Search results for "Learning"
showing 10 items of 6669 documents
Ant Colony Models for a Virtual Educational Environment Based on a Multi-Agent System
2008
We have designed a virtual learning environment where students interact through their computers and with the software agents in order to achieve a common educational goal. The Multi-Agent System (MAS) consisting of autonomous, cognitive and social agents communicating by messages is used to provide a group decision support system for the learning environment. Learning objects are distributed in a network and have different weights in function of their relevance to a specific educational goal. The relevance of a learning object can change in time; it is affected by students', agents' and teachers' evaluation. We have used an ant colony behavior model for the agents that play the role of a tu…
Emotional Business Intelligence
2014
The domain of Emotional Business Intelligence (EBI) aims to support business-relevant emotional and emotion-aware decisions in addition to rational decision making. EBI originates from three root domains: Emotional Business, Emotional Intelligence and Business Intelligence (BI). In this paper we emphasize emotional empowerment of the traditional BI function; outline its main characteristics as a business working model of an emotionally smart, continuously learning organization; and introduce a first candidate of the EBI Toolkit, the FeelingsExplorer (FE). FE is a mash-up browser based on 4i (“ForEye”) technology, capable of visualizing objects in an emotional semantic space and thereby supp…
Deep Learning Techniques for Depression Assessment
2018
Depression is a typical mood disorder, which affects a significant number of individuals worldwide at an increasing rate. Objective measures for early detection of signs related to depression could be beneficial for clinicians with regards to a decision support system. In this paper, assessment of depression is done by applying three deep learning techniques of Convolutional Neural Network (CNN). These techniques are transfer learning using AlexNet, fine-tuning using AlexNet and building an end to end CNN. The inputs of the CNNs are a combination of Motion History Image, Landmark Motion History Image and Gabor Motion History Image, and have been generated on a depression dataset. Accuracy o…
Big Data as a Driver for Clinical Decision Support Systems: A Learning Health Systems Perspective
2018
Big data technologies are nowadays providing health care with powerful instruments to gather and analyze large volumes of heterogeneous data collected for different purposes, including clinical care, administration, and research. This makes possible to design IT infrastructures that favor the implementation of the so-called “Learning Healthcare System Cycle,” where healthcare practice and research are part of a unique and synergic process. In this paper we highlight how “Big Data enabled” integrated data collections may support clinical decision-making together with biomedical research. Two effective implementations are reported, concerning decision support in Diabetes and in Inherited Arrh…
Feature extraction for classification in knowledge discovery systems
2003
Dimensionality reduction is a very important step in the data mining process. In this paper, we consider feature extraction for classification tasks as a technique to overcome problems occurring because of "the curse of dimensionality". We consider three different eigenvector-based feature extraction approaches for classification. The summary of obtained results concerning the accuracy of classification schemes is presented and the issue of search for the most appropriate feature extraction method for a given data set is considered. A decision support system to aid in the integration of the feature extraction and classification processes is proposed. The goals and requirements set for the d…
A fuzzy decision support tool for demand forecasting
2007
In this paper we present a decision support forecasting system to work with univariate time series based on the generalized exponential smoothing (Holt-Winters) approach. It is conceived as an integrated tool which has been implemented in Visual Basic. For improving the accuracy of the automatic forecasting it uses an optimization-based scheme which unifies the stages of estimation of the parameters and selects the best method using a fuzzy multicriteria approach. The elements of the set of local minima of the non-linear programming problems allow us to build the membership functions of the conflicting objectives. A set of real data is analyzed to show the performance of our forecasting too…
Viabilidad de la informatización del examen lengua extranjera de las Pruebas de Acceso a la Universidad
2016
[ES] Tras el anuncio por parte del Gobierno de la inclusión de una sección oral en el examen de lengua extranjera de la Prueba de Acceso a la Universidad, que estaba prevista para 2012, diferentes posibilidades en cuanto a la informatización de dicha sección se analizaron en un esfuerzo por encontrar una propuesta viable para la evaluación de las destrezas orales y un estudio cualitativo se llevó a cabo con 286 participantes. Los resultados arrojaron luz en cuanto a la recepción inicial de las soluciones tecnológicas desarrolladas dentro de un sistema de gestión del aprendizaje y en cuanto a la viabilidad de la informatización de la sección oral de la prueba, mostrando que es posible implan…
A Simple and Efficient Deep Learning-Based Framework for Automatic Fruit Recognition
2022
Accurate detection and recognition of various kinds of fruits and vegetables by using the artificial intelligence (AI) approach always remain a challenging task due to similarity between various types of fruits and challenging environments such as lighting and background variations. Therefore, developing and exploring an expert system for automatic fruits’ recognition is getting more and more important after many successful approaches; however, this technology is still far from being mature. The deep learning-based models have emerged as state-of-the-art techniques for image segmentation and classification and have a lot of promise in challenging domains such as agriculture, where they can …
Semantic Analysis of the Driving Environment in Urban Scenarios
2021
Understanding urban scenes require recognizing the semantic constituents of a scene and the complex interactions between them. In this work, we explore and provide effective representations for understanding urban scenes based on in situ perception, which can be helpful for planning and decision-making in various complex urban environments and under a variety of environmental conditions. We first present a taxonomy of deep learning methods in the area of semantic segmentation, the most studied topic in the literature for understanding urban driving scenes. The methods are categorized based on their architectural structure and further elaborated with a discussion of their advantages, possibl…
Compréhension de scènes urbaines basées sur la polarisation
2021
Humans possess an innate ability to interpret scenes under any condition. Computer Vision tends to mimic these capabilities by implementing intelligent algorithms to address complex understanding problems. In this regard, we are interested in understanding outdoor urban scenes in various weather conditions. This thesis specifically addresses the problems arising from the presence of specularity in the scenes. To this end, we aim to take advantage of polarization indices to define such surfaces in addition to traditional objects. In terms of understanding, we aim to introduce polarization to the fields of computer vision and deep learning.This thesis focuses on the following underlying challeng…