A modified ART 1 algorithm more suitable for VLSI implementations

This paper presents a modification to the original ART 1 algorithm (Carpenter and Grossberg, 1987a, A massively parallel architecture for a self-organizing neural pattern recognition machine, Computer Vision, Graphics, and Image Processing, 37, 54–115) that is conceptually similar, can be implemented in hardware with less sophisticated building blocks, and maintains the computational capabilities of the originally proposed algorithm. This modified ART 1 algorithm (which we will call here ART 1m) is the result of hardware motivated simplifications investigated during the design of an actual ART 1 chip [Serrano-Gotarredona et al., 1994, Proc. 1994 IEEE Int. Conf. Neural Networks (Vol. 3, pp. 1912–1916); Serrano-Gotarredona and Linares-Barranco, 1996, IEEE Trans. VLSI Systems, (in press)]. The purpose of this paper is simply to justify theoretically that the modified algorithm preserves the computational properties of the original one and to study the difference in behavior between the two approaches

The C++0x "Concepts" Effort

C++0x is the working title for the revision of the ISO standard of the C++ programming language that was originally planned for release in 2009 but that was delayed to 2011. The largest language extension in C++0x was "concepts", that is, a collection of features for constraining template parameters. In September of 2008, the C++ standards committee voted the concepts extension into C++0x, but then in July of 2009, the committee voted the concepts extension back out of C++0x. This article is my account of the technical challenges and debates within the "concepts" effort in the years 2003 to 2009. To provide some background, the article also describes the design space for constrained parametric polymorphism, or what is colloquially know as constrained generics. While this article is meant to be generally accessible, the writing is aimed toward readers with background in functional programming and programming language theory. This article grew out of a lecture at the Spring School on Generic and Indexed Programming at the University of Oxford, March 2010

Generating indicative-informative summaries with SumUM

We present and evaluate SumUM, a text summarization system that takes a raw technical text as input and produces an indicative informative summary. The indicative part of the summary identifies the topics of the document, and the informative part elaborates on some of these topics according to the reader's interest. SumUM motivates the topics, describes entities, and defines concepts. It is a first step for exploring the issue of dynamic summarization. This is accomplished through a process of shallow syntactic and semantic analysis, concept identification, and text regeneration. Our method was developed through the study of a corpus of abstracts written by professional abstractors. Relying on human judgment, we have evaluated indicativeness, informativeness, and text acceptability of the automatic summaries. The results thus far indicate good performance when compared with other summarization technologies

Issues Affecting Security Design Pattern Engineering

Security Design Patterns present the tried and tested design decisions made by security engineers within a well documented format. Patterns allow for complex security concepts, and mechanisms, to be expressed such that non domain experts can make use of them. Our research is concerned with the development of pattern languages for advanced crypto-systems. From our experience developing pattern languages we have encountered several recurring issues within security design pattern engineering. These issues, if not addressed, will affect the adoption of security design patterns. This paper describes these issues and discusses how they could be addressed

Frontoparietal action-oriented codes support novel task set implementation

A key aspect of human cognitive flexibility concerns the ability to rapidly convert complex symbolic instructions into novel behaviors. Previous research proposes that this fast configuration is supported by two differentiated neurocognitive states, namely, an initial declarative maintenance of task knowledge, and a progressive transformation into a pragmatic, action-oriented state necessary for optimal task execution. Furthermore, current models predict a crucial role of frontal and parietal brain regions in this transformation. However, direct evidence for such frontoparietal formatting of novel task representations is still lacking. Here, we report the results of an fMRI experiment in which participants had to execute novel instructed stimulus-response associations. We then used a multivariate pattern-tracking procedure to quantify the degree of neural activation of instructions in declarative and procedural representational formats. This analysis revealed, for the first time, format-unique representations of relevant task sets in frontoparietal areas, prior to execution. Critically, the degree of procedural (but not declarative) activation predicted subsequent behavioral performance. Our results shed light on current debates on the architecture of cognitive control and working memory systems, suggesting a contribution of frontoparietal regions to output gating mechanisms that drive behavior