High char‐yielding poly[acrylonitrile‐co‐(itaconic acid)‐co‐(methyl acrylate)]: synthesis and properties

Polyacrylonitrile terpolymers of various compositions consisting of acrylonitrile (AN), itaconic acid (IA) and methyl acrylate (MA) were synthesized by solution polymerization in dimethylsulfoxide. Increase in concentration of either IA or MA retarded the overall polymerization rate and the polymer molecular weight. The system consisting of AN + MA and varying IA concentration was more prone to retardation in comparison with the system composed of AN + IA with variable MA concentration. The retardation factors were quantified. Minor quantities of MA boost the reactivity of IA in the terpolymer system. The terpolymer was richer in MA vis‐à‐vis the feed. The thermal characteristics of the terpolymer were examined as a function of its composition. In contrast to the copolymer of AN and IA requiring 1–1.5 mol% IA, the terpolymer required an IA content of approximately 2.5 mol% for optimum thermal stability. The polymer with 90 mol% AN, 2.5 mol% IA and 7.5 mol% MA exhibited reasonably good char‐forming characteristics and thermal stability. The overall crystallinity and crystallite size of the polymers were found to decrease on incorporation of the comonomers. The ‘aromatization index’ of the copolymer increased with the temperature of pyrolysis through re‐organization of the tetrahydropyridine ladder structure. Copyright © 2005 Society of Chemical Industry     

A stochastic realization algorithm via block LQ decomposition in Hilbert space

A stochastic realization problem of a stationary stochastic process is re-visited, and a new stochastically balanced realization algorithm is derived in a Hilbert space generated by second-order stationary processes. The present algorithm computes a stochastically balanced realization by means of the singular value decomposition of a weighted block Hankel matrix derived by a “block LQ decomposition”. Extension to a stochastic subspace identification method explains how the proposed abstract algorithm is implemented in system identification.     

Pedestrian detection and tracking at crossroads

This paper presents a system that can perform pedestrian detection and tracking using vision-based techniques. A very important issue in the field of intelligent transportation system is to prevent pedestrians from being hit by vehicles. Recently, a great number of vision-based techniques have been proposed for this purpose. In this paper, we propose a vision-based method, which combines the use of a pedestrian model as well as the walking rhythm of pedestrians to detect and track walking pedestrians. Through integrating some spatial and temporal information grabbed by a vision system, we are able to develop a reliable system that can be used to prevent traffic accidents happened at crossroads. In addition, the proposed system can deal with the occlusion problem. Experimental results obtained by executing some real world cases have demonstrated that the proposed system is indeed superb.     

An immune oriented multi-agent system for biological image processing

In this article, we present a parallel image processing system based on the concept of reactive agents. Our system lies in the oRis language, which allows to describe finely and simply the agents’ behaviors to detect image features. We also present a method of segmentation using a multi-agent system, and two biological applications made with oRis. The stopping of this multi-agent system is implemented through a technique issued from immunology: the apoptosis.     

Frequency domain identification of Wiener models

This paper proposes a frequency domain algorithm for Wiener model identifications based on exploring the fundamental frequency and harmonics generated by the unknown nonlinearity. The convergence of the algorithm is established in the presence of white noise. No a priori knowledge of the structure of the nonlinearity is required and the linear part can be nonparametric.     

Frequency domain solution to delay-type Nehari problem

This paper generalizes the frequency-domain results on the delay-type Nehari problem in the stable case to the unstable case. The solvability condition of the delay-type Nehari problem is formulated in terms of the nonsingularity of three matrices. The optimal value γ_opt is the maximal γ∈(0,∞) such that one of the three matrices becomes singular. All sub-optimal compensators are parameterized in a transparent structure incorporating a modified Smith predictor.     

Directional features in online handwriting recognition

The selection of valuable features is crucial in pattern recognition. In this paper we deal with the issue that part of features originate from directional instead of common linear data. Both for directional and linear data a theory for a statistical modeling exists. However, none of these theories gives an integrated solution to problems, where linear and directional variables are to be combined in a single, multivariate probability density function. We describe a general approach for a unified statistical modeling, given the constraint that variances of the circular variables are small. The method is practically evaluated in the context of our online handwriting recognition system frog on hand and the so-called tangent slope angle feature. Recognition results are compared with two alternative modeling approaches. The proposed solution gives significant improvements in recognition accuracy, computational speed and memory requirements.