A New Technique To Identify Arbitrarily Shaped Noise Sources

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Efficient Clustering Techniques in presence of Noise

new knowledge. The iterative process consists of the following steps: 1) Data cleaning: It also known as data cleansing, it is a phase in which noise data and irrelevant data are removed from the collection. 2) Data integration: In this stage, multiple data sources, often heterogeneous, may be combined in a common source.

A hybrid unsupervised clustering-based anomaly detection method

produces arbitrarily-shaped clusters. Density is defined as the number of points within a specified radius. It is particularly useful when dealing with spatial clusters or when there is noise in the dataset. It works with two parameters: radius and minimum points. DBSCAN is robust to outliers, and it can even find a cluster

Dorian Vigoureux, Nicolas Totaro, Jonathan Lagneaux, Jean

Many methods to detect, quantify or reconstruct acoustic sources exist in the literature and are widely used in in-dustry (Near-field acoustic holography, inverse Boundary Element Method, etc.). However, the source identification in a reverberant or non-anechoic environment on an irregularly shaped structure is still an open issue.

Revealing the distribution of transmembrane currents along

consider reconstruction of sources for random synaptic activation of the ball-and-stick cell. Secondly, we consider a Y-shaped neuron with a single branching point, we check if skCSD can differentiate between synaptic activations located on the different branches close to the branching point.

Turkish Journal of Computer and Mathematics Education Vol.12

Hussien et al. [1], proposed a utility-based privacy-preserving technique. Their approach takes into account the attributes of sensitive values represented in the queries. They allowed data owners to assign weights to the attributes and anonymized the queries using generalization boundaries only if the sensitive attribute's values

G Automatic Inspection and Processing Based on Vision

images is an important technique for the recognition of large objects. However, image stitching incurs large computational costs and can fail if shared features cannot be identified [1-3]. Most conventional approaches to image stitching are based on scale-invariant feature transforms (SIFT) [4-6] and feature matching [7, 8].

ASSESSING SEMANTIC RELEVANCE BY USING AUDIOVISUAL CUES

sources. They are also able to represent arbitrarily complex probability density functions [7]. Arbitrary shaped distributions can be modeled using a mixture of Gaussians with infinite number of components. This is however practically infeasible. Here, we model

Interferometric correlogram-space analysis

a VSP acquisition geometry using surface sources and down-hole receivers. The model is purely acoustic and contains at or dipping layers and/or point inclusions that act as di ractors. Results of a semblance-based moveout scan of the cross-correlograms are used to identify the potential geometry of the re ectors.

A survey on Efficient Enhanced K-Means Clustering Algorithm

identify patterns and prospects from large amount of information. In Data Mining, Clustering is an important research topic and wide range of unverified classification application. Clustering is technique which divides a data into meaningful groups. K-means clustering is a method of

On the Use of Standards for PECIALIZED METHODS Microarray

different publicly available sources. The technique proposed by J¤ornsten et al. [2] for handling arbitrarily shaped regions is used for encoding the spots and background sep-

Model-independent extraction of the shapes and Fourier

This work presents a technique for extracting the detailed shape of peaks with extended, overlapping tails in an X-ray powder diffraction pattern. The application discussed here concerns crystallite size broadening, though the technique can be applied to spectra of any origin and without regard to how the profiles are to be subsequently analyzed.

Gaussian Segmentation and Tokenization for Low Cost Language

Gaussian Segmentation and Tokenization 3 1.1 Problem Description The phonotactic based systems use observed phono sequences to construct a sta-tistical language model (LM) for each language of

Dynamically Constrained Nowcasting in the Coastal Ocean

Dynamically Constrained Nowcasting in the Coastal Ocean A. D. Kirwan, Jr. College of Marine Studies University of Delaware Newark, DE 19716 phone:(302) 831-2977 fax: (302) 831-6838 email:

ISTITUTO NAZIONALE DI RICERCA METROLOGICA Repository

34 the proposed technique will inspire a new generation of simple and cheap, high-35 resolution spectroscopy tools with reduced footprint. 36 37 In general, the concept of super-resolution refers to the possibility to obtain a higher quality digital 38 reconstruction of a detected signal, using sets of low-resolution measurements. In the field

LNICST 74 - Mobile Sensing Enabled Robust Detection of

utilized Mean Shift Clustering algorithm, a nonparametric clustering technique, does not assume any prior knowledge of the number of clusters, and can handle arbitrarily shaped clusters. Thus, it is suitable for handling clusters of arbitrary shape and number for detecting security threats using mobile sensing data. 3SystemOverview

2D Resonances in Alpine Valleys Identified from Ambient

To investigate the response of the site to ambient noise typical for densely-populated areas, we placed all sources randomly on the sediment surface inside the valley (Fig. 5). Each source is characterised by a random amplitude, direction and time function. transversal radial 0 200 400 600 300 350 400 receivers sources −800 −600 −400 −200 0

Kernel-phase for interferometrywith arich aperture

ray: the technique is therefore relevant to both sparse pupil interferometry and conventional imaging. Section 2. of this paper shows how linear algebra formal-ism offers a convenient extension of the classical model of closure-phase suited to rich arrays, used in section 3. to introduce a generalisation of the closure-phase: the kernel-phase.

A Hybrid Unsupervised Clustering-Based Anomaly Detection Method

identify intrusions by analyzing data collected through network devices [3]. According to the detection mechanism, IDS can be classified as misuse (also called signature-based) detection and anomaly (also called behavior-based) detection [4]. Misuse detection approaches are designed to detect attacks by using a database of predefined attack

Determination of deposited flux and energy of sputtered

A time-resolved tunable diode-laser (DL) induced fluorescence (TR-TDLIF) technique has been used to identify different populations of atoms (on different stages of transport) to determine their corresponding deposited energy and flux.

i-CODAS: An Improved Online Data Stream Clustering in

The technique shows good cluster quality, but it requires predetermining the number of clusters in the system and cannot generate arbitrarily shaped clusters. Recently, an online clustering algorithm, CODAS [11] has been proposed which generates arbitrary shaped clusters from data streams. The purity and accuracy of CODAS are quite high and it

A new technique to identify arbitrarily shaped noise sources

220 R.A. Tenenbaum and M.B.S. Magalh˜aes / A new technique to identify arbitrarily shaped noise sources how much energy is in fact transported to the far-field, can be extracted either from sound intensity measurements or numerical simulation. In a later work, Williams [17] details of the evaluation of supersonic acoustic intensity for

Fully Online Clustering of Evolving Data Streams into

only hyper-elliptical clusters. In this paper we present a fully online technique for clustering evolving data streams into arbitrary shaped clusters. It is a two stage technique that is accurate, robust to noise, computationally and memory e cient, with a low time penalty as the number of data dimensions increases.