Visual information overload is a threat to the interpretation of displays presenting large data sets or complex application environments. To combat this problem, researchers have begun to explore how haptic feedback c...
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ISBN:
(纸本)1595930280
Visual information overload is a threat to the interpretation of displays presenting large data sets or complex application environments. To combat this problem, researchers have begun to explore how haptic feedback can be used as another means for information transmission. In this paper, we show that people can perceive and accurately process haptically rendered ordinal data while under cognitive workload. We evaluate three haptic models for rendering ordinal data with participants who were performing a taxing visual tracking task. The evaluation demonstrates that information rendered by these models is perceptually available even when users are visually busy. This preliminary research has promising implications for haptic augmentation of visual displays for information visualization. Copyright 2005 ACM.
In Northern European fresh produce Supply Chain (SC) the evolution from horizontal alignment to vertically coordinated value chains allows the implementation of sophisticated traceability information systems, providin...
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ISBN:
(纸本)0975339346
In Northern European fresh produce Supply Chain (SC) the evolution from horizontal alignment to vertically coordinated value chains allows the implementation of sophisticated traceability information systems, providing with necessary transparency in information sharing between SC actors. On the other hand, fresh produce SCs aim in local markets in the South lack of efficient communication and information transparency.
Robust and accurate cancer classification is critical in cancer treatment. Gene expression profiling is expected to enable us to diagnose tumors precisely and systematically. However, the classification task in this c...
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ISBN:
(纸本)0769523447
Robust and accurate cancer classification is critical in cancer treatment. Gene expression profiling is expected to enable us to diagnose tumors precisely and systematically. However, the classification task in this context is very challenging because of the curse of dimensionality and the small sample size problem. In this paper, we propose a novel method to solve these two problems. Our method is able to map gene expression data into a very low dimensional space and thus meets the recommended samples to features per class ratio. As a result, it can be used to classify new samples robustly with low and trustable (estimated) error rates. The method is based on linear discriminant analysis (LDA). However, the conventional LDA requires that the within-class scatter matrix S/sub w/ be nonsingular. Unfortunately, S/sub w/ is always singular in the case of cancer classification due to the small sample size problem. To overcome this problem, we develop a generalized linear discriminant analysis (GLDA) that is a general, direct, and complete solution to optimize Fisher's criterion. GLDA is mathematically well-founded and coincides with the conventional LDA when S/sub w/ is nonsingular. Different from the conventional LDA, GLDA does not assume the nonsingularity of S/sub w/, and thus naturally solves the small sample size problem. To accommodate the high dimensionality of scatter matrices, a fast algorithm of GLDA is also developed. Our extensive experiments on seven public cancer datasets show that the method performs well. Especially on some difficult instances that have very small samples to genes per class ratios, our method achieves much higher accuracies than widely used classification methods such as support vector machines, random forests, etc.
With advanced technologies, computer devices have become smaller and powerful. As a result, many people enjoy ubiquitous learning using mobile devices such as Pocket PCs. Pocket PCs are easy to carry and use as a dist...
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Movements of interfaces can be analyzed in terms of whether they are expected, sensed, and desired. Expected movements are those that users naturally perform;sensed are those that can be measured by a computer;and des...
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We give an overview of the RWTH phrase-based statistical machine translation system that was used in the evaluation campaign of the International Workshop on Spoken Language Translation 2005. We use a two pass approac...
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The tagging of discourse is important not only for natural language processing research, but for many applications in the social sciences as well. This paper describes an evaluation of a range of different tagging tec...
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Interrupting users engaged in tasks typically has negative effects on their task completion time, error rate, and affective state. Empirical research has shown that these negative effects can be mitigated by deferring...
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ISBN:
(纸本)1595932208
Interrupting users engaged in tasks typically has negative effects on their task completion time, error rate, and affective state. Empirical research has shown that these negative effects can be mitigated by deferring interruptions until more opportune moments in a user's task sequence. However, existing systems that reason about when to interrupt do not have access to task models that would allow for such finer-grained temporal reasoning. We outline our method of finding opportune moments that links a physiological measure of workload with task modeling techniques and theories of attention. We describe the design and implementation of our interruption management system, showing how it can be used to specify and monitor practical, representative user tasks. We discuss our ongoing empirical work in this area, and how the use of our framework may enable attention aware systems to consider a user's position in a task when reasoning about when to interrupt. Copyright 2005 ACM.
Dance is believed to be important in the courtship of a variety of species, including humans, but nothing is known about what dance reveals about the underlying phenotypic - or genotypic - quality of the dancer1-6. On...
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Recent work on intelligent tutoring systems has used Bayesian networks to model students' acquisition of skills. In many cases, researchers have hand-coded the parameters of the networks, arguing that the conditio...
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