Fabrizio Deriu, Performático. Teoria delle arti dinamiche - Mediologia della performance. Arti performátiche nell’epoca della riproducibilità digitale

Review of the book Performático. Teoria delle arti dinamiche - Mediologia della performance. Arti performátiche nell’epoca della riproducibilità digitale by Fabrizio Deriu.\Nonostante la loro collocazione editoriale separata, Performático. Teoria delle arti dinamiche e Mediologia della performance. Arti performátiche nell'epoca della riproducibilità digitale costituiscono il frutto di un lavoro di ricerca unitario e coerente, tale che, come suggerisce in più occasioni lo stesso autore, soltanto la lettura di entrambi i volumi sarebbe in grado di metterne in luce la fitta rete di connessioni

Improved dynamic window approach by using Lyapunov stability criteria

This paper presents improvements over the Dynamic Window Approach (I-DWA), used for computing in real time autonomous robot navigation. A novel objective function that includes Lyapunov stability criteria is proposed. It allows to guarantee a global and asymptotic convergence to the goal avoiding collisions and resulting in a more simple and self-contained approach. Experimental results with simulated and real environments are presented to validate the capability of the proposed approach. Additionally, comparisons with the original DWA are given

Hal Foster (Ed.), L’antiestetica. Saggi sulla cultura postmoderna

Review of the book L’antiestetica. Saggi sulla cultura postmodernaLa notevole distanza temporale che separa la prima edizione, nel 1983, della raccolta di saggi curata da Hal Foster e intitolata The Anti-Aesthetics e la recentissima pubblicazione di quest'ultima nella sua traduzione italiana, L'antiestetica, da parte di Postmedia Books costituisce una circostanza singolare per un'opera di così ampia e diffusa risonanza internazionale da essere definita da Ester Coen, nella sua postfazione, come il «vademecum di un'intera generazione» (187). A poco più di trent'anni di distanza questo testo ci appare per molti versi come un documento postumo, manifesto di un progetto – il postmodernismo – già esauritosi, riproposto «quando ormai la discussione si volge piuttosto altrove, alla consunzione di questo termine e, in definitiva, all'epilogo di una fase» (ibid.)

A method for enhancing eye movements data from eye-tracking devices

Eye movements play an important role in actual neuroscience and in the last twenty years, many eye-tracking devices have emerged with different methods and performance features. Generally, the highest quality ones with best performance in terms of accuracy and high framerates, are the most expensive apparatus and very often complicated to assembly. Also, they tend to work in fixed setups and it is hard to perform outdoor experiments, like driving a real car or walking long distances. The comfortable and cheaper ones are usually those having the poorest measuring characteristics, reaching maximum framerates below 250fps, yet with great advantages. These modern remote eye-tracking systems allow, in general, small head movements and the subject has not wear any kind of hardware. This feature is especially important when working with children or people with some kind of physical impairment. They are independent, small and one-piece hardware ready to plug into a mobile computer or laptop, making easy to set a large variety of experiments. In this work, we propose to use wavelet methods to improve real eye movements data, allowing the reconstruction of the signal at a higher resolution than the original one. Transformed data was upsampled and the new coefficients were obtained by interpolation using different techniques and looking for a minimum percentage error between the original and recovered signals. Then, treating the eyetracker data with low samplerate as a complete signal with periodic miss- ing parts or information and inspired in a method for restoring very damaged images, we present an approach to adapt one of the the algorithms for images to 1D signals. Mecánica Computacional Vol XXXV, págs. 2521-2532 (artículo completo) Martín I. Idiart, Ana E. Scarabino y Mario A. Storti (Eds.) La Plata, 7-10 Noviembre 2017 Copyright ©Publicado en: Mecánica Computacional vol. XXXV, no. 43Facultad de Ingenierí

Evaluación de patologías neurocognitivas mediante los movimientos oculares

La lectura es un proceso retroalimentado que requiere la integración de diferentes sistemas cognitivos, y por consiguiente constituye una actividad ideal para explorar las relaciones entre los movimientos oculares y los procesos neuropsicológicos involucrados en la misma. Se sabe que varios de los procesos cognitivos asociados, como la memoria de trabajo y la memoria semántica, son relevantes a la hora de leer oraciones. Por ejemplo; en personas sanas, durante la lectura de frases predecibles, la predictibilidad de la palabra siguiente facilita el procesamiento del texto leído. En el presente trabajo se muestra el efecto de la predictibilidad de las palabras en el comportamiento del movimiento ocular en pacientes con deterioro cognitivo leve debido a demencias neuropsiquiátricas como la enfermedad de Alzheimer (EA) y la esquizofrenia (EZ), en comparación con grupos control de edades y nivel educativo similares. Las diferencias en los patrones de lectura se pueden apreciar claramente. Nuestros resultados muestran que es posible desarrollar una nueva técnica objetiva, no invasiva y económica para evaluar deterioro cognitivo leve(DCL) que podrían ayudar en el diagnóstico temprano y adecuado de tales patologías

Clasificación de emociones básicas mediante análisis cuantitativo de señales EEG

En este trabajo se presenta un metodo de clasificación automática de emociones humanas utilizando la Transformada Wavelet Discreta (TWD) y una red neuronal profunda. Para ello se extraen características cuantitativas de la información espectral de las señales electroencefalográficas (EEG) utilizando la TWD y se separan los datos en cuatro grupos de acuerdo a los atributos de los estímulos emocionales. Posteriormente, se clasifica automáticamente la información espectral utilizando una red neuronal profunda con una efectividad un poco superior a la alcanzada por otros métodos.Fil: Arriola, Juan Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; Argentina. Universidad Nacional del Sur; ArgentinaFil: Alvarez, Marcela Patricia. Universidad Nacional del Sur; ArgentinaFil: Castro, Liliana Raquel. Universidad Nacional del Sur; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; ArgentinaFil: Agamennoni, Osvaldo Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; Argentina. Universidad Nacional del Sur; ArgentinaVI Congreso de Matemática Aplicada, Computacional e IndustrialComodoro RivadaviaArgentinaAsociación Argentina de Matemática Aplicada, Computacional e Industria

High-dimensional Log-Error-in-Variable Regression with Applications to Microbial Compositional Data Analysis

In microbiome and genomic study, the regression of compositional data has been a crucial tool for identifying microbial taxa or genes that are associated with clinical phenotypes. To account for the variation in sequencing depth, the classic log-contrast model is often used where read counts are normalized into compositions. However, zero read counts and the randomness in covariates remain critical issues. In this article, we introduce a surprisingly simple, interpretable, and efficient method for the estimation of compositional data regression through the lens of a novel high-dimensional log-error-in-variable regression model. The proposed method provides both corrections on sequencing data with possible overdispersion and simultaneously avoids any subjective imputation of zero read counts. We provide theoretical justifications with matching upper and lower bounds for the estimation error. We also consider a general log-error-in-variable regression model with corresponding estimation method to accommodate broader situations. The merit of the procedure is illustrated through real data analysis and simulation studies

An approach to the study of microsaccades during reading using wavelets

Reading requires the integration of several central cognitive subsystems from attention and oculomotor control to word identification and language comprehension. When reading, the eyes alternate between long movements and relative stillness, that are called saccadic movements and fixations, respectively. The average fixation lasts for 150 to 250 ms and it is composed by three movements called microsaccades (or microsaccadic movements), tremor and drift. Drift and tremor are slow movements with small amplitude; microsaccades represent a ballistic component of fixational eye movements. Then, microsaccades are characterized as roughly linear movement epochs with durations up to 30ms and a frequency of one to two per second in fixations not related with reading. There are just a few works analyzing microsaccades while subjects are processing complex information and fewer when doing predictions about upcoming events. In all of them there is evidence that microsaccades are sensitive to changes of perceptual inputs as well as modulations of cognitive states. Changes in perceptual inputs are related to the type of sentences (low/high predictability, proverbs) and the characteristics of the words in the sentence (frequency, predictability, length, etc.). Let us recall the definition of maxjump: it is the word with the largest difference between the cloze predictability of two consecutive words. Then, in this work we present a first analysis of the energy of the wavelet coefficients of microsaccades during reading proverbs and low predictability sentences on words before maxjump, during maxjump and words after maxjump. The idea of this approach is to try to characterize its behavior along each one of those set of words in order to have another tool for evaluating microsaccades during reading sentences with different contextual predictability since this might provide information about specific effect of cue attention on complex task.Publicado en: Mecánica Computacional vol. XXXV, no. 43Facultad de Ingenierí