The nature of the kernel density estimator (KDE) is to find underlying probability function (p.d.f) for a given dataset. key training KDE determine optimal bandwidth or Parzen window. All data points share fixed (scalar univariate and vector multivariate KDE) in (FKDE). In this paper, we propose an improved variable (IVKDE) which determines each point dataset based on integrated squared error (...

BACKGROUND Myocardial ischemia can be developed into more serious diseases. Early Detection of the ischemic syndrome in electrocardiogram (ECG) more accurately and automatically can prevent it from developing into a catastrophic disease. To this end, we propose a new method, which employs wavelets and simple feature selection. METHODS For training and testing, the European ST-T database is us...

We propose statistical processing methods and performance analysis techniques for discrimination and localization of Unexploded Ordnance (UXOs) using EMI sensors based on nonparametrically defined prior probability density functions for target-relevant features. In the first part of this thesis, new sets of UXO discrimination methods using these nonparametric prior models are introduced where w...

The BCR-ABL1 kinase expressed in acute lymphoblastic leukemia (ALL) drives malignant transformation of pre-B cells and prevents further development. We studied whether inhibition of BCR-ABL1 kinase activity using STI571 can relieve this differentiation block. STI571 treatment of leukemia patients induced expression of the Ig L chain-associated transcription factors IRF4 and SPIB, up-regulation ...

Data streams are ordered sets of values that are fast, continuous, mutable, and potentially unbounded. Examples of data streams include the pervasive time series which span domains such as finance, medicine, and transportation. Mining data streams require approaches that are efficient, adaptive, and scalable. For several stream mining tasks, knowledge of the data’s probability density function ...

Rainfall event separation is mainly based on the selection of minimum inter-event time (MIET). The traditional approach to determining a suitable MIET for estimating probability density functions often using frequency histograms. However, this cannot avoid arbitrariness and subjectivity in selecting histogram parameters. To overcome above limitations, study proposes kernel estimation (KDE) rain...

When an observer views the twodimensional (2-D) projection, e.g., shadow, of a moving three-dimensional (3-D) object, he usually perceives the shadow pattern as a form with depth. This has been called the Kinetic Depth Effect (KDE). Wallach and O'Connell (1953) concluded that an essential condition for the occurrence of the KDE seemed to be contours or lines that change their direction and thei...

In this paper, a modified kernel-based ensemble Gaussian mixture filtering (EnGMF) is introduced to produce fast and consistent orbit determination capabilities in sparse measurement environment. The EnGMF based on kernel density estimation (KDE) combine particle filters sum filters. This work proposes using Silverman’s rule of thumb reduce the computational burden KDE. Equinoctial orbital elem...

There are many examples of scientific workflow systems [1, 2]; in this short article I will concentrate only on cheminformatics applications and the workflow tools most commonly used in cheminformatics, namely Pipeline Pilot [3] and KNIME [4]. Workflow solutions have been used for years in bioinformatics and other sciences, and some also have applications in so-called ‘‘business intelligence’’ ...