Structural and electronic properties of CuInSe2

Structural investigation on monocrystalline CuInSe₂ samples has been made. From the single crystal results, the space group of CuInSe₂ was confirmed to be Iˉ42d and the crystal solidification direction was investigated. Compositional uniformity of the ingots was established by EPMA and it was found that the indium concentration was greater than that for copper. Systematic annealing experiments were carried out in vacuum at different temperatures (as low as 160° C) and for different times. Large variation in resistivity was observed after the annealing treatment. P-type samples were found to convert to n-type after the heat-treatments.     

一种抗NLOS的TDOA定位算法

本文提出了一种抗非视线传播(Non-Line-of-Sight)干扰的TDOA定位算法。该算法采用退火与遗传算法相结合的方式，在满足给定条件的空间内搜索源点坐标值。数值仿真表明，该算法具备抗NLOS干扰的能力，与传统TDOA算法相比，该算法无需知道各基站的非视线传播干扰分布，是一种实用有效的定位算法。     

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     

热处理WO3电变色膜稳定性研究

采用电子束蒸发淀积ＷＯ３薄膜。根据已有的ＷＯ３薄膜脱水过程结论而选择适当温度对薄膜进行退火处理。在大量含水的和不含水的两类Ｌｉ＾＋电解质中进行比较性着色和消色循环实验，表明在２９０℃以下热退火处理能明显增加ＷＯ３薄膜在含水 电解质中的循环寿命。     

环面上具有间断梯度的势函数的模拟退火

本文证明了环面上具有间断梯度的势函数的模拟退火过程：dXt=-VU(Xt)dt √2dWt概率收敛到势函数的全局极小集附近。     

激光结晶a-Si:H SOI离子注入和快速退火

本文对激光结晶a-Si∶H SOI结构砷注入和快速退火行为作了研究.a-Si∶H激光结晶有Lp-LCR,OD,FCR-2,FCR-1四个结晶区.用剖面电镜观察了结晶区的结构.扩展电阻测量表明Lp-LCR区中有两种扩散机制,即杂质在晶粒体内扩散和沿缺陷扩散.OD区中有三种扩散形式,除有上述两种以外,还有沿缺陷的扩散.首次比较了沿晶界和缺陷的扩散速度.     

现代优化计算方法在蛋白质结构预测中的应用

现代优化计算方法在蛋白质结构预测中占有重要地位.简要地介绍了模拟退火算法,遗传算法,人工神经网络和图论算法在蛋白质结构预测中的应用.对国内外近年来应用这些算法,特别是在蛋白质构象搜索问题中,解决蛋白质结构预测的研究作了回顾,并分析、比较了这几种算法的效果和特点.     

Annealing behavior of gel‐spun polyethylene fibers at temperatures lower than needed for significant shrinkage

The annealing at 373 K of ultrastrong, gel‐spun polyethylene (PE) has been studied. At this temperature, the fibers show no significant shrinkage. Still, a significant decrease in the mechanical properties is observed. The fibers have been analyzed with differential scanning calorimetry (DSC), temperature‐modulated differential scanning calorimetry (TMDSC), atomic force microscopy (AFM), and small‐angle X‐ray scattering (SAXS). During the annealing, the glass transition of the intermediate phase is exceeded, as shown by DSC. When split for structure analysis by AFM, the annealed fibers undergo plastic deformation around the base fibrils instead of brittle fracture. The quasi‐isothermal TMDSC experiments are compared to the minor structural changes seen with SAXS and AFM. The loss of performance of the PE fibers at 373 K is suggested to be caused by the oriented intermediate phase, and not by major changes in the structure or morphology. The overall metastable, semicrystalline structure is shown by TMDSC to posses local regions that can melt reversibly. © 2003 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 41: 403–417, 2003     

SAR图像组合分割算法

由于存在乘性斑点噪声的影响,给SAR图像分割造成很大困难,本文研究利用最大似然区域增长分割算法,提出区域增长前引入自适应边缘检测,图像分割性能获得较大提高.介绍了我们研究的分割性能优异的模拟退火分割算法,提出了分割性能接近模拟退火并且在SAR图像分割中比较实用的模拟退火和最大似然混合分割算法,并给出了这些分割算法的分割性能比较,以及在实际分割SAR图像时应当如何选择分割算法.