Search results for "HBO"

Semisupervised nonlinear feature extraction for image classification

2012

Feature extraction is of paramount importance for an accurate classification of remote sensing images. Techniques based on data transformations are widely used in this context. However, linear feature extraction algorithms, such as the principal component analysis and partial least squares, can address this problem in a suboptimal way because the data relations are often nonlinear. Kernel methods may alleviate this problem only when the structure of the data manifold is properly captured. However, this is difficult to achieve when small-size training sets are available. In these cases, exploiting the information contained in unlabeled samples together with the available training data can si…

Head-group variations and monolayer structures of diol derivatives

2007

Monolayers of 5 chemically modified diols varying the headgroup (nonadecane-1,2-diol (C1), hexadecyl-propane-1,3-diol (C2), hexadecyl-oxy-propane-1,2-diol (C3), hexadecyl-oxy-butane-1,2-diol (C4), hexadecanoyl-oxy-propane-1,2-diol (C5)) have been investigated by grazing incidence x-ray diffraction at 20°C and at different lateral pressures. C1 and C5 exhibit a centred-rectangular lattice with NN (nearest neighbour) tilt and NN distortion directions. In the case of C1 on increasing the lateral pressure the distortion changes to NNN (next-nearest neighbour direction) without a change in tilt direction (NN). This behaviour could not be observed for the other compounds. C3 and C4 display a phas…

Discussion of “Soil Water Retention Characteristics of Vertisols and Pedotransfer Functions Based on Nearest Neighbor and Neural Networks Approaches …

2013

STN area detection using K-NN classifiers for MER recordings in Parkinson patients during neurostimulator implant surgery

2016

Deep Brain Stimulation (DBS) applies electric pulses into the subthalamic nucleus (STN) improving tremor and other symptoms associated to Parkinson's disease. Accurate STN detection for proper location and implant of the stimulating electrodes is a complex task and surgeons are not always certain about final location. Signals from the STN acquired during DBS surgery are obtained with microelectrodes, having specific characteristics differing from other brain areas. Using supervised learning, a trained model based on previous microelectrode recordings (MER) can be obtained, being able to successfully classify the STN area for new MER signals. The K Nearest Neighbours (K-NN) algorithm has bee…

HEp-2 Cell Classification with heterogeneous classes-processes based on K-Nearest Neighbours

2014

We present a scheme for the feature extraction and classification of the fluorescence staining patterns of HEp-2 cells in IIF images. We propose a set of complementary processes specific to each class of patterns to search. Our set of processes consists of preprocessing,features extraction and classification. The choice of methods, features and parameters was performed automatically, using the Mean Class Accuracy (MCA) as a figure of merit. We extract a large number (108) of features able to fully characterize the staining pattern of HEp-2 cells. We propose a classification approach based on two steps: the first step follows the one-against-all(OAA) scheme, while the second step follows the…

"Tea for two": the Archive of the Italian Latinity of the Middle Ages meets the CLARIN infrastructure

2020

This paper aims at showing how integrating the Archive of the Italian Latinity of the Middle Ages (ALIM) into the ILC4CLARIN repository can provide mutual benefits. Making ALIM available to a large community of scholars and researchers, on the one side, represents the first step to reduce the lack of resources for Medieval Latin in CLARIN and, on the other side, constitutes an unprecedented contribution to not only linguistic investigations, but also to the studies of the culture and science at the basis of the Western European society. The paper describes the adopted approach aiming to keep intact the structure of the archive and its metadata, which are both accurately mirrored into the IL…

Some Experiments in Supervised Pattern Recognition with Incomplete Training Samples

2002

This paper presents some ideas about automatic procedures to implement a system with the capability of detecting patterns arising from classes not represented in the training sample. The procedure aims at incorporating automatically to the training sample the necessary information about the new class for correctly recognizing patterns from this class in future classification tasks. The Nearest Neighbor rule is employed as the central classifier and several techniques are added to cope with the peril of incorporating noisy data to the training sample. Experimental results with real data confirm the benefits of the proposed procedure.

Variable Neighborhood Search for the Vertex Separation Problem

2012

The vertex separation problem belongs to a family of optimization problems in which the objective is to nd the best separator of vertices or edges in a generic graph. This optimization problem is strongly related to other well-known graph problems; such as the Path-Width, the Node Search Number or the Interval Thickness, among others. All of these optimization problems are NP-hard and have practical applications in VLSI, computer language compiler design or graph drawing. Up to know, they have been generally tackled with exact approaches, presenting polynomial-time algorithms to obtain the optimal solution for speci c types of graphs. However, in spite of their practical applications, these…

Smart Grid Security: A new Approach to Detect Intruders in a Smart Grid Neighborhood Area Network

2016

International audience; In this paper, we propose an efficient and lightweight attack detection mechanism for a smart grid Neighborhood Area Network (NAN) that combine between distributed and centralized intrusion detection. A NAN includes the customers' appliances, smart meters and collectors. The smart meters measure the power consumption of each appliance and the collectors aggregate the measures and forward them to the control center for analysis. Intrusion Detection System (IDS) agents, proposed in our framework, run in a distributed fashion at smart meters level and in a centralized fashion at collector and control center nodes. A combination between a rule-based detection and a learn…

NEIGHBORHOOD EFFECTS IN SPATIAL HOUSING VALUE MODELS. THE CASE OF THE METROPOLITAN AREA OF PARIS (1999)

2009

In hedonic housing models, the spatial dimension of housing values are traditionally processed by the impact of neighborhood variables and accessibility variables. In this paper we show that spatial effects might remain once neighborhood effects and accessibility have been controlled for. We notably stress on three sides of neighborhood effects: social capital, social status and social externalities and consider the accessibility to the primary economic center as describing the urban spatial trend. Using spatial econometrics specifications of the hedonic equation, we estimate whether spatial effects impact the housing values. Our empirical case concerns the Metropolitan Area (MA) of Paris i…