The development of automatic analysis and classification methods for large databases of X-ray images is a pressing need that may have a great impact on clinical practice. To advance this objective the ImageCLEF-2015 clustering of body part X-ray images challenge was created. The aim of the challenge is to group digital X-ray images into five structural groups: head-neck, upper-limb, body, lower...

Patients receiving warfarin who have unstable control of anticoagulation have a significantly lower intake of dietary vitamin K compared with their stable counterparts. We hypothesized that supplementation with oral vitamin K would improve stability in patients with previously unstable control of anticoagulation. Seventy warfarin-treated patients with unstable anticoagulation control were rando...

A challenging problem of computer vision is scene classification. An efficient method for classifying natural scenes from the Oliva – Torralba dataset is proposed. The method is based on K-Means clustering algorithm followed by a novel two phase voting method for classification which is the main contribution of this paper. Two distinct feature sets have been used. The first feature set is used ...

This paper describes a project to compare two feature classification algorithms used in activity recognition in relation to accelerometer and heart rate data. Data was collected from six male and female subjects using a single tri-axial accelerometer and heart monitor attached to each subject’s dominant thigh. Subjects carried out eight activities and the data was labelled semi-automatically. F...

Flavor changing neutral current processes in B and K decays in the supergravity model 1 * Abstract Flavor changing neutral current processes such as b → s γ, b → s l + l − , b → s ν ν, ǫ K , ∆m B , K + → π + ν ν and K L → π 0 ν ν are calculated in the supersymmetric standard model based on supergravity. We consider two assumptions for the soft supersym-metry breaking terms. In the minimal case ...

We report a general method of Bayesian estimation that uses prior measurements to improve the signal-to-noise ratio of parametric images computed from dynamic PET scanning. In our method, the ordinary weighted least squares cost function is augmented by a penalty term to yield Phi(K,S)=minK{(C-f(K))(T)Omega(C)(-1)(C-f(K))+SPhi(K,S=0)(K-K;)(T)Omega(K)(-1)(K-K;)}, where C is a PET concentration h...

A well-known clustering algorithm is K-means. This algorithm, besides advantages such as high speed and ease of employment, suffers from the problem of local optima. In order to overcome this problem, a lot of studies have been done in clustering. This paper presents a hybrid Extended Cuckoo Optimization Algorithm (ECOA) and K-means (K), which is called ECOA-K. The COA algorithm has advantages ...

Nuclear magnetic resonance (NMR) logging provides a new means of estimating the hydraulic conductivity (K) of unconsolidated aquifers. The estimation of K from the measured NMR parameters can be performed using the Schlumberger-Doll Research (SDR) equation, which is based on the Kozeny-Carman equation and initially developed for obtaining permeability from NMR logging in petroleum reservoirs. T...

We define an exact functor Fn,k from the category of Harish-Chandra modules for GL(n, R) to the category of finite-dimensional representations for the degenerate affine Hecke algebra for gl(k). Under certain natural hypotheses, we prove that the functor maps standard modules to standard modules (or zero) and irreducibles to irreducibles (or zero).