Search results for " mining"
showing 10 items of 1548 documents
Neural networks with non-uniform embedding and explicit validation phase to assess Granger causality
2015
A challenging problem when studying a dynamical system is to find the interdependencies among its individual components. Several algorithms have been proposed to detect directed dynamical influences between time series. Two of the most used approaches are a model-free one (transfer entropy) and a model-based one (Granger causality). Several pitfalls are related to the presence or absence of assumptions in modeling the relevant features of the data. We tried to overcome those pitfalls using a neural network approach in which a model is built without any a priori assumptions. In this sense this method can be seen as a bridge between model-free and model-based approaches. The experiments perfo…
Panel Summary: Knowledge Model Representations
1997
Following the usual classifications of cognitive psychologists, we can say that the problem of representation spans three domains: the environment, the brain, and cognitive processes, which are usually studied by different scientists: the physicists, the neurobiologists and the psychologists. With the development of computer science and artificial intelligence new approaches have been introduced, which make possible simulation and implementation of cognitive processes through neural networks and symbolic systems. But the contribution of new methods is not limited to simulation, because they try to provide new models which consider cognitive process as information processing, not as reaction…
A framework to identify primitives that represent usability within Model-Driven Development methods
2014
Context: Nowadays, there are sound methods and tools which implement the Model-Driven Development approach (MDD) satisfactorily. However, MDD approaches focus on representing and generating code that represents functionality, behaviour and persistence, putting the interaction, and more specifically the usability, in a second place. If we aim to include usability features in a system developed with a MDD tool, we need to extend manually the generated code. Objective: This paper tackles how to include functional usability features (usability recommendations strongly related to system functionality) in MDD through conceptual primitives. Method: The approach consists of studying usability guide…
A Proposal for Modelling Usability in a Holistic MDD Method
2014
Holistic methods for Model-Driven Development (MDD) aim to model all the system features in a conceptual model. This conceptual model is the input for a model compiler that can generate software systems by means of automatic transformations. However, in general, MDD methods focus on modelling the structure and functionality of systems, relegating the interaction and usability features to manual implementations at the last steps of the software development process. Some usability features are strongly related to the functionality of the system and their inclusion is not so easy. In order to facilitate the inclusion of functional usability features from the first steps of the development proc…
Compaction of Open-Graded HMAs Evaluated by a Fuzzy Clustering Technique
2015
The aim of this paper is the proposal of an expeditious procedure to be used during the execution of an asphalt layer for improving the compaction task. This procedure, based on a fuzzy clustering technique, starts from the knowledge of some information recorded by ordinary measuring instruments and provides an aid to the decision-maker on the number of roller passes needed to achieve a specific density at a certain temperature. This result can be deduced with great rapidity during the paving operations on site without waiting for the time spent in the core extraction and in the subsequent laboratory analysis. In this way it is possible to identify more precisely which aspects of the execut…
On the Online Classification of Data Streams Using Weak Estimators
2016
In this paper, we propose a novel online classifier for complex data streams which are generated from non-stationary stochastic properties. Instead of using a single training model and counters to keep important data statistics, the introduced online classifier scheme provides a real-time self-adjusting learning model. The learning model utilizes the multiplication-based update algorithm of the Stochastic Learning Weak Estimator (SLWE) at each time instant as a new labeled instance arrives. In this way, the data statistics are updated every time a new element is inserted, without requiring that we have to rebuild its model when changes occur in the data distributions. Finally, and most impo…
Local operators to detect regions of interest
1997
The performance of a visual system is strongly influenced by the information processing that is done in the early vision phase. The need exists to limit the computation on areas of interest to reduce the total amount of data and their redundancy. This paper describes a new method to drive the attention during the analysis of complex scenes. Two new local operators, based on the computation of local moments and symmetries, are combined to drive the selection. Experimental results on real data are also reported. © 1997 Elsevier Science B.V.
The windowed scalogram difference: A novel wavelet tool for comparing time series
2017
Abstract We introduce a new wavelet-based tool called windowed scalogram difference (WSD), which has been designed to compare time series. This tool allows quantifying if two time series follow a similar pattern over time, comparing their scalograms and determining if they give the same weight to the different scales. The WSD can be seen as an alternative to another tool widely used in wavelet analysis called wavelet squared coherence (WSC) and, in some cases, it detects features that the WSC is not able to identify. As an application, the WSD is used to examine the dynamics of the integration of government bond markets in the euro area since the inception of the euro as a European single c…
Moving Learning Machine Towards Fast Real-Time Applications: A High-Speed FPGA-based Implementation of the OS-ELM Training Algorithm
2018
Currently, there are some emerging online learning applications handling data streams in real-time. The On-line Sequential Extreme Learning Machine (OS-ELM) has been successfully used in real-time condition prediction applications because of its good generalization performance at an extreme learning speed, but the number of trainings by a second (training frequency) achieved in these continuous learning applications has to be further reduced. This paper proposes a performance-optimized implementation of the OS-ELM training algorithm when it is applied to real-time applications. In this case, the natural way of feeding the training of the neural network is one-by-one, i.e., training the neur…
Locally constrained synthetic LoDs generation for natural terrain meshes
2004
Terrain representation is a basic topic in the field of interactive graphics. The amount of data required for a good quality of the terrain offers an important challenge to developers of such systems. For users of these applications, the accuracy of geographical data is generally less important than its natural visual appearance. This makes it possible to maintain a limited geographical database for the system and to extend it generating synthetic data. The evaluation of the intrinsic properties of the terrain (i.e. fractal dimension, roughness, etc.) may be used as the basis for generating extra data accomplishing the same patterns discovered in the actual information. However, it is also …