TCQ Practical Evaluation in the Hyper-Cube Watermarking Framework

International audienceThe Hyper-Cube watermarking has shown a high potential for high-rate robust watermarking. In this paper, we carry on the study and the evaluation of this quantization-based approach. We especially focus on the use of a Trellis Coded Quantization (TCQ) and its impact on the Hyper-Cube performances. First, we recall the TCQ functioning principle andwe propose adapted quantizers. Second, we analyze the integration of the TCQ module in a cascade of two coders (resp. two decoders). Finally, we experimentally compare the proposed approach with the state-of-the-art of high-rate watermarking schemes. The obtained results show that our Multi-Hyper-Cube scheme always provides good average performance

Fast implementation of model predictive control with guaranteed performance

A fast implementation of a given predictive controller for nonlinear systems is introduced through a piecewise constant approximate function defined over an hyper-cube partition of the system state space. Such a state partition is obtained by maximizing the hyper-cube volumes in order to guarantee, besides stability, an a priori fixed trajectory error as well as input and state constraints satisfaction. The presented approximation procedure is achieved by solving a set of nonconvex polynomial optimization problems, whose approximate solutions are computed by means of semidefinite relaxation techniques for semialgebraic problems

THE DESIGN AND IMPLEMENTATION OF OLAP SYSTEM. CASE STUDY – UNIVERSITY RESEARCH

The aim of this study is to show that multidimensional modelling of existing data in organizations, depending on the topics of interest of managers and multidimensional view of data. It may also provide an effective informational support of managers in decision making, regardless of field of activity. To prove it, this study will design a data model and an OLAP multidimensional analysis of scientific research in education university.OLAP, hyper - cube, n-dimensional cube, conceptual model

Scaling Dynamics of Domain Walls in the Cubic Anisotropy Model

We have investigated the dynamics of domain walls in the cubic anisotropy model. In this model a global O(N) symmetry is broken to a set of discrete vacua either on the faces, or vertices of a (hyper)cube. We compute the scaling exponents for $2\le N\le 7$ in two dimensions on grids of $2048^2$ points and compare them to the fiducial model of $Z_2$ symmetry breaking. Since the model allows for wall junctions lattice structures are locally stable and modifications to the standard scaling law are possible. However, we find that since there is no scale which sets the distance between walls, the walls appear to evolve toward a self-similar regime with $L\sim t$.Comment: 16 pages, 12 figure

Software Project Scheduling using the Hyper-Cube Ant Colony Optimization algorithm

U radu se daje prijedlog dizajna paradigme algoritma za optimizaciju kolonije mrava primjenom Hyper-Cube sustava za rješenje problema programiranja računarskog projekta (Software Project Scheduling Problem). Taj se NP-hard problem sastoji od davanja zaduženja zaposlenicima u svrhu smanjenja trajanja projekta i njegovih ukupnih troškova. To zaduženje mora zadovoljiti ograničenja problema i pitanje prvenstva među zadacima. Pristup prikazan ovdje koristi Hyper-Cube sustav za uspostavljanje eksplicitno multidimenzionalnog prostora za kontrolu ponašanja mravi. Time nam se omogućava autonomno vođenje istraživanja u cilju pronalaženja ohrabrujućih rješenja.This paper introduces a proposal of design of Ant Colony Optimization algorithm paradigm using Hyper-Cube framework to solve the Software Project Scheduling Problem. This NP-hard problem consists in assigning tasks to employees in order to minimize the project duration and its overall cost. This assignment must satisfy the problem constraints and precedence between tasks. The approach presented here employs the Hyper-Cube framework in order to establish an explicitly multidimensional space to control the ant behaviour. This allows us to autonomously handle the exploration of the search space with the aim of reaching encouraging solutions

Monotonicity and error bounds for networks of Erlang loss queues

Networks of Erlang loss queues naturally arise when modelling finite communication systems without delays, among which, most notably\ud (i) classical circuit switch telephone networks (loss networks) and\ud (ii) present-day wireless mobile networks.\ud \ud Performance measures of interest such as loss probabilities or throughputs can be obtained from the steady state distribution. However, while this steady state distribution has a closed product form expression in the first case (loss networks), it has not in the second case due to blocked (and lost) handovers. Product form approximations are therefore suggested. These approximations are obtained by a combined modification of both the state space (by a hyper cubic expansion) and the transition rates (by extra redial rates). It will be shown that these product form approximations lead to\ud \ud - secure upper bounds for loss probabilities and\ud - analytic error bounds for the accuracy of the approximation for various performance measures.\ud \ud The proofs of these results rely upon both monotonicity results and an analytic error bound method as based on Markov reward theory. This combination and its technicalities are of interest by themselves. The technical conditions are worked out and verified for two specific applications:\ud \ud - pure loss networks as under (i)\ud - GSM-networks with fixed channel allocation as under (ii).\ud \ud The results are of practical interest for computational simplifications and, particularly, to guarantee blocking probabilities not to exceed a given threshold such as for network dimensioning.\u

Design of Experiments: An Overview

Design Of Experiments (DOE) is needed for experiments with real-life systems, and with either deterministic or random simulation models. This contribution discusses the different types of DOE for these three domains, but focusses on random simulation. DOE may have two goals: sensitivity analysis including factor screening and optimization. This contribution starts with classic DOE including 2k-p and Central Composite designs. Next, it discusses factor screening through Sequential Bifurcation. Then it discusses Kriging including Latin Hyper cube Sampling and sequential designs. It ends with optimization through Generalized Response Surface Methodology and Kriging combined with Mathematical Programming, including Taguchian robust optimization.simulation;sensitivity analysis;optimization;factor screening;Kriging;RSM;Taguchi