Effective bandwidth estimation and testing for Markov sources

This work addresses the resource sharing problem in broadband communication networks that can guarantee some quality of service (QoS), and develops some results about data source and traffic modelling, especially in aspects of model testing and parameter estimation. The multiplexing of variable bit rate (VBR) sources poses a mathematical and statistical problem: the estimation of the resource requirements of a source or set of sources. The estimation method shall be simple enough to be practically implemented in the connection acceptance control (CAC) function.

In this paper, the VBR video sources are taken as a typical case of variable rate, with real-time constraints. This association of requirements makes the case especially interesting. A Markov model is assumed for the VBR sources. The validity of such models is under research; they seem to be appropriate at least in certain time scales. The model is tested against real video traces. In order to estimate the resource allocation or “channel occupation” of each source, the concept of equivalent bandwidth proposed by Kelly [Notes on effective bandwidth, in: F.P. Kelly, S. Zachary, I.B. Ziedins (Eds.), Stochastic Networks: Theory and Applications, Oxford University Press, Oxford, 1996, pp. 141] is used; it is based on a consistent mathematical theory, and has proven to be robust and useful for technical applications.

A calculation of the equivalent bandwidth of a Markov source, given its parameters, can be found in the literature [IEEE ACM Trans. Networking 1 (4) (1993) 424]. But in fact, one can only estimate model and parameters. In this work, an estimation of the equivalent bandwidth is given, which can be obtained from real data. The convergence and the consistency of the estimation are studied, and practical bounds are found. Illustrative calculations are performed from real video traces that were obtained using a software MPEG coder, developed by the authors. The mathematical and statistical results are valid for whatever phenomenon that can be modelled as a Markov process.     

Stronger Lempel-Ziv Based Compressed Text Indexing

Given a text T[1..u] over an alphabet of size σ, the full-text search problem consists in finding the occ occurrences of a given pattern P[1..m] in T. In indexed text searching we build an index on T to improve the search time, yet increasing the space requirement. The current trend in indexed text searching is that of compressed full-text self-indices, which replace the text with a more space-efficient representation of it, at the same time providing indexed access to the text. Thus, we can provide efficient access within compressed space. The Lempel-Ziv index (LZ-index) of Navarro is a compressed full-text self-index able to represent T using 4uH _k (T)+o(ulog?σ) bits of space, where H _k (T) denotes the k-th order empirical entropy of T, for any k=o(log? _σ u). This space is about four times the compressed text size. The index can locate all the occ occurrences of a pattern P in T in O(m ³log?σ+(m+occ)log?u) worst-case time. Although this index has proven very competitive in practice, the O(m ³log?σ) term can be excessive for long patterns. Also, the factor 4 in its space complexity makes it larger than other state-of-the-art alternatives. In this paper we present stronger Lempel-Ziv based indices (LZ-indices), improving the overall performance of the original LZ-index. We achieve indices requiring (2+ε)uH _k (T)+o(ulog?σ) bits of space, for any constant ε>0, which makes them the smallest existing LZ-indices. We simultaneously improve the search time to O(m ²+(m+occ)log?u), which makes our indices very competitive with state-of-the-art alternatives. Our indices support displaying any text substring of length ? in optimal O(?/log? _σ u) time. In addition, we show how the space can be squeezed to (1+ε)uH _k (T)+o(ulog?σ) to obtain a structure with O(m ²) average search time for m≥2log? _σ u. Alternatively, the search time of LZ-indices can be improved to O((m+occ)log?u) with (3+ε)uH _k (T)+o(ulog?σ) bits of space, which is much less than the space needed by other Lempel-Ziv-based indices achieving the same search time. Overall our indices stand out as a very attractive alternative for space-efficient indexed text searching.     

A direct calculation of moments of the sample variance

A systematic method to deal with the interrelations of systems with multi-index quantities (random variables) is proposed. The method differs of the well-known Polykays. An application of the theoretical results here presented is the calculation of the moments of the sample variance for general populations in a direct way. The main advantage of the proposed methodology is that no conversion formulae and other complicated Polykays rules are needed. However, the proposed method is compatible with Polykays philosophy and conversion formulae and multiplication rules can be derived by using the theoretical results of this work. For practical purposes, two algorithms for the calculation of the moments of the sample variance are proposed.     

t-Spanners for metric space searching

The problem of Proximity Searching in Metric Spaces consists in finding the elements of a set which are close to a given query under some similarity criterion. In this paper we present a new methodology to solve this problem, which uses a t-spanner G′(V, E) as the representation of the metric database. A t-spanner is a subgraph G′(V, E) of a graph G(V, A), such that E  A and G′ approximates the shortest path costs over G within a precision factor t.

Our key idea is to regard the t-spanner as an approximation to the complete graph of distances among the objects, and to use it as a compact device to simulate the large matrix of distances required by successful search algorithms such as AESA. The t-spanner properties imply that we can use shortest paths over G′ to estimate any distance with bounded-error factor t.

For this sake, several t-spanner construction, updating, and search algorithms are proposed and experimentally evaluated. We show that our technique is competitive against current approaches. For example, in a metric space of documents our search time is only 9% over AESA, yet we need just 4% of its space requirement. Similar results are obtained in other metric spaces.

Finally, we conjecture that the essential metric space property to obtain good t-spanner performance is the existence of clusters of elements, and enough empirical evidence is given to support this claim. This property holds in most real-world metric spaces, so we expect that t-spanners will display good behavior in most practical applications. Furthermore, we show that t-spanners have a great potential for improvements.     

Functional stabilization of unstable fixed points: Human pole balancing using time-to-balance information.

Humans are often faced with tasks that require stabilizing inherently unstable situations. The authors explored the dynamics of human functional stabilization by having participants continually balance a pole until a minimum time criterion was reached. Conditions were manipulated with respect to geometry, mass, and characteristic "fall time" of the pole. Distributions of timing between pole and hand velocities showed strong action–perception coupling. When actions demonstrated a potential for catastrophic failure, the period of hand oscillation correlated well with the perceptual quantity "time to balance" (τbal = θ/θ?), but not other quantities such as θ and θ? alone. This suggests that participants were using available τbal information during critical conditions, although they may not have been attending to this type of perceptual information during typical, noncritical motions of successful performance. In a model analysis and simulation, the authors showed how discrete τbal information may be used to adjust the parameters of a controller to perform this task. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Flow Intensity Parameter in Pier Scour Experiments

Technical note discusses a detailed approach to dimensional analysis for the bridge pier scour phenomenon and the introduction of flow intensity. It demonstrates the dependence of critical upstream velocity on the rest of the parameters describing the process and its implications on dimensional analysis. Assuming that the viscous effects are negligible in the local scour phenomenon, it is concluded that the flow intensity of the approaching undisturbed flow is not an adequate parameter to describe the process in usual laboratory conditions. A new proposal is established.     

Long short-term cognitive networks

Neural Computing and Applications - In this paper, we present a recurrent neural system named long short-term cognitive networks (LSTCNs) as a generalization of the short-term cognitive network...     

Insights on Aliasing Driven Instabilities for Advection Equations with Application to Gauss–Lobatto Discontinuous Galerkin Methods

We analyse instabilities due to aliasing errors when solving one dimensional non-constant advection speed equations and discuss means to alleviate these types of errors when using high order discontinuous Galerkin (DG) schemes. First, we compare analytical bounds for the continuous and discrete version of the PDEs. Whilst traditional \(L^2\) norm energy bounds applied to the discrete PDE do not always predict the physical behaviour of the continuous version of the equation, more strict elliptic norm bounds correctly bound the behaviour of the continuous PDE. Having derived consistent bounds, we analyse the effectiveness of two stabilising techniques: over-integration and split form variations (conservative, non-conservative and skew-symmetric). Whilst the former is shown to not alleviate aliasing in general, the latter ensures an aliasing-free solution if the splitting form of the discrete PDE is consistent with the continuous equation. The success of the split form de-aliasing is restricted to DG schemes with the summation-by-parts simultaneous-approximation-term properties (e.g. DG with Gauss–Lobatto points). Numerical experiments are included to illustrate the theoretical findings.     

Monte Carlo uncertainty analysis of an ANN-based spectral analysis method

Neural Computing and Applications - This work presents the uncertainty analysis of an artificial neural network (ANN)-based method, called multiharmonic ANN fitting method (MANNFM), which is able...     

Combining Support Vector Machines and simulated annealing for stereovision matching with fish eye lenses in forest environments

We present a novel strategy for computing disparity maps from omni-directional stereo images obtained with fish-eye lenses in forest environments. At a first segmentation stage, the method identifies textures of interest to be either matched or discarded. Two of them are identified by applying the powerful Support Vector Machines approach. At a second stage, a stereovision matching process is designed based on the application of four stereovision matching constraints: epipolarity, similarity, uniqueness and smoothness. The epipolarity guides the process. The similarity and uniqueness are mapped once again through the Support Vector Machines, but under a different way to the previous case; after this an initial disparity map is obtained. This map is later filtered by applying the Discrete Simulated Annealing framework where the smoothness constraint is conveniently mapped. The combination of the segmentation and stereovision matching approaches makes the main contribution. The method is compared against the usage of simple features and combined similarity matching strategies.