Data fusion and transfer learning empowered granular trust evaluation for Internet of Things

In the Internet of Things (IoT), a huge amount of valuable data is generated by various IoT applications. As the IoT technologies become more complex, the attack methods are more diversified and can cause serious damages. Thus, establishing a secure IoT network based on user trust evaluation to defend against security threats and ensure the reliability of data source of collected data have become urgent issues, in this paper, a Data Fusion and transfer learning empowered granular Trust Evaluation mechanism (DFTE) is proposed to address the above challenges. Specifically, to meet the granularity demands of trust evaluation, time–space empowered fine/coarse grained trust evaluation models are built utilizing deep transfer learning algorithms based on data fusion. Moreover, to prevent privacy leakage and task sabotage, a dynamic reward and punishment mechanism is developed to encourage honest users by dynamically adjusting the scale of reward or punishment and accurately evaluating users’ trusts. The extensive experiments show that: (i) the proposed DFTE achieves high accuracy of trust evaluation under different granular demands through efficient data fusion; (ii) DFTE performs excellently in participation rate and data reliability.     

p-Median and p-dispersion problems: A bi-criteria analysis

Given a collection of n locations and a symmetric measure of distance (difference) between each pair of locations, we seek to identify (select) a subset of p locations so as to achieve two distinct objectives. The first objective is to use the selected locations as centers (medians) of p groups that would partition the entire collection and minimize the total distance between the locations and their respective group medians. The second objective is to maximize the minimum distance (diversity) among the selected locations themselves. We study this problem as a multi-objective optimization problem and propose an iterative algorithm to obtain its non-dominated frontier. At each iteration we construct and solve a 0–1 integer programming problem. Through a computational experiment we show that this algorithm is computationally effective for small to medium size instances of the problem. We also propose a Lagrangian heuristic algorithm for solving larger instances of this problem.     

Efficient multicast search under delay and bandwidth constraints

The issue of a multicast search for a group of users is discussed in this study. Given the condition that the search is over only after all the users in the group are found, this problem is called the Conference Call Search (CCS) problem. The goal is to design efficient CCS strategies under delay and bandwidth constraints. While the problem of tracking a single user has been addressed by many studies, to the best of our knowledge, this study is one of the first attempts to reduce the search cost for multiple users. Moreover, as oppose to the single user tracking, for which one can always reduce the expected search delay by increasing the expected search cost, for a multicast search the dependency between the delay and the search cost is more complicated, as demonstrated in this study. We identify the key factors affecting the search efficiency, and the dependency between them and the search delay. Our analysis shows that under tight bandwidth constraints, the CCS problem is NP-hard. We therefore propose a search method that is not optimal, but has a low computational complexity. In addition, the proposed strategy yields a low search delay as well as a low search cost. The performance of the proposed search strategy is superior to the implementation of an optimal single user search on a group of users. Amotz Bar-Noy received the B.Sc. degree in 1981 in Mathematics and Computer Science and the Ph.D. degree in 1987 in Computer Science, both from the Hebrew University, Israel. From October 1987 to September 1989 he was a post-doc fellow in Stanford University, California. From October 1989 to August 1996 he was a Research Staff Member with IBM T. J. Watson Research Center, New York. From February 1995 to September 2001 he was an associate Professor with the Electrical Engineering-Systems department of Tel Aviv University, Israel. From September 1999 to December 2001 he was with AT research labs in New Jersey. Since February 2002 he is a Professor with the Computer and Information Science Department of Brooklyn College - CUNY, Brooklyn New York. Zohar Naor received the Ph.D. degree in Computer Science from Tel Aviv University, Tel Aviv, Israel, in 2000. Since 2003 he is with the University of Haifa, Israel. His areas of interests include wireless networks, resource management of computer networks, mobility, search strategies, and multiple access protocols.     

信息社会的理念与发展

首先介绍了信息社会的基本特征，并围绕信息的接入、信息的发布、知识产权、隐私权、信息安全和文化多元性等阐述了信息伦理的内容和概念。最后介绍了信息对人类生活的影响，主要包括交往方式、信息处理方式、学习方式、商业运作方式、医疗方式、产品设计方式、科研方式和政府工作方式等。     

我国放射性物质运输概况

本文介绍了我国放射性物质运输概况(除台湾省外)。目前,全国放射性物质货包的年运输最约10万件,总放射性活度为1.8PBq,运输的放射性同位素主要是~(131)I、~(32)P 和~(198)Au 等。承运人员的年剂量当量是相当低的,一般小于5mSv。由于十分重视放射性物质的安全运输,所以没有发生过严重事故。文中还讨论了放射性物质运输中的防护问题。     

烟气轮机特殊状态下的保护

从烟气轮机超速的极限开始 ,分别按照阀门的关闭时间为 1 .5s和 6s的两种典型状态 ,对烟机在联轴节断裂等特殊工况下的超速情况进行了分析。最后 ,对烟气轮机在特殊工况下的保护提出了建议。     

钻井液完井液质量监控体系

经多年实践，中原油田建立了钻井过程中的钻井液完井液质量监控体系。讨论了钻井过程中钻井液完井液质量监控体系的控制指标及对有关指标的要求，对油气层保护工作措施和效果进行了分析。钻井过程中应进一步加强钻井液完井液质量监控措施，形成更加规范的监督、监测一体化队伍。     

开关磁阻电机调速系统在煤矿井下的应用

随着开关磁阻电机的调速控制系统日臻完善，因其优越性能使得在各行业得到迅速推广，但在煤矿井下的特定环境中使用该调速系统仍存在着诸多问题有待分析研究。     

单片机破解的常用方法及应对策略

介绍了单片机内部密码破解的常用方法，重点说明了侵入型攻击／物理攻击方法的详细步骤，最后，从应用角度出发，提出了对付破解的几点建议。     

Efficient primal-dual heuristic for a dynamic location problem

In this paper the dynamic location problem with opening, closure and reopening of facilities is formulated and an efficient primal-dual heuristic that computes both upper and lower limits to its optimal solution is described. The problem here studied considers the possibility of reconfiguring any location more than once over the planning horizon. This problem is NP-hard (the simple plant location problem is a special case of the problem studied). A primal-dual heuristic based on the work of Erlenkotter [A dual-based procedure for uncapacitated facility location. Operations Research 1978;26:992–1009] and Van Roy and Erlenkotter [A dual-based procedure for dynamic facility location. Management Science 1982;28:1091–105] was developed and tested over a set of randomly generated test problems. The results obtained are quite good, both in terms of the quality of lower and upper bounds calculated as in terms of the computational time spent by the heuristic. A branch-and-bound procedure that enables to optimize the problem is also described and tested over the same set of randomly generated problems.