Formulation of the Audze–Eglais Uniform Latin Hypercube design of experiments

This paper describes a method for formulating the Audze–Eglais Uniform Latin Hypercube design of experiments (DoE). The formulation of the Audze–Eglais DoE has not been reported in any previous research.The principle of the Audze–Eglais DoE is to distribute experiment points as uniformly as possible within the design variable domain. This is achieved by minimizing the potential energy of the points of a DoE. The DoE for N variables and P experiments is independent of the application under consideration, so once the design is formulated for P points and N design variables, it is stored in a matrix and need not be formulated again.The generation of the Audze–Eglais DoE is time consuming and requires optimization to solve the minimization problem. Therefore, the major aim of the paper is to identify a design variable encoding method for use in optimization. The two methods for encoding the DoE for use in the optimizer are presented. The method adopted in this study uses the co-ordinates of the plan points as design variables. The results for the potential energy are compared to published Audze–Eglais Uniform Latin Hypercube DoE and to random sampling Latin Hypercube DoE. The results indicate that the method works well and improvement over previous results has been achieved.     

Application of mathematical programming in the design of optimal control systems†

The problem of applying the various computational methods of mathematical programming in the design of an optimal control system is discussed. A general case of non-linear, non-autonomous, state equations, subject to inequality constraints on both state and control variables, is considered. Both continuous and discrete time systems are investigated. In case of discrete time systems, the sampling intervals are assumed generally unequal and aperiodic, with inequality constraints imposed upon them.

Systems like these impose considerable computational difficulties when treated by the maximum principle or dynamie programming. Using mathematical programming, one may simplify a wide class of those computational problems.

Several examples of applying mathematical programming to particular control problems are presented.     

On the design of optimal output feedback control systems†

For a linear control system with quadratic performance index the optimal control takes a feedback form of all state variables. However, if there are some states which are not fed in the control system, it is impossible to obtain the optimal feedback control by using the usual mathematical optimization technique such as dynamic programming or the maximum principle.

This paper presents the optimal control of output feedback systems for a quadratic performance index by using a new parameter optimization technique.

Since the optimal feedback gains depend on the initial states in the output feedback control system, two cases where (1) the initial states are known, and (2) the statistical properties of initial states such as mean and covariance matrices are known, are considered here. Furthermore, the proposed method for optimal output feedback control is also applied to sampled-data systems.     

Dissecting SpyEye – Understanding the design of third generation botnets

Botnet malware is improving with the latest (3rd) generation exemplified by the SpyEye and Zeus botnets. These botnets are important to understand because they target online financial transactions, primarily with banks. In this paper, we analyze the components from multiple generations of the SpyEye botnet in order to understand both how it works and how it is evolving. SpyEye is a sophisticated piece of malware with a modular design that eases the incorporation of improvements. We will discuss in detail the complete framework of SpyEye botnet consisting of the Bot Development Kit (BDK), the plugin architecture, the backend storage server, the bot design and the web-based Command and Control (C&C) management system. In addition, we also examine the techniques used by SpyEye to steal money.     

On the design of optimal and sub-optimal control systems†

Though dynamic programming is an excellent and versatile algorithm, there are many cases in which we cannot apply this algorithm favourably to control system design because of the limited capacity of a digital computer and other difficulties.

Considering these facts, the successively optimizing method and the combined algorithm of dynamic programming and successively optimizing method are presented in this paper.

One of the objects of this paper is to present a practical method for obtaining the optimal solution of control systems with an integral form performance index by the use of dynamic programming.

The other is to present sub-optiinal solutions by the successively optimizing method and the combined algorithm.

These methods are very easy when compared with dynamic programming. Furthermore, these sub-optimal solutions can be made to converge to the optimum by using the recurrent equations repeatedly.     

Dynamic anti-windup design for anticipatory activation：enlargement of the domain of attraction

Traditional anti-windup compensators are designed for activation immediately at the occurrence of actuator saturation.Recently,anti-windup compensators were designed for actuation either after the saturation has reached a certain level or in anticipation of its occurrence.In the case of static anti-windup compensators,it has been shown that an anti-windup compensator designed for activation in anticipation of actuator saturation would lead to better performance than those designed for immediate or delayed activation could,both in terms of transient performance and the size of the domain of attraction.More recently,it has been shown that a dynamic anti-windup compensator designed for anticipatory activation would also result in better transient performance than those designed for immediate or delayed activation could.In this paper,we design dynamic anti-windup compensators for the enlargement of the domain of attraction.These compensators are designed respectively for immediate,delayed and anticipatory activation.We will show by simulation that a dynamic anti-windup compensator designed for anticipatory activation would result in a larger domain of attraction than a dynamic anti-windup compensator designed for immediate or delayed activation could.     

Modular approach to the design and analysis of password-based security protocols

In this paper, a general framework for designing and analyzing password-based security protocols is presented. First we introduce the concept of "weak computational indistinguishability" based on current progress of password-based security protocols. Then, we focus on cryptographic foundations for password-based security protocols, i.e., the theory of "weak pseudorandomness". Furthermore, based on the theory of weak pseudorandomness, we present a modular approach to design and analysis of password-based security protocols. Finally, applying the modular approach, we design two kinds of password-based security protocols, i.e., password-based session key distribution (PSKD) protocol and protected password change (PPC) protocol. In addition to having forward secrecy and improved efficiency, new protocols are proved secure.     

Questions raised on the design of the “dead-man” device installed on trams

The reappearance of the tram in French cities over the past 20 years has stimulated innovation. Ensuring the attractiveness of this transit mode has meant conveying a distinctly modern image of the system. Inherent in the resurgence of this transit mode, a safety device, in the form of a monitoring system (the “dead-man device” in rail parlance) intended to mitigate risks related to driver blackout, has been reconfigured. This new device, inspired by subway systems, has been introduced without inciting any real inquiry into either the benefits or consequences, in terms of the conductor’s role and transport safety, arising from such an alternative form of tramway monitoring. An analysis of the process by which the mode of monitoring has been implemented serves to examine and reconsider, at least in part, the certification and regulatory system that accompanies tramway renovation projects in France.

The application of the methodology for secure cyber–physical systems design to improve the semi-natural model of the railway infrastructure

The paper suggests a new methodology for secure cyber–physical systems design. The proposed methodology consists of two main cycles. The main goal of the first cycle is in design of the system model, while the second one is about development of the system prototype. The key idea of the methodology is in providing of the most rational solutions that are improving the security of cyber–physical systems. Such solutions are called alternatives and built according to functional requirements and non-functional limitations to the system. Each cycle of the methodology consists of the verification process and seven stages that are associated with the used cyber–physical system model. The objective of the verification process is in checking of constructed models and prototypes in terms of their correctness and compatibility. The model represents cyber–physical systems as sets of building blocks with network between them, takes elements internal structure into account and allows direct and reverse transformations. The novelty of the suggested methodology is in the combination of design, development and verification techniques within a single approach. To provide an example of the design methodology application, in this paper it is used to improve the semi-natural model of the railway infrastructure.     

the 3rd way Corporate design

企业设计的理解并不仅仅在于规章制度。你可以在工作中获得不小的创意空间及可观的收入。本期，Darren Smith将带领大家走进这一重要的设计领域。[编者按]     

Hardware-in-the-loop simulation for the design and verification of the control system of a series–parallel hybrid electric city-bus

Hybrid electric buses have been a promising technology to dramatically lower fuel consumption and carbon dioxide (CO₂) emission, while energy management strategy (EMS) is a critical technology to the improvements in fuel economy for hybrid electric vehicles (HEVs). In this paper, a suboptimal EMS is developed for the real-time control of a series–parallel hybrid electric bus. It is then investigated and verified in a hardware-in-the-loop (HIL) simulation system constructed on PT-LABCAR, a commercial real-time simulator. First, an optimal EMS is obtained via iterative dynamic programming (IDP) by defining a cost function over a specific drive cycle to minimize fuel consumption, as well as to achieve zero battery state-of-charge (SOC) change and to avoid frequent clutch operation. The IDP method can lower the computational burden and improve the accuracy. Second, the suboptimal EMS for real-time control is developed by constructing an Elman neural network (NN) based on the aforementioned optimal EMS, so the real-time suboptimal EMS can be used in the vehicle control unit (VCU) of the hybrid bus. The real VCU is investigated and verified utilizing a HIL simulator in a virtual forward-facing HEV environment consisting of vehicle, driver and driving environment. The simulation results demonstrate that the proposed real-time suboptimal EMS by the neural network can coordinate the overall hybrid powertrain of the hybrid bus to optimize fuel economy over different drive cycles, and the given drive cycles can be tracked while sustaining the battery SOC level.     

The design of absorbing Bayesian pursuit algorithms and the formal analyses of their ε-optimality

The fundamental phenomenon that has been used to enhance the convergence speed of learning automata (LA) is that of incorporating the running maximum likelihood (ML) estimates of the action reward probabilities into the probability updating rules for selecting the actions. The frontiers of this field have been recently expanded by replacing the ML estimates with their corresponding Bayesian counterparts that incorporate the properties of the conjugate priors. These constitute the Bayesian pursuit algorithm (BPA), and the discretized Bayesian pursuit algorithm. Although these algorithms have been designed and efficiently implemented, and are, arguably, the fastest and most accurate LA reported in the literature, the proofs of their \(\epsilon\)-optimal convergence has been unsolved. This is precisely the intent of this paper. In this paper, we present a single unifying analysis by which the proofs of both the continuous and discretized schemes are proven. We emphasize that unlike the ML-based pursuit schemes, the Bayesian schemes have to not only consider the estimates themselves but also the distributional forms of their conjugate posteriors and their higher order moments—all of which render the proofs to be particularly challenging. As far as we know, apart from the results themselves, the methodologies of this proof have been unreported in the literature—they are both pioneering and novel.     

Reverse engineering in the design of turbine blades – a case study in applying the MAMDP

This paper presents a case study on the reverse engineering of turbine blades used in nuclear power generators. Reverse engineering has been widely recognised as a crucial step in the product design cycle. However, major problems with current reverse engineering technology are the inefficient surface reconstruction process, lack of digitising accuracy control in the data digitisation process, and bottlenecks resulted from huge amounts of digitised surface points in the surface modeling process. Moreover, under this limitation, modern concurrent engineering concepts are difficult to implement to obtain optimal product design. This study applies a developed reverse engineering approach – the modified adaptive model-based digitizing process (MAMDP) to the 3D geometric design of turbine blades. The approach integrates surface digitising and modeling processes of turbine blades into a single surface reconstruction process. Using the approach, accurate product CAD models can be efficiently generated and the product design cycle of turbine blades can be successfully linked.     

Evaluating the benefits of multimodal interface design for CoMPASS—a mobile GIS

The context of mobility raises many issues for geospatial applications providing location-based services. Mobile device limitations, such as small user interface footprint and pen input whilst in motion, result in information overload on such devices and interfaces which are difficult to navigate and interact with. This has become a major issue as mobile GIS applications are now being used by a wide group of users, including novice users such as tourists, for whom it is essential to provide easy-to-use applications. Despite this, comparatively little research has been conducted to address the mobility problem. We are particularly concerned with the limited interaction techniques available to users of mobile GIS which play a primary role in contributing to the complexity of using such an application whilst mobile. As such, our research focuses on multimodal interfaces as a means to present users with a wider choice of modalities for interacting with mobile GIS applications. Multimodal interaction is particularly advantageous in a mobile context, enabling users of location-based applications to choose the mode of input that best suits their current task and location. The focus of this article concerns a comprehensive user study which demonstrates the benefits of multimodal interfaces for mobile geospatial applications.     

Interactive scenarios—building ubiquitous computing concepts in the spirit of participatory design

The amount of information technology in our everyday lives is increasing and getting more and more ambient in our daily environments. The environments are supposed to be intelligent, adaptive, intuitive and interactive in the future. User participation for future concept building is essential, but challenging, when designing appliances that might be unfamiliar in their appearance, functionality and impressiveness compared to the users current everyday life. New allocated methods and viewpoints are needed for user experience design and evaluation of intelligent environments to build systems that naturally support the users in their daily life. We present interactive scenario building together with potential users (including role-playing, drama and improvisational aspects) as one promising tool for early concept definition phase.     

A value-driven approach to the design of service-oriented information systems—making use of conceptual models

We explain the importance of conceptual models for process design with service-oriented architectures (SOA) and illustrate how these models can be used to evaluate the value of SOA. To do so, a methodology is introduced, which comprises both the configuration and the implementation of processes by services and IT components. The approach presented here, makes it possible to evaluate the monetary and objective potentials of SOA, as well as to enhance SOA implementation by providing guidelines. The requirements analysis from an online-mail order company serves as a case study. The results show that up to now, economic aspects were ascribed too little importance in the SOA discussion.     

On the design of a reduced-order H ∞ controller for nonlinear sampled-data systems

In this paper, the problem of designing reduced-order H ^∞ controllers is studied for nonlinear continuous-time systems with sampled measurements. Using the concepts of dissipativity and differential game, sufficient conditions are derived for the existence of such reduced-order H ^∞ controllers. These conditions are expressed in terms of the solutions of two Hamilton–Jacobi inequalities, comprising a standard Hamilton–Jacobi inequality and a differential Hamilton–Jacobi inequality with jumps. These Hamilton–Jacobi inequalities are exactly those used in the construction of full-order H ^∞ controllers. When these conditions hold, state-space formulae are also given for such reduced-order controllers. An illustrative example is also included.     

Ontological reasoning in the design space exploration of advanced cyber–physical systems

Cyber–physical systems are becoming increasingly complex. In these advanced systems, the different engineering domains involved in the design process become more and more intertwined. Therefore, a traditional (sequential) design process becomes inefficient in finding good design options. Instead, an integrated approach is needed where parameters in multiple different engineering domains can be chosen, evaluated, and optimized to achieve a good overall solution. However, in such an approach, the combined design space becomes vast. As such, methods are needed to mitigate this problem.In this paper, we show a method for systematically capturing and updating domain knowledge in the context of a co-design process involving different engineering domains, i.e. control and embedded. We rely on ontologies to reason about the relationships between parameters in the different domains. This allows us to derive a stepwise design space exploration workflow where this domain knowledge is used to quickly reduce the design space to a subset of likely good candidates. We illustrate our approach by applying it to the design space exploration process for an advanced electric motor control system and its deployment on embedded hardware.