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This paper investigates resource provisioning in cyber-physical systems (CPSs) by developing a new definition of anelasticity. A flat semi-dormant multicontroller (FSDMC) model is established on a special type of CPS platform named arbitrated networked control system with dual communication channels. A novel, quantitative, and formal definition of anelasticity for the FSDMC is proposed. A new finite capacity M/M/c queuing system with ${N}$ -policy and asynchronous multiple working vacations of partial servers is established, and the FSDMC is modeled as a quasi-birth-and-death process to obtain the stationary probability distribution of the system. Based on the queueing model, we quantify various performance indices of the system to build a nonlinear cost-performance ratio (CPR) function. An optimization model is presented to minimize the CPR. A particle swarm optimization (PSO) algorithm is used to find the optimum solution of the optimization model and obtain the optimal configuration values of the system parameters under stability condition. By changing the system parameters, the sensitivity of the system performance indices and the CPR are analyzed, respectively. The unexpected workload varies randomly over time. Thus, an M/M/1/K queue is constructed in a Markovian environment by employing a three-state, irreducible Markov process. In this queue, the conditional average queue length and the probabilities of the three-state process are calculated. Then, the anelasticity value of the system is precisely determined. When the average arrival rate exceeds the average service rate in the queueing system, an optimal CPR unchanged adaptive algorithm based on PSO is designed to dynamically adjust the controller service rate. Extensive numerical results show the usefulness and effectiveness of the proposed techniques and exhibit that the system can maintain elastic invariance in adaptive adjustment parameters. [ABSTRACT FROM AUTHOR]

Liveness of Petri nets means all activities in a modeled system can potentially take place and thus implies deadlock freedom. The research on liveness analysis approaches is inadequate. This paper proposes a liveness judgment reachability graph (LJRG) approach to analyze the liveness of \omega -independent Petri nets. Such nets can be loosely explained as a class of unbounded Petri nets in which the changes of tokens in unbounded places are not related to each other. This paper proposes several algorithms to transform a new modified reachability tree to a new modified reachability graph and then transform it to an LJRG. It then develops the application of LJRG into the liveness analysis of \omega -independent unbounded Petri nets. The proposed method provides a new theoretical method and important tool for the liveness analysis of unbounded Petri nets. It is illustrated via some examples. [ABSTRACT FROM AUTHOR]

This paper presents an ordinary Petri net (PN)-based approach to the modeling and race-detection problems of programs for programmable logic controllers (PLCs). First, a PLC program is formalized by a graph where nodes represent contacts and coils. Second, an algorithm is proposed to translate this graph into an ordinary PN. Third, a method is presented to detect whether there exists a race in a program by using a reachability graph technique, to locate a race by introducing the race path, and to correct a race by analyzing the subnet that contains it. An example is utilized to illustrate the theoretic results. [ABSTRACT FROM AUTHOR]

While recently published face alignment algorithms mainly focused on occlusion, low image quality, and complex head poses, subtle variances of facial components were often overlooked. In this correspondence paper, we propose a new approach called cascaded elastically progressive model aiming for pixel-wise landmark localization. First of all, elastically progressive model (EPM) is designed to synthesize the prior knowledge of face shape and appearance of test image. More specifically, a novel framework referred to as inherent linear structure (ILS) is explored for capturing the characteristics of the shape, which is more plastic and flexible than extensively used principle component analysis-based modeling. A locally linear support vector machine (LL-SVM) is used as local expert for searching candidate feature points. In order to optimally integrate ILS with localization results of LL-SVM, we introduce Kalman filter (KF) to dynamically estimate the true shape in the sense of least mean square error. Two schemes are utilized based on our modeling of KF. First, we embedded heuristic line-like search strategy into the framework to guarantee and accelerate the convergence. Second, Kalman gain is manipulated adaptively in accordance with the confidence of the localizers so that poorly localized points are more subject to global constraint than well localized ones. To further improve robustness to initializations, two EPMs are cascaded, in which primary EPM detects the global structure and secondary EPM captures the details. Validation experiments are conducted on in-the-wild LFPW and HELEN databases. Our method shows advantages for accurate landmark localization compared with prevailing methods. [ABSTRACT FROM AUTHOR]

The systems dynamics and control engineering (FDI) and the artificial intelligence diagnosis (DX) communities have developed complementary approaches that exploit structural relations in the system model to find efficient solutions for the residual generation and residual evaluation steps in fault detection and isolation in dynamic systems. This paper compares three different structural fault diagnosis techniques, two from the DX community and one from the FDI community. To simplify our comparison, we start with bond graphs as the common system modeling language and develop a graph-based framework using temporal causal graphs as the basis for analyzing the three fault isolation approaches. This framework allows for systematic comparison of the diagnosability properties of the three algorithms. The three-tank system is used as a running example to illustrate our concepts and algorithms. [ABSTRACT FROM AUTHOR]

Petri nets are suitable for modeling and analysis of business processes. However, the lack of data concepts often makes Petri-net-based models excessively large and difficult to analyze especially when process logic is sensitive to changes of process attribute values. Emergency treatment processes are a typical example of this situation. To solve the aforementioned problems, this paper proposes a new hierarchical Petri net model for modeling and verification of emergency treatment processes. The hierarchical Petri net model includes three separate but closely related models, i.e., a business process logic net, a business process semantic net, and a set of case models. Business process logic nets are used to model the task dependencies disregarding semantic information. Business process semantic nets introduce data concepts to business process logic nets to model semantic information such as process attributes or conditions of sequence flows. Case models are used to model the practical routes of specific business instances. Based on the three models, a formal verification algorithm of an emergency treatment process is presented. Finally, the hierarchical modeling and verification methods are validated by an emergency treatment process of highways under snow/ice weather conditions. [ABSTRACT FROM AUTHOR]