On effectiveness of wiretap programs in mapping social networks

Snowball sampling methods are known to be a biased toward highly connected actors and consequently produce core-periphery networks when these may not necessarily be present. This leads to a biased perception of the underlying network which can have negative policy consequences, as in the identification of terrorist networks. When snowball sampling is used, the potential overload of the information collection system is a distinct problem due to the exponential growth of the number of suspects to be monitored. In this paper, we focus on evaluating the effectiveness of a wiretapping program in terms of its ability to map the rapidly evolving networks within a covert organization. By running a series of simulation-based experiments, we are able to evaluate a broad spectrum of information gathering regimes based on a consistent set of criteria. We conclude by proposing a set of information gathering programs that achieve higher effectiveness then snowball sampling, and at a lower cost. Maksim Tsvetovat is an Assistant Professor at the Center for Social Complexity and department of Public and International Affairs at George Mason University, Fairfax, VA. He received his Ph.D. from the Computation, Organizations and Society program in the School of Computer Science, Carnegie Mellon University. His dissertation was centered on use of artificial intelligence techniques such as planning and semantic reasoning as a means of studying behavior and evolution of complex social networks, such as these of terrorist organizations. He received a Master of Science degree from University of Minnesota with a specialization in Artificial Intelligence and design of Multi-Agent Systems, and has also extensively studied organization theory and social science research methods. His research is centered on building high-fidelity simulations of social and organizational systems using concepts from distributed artificial intelligence and multi-agent systems. Other projects focus on social network analysis for mapping of internal corporate networks or study of covert and terrorist orgnaizations. Maksim’s vita and publications can be found on Kathleen M. Carley is a professor in the School of Computer Science at Carnegie Mellon University and the director of the center for Compuational Analysis of Social and Organizational Systems (CASOS) which has over 25 members, both students and research staff. Her research combines cognitive science, social networks and computer science to address complex social and organizational problems. Her specific research areas are dynamic network analysis, computational social and organization theory, adaptation and evolution, text mining, and the impact of telecommunication technologies and policy on communication, information diffusion, disease contagion and response within and among groups particularly in disaster or crisis situations. She and her lab have developed infrastructure tools for analyzing large scale dynamic networks and various multi-agent simulation systems. The infrastructure tools include ORA, a statistical toolkit for analyzing and visualizing multi-dimensional networks. ORA results are organized into reports that meet various needs such as the management report, the mental model report, and the intelligence report. Another tool is AutoMap, a text-mining systems for extracting semantic networks from texts and then cross-classifying them using an organizational ontology into the underlying social, knowledge, resource and task networks. Her simulation models meld multi-agent technology with network dynamics and empirical data. Three of the large-scale multi-agent network models she and the CASOS group have developed in the counter-terrorism area are: BioWar a city-scale dynamic-network agent-based model for understanding the spread of disease and illness due to natural epidemics, chemical spills, and weaponized biological attacks; DyNet a model of the change in covert networks, naturally and in response to attacks, under varying levels of information uncertainty; and RTE a model for examining state failure and the escalation of conflict at the city, state, nation, and international as changes occur within and among red, blue, and green forces. She is the founding co-editor with Al. Wallace of the journal Computational Organization Theory and has co-edited several books and written over 100 articles in the computational organizations and dynamic network area. Her publications can be found at: http://www.casos.cs.cmu.edu/bios/carley/publications.php     

Charge transport properties in carbon black/polymer composites

The charge transport properties of polymer matrix–carbon black composites are investigated in this study. Direct current conductivity is examined with varying parameters: the temperature and the conductive filler content. Conductivity data are analyzed by means of percolation theory, and both percolation threshold and critical exponent are determined at each of the examined temperatures. The temperature dependence of conductivity and the agreement of experimental results with the variable range hopping model reveal hopping conduction as the predominant transport mechanism, below and in the vicinity of the critical concentration of carbon black particles. At higher concentrations, the contribution of hopping transport to the overall conductivity is reduced and a balance between hopping and conduction via geometrical contact occurs. © 2007 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 45: 2535–2545, 2007     

Identifying sets of key players in a social network

A procedure is described for finding sets of key players in a social network. A key assumption is that the optimal selection of key players depends on what they are needed for. Accordingly, two generic goals are articulated, called KPP-POS and KPP-NEG. KPP-POS is defined as the identification of key players for the purpose of optimally diffusing something through the network by using the key players as seeds. KPP-NEG is defined as the identification of key players for the purpose of disrupting or fragmenting the network by removing the key nodes. It is found that off-the-shelf centrality measures are not optimal for solving either generic problem, and therefore new measures are presented. Stephen P. Borgatti is Professor of Organization Studies at the Carroll School of Management, Boston College. His research is focused on social networks, social cognition and knowledge management. He is also interested in the application of social network analysis to the solution of managerial problems.     

Study of the peak effect phenomenon in single crystals of 2H-NbSe2

The weakly pinned single crystals of the hexagonal 2H-NbSe₂ compound have emerged as prototypes for determining and characterizing the phase boundaries of the possible order-disorder transformations in the vortex matter. We present here a status report based on the ac and dc magnetization measurements of the peak effect phenomenon in three crystals of 2H-NbSe₂, in which the critical current densities vary over two orders of magnitude. We sketch the generic vortex phase diagram of a weakly pinned superconductor, which also utilizes theoretical proposals. We also establish the connection between the metastability effects and pinning.     

Mössbauer and X-ray diffraction characterization of Fe60Al40 coatings prepared by thermal spraying

Microstructured (atomized) and nanostructured (milled) Fe₆₀Al₄₀ powders together with their corresponding coatings synthesized by High Velocity Oxy-fuel (HVOF) or Atmospheric Plasma Spray (APS) thermal spraying techniques have been characterized by Mössbauer Spectroscopy (MS) and X-ray Diffraction (XRD). The evolution of the microstructure and the atomic ordering degree in the powders and coatings are discussed at the light of the various processing conditions. The operational correlation between the parameters of the duplex morphology of coatings and the processing parameters is discussed.     

Synthesis and crystal structure of the octahedral cluster complex [Th(DMSO)8Cl][Re6Se7Cl7]

A cluster complex of the composition [Th(DMSO)₈Cl][Re₆Se₇Cl₇] has been obtained by interaction of ThCl₄ solution in DMSO with a water solution of K₃[Re₆Se₇Cl₇] and KCl. The compound crystallizes in the rhombic space group Pbcm with unit cell parameters a = 12.262(2) Å, b = 19.653(6) Å, c = 23.603(6) Å, V = 5688(2) ų, Z = 4, d _calc = 3.282 g/cm³. The structure is built from centrosymmetric cluster anions [Re₆Se₇Cl₇]^3? and complex cations [Th(DMSO)₈Cl]³⁺ possessing mirror-plane symmetry, half of the DMSO ligands being doubly disordered.     

Quark confinement in 2+1 dimensional pure Yang-Mills theory

We report some progress on the quark confinement problem in 2 + 1 dim. pure Yang-Mills theory, using Euclidean instanton methods. The instantons are regularized Wu-Yang ‘monopoles’, whose long range Coulomb field is screened by collective effects. Such configurations are stable to small perturbations unlike the case of singular, undressed monopoles. Using exact non-perturbative results for the 3-dim. Coulomb gas, where Debye screening holds for arbitrarily low temperatures, we show in a self-consistent way that a mass gap is dynamically generated in the gauge theory. The mass gap also determines the size of the monopoles. We also identify the disorder operator of the model in terms of the Sine-Gordon field of the Coulomb gas and hence obtain a dual representation whose symmetry is the centre ofSU(2).     

Limited resolution in complex network community detection with Potts model approach

According to Fortunato and Barthélemy, modularity-based community detection algorithms have a resolution threshold such that small communities in a large network are invisible. Here we generalize their work and show that the q-state Potts community detection method introduced by Reichardt and Bornholdt also has a resolution threshold. The model contains a parameter by which this threshold can be tuned, but no a priori principle is known to select the proper value. Single global optimization criteria do not seem capable for detecting all communities if their size distribution is broad.     

二维随机激光器的模式选择及阈值与饱和特性

基于将Maxwell方程与四能级原子系统速率方程相结合而建立起随机激光时域理论，并利用有限时域差分法，研究了二维随机介质中激光模式的输出特性与介质尺寸、外形及抽运速率等参数的关系.结果表明，与传统激光模式相似，随机激光模式的强度随抽运速率的变化不仅具有阈值特性，而且具有饱和特性.基于模式特性对介质及抽运参数的依赖关系，提出了二维随机激光器的选模方式，在很大程度上不同于传统激光器的选模方式. 关键词： 随机激光器 模式选择 无序介质中的光学特性     

Dimensionally and thermally stable polymer,containing disordered graphitic structure and adamantane

In an attempt to develop a low‐k interlayer dielectric, adamantane‐diphenyldiethynyl moiety containing oligomer is prepared. Oligomerization of 1,3,5,7‐tetrakis[3/4‐ethynylphenyl]adamantane ( 4 ) is accomplished by a Glaser–Hay oxidative coupling with 1,3,5‐triethynylbenzene and phenylacetylene end‐capping agent. The CHCl₃ soluble oligomer is then thermally treated by step‐curing at 200, 300, 380, and 450 °C for 30 min at each temperature under nitrogen flow to render a shiny void‐free black polymer. TGA analysis indicates that the polymer is stable under nitrogen up to 500 °C with a marginal decomposition up to 800 °C. Solid‐state ¹³C NMR, Raman scattering, and FTIR are used to characterize the structure of the polymer. The polymer consists of amorphous carbon networks with the adamantane moieties and nanosized graphitic regions (clusters), which are generated from the thermal crosslinking of the diphenyldiethynyl units. It shows a remarkably low linear coefficient of thermal expansion (～25 ppm/°C), presumably due to the presence of the disordered graphitic structure. Its high density (～1.21 g/cm³), refractive index (～1.80 at 632 nm), and Young's modulus (～17.0 GPa) are also consistent with the interpretation. This study reveals important details about the effect of microscopic structure on the macroscopic properties of the highly crosslinked polymer. © 2006 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 44: 6909–6925, 2006