Visualizing the evolution of a web-based social network

Weblogs are dynamic websites updated via easy-to-use content management systems and organized as a set of chronologically ordered stories, frequently built around a link or including links to other weblogs. Since they are managed by individuals, their links tend to mirror or, in some cases, establish new types of social relations, thereby creating a social network. Studying the evolution of this network allows the discovery of emerging social structures and their growth trends. In this paper, we demonstrate the advantages of using the self-organizing maps (SOM) to visualize the evolution of a social network formed by a set of blogs, from their beginning to their current state. By observing the position a weblog is mapped to, it is easy to see what communities it belongs to nowadays, and how and when it became a part of those communities. The proposed procedure gives some insight on how communities are formed and have evolved. In this study, we apply this method to Blogalia, a blog-hosting site from which we have obtained a complete set of data and, by using SOM projections, we have drawn some conclusions on what drives the evolution of its implicit social network.     

Interactive Display of Global Illumination Solutions for Non-diffuse Environments – A Survey

In recent years there has been a lot of work on interactively displaying global illumination solutions for non-diffuse environments. This is an extremely active field of research, in which a lot of different approaches have recently been proposed. In this survey, we will discuss and compare these. This will hopefully prepare the ground for systematically addressing the open questions in the future.     

Prediction of the fretting fatigue resistance of various surface-modification layers on 1045 steel: the role of fretting maps

In this work, fretting maps of various surface modifications were established based on the friction logs of fretting experiments. The fretting fatigue resistance of the coatings was analyzed according to the features of the fretting maps of the coatings. The results showed clearly that fretting maps of materials are effective tools to predict the fretting fatigue properties of substrates and surface-modification coatings. It was also demonstrated that the fretting fatigue resistance of a 1045 steel substrate could be improved to different extents through surface modification. The fretting fatigue resistance of solid lubricating coatings was the best and the tendency for initiation and propagation of cracks in the substrate material could also be restrained by depositing hard coatings.     

向量优化问题的Benson真有效解

在广义凸条件下,研究了带控制参量的向量优化问题.给出了Benson真有效解与相应标量化问题最优解的关系及Benson真有效解的充要条件.     

Diagrammatic Separation of Different Crystal Structures of A2BX4 Compounds Without Energy Minimization: A Pseudopotential Orbital Radii Approach

The A₂BX₄ family of compounds manifest a wide range of physical properties, including transparent conductivity, ferromagnetism, and superconductivity. A 98% successful diagrammatic separation of the 44 different crystal structures of 688 oxide A₂BX₄ compounds (96% for 266 oxide‐only) is described by plotting the total radius of the A atom R_A versus the radius of the B atom R_B for many A₂BX₄ compounds of known structure types and seeking heuristically simple, straight boundaries in the R_A versus R_B plane that best separate the domains of different structure types. The radii are sums R_A = R_s(A) + R_p(A) of the quantum‐mechanically calculated “orbital radii” R_s(R_p), rather than empirical radii or phenomenological electronegativity scales. These success rates using first‐principles orbital radii uniformly exceed the success rates using classic radii. Such maps afford a quick guess of the crystal structure of a yet unmade A₂BX₄ compound by placing its atomic orbital radii on such maps and reading off its structure type.     

八碳烯分离过程的脱水研究

本文运用残余曲线图对八碳烯分离过程进行了分析研究,提出了采用非均相共沸精馏的方法脱除待分离物系中的水的新工艺。研究结果表明,该方法即节省了原工艺中脱水所需的一些设备,又降低了分离能耗,并且可大幅度提高脱水效率,改善产品质量。     

Self-organizing maps for surveying lubrication within squeeze film dampers

Self-organizing maps (SOMs) represent a well-known neural network technique particularly suited to classification tasks. Here, it is adopted to monitor the lubricating conditions within squeeze film dampers for rotor support and was aimed, in particular, at identifying the aspect of the pressure waves within the oil film. Pressure distribution is indeed significantly influenced by a number of factors, which affect damper operation. Results from past research in the field make it possible to infer that the pattern of pressure signals taken in the oil film represents a valuable source of information as regards the lubricating conditions within the damper. Surveillance procedures in the operation of turbomachinery could benefit from prompt detection of possible, unwanted changes in the characteristics of lubrication, for example, when modeling bearing operations within model-based schemes. In this paper, SOM capabilities are first evaluated, dealing separately with theoretically simulated data. The subsequent tests adopted theoretical data as a reference for identifying experimental conditions. Further tests were carried out to map experimental data. Despite constraints consisting in the damper motion being imposed during the theoretical and experimental tests, the results confirmed the potential of the method and encourage further tests in conditions which are closer to real operation.     

Additive Composition of Supervised Self-Organizing Maps

The learning of complex relationships can be decomposed into several neural networks. The modular organization is determined by prior knowledge of the problem that permits to split the processing into tasks of small dimensionality. The sub-tasks can be implemented with neural networks, although the learning examples cannot be used anymore to supervise directly each of the networks. This article addresses the problem of learning in a modular context, developing in particular additive compositions. A simple rule allows defining efficient training, and combining, for example, several Supervised-SOM networks. This technique is important because it introduces interesting generalizations in many modular compositions, permitting data fusion or sequential combinations of neural networks. This revised version was published online in August 2006 with corrections to the Cover Date.     

Self-Organizing Dynamic Graphs

We propose a new self-organizing neural model that considers a dynamic topology among neurons. This leads to greater plasticity with respect to the self-organizing neural network (SOFM). Theorems are presented and proved that ensure the stability of the network and its ability to represent the input distribution. Finally, simulation results are shown to demonstrate the performance of the model, with an application to colour image compression.