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This paper considers the real-time power quality monitoring in power grid systems. The goal is to detect the occurrence of disturbances in the nominal sinusoidal voltage/current signal as quickly as possible such that protection measures can be taken in time. Based on an autoregressive (AR) model for the disturbance, we propose a generalized local likelihood ratio (GLLR) detector which processes meter readings sequentially and alarms as soon as the test statistic exceeds a prescribed threshold. The proposed detector not only reacts to a wide range of disturbances, but also achieves lower detection delay compared to the conventional block processing method. Then we further propose to deploy multiple meters to monitor the power signal cooperatively. The distributed meters communicate wirelessly to a central meter, where the data fusion and detection are performed. In light of the limited bandwidth of wireless channels, we develop a level-triggered sampling scheme, where each meter transmits only one-bit each time asynchronously. The proposed multi-meter scheme features substantially low communication overhead, while its performance is close to that of the ideal case where distributed meter readings are perfectly available at the central meter.

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It is a robust and efficient method that utilizes morphological operators, and Otsu threshold together with GIS road vector to detect vehicles from high resolution highway aerial images.Our previous experiments showed that the method resulted in a high correctness, completeness, and quality. However, we did not discuss the relation between the accuracy and the size of structure element for vehicle detection with high resolution highway aerial images. The space resolution of our aerial images is 0.15×0.15m, and most vehicles' size is normally 5×2m, approaching 34×14 pixels. Thus, we selected a disc as structure element, but the disc's radius should be less than 7 pixels. We compared the vehicle detection accuracy with 3 pixels, 4 pixels, 5 pixels, 6 pixels, and 7 pixels of disc with different size. Our result showed that the radius with 5 pixels or 6 pixels obtained the highest accuracy.Index Terms-Vehicle detection, size of structure element, morphological operators.