상관관계에 대한 분석을 수행하였다.

• The Journal of Asian Finance, Economics and Business
• /
• 제9권10호
• /
• pp.97-104
• /
• 2022

The purpose of the existing work is to inspect the impact of knowledge management on organizational performance. Business experts now appreciate how important knowledge management is for organizational performance. Earlier studies have investigated the research model with causal linkages, however, only a few of them have considered sample-selecting bias problems when analyzing the model of knowledge management on organizational performance. The number of 312 executives related to knowledge management from 312 enterprises that have been approved with quality management systems offered suitable responses for analyses. The data was employed to investigate the effect of knowledge management on organizational performance, considering sample-selecting bias. The empirical outcomes indicate that sample-selecting bias exists in the causal impact of knowledge management on organizational performance. The empirical findings are helpful to scholars of knowledge management as well as business executives by giving an insight into the casual effect of knowledge management on organizational performance with the intervention of sample-selecting bias. The acceptance of knowledge management should be tailored to improve competitive advantages that will lead to better organizational performance.