BACKGROUND AND PURPOSE Reproducible segmentation of brain tumors on magnetic resonance images is an important clinical need. This study was designed to evaluate the reliability of a novel fully automated segmentation tool for brain tumor image analysis in comparison to manually defined tumor segmentations. METHODS We prospectively evaluated preoperative MR Images from 25 glioblastoma patients...

This paper presents the architecture of a virtual machine designed specifically for the execution of multiple languages, which we call Seam. The architecture consists of a number of generic components, usable by all languages, and of a number of interfaces for which implementations have to be provided by language implementors. Our contribution is the identification of the generic services and t...

Scheduling of multiple parallel machines in the face of sequence dependent setups and downstream considerations is a hard problem. No single efficient algorithm is guaranteed to produce optimal results. We describe a solution for an instance of this problem, in the domain of paper manufacturing. The problem has additional job machine restrictions and fixed costs of assigning jobs to machines. W...

We motivate our contribution to the shared MT task as a first step towards an integrated architecture that combines advantages of statistical and knowledge-based approaches. Translations were generated using the Pharaoh decoder with tables derived from the provided alignments for all four languages, and for three of them using web-based and locally installed commercial systems. We then applied ...

In order to simultaneously translate speech into multiple languages an extension of stochastic finite-state transducers is proposed. In this approach the speech translation model consists of a single network where acoustic models (in the input) and the multilingual model (in the output) are embedded. The multi-target model has been evaluated in a practical situation, and the results have been c...

Xia Sun 1,*, Jingting Xu 1, Changmeng Jiang 1, Jun Feng 1, Su-Shing Chen 2 and Feijuan He 3 1 School of Information Science and Technology, Northwest University, Xi’an 710069, China; [email protected] (J.X.); [email protected] (C.J.); [email protected] (J.F.) 2 Computer Information Science and Engineering, University of Florida, Gainesville, FL 32608, USA; [email protected] 3 Department o...

We describe an e cient multi-attribute pattern matching machine to locate all occurrences of any of a nite number of the sequence of rule structures (called matching rules) in a sequence of input structures. The proposed algorithm enables us to match set representations containing multiple attributes. Therefore, in proposed algorithm, con rming transition is decided by the relationship, whether...

This paper describes a hybrid machine translation system that explores a parser to acquire syntactic chunks of a source sentence, translates the chunks with multiple online machine translation (MT) system application program interfaces (APIs) and creates output by combining translated chunks to obtain the best possible translation. The selection of the best translation hypothesis is performed b...

This paper presents the concept of Multi-Function Operating Machine mainly carried out for production based industries. Industries are basically meant for Production of useful goods and services at low production cost, machinery cost and low inventory cost. Today in this world every task have been made quicker and fast due to technology advancement but this advancement also demands huge investm...

We propose MRU (Multi-Range Reasoning Units), a new fast compositional encoder for machine comprehension (MC). Our proposed MRU encoders are characterized by multi-ranged gating, executing a series of parameterized contractand-expand layers for learning gating vectors that benefit from long and short-term dependencies. The aims of our approach are as follows: (1) learning representations that a...