Humans are sensitive to complexity and regularity in patterns [YKM13, FK97]. The subjective perception of pattern complexity is correlated to algorithmic (Kolmogorov-Chaitin) complexity as defined in computer science [LV08], but also to the frequency of naturally occurring patterns [HGS10]. However, the possible mediational role of natural frequencies in the perception of algorithmic complexity...

The parametric cubic curve is a well-developed subject in the field of computer-aided design. Yet there are still some aspects of its nature that need to be more fully investigated. In this paper, formulations of composite PC curves are presented in an order of increasing rigorousness and order of accuracy. A unique PC curve formulation is developed for the practical use in circle approximation...

Poole’s (2000, Non-parametric unfolding of binary choice data. Political Analysis 8:211–37) nonparametric Optimal Classification procedure for binary data produces misleading rank orderings when applied to the modern House of Commons. With simulations and qualitative evidence, we show that the problem arises from the government-versus-opposition nature of British (Westminster) parliamentary pol...

In this paper, we use the blending functions of Lupaş type (rational) (p, q)-Bernstein operators based on (p, q)-integers for construction of Lupaş (p, q)-Bézier curves (rational curves) and surfaces (rational surfaces) with shape parameters. We study the nature of degree elevation and degree reduction for Lupaş (p, q)-Bézier Bernstein functions. Parametric curves are represented using Lupaş (p...

Mechanical and electromechanical parametric amplifiers have garnered significant interest, as of late, due to the increased need for low-noise signal amplification in resonant micro/nanosystems. While these devices, which are traditionally designed to operate in a linear range, potentially represent an elegant, on-chip amplification solution, it is not readily apparent that this technical appro...

background: precise diagnosis of disease risk factors via efficient statistical models is the primary step for reducing the heavy costs of breast cancer, as one of the most highly prevalent cancer throughout the world. therefore, the aim of this study was to present a recently introduced statistical model in order to assess its proficiency for model fitting. methods: the information of 1465 eli...

The world of robot soccer is a subjective one due to the di cult nature of collecting data. In this paper we present a number of non-parametric statistical tests that can be used to analyze the performance of strategies without the need for a large sample size. We present results that show a \case-based" strategy performs signi cantly better (statistically) than a \potential eld" strategy in si...

Using standard nonlinear programming (NLP) theory, we establish formulas for first and second order directional derivatives for optimal value functions of parametric mathematical programs with complementarity constraints (MPCCs). The main point is that under a linear independence condition on the active constraint gradients, optimal value sensitivity of MPCCs is essentially the same as for NLPs...

We present new results of interference experiments for undergraduates that underscore the quantum nature of the light. The experiments use parametric down-conversion to generate pairs of correlated photons. The experiments involve oneand two-photon interference schemes that rely on first and second-order coherence effects. They can be used as a complement to teaching quantum mechanics or quantu...

Unit selection (US) TTSs generate quite natural speech but highly variable in quality. Statistical parametric (SP) systems offer far more consistent quality but reduced naturalness due to its vocoding nature. We present a hybrid approach (HA) that tries to improve the overall naturalness combining both synthesis methods. Contrary to other works, the fusion of methods is performed both in prosod...