Search results for "artificial intelligence"

Attention-based environment perception in autonomous robotics

2007

This paper describes a robotic architecture that uses visual attention mechanisms for autonomous navigation in unknown indoor environments. A foveation mechanism based on classical bottom-up gaze shifts allows the robot to autonomously select landmarks, defined as salient points in the camera images. Landmarks are memorized in a behavioral fashion, coupling sensing and acting to achieve a representation view and scale independent. Selected landmarks are stored in a topological map; during the navigation a top-down mechanism controls the attention system to achieve robot localization. Experiments and results show that our system is robust to noise and odometric errors, being at the same time…

Editorial: Robot-Assisted Learning and Education

2020

EMERGING RESEARCH MILESTONES FOR SOCIAL SCIENCES IN A SMART SOCIETY

2019

Scientific and technological development goes hand in hand and has always sustained mankind, being the sources of a better living for humans. Until recent years, people were the ones that coordinated and maneuvered machines or production chains, used telephones or droved cars, which only operated as tools, according to their handlers will. This scenario is nowadays less obvious, and devices are currently less subordinated to man manipulation. They become smart, record and share information, decide to act or communicate, simulating human behavior, independent from a human decider. All the above-mentioned issues are considered facets of the Fourth Industrial Revolution, as defined by the lead…

Fortalezas y debilidades de la mediación escolar desde la perspectiva del alumnado de educación secundaria

2016

In this paper we present a study to know the valuation of school mediation as an educational strategy taking into account the views of students in five schools in secondary Valencia, where the formal mediation process has been active for at least two years. It also seeks to identify the strengths and weaknesses identified.To achieve the objectives it has collected information from 593 students through an ad hoc difference between issues that all students must answer questionnaire; questions addressed only the students who have gone to mediation service; and finally issues to respond only the students who have acted as mediators.Through descriptive exploratory study conducted, is highlighted…

Requirements Model of Sociotechnical Systems Simulator Architecture

2017

To avoid any voluntary decisions it is desirable to examine the possible consequences that can be done by simulation. Unfortunately there is no unified methodology and technology for simulators designing. Above mentioned problem when development of each simulator has to be started from the scratches makes elaboration expensive and cumbersome. The article dealt with the way to joint understanding of simulators designing concept.

Fuzzy Degree of Geographic Appropriateness for Social Impact Investing

2017

Impact investing is an investment practice that is characterized by the explicit intentionality of attaining a social impact and the requisite of report and measure this impact in a transparent way. The investment decision making process has two main stages. In the first stage, filters are applied regarding four critical issues: target geography, impact theme, asset class and target return category. In this phase, the set of possible investment alternatives are determined based on their appropriateness for impact investment in terms of those four essential aspects. In a second stage, efficient portfolios are obtained taking into account financial criteria (maximizing expected return, minimi…

Performance evaluation of fuzzy-neural HTTP request distribution for Web clusters

2006

In this paper we present the performance evaluation of our fuzzy-neural HTTP request distribution algorithm called FNRD, which assigns each incoming request to the server in the Web cluster with the quickest expected response time. The fuzzy mechanism is used to estimate the expected response times. A neural-based feedback loop is used for real-time tuning of response time estimates. To evaluate the system, we have developed a detailed simulation and workload model using CSIM19 package. Our simulations show that FNRD can be more effective than its competitors.

RANKING DECISION MAKING UNITS BY MEANS OF SOFT COMPUTING DEA MODELS

2011

This paper presents a method for ranking a set of decision making units according to their level of efficiency and which takes into account uncertainty in the data. Efficiency is analysed using fuzzy DEA techniques and the ranking is based on the statistical analysis of cases that include representative situations. The method enables the removal of the sometimes unrealistic hypothesis of a perfect trade-off between increased inputs and outputs. This model is compared with other DEA models that work with imprecise or fuzzy data. As an illustration, we apply our ranking method to the evaluation of a group of Spanish seaports, as well as teams playing in the Spanish football league. We compar…

A Memetic Island Model for Discrete Tomography Reconstruction

2011

Soft computing is a term indicating a coalition of methodologies, and its basic dogma is that, in general, better results can be obtained through the use of constituent methodologies in combination, rather than in a stand alone mode. Evolutionary computing belongs to this coalition, and thus memetic algorithms. Here, we present a combination of several instances of a recently proposed memetic algorithm for discrete tomography reconstruction, based on the island model parallel implementation. The combination is motivated by the fact that, even though the results of the recently proposed approach are finally better and more robust compared to other approaches, we advised that its major drawba…

Artificial Vision and Soft Computing

1999

The term soft-computing has been introduced by Zadeh in 1994. Soft-computing provides an appropriate paradigm to program malleable and smooth concepts. For example, it can be used to introduce flexibility in artificial systems to improve their Intelligent Quotient. The aim of this paper is to describe the applicability of soft-computing to artificial vision problems. Good performance of this approach is assured by the fact that digital images are examples of fuzzy entities, where shapes are not always describable by exact equations and their approximation can be very complex.