Search results for "Processi"
showing 10 items of 9638 documents
The Use of Latent Semantic Analysis in the Positive Psychology: A Comparison with Twitter Posts
2017
In the last decade, the positive psychology and specifically the 'Positive Youth Development' (PYD) give efforts to positive aspect and strength that performance as protective factors of adjustment problems and psycho-social well-being, such as courage. To better understand the definition of courage in Italian context, 1199 participants were involved in the present study and we asked them to answer to the following question "Courage is...". The participant's definitions of courage were analyzed with the Latent Semantic Analysis (LSA), in order to study the "fundamental concepts" arising from the population. An analogous comparison with Twitter posts has been also carried out.
An adaption mechanism for the error threshold of XCSF
2020
Learning Classifier System (LCS) is a class of rule-based learning algorithms, which combine reinforcement learning (RL) and genetic algorithm (GA) techniques to evolve a population of classifiers. The most prominent example is XCS, for which many variants have been proposed in the past, including XCSF for function approximation. Although XCSF is a promising candidate for supporting autonomy in computing systems, it still must undergo parameter optimization prior to deployment. However, in case the later deployment environment is unknown, a-priori parameter optimization is not possible, raising the need for XCSF to automatically determine suitable parameter values at run-time. One of the mo…
Population and Query Interface for a Content-Based Video Database
2002
In this paper we describe the first full implementation of a content-based indexing and retrieval system for MPEG-2 and MPEG-4 videos. We consider a video as a collection of spatiotemporal segments called video objects; each video object is a sequence of video object planes. A set of representative video object planes is used to index each video object. During the database population, the operator, using a semi-automatic outlining tool we developed, manually selects video objects and insert some semantical information. Low-level visual features like color, texture, motion and geometry are automatically computed. The system has been implemented on a commercial relational DBMS and is based on…
Cognitive and neuropsychological profiles of the elderly
1993
Testing the cognitive functions of the elderly is often eclectic and atheoretical. We take a theoretical model, simultaneous and successive processing, and the tests derived from it to describe the cognitive functions of the elderly. Subsequently, the performance of an elderly sample on a battery of neuropsychological tests is examined and also understood in relation to the two processing modes. Subjects were 81 individuals, 75 years old, from a population of nearly 300 persons participating in a Finnish research project on aging. They were administered tests of simultaneous and successive processing as well as an extensive battery of neuropsychological tasks. Multivariate and univariate an…
Smartphone data analysis for human activity recognition
2017
In recent years, the percentage of the population owning a smartphone has increased significantly. These devices provide the user with more and more functions, so that anyone is encouraged to carry one during the day, implicitly producing that can be analysed to infer knowledge of the userâs context. In this work we present a novel framework for Human Activity Recognition (HAR) using smartphone data captured by means of embedded triaxial accelerometer and gyroscope sensors. Some statistics over the captured sensor data are computed to model each activity, then real-time classification is performed by means of an efficient supervised learning technique. The system we propose also adopts a …
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 …
Scratch detection and removal from static images using simple statistics and genetic algorithms
2002
This paper investigates the removal of line scratches from old movies and gives a twofold contribution. First, it presents simple technique for detecting the scratches, based on an analysis of the statistics of the grey levels. Second, the scratch removal is approached as an optimisation problem, and it is solved by using a genetic algorithm. The method can be classified as a static approach, as it works independently on each single frame of the sequence. It does not require any a-priori knowledge of the absolute position of the scratch, nor an external starting population of chromosomes for the genetic algorithm. The central column of the line scratch once detected is changed with a conven…
A Method Based on Multi-source Feature Detection for Counting People in Crowded Areas
2019
We propose a crowd counting method for multisource feature fusion. Image features are extracted from multiple sources, and the population is estimated by image feature extraction and texture feature analysis, along with for crowd image edge detection. We count people in high-density still images. For instance, in the city’s squares, sports fields, subway stations, etc. Our approach uses a still image taken by a camera on a drone to appraise the count in the population density image, using a kind of sources of information: HOG, LBP, CANNY. We furnish separate estimates of counts and other statistical measurements through several types of sources. Support vector machine SVM, classification an…
Shared feature representations of LiDAR and optical images: Trading sparsity for semantic discrimination
2015
This paper studies the level of complementary information conveyed by extremely high resolution LiDAR and optical images. We pursue this goal following an indirect approach via unsupervised spatial-spectral feature extraction. We used a recently presented unsupervised convolutional neural network trained to enforce both population and lifetime spar-sity in the feature representation. We derived independent and joint feature representations, and analyzed the sparsity scores and the discriminative power. Interestingly, the obtained results revealed that the RGB+LiDAR representation is no longer sparse, and the derived basis functions merge color and elevation yielding a set of more expressive…
3D inter-subject medical image registration by scatter search
2005
Image registration is a very active research area in computer vision, namely it is used to find a transformation between two images taken under different conditions. Point matching is an image registration approach based on searching for the right pairing of points between the two images. From this matching, the registration transformation we are searching, can be inferred by means of numerical methods. In this paper, we propose a scatter search (SS) algorithm to solve the matching problem. SS is a hybrid metaheuristic with a good trade-off between search space diversification and intensification. On the one hand, diversity is basically introduced from a population-based approach where syst…