Theoretical foundation of a decision network for urban development

Planning problems are challenging and complex in that they usually involve multiple stakeholders with multi-attribute preferences. Thus few, if any, planning tools are useful in helping planners address such problems. Decision analysis is less useful than expected in dealing with planning problems because it focuses overwhelmingly on making a single decision for a particular decision-maker. In this paper, we describe the theoretical foundation of a planning tool called the ＇decision network＇, which aims to help planners make multiple and linked decisions when facing multiple stakeholders with multi-attribute preferences. The research provides a starting point for a fully fledged technology that is useful for dealing with complex planning problems. We first provide a general formulation of the planning problem that the decision network intends to address. We then introduce an efficient solution algorithm for this problem, with a numerical example to demonstrate how the algorithm works. The proposed solution algorithm is efficient, allowing computerization of the planning tool. We also demonstrate that the diagrammatic representation of the decision network is more efficient than that of a decision tree. Therefore, when dealing with challenging and complex planning problems, using the decision network to make multiple and linked decisions may yield more benefits than making such decisions independently.

Evolution Handoff Strategy for Real-Time Video Transmission over Practical Cognitive Radio Networks

The transmission delay of realtime video packet mainly depends on the sensing time delay(short-term factor) and the entire frame transmission delay(long-term factor).Therefore,the optimization problem in the spectrum handoff process should be formulated as the combination of microscopic optimization and macroscopic optimization.In this paper,we focus on the issue of combining these two optimization models,and propose a novel Evolution Spectrum Handoff(ESH)strategy to minimize the expected transmission delay of real-time video packet.In the microoptimized model,considering the tradeoff between Primary User's(PU's) allowable collision percentage of each channel and transmission delay of video packet,we propose a mixed integer non-linear programming scheme.The scheme is able to achieve the minimum sensing time which is termed as an optimal stopping time.In the macro-optimized model,using the optimal stopping time as reward function within the partially observable Markov decision process framework,the EHS strategy is designed to search an optimal target channel set and minimize the expected delay of packet in the long-term real-time video transmission.Meanwhile,the minimum expected transmission delay is obtained under practical cognitive radio networks' conditions,i.e.,secondary user's mobility,PU's random access,imperfect sensing information,etc..Theoretical analysis and simulation results show that the ESH strategy can effectively reduce the transmission delay of video packet in spectrum handoff process.

AN OPTIMAL C&D WASTE LOGISTICS NETWORK DESIGN FROM CONTRACTORS’PERSPECTIVE

The construction industry is one of the major producers of municipal solid waste.Although there are many studies in municipal solid waste management,the research on the recovery of recyclable building material from construction sites remains limited.This paper addresses the optimal design issue of the construction and demolition(C&D)waste logistics network based on the features of the construction industry from the contractors’perspective.The purpose of this paper is to provide an optimal C&D waste recycling network decision(RND)model considering the change of construction sites location over time.A multi-period and multi-objective mixed-integer linear programming model was developed to minimize the cost of C&D waste disposal for contractors,and to minimize the carbon emissions from C&D waste transportation.An application study was conducted to assess the performance of the RND model.Through some sensitivity analysis experiments based on an immune genetic algorithm,the influences of environmental policies and carbon tax policy on improving the recycling rate of C&D waste and reduce the carbon emission were explored.The findings of this research suggest that:(1)a RND model with the feature of the construction industry developed in this paper can effectively optimize the C&D waste logistics network;(2)government policies and laws are valid political instruments to improve the recycling rate of C&D waste;(3)the carbon-tax analyses demonstrate that a carbon tax policy can effectively reduce carbon emissions.

多跳无线网络中基于身份的解决方案

结合组合公钥的思想提出了一个较实用的基于身份的加密方案(IBE方案)——L-IBE方案。在安全性方面,L-IBE具有标准模型下可证明安全性,即在标准模型下有效的实现了DDH问题到新IBE方案的IND-sID-CPA攻击者的归约,并通过对比可知,其在模型、难题假设和归约程度方面优势明显。通过仿真表明,和已有的知名方案相比,L-IBE方案在计算效率(加解密计算开销)、密文长度和密钥长度方面具有更好的性能指标。由于L-IBE方案无需在线可信第三方即可实现节点间安全认证,适用于无固定基础设施支撑的多跳无线电网络密钥管理。

Statistical Prediction of Heavy Rain in South Korea

This study is aimed at the development of a statistical model for forecasting heavy rain in South Korea. For the 3-hour weather forecast system, the 10 km×10 km area-mean amount of rainfall at 6 stations （Seoul, Daejeon, Gangreung, （Jwangju, Busan, and Jeju） in South Korea are used. And the corresponding 45 synoptic factors generated by the numerical model are used as potential predictors. Four statistical forecast models （linear regression model, logistic regression model, neural network model and decision tree model） for the occurrence of heavy rain are based on the model output statistics （MOS） method. They are separately estimated by the same training data. The thresholds are considered to forecast the occurrence of heavy rain because the distribution of estimated values that are generated by each model is too skewed. The results of four models are compared via Heidke skill scores. As a result, the logistic regression model is recommended.

5G网络下的无证书身份隐藏签密方案

为解决5G网络下的用户身份信息泄露及隐私保护问题,提出一种无证书身份隐藏签密方案。运用密码学哈希函数将签密者的身份信息与其公钥进行绑定并生成用户部分私钥,以防止用户公钥替换攻击。在解签密阶段,输入信息中不包含签密者的身份信息,而是将其作为输出信息进行验证,从而实现签密者身份信息的隐藏。实验结果表明,在随机预言模型下,该方案的安全性规约于计算判定性Diffie-Hellman问题,且具有较高的通信效率与较低的计算开销。

Reliability Analysis of Aircraft Condition Monitoring Network Using an Enhanced BDD Algorithm

The aircraft condition monitoring network is responsible for collecting the status of each component in aircraft. The reliability of this network has a significant effect on safety of the aircraft. The aircraft condition monitoring network works in a real-time manner that all the data should be transmitted within the deadline to ensure that the control center makes proper decision in time. Only the connectedness between the source node and destination cannot guarantee the data to be transmitted in time. In this paper, we take the time deadline into account and build the task-based reliability model. The binary decision diagram （BDD）, which has the merit of efficiency in computing and storage space, is introduced when calculating the reliability of the network and addressing the essential variable. A case is analyzed using the algorithm proposed in this paper. The experimental results show that our method is efficient and proper for the reliability analysis of the real-time network.

An Information Fusion Model of Innovation Alliances Based on the Bayesian Network

To solve the problem of information fusion from multiple sources in innovation alliances, an information fusion model based on the Bayesian network is presented. The multi-source information fusion process of innovation alliances was classified into three layers, namely, the information perception layer, the feature clustering layer,and the decision fusion layer. The agencies in the alliance were defined as sensors through which information is perceived and obtained, and the features were clustered. Finally, various types of information were fused by the innovation alliance based on the fusion algorithm to achieve complete and comprehensive information. The model was applied to a study on economic information prediction, where the accuracy of the fusion results was higher than that from a single source and the errors obtained were also smaller with the MPE less than 3%, which demonstrates the proposed fusion method is more effective and reasonable. This study provides a reasonable basis for decision-making of innovation alliances.