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     

Synthesis and properties of the nanocomposite of zink oxide and poly(amic acid)

The composite comprised of zinc oxide quantum dots and poly(amic acid) (PAAc) was prepared and studied by X-rays diffraction, X-ray photoelectron spectroscopy, light scattering, UV absorbance and UV fluorescence. The UV absorbance of the ZnO/PAAc composite was found to be much larger than that of its components taken separately. The fluorescence of the ZnO/PAAc composite was found to be shifted to longer wavelengthes in comparison with pure ZnO. The presence of the dopant dodecylbenzenesulfonic acid was found to affect the observed fluorescence.     

A novel tridentate nitrogen donor as ligand in copper catalyzed ATRP of methyl methacrylate

A tridentate ligand, BPIEP: 2,6‐bis[1‐(2,6‐diisopropyl phenylimino) ethyl] pyridine, having central pyridine unit and two peripheral imine coordination sites was effectively employed in controlled/“living” radical polymerization of MMA at 90°C in toluene as solvent, Cu^IBr as catalyst, and ethyl‐2‐bromoisobutyrate (EBiB) as initiator resulting in well‐defined polymers with polydispersities M_w/M_n ≤ 1.23. The rate of polymerization follows first‐order kinetics, k_app = 3.4 × 10^?5 s^?1, indicating the presence of low radical concentration ([P*] ≤ 10^?8) throughout the reaction. The polymerization rate attains a maximum at a ligand‐to‐metal ratio of 2:1 in toluene at 90°C. The solvent concentration (v/v, with respect to monomer) has a significant effect on the polymerization kinetics. The polymerization is faster in polar solvents like, diphenylether, and anisole, as compared to toluene. Increasing the monomer concentration in toluene resulted in a better control of polymerization. The molecular weights (M_n,SEC) increased linearly with conversion and were found to be higher than predicted molecular (M_n,Cal). However, the polydispersity remained narrow, i.e., ≤1.23. The initiator efficiency at lower monomer concentration approaches a value of 0.7 in 110 min as compared to 0.5 in 330 min at higher monomer concentration. The aging of the copper salt complexed with BPIEP had a beneficial effect and resulted in polymers with narrow polydispersitities and higher conversion. PMMA obtained at room temperature in toluene (33%, v/v) gave PDI of 1.22 (M_n = 8500) in 48 h whereas, at 50°C the PDI is 1.18 (M_n = 10,300), which is achieved in 23 h. The plot of lnk_app versus 1/T gave an apparent activation energy of polymerization as (ΔE^≠_app) 58.29 KJ/mol and enthalpy of equilibrium (ΔH⁰_eq) to 28.8 KJ/mol. Reverse ATRP of MMA was successfully performed using AIBN in bulk as well as solution. The controlled nature of the polymerization reaction was established through kinetic studies and chain extension experiments. © 2005 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 43: 4996–5008, 2005     

Fiber-Optic Chemical Sensor for Detection of NO2 Using Poly (3-Octylthiophene)

A fiber-optic chemical sensor (FOCS) for detection of nitrogen dioxide (NO₂) molecules is reported. The FOCS presents an optropode structure because of the transmission properties of the sensitive material. The NO₂ FOCS is activated by using the semiconductor polymer: regioregular head-to-tail poly(3-octylthiophene-2,5-diyl). The operation wavelength of the sensor is 543.5 nm such that a simple LED and detector can be used for the design of this device. The sensor response decreases after each exposure, demonstrating the reduction in sensitivity as well as irreversibility lower than 5%. However, its properties such as rapid response, high selectivity, high sensitivity (0.43 ± 0.01 muW/ppm), hygroscopic properties, and its operation at room temperature make this kind of FOCS a good alternative for NO₂ toxic gas detection.     

On the counting function of the lattice profile of periodic sequences

The lattice profile analyzes the intrinsic structure of pseudorandom number sequences with applications in Monte Carlo methods and cryptology. In this paper, using the discrete Fourier transform for periodic sequences and the relation between the lattice profile and the linear complexity, we give general formulas for the expected value, variance, and counting function of the lattice profile of periodic sequences with fixed period. Moreover, we determine in a more explicit form the expected value, variance, and counting function of the lattice profile of periodic sequences for special values of the period.     

A Dominated Theorem on 5L(2, R) and Its Application

In this paper, we give the following dominated theorem: Let φ(g) ∈ L1(G//K),φε(t)=ε> 0, and the least radical decreasing dominatedfunction φ(t) = sup |φ(y)| ∈L1(G//K). If shtφ(t) is monotonically decreasingon (0, ∞), then for any f∈L1loc(G//K) , the following inequality holds:sup |φε * f(x)| ≤ Cmf(x),where mf(x) is the Hardy-Littlewood maximal function of f, and C = ||φ||1.An application of this dominated theorem is also given.     

CONVERGENCE OF CASCADE ALGORITHMS AND SMOOTHNESS OF REFINABLE DISTRIBUTIONS

In this paper, the author at first develops a method to study convergence of the cascade algorithm in a Banach space without stable assumption on the initial (see Theorem 2.1), and then applies the previous result on the convergence to characterizing compactly supported refinable distributions in fractional Sobolev spaces and Holder continuous spaces (see Theorems 3.1, 3.3, and 3.4). Finally the author applies the above characterization to choosing appropriate initial to guarantee the convergence of the cascade algorithm (see Theorem 4.2).     

Generation of UV laser light by stimulated Raman scattering in D2, D2/Ar and D2/He using a pulsed Nd:YAG laser at 355nm

A pulsed Nd:YAG laser at 355nm is used to pump Raman cell filled with D_2, D_2/Ar and D_2/He. With adequately adjusted parameters, the maximum photon conversion efficiency of the first-order Stokes light (S_1, 396.796nm) reaches 33.33% in D_2/Ar and the stability of S_1 in pure D_2 is fairly high, the energy drift being less than 10% when the pump energy drifts in the range of 5%. The conversion efficiency and stability, which are functions of the composition and pressure of the Raman medium and the energy of pump laser, are investigated. The result has been used to optimize the laser transmitter system for a differential absorption lidar system to measure NO_2 concentration profiles.     

Förster energy transfer from poly(arylene–ethynylene)s to an erbium–porphyrin complex

We study the infrared emission at 1.54 μm of an organolanthanide complex, Er(III)-tetraphenylporphyrin [Er(TPP)acac], both as a result of direct optical excitation and via energy transfer from host π-conjugate polymers of type poly(arylene–ethynylene) [PAE]. In the first case, the emission of the neat complex is characterized in inert transparent materials and a value of the quantum yield at 1.54 μm φ_IR=4×10⁻⁴ is measured. Then, fluorescence resonance transfer is investigated in blends of Er(TPP)acac with PAEs by monitoring the quenching of the polymer fluorescence along with the enhancement of both the visible emission of the ligand and the near-infrared band of Er³⁺. These different procedures allow a detailed analysis of the transfer efficiency within a specific implementation of the Förster model for polymeric donors. The experimental values of the critical radius R₀, ranging from 1.3 to 2.5 nm for the different blends, are in good agreement with theory for a wide interval of the physical and spectroscopic parameters. This suggests that other mechanisms for excitation transfer do not play a significant role in these materials.