The current formal verification practice focuses on functionality and does not consider verification of the non-functional attributes. In this study, we propose a method in which non-functional attributes are incorporated into the logic rules of inference in terms of composition of the linear logic and pi-calculus. Giving the credibility to non-functional attributes is important, especially in the cloud computing platform and IoT environments, where trust and security are ultra-important. Such studies have not been paid much attention by researchers and practitioners. In our approach, the evolvement of the non-functional attributes is included in the process of formal verification of the service composition scheme. In addition to theoretical analysis, we applied a tool named Visual IoT/robotics Programming Language Environment (VIPLE) to execute and verify the validity of the service composition model's function. We translate the proving process of the linear logic into the corresponding pi-calculus expressions. VIPLE can translate visual work flow into pi-calculus and can verify the correctness of pi-calculus expressions.

The focus area of this work is integrating reliability, availability, and maintainability (RAM) aspects into the conceptual process design of a real industrial system. Quantitative performance analysis has been carried out using Petri nets (PN) approach. In the present study, availability is considered as a performance measure which has been used as an indicator of the reliability and maintainability of the plant. The availability is considered in the process design stage for sorting different design alternatives. The proposed technique suggested in this paper provides a better way of understanding the behaviour of a system under varying operating conditions. It will also help practitioners in deciding upon maintenance strategy so that operation and maintenance cost can be optimised. Stochastic Petri nets (SPN) has been used to model the possible interactions among all active or parallel equipments in the system. Performance parameters have been evaluated using modelling and simulation software GRIF of Petri module.

The work described in this paper is concerned with a model-driven development of distributed real-time systems, like cyber-physical systems. A challenge in such systems' development consists of ensuring that a final implementation is compliant with its model used for functional and temporal property checking. In particular, a modern Java framework called Theatre is described which enables the modelling, analysis and synthesis of distributed real-time systems in a way which preserves such compliance. Theatre is based on the paradigm of actors, that is highly modular and encapsulated software entities which communicate with each other by asynchronous message-passing. Theatre rests on lightweight actors regulated by a customisable reflective control layer. Key features of Theatre are its support to seamless application development and timing predictability. The same model can be developed, without distortions, from early analysis through design and to a series of implementations. The paper describes Theatre and demonstrates its application to the development of a distributed dependable real-time system. Both modelling and property checking by simulation and real-time prototyping are illustrated. Theatre's current level of maturity and practical implementation in Java are detailed.

Knowing the occupancy information in each room can create energy saving through intelligent control of HVAC systems. In this paper, a classification-based occupant counting method using multiple WiFi sniffers is proposed firstly to get a coarse estimation of occupancy. Then, to deal with the false negative problem, i.e., those occupants who do not carry a smartphone or if the WiFi module is not enabled and cannot be counted, a p-persistent frequent itemsets with 1-right-hand-side (RHS)-based occupant correction algorithm is further proposed to improve the occupant detection accuracy using association analysis. Finally, our methods are validated through real experiments. Results show that our classification-based occupant detection method using multiple WiFi sniffers outperforms the 1-WiFi-sniffer-based method, and the association analysis-based correction algorithm can improve the accuracy because it can see occupants in buildings that the naive WiFi-based occupant detection method cannot see, which makes it suffice to be a viable approach to occupant estimation for intelligent buildings.

In Hall-Héroult cell, alumina dissolution has minimum requirement for superheat, however the superheat may not be uniform because the heat dissipation at the end parts is obviously higher than the middle part, which leads to the lower temperature at the end parts. In this study, the influences of alumina feeding dose distribution on the alumina concentration and the bath temperature near the feeder were simulated in computational numerical simulation, and then several cases with different feeding dose distribution were assessed by comparing the superheat per unit feeding dose. Furthermore, a methodology was proposed to optimise the alumina feeding dose distribution. It shows that the cases with lower alumina feeding dose at the end parts have better superheat distribution than the cases with uniform alumina feeding dose distribution. The optimal one is the case with feeding dose distribution (1.6, 1.8, 2.0, 2.0, 1.8, 1.6 kg) of alumina.

Dynamic performance of a high full-scale supporting formwork (HSF) subjected to horizontal impact loading was examined. It could be concluded that transverse X-bracings in the horizontal impact load direction have a more significant effect on the bearing performance and dynamic characteristics of an HSF than longitudinal X-bracings. An increase in the amount of poured concrete and the failure of the X-bracings reduces the natural frequency of the HSF. With the gradual increase in the amount of poured concrete, the maximum dynamic axial force of posts may increase from 4.33 kN to 12.77 kN under different X-bracing conditions during concrete placement. With failure of some main nodes, any impact load significantly increases the axial force acting on the posts. Dynamic axial force acting on some of the posts can increase by as much as 120% if 5% of fasteners fail during concrete pouring compared with that when all fasteners and X-bracings are intact.

Photovoltaic system maximum power point tracking (MPPT) has great potential for improvement of power generation. To optimise MPPT, this paper presents a prediction model based on an intelligent water drops optimisation support vector machine (IWD-SVM) for maximum power point working voltage. The Intelligent Water Drops (IWD) algorithm is used to optimise the penalty factor and kernel function parameters of the SVM, thus improving the training efficiency of the learning machine. Based on the optimisation algorithm, the SVM is used to model the PV array, the prediction results are compared to verify the accuracy and effectiveness of the IWD-SVM model. In addition, the IWD-SVM model is compared with the traditional neural network prediction results, which further verifies the validity of the proposed IWD-SVM model.

This article presents the NB-DEVS approach for the modelling and simulation of discrete event systems (DES), our objectives are to propose a new formal approach for describing the complex systems involving imperfectly. In our research we propose to integrate the naïve Bayesian network (NB) into DEVS formalism. The association of these two formalisms we have allow to extend the classic DEVS formalism to new domains. This new approach permits to study the system when its behaviour is uncertain. Finally, we simulated the evolution of the production system using our NB-DEVS approach. In simulation, we used several different models to replicate the empirical data. From these simulation iterations, we were able to verify and validate our model.