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With the constraints of network topologies and link capacities, achieving the optimal end-to-end throughput in data networks has been known as a fundamental but computationally hard problem. In this paper, we seek efficient solutions to the problem of achieving optimal throughput in data networks, with single or multiple unicast, multicast and broadcast(More)
— With the constraints of network topologies and link capacities, achieving the optimal end-to-end throughput in data networks has been known as a fundamental but computationally hard problem. In this paper, we seek efficient solutions to the problem of achieving optimal throughput in data networks, with single or multiple uni-cast, multicast and broadcast(More)
The basic idea of traditional density estimation is to model the overall point density analytically as the sum of influence functions of data points. However, traditional density estimation techniques only consider the location of a point. Supervised density estimation techniques, on the other hand, additionally consider a variable of interest that is(More)
The discovery of interesting regions in spatial datasets is an important data mining task. In particular, we are interested in identifying disjoint, contiguous regions that are unusual with respect to the distribution of a given class; i.e. a region that contains an unusually low or high number of instances of a particular class. This paper centers on the(More)
BACKGROUND We recently developed high-throughput assays of inflammation-independent anti-fibrotic activities based on TGF-beta1-induced total collagen accumulation and nodule formation in normal rat kidney fibroblasts. METHODS These assays were applied to examine the anti-fibrotic activities of 21 compounds isolated from plants used in Chinese medicine(More)
This paper presents a novel region discovery framework geared towards finding scientifically interesting places in spatial datasets. We view region discovery as a clustering problem in which an externally given fitness function has to be maximized. The framework adapts four representative clustering algorithms, exemplifying prototype-based, grid-based,(More)
We report three experiments investigating the hypothesis that use of internal visual imagery (IVI) would be superior to external visual imagery (EVI) for the performance of different slalom-based motor tasks. In Experiment 1, three groups of participants (IVI, EVI, and a control group) performed a driving-simulation slalom task. The IVI group achieved(More)
HYPOTHESIS The aim of this study was to measure the mass loading effect of an active middle-ear implant (the Vibrant Soundbridge) in cadaver temporal bones. BACKGROUND Implantable middle ear hearing devices such as Vibrant Soundbridge have been used as an alternative to conventional hearing aids for the rehabilitation of sensorineural hearing loss. Other(More)
The basic idea of traditional density estimation is to model the overall point density analytically as the sum of influence functions of the data points. However, traditional density estimation techniques only consider the location of a point. Supervised density estimation techniques, on the other hand, additionally consider a variable of interest that is(More)
Anti-counterfeiting is a global problem. Brand owners turn to advanced anti-counterfeiting techniques to seek for a good technical solution. An anti-counterfeiting system normally binds a product with a digital identifier, which per se is encoded by a physical identifier. The physical identifier then is attached with the product. If the physical identifier(More)