arXiv subjects

Carlos Velasco

Publications and source records attributed to Carlos Velasco.

7 recordsLinked to original sources

arXiv2026

xSense Design Cards: Guiding the Design of Multisensory Experiences

Designing multisensory experiences involves the deliberate combination of sensory elements to shape specific impressions for a given audience. Advances in technologies beyond audiovisual modalities now make it feasible to design across touch, taste, smell, and more. However, HCI still lacks the tools and shared vocabulary needed to systematically create and evaluate such experiences. The xSense Design Cards address this gap with four card types: (1) Experience Cards define purpose, context, and audience; (2) Sensory Cards break down multisensory concepts into elements and events; (3) Technology Cards prompt consideration of relevant technologies; and (4) Exploration Cards guide reflection on the broader context, including responsible innovation. This work introduces the cards and their theoretical grounding, showing how they support structured design, reflection, and evaluation of an experience's multisensory composition. By presenting xSense, we aim to broaden the vocabulary for multisensory design and stimulate discussion within the growing multisensory HCI community.

cs.ET↗

arXiv2020

Identification and estimation of Structural VARMA models using higher order dynamics

We use information from higher order moments to achieve identification of non-Gaussian structural vector autoregressive moving average (SVARMA) models, possibly non-fundamental or non-causal, through a frequency domain criterion based on a new representation of the higher order spectral density arrays of vector linear processes. This allows to identify the location of the roots of the determinantal lag matrix polynomials based on higher order cumulants dynamics and to identify the rotation of the model errors leading to the structural shocks up to sign and permutation. We describe sufficient conditions for global and local parameter identification that rely on simple rank assumptions on the linear dynamics and on finite order serial and component independence conditions for the structural innovations. We generalize previous univariate analysis to develop asymptotically normal and efficient estimates exploiting second and non-Gaussian higher order dynamics given a particular structural shocks ordering without assumptions on causality or invertibility. Bootstrap approximations to finite sample distributions and the properties of numerical methods are explored with real and simulated data.

math.ST↗

arXiv2020

Single-step exfoliation and functionalization of few-layers black phosphorus and its application for polymer composites

We demonstrate the large scale exfoliation of bulk black phosphorus into few-layers black phosphorus. We use wet-jet mill (WJM) as an industrially scalable exfoliation technique. In order to avoid the degradation by oxidation of the exfoliated flakes, the few-layers black phosphorus is protected by functionalisation (with 4-bromobenzene-diazonium tetrafluoroborate) during the exfoliation process. We used the exfoliated and functionalised flakes as fillers in a polymethyl methacrylate matrix to test the mechanical endurance, obtaining an improvement in the Young modulus of 106% compared to the bare polymer. These data support the development of black phosphorus materials as 2D-polymer fillers and performance-enhancers.

physics.app-ph↗

arXiv2018

Modern Physics Simulations

Modern physics is now a regular course for non-physics majors who do not have to take the accompanying laboratory. This lack of an experimental component puts the engineering students at a disadvantage. A possible solution is the use of computer simulations to add a constructivist element to the class. In this work, we present a set of computer simulations of fundamental experiments, a key to the teaching of modern physics, as well as their in-class implementation and assessment. Preliminary results indicate that the use of these simulations produces a substantial increase in student comprehension.

physics.ed-ph↗

arXiv2017

New goodness-of-fit diagnostics for conditional discrete response models

This paper proposes new specification tests for conditional models with discrete responses, which are key to apply efficient maximum likelihood methods, to obtain consistent estimates of partial effects and to get appropriate predictions of the probability of future events. In particular, we test the static and dynamic ordered choice model specifications and can cover infinite support distributions for e.g. count data. The traditional approach for specification testing of discrete response models is based on probability integral transforms of a jittered discrete data which leads to continuous uniform iid series under the true conditional distribution. Then, standard specification testing techniques for continuous variables could be applied to the transformed series, but the extra randomness from jitters affects the power properties of these methods. We investigate in this paper an alternative transformation based only on original discrete data that avoids any randomization. We analyze the asymptotic properties of goodness-of-fit tests based on this new transformation and explore the properties in finite samples of a bootstrap algorithm to approximate the critical values of test statistics which are model and parameter dependent. We show analytically and in simulations that our approach dominates the methods based on randomization in terms of power. We apply the new tests to models of the monetary policy conducted by the Federal Reserve.

math.ST↗

arXiv2012

Model Adequacy Checks for Discrete Choice Dynamic Models

This paper proposes new parametric model adequacy tests for possibly nonlinear and nonstationary time series models with noncontinuous data distribution, which is often the case in applied work. In particular, we consider the correct specification of parametric conditional distributions in dynamic discrete choice models, not only of some particular conditional characteristics such as moments or symmetry. Knowing the true distribution is important in many circumstances, in particular to apply efficient maximum likelihood methods, obtain consistent estimates of partial effects and appropriate predictions of the probability of future events. We propose a transformation of data which under the true conditional distribution leads to continuous uniform iid series. The uniformity and serial independence of the new series is then examined simultaneously. The transformation can be considered as an extension of the integral transform tool for noncontinuous data. We derive asymptotic properties of such tests taking into account the parameter estimation effect. Since transformed series are iid we do not require any mixing conditions and asymptotic results illustrate the double simultaneous checking nature of our test. The test statistics converges under the null with a parametric rate to the asymptotic distribution, which is case dependent, hence we justify a parametric bootstrap approximation. The test has power against local alternatives and is consistent. The performance of the new tests is compared with classical specification checks for discrete choice models.

math.ST↗

arXiv2006

Distribution free goodness-of-fit tests for linear processes

This article proposes a class of goodness-of-fit tests for the autocorrelation function of a time series process, including those exhibiting long-range dependence. Test statistics for composite hypotheses are functionals of a (approximated) martingale transformation of the Bartlett $T_p$-process with estimated parameters, which converges in distribution to the standard Brownian motion under the null hypothesis. We discuss tests of different natures such as omnibus, directional and Portmanteau-type tests. A Monte Carlo study illustrates the performance of the different tests in practice.

math.ST↗