Search results for "Software"
showing 10 items of 7396 documents
Evolutionary approach to coverage testing of IEC 61499 function block applications
2015
The paper addresses the problem of coverage testing of industrial automation software represented in the IEC 61499 standard, one of the recent standards for distributed control system design. Contrary to model-based testing (MBT), the paper focuses on implementation coverage, not model coverage. An approach based on evolutionary algorithms is presented which generates coverage test suites for both basic and composite IEC 61499 function blocks. It employs two third-party tools, FBDK and EvoSuite. The evaluation of the approach was performed on a set of control applications for two lab-scale demonstration plants. Results show that the approach is applicable and shows good performance at least…
On the use of LSPIV-based free software programs for the monitoring of river: testing the PIVlab and the FUDAA-LSPIV with synthetic and real image se…
2020
<p>The development of new image-based techniques is allowing a radical change in the environmental monitoring field. The fundamental characteristics of these methods are related to the possibility of obtaining non-intrusive measurements even in adverse circumstances, such as high flow conditions, which may seriously threaten the operators’ safety conditions in traditional approaches.</p><p>Optical techniques, based on the acquisition, analysis and elaboration of sequences of images acquired by digital cameras, are aimed at a complete characterization of the river instantaneous surface velocity field, through the analysis of a floating…
Feature extraction from remote sensing data using Kernel Orthonormalized PLS
2007
This paper presents the study of a sparse kernel-based method for non-linear feature extraction in the context of remote sensing classification and regression problems. The so-called kernel orthonormalized PLS algorithm with reduced complexity (rKOPLS) has two core parts: (i) a kernel version of OPLS (called KOPLS), and (ii) a sparse (reduced) approximation for large scale data sets, which ultimately leads to rKOPLS. The method demonstrates good capabilities in terms of expressive power of the extracted features and scalability.
Correlation-Based and Contextual Merit-Based Ensemble Feature Selection
2001
Recent research has proved the benefits of using an ensemble of diverse and accurate base classifiers for classification problems. In this paper the focus is on producing diverse ensembles with the aid of three feature selection heuristics based on two approaches: correlation and contextual merit -based ones. We have developed an algorithm and experimented with it to evaluate and compare the three feature selection heuristics on ten data sets from UCI Repository. On average, simple correlation-based ensemble has the superiority in accuracy. The contextual merit -based heuristics seem to include too many features in the initial ensembles and iterations were most successful with it.
Distance-based relevance feedback using a hybrid interactive genetic algorithm for image retrieval
2011
Content-based image retrieval (CBIR) systems aim to provide a means to find pictures in large repositories without using any other information except the own content of the images, which is usually represented as a feature vector extracted from low-level descriptors. This paper describes a CBIR algorithm which combines relevance feedback, evolutionary computation concepts and distance-based learning in an attempt to reduce the existing gap between the high level semantic content of the images and the information provided by their low-level descriptors. In particular, a framework which is independent from the particular features used is presented. The effect of different crossover strategies…
Local dimensionality reduction within natural clusters for medical data analysis
2005
Inductive learning systems have been successfully applied in a number of medical domains. Nevertheless, the effective use of these systems requires data preprocessing before applying a learning algorithm. Especially it is important for multidimensional heterogeneous data, presented by a large number of features of different types. Dimensionality reduction is one commonly applied approach. The goal of this paper is to study the impact of natural clustering on dimensionality reduction for classification. We compare several data mining strategies that apply dimensionality reduction by means of feature extraction or feature selection for subsequent classification. We show experimentally on micr…
Extracting information from support vector machines for pattern-based classification
2014
Statistical machine learning algorithms building on patterns found by pattern mining algorithms have to cope with large solution sets and thus the high dimensionality of the feature space. Vice versa, pattern mining algorithms are frequently applied to irrelevant instances, thus causing noise in the output. Solution sets of pattern mining algorithms also typically grow with increasing input datasets. The paper proposes an approach to overcome these limitations. The approach extracts information from trained support vector machines, in particular their support vectors and their relevance according to their coefficients. It uses the support vectors along with their coefficients as input to pa…
Improving distance based image retrieval using non-dominated sorting genetic algorithm
2015
Image retrieval is formulated as a multiobjective optimization problem.A multiobjective genetic algorithm is hybridized with distance based search.A parameter balances exploration (genetic search) or exploitation (nearest neighbors).Extensive comparative experimentation illustrate and assess the proposed methodology. Relevance feedback has been adopted as a standard in Content Based Image Retrieval (CBIR). One major difficulty that algorithms have to face is to achieve and adequate balance between the exploitation of already known areas of interest and the exploration of the feature space to find other relevant areas. In this paper, we evaluate different ways to combine two existing relevan…
The Expressibility of Languages and Relations by Word Equations
1997
Classically, several properties and relations of words, such as being a power of a same word, can be expressed by using word equations. This paper is devoted to study in general the expressive power of word equations. As main results we prove theorems which allow us to show that certain properties of words are not expressible as components of solutions of word equations. In particular, the primitiveness and the equal length are such properties, as well as being any word over a proper subalphabet.
Pico: A data acquisition program for picosecond laser spectroscopy
1992
Abstract A data acquisition and control program for picosecond pump and probe experiments has been developed. The program PICO is written in C-programming language for maximum efficiency. The software which runs on an IBM PC compatible microcomputer controls a stepper motor driven optical delay, and at the same time collects data from a digital lock-in amplifier. PICO can be used to control any experiment utilizing two-beam pump probe technique. The modular structure of the software allows for easy implementation with different hardware configurations. The program includes: measurement option, manual control of the delay line using a joystick and functions for file retrieval and editing. Ad…