Use of the time constant to detect corrosion speed in reinforced concrete structures

The relatively simple to measure ‘time constant’ is presented as an index for characterizing the level of corrosion experienced by steel in concrete. This communication, largely in the form of a technical note, explicitly illustrates that the time constant determined from electrochemical testing has significant merit for monitoring corrosion of steel in concrete, and appears to be insensitive to the area of electrode being probed. In this work, the time constant, κ, is determined following a galvanostatic excitation signal, revealing a good correlation between the value of κ and corrosion status across specimens of widely varying geometry. Although this notion has been suggested in the past, this work presents both a survey and consolidated review to indicate the utility of the parameter as an index to corrosion rate on-site.     

A review on improving the autonomy of unmanned surface vehicles through intelligent collision avoidance manoeuvres

In recent years unmanned vehicles have grown in popularity, with an ever increasing number of applications in industry, the military and research within air, ground and marine domains. In particular, the challenges posed by unmanned marine vehicles in order to increase the level of autonomy include automatic obstacle avoidance and conformance with the Rules of the Road when navigating in the presence of other maritime traffic. The USV Master Plan which has been established for the US Navy outlines a list of objectives for improving autonomy in order to increase mission diversity and reduce the amount of supervisory intervention. This paper addresses the specific development needs based on notable research carried out to date, primarily with regard to navigation, guidance, control and motion planning. The integration of the International Regulations for Avoiding Collisions at Sea within the obstacle avoidance protocols seeks to prevent maritime accidents attributed to human error. The addition of these critical safety measures may be key to a future growth in demand for USVs, as they serve to pave the way for establishing legal policies for unmanned vessels.     

Collaborative representation with reduced residual for face recognition

Collaboration representation-based classification (CRC) was proposed as an alternative approach to the sparse representation method with similar efficiency. The CRC is essentially a competition scheme for the training samples to compete with each other in representing the test sample, and the training class with the minimum representation residual from the test sample wins the competition in the classification. However, the representation error is usually calculated based on the Euclidean distance between a test sample and the weighted sum of all the same-class samples. This paper exploits alternative methods of calculating the representation error in the CRC methods to reduce the representation residual in a more optimal way, so that the sample classes compete with each other in a closer range to represent the test sample. A large number of face recognition experiments on three face image databases show that the CRC methods with optimized presentation residual achieve better performance than the original CRC, and the maximum improvement in classification accuracy is up to 12 %.     

Model checking response times in Networked Automation Systems using jitter bounds

Response time (RT) of Networked Automation Systems (NAS) is affected by timing imperfections induced due to the network, computing and hardware components. Guaranteeing RT in the presence of such timing imperfections is essential for building dependable NAS, and to avoid costly upgrades after deployment in industries.This investigation proposes a methodology and work-flow that combines modelling, simulation, verification, experiments, and software tools to verify the RT of the NAS during the design, rather than after deployment. The RT evaluation work-flow has three phases: model building, modelling and verification. During the model building phase component reaction times are specified and their timing performance is measured by combining experiments with simulation. During the modelling phase, component based mathematical models that capture the network architecture and inter-connection are proposed. Composition of the component models gives the NAS model required for studying the RT performance on system level. Finally, in the verification step, the NAS formal models are abstracted as UPPAAL timed automata with their timing interfaces. To model timing interfaces, the action patterns, and their timing wrapper are proposed. The formal model of high level of abstraction is used to verify the total response time of the NAS where the reactions to be verified are specified using a subset of timed computation tree logic (TCTL) in UPPAAL model checker. The proposed approach is illustrated on an industrial steam boiler deployment.     

灾害中生活类物资的供应分析——以汶川地震重灾区物资供应为例

救灾生活类物资在供应中面临着优化运输路线、降低运输成本、缩短运输时间3个难题。文章采用相关机会多目标规划模型,以汶川地震为例,总结并完善了自然灾害救助中的多物资的协作供应模式,为突发性重大灾害中多物资的协作供应的组织、实施、管理提供参考支持。     

A passive tree-based backbone construction scheme for MANETs

Backbone-based broadcast schemes are effective in alleviating the broadcast storm problem in mobile ad hoc networks (MANETs). However, periodically hello packets used to maintain a backbone usually lead to extra control overhead. In this paper, passive tree-based backbone construction scheme (PTBCS) is proposed as a backbone construction scheme for MANETs. Different from other schemes, each node in PTBCS determines its role by intercepting packet transmissions in the air during a special waiting period. Hence, its most remarkable advantage is that there are no periodical packet transmissions specially for backbone construction. The property that the nodes selected by PTBCS make up a connected dominating set (CDS) of the network is proven with several ideal assumptions. Simulation results show that PTBCS is effective when compared with some other typical backbone construction schemes.     

Optimization for limited angle tomography in medical image processing

This paper aims to reduce the problems of incomplete data in computed tomography, which happens frequently in medical image process and analysis, e.g., when the high-density region of objects can only be penetrated by X-rays at a limited angular range. As the projection data are available only in an angular range, the incomplete data problem can be attributed to the limited angle problem, which is an ill-posed inverse problem. Image reconstruction based on total variation (TV) reduces the problem and gives better performance on edge-preserving reconstruction; however, the artificial parameter can only be determined through considerable experimentation. In this paper, an effective TV objective function is proposed to reduce the inverse problem in the limited angle tomography. This novel objective function provides a robust and effective reconstruction without any artificial parameter in the iterative processes, using the TV as a multiplicative constraint. The results demonstrate that this reconstruction strategy outperforms some previous ones.