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Linear discriminant analysis (LDA) is well known as a powerful tool for discriminant analysis. In the case of a small training data set, however, it cannot directly be applied to high-dimensional data. This case is the so-called small-sample-size or undersampled problem. In this paper, we propose an exponential discriminant analysis (EDA) technique to(More)
Fasudil is believed to be at least equally effective as nimodipine for the prevention of cerebral vasospasm and subsequent ischemic injury in patients undergoing surgery for subarachnoid hemorrhage (SAH). We report the final results of a randomized, open trial to compare the efficacy and safety of fasudil with nimodipine. A total of 63 patients undergoing(More)
The most expressive way human display emotion is through facial expressions. Facial expression recognition is necessary for designing any practical human-machine interfaces. This paper proposes a novel framework to real-time facial expression recognition within the interactive computer environment. The two major contributions of this work are: first, we(More)
Wireless channels usually face bursty errors, i.e., errors are prone to occur in clusters. These bit errors can be mod-eled using the Gilbert-Elliott model. When data packets are transferred over channels with bursty errors, packet error statistics are more important than bit error statistics to analyze the communication performance. This has been modeled(More)
Although there is uncertainty about whether extracranial-intracranial arterial bypass is useful for the treatment of steno-occlusive cerebrovascular disease in general, there is some argument for its continued use in particular patients. In the present study, we evaluated the efficacy of superficial temporal artery-middle cerebral artery (STA-MCA)(More)
Contrary to the traditional view that receptive fields are limited in spatial extent, recent studies have indicated that the response of neurons to a local stimulus within the receptive field can be modulated by stimulation of the surrounding region. Here we quantified the nature of these contextual effects on visual motion responses of neurons in the(More)
A novel neural network-based strategy is proposed and developed for the direct identification of structural parameters (stiffness and damping coefficients) from the time-domain dynamic responses of an object structure without any eigenvalue analysis and extraction and optimization process that is required in many identification algorithms for inverse(More)
Collagen type I scaffolds are commonly used due to its abundance, biocompatibility, and ubiquity. Most applications require the scaffolds to operate under mechanical stresses. Therefore understanding and being able to control the structural-functional integrity of collagen scaffolds becomes crucial. Using a combined experimental and modeling approach, we(More)