Scheduling links for heavy traffic on interfering routes in wireless mesh networks

We consider wireless mesh networks and the problem of scheduling the links of a given set of routes under the assumption of a heavy-traffic pattern. We assume some TDMA protocol provides a background of synchronized time slots and seek to schedule the routes’ links to maximize the number of packets that get delivered to their destinations per time slot. Our approach is to construct an undirected graph G and to heuristically obtain node multicolorings for G that can be turned into efficient link schedules. In G each node represents a link to be scheduled and the edges are set up to represent every possible interference for any given set of interference assumptions. We present two multicoloring-based heuristics and study their performance through extensive simulations. One of the two heuristics is based on relaxing the notion of a node multicoloring by dynamically exploiting the availability of communication opportunities that would otherwise be wasted. We have found that, as a consequence, its performance is significantly superior to the other’s.     

An Auto-Adaptive Multidomain Spectral Technique for Linear Stability Analysis: Application to Viscous Compressible Flows

An auto-adaptive multidomain pseudo-spectral technique is considered in order to solve the linear stability problem of viscous compressible flows. Both the locations of the interfaces and the parameters of the mappings in each subdomain are adapted by minimizing the H ² -norm of the calculated solution. Such method provides automatically—this is the key point—the best polynomial interpolation of the basic state the stability of which is studied. It turns out that the whole procedure is needed to obtain reliable results. The method is first validated against results available in the literature (both viscous incompressible and inviscid compressible Rayleigh–Taylor configurations). The efficiency of the numerical method is illustrated with results on the linear stability of the compressible viscous diffusive Rayleigh–Taylor flow where no analytical or numerical results are available. New results showing the influence of stratification, viscosity, diffusity between species and thermal diffusivity are presented.     

Stability Properties of Cerebellar Neural Networks: The Purkinje Cell — Climbing Fiber Dynamic Module

In the last few decades it has been proven, that the cerebellum takes part in learning the bulk of motor control. The mechanisms which provide such properties are still largely unknown, but an involvement of parallel fibers and climbing fibers in this process, as have been proposed decades ago in cerebellar learning theories, is now clear. Among difficulties of the learning theories is an evident necessity for spontaneous activity of the cerebellar climbing fibers [5]. Recently, the group of M. Mauk proposed an elegant explanation of this inconsistency [11, 12]. We present here a stochastic model of a cerebellar module, based on this new approach. Theoretical treatment yields some consequences for experimental verification. Besides an explanation of real cerebellar functions, the analyzed control system presents a new paradigm for neural network memorizing systems.     

Vision-based real estate price estimation

Since the advent of online real estate database companies like Zillow, Trulia and Redfin, the problem of automatic estimation of market values for houses has received considerable attention. Several real estate websites provide such estimates using a proprietary formula. Although these estimates are often close to the actual sale prices, in some cases they are highly inaccurate. One of the key factors that affects the value of a house is its interior and exterior appearance, which is not considered in calculating automatic value estimates. In this paper, we evaluate the impact of visual characteristics of a house on its market value. Using deep convolutional neural networks on a large dataset of photos of home interiors and exteriors, we develop a method for estimating the luxury level of real estate photos. We also develop a novel framework for automated value assessment using the above photos in addition to home characteristics including size, offered price and number of bedrooms. Finally, by applying our proposed method for price estimation to a new dataset of real estate photos and metadata, we show that it outperforms Zillow’s estimates.