Verifiable Distributed Oblivious Transfer and Mobile Agent Security

The mobile agent is a fundamental building block of the mobile computing paradigm. In mobile agent security, oblivious transfer (OT) from a trusted party can be used to protect the agent’s privacy and the hosts’ privacy. In this paper, we introduce a new cryptographic primitive called Verifiable Distributed Oblivious Transfer (VDOT), which allows us to replace a single trusted party with a group of threshold trusted servers. The design of VDOT uses a novel technique called consistency verification of encrypted secret shares. VDOT protects the privacy of both the sender and the receiver against malicious attacks of the servers. We also show the design of a system to apply VDOT to protect the privacy of mobile agents. Our design partitions an agent into the general portion and the security-sensitive portion. We also implement the key components of our system. As far as we know, this is the first effort to implement a system that protects the privacy of mobile agents. Our preliminary evaluation shows that protecting mobile agents not only is possible, but also can be implemented efficiently. This work was supported in part by the DoD University Research Initiative (URI) program administered by the Office of Naval Research under grant N00014-01-1-0795. Sheng Zhong was supported by ONR grant N00014-01-1-0795 and NSF grants ANI-0207399 and CCR-TC-0208972. Yang Richard Yang was supported in part by NSF grant ANI-0207399. A preliminary version of this paper was presented at the DialM-POMC Joint Workshop on Foundations of Mobile Computing in 2003. Sheng Zhong received his Ph.D. in computer science from Yale University in the year of 2004. He holds an assistant professor position at SUNY Buffalo and is currently on leave for postdoctoral research at the Center for Discrete Mathematics and Theoretical Computer Science (DIMACS). His research interests, on the practical side, are security and incentives in data mining, databases, and wireless networks. On the theoretical side, he is interested in cryptography and game theory. Yang Richard Yang is an Assistant Professor of Computer Science at Yale University. His research interests include computer networks, mobile computing, wireless networking, sensor networks, and network security. He leads the LAboratory of Networked Systems (LANS) at Yale. His recent awards include a Schlumberger Fellowship and a CAREER Award from the National Science Foundation. He received his B.E. degree from Tsinghua University (1993), and his M.S. and Ph.D. degrees from the University of Texas at Austin (1998 and 2001).     

Perceptual evaluation of color gamut mapping algorithms

The recommendation of the CIE has been followed as closely as possible to evaluate the accuracy of five color gamut mapping algorithms (GMAs)—two nonspatial and three spatial algorithms—by psychophysical experiments with 20 test images, 20 observers, one test done on paper and a second one on display. Even though the results do not show any overall “winner,” one GMA is definitely perceived as not accurate. The importance of a high number of test images to obtain robust evaluation is underlined by the high variability of the results depending on the test images. Significant correlations between the percentage of out‐of‐gamut pixels, the number of distinguishable pairs of GMAs, and the perceived difficulty to distinguish them have been found. The type of observers is also important. The experts, who prefer a spatial GMA, show a stronger consensus and look especially for a good rendering of details, whereas the nonexperts hardly make a difference between the GMAs. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 470–476, 2008     

河南油田泌阳凹陷稠油地化录井评价方法

河南油田泌阳凹陷分布有古城、井楼、杨楼、新庄4个稠油油田，各油田油质复杂，查清各区块、各层系稠油油质是开发生产的重要工作之一。通过对稠油层基本特征分析，应用地化录井参数建立了TPI评价法、原油密度评价法及原油黏度评价法。TPI评价法主要是利用原油中气态烃和液态烃与全烃比值大小划分油质类型；原油密度评价法主要利用油质重，TPI值小，反之TPI值大的关系划分油质类型；原油黏度评价法主要利用TPI反映油质组分的综合性参数的特点，建立TPI与黏度的关系。这套评价评价方法提供了快速精细评价稠油油质的新手段。     

HSE管理体系认证审核的要点

企业所建立的HSE管理体系已运行多年,大多满足认证的条件,HSE体系认证是体系运行的重要环节,也是体系运行绩效的肯定。审核时要面对大量的体系文件和作业记录,因此把握住审核要点会起到事半功倍的效果。     

基于互信息域的L2S接口方法研究

分析了基于互信息域的有效信噪比映射的L2S(link level to system level)接口方法,研究了信道相关带宽对接口复杂度的影响,在不明显降低预测准确度的前提下,验证了利用信道相关带宽来简化接口计算复杂度的可能性。     

影响GPS水准高程的因素及高程拟合方法的探讨

在简单介绍高程系统的基础上，对影响GPS高程精度的几何水准联测误差、卫星分布不对称、星历误差、多路径误差等因素逐一进行了分析，并提出了相应的改进措施。同时，还对高程拟合使用的稳健估计方法进行了探讨。     

气藏储层可采性评价方法探讨

气藏储量可采性评价的实质是对储层进行可采性评价。以苟西C2hl气藏为例，通过对该气藏储层孔隙度与渗透率、孔隙度与排驱压力及孔喉结构等反映储层连通性的各项参数分析，讨论储层可采性评价的方法。对气藏储量可采性评价及苟西C2hl气藏开发有一定指导意义。     

带肋钢筋套筒挤压连接的质量控制

针对太原可口可乐综合厂房主筋采用φ28、φ32三级钢存在的可焊性差的问题，提出了在施工中采用套筒挤压连接的方式，并对该方法的操作要点及质量控制措施进行了总结。     

Evaluating an intelligent diagnosis system of historical text comprehension

This work aims to present and evaluate a Fuzzy-Case Based Reasoning Diagnosis system of Historical Text Comprehension. The synergism of fuzzy logic and case based reasoning techniques handles the uncertainty in the acquisition of human expert's knowledge regarding learner's observable behaviour and integrates the right balance between expert's knowledge described in the form of fuzzy sets and previous experiences documented in the form of cases. The formative evaluation focused on the comparison of the system's performance to the performance of human experts concerning the diagnosis accuracy. The system was also evaluated for its behaviour when using two different historical texts. Empirical evaluation conducted with human experts and real students indicated the need for revision of the diagnosis model. The evaluation results are encouraging for the system's educational impact on learners and for future work concerning an intelligent educational system for individualized learning.     

FuzzyBagging: A novel ensemble of classifiers

In this work, a new method for the creation of classifier ensembles is introduced. The patterns are partitioned into clusters to group together similar patterns, a training set is built using the patterns that belong to a cluster. Each of the new sets is used to train a classifier. We show that the approach here presented, called FuzzyBagging, obtains performance better than Bagging.