Gradient vector flow （GVF） is an effective external force for active contours, but its iso- tropic nature handicaps its performance. The recently proposed gradient vector flow in the normal direction （NGVF） is anisotropic since it only keeps the diffusion along the normal direction of the isophotes; however, it has difficulties forcing a snake into long, thin boundary indentations. In this paper, a novel external force for active contours called normally generalized gradient vector flow （NGGVF） is proposed, which generalizes the NGVF formulation to include two spatially varying weighting functions. Consequently, the proposed NGGVF snake is anisotropic and would improve ac- tive contour convergence into long, thin boundary indentations while maintaining other desirable properties of the NGVF snake, such as enlarged capture range, initialization insensitivity and good convergence at concavities. The advantages on synthetic and real images are demonstrated.
Software aging is a phenomenon observed in a software application executing continuous- ly for a long period of time, where the state of software degrades and leads to performance degrada- tion, hang/crash failures or both. A technique named rejuvenation was proposed to counteract this problem. Rejuvenation in period is not a good idea, because the speed of software aging is not constant, but variable. The key to find an optimal timing to resist aging problem is how to analyze/fore- cast the resource consumption of aging system. An ARIMA model is applied to forecast resource con- sumption due to software aging in a running web server. First, order and parameters of ARIMA model need to be identified. Second, it needs to be checked whether the model satisfies stationarity and reversibility. Finally, ARIMA model is used to predict resource consumption. The experiment results indicate that ARIMA model can do better than ANN model and SVM model in the forecasts of available memory and heap memory.
