Distinguishing video quality through differential matrices

Multicast multi-layered communications must implement efficient control algorithms to address undesirable network behaviors. This paper proposes two multi-metric algorithms for computing the rates of the video layers and improve the global video quality of a multicast session. In fact, we show that a single-metric approach may degrade some network parameters without obtaining any substantial improvements. Our first algorithm combines three metrics and a set of weights in such a way that one metric can be prioritized. This leads to an improved quality of multicast sessions, as we show through a number of experiments. In networks where the available resources are highly variable, however, the stability of the video quality is compromised if absolute values of the metrics are adopted. We then propose a second algorithm that uses the relative values of the metrics on a per-entry basis. Computation of the global quality of the multicast session is based on a differential matrix that stores the metrics for each receiver. This scheme takes into account the dynamics of the available resources and the heterogeneity of receivers. The great benefit of this approach is that the global video quality is always improved for every loop of the algorithm.     

The First Report on Scheme Revisited

Higher-Order and Symbolic Computation -     

Quantitative and reliable in vitro method combining scanning electron microscopy and image analysis for the screening of osteotropic modulators

The increased generation and up-regulated activity of bone resorbing cells (osteoclasts) play a part in the impairment of bone remodeling in many bone diseases. Numerous drugs (bisphosphonates, calcitonin, selective estrogen receptor modulators) have been proposed to inhibit this increased osteoclastic activity. In this report, we describe a pit resorption assay quantified by scanning electron microscopy coupled with image analysis. Total rabbit bone cells with large numbers of osteoclasts were cultured on dentin slices. The whole surface of the dentin slice was scanned and both the number of resorption pits and the total resorbed surface area were measured. Resorption pits appeared at 48 h and increased gradually up to 96 h. Despite the observation of a strong correlation between the total resorption area and the number of pits, we suggest that area measurement is the most relevant marker for osteoclastic activity. Osteotropic factors stimulating or inhibiting osteoclastic activity were used to test the variations in resorption activity as measured with our method. This reproducible and sensitive quantitative method is a valuable tool for screening for osteoclastic inhibitors and, more generally, for investigating bone modulators.     

INFORMATION AND SELF-ORGANIZATION REVISITED VIA COMPLEX-VALUED FRACTIONAL BROWNIAN MOTION OF ORDER n

Haken obtained many interesting results on information and self-organization by using Jaynes' maximum entropy principle with constraints in the form of given values of state moments up to the fourth order. The basic contention of this approach lies on the selection of these constraints, for the very reason that the result so obtained depended heavily upon them. The mean values of the state moments are quite acceptable and understandable, but why not the fifth one? In this paper, it is shown that the use of complex valued fractional Brownian motion of order n can contribute to answering this question. In addition, one examines how Haken's results are modified when the disturbing random term is not a Gaussian white noise, but a fractional Gaussian white noise of order n. The effect of such a noise on the stability of dynamical systems is analyzed. The key is that one has to consider much more state moments than when one works with Gaussian white noise.     

A semi‐adaptive control approach to closed‐loop medication infusion

This paper presents a semi‐adaptive control approach to closed‐loop medication infusion problems. The rationale underlying this approach is to design a controller that can adapt model parameters with a large impact on the model's fidelity while fixing the remaining parameters at nominal values. In this paper, a control‐oriented model for this purpose is derived via system identification and sensitivity analysis of a low‐order model capturing the direct dose‐response relationship Using the model thus derived, a model‐reference adaptive controller and a composite adaptive controller are designed and compared with each other. In‐silico simulation results using remifentanil's effect on respiratory rate as an example indicate that both controllers can regulate the output at commanded set points. Copyright © 2016 John Wiley & Sons, Ltd.