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     

数字全息图变频采样研究

根据Whittaker-Shannon抽样定理,对菲涅耳全息图进行变频率采样,保证整个全息图各部分采样频率为该处相应空间频率的两倍,从而完全消除数字全息图由于采样冗余而带来全息图的信息冗余.并且,对变频采样后的全息图进行线性插值恢复即可获得良好的再现像质.实验和理论均证明了该方法的有效性和可行性,为全息图的信息存贮与传输提出一条新的思路.     

Estimating Sampling Errors in REA Survey: A Model Approach for the Synthetic Presentation of Results for Main Variables Involved in Economic Analysis

A new sample business survey for agriculture, the REA survey, and a project of integration with the FADN network (RICA in Italy) have significantly changed the production of statistical information nowadays available with reference to the agricultural sector. On the basis of this relevant information, new economic analyses are being developed on farms’ performance, agricultural households’ income and the Common Agricultural Policy (CAP). In this paper the authors estimate the relationship between the levels of variables of interest and their sampling errors using models in order to improve the accessibility of the information on estimates accuracy to the final users (agricultural analysts, policy makers). The paper is the result of a joint research of the three authors. Sections 1–3 and 6 by Pizzoli, Sects. 4 and 5 by Rondinelli, Sect. 7 by Filiberti, conclusions joint to the three authors.     

Approximation of signals from local averages

This work is concerned with approximation of a signal from local averages. It improves a result of Butzer and Lei [P.L. Butzer, J. Lei, Approximation of signals using measured sampled values and error analysis, Commun. Appl. Anal. 4 (2000) 245–255].     

氧化铁浆液脱硫的实验研究与理论分析

本文实验研究了氧化铁浆液在酸性环境下脱除烟气中的二氧化硫气体。实验在一自制的脱硫塔中进行。通过燃烧液化石油气来产生烟气,将氧化铁的超细粉加入水中作为脱硫介质。实验中研究了二氧化硫初始浓度、水气比对脱硫效率的影响。从实验结果可以看出,脱硫率随着水气比的增加而增大;随二氧化硫的初始浓度的增加,其脱硫率呈降低趋势。在文中同时分析了氧化铁浆液的脱硫机理和此方法脱硫的优点以及目前存在的问题。     

Cyclic BSEC of block size 3

Balanced sampling plans excluding contiguous units (or BSEC) were first introduced by Hedayat, Rao and Stufken in 1988. In this note, we discuss constructions of these designs having cyclic automorphisms. We use Langford sequences to construct all possible cyclic BSEC (or CBSEC) with block size 3 and λ = 1,2, which establishes the necessary and sufficient conditions for such designs. Some constructions of the balanced sampling plan avoiding adjacent units, a generalization of BSEC, are also given for fixed λ.     

Marcinkiewicz–Zygmund inequalities

We study a generalization of the classical Marcinkiewicz–Zygmund inequalities. We relate this problem to the sampling sequences in the Paley–Wiener space and by using this analogy we give sharp necessary and sufficient computable conditions for a family of points to satisfy the Marcinkiewicz–Zygmund inequalities.     

Direct analysis of fly ash materials by inductively coupled plasma atomic emission spectrometry using slurry nebulization

Fly ash samples of cement works were analysed using slurry nebulization inductively coupled plasma atomic emission spectrometric (ICP-AES). Because of the influence of the experimental factors on the signal intensity, the optimal conditions of the analysis circumstances were determined. Control analyses (wet digestion followed by ICP-AES, and XRF of dry powders (pressed pellets)) were also carried out to compare the results. Based on the result, it was concluded that the slurry nebulization method using slurry standard of same type reference material for calibration can be applied for rapid but less precise (RSD 5–10%) determination of the elements in fly ash.     

Determination of manganese in brain samples by slurry sampling graphite furnace atomic absorption spectrometry

A simple procedure for the determination of manganese in different sections of human brain samples by graphite furnace atomic absorption spectrometry has been developed. Brain sections included cerebellum, hypothalamus, frontal cortex, vermix and encephalic trunk. Two sample preparation procedures were evaluated, namely, slurry sampling and microwave-assisted acid digestion. Brain slurries (2% w/v) could be prepared in distilled, de-ionized water, with good stability for up to 30 min. Brain samples were also digested in a domestic microwave oven using 5 ml of concentrated HNO₃. A mixed palladium+magnesium nitrate chemical modifier was used for thermal stabilization of the analyte in the electrothermal atomizer up to pyrolysis temperatures of 1300 °C, irrespective of the matrix. Quantitation of manganese was conducted in both cases by means of aqueous standards calibration. The detection limits were 0.3 and 0.4 ng ml⁻¹ for the slurry and the digested samples, respectively. The accuracy of the procedure was checked by comparing the results obtained in the analysis of slurries and digested brain samples, and by analysis of the NIST Bovine Liver standard reference material (SRM 1577a). The ease of slurry preparation, together with the conventional set of analytical and instrumental conditions selected for the determination of manganese make such methodology suitable for routine clinical applications.     

Slurry nebulization ICP-AES spectrometry method for the determination of tin in organotin(IV) complexes

This paper proposes a quick, novel method for tin determination in organotin chemicals by slurry nebulization inductively coupled plasma atomic emission (ICP-AES) spectrometry. The method was tested by the measurement of five organotin carboxylate complexes of known composition for obtaining simple stoichiometric data. The slurries were prepared by first dissolving the organotins in an adequate solvent (methanol, pyridine or acetone) well miscible with water and then adding this solution drop-by-drop to a 0.005% TX-100 tenzide solution while maintaining intensive mixing. Dynamic laser light scattering experiments showed that the average equivalent particle size in the resulting slurry was ≈0.3 μm for all samples and solvents. Under suitable ICP-AES measuring conditions, the signal recoveries were found to be between 101.8 and 106.6%, which allowed direct nebulization and calibration against aqueous solutions. Typically, 70 μg l⁻¹ detection limit and 1–5% relative S.D. on five replicates can be achieved by the described method.