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Many research efforts for image encryption schemes have elaborated for designing nonlinear functions since security of these schemes closely depends on inherent characteristics of non-linear functions. It is commonly believed that a chaotic map can be used as a good candidate of a nonlinear component for image encryption schemes. We propose a new image(More)
BACKGROUND EGb761, a standardized Ginkgo biloba extract, has antioxidant and antiplatelet aggregation and thus might protect against atherosclerosis. However, molecular and functional properties of EGb761 and its major subcomponents have not been well characterized. We investigated the effect of EGb761 and its major subcomponents (bilobalide, kaemferol, and(More)
BACKGROUND Fat accumulation in android compartments may confer increased metabolic risk. The incremental utility of measuring regional fat deposition in association with metabolic syndrome (MS) has not been well described particularly in an elderly population. METHODS AND FINDINGS As part of the Korean Longitudinal Study on Health and Aging, which is a(More)
OBJECTIVE We investigated the prevalence of sarcopenic obesity (SO) and its relationship with metabolic syndrome in a community-based elderly cohort in Korea. RESEARCH DESIGN AND METHODS In this study, 287 men and 278 women aged 65 or older were recruited. Sarcopenia was defined as the appendicular skeletal muscle mass (ASM) divided by height squared(More)
Single molecule tracking is widely used to monitor the change in position of lipids and proteins in living cells. In many experiments in which molecules are tagged with a single or small number of fluorophores, the signal/noise ratio may be limiting, the number of molecules is not known, and fluorophore blinking and photobleaching can occur. All these(More)
We present a general method called dynamic single-molecule colocalization for quantitating the associations of single cell surface molecules labeled with distinct autofluorescent proteins. The chief advantages of the new quantitative approach are that, in addition to stable interactions, it is capable of measuring nonconstitutive associations, such as those(More)
Adaptive classification is a key function of Brain Computer Interfacing (BCI) systems. This paper proposes robust mathematical frameworks and their implementation for the on-line sequential classification of EEG signals in BCI systems. The proposed algorithms are extensions to the basic method of Andrieu et al. [Andrieu, C., de Freitas, N., and Doucet, A.(More)
—This paper proposes a robust algorithm to adapt a model for EEG signal classification using a modified Extended Kalman Filter (EKF). By applying Bayesian conjugate priors and marginalis-ing the parameters, we can avoid the needs to estimate the covariances of the observation and hidden state noises. In addition, Laplace approximation is employed in our(More)