Search results for "Data mining"
showing 10 items of 907 documents
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…
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 …
Using an Adaptive Network-based Fuzzy Inference System to Estimate the Vertical Force in Single Point Incremental Forming
2019
Manufacturing processes are usually complex ones, involving a significant number of parameters. Unconventional manufacturing processes, such as incremental forming is even more complex, and the establishment of some analytical relationships between parameters is difficult, largely due to the nonlinearities in the process. To overcome this drawback, artificial intelligence techniques were used to build empirical models from experimental data sets acquired from the manufacturing processes. The approach proposed in this work used an adaptive network-based fuzzy inference system to extract the value of technological force on Z-axis, which appears during incremental forming, considering a set of…
A measurement-based study on the correlations of inter-domain Internet application flows
2014
Internet traffic characterization has a profound impact on network engineering and traffic identification. Existing studies are often carried out on a per-flow basis, focusing on the properties of individual flows. In this paper, we study the interaction of Internet traffic flows and network features from a complex network perspective, focusing on six types of applications: P2P file sharing, P2P stream, HTTP, instant messaging, online games and abnormal traffic. With large-volume traffic flow records collected through proprietary line-speed hardware-based monitors, we construct flow graphs of these different application types. Based on the flow graphs, we calculate the correlation coefficie…
Support vector machines in engineering: an overview
2014
This paper provides an overview of the support vector machine SVM methodology and its applicability to real-world engineering problems. Specifically, the aim of this study is to review the current state of the SVM technique, and to show some of its latest successful results in real-world problems present in different engineering fields. The paper starts by reviewing the main basic concepts of SVMs and kernel methods. Kernel theory, SVMs, support vector regression SVR, and SVM in signal processing and hybridization of SVMs with meta-heuristics are fully described in the first part of this paper. The adoption of SVMs in engineering is nowadays a fact. As we illustrate in this paper, SVMs can …
Kernel manifold alignment for domain adaptation
2016
The wealth of sensory data coming from different modalities has opened numerous opportu- nities for data analysis. The data are of increasing volume, complexity and dimensionality, thus calling for new methodological innovations towards multimodal data processing. How- ever, multimodal architectures must rely on models able to adapt to changes in the data dis- tribution. Differences in the density functions can be due to changes in acquisition conditions (pose, illumination), sensors characteristics (number of channels, resolution) or different views (e.g. street level vs. aerial views of a same building). We call these different acquisition modes domains, and refer to the adaptation proble…
Sorting of Single Biomolecules based on Fourier Polar Representation of Surface Enhanced Raman Spectra
2016
AbstractSurface enhanced Raman scattering (SERS) spectroscopy becomes increasingly used in biosensors for its capacity to detect and identify single molecules. In practice, a large number of SERS spectra are acquired and reliable ranking methods are thus essential for analysing all these data. Supervised classification strategies, which are the most effective methods, are usually applied but they require pre-determined models or classes. In this work, we propose to sort SERS spectra in unknown groups with an alternative strategy called Fourier polar representation. This non-fitting method based on simple Fourier sine and cosine transforms produces a fast and graphical representation for sor…
Ranking-Oriented Collaborative Filtering: A Listwise Approach
2016
Collaborative filtering (CF) is one of the most effective techniques in recommender systems, which can be either rating oriented or ranking oriented. Ranking-oriented CF algorithms demonstrated significant performance gains in terms of ranking accuracy, being able to estimate a precise preference ranking of items for each user rather than the absolute ratings (as rating-oriented CF algorithms do). Conventional memory-based ranking-oriented CF can be referred to as pairwise algorithms. They represent each user as a set of preferences on each pair of items for similarity calculations and predictions. In this study, we propose ListCF, a novel listwise CF paradigm that seeks improvement in bot…