abstract: this paper represents a novel use of artificial neural networks in medical science. the proposed technique involves training a multi layer perceptron (mlp) (a kind of artificial neural network) with a bp learning algorithm to recognize a pattern for the diagnosing and prediction of five blood disorders, through the results of blood tests from h1 machine. the blood test parameters and ...

Introduction: Visual evoked potentials contain certain diagnostic information which have proved to be of importance in the visual systems functional integrity. Due to substantial decrease of amplitude in extra macular stimulation in commonly used pattern VEPs, differentiating normal and abnormal signals can prove to be quite an obstacle. Due to developments of use of machine l...

Presented here is a set of methods and tools developed to provide transportable measurements of performance in heterogeneous networks of machines operating together as a single virtual heterogeneous machine (VHM). The methods are work-based rather than time-based, and yield significant analytical information. A technique for normalizing the measure of useful work performed across a heterogeneou...

Large amounts of information is embedded in the natural scenes. Signs are good examples of objects in natural environments which have rich information content. In this paper, we present our efforts in the automatic sign translation. We describe the challenges in the automatic sign translation and introduce the architecture of our current system for automatic detection and translation of Chinese...

Neural network language models are often trained by optimizing likelihood, but we would prefer to optimize for a task specific metric, such as BLEU in machine translation. We show how a recurrent neural network language model can be optimized towards an expected BLEU loss instead of the usual cross-entropy criterion. Furthermore, we tackle the issue of directly integrating a recurrent network i...

Multitasking is an important part of today’s manufacturing plants. Multitask machine tools are capable of processing multiple operations at the same time by applying a different set of part and tool holding devices. Mill-turns are multitask machines with the ability to perform a variety of operations with considerable accuracy and agility. One critical factor in simultaneous machining is to cre...

Due to the increase of users the efficient usage of spectrum plays an important role in digital terrestrial television networks. In digital video broadcasting, local and global content are transmitted by single frequency network and multifrequency network respectively. Multifrequency network support transmission of global content and it consumes large spectrum. Similarly local content are well ...

A new type of single-phase stand-alone induction generator using a three-phase induction machine and a single-phase voltage-source PWM inverter is introduced. The generator scheme is capable of producing constant load frequency with a very well regulated output voltage. A small lead acid battery and a single-phase full diode-bridge rectifier are used to feed the inverter. The inverter feeds one...

Machine learning is the key to text classification, a granular computing approach to machine learning is applied to learning classification rules by considering the two basic issues: concept formation and concept relationships identification. In this paper, we concentrate on the selection of a single granule in each step to construct a granule network. A classification rule induction method is ...

Single root I/O virtualization (SRIOV) is a hardware/software interface that allows devices to “selfvirtualize” and thereby remove the host from the critical I/O path. SRIOV thus brings bare-metal performance to untrusted guest virtual machines (VMs) in public clouds, enterprise data centers, and high-performance computing setups. We identify a design flaw in current SRIOV deployments that enab...