Microshrinkages are known as probably the most difficult defects to avoid in high-precision foundry. The presence of this failure renders the casting invalid, with the subsequent cost increment. Modelling the foundry process as an expert knowledge cloud allows properly-trained machine learning algorithms to foresee the value of a certain variable, in this case the probability that a microshrink...

We investigate the design and functionality of a network of loopshaped charge qubits with switchable nearest-neighbour coupling. The qubit coupling is achieved by placing large Josephson junctions (JJs) at the intersections of the qubit loops and selectively applying bias currents. The network is scalable and makes it possible to perform a universal set of quantum gates. The coupling scheme all...

Over the last decade, due to the rapid developments in information technology (IT), a new breed of information systems has appeared such as geographic information systems that introduced new challenges for researchers, developers and users. One of its applications is the car navigation system, which allows drivers to receive navigation instructions without taking their eyes off the road. Using ...

A neurally-inspired visual object recognition system is described called SEEMORE, whose goal is to identify common objects from a large known set-independent of 3-D viewiag angle, distance, and non-rigid distortion. SEEMORE's database consists of 100 objects that are rigid (shovel), non-rigid (telephone cord), articulated (book), statistical (shrubbery), and complex (photographs of scenes). Rec...

Developing a stable early warning system (EWS) model that is capable to give an accurate prediction is a challenging task. This paper introduces k-nearest neighbour (k-NN) method which never been applied in predicting currency crisis before with the aim of increasing the prediction accuracy. The proposed k-NN performance depends on the choice of a distance that is used where in our analysis; we...

Multiple linear regression (MLR) is a popular method for producing forecasts when data on relevant independent variables (or cues) is available. The accuracy of the technique in forecasting the impact on Greek TV audience shares of programmes showing sport events is compared with forecasts produced by: (1) a simple bivariate regression model, (2) three different types of artificial neural netwo...

We describe a real time robot navigation system based on three VLSI neural network modules. These are a resistive grid for path planning, a nearest-neighbour classifier for localization using range data from a timeof-flight infra-red sensor and a sensory-motor associative network for dynamic obstacle avoidance .

In this paper, we propose a model for automatic classification of Animals using different classifiers Nearest Neighbour, Probabilistic Neural Network and Symbolic. Animal images are segmented using maximal region merging segmentation. The Gabor features are extracted from segmented animal images. Discriminative texture features are then selected using the different feature selection algorithm l...

The explosive growth of image data leads to the research and development of image content searching and indexing systems. Image annotation systems aim at annotating automatically animage with some controlled keywords that can be used for indexing and retrieval of images. This paper presents a comparative evaluation of the image content annotation system by using the multilayer neural networks a...

In recent years, large scale land cover maps constructed from remotely sensed data have become important information sources for resource management. Classifiers are commonly used to predict land cover for unsampled map units; hence, they play a key role in map construction. Achieving adequate classifier accuracy is often problematic for highly variable and difficult-to-sample landscapes. This ...