Discovery of Spatial Periodicities in a Coronal Loop Using Automated Edge-Tracking Algorithms

A new method for automated coronal loop tracking, in both spatial and temporal domains, is presented. Applying this technique to TRACE data, obtained using the 171 angstrom filter on 1998 July 14, we detect a coronal loop undergoing a 270 s kink-mode oscillation, as previously found by Aschwanden et al. However, we also detect flare-induced, and previously unnoticed, spatial periodicities on a scale of 3500 km, which occur along the coronal loop edge. Furthermore, we establish a reduction in oscillatory power for these spatial periodicities of 45% over a 222 s interval. We relate the reduction in detected oscillatory power to the physical damping of these loop-top oscillations.

‘Ghosts in the Head and Ghost Towns in the Field: Ethnography and the Experience of Presence and Absence’

This article is about an anthropologist coming to terms with the field and fieldwork. In 1995, I left – was evacuated from – my fieldsite as a volcanic eruption started just as my period of fieldwork drew to a close. These eruptions dramatically and instantaneously altered life on the island of Montserrat, a British colony in the Caribbean. While Montserrat the land, and Montserratians the people, migrated and moved on with their lives, Montserrat and Montserratians were preserved in my mind and in my anthropological writings as from “back home.” Revisiting Montserrat several years into the volcano crisis, I drove through the villages and roads leading to the former capital of the island, where I had worked from. My route to this modern-day Pompeii threw up a stark contrast between absence and presence, the imagined past and the experienced present. This is understood, in part, by examining the literary work of two other travelers through Montserrat, Henry Coleridge and Pete McCarthy, both of whom have a very different experience of the place and the people.

Multiple model bootstrap filter for maneuvering target tracking

The extension of the bootstrap filter to the multiple model target tracking problem is considered. Bayesian bootstrap filtering is a very powerful technique since it represents samples by random samples and is therefore not restricted to linear, Gaussian systems, making it ideal for the multiple model problem where very complex densities fan be generated.

Target Detection and Tracking With Heterogeneous Sensors

We present a multimodal detection and tracking algorithm for sensors composed of a camera mounted between two microphones. Target localization is performed on color-based change detection in the video modality and on time difference of arrival (TDOA) estimation between the two microphones in the audio modality. The TDOA is computed by multiband generalized cross correlation (GCC) analysis. The estimated directions of arrival are then postprocessed using a Riccati Kalman filter. The visual and audio estimates are finally integrated, at the likelihood level, into a particle filter (PF) that uses a zero-order motion model, and a weighted probabilistic data association (WPDA) scheme. We demonstrate that the Kalman filtering (KF) improves the accuracy of the audio source localization and that the WPDA helps to enhance the tracking performance of sensor fusion in reverberant scenarios. The combination of multiband GCC, KF, and WPDA within the particle filtering framework improves the performance of the algorithm in noisy scenarios. We also show how the proposed audiovisual tracker summarizes the observed scene by generating metadata that can be transmitted to other network nodes instead of transmitting the raw images and can be used for very low bit rate communication. Moreover, the generated metadata can also be used to detect and monitor events of interest.

Object tracking using SIFT features and mean shift

A scale invariant feature transform (SIFT) based mean shift algorithm is presented for object tracking in real scenarios. SIFT features are used to correspond the region of interests across frames. Meanwhile, mean shift is applied to conduct similarity search via color histograms. The probability distributions from these two measurements are evaluated in an expectation–maximization scheme so as to achieve maximum likelihood estimation of similar regions. This mutual support mechanism can lead to consistent tracking performance if one of the two measurements becomes unstable. Experimental work demonstrates that the proposed mean shift/SIFT strategy improves the tracking performance of the classical mean shift and SIFT tracking algorithms in complicated real scenarios.

Common input to different regions of biceps brachii long head

The purpose of the experiment was to compare the level of synchronization exhibited by pairs of motor units located within and between functionally distinct regions of the biceps brachii muscle. Pairs of single motor units were recorded from seven subjects using separate electrodes located in the lateral and medial aspects of the long head of biceps brachii. Participants were required to exert a combination of flexion and supination torques so that both motor units discharged at approximately 10 pps for a parts per thousand yen200 s and the level of motor unit synchronization could be quantified. When motor unit recordings were sufficiently stable at the completion of this synchrony task, a series of ramp contractions with multiple combinations of flexion and supination torques were performed to characterize the recruitment thresholds of the motor units. Common input strength (CIS) was significantly greater (P <0.01) for the within-region pairs of motor units (0.28 extra sync. imps/s, n = 26) than for the between-region pairs (0.13 extra sync. imps/s, n = 18), but did not differ significantly for the 12 within-region pairs from the lateral head and 14 from the medial head (0.27 vs. 0.29 extra sync. imps/s; P = 0.83). Recruitment thresholds were measured for 33 motor units, but there was only a weak association between CIS and the respective recruitment patterns for motor unit pairs (n = 9). The present investigation provides evidence of a differential distribution of synaptic input across the biceps brachii motor neuron pool, but this appears to have minimal association with the recruitment patterns for individual motor units.