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Communications of the ACM

151 - 160 of 286 for bentley

A root cause analysis interface for error reporting

We describe a web-based interface that facilitates entering and analyzing medical errors. It uses an interactive causal tree-building component. The interactive component allows a user to build a causal tree with any number of events and antecedents. This replaces a form-based approach that is limited to a predetermined number of events and antecedents. After the causal tree is completed, the user can save the tree to a database. Causal trees can be retrieved and rebuilt as well. We developed an algorithm that, given a data bank of reported errors, will help detect similar events. This facilitates recognizing patterns of errors.


Sharing motion information with close family and friends

We present the Motion Presence application, an augmented phone book style application that allows close friends and family to view each other's current motion status ("moving" or "not moving") on their mobile phones. We performed a two week long field trial with 10 participants to observe usage and investigate any privacy concerns that might arise. We found that our participants used the motion information to infer location and activity as well as to plan communication, to help in coordinating in-person get-togethers, and to stay connected to patterns in each others' lives. Participants saw the motion data as mostly confirming their existing thoughts about the locations and activities of others and expressed few privacy concerns. In fact, they frequently asked for more information to be shared to make the application more compelling.


A clustering entropy-driven approach for exploring and exploiting noisy functions

Linear, Gaussian, fitness proportional, clustering, and Rosca entropies are succinct measures of diversity that have been applied to balance exploration and exploitation in evolutionary algorithms. In previous studies, an entropy-driven approach using linear entropy explicitly balances and/or searches optimal solutions for the selected unimodal and multimodal functions excluding noisy functions. This paper investigates the reasons for such an exception and introduces a clustering entropy-driven approach to solve the problem. Such an approach provides a coarse-grained diversity measure that filters the noise of functions, varies cluster size and categorizes individuals at the genotype level. The experimental results show that the clustering entropy-driven approach further improves the searching results of noisy functions by one more degree.


Implicit array bounds checking on 64-bit architectures

Several programming languages guarantee that array subscripts are checked to ensure they are within the bounds of the array. While this guarantee improves the correctness and security of array-based code, it adds overhead to array references. This has been an obstacle to using higher-level languages, such as Java, for high-performance parallel computing, where the language specification requires that all array accesses must be checked to ensure they are within bounds. This is because, in practice, array-bounds checking in scientific applications may increase execution time by more than a factor of 2. Previous research has explored optimizations to statically eliminate bounds checks, but the dynamic nature of many scientific codes makes this difficult or impossible. Our approach is, instead, to create a compiler and operating system infrastructure that does not generate explicit bounds checks. It instead places arrays inside of Index Confinement Regions (ICRs), which are large, isolated, mostly unmapped virtual memory regions. Any array reference outside of its bounds will cause a protection violation; this provides implicit bounds checking. Our results show that when applying this infrastructure to high-performance computing programs written in Java, the overhead of bounds checking relative to a program with no bounds checks is reduced from an average of 63% to an average of 9%.


On-line spam filter fusion

We show that a set of independently developed spam filters may be combined in simple ways to provide substantially better filtering than any of the individual filters. The results of fifty-three spam filters evaluated at the TREC 2005 Spam Track were combined post-hoc so as to simulate the parallel on-line operation of the filters. The combined results were evaluated using the TREC methodology, yielding more than a factor of two improvement over the best filter. The simplest method -- averaging the binary classifications returned by the individual filters -- yields a remarkably good result. A new method -- averaging log-odds estimates based on the scores returned by the individual filters -- yields a somewhat better result, and provides input to SVM- and logistic-regression-based stacking methods. The stacking methods appear to provide further improvement, but only for very large corpora. Of the stacking methods, logistic regression yields the better result. Finally, we show that it is possible to select a priori small subsets of the filters that, when combined, still outperform the best individual filter by a substantial margin.


A genetic algorithm with a variable-length genotype and embryogeny for microstructured optical fibre design

Microstructured optical fibres are a relatively recent advance in fibre technology which guide light by using arrays of air holes which run the length of the fibre. The internal microstructure of optical fibres can be altered to reshape and transform light for use in medical applications, sensing, long distance and local area network high bandwidth communications. Recent progress in the production of polymer fibres allows designs with complex microstructures consisting of hundreds of holes to be manufactured. In this paper we present a generative (embryogenic) representation which can produce symmetric fibre designs with a variable number of holes. The resulting genetic algorithm has the ability to search designs of varying complexity over time, allowing less or more complex designs to be evolved as required. Various aspects of this representation are discussed in light of the supporting genetic algorithm such as as recombination of designs and the conversion of the variable length binary genotype to the phenotype (optical fibre structure). We include some single objective design results for a high-bandwidth optical fibre along with manufactured designs.


Modular thinking: evolving modular neural networks for visual guidance of agents

This paper investigates whether replacing non-modular artificial neural network brains of visual agents with modular brains improves their ability to solve difficult tasks, specifically, survive in a changing environment. A set of experiments was conducted and confirmed that agents with modular brains are in fact better. Further analysis of the evolved modules characterised their function and determined their mechanism of operation. The results indicate that the greater survival ability is obtained due to functional specialisation of the evolved modules; good agents do well because their modules are more specialised at tasks such as reproduction and consumption. Overall, the more specialised the modules, the fitter the agents.


Personal vs. commercial content: the similarities between consumer use of photos and music

We describe the results of two ethnographic-style studies that investigated consumer use of photos and music respectively. Although the studies were designed, executed, and analyzed separately, in our findings we discovered striking similarities between the ways in which our participants used personally captured photos and commercially purchased music. These findings have implications for the design of future systems with respect to handling and sharing content in photo or music form. We discuss making allowances for satisficing behavior, sharing media as a way to reminisce or to communicate an experience (tell a story), getting sidetracked while browsing, and similarities in organizing behaviors.


Interpolating implicit surfaces from scattered surface data using compactly supported radial basis functions

We describe algebraic methods for creating implicit surfaces using linear combinations of radial basis interpolants to form complex models from scattered surface points. Shapes with arbitrary topology are easily represented without the usual interpolation or aliasing errors arising from discrete sampling. These methods were first applied to implicit surfaces by Savchenko, et al. and later developed independently by Turk and O'Brien as a means of performing shape interpolation. Earlier approaches were limited as a modeling mechanism because of the order of the computational complexity involved. We explore and extend these implicit interpolating methods to make them suitable for systems of large numbers of scattered surface points by using compactly supported radial basis interpolants. The use of compactly supported elements generates a sparse solution space, reducing the computational complexity and making the technique practical for large models. The local nature of compactly supported radial basis functions permits the use of computational techniques and data structures such as k-d trees for spatial subdivision, promoting fast solvers and methods to divide and conquer many of the subproblems associated with these methods. Moreover, the representation of complex models permits the exploration of diverse surface geometry. This reduction in computational complexity enables the application of these methods to the study of shape properties of large complex shapes.


Bias and scalability in evolutionary development

The introduction of a genotype-phenotype map modelled on biological development can potentially improve the scalability of evolutionary algorithms. Previous work by Gordon and Bentley demonstrated that such a model can be used to evolve patterns that map to useful but small phenotypes. This paper uses the same model to generate much larger patterns covering arrays of up to 64x64 cells. The results show that the model's performance is generally comparable to similar development-based systems [12, 14], and with some measures outperforms them. Additionally the inherent biases of the model are explored, such as the need to use symmetry-breaking initial conditions which some other models do not require. This exploration yields a set of guidelines that suggest what kinds of problem the model is suited to exploring.