Model checking temporal knowledge and commitments in multi-agent systems using reduction

Though modeling and verifying Multi-Agent Systems (MASs) have long been under study, there are still challenges when many different aspects need to be considered simultaneously. In fact, various frameworks have been carried out for modeling and verifying MASs with respect to knowledge and social commitments independently. However, considering them under the same framework still needs further investigation, particularly from the verification perspective. In this article, we present a new technique for model checking the logic of knowledge and commitments (CTLKC⁺). The proposed technique is fully-automatic and reduction-based in which we transform the problem of model checking CTLKC⁺ into the problem of model checking an existing logic of action called ARCTL. Concretely, we construct a set of transformation rules to formally reduce the CTLKC⁺ model into an ARCTL model and CTLKC⁺ formulae into ARCTL formulae to get benefit from the extended version of NuSMV symbolic model checker of ARCTL. Compared to a recent approach that reduces the problem of model checking CTLKC⁺ to another logic of action called GCTL¹, our technique has better scalability and efficiency. We also analyze the complexity of the proposed model checking technique. The results of this analysis reveal that the complexity of our reduction-based procedure is PSPACE-complete for local concurrent programs with respect to the size of these programs and the length of the formula being checked. From the time perspective, we prove that the complexity of the proposed approach is P-complete with regard to the size of the model and length of the formula, which makes it efficient. Finally, we implement our model checking approach on top of extended NuSMV and report verification results for the verification of the NetBill protocol, taken from business domain, against some desirable properties. The obtained results show the effectiveness of our model checking approach when the system scales up.     

Multiobjective PSO based adaption of neural network topology for pixel classification in satellite imagery

The proposed work involves the multiobjective PSO based adaption of optimal neural network topology for the classification of multispectral satellite images. It is per pixel supervised classification using spectral bands (original feature space). This paper also presents a thorough experimental analysis to investigate the behavior of neural network classifier for given problem. Based on 1050 number of experiments, we conclude that following two critical issues needs to be addressed: (1) selection of most discriminative spectral bands and (2) determination of optimal number of nodes in hidden layer. We propose new methodology based on multiobjective particle swarm optimization (MOPSO) technique to determine discriminative spectral bands and the number of hidden layer node simultaneously. The accuracy with neural network structure thus obtained is compared with that of traditional classifiers like MLC and Euclidean classifier. The performance of proposed classifier is evaluated quantitatively using Xie-Beni and β indexes. The result shows the superiority of the proposed method to the conventional one.     

Comparative evaluation of different statistical tools for the prediction of uniaxial compressive strength of rocks

In this study, uniaxial compressive strength (UCS), unit weight (UW), Brazilian tensile strength (BTS), Schmidt hardness (SHH), Shore hardness (SSH), point load index (Is₅₀) and P-wave velocity (V_p) properties were determined. To predict the UCS, simple regression (SRA), multiple regression (MRA), artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS) and genetic expression programming (GEP) have been utilized. The obtained UCS values were compared with the actual UCS values with the help of various graphs. Datasets were modeled using different methods and compared with each other. In the study where the performance indice PI_at was used to determine the best performing method, MRA method is the most successful method with a small difference. It is concluded that the mean PI_at equal to 2.46 for testing dataset suggests the superiority of the MRA, while these values are 2.44, 2.33, and 2.22 for GEP, ANFIS, and ANN techniques, respectively. The results pointed out that the MRA can be used for predicting UCS of rocks with higher capacity in comparison with others. According to the performance index assessment, the weakest model among the nine model is P7, while the most successful models are P2, P9, and P8, respectively.     

Liner services network design and fleet deployment with empty container repositioning

Transportation demand of shipping container fluctuates due to the seasonality of international trade, thus, every 3–6 months, the liner company has to alter its current liner shipping service network, redeploy ships and design cargo routes with the objective of minimizing the total cost. To solve the problem, the paper presents a mixed integer linear program model. The proposed model incorporates several relevant constraints, such as weekly frequency, the transshipment of cargo between two or more service routes, and transport time. Extensive numerical experiments based on realistic date of Asia–Europe–Oceania shipping operations show that the proposed model can solve real-case problems efficiently by CPLEX. The results demonstrate that the model can reduce ship’s capacity consumption and raise ships’ capacity utilization.     

A new wavelet based fault detection,classification and location in transmission lines

This paper deals with the application of wavelet transforms for the detection, classification and location of faults on transmission lines. A Global Positioning System clock is used to synchronize sampling of voltage and current signals at both the ends of the transmission line. The detail coefficients of current signals of both the ends are utilized to calculate fault indices. These fault indices are compared with threshold values to detect and classify the faults. Artificial Neural Networks are employed to locate the fault, which make use of approximate decompositions of the voltages and currents of local end. The proposed algorithm is tested successfully for different locations and types of faults.     

Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak

An intertwined supply network (ISN) is an entirety of interconnected supply chains (SC) which, in their integrity secure the provision of society and markets with goods and services. The ISNs are open systems with structural dynamics since the firms may exhibit multiple behaviours by changing the buyer-supplier roles in interconnected or even competing SCs. From the positions of resilience, the ISNs as a whole provide services to society (e.g. food service, mobility service or communication service) which are required to ensure a long-term survival. The analysis of survivability at the level of ISN requires a consideration at a large scale as resilience of individual SCs. The recent example of coronavirus COVID-19 outbreak clearly shows the necessity of this new perspective. Our study introduces a new angle in SC resilience research when a resistance to extraordinary disruptions needs to be considered at the scale of viability. We elaborate on the integrity of the ISN and viability. The contribution of our position study lies in a conceptualisation of a novel decision-making environment of ISN viability. We illustrate the viability formation through a dynamic game-theoretic modelling of a biological system that resembles the ISN. We discuss some future research areas.     

大口径光学元件装夹转运结构设计及分析

为了实现大口径光学元件的安全装夹、转运,通过光学元件开槽与不开槽两种装夹方式的分析,得出开槽夹紧转运方式将带来微裂纹、应力集中、成本高等缺陷,提出了利用摩擦力克服光学零件的重力和惯性力的低应力装夹转运方案。通过对光学元件低应力夹紧结构设计,并利用有限元分析方法,得到不开槽装夹方式下,光学元件的最大主应力为1.11 MPa,最大切应力为0.73 MPa,远低于光学元件破坏的强度极限,且受力均匀,无应力集中现象。     

高校实验室计算机网络故障诊断技术研究

为了提升高校实验数据处理水平,高校实验室的相关建设工作已经步入正轨,但层出不穷的信息安全问题也向高校实验室计算机网络维护工作提出了新的挑战。文章从现阶段高校实验室计算机网络的相关建设工作出发,简要论述引发网络故障的具体原因,并对其诊断技术进行探讨。     

基于“IPv6+”的智能IP网络方案

随着第4次工业革命的到来，人类社会正逐步迈向万物互联的智能时代。智能时代需要更加自动化、智能化的IP网络，基于“IPv6+”的SRv6、BIERv6等技术是使能新一代IP网络的关键基础。全面阐述了“IPv6+”的技术内涵，结合华为在智能 IP 网络解决方案上的创新和思考，介绍了“IPv6+”在极简连接、SLA 保障、专网体验、质量感知和云网一体等多个解决方案场景的关键技术与典型应用，助力5G与云业务发展。