In recent years, we have witnessed significant increase in the amount of data in digital format, due to the widespread use of computers and advances in storage systems. As the volume of digital information increases, there arises the need for more effective tools to better find, filter and manage these resources. Therefore, developing fast and highly accurate algorithms to automatically classif...

This is the first paper to present such a digital redesign method for the (conventional) OKID system and apply this novel technique for nonlinear system identification. First, the Observer/Kalman filter Identification (OKID) method is used to obtain the lower-order state-space model for a stochastic chaos system. Then, a digital redesign approach with the high-gain property is applied to improv...

Quality of Service (QoS) guarantee is an important component of service recommendation. Generally, some QoS values of a service are unknown to its users who has never invoked it before, and therefore the accurate prediction of unknown QoS values is significant for the successful deployment of Web service-based applications. Collaborative filtering is an important method for predicting missing v...

The delay distribution of a digital circuit path is crucial for the early reliability evaluation of a digital design. As transistors are shrunk to unprecedented dimensions, accurate yet fast estimation of such distributions remains a valid goal. Such distributions may not be provided or are delivered in a heavily abstracted fashion to designers, which reduces the insight into design dependabili...

A new spectral code for constructing general–relativistic models of rapidly rotating stars with an unprecedented accuracy is presented. As a first application, we reexamine uniformly rotating homogeneous stars and compare our results with those obtained by several previous codes. Moreover, representative relativistic examples corresponding to highly flattened rotating bodies are given.

With the rapid growth of internet, it is a scientific challenge and a massive economic need to discover an efficient and accurate text classifier for handling tons of online documents. This paper presents a distributed model for efficient web document classifications. In the model, the distributed text classifiers are trained serially with the weights on the training instances, which are adapti...