This paper describes the new Java memory model, which has been revised as part of Java 5.0. The model specifies the legal behaviors for a multithreaded program; it defines the semantics of multithreaded Java programs and partially determines legal implementations of Java virtual machines

A novel method to model and predict the location and orientation of alpha helices in membrane- spanning proteins is presented. It is based on a hidden Markov model (HMM) with an architecture that corresponds closely to the biological system. The model is cyclic with 7 types of states for helix core

), the algorithm has two integral parts: a low-resolution initial estimate of the real signal and the iteration process that refines the initial estimate to the final localized energy solution. The iterations are based on weighted norm minimization of the dependent variable with the weights being a function

We describe a single convolutional neural network architecture that, given a sentence, outputs a host of language processing predictions: part-of-speech tags, chunks, named entity tags, semantic roles, semantically similar words and the likelihood that the sentence makes sense (grammatically

After presenting a novel O(n³) parsing algorithm for dependency grammar, we develop three contrasting ways to stochasticize it. We propose (a) a lexical affinity model where words struggle to modify each other, (b) a sense tagging model where words fluctuate randomly in their selectional

the design for higher feed rates; and (iv) generate simple dynamic models of their behavior. I. Introduction The Impulse dynamic simulator [1] is used to generate a wide range of synthetic measurements for two novel parts feeder designs. The first design is a MEMs-based actuator array called the M-Chip [2

568 nature neuroscience • volume 2 no 6 • june 1999 articles Evidence for specialization in the fusiform gyrus for human face perception comes from both neuroimaging and neuropsychological studies Subjects were trained with novel objects called greebles 14 RESULTS We localized the brain areas

. The method makes possible a novel treatment of the boundary in which cells abutting the bottom or coast may take on irregular shapes and be "shaved" to fit the boundary. The algorithm can conveniently exploit massively parallel computers and suggests a domain decomposition which allocates vertical

In this paper, we address the problem of detecting pedestri-ans in crowded real-world scenes with severe overlaps. Our basic premise is that this problem is too difficult for any type of model or feature alone. Instead, we present a novel al-gorithm that integrates evidence in multiple iterations

In this paper, we propose a novel method, called local nonnegative matrix factorization (LNMF), for learning spatially localized, parts-based subspace representation of visual patterns. An objective function is defined to impose localization constraint, in addition to the non-negativity constraint