The effects of the global structure of the mask in visual backward masking

The visibility of a target can be strongly affected by a trailing mask. Research on visual backward masking has typically focused on the temporal characteristics of masking, whereas non-basic spatial aspects have received much less attention. However, recently, it has been demonstrated that the spatial layout is an important determinant of the strength of a mask. Here, we show that not only local but also global aspects of the mask's spatial layout affect target processing. Particularly, it is the regularity of the mask that plays an important role. Our findings are of importance for theoretical research, as well as for applications of visual masking

Scalable Sparse Cox's Regression for Large-Scale Survival Data via Broken Adaptive Ridge

This paper develops a new scalable sparse Cox regression tool for sparse high-dimensional massive sample size (sHDMSS) survival data. The method is a local $L_0$-penalized Cox regression via repeatedly performing reweighted $L_2$-penalized Cox regression. We show that the resulting estimator enjoys the best of $L_0$- and $L_2$-penalized Cox regressions while overcoming their limitations. Specifically, the estimator is selection consistent, oracle for parameter estimation, and possesses a grouping property for highly correlated covariates. Simulation results suggest that when the sample size is large, the proposed method with pre-specified tuning parameters has a comparable or better performance than some popular penalized regression methods. More importantly, because the method naturally enables adaptation of efficient algorithms for massive $L_2$-penalized optimization and does not require costly data driven tuning parameter selection, it has a significant computational advantage for sHDMSS data, offering an average of 5-fold speedup over its closest competitor in empirical studies

Speech and music discrimination: Human detection of differences between music and speech based on rhythm

Rhythm in speech and singing forms one of its basic acoustic components. Therefore, it is interesting to investigate the capability of subjects to distinguish between speech and singing when only the rhythm remains as an acoustic cue. For this study we developed a method to eliminate all linguistic components but rhythm from the speech and singing signals. The study was conducted online and participants could listen to the stimuli via loudspeakers or headphones. The analysis of the survey shows that people are able to significantly discriminate between speech and singing after they have been altered. Furthermore, our results reveal specific features, which supported participants in their decision, such as differences in regularity and tempo between singing and speech samples. The hypothesis that music trained people perform more successfully on the task was not proved. The results of the study are important for the understanding of the structure of and differences between speech and singing, for the use in further studies and for future application in the field of speech recognition

A Framework for Symmetric Part Detection in Cluttered Scenes

The role of symmetry in computer vision has waxed and waned in importance during the evolution of the field from its earliest days. At first figuring prominently in support of bottom-up indexing, it fell out of favor as shape gave way to appearance and recognition gave way to detection. With a strong prior in the form of a target object, the role of the weaker priors offered by perceptual grouping was greatly diminished. However, as the field returns to the problem of recognition from a large database, the bottom-up recovery of the parts that make up the objects in a cluttered scene is critical for their recognition. The medial axis community has long exploited the ubiquitous regularity of symmetry as a basis for the decomposition of a closed contour into medial parts. However, today's recognition systems are faced with cluttered scenes, and the assumption that a closed contour exists, i.e. that figure-ground segmentation has been solved, renders much of the medial axis community's work inapplicable. In this article, we review a computational framework, previously reported in Lee et al. (2013), Levinshtein et al. (2009, 2013), that bridges the representation power of the medial axis and the need to recover and group an object's parts in a cluttered scene. Our framework is rooted in the idea that a maximally inscribed disc, the building block of a medial axis, can be modeled as a compact superpixel in the image. We evaluate the method on images of cluttered scenes.Comment: 10 pages, 8 figure

School starters’ early structure sense

Low and high achieving children’s competences regarding pattern and structure at the beginning of formal schooling are comparatively analyzed in order to evaluate the range of school starters’ early structure sense. The results suggest overall high pre-instructional competences which, however, differ strongly between the mathematical high and low achievers. Cognitive milestones for the development of a sound early structure sense are named

Infants’ perception of rhythmic patterns

We explored 9-month-old infants perception of auditory temporal sequences in a series of three experiments. In Experiment 1, we presented some infants with tone sequences that were expected to induce a strongly metric framework and others with a sequence that was expected to induce a weakly metric framework or no such framework. Infants detected a change in the context of the former sequences but not in the latter sequence. In Experiment 2, infants listened to a tone sequence with temporal cues to duple or triple meter. Infants detected a change in the pattern with duple meter but not in the pattern with triple meter. In Experiment 3, infants listened to a tone sequence with harmonic cues to duple or triple meter. As in Experiment 2, infants detected a change in the context of the duple meter pattern but not in the context of triple meter. These findings are consistent with processing predispositions for auditory temporal sequences that induce a metric framework, particularly those in duple meter

Suszko's Problem: Mixed Consequence and Compositionality

Suszko's problem is the problem of finding the minimal number of truth values needed to semantically characterize a syntactic consequence relation. Suszko proved that every Tarskian consequence relation can be characterized using only two truth values. Malinowski showed that this number can equal three if some of Tarski's structural constraints are relaxed. By so doing, Malinowski introduced a case of so-called mixed consequence, allowing the notion of a designated value to vary between the premises and the conclusions of an argument. In this paper we give a more systematic perspective on Suszko's problem and on mixed consequence. First, we prove general representation theorems relating structural properties of a consequence relation to their semantic interpretation, uncovering the semantic counterpart of substitution-invariance, and establishing that (intersective) mixed consequence is fundamentally the semantic counterpart of the structural property of monotonicity. We use those to derive maximum-rank results proved recently in a different setting by French and Ripley, as well as by Blasio, Marcos and Wansing, for logics with various structural properties (reflexivity, transitivity, none, or both). We strengthen these results into exact rank results for non-permeable logics (roughly, those which distinguish the role of premises and conclusions). We discuss the underlying notion of rank, and the associated reduction proposed independently by Scott and Suszko. As emphasized by Suszko, that reduction fails to preserve compositionality in general, meaning that the resulting semantics is no longer truth-functional. We propose a modification of that notion of reduction, allowing us to prove that over compact logics with what we call regular connectives, rank results are maintained even if we request the preservation of truth-functionality and additional semantic properties.Comment: Keywords: Suszko's thesis; truth value; logical consequence; mixed consequence; compositionality; truth-functionality; many-valued logic; algebraic logic; substructural logics; regular connective