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To effectively protect critical infrastructure facilities (CIF), it is important to understand the focus of cybersecurity efforts. The concept of building security systems based on a variety of models describing various CIF functioning aspects is presented. The development of the concept is presented as a sequence of solving the following tasks. The basic concepts related to cyberattacks on CIF were determined, which make it possible to outline the boundaries of the problem and determine the level of formalization of the modeling processes. The proposed threat model takes into account possible synergistic/emergent features of the integration of modern target threats and their hybridity. A unified threat base that does not depend on CIF was formed. The concept of modeling the CIF security system was developed based on models of various classes and levels. A method to determine attacker's capabilities was developed. A concept for assessing the CIF security was developed, which allows forming a unified threat base, assessing the signs of their synergy and hybridity, identifying critical CIF points, determining compliance with regulatory requirements and the state of the security system. The mathematical tool and a variety of basic models of the concept can be used for all CIFs, which makes it possible to unify preventive measures and increase the security level. It is proposed to use post-quantum cryptography algorithms on crypto-code structures to provide security services. The proposed mechanisms provide the required stability (230–235group operations), the rate of cryptographic transformation is comparable to block-symmetric ciphers (BSC) and reliability (Perr10–9–10–12)

The increasing penetration of renewable energy sources (RESs) brings more power generation fluctuations into power systems, which puts forward higher requirement on the regulation capacities for maintaining the power balance between supply and demand. In addition to traditional generators for providing regulation capacities, the progressed information and communication technologies enable an alternative method by controlling flexible loads, especially thermostatically controlled loads (TCLs) for regulation services. This paper investigates the modeling and control strategies of aggregated TCLs as the virtual energy storage system (VESS) for demand response. First, TCLs are modeled as VESSs and compared with the traditional energy storage system (ESS) to analyze their characteristic differences. Then, the control strategies of VESS are investigated in microgrid and main grid aspects, respectively. It shows that VESS control strategies can play important roles in frequency regulation and voltage regulation for power systems’ stability. Finally, future research directions of VESS are prospected, including the schedulable potential evaluation, modeling of TCLs, hierarchical control strategies of VESS considering ESSs and RESs and reliability and fast response in frequency control for VESS.

International audience; Healthcare processes, such as sterilization, are extremely dynamic, complex, and multidisciplinary, making risk management in healthcare facilities particularly challenging. Risk-aware business process management is a new paradigm for better understanding such processes by identifying and evaluating the risks that go along with them. This paper focuses on analyzing the vulnerability of a hospital sterilization service through the use of a new framework, called e-BPRIM, which consists of the digitalization of the Business Process-risk management - Integrated Method (BPRIM). The e-BPRIM framework promotes and supports risk-aware process management with AdoBPRIM, a modeling environment using the ADOxx meta-modeling platform. The main e-BPRIM components will be introduced and then used to study the robustness of a given sterilization process taking into consideration several potential risks.

COVID-19 pandemic in France Coronavirus disease 2019 (COVID-19) exacted a heavy toll in France during March and April 2020. Quarantine measures were effective in reducing transmission by 84%, and some relaxation of social isolation was expected in May. Salje et al. fit transmission models for the epidemic in France to hospital admissions. The authors forecast that 2.9 million people will have been infected by 11 May, representing 4.4% of the population—a value inadequate for herd immunity. Daily critical care hospitalizations should reduce from several hundreds to tens of cases, but control will remain a delicate balancing act. Any relaxation of lockdown in France will have to be carefully controlled and monitored to avoid undermining more optimistic forecasts. Science , this issue p. 208

Urban water resources are the basis for the formation and development of cities and the source of urban water supply. However, with the acceleration of urbanization and the explosion of urban populations, the contradiction between water supply and demand in some areas, especially in big cities, has become increasingly prominent. It is simply not sufficient to rely on local conventional water resources to meet urban water demand, and a single source water supply mode has a higher vulnerability, resulting in greater safety risks in urban or regional water supply systems. Therefore, giving full play to the water supply capacity and carrying out multi-source water supplies are necessary and urgent. This paper gives an overview of the optimal allocation of multi-source for urban water supply concerning variation tendency, modeling methods and facing challenges. Based on the variation tendency of water consumption and water supply pattern in China, Tianjin is taken as a typical city for systematically outlining water supply changes and cause analysis. Subsequently, the modeling methods for proposing the optimal allocation scheme are summarized, which are composed of defining the topological relation, constructing the mathematical model and seeking the optimal solution. Ultimately, the current and emerging challenges are discussed including emergency operation of multi-source water supply and joint operation of water quality and quantity. These summaries and prospects provide a valuable reference for giving full play to the multi-source water supply capacity and carrying out relevant research so as to propose the optimal allocation scheme in urban multi-source water supply systems.

The key factors required to establish a precise soft sensor model for industrial processes include selection of variables affecting vital indicators from a large number of online measurement variables and elimination of the effects of unrelated disturbance variables. How to compress redundant information and retain the unique characteristic information contained by the selected variables is worthy of in-depth research. A novel soft sensor modeling method based on weighted maximal information coefficients (MICs) and a stacked autoencoder (SAE), hereinafter referred to as MICW-SAE, is proposed in this work. In our model, the MICs between each input and output variable are calculated and compared with the threshold before training each network in SAE. Then, input variables with low MICs are selected, and the average MIC index is calculated using other input variables. If the index is higher than the second threshold, the MIC of this specific variable is set to 0. Finally, the weights of all input variables are determined in accordance with the scale and placed into the loss function for training. The Boston house-price and naphtha dry point temperature datasets are used to prove the prediction ability of our model. Results demonstrate that MICW-SAE can enhance the output-related features of the input variables. Moreover, redundant information that can also be represented by other input variables are identified and excluded.

This paper presents a new method for modelling building energy performance based on a physical model to predict indoor environment and energy consumption by selecting best match parameters and variables. The innovative aspect is the introduction of an open and closed loop dynamics approach to explicitly presenting the complex behaviour and relationships between building indoor environment and energy consumption over time under uncertainty and disturbances and to simultaneously tracking the evolution of the complex lag-lead relationships between heating system and the building in order to keep the parameters and variables to the minimum. The model system is solved for an approximate analytical solution including physical and generalized parameters calibrated by measurements. Singular value decomposition model reduction technique is also applied to determine the model variables for the best approximation using lower dimensions. The approach is illustrated and validated with a case study of a swimming hall. A two-stage validation shows excellent agreements between the measurements and model (R2>0.9). The developed model is simple, accurate and straightforward that can serve the need in prediction and control in a wide variety of building applications.

Mechatronic engineers are essential joints within modern product development processes. They closely interact with the classical domains of mechanical, electrical and software engineering in order to support the design of customer oriented products of high integral functionality. Due to this, their day-to-day business in practice is strongly characterized by working with different departments and stakeholders out of different disciplines. For improving their communication and to build up a common understanding, an interdisciplinary model language is needed. The Systems Modeling Language (SysML) is a language for modeling these interdisciplinary technical aspects of a system. This paper presents an educational concept for SysML focusing the students’ abilities. The concept is taught to undergraduate mechatronic students in the fifth semester. In a multidisciplinary course (mechanical, electrical and software engineering) the students have lectures, exercises and a development project. In their development project they have to use SysML for modeling – concepts, prototypes, validation and optimization. So the developed SysML workshop is at the very beginning of the semester. This approach is designed as a two day workshop. It is split into three sessions – introduction, abstract modeling and detailing. At first basic elements and modeling techniques are introduced and the students start with a guided step-by-step example. The complexity of the modeling tasks is raised during the second and third session. During the workshop the undergraduate students start with individual pen and paper modeling, followed by small modeling groups with whiteboards. To simulate the industrial environment they finally interact in teams and build up a complex model, learn how they have to change and modify their model by changing boundary conditions and generating different views targeted for stakeholder domains – simulated by a role-play. After this two day workshop the students should have learned how to model in a non-sequential approach – like in reality - and are well prepared for their development project. The usage of software tools for modeling SysML isn’t part of this workshop. Goal of this approach is to teach the understanding and application of modeling with SysML. Working in a team together at the same model is practiced as well. The concept is currently tested in a pilot study with 10 students. The modeling understanding and knowledge of these students is nearly the same as of the mechatronic students. Aim of the study is to show the comprehensibility of the SysML-teaching approach, the needed time for the whole workshop and to identify lacks in the teaching material. This paper introduces the KIT SysML teaching approach for mechatronic engineering and reflects the concept with reference to publications of comparable development methods. It further points out the differences between teaching SysML to modeling beginners and the productive usage.

In this paper we proposed the novel air-conditioning system which combined induction ventilation and radiant air-conditioning. The indoor terminal device is the radiant induction-unit (RIDU). The RIDU is the induction unit combined with the pore radiant panel on which the copper pipes with rigid aluminum diffusion fins are installed. The two-stage evaporator chiller with the non-azeotropic mixture refrigerant is utilized in the system to reduce the initial investment in equipment. With the performance test and the steady state heat transfer model based on the theory of radiative heat transfer, the relationship between the induction ratio of the RIDU and the characteristic of the air supply was studied. Based on this, it is verified that the RIDU has a lower dew-point temperature and better anti-condensation performance than a traditional plate-type radiant panel. The characteristics of the radiation and convection heat transfer of the RIDU were studied. The total heat exchange of the RIDU can be 16.5% greater than that of the traditional plate-type radiant terminal.

With the popularity of various IoT mobile terminals such as mobile phones and sensors, the energy problems of IoT mobile terminals have attracted increasingly more attention. In this paper, we explore the impacts of some important factors of WiFi environments on the energy consumption of mobile phones, which are typical IoT end devices. The factors involve the WiFi signal strength under good signal conditions, the type and the amount of protocol packets that are initiated by WiFi APs (Access Points) to maintain basic network communication with the phones. Controlled experiments are conducted to quantitatively study the phone energy impacts by the above WiFi environmental factors. To describe such impacts, we construct a time-based signal strength-aware energy model and packet type/amount-aware energy models. The models constructed in the paper corroborate the following user experience on phone energy consumption: (1) a phone’s energy is drawn faster under higher WiFi signal strengths than under lower ones even in normal signal conditions; (2) phones consume energy faster in a public WiFi network than in a private one even in the basic phone state. The energy modeling methods proposed in the paper enable ordinary developers to analyze phone energy draw conveniently by utilizing inexpensive power meters as measurement tools. The modeling methods are general and are able to be used for phones of any type and any platform.

International audience; Although some research and commercial software for NC simulation is available, NC simulation modeling is still not matured. Most of them are based on G&M code. STEP-NC is a new data model for computer numerical control (CNC). It provides rich information for CNC machine tools, i.e. "what to do" based on features rather than "how to do" as for G-code. IDEF0 is a method designed to model the decisions, actions, and activities of an organization or system. It helps to organize and analyze a system and to promote a good communications between the analyst and the customer. So in this paper, from the view of system modeling, function modeling of NC simulation system based on STEP-NC is built by IDEF0 method. As a result, NC simulation system can be realized more efficiently.

3D modeling and visualization of geology volume is very important to interpret accurately and locate subsurface geology volume for mining exploration and deep prospecting. However, it faces a lack of information because the target area is usually unexplored and lacks geological data. This paper presents our experience in applying a 3D model of geology volume based on geophysics. This work has researched and developed a 3D visualization system. It is based on an OO (orientated object) approach and modular programming, uses the C++ language and Microsoft .NET platform. This system has built first a high resistivity method and MT database. The system uses irregular tetrahedrons to construct its model and then finally has built the 3D geological model itself.

The fast wave concept iterative process (FWCIP) and the boundary element method (BEM) are combined to evaluate the characteristic impedance of a microstrip filter, which is composed of (8×8) metallic via holes array. Simulations, measurements, and previous publications are in good agreement. © 2002 Wiley Periodicals, Inc. Int J RF and Microwave CAE 12: 236–246, 2002.

In order to establish an adaptive turbo-shaft engine model with high accuracy, a new modeling method based on parameter selection (PS) algorithm and multi-input multi-output recursive reduced least square support vector regression (MRR-LSSVR) machine is proposed. Firstly, the PS algorithm is designed to choose the most reasonable inputs of the adaptive module. During this process, a wrapper criterion based on least square support vector regression (LSSVR) machine is adopted, which can not only reduce computational complexity but also enhance generalization performance. Secondly, with the input variables determined by the PS algorithm, a mapping model of engine parameter estimation is trained off-line using MRR-LSSVR, which has a satisfying accuracy within 5‰. Finally, based on a numerical simulation platform of an integrated helicopter/turbo-shaft engine system, an adaptive turbo-shaft engine model is developed and tested in a certain flight envelope. Under the condition of single or multiple engine components being degraded, many simulation experiments are carried out, and the simulation results show the effectiveness and validity of the proposed adaptive modeling method.