Composites realized by hand lay-up process in a civil engineering environment: initial properties and durability

The repair, the reinforcement as well as the setting in safety of buildings and existing reinforced and/or pre-stressed concrete structure is a real technological stake and a socio-economic problem for the near future. The introduction of composites in civil engineering is an interesting answer to these goals, but they brought an important amount of new problems that have to be solved for safe structural applications under combined mechanical and environmental loadings. In fact during the past five years, we have witnessed exponential growth in research or field demonstrations of fiber-reinforced composites in civil engineering. Manufacturers and designers have now access to a wide range of composite materials. However, they face great problems with forecasting the reliability of composite materials. Their introduction in civil engineering applications is a difficult operation due to working environment and weathering conditions. The objective of this paper is to study the effect of these conditions and their consequences on the mechanical properties of the final composite. An analysis of the rheological (viscoelastic) properties was carried out in order to observe the glass transition temperature evolution according to reactive mixture stoichiometry and weathering conditions.     

Quantitative analysis of location management and QoS in wireless networks

As a fundamental component in wireless networks, location management consists of two operations: location update and paging. These two supplementary operations enable the mobile user ubiquitous mobility. However, in case of failed location update, a significant consequence is the obsolete location identity in the network databases and thereafter the incapability in establishing the valid route for the potential call connection, which will seriously degrade the network quality-of-service (QoS). This issue is not theoretically studied in the literature. In this paper, we perform a quantitative analysis of the location management effect on QoS in the wireless networks. The metrics call blocking probability and the average number of blocked calls are introduced to reflect the QoS. For the sake of general applicability, the performance metrics are formulated with the relaxed tele-traffic parameters. Namely, the call inter-arrival time, cell residence time, location area residence time and location update inter-arrival time follow a general probability density function. The formulae are additionally specified in the static and several dynamic location management mechanisms. Numerical examples are presented to show the interaction between the performance metrics and location management schemes. The discussions on the sensitivity of tele-parameters are also given.     

The use of fuzzy logic and neural networks models for sensory properties prediction from process and structure parameters of knitted fabrics

In a competitive business environment, the textile industrialists intend to propose diversified products according to consumers preference. For this purpose, the integration of sensory attributes in the process parameters choice seems to be a useful alternative. This paper provides fuzzy and neural models for the prediction of sensory properties from production parameters of knitted fabrics. The prediction accuracy of these models was evaluated using both the root mean square error (RMSE) and mean relative percent error (MRPE). The results revealed the models ability to predict tactile sensory attributes based on the production parameters. The comparison of the prediction performances showed that the neural models are slightly powerful than the fuzzy models.     

A security management scheme for failure detector distributed systems based on self-tuning control theory

Information security management has become an important research issue in distributed systems, and the detection of failures is a fundamental issue for fault tolerance in large distributed systems. Recently, many people have come to realize that failure detection ought to be provided as some form of generic service, similar to IP address lookup. However, this has not been successful so far; one of the reasons being the fact that classical failure detectors were not designed to satisfy several application requirements simultaneously. More specifically, traditional implementations of failure detectors are often tuned for running over local networks and fail to address some important problems found in wide-area distributed systems with a large number of monitored components, such as Grid systems. In this paper, we study the security management scheme for failure detector distributed systems. We first identify some of the most important QoS problems raised in the context of large wide-area distributed systems. Then we present a novel failure detector scheme combined with self-tuning control theory that can help in solving or optimizing some of these problems. Furthermore, this paper discusses the design and analysis of implementing a scalable failure detection service for such large wide-area distributed systems considering dynamically adjusting the heartbeat streams, so that it satisfies the bottleneck router requirements. The basic z-transformation stability test is used to achieve the stability criterion, which ensures the bounded rate allocation without steady state oscillation. We further show how the online failure detector control algorithm can be used to design a controller, analyze the theoretical aspects of the proposed algorithm and verify its agreement with the simulations in the LAN and WAN case. Simulation results show the efficiency of our scheme in terms of high utilization of the bottleneck link, fast response and good stability of the bottleneck router buffer occupancy as well as of the controlled sending rates. In conclusion, the new security management failure detector algorithm provides a better QoS than an algorithm that is proposed by Stelling et al. (Proceedings of 7th IEEE symposium on high performance distributed computing, pp. 268–278, 1998), Foster et al. (Int J Supercomput Appl, 2001).     

A Sketch-Based Interface for Clothing Virtual Characters

This interactive system for garment creation determines a garment's shape and how the character wears it based on a user-drawn sketch. The system then uses distances between the 2D garment silhouette and the character model to infer remaining distance variations in 3D     

Parallel Training of An Improved Neural Network for Text Categorization

This paper studies parallel training of an improved neural network for text categorization. With the explosive growth on the amount of digital information available on the Internet, text categorization problem has become more and more important, especially when millions of mobile devices are now connecting to the Internet. Improved back-propagation neural network (IBPNN) is an efficient approach for classification problems which overcomes the limitations of traditional BPNN. In this paper, we utilize parallel computing to speedup the neural network training process of IBPNN. The parallel IBNPP algorithm for text categorization is implemented on a Sun Cluster with 34 nodes (processors). The communication time and speedup for the parallel IBPNN versus various number of nodes are studied. Experiments are conducted on various data sets and the results show that the parallel IBPNN together with SVD technique achieves fast computational speed and high text categorization correctness.     

A parallel algorithm for approximate regularity

Spatial regularity amidst a seemingly chaotic image is often meaningful. Many papers in computational geometry are concerned with detecting some type of regularity via exact solutions to problems in geometric pattern recognition. However, real-world applications often have data that is approximate, and may rely on calculations that are approximate. Thus, it is useful to develop solutions that have an error tolerance.

A solution has recently been presented by Robins et al. [Inform. Process. Lett. 69 (1999) 189–195] to the problem of finding all maximal subsets of an input set in the Euclidean plane that are approximately equally-spaced and approximately collinear. This is a problem that arises in computer vision, military applications, and other areas. The algorithm of Robins et al. is different in several important respects from the optimal algorithm given by Kahng and Robins [Patter Recognition Lett. 12 (1991) 757–764] for the exact version of the problem. The algorithm of Robins et al. seems inherently sequential and runs in O(n^5/2) time, where n is the size of the input set. In this paper, we give parallel solutions to this problem.     

Scalable Parallel Algorithms for Geometric Pattern Recognition

This paper considers a variety of geometric pattern recognition problems on input sets of size n using a coarse grained multicomputer model consisting of p processors with Ω(n/p) local memory each (i.e., Ω(n/p) memory cells of Θ(log n) bits apiece), where the processors are connected to an arbitrary interconnection network. It introduces efficient scalable parallel algorithms for a number of geometric problems including the rectangle finding problem, the maximal equally spaced collinear points problem, and the point set pattern matching problem. All of the algorithms presented are scalable in that they are applicable and efficient over a very wide range of ratios of problem size to number of processors. In addition to the practicality imparted by scalability, these algorithms are easy to implement in that all required communications can be achieved by a small number of calls to standard global routing operations.