Search results for "computer.software_genre"
showing 10 items of 3858 documents
<title>Distance functions in dynamic integration of data mining techniques</title>
2000
One of the most important directions in the improvement of data mining and knowledge discovery is the integration of multiple data mining techniques. An integration method needs to be able either to evaluate and select the most appropriate data mining technique or to combine two or more techniques efficiently. A recent integration method for the dynamic integration of multiple data mining techniques is based on the assumption that each of the data mining techniques is the best one inside a certain subarea of the whole domain area. This method uses an instance-based learning approach to collect information about the competence areas of the mining techniques and applies a distance function to…
F.A.L.C.A.D.E.: a fuzzy software for the energy and environmental balances of products
2004
Abstract It is generally well known that the reliability of Life Cycle Analysis (LCA) studies depends upon exact, complete and sharp input data that, unfortunately, are not always available. Furthermore, when available, the input data are affected by uncertainty whose importance is not always adequately taken into consideration. This paper describes the software F.A.L.C.A.D.E. (Fuzzy Approach to Life Cycle Analysis and Decision Environment): a tool designed for the calculation of the eco-profile of products, based on a fuzzy logic approach. The originality of the method already treated in other papers is to use the fuzzy representation to manage the complex relationships that arise in compi…
Machine Learning Methods for Spatial and Temporal Parameter Estimation
2020
Monitoring vegetation with satellite remote sensing is of paramount relevance to understand the status and health of our planet. Accurate and constant monitoring of the biosphere has large societal, economical, and environmental implications, given the increasing demand of biofuels and food by the world population. The current democratization of machine learning, big data, and high processing capabilities allow us to take such endeavor in a decisive manner. This chapter proposes three novel machine learning approaches to exploit spatial, temporal, multi-sensor, and large-scale data characteristics. We show (1) the application of multi-output Gaussian processes for gap-filling time series of…
The University of Valencia’s computerized word pool
1988
This paper presents the University of Valencia’s computerized word pool. This is a database that includes 16,109 Spanish words, together with 11 psychological variables for limited groups of items. The purpose behind the creation of this database was to have available a large quantity of verbal stimuli in a well-controlled system, ready for automatic selection. The description includes a summary of statistics on each of the 11 psychological variables, together with a correlational and factor analysis of them. This statistical analysis produces results close to those obtained for equivalent English material.
Computerunterstützte Diagnostik in der Thoraxradiologie - aktuelle Schwerpunkte und Techniken
2003
The proliferation of digital data sets and the increasing amount of images, e. g. through the use of multislice spiral CT or multiple follow-up examinations in the context of new therapies, are ideal prerequisites for computer-aided diagnosis (CAD) in chest radiology. Multiple studies have described the applications and advantages of computer assistance in performing different diagnostic tasks. More powerful computers will enable the introduction of these systems into the clinical routine and could provide an enormous increase in morphological and functional information. The commercial introduction of tools for detection and visualization of pulmonary nodules has already begun. This is one …
Semisupervised Kernel Feature Extraction for Remote Sensing Image Analysis
2014
This paper presents a novel semisupervised kernel partial least squares (KPLS) algorithm for nonlinear feature extraction to tackle both land-cover classification and biophysical parameter retrieval problems. The proposed method finds projections of the original input data that align with the target variable (labels) and incorporates the wealth of unlabeled information to deal with low-sized or underrepresented data sets. The method relies on combining two kernel functions: the standard radial-basis-function kernel based on labeled information and a generative, i.e., probabilistic, kernel directly learned by clustering the data many times and at different scales across the data manifold. Th…
Implementation of a PLC Field Analyzer on a G3 Modem Platform
2021
Nowadays, power line communications (PLC) are a widely used technology in distribution grids, both for automatic meter reading and automation applications. PLC performances (in terms of capacity, coverage, robustness, and data transmission rate) can be significantly affected by electrical network topologies, connected loads and disturbances. Thus, utilities and modem manufacturers are increasing their interest in electrical network characterization. In this framework, a software tool is proposed in this paper to measure received signal and noise levels. As case study, it is implemented on a G3 PLC transceiver, widely used for smart metering purposes. In this way, a PLC channel characterizat…
Some applications of a theorem of Shirshov to language theory
1983
Some applications of a theorem of Shirshov to language theory are given: characterization of regular languages, characterization of bounded languages, and a sufficient condition for a language to be Parikh-bounded.
A generalizability measure for program synthesis with genetic programming
2021
The generalizability of programs synthesized by genetic programming (GP) to unseen test cases is one of the main challenges of GP-based program synthesis. Recent work showed that increasing the amount of training data improves the generalizability of the programs synthesized by GP. However, generating training data is usually an expensive task as the output value for every training case must be calculated manually by the user. Therefore, this work suggests an approximation of the expected generalization ability of solution candidates found by GP. To obtain candidate solutions that all solve the training cases, but are structurally different, a GP run is not stopped after the first solution …
Adaptation of a German Multidimensional Networking Scale into English
2011
Networking refers to building and maintaining personal contacts in order to obtain resources that, in turn, enhance one’s career success and work performance. This study reports the translation and adaptation of a multifaceted German networking scale ( Wolff & Moser, 2006 ) into English and focuses on the equivalence of the two language versions. Going beyond the often used translation-backtranslation method, we used a parallel translation-backtranslation method in combination with two expert committees to arrive at the English scale version, aiming to obtain at least structural equivalence. We utilize a bilingual sample (N = 76) as well as monolingual samples from the US (N = 174) and…