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Bandwagons are ubiquitous in social life. No one doubts that people vote at least sometimes for political candidates simply because they are winning and or embrace many fashions simply because they want to "follow the crowd." But estimating how much a bourgeoning trend owes to pure "bandwagon effects" can be very difficult. Often other factors motivate the people taking action to an unknown degree. In this paper we investigate the use of two variable window scan statistics, the minimum P value scan statistic and the generalized likelihood ratio test (GLRT) statistic, to analyze one important form of the bandwagon problem. We show how these scan statistics can be used to detect the clustering of bandwagon events in a time interval. Once the events are identified, the information can be used to set boundaries on the extent of bandwagoning. The method is illustrated by reference to data on political contributions in the 2016 U.S. Senate elections. [ABSTRACT FROM AUTHOR]

Target detection in the multiscale situation where there exit multiple ship targets with different sizes is a challenging task due to the mismatch of the sizes of ship targets and fixed windows. A new constant false alarm rate (CFAR) algorithm based on variable window for ship target detection in SAR images is proposed. First, the multiscale local contrast measure is introduced to estimate the ship target size without any prior knowledge about ships. Second, the size of neighborhood area is adaptively set and a transform algorithm is designed to enhance the contrast between targets and background. Finally, CFAR detection is implemented by adopting variable window to gain the accurate ship targets. Experimental results indicate that the proposed algorithm has better performance compared with other CFAR detection algorithms. [ABSTRACT FROM AUTHOR]

This paper presents the journal relative impact ( JRI), an indicator for scientific evaluation of journals. The JRI considers in its calculation the different culture of citations presented by the Web of Science subject categories. The JRI is calculated considering a variable citation window. This citation window is defined taking into account the time required by each subject category for the maturation of citations. The type of document considered in each subject category depends on its outputs in relation to the citations. The scientific performance of each journal in relation to each subject category that it belongs to is considered allowing the comparison of the scientific performance of journals from different fields. The results obtained show that the JRI can be used for the assessment of the scientific performance of a given journal and that the SJR and SNIP should be used to complement the information provided by the JRI. The JRI presents good features as stability over time and predictability. [ABSTRACT FROM AUTHOR]

Existing stereo methods tend not to deal with depth discontinuity due to area-based problems, and so give inaccurate and noisy three-dimensional (3D) information in the surface morphology with steep disparity variations. In this paper, a hybrid stereo approach has been presented to estimate accurate, detailed and smooth information for the reconstruction and inspection of the surface morphology with both depth discontinuity and curved regions. It reduces the smoothing problems resulting from depth discontinuity by evaluating a new correlation function based on voxel components in the 3D disparity space. In addition, the connectivity of match candidate voxels is investigated to improve robustness to noise and then integer disparities are determined in the updated disparity space. A variable window based on voxel components is newly devised to cope effectively with curved regions as well as depth discontinuity. Sub-pixel disparities are accurately estimated through formulating the optimal error function in the variable window. We show how our results improve upon those of closely related techniques in terms of accuracy, robustness, matching density and computing speed. [ABSTRACT FROM AUTHOR]

This paper describes a stereo algorithm based on a new variable window for surface morphology inspection and its reconstruction on a machine tool. It has been surveyed that previous stereo algorithms generate large matching errors due to large disparity variations near depth discontinuities. The proposed stereo algorithm devises the variable window in three-dimensional disparity space constructed with match candidate points, which are selected by a correlation function with robust estimator, including line masks. Also, it takes into account intensity variations using intensity gradient-based similarity and then reflects on projective distortion in the variable window to estimate accurate and robust disparities in surface morphology with depth discontinuity. Several experiments show that the proposed technique outperforms closely related stereo methods. [ABSTRACT FROM AUTHOR]