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In this paper, we introduce Explicit Rate Adjustment (ERA), a new Multi-rate Multicast Congestion Control (MU-MCC) algorithm. Via ERA, the receiver explicitly adjusts its reception rate accordiug to the network conditions using the TCP throughput equation and Packet-pair Probe. The design goals are responsiveness, elliciency in network utilization, scalability and fairness (including inter-protocol fairness, intraprotocol fairness, intra-session fairness and TCP-friendliness) as well as simple implementation. We have built ERA into a network simulator (nsZ) and demonstrate via simulations that the goals are reached.

In this paper we present a novel scheme for modelling and tracking complex real life objects. The scheme uses multiple models based on a variation of the Point Distribution Model [1] known as the Vector Distribution Model [2]. Inter and intra-class variation is separated using a variation on Linear Discriminant Analysis known as 'Delta Analysis'. The tracking scheme is stochastic and is based on modelling model characteristics by a set of discrete probability distributions, which are updated in an iterative manner. Initialisation is performed using low level processing and a predictor is used to initialise characteristic probabilities on subsequent frames. This scheme has been applied to the task of tracking livestock in a realistic farmyard situation.

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