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     

电子商务的应用及对企业的影响

简述了电子商务理论的演变过程及电子商务的应用形式,包括电子数据交换、网上营销、网络银行等。探讨了电子商务的应用使企业面临的历史变革,指出作为21世纪的一种基本商务形式,电子商务已经成为具有敏锐战略眼光企业家的选择。     

A posteriori error estimates for a time discrete scheme for a phase-field system of Penrose-Fife type

A time discrete scheme is used to approximate the solution toa phase field system of Penrose–Fife type with a non-conservedorder parameter. An a posteriori error estimate is presentedthat allows the estimation of the difference between continuousand semidiscrete solutions by quantities that can be calculatedfrom the approximation and given data.     

System Identification Models of the Equivalent Permittivity for Rain Medium

The dielectric constant for rain medium is investigated by utilizing the system identification method. The rain rate model and frequency model of permittivity in millimeter waves band for rain medium are presented. The results obtained with models are in very good agreement with references in calculating the attenuation of electromagnetic waves induced by rain, which Shows that the obtained models are valid and practicable. The cross-polar discrimination gotten with rain rate model is in agreement with references.     

A NEW DESCRIPA NEW DESCRIPTOR OF AMINO ACIDS BASED ON THE THREEDIMENSIONAL VECTOR OF ATOMIC INTERACTION FIELD

QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIP (QSAR) IS A VERY IMPORTANT TOPIC FOR MANY SCIENTIFIC FIELDS AND CAN BE TERMED AS QUANTITATIVE SEQUENCE ACTIVITY MODELS(QSAM)[1] WHEN REFERRED TO THE RESEARCH ON RELATION- SHIPS BETWEEN STRUCTURES AND ACTIVITIES OF BIOLOGICAL MOLECULES, SUCH AS PROTEINS, AND NUCLEIC ACIDS. HOW- EVER, IT IS VERY DIFFICULT TO ESTABLISH A QSAM MODEL,…     

带惩罚项与随机输入的BP神经网络在线梯度学习算法的收敛性

本文对三层BP神经网络中带有惩罚项的在线梯度学习算法的收敛性问题进行了研究,在网络训练每一轮开始执行之前,对训练样本随机进行重排,以使网络学习更容易跳出局部极小,文中给出了误差函数的单调性定理以及该算法的弱收敛和强收敛性定理。     

识别混凝土板内部缺陷的人工神经网络算法

以一维有缺陷混凝土板为研究对象，分别采用Leverberg-Marcluardt和径向基神经网络算法，对缺陷的深度与厚度进行识别，从而实现对混凝土板内部缺陷的三维重构，称为红外CT模拟．两类神经网络算法的识别结果表明：Leverberg-Marcluardt神经网络较径向基神经网络具有更好的收敛精度与计算效率．     

抽指加权宽带扇形叉指声表面波滤波器的等效电路分析

扇形换能器可以看成若干个沿孔径方向划分的均匀孔径换能器电端并联而成，根据梅森(Mason)等效电路模型以及由其延伸的混合场等效电路模型，推导出整个扇形换能器的导纳矩阵和频率响应，其中采用复阻抗模型考虑了叉指电极与自由表面的阻抗不连续的因素。本方法能够模拟指间反射、三次行程、指条寄生阻抗以及外围电路等对器件性能的影响；理论模拟与实验结果吻合。     

浅谈网络环境下高校图书馆信息资源建设

阐述了网络环境下高校图书馆信息资源建设存在的主要问题,探讨了网络环境对信息资源建设的影响,提出了信息资源建设的具体措施。     

开源软件在网络教育中的应用

论述了在教育领域中使用开源软件的必要性,介绍了几种应用于网络教育的开源软件,主要包括服务器软件、工作站软件和课程管理系统。