Structural health monitoring system based on multi-agent coordination and fusion for large structure

In practical applications of structural health monitoring technology, a large number of distributed sensors are usually adopted to monitor the big dimension structures and different kinds of damage. The monitored structures are usually divided into different sub-structures and monitored by different sensor sets. Under this situation, how to manage the distributed sensor set and fuse different methods to obtain a fast and accurate evaluation result is an important problem to be addressed deeply. In the paper, a multi-agent fusion and coordination system is presented to deal with the damage identification for the strain distribution and joint failure in the large structure. Firstly, the monitoring system is adopted to distributedly monitor two kinds of damages, and it self-judges whether the static load happens in the monitored sub-region, and focuses on the static load on the sub-region boundary to obtain the sensor network information with blackboard model. Then, the improved contract net protocol is used to dynamically distribute the damage evaluation module for monitoring two kinds of damage uninterruptedly. Lastly, a reliable assessment for the whole structure is given by combing various heterogeneous classifiers strengths with voting-based fusion. The proposed multi-agent system is illustrated through a large aerospace aluminum plate structure experiment. The result shows that the method can significantly improve the monitoring performance for the large-scale structure.     

Low complexity quantum private queries protocol

Private information retrieval(PIR) is an important privacy protection issue of secure multi-party computation, but the PIR protocols based on classical cryptography are vulnerable because of new technologies,such as quantum computing and cloud computing. The quantum private queries(QPQ) protocols available, however, has a high complexity and is inefficient in the face of large database. This paper, based on the QKD technology which is mature now, proposes a novel QPQ protocol utilizing the key dilution and auxiliary parameter. Only N quits are required to be sent in the quantum channel to generate the raw key, then the straight k bits in the raw key are added bitwise to dilute the raw key, and a final key is consequently obtained to encrypt the database. By flexible adjusting of auxiliary parameters θ and k, privacy is secured and the query success ratio is improved. Feasibility and performance analyses indicate that the protocol has a high success ratio in first-trial query and is easy to implement, and that the communication complexity of O(N) is achieved.     

Enhance cycling performance of LiMn2O4 cathode by Sr2+ and Cr3+ doping

Spinel LiSr_0·1Cr_0·1Mn_1·8O₄ was synthesised by high temperature solid state method in order to enhance the electrochemical performance. The LiSr_0·1Cr_0·1Mn_1·8O₄ (LSCMO) materials were characterised by X-ray diffraction (XRD), scanning electron microscopy (SEM) and electrochemical tests. The XRD and SEM studies confirm that LSCMO had spinel crystal structure with a space group of Fd3m, and the particle of LSCMO shows irregular shape. The cyclic voltammetry data illustrated that the heavy current charge–discharge performance of LMO was improved by Sr²⁺ and Cr³⁺ doping. The galvanostatic charge–discharge of LSCMO cathode materials was measured at 1, 5, 10 and 20 C. The results indicated that LSCMO improved the capacity retention.     

Usability of a cloud-based collaborative learning framework to improve learners’ experience

Computer-Supported Collaborative Learning (CSCL) is concerned with how Information and Communication Technology (ICT) might facilitate learning in groups which can be co-located or distributed over a network of computers such as Internet. CSCL supports effective learning by means of communication of ideas and information among learners, collaborative access of essential documents, and feedback from instructors and peers on learning activities. As the cloud technologies are increasingly becoming popular and collaborative learning is evolving, new directions for development of collaborative learning tools deployed on cloud are proposed. Development of such learning tools requires access to substantial data stored in the cloud. Ensuring efficient access to such data is hindered by the high latencies of wide-area networks underlying the cloud infrastructures. To improve learners’ experience by accelerating data access, important files can be replicated so a group of learners can access data from nearby locations. Since a cloud environment is highly dynamic, resource availability, network latency, and learner requests may change. In this paper, we present the advantages of collaborative learning and focus on the importance of data replication in the design of such a dynamic cloud-based system that a collaborative learning portal uses. To this end, we introduce a highly distributed replication technique that determines optimal data locations to improve access performance by minimizing replication overhead (access and update). The problem is formulated using dynamic programming. Experimental results demonstrate the usefulness of the proposed collaborative learning system used by institutions in geographically distributed locations.     

Two-agent two-machine flowshop scheduling with learning effects to minimize the total completion time

We study a two-agent scheduling problem in a two-machine permutation flowshop with learning effects. The objective is to minimize the total completion time of the jobs from one agent, given that the maximum tardiness of the jobs from the other agent cannot exceed a bound. We provide a branch-and-bound algorithm for the problem. In addition, we present several genetic algorithms to obtain near-optimal solutions. Computational results indicate that the algorithms perform well in either solving the problem or efficiently generating near-optimal solutions.     

Modelling of black carbon statistical distribution and return periods of extreme concentrations

Eight datasets of 1-h black carbon (BC) concentrations measured in Warsaw agglomeration (Poland), at urban background and sub-urban sites, and in Racibórz, a small town in Upper Silesia district (regional background site) were analyzed to evaluate BC levels, daily profiles and statistical distributions of concentrations in Central-Eastern European region. The observed mean levels ranged from 1483 ng m⁻³ in suburban site during summer to 3358 ng m⁻³ in regional background site in winter. Observed diurnal patterns were bimodal in the locations dominated by traffic emissions, but unimodal, with elevated evening peak in individually heated residential area. Three theoretical frequency distributions were applied to fit analyzed datasets separately. The lognormal distribution was the most appropriate to represent the middle-range values, while the high concentrations were satisfactorily predicted by the type I two-parameter exponential distribution which was used to estimate the return periods of extreme concentrations for winter months.     

一种实用的多数据库量子信息检索协议

针对目前量子私有信息检索不能适用与云存储的多数据库问题,基于现在成熟的量子密钥分发方法,提出了一种适合在多数据库环境下,实用的量子私有信息检索协议。对于不同大小的数据库,协议可通过调节参数θ和k,在保证数据库安全及用户隐私的情况下,完成信息的检索。性能分析结果表明,协议的通信复杂度低,检索成功率高、易于实施。     

Use of conditioning time to investigate the mechanisms of interactions of selected fatty acids on hematite Part II laboratory investigations

It is the aim of this paper to examine the effects of conditioning time on the flotation of hematite using three technical grade fatty acid reagents as providing additional evidence on their mechanism of interaction with the hematite surface. Various mechanisms have been postulated as occurring as conditioning time is increased. Both physical (e.g. conditioning time and power input) and chemical (nature, dispersion and solubility of the adsorbing species) contribute to the mechanisms of attachment of collector. In this paper, the mechanism of attachment of oleate to hematite can be readily explained by chemisorption, but the mechanism of attachment of lauric acid appears to be physical adsorption at neutral pH. The flotation of hematite with a mixture of tallow-type fatty acids (palmitic, stearic and oleic acids) is very sensitive to conditioning time, and suggests that, even though flotation is very effective at short conditioning times, it is very susceptible to the presence of fines and their associated high surface areas. It is therefore obvious that both the physical and chemical conditions contribute to the mechanisms of adsorption of fatty acids on iron-containing oxide minerals and must be understood in order to optimise the flotation of these minerals in an industrial situation.