Search results for " artificial intelligence"
showing 10 items of 1992 documents
An analysis of the bias of variation operators of estimation of distribution programming
2018
Estimation of distribution programming (EDP) replaces standard GP variation operators with sampling from a learned probability model. To ensure a minimum amount of variation in a population, EDP adds random noise to the probabilities of random variables. This paper studies the bias of EDP's variation operator by performing random walks. The results indicate that the complexity of the EDP model is high since the model is overfitting the parent solutions when no additional noise is being used. Adding only a low amount of noise leads to a strong bias towards small trees. The bias gets stronger with an increased amount of noise. Our findings do not support the hypothesis that sampling drift is …
Thermographic quantitative variables for diabetic foot assessment: preliminary results
2018
The aim of this study was to define aspects of a protocol for a diabetic population by obtaining and evaluating thermographic images following thermal stress (cooling of the sole of the foot with c...
Classification of Solutions to the Minimum Energy Problem in One Dimensional Sensor Networks
2016
We classify of the minimum energy problem in one dimensional wireless sensor networks for the data transmission cost matrix which is a power function of the distance between transmitter and receiver with any real exponent. We show, how these solutions can be utilized to solve the minimum energy problem for the data transmission cost matrix which is a linear combination of two power functions. We define the minimum energy problem in terms of the sensors signal power, transmission time and capacities of transmission channels. We prove, that for the point-to-point data transmission method utilized by the sensors in the physical layer, when the transmitter adjust the power of its radio signal t…
Towards Ethical Guidelines of Using Telepresence Robots in Residential Care
2021
AbstractRobotic telepresence is a potential technology to help alleviating the loneliness of elderly people. The impacts of long-term use of telepresence robots in residential care are not well known. We were interested in how using a telepresence robot influences the resident, family members and care workers at a facility, and what challenges and solutions there are for wider adoption of such robots in residential care. With a telepresence robot Double, we arranged a series of three trials in two separate residential care facilities: one 12-week trial in a private facility and two successive 6-week trials in a public facility. In each trial, we installed the telepresence robot in a room of…
Revista electrónica de investigación y evaluación educativa
2017
Resumen basado en el de la publicación Título, resumen y palabras clave en español e inglés Disponible la versión en inglés El objetivo es analizar el proyecto de nuevo cuestionario diseñado por la Universidad del País Vasco (UPV/EHU) para realizar la evaluación de sus docentes (SET). Se analizan las respuestas de una muestra de 941 estudiantes y se estudia la fiabilidad del cuestionario, la dimensionalidad, la validez de constructo y criterial, finalizando con un estudio diferencial tomando en cuenta variables como el género, el campo disciplinar, el nivel percibido de dificultad o el interés de las materias. Los resultados permiten afirmar que se trata de un instrumento de alta consistenc…
Movement Detection with Event-Based Cameras: Comparison with Frame-Based Cameras in Robot Object Tracking Using Powerlink Communication
2018
Event-based cameras are not common in industrial applications despite the fact that they can add multiple advantages for applications with moving objects. In comparison with frame-based cameras, the amount of generated data is very low while keeping the main information in the scene. For an industrial environment with interconnected systems, data reduction becomes very important to avoid network congestion and provide faster response time. However, the use of new sensors as event-based cameras is not common since they do not usually provide connectivity to industrial buses. This work develops a network node based on a Field Programmable Gate Array (FPGA), including data acquisition and trac…
Balanced Large Scale Knowledge Matching Using LSH Forest
2015
Evolving Knowledge Ecosystems were proposed recently to approach the Big Data challenge, following the hypothesis that knowledge evolves in a way similar to biological systems. Therefore, the inner working of the knowledge ecosystem can be spotted from natural evolution. An evolving knowledge ecosystem consists of Knowledge Organisms, which form a representation of the knowledge, and the environment in which they reside. The environment consists of contexts, which are composed of so-called knowledge tokens. These tokens are ontological fragments extracted from information tokens, in turn, which originate from the streams of information flowing into the ecosystem. In this article we investig…
Comparison of feature importance measures as explanations for classification models
2021
AbstractExplainable artificial intelligence is an emerging research direction helping the user or developer of machine learning models understand why models behave the way they do. The most popular explanation technique is feature importance. However, there are several different approaches how feature importances are being measured, most notably global and local. In this study we compare different feature importance measures using both linear (logistic regression with L1 penalization) and non-linear (random forest) methods and local interpretable model-agnostic explanations on top of them. These methods are applied to two datasets from the medical domain, the openly available breast cancer …
A Curvature Based Method for Blind Mesh Visual Quality Assessment Using a General Regression Neural Network
2016
International audience; No-reference quality assessment is a challenging issue due to the non-existence of any information related to the reference and the unknown distortion type. The main goal is to design a computational method to objectively predict the human perceived quality of a distorted mesh and deal with the practical situation when the reference is not available. In this work, we design a no reference method that relies on the general regression neural network (GRNN). Our network is trained using the mean curvature which is an important perceptual feature representing the visual aspect of a 3D mesh. Relatively to the human subjective scores, the trained network successfully asses…
Claves vertebradoras del modelo de justicia en el siglo XXI
2021
The 21st Century presents a dynamic, international, digital, changing, agile, and fast Society, that demands an adequated Justice System. The Incorporation due to Globalization of Keys such a Supranationality, Internationalization, Efficiency, Feminization, Technology, Algorithms and Artificial Intelligence, are involved in the changes of the new look of Justice.