Ruqian Lu first presented the notion of knowware in 2005 through his IEEE Intelligent Systems paper entitled "From hardware to software to knowware: IT's third liberation?". He further elaborated the not...
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Internetwares [1] are a new type of software oriented to Internet. How to guarantee the QoS (Quality of Service) of Internetwares in highly open Internet is a challenge problem. This problem is especially important fo...
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ISBN:
(纸本)9781605588728
Internetwares [1] are a new type of software oriented to Internet. How to guarantee the QoS (Quality of Service) of Internetwares in highly open Internet is a challenge problem. This problem is especially important for e-commerce applications, because the users of e-commerce business are sensitive to QoS, such as the accessibility and responsiveness, and consequently the QoS of e-commerce applications are vital to their successes. Therefore, it is critical to evaluate and optimize the QoS of an e-commerce site by benchmarks off-line. Copyright 2009 ACM.
The liveness of Petri net models of parallel programs is a very important property . The existing analysis techniques take Petri net models as a whole to study properties,which is subject to the state explosion *** th...
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Recent years have witnessed the pilot deployments of audio or low-rate video wireless sensor networks for a class of mission-critical applications including search and rescue, security surveillance, and disaster manag...
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Image warping techniques are frequently used to render 3D scenes from images with depth information for VR applications. In this paper, we first propose a spherical representation of image-based models call the Spheri...
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We present a particle-based method for viscoelastic fluids simulation. In the method, based on the traditional Navier-Stokes equation, an additional elastic stress term is introduced to achieve viscoelastic flow behav...
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Learning systems are very effective tools for discovering knowledge from databases. Most symbolic learning systems face difficulties when discovering knowledge from large databases. Adapting the learning systems to co...
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ISBN:
(纸本)9780791802977
Learning systems are very effective tools for discovering knowledge from databases. Most symbolic learning systems face difficulties when discovering knowledge from large databases. Adapting the learning systems to cope with large databases is the traditional solution to overcome these limitations. This paper evaluates a new methodology for partitioning the representation space. The method selects an irrelevant attribute, determined by a utility function, to partition the representation space. Since irrelevant attributes are not needed to describe concepts learned from the original data, the knowledge discovered from all subspaces should be independent of such an attribute. If the representation space is partitioned by a relevant attribute, the knowledge discovered from all subspaces are combined simply using information about that attribute. The method is analyzed using C5 learning system, or See5.
We present a new method for adding furry effects for cartoon characters in images and videos. We synthesize furry stylized textures based on 3D texel structure. Given an image or a video as input, realistic fur texels...
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In China, there are some wide and environmentdisgusting offshore, which is not easy for manpower or ordinary ship to monitor. What’s more, ship with special materials is too expensive. This paper introduces a Huma...
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In China, there are some wide and environmentdisgusting offshore, which is not easy for manpower or ordinary ship to monitor. What’s more, ship with special materials is too expensive. This paper introduces a Human-Robot named OFFSHORE_ 1. It’s a half-intelligence robot, which can be used in the disgusting offshore environment. The robot can explore remote environment for monitoring, research and object identify etc.. Conclusion is drawn from the experiment that this robot can overcome the defect of manpower monitoring, share cost and improve the effect of monitoring, thus implements real-time and effective monitoring of the offshore.
Learning user preferences is a complex area, especially difficult for performing experiments - every person is different and has different preferences, which often change in time. In this paper, we propose a method fo...
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Learning user preferences is a complex area, especially difficult for performing experiments - every person is different and has different preferences, which often change in time. In this paper, we propose a method for testing a preference learning method that is in a sense more general than our previous attempts of testing an inductive method. We address the issue of limited rating set that results on larger datasets into more objects with the highest rating.
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