How can we enable computers to automatically answer questions like “Who created the character Harry Potter”? Carefully built knowledge bases provide rich sources of facts. However, it remains a challenge to answer factoid questions raised in natural language due to numerous expressions of one question. In particular, we focus on the most common questions — ones that can be answered with a singl...

Partial discharge (PD) pattern recognition is an important tool in HV insulation diagnosis. A PD pattern recognition approach of HV power transformers based on a neural network is proposed in this paper. A commercial PD detector is firstly used to measure the 3-D PD patterns of epoxy resin power transformers. Then, two fractal features (fractal dimension and lacunarity) extracted from the raw 3...

Agile Software development has become famous in industries and replacing the traditional methods of software development. A correct estimation of effort in this concept still remains an argument in industries. Thus, the industry must be able to estimate the effort necessary for software development using agile methodology. For estimating effort different types of neural-networks Probabilistic N...

We introduce the use of conditional generative adversarial networks forgeneralised gravitational wave burst generation in time domain.Generativeadversarial are machine learning models that produce new databased on features training data set. condition network fiveclasses time-series signals often used to characterise waveburst searches: sine-Gaussian, ringdown, white noise burst, Gaussian pulse...

Artificial neural networks (ANNs) are usually designed around vector-matrix multipliers, where the inputs to the neurons are represented by the vectors while the interconnection weights are represented by the matrix. Optics, with its interferenceless free-space communication capabilities, is therefore an efficient and natural way to implement ANNs; however, it is not without practical problems....

This paper describes work in progress involving the development of techniques for use in enhanced internalcombustion engine-management systems for application in motor vehicles. The aim is to improve the control of the engine by the application of intelligent-systems techniques, thus leading to reduced exhaust emissions and improved fuel economy. A neural-network technique is described for the ...

We present a dual contribution to the task of machine reading-comprehension: a technique for creating large-sized machine-comprehension (MC) datasets using paragraph-vector models; and a novel, hybrid neural-network architecture that combines the representation power of recurrent neural networks with the discriminative power of fully-connected multi-layered networks. We use the MC-dataset gener...

The Self-Organising Map (SOM) is a well-known neuralnetwork model that has successfully been used as a data analysis tool in many different domains. The SOM provides a topology-preserving mapping from a high-dimensional input space to a lower-dimensional output space, a convenient interface to the data. However, the real power of this model can only be utilised with sophisticated visualisations...

In an experiment of multi-trial task to obtain a reward, reward expectancy neurons, which responded only in the non-reward trials that are necessary to advance toward the reward, have been observed in the anterior cingulate cortex of monkeys. In this paper, to explain the emergence of the reward expectancy neuron in terms of reinforcement learning theory, a model that consists of a recurrent ne...