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.     

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     

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.     

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.     

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.     

Effects of Botrytis cinerea infection on Champagne wine foaming properties

Qualitative effects of Botrytis cinerea infection were studied by comparing the foaming properties of Champagnes obtained from healthy grapes with those from grapes infected by B cinerea. This is of particular interest when it is considered that the foaming properties of Champagne wines are important in terms of product attractiveness for the consumer. Experiments using artificial viewing equipment clearly showed the dramatic effects on Champagne foam characteristics when grape berries were highly infected. The speed at which liquid separated from the foam (expressed as liquid height L_S) in the glass depended largely on the level of infection for Chardonnary and Pinot noir wines (+268% for Chardonnary wines at 40% infection and +627% for Pinot noir wines at 20% infection). B cinerea infection reduced the time (L_T) at which liquid first appeared in the glass; for Pinot noir wines an infection level of 20% caused very rapid drainage. The time of pouring (P_T, ie the time to fill the glass under controlled conditions) also diminished considerably at an infection level of 20% for both Pinot noir and Pinot meunier wines (?74 and ?58% respectively). Mouldiness considerably altered the foam height observed 80 s (H₈₀) after the start of pouring (?83% for Pinot noir and ?89% for Pinot meunier at 20% infection). Champagne foamability was also quantified using a sparging technique to standardise effervescence. Foamability suffered considerably (?60 to ?65%) when the B cinerea infection level was 20% as compared to control Champagnes. All wines studied had low and very similar protein contents. Differences in the concentrations of these compounds, which are generally implicated in the formation of foam in sparkling wines, could not explain the differences in Champagne foaming properties observed here. © 2001 Society of Chemical Industry