Fast internal dynamics in polyelectrolyte gels measured by dynamic light scattering

Summary Dynamic light scattering was used to investigate the dynamics of sodium poly(styrene sulfonate) and fully neutralized poly(acrylic acid) gels as a function of the degree of swelling and weight ratio of cross-linking agent. It was shown that the collective diffusion coefficient increases with increasing degree of swelling and that the diffusion coefficient shows stronger concentration dependence than predicted by scaling arguments. For gel samples measured at the swelling equilibrium, the diffusion coefficient increases with increasing gel concentration for both gel systems.     

Distributed self-stabilizing placement of replicated resources in emerging networks

Emerging large scale distributed networking systems, such as P2P file sharing systems, sensor networks, and ad hoc wireless networks, require replication of content, functionality, or configuration to enact or optimize communication tasks. The placement of these replicated resources can significantly impact performance. We present a novel self-stabilizing, fully distributed, asynchronous, scalable protocol that can be used to place replicated resources such that each node is "close" to some copy of any object. We describe our protocol in the context of a graph with colored nodes, where a node's color indicates the replica/task that it is assigned. Our combination of theoretical results and simulation prove stabilization of the protocol, and evaluate its performance in the context of convergence time, message transmissions, and color distance. Our results show that the protocol generates colorings that are close to the optimal under a set of metrics, making such a protocol ideal for emerging networking systems.     

Nonuniformity of phase structure in immiscible polymer blends

This article is focused on the phase structure development in immiscible polymer blends during melt mixing. Nonuniformity of the phase structure, i.e., the coexistence of areas containing particles with markedly different size distribution, was detected in quenched and compression molded samples of a number of various blends prepared by long and intensive mixing in the chamber of a Plasticorder. The same effect was found also for polystyrene/polyamide blends prepared in a twin‐screw extruder. It was shown that neglecting nonuniformity of the phase structure can lead to considerable error in evaluation of the effect of system parameters on the blend morphology. The reasons for the effect were discussed and it was found that inhomogeneous flow field in mixers is a plausible explanation of the nonuniform phase structure. POLYM. ENG. SCI., 2008. © 2008 Society of Plastics Engineers     

Microstructural and compositional aspects of ZnO-based varistor ceramics prepared by direct mixing of the constituent phases and high-energy milling

ZnO-based varistor samples were prepared by the direct mixing of the constituent phases (DMCP) and sintering at 1100 °C for 2 h. The influence of the starting powder mixture's composition – the amounts of the pre-reacted varistor compounds and their composition – and its preparation, either with or without mechano-chemical activation (MCA), on the microstructure, phase composition and electrical characteristics of the varistor samples was studied. It showed that MCA improved the density and microstructural homogeneity of the varistor samples. MCA strongly affected the grain growth: it enhanced the nucleation of inversion boundaries (IBs) in the ZnO grains and the IBs-induced grain-growth mechanism resulted in uniform grain growth and hence a microstructure with smaller ZnO grains and a narrower grain size distribution. The final phase composition of the samples prepared by the DMCP method mainly depended on the presence of varistor dopants that can prevent the formation of the pyrochlore phase, especially Cr₂O₃, while MCA can affect it mostly by providing a homogeneous distribution of those dopants. The DMCP varistor samples prepared with MCA had much better current–voltage characteristics than the samples of the same composition prepared from unactivated powders.     

Using classification techniques for informal requirements in the requirements analysis-supporting system

In order to efficiently develop large-scale and complicated software, it is important for system engineers to correctly understand users’ requirements. Most requirements in large-scale projects are collected from various stakeholders located in various regions, and they are generally written in natural language. Therefore, the initial collected requirements must be classified into various topics prior to analysis phases in order to be usable as input in several requirements analysis methods. If this classification process is manually done by analysts, it becomes a time-consuming task. To solve this problem, we propose a new bootstrapping method which can automatically classify requirements sentences into each topic category using only topic words as the representative of the analysts’ views. The proposed method is verified through experiments using two requirements data sets: one written in English and the other in Korean. The significant performances were achieved in the experiments: the 84.28 and 87.91 F1 scores for the English and Korean data sets, respectively. As a result, the proposed method can provide an effective function for an Internet-based requirements analysis-supporting system so as to efficiently gather and analyze requirements from various and distributed stakeholders by using the Internet.     

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Toughening mechanism for a rubber-toughened epoxy resin with rubber/matrix interfacial modification

For a rubber-toughened piperidine-DGEBA epoxy resin, the interface between the rubber particle and the epoxy resin matrix was modified by an epoxide end-capped carboxyl terminated butadiene and acrylonitrile random copolymer (CTBN). The end-capping epoxides used were a rigid diglycidyl ether of bisphenol-A (Epon 828), a short-chain flexible diglycidyl ether of propylene glycol (DER 736), and a long-chain flexible diglycidyl ether of propylene glycol (DER 732). The microstructures and the fracture behaviour of these rubber-modified epoxy resins were studied by transmission electron microscopy and scanning electron microscopy. Their thermal and mechanical properties were also investigated. In the rubber-modified epoxy resins, if the added CTBNs were end-capped by a flexible diglycidyl ether of propylene glycol (DER 732 or DER 736) before curing, the interfacial zone of the undeformed rubber particle, the degree of cavitation of the cavitated rubber particle on the fracture surface and the fracture energy of the toughened epoxy resin were all significantly increased. The toughening mechanism based on cavitation and localized shear yielding was considered and a mechanism for the interaction between cavitation and localized shear yielding that accounts for all the observed characteristics is proposed.     

Influence of Cu<Superscript>2+</Superscript> ions on structural and magnetic properties of NiZn ferrites

The paper is devoted to the preparation of NiZn ferrite with small substitutions of copper by means of ceramic technology. The influence of small Cu substitution on the microstructural and magnetic properties of NiZn ferrites have been analysed by means of various experimental methods and interpreted from the point of view of preparation technology optimisation and possible applications of such materials. A strong correlation between the substituent content and resulting properties has been observed, thus allowing preparation of material with the properties tailored for any particular application.     

Modeling of Temperature–Frequency Correlation Using Combined Principal Component Analysis and Support Vector Regression Technique

A good understanding of environmental effects on structural modal properties is essential for reliable performance of vibration-based damage diagnosis methods. In this paper, a method of combining principal component analysis (PCA) and support vector regression (SVR) technique is proposed for modeling temperature-caused variability of modal frequencies for structures instrumented with long-term monitoring systems. PCA is first applied to extract principal components from the measured temperatures for dimensionality reduction. The predominant feature vectors in conjunction with the measured modal frequencies are then fed into a support vector algorithm to formulate regression models that may take into account thermal inertia effect. The research is focused on proper selection of the hyperparameters to obtain SVR models with good generalization performance. A grid search method with cross validation and a heuristic method are utilized for determining the optimal values of SVR hyperparameters. The proposed method is compared with the method directly using measurement data to train SVR models and the multivariate linear regression (MLR) method through the use of long-term measurement data from a cable-stayed bridge. It is shown that PCA-compressed features make the training and validation of SVR models more efficient in both model accuracy and computational costs, and the formulated SVR model performs much better than the MLR model in generalization performance. When continuously measured data is available, the SVR model formulated taking into account thermal inertia effect can achieve more accurate prediction than that without considering thermal inertia effect.     

An approach to efficient business intelligent system for financial prediction

A concept of business intelligent system for financial prediction is considered in this paper. It provides data needed for fast, precise and good business decision support to all levels of management. The aim of the project is the development of a new online analytical processing oriented on case-based reasoning (CBR) where a previous experience for every new problem is taken into account. Methodological aspects have been tested in practice as a part of the management information system development project of “Novi Sad Fair”. A case study of an improved application of CBR in prediction of future payments is discussed in the paper. This paper is originally presented at The International Conference on Hybrid Information Technology 2006, at the special session on “Intelligent Information Systems for Financial Engineering”, November 2006 in Cheju Island, Korea.