Social signals as design interventions for enhancing citizen science contributions*

Despite the scientific potential and increasing popularity of web-based citizen science, low contribution from volunteers is often a major hurdle. Studies have shown that individual behavior could be altered through targeted design interventions, but little is known about the specific factors that modulate volunteers’ contributions. A particularly elusive question entails the role of social feedback, in the form of targeted notifications about the contribution of other volunteers. Based on social comparison theory, we hypothesized that (1) volunteers increase contribution when presented with information about a high-performing peer or group, and (2) volunteers conform more strongly to a group rather than to a single peer. To test whether volunteers’ contributions change due to the exposure to the contribution of a peer or group norm, we systematically varied the information presented to participants in an environmental monitoring citizen science project. Volunteers increased their contributions when they were presented with the contribution of a high-performing peer and norm, but they were not influenced by a low-performing peer or norm. Further, we found that volunteers were more likely to match the contributions of a group than that of a peer. However, when volunteers were simultaneously exposed to information about a peer and a group, the effect depended on the respective performance of the peer and group. A theoretical model was developed to explain volunteers’ response and dissect the specific role of social comparison. Our findings offer the possibility of increasing volunteers’ contributions through design interventions.     

社会规范的形成与运作——以合作为视角

秩序的萌发、形成与维系并非完全以法律为依托,对其理解应摆脱法律中心主义的观念。社会规范在前政府时代社会秩序维持中起着重要的作用。博弈论和信号传递理论为理解社会规范的出现和运作提供了一个更加清晰的视角,同时也为社会规范的弱点及法律的功能提供了一个较为有力的解说。     

Inference on constant stress accelerated life tests for log-location-scale lifetime distributions with type-I hybrid censoring

In this paper, we consider a constant stress accelerated life test terminated by a hybrid Type-I censoring at the first stress level. The model is based on a general log-location-scale lifetime distribution with mean life being a linear function of stress and with constant scale. We obtain the maximum likelihood estimators (MLE) and the approximate maximum likelihood estimators (AMLE) of the model parameters. Approximate confidence intervals, likelihood ratio tests and two bootstrap methods are used to construct confidence intervals for the unknown parameters of the Weibull and lognormal distributions using the MLEs. Finally, a simulation study and two illustrative examples are provided to demonstrate the performance of the developed inferential methods.     

Asymptotic properties of approximate maximum quasi-likelihood estimator in quasi-likelihood nonlinear models with random effects

Quasi-likelihood nonlinear models with random effects (QLNMWRE) include generalized linear models with random effects and quasi-likelihood nonlinear models as special cases. In this paper, some regularity conditions analogous to those given by Breslow and Clatyton (1993) are proposed. On the basis of the proposed regularity conditions and Laplace approximation, the existence, the strong consistency and asymptotic normality of the approximate maximum quasi-likelihood estimation of the fixed effects are proved in QLNMWRE.     

Pivotal inference for the inverse Rayleigh distribution based on general progressively Type-II censored samples

In this paper, we consider the problem of estimating the scale parameter of the inverse Rayleigh distribution based on general progressively Type-II censored samples and progressively Type-II censored samples. The pivotal quantity method is used to derive the estimator of the scale parameter. Besides, considering that the maximum likelihood estimator is tough to obtain for this distribution, we derive an explicit estimator of the scale parameter by approximating the likelihood equation with Taylor expansion. The interval estimation is also studied based on pivotal inference. Then we conduct Monte Carlo simulations and compare the performance of different estimators. We demonstrate that the pivotal inference is simpler and more effective. The further application of the pivotal quantity method is also discussed theoretically. Finally, two real data sets are analyzed using our methods.     

A backward procedure for change-point detection with applications to copy number variation detection

Change-point detection regains much attention recently for analyzing array or sequencing data for copy number variation (CNV) detection. In such applications, the true signals are typically very short and buried in the long data sequence, which makes it challenging to identify the variations efficiently and accurately. In this article, we propose a new change-point detection method, a backward procedure, which is not only fast and simple enough to exploit high-dimensional data but also performs very well for detecting short signals. Although motivated by CNV detection, the backward procedure is generally applicable to assorted change-point problems that arise in a variety of scientific applications. It is illustrated by both simulated and real CNV data that the backward detection has clear advantages over other competing methods, especially when the true signal is short. The Canadian Journal of Statistics 48: 366–385; 2020 © 2020 Statistical Society of Canada     

P帧快速模式选择算法

针对H.264编码算法中,预测帧(P帧)编码模式的选择过程异常复杂,开销大的问题,提出了一种新的快速模式选择算法,该算法利用直流系数能预先判定P帧编码模式的有效范围,缩小备选编码模式的可选范围,从而使模式选择的复杂度大为降低。实验结果表明,该算法可以使编码时间降低54%～74%,峰值信噪比提高0.05 dB～0.17 dB,同时码率变化范围为-3.14%～3.97%。应用结果表明,该算法在基于TI's TMS320DM642视频压缩系统中1路D1视频的压缩速度为25帧/s。     

On the distributions of multivariate sample skewness

In this paper, we consider the multivariate normality test based on measure of multivariate sample skewness defined by Srivastava (1984). Srivastava derived asymptotic expectation up to the order N⁻¹ for the multivariate sample skewness and approximate χ²${\chi }^2$ test statistic, where N   is sample size. Under normality, we derive another expectation and variance for Srivastava's multivariate sample skewness in order to obtain a better test statistic. From this result, improved approximate χ²${\chi }^2$ test statistic using the multivariate sample skewness is also given for assessing multivariate normality. Finally, the numerical result by Monte Carlo simulation is shown in order to evaluate accuracy of the obtained expectation, variance and improved approximate χ²${\chi }^2$ test statistic. Furthermore, upper and lower percentiles of χ²${\chi }^2$ test statistic derived in this paper are compared with those of χ²${\chi }^2$ test statistic derived by Mardia (1974) which is used multivariate sample skewness defined by Mardia (1970).     

Statistical Inference of Type-II Progressively Hybrid Censored Data with Weibull Lifetimes

In this article, we discuss the maximum likelihood estimators and approximate maximum likelihood estimators of the parameters of the Weibull distribution with two different progressively hybrid censoring schemes. We also present the associated expressions of the expected total test time and the expected effective sample size which will be useful for experimental planning purpose. Finally, the efficiency of the point estimation of the parameters based on the two progressive hybrid censoring schemes are compared and the merits of each censoring scheme are discussed.