28,666 research outputs found

    Self-diffusion in remodelling and growth

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    Self-diffusion, or the flux of mass of a single species within itself, is viewed as an independent phenomenon amenable to treatment by the introduction of an auxiliary field of diffusion velocities. The theory is shown to be heuristically derivable as a limiting case of that of an ordinary binary mixture

    Social Conformity Despite Individual Preferences for Distinctiveness

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    We demonstrate that individual behaviors directed at the attainment of distinctiveness can in fact produce complete social conformity. We thus offer an unexpected generative mechanism for this central social phenomenon. Specifically, we establish that agents who have fixed needs to be distinct and adapt their positions to achieve distinctiveness goals, can nevertheless self-organize to a limiting state of absolute conformity. This seemingly paradoxical result is deduced formally from a small number of natural assumptions, and is then explored at length computationally. Interesting departures from this conformity equilibrium are also possible, including divergence in positions. The effect of extremist minorities on these dynamics is discussed. A simple extension is then introduced, which allows the model to generate and maintain social diversity, including multimodal distinctiveness distributions. The paper contributes formal definitions, analytical deductions, and counterintuitive findings to the literature on individual distinctiveness and social conformity.Comment: 11 pages, 6 figures, appendi

    Effects of Aprons on Pitfall Trap Catches of Carabid Beetles in Forests and Fields

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    This study compared the efficacy of three types of pitfall traps in four forest and two field habitats. Two traps had aprons and one did not. The two apron traps were the same except for a gap between the trap and the plywood-apron, allowing captures from above or below. Traps were placed in a split-plot design and had three replicates of the three trap types per habitat. The traps were emptied each week from May to September. ANOVA\u27s were performed on 12 trapped species separately over habitats, weeks, and the in- teractions between them. The nonapron trap captured over 40% more individuals than either apron trap, though apron traps tended to be more effective in fields for species found in both habitats. Habitat-trap interactions were only significant in two species. Trap-week interactions were significant in four species

    Estimation Schemes for Networked Control Systems Using UDP-Like Communication

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    In this work we consider a class of networked control systems (NCS) when the control signal is sent to the plant via a UDP-like communication protocol, the controller sends a communication packet to the plant across a lossy network but the controller does not receive any acknowledgement signal indicating the status of reception/delivery of the control packet. Standard observer based estimators assume the estimator has knowledge of what control signal is applied to the plant, but under the UDP-like communication scheme the estimator does not know what control is applied. Continuing previous work, we present a simple estimation algorithm consisting of a state estimator and mode observer. For single input systems we can add an extra control signal that guarantees recovery of the fate of the control packet. Using a modified state feedback with the added input we can guarantee the estimation error is bounded as is the expected value of the state. This extra input is removed and sufficient conditions on the system properties are given to assure the estimation remain bounded. Comparisons are made between the algorithm presented and the method of unknown input observer. Simulations are provided to demonstrate the algorithm

    Kalman Filtering Over A Packet Dropping Network: A Probabilistic Approach

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    We consider the problem of state estimation of a discrete time process over a packet dropping network. Previous pioneering work on Kalman filtering with intermittent observations is concerned with the asymptotic behavior of E[P_k], i.e., the expected value of the error covariance, for a given packet arrival rate. We consider a different performance metric, Pr[P_k ≤ M], i.e., the probability that P_k is bounded by a given M, and we derive lower and upper bounds on Pr[P_k ≤ M]. We are also able to recover the results in the literature when using Pr[P_k ≤ M] as a metric for scalar systems. Examples are provided to illustrate the theory developed in the paper

    On Colorful Bin Packing Games

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    We consider colorful bin packing games in which selfish players control a set of items which are to be packed into a minimum number of unit capacity bins. Each item has one of m2m\geq 2 colors and cannot be packed next to an item of the same color. All bins have the same unitary cost which is shared among the items it contains, so that players are interested in selecting a bin of minimum shared cost. We adopt two standard cost sharing functions: the egalitarian cost function which equally shares the cost of a bin among the items it contains, and the proportional cost function which shares the cost of a bin among the items it contains proportionally to their sizes. Although, under both cost functions, colorful bin packing games do not converge in general to a (pure) Nash equilibrium, we show that Nash equilibria are guaranteed to exist and we design an algorithm for computing a Nash equilibrium whose running time is polynomial under the egalitarian cost function and pseudo-polynomial for a constant number of colors under the proportional one. We also provide a complete characterization of the efficiency of Nash equilibria under both cost functions for general games, by showing that the prices of anarchy and stability are unbounded when m3m\geq 3 while they are equal to 3 for black and white games, where m=2m=2. We finally focus on games with uniform sizes (i.e., all items have the same size) for which the two cost functions coincide. We show again a tight characterization of the efficiency of Nash equilibria and design an algorithm which returns Nash equilibria with best achievable performance
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