Imaging of cartilage has traditionally been achieved indirectly with conventional radiography. Loss of joint space width, or 'joint space narrowing', is considered a surrogate marker for cartilage thinning. However, radiography is severely limited by its inability to visualize cartilage, the difficulty of ascertaining the optimum and reproducible positioning of the joint in serial assessments, ...

Traditional supervised machine learning techniques require training on large volumes of data to acquire efficiency and accuracy. As opposed to traditional systems Active Learning systems minimizes the size of training data significantly because the selection of the data is done based on a strong mathematical model. This helps in achieving the same accuracy levels of the results as baseline tech...

The BFT approach is used to formulate the electronic states in graphene through a non-commutative space in the presence of a constant magnetic field B for the first time. In this regard, we introduce a second class of constrained system, which is not gauge symmetric but by applying BFT method and extending phase space, the second class constraints  converts  to the first class constraints so th...

Researchers have identified and defined β- approach normed space if some conditions are satisfied. In this work, we show that every is a space.However, the converse not necessarily true by giving an example. addition, define β – Banach space, examples given. We also solve problems. discuss finite β-dimensional app-normed β-complete consequent app- space. explain metric but give propositions. If...

In this paper two external schema generation algorithms are presented. These algorithms are defined in the framework of the new external schema definition methodology for OODBs put forward in (Samos, 1995); they generate an external schema from a set of classes selected from those existing in an external schema definition repository. Their main characteristic is that they avoid the generation o...

The curse of dimensionality is one of the severest problems concerning the application of RBF networks. The number of RBF nodes and therefore the number of training examples needed grows exponentially with the intrinsic dimensionality of the input space. One way to address this problem is the application of feature selection as a data pre-processing step. In this paper we propose a two-step app...