Orienting body coordinate frames using Karhunen–Loève expansion for more effective structural simplification

As part of an effort to create an automated modular modeling environment, previous work by the authors developed a junction-inactivity-based structural simplification technique that is particularly suitable for bond-graph models. The technique is highly sensitive to the orientation of the body coordinate frames in multibody systems: improper alignment of body coordinate frames may prohibit a significant simplification. This paper demonstrates how the Karhunen–Loève expansion can be used to automatically detect the existence of and to find the transformation into body coordinate frames that render the bond graph of a multibody system more conducive to simplification. The proposed technique is demonstrated using the simple example of a 3D pendulum constrained to move in a plane, but is applicable to arbitrarily complex multibody dynamics problems. The conclusion is that the Karhunen–Loève expansion successfully complements the junction-inactivity-based structural simplification technique when multibody dynamics are involved in the system, and thus significantly contributes to the development of an automated modular modeling environment.     

Collecting Metrics for CORBA-Based Distributed Systems

The Common Object Request Broker Architecture (CORBA) supports the creation of distributed systems that cross processor, language and paradigm boundaries. These systems can be large and complex entities that consume considerable resources in their creation and execution. Measurements of characteristics of software systems is an important area of study in general and of particular interest for distributed systems. In this paper, we present a specific technique for instrumenting components in a distributed system. The technique constructs a wrapper around the component being measured. The wrapper monitors interactions with the ORB (Object Request Broker) and other components. Each wrapper mimics the interface of the component that it is wrapping so that the remaining objects in the system do not need modification. Two approaches to wrapping the component are presented and contrasted. The result is an efficient and modular technique that can quickly be applied to a component.     

A modular approach to the dynamics of complex multirobot systems

This work presents a modular approach for the dynamic modeling and efficient simulation of complex robot systems composed of multiple robots constrained by multiple concurrent contacts. The modular nature of the algorithm enables existing open-chain models for individual robots and other mechanisms to be incorporated without significant reprogramming, while a general contact model allows both holonomic and nonholonomic constraints in the system. An example is provided to illustrate the algorithm's modularity and demonstrate its application. In addition to the development of the dynamic equations, this paper will discuss the implementation of the simulation algorithm in detail, including issues of computational complexity.     

Quantitative risk-based security prediction for component-based systems with explicitly modeled attack profiles

Systems and software architects require quantitative dependability evaluations, which allow them to compare the effect of their design decisions on dependability properties. For security, however, quantitative evaluations have proven difficult, especially for component-based systems. In this paper, we present a risk-based approach that creates modular attack trees for each component in the system. These modular attack trees are specified as parametric constraints, which allow quantifying the probability of security breaches that occur due to internal component vulnerabilities as well as vulnerabilities in the component’s deployment environment. In the second case, attack probabilities are passed between system components as appropriate to model attacks that exploit vulnerabilities in multiple system components. The probability of a successful attack is determined with respect to a set of attack profiles that are chosen to represent potential attackers and corresponding environmental conditions. Based on these attack probabilities and the structure of the modular attack trees, risk measures can be estimated for the complete system and compared with the tolerable risk demanded by stakeholders. The practicability of this approach is demonstrated with an example that evaluates the confidentiality of a distributed document management system.     

Symbolic manipulation techniques for model simplification in object-oriented modelling of large scale continuous systems

In the present work, techniques for the symbolic manipulation of general nonlinear differential algebraic equation (DAE) systems are presented, and used for model simplification purposes, to support efficient simulation of large scale continuous systems in an object-oriented modelling environment. The specific problems addressed are efficient elimination of trivial equations by means of substitution, system block lower triangular (BLT) partitioning, and tearing, i.e. hiding of algebraic variables. Moreover, the weakening heuristic criterion for decoupling of large systems, via dynamic approximation, is studied. All these techniques have been successfully implemented and tested in MOSES (modular object-oriented software environment for simulation), in order to define a complete model simplification process. The results achieved by applying the discussed algorithms and criteria on serial multibody systems are illustrated. A brief overview on further known symbolic manipulation techniques is also given, comparing them with the proposed ones, throughout the paper.     

A contribution to the real-time simulation of coupled finite element models of machine tools – A numerical comparison

In this paper the real-time simulation of finite element (FE) models of machine tools on a multi-processor architecture is presented. The simulation model is based on several FE component models that are connected by non-linear couplings. These couplings allow relative motions of the components in a wide range. The coupled linear FE models are decomposed at the non-linear coupling nodes and each component is solved locally. The linear structure of the components can be used for efficient simulation methods and the components can be distributed to several processors for a parallel computation. Methods that differ in numerical accuracy and stability, computational effort and real-time capacity will be presented. By means of a complex example, it will be illustrated that a parallel, stable computation can be realized time-deterministically.     

A regularization-based deep unsupervised model for affine multimodal co-registration

Extensive network receptive field is key for unsupervised affine registration because instead of deformable registration that takes care of local subtleties, the affine registration is global so that the last layers need to see big patches of the organ-in-interest. To extend the network's receptive field, we need to go for deeper networks, which causes producing complex models. On the other hand, affine transformation is restricted by its low degree-of-freedom (DoF) where larger models increasingly develop the hazard of overfitting. To worsen the situation, the regularizer module cannot be applied to the affine transformation with such a restricted DoF. In this paper, we propose a differentiable computational layer to convert the affine transformation outputted by the network to its corresponding dense displacement field. Such an affine-to-field layer enables us to apply different regularization terms on the outputted transformation in order to avoid the overfitting phenomenon while deepening the network. The proposed approach was evaluated on an annotated hard multimodal dataset containing 1109 pairs of CT/MR images of the brain with different heterogeneity for example, variety in scanners, setups and resolutions. Based on the results, the proposed customized layer is fully successful to handle the overfitting for deeper networks that are able to produce richer transformations than the shallower networks from different evaluation metrics for example, in target registration error the proposed network with seven layers has a 13.3% (or 9.1 mm) improvement in performance. The implementation of the proposed customized affine-to-field layer in the Python, Keras package with the Tensorflow backend can be publically accessed via https://github.com/boveiri/Deep-coReg .     

Increasing eigenstructure assignment design degree of freedom using lifting

This paper presents the exposition of an output-lifting eigenstructure assignment (EA) design framework, wherein the available EA design degrees of freedom (DoF) is significantly increased, and the desired eigenstructure of a single-rate full state feedback solution can be achieved within an output feedback system. A structural mapping is introduced to release the output-lifting causality constraint. Additionally, the available design DoF can be further enlarged via involving the input-lifting into the output-lifting EA framework. The newly induced design DoF can be utilised to calculate a structurally constrained, causal gain matrix which will maintain the same assignment capability. In this paper, the robustification of the output-lifting EA is also proposed, which allows a trade-off between performance and robustness in the presence of structured model uncertainties to be established. A lateral flight control benchmark in the EA literature and a numerical example are used to demonstrate the effectiveness of the design framework.     

Investigations on the dynamic coupling in AUV-manipulator system and the manipulator trajectory errors using bond graph method

This article presents the modelling and simulation of the dynamic coupling in an autonomous underwater vehicle (AUV)-manipulator system, used for subsea intervention tasks. Bond graph, a powerful tool in multi-domain dynamic system modelling, is used for the first time to model the coupled dynamics of the AUV-manipulator system. This method enables the development of the system model in a modular form by creating sub-system models and connecting these models together at energy interactions ports, thus overcoming many of the computational difficulties encountered in conventional modelling methods. The effects of gravity, buoyancy, added mass and fluid drag on the dynamics of a 3 degrees of freedom (DoF) manipulator mounted on a 6 DoF AUV are analysed. The manipulator trajectory errors due to the interaction forces and moments between the vehicle and the manipulator have also been investigated and the results are presented. The dynamic model predicts the reaction forces on the vehicle under various operating conditions of the manipulator and their influence on the manipulator trajectory. The percentage errors of manipulator tip trajectory for different initial configurations and operating conditions are analysed. The estimation of resulting errors in the manipulator path due to dynamic coupling effect on the manipulator trajectory helps in the design of suitable trajectory controller for the system. Cartesian space transpose Jacobian controller for trajectory control of manipulator has been implemented and results are presented.     

Asim: a performance model framework

The longevity and usefulness of a microprocessor performance model has historically depended on the model writer's skills and discipline. However, at Compaq the models became extremely complex and unmanageable because designers lacked a structured way to develop them. To cope with these complexities, Compaq researchers began developing Asim in late 1998 to allow model writers to faithfully represent the detailed timing of complex modern machines and effectively manage the large software projects needed to model such machines. Asim addresses these needs by providing a modular and reusable framework for creating many models. The framework's modularity helps break down the performance-modeling problem into individual pieces that can be modeled separately, while its reusability allows using a software component repeatedly in different contexts     

一种新的多分辨率模型表示方法

提出了一种简洁高效的多分辨率模型表示方法MRM,该方法能对网格简化或精化过程进行编码,并在此基础上实现了一个多分辨率造型与编辑系统。该系统能为给定的模型生成多分辨率表示,并支持对模型的分辨率进行编辑,统一地完成有选择地精化和简化操作。     

Simulation of distributed processing networks

A discrete event simulator named DDPSIM for distributed processing networks is presented. The simulator which was initially developed to support the design of a distributed processing system for an air defense application, has continued to evolve to accommodate a more general class of bus-connected networks in which software modules, or tasks, are distributed. It has also been used to model a complex air traffic control application which involved multiple networks. The modular organization and various distributed network component models of the simulator are described in detail. The simulator provides user friendly interfaces that include simple input conventions for system definition, and tabular and graphic outputs for comprehensive analyses of the simulation results. A relatively complex distributed processing system for air traffic control is used as an example to illustrate the simulation procedure and to show the simulation results. To conclude, the lessons learned from the experience in simulation are discussed.     

Analysis of early-design timber models for sound insulation

Timber construction is associated with a low carbon footprint and offers a high degree of sustainability. However, it poses challenges considering sound insulation. Acoustic analyses, which could require major expensive and time consuming changes in the building design, are typically performed once the design is already in the detailed stage. By using building information modelling (BIM), it is possible to shift the planning of the building physics, including acoustic analysis, to earlier phases. To make this possible, building models must include all the information necessary to perform acoustic analyses. One important part of acoustic analysis is identifying junctions between elements and map them to the junction types in standards. Until now, this investigation involves tedious manual processing for extracting multiple topological dependencies between different elements. Hence, this paper presents a framework for a seamless workflow between building models and acoustic analysis tools, based on an analysis of data models. The framework extracts and analyzes the element types, their geometry, and the connections of the individual elements in relation to each other. Through topological reasoning, along with a set of logical rules, the proposed framework identifies fifteen types of junctions, which can be distinguished acoustically for timber construction. The approach was evaluated in a prototypical implementation using a real-world model based on Industry Foundation Classes (IFC) as an example, in which the potential connection types were successfully extracted. This paper shows that junction analysis can be done with a geometric analysis to fill in missing semantic information about junctions of elements from the original data model.     

基于多边形顶点法矢量的网格模型简化算法

在计算机图形学中，经常采用网格模型进行几何物体的描述，而网格模型的大数据量成为实时绘制的瓶颈，因此，必须对网格模型进行简化。目前的简化算法，主要是以网格模型几何误差的最小化为准则，而忽略了模型的视觉特征，为此提出了一种基于法矢量的模型简化算法，其简化准则是视觉特征的最优化。首先获取多边形顶点的平均法矢量，然后依据该法矢量确定简化门限。实验结果表明，当地景模型简化至95.4%时，仍然保持了令人满意的图象质量。该算法能够在保证高度真实感视觉效果的前提下，实现模型较大幅度的简化。     

On the Systematic Analysis of Natural Language Requirements with CIRCE

This paper presents Circe, an environment for the analysis of natural language requirements. Circe is first presented in terms of its architecture, based on a transformational paradigm. Details are then given for the various transformation steps, including (i) a novel technique for parsing natural language requirements, and (ii) an expert system based on modular agents, embodying intensional knowledge about software systems in general. The result of all the transformations is a set of models for the requirements document, for the system described by the requirements, and for the requirements writing process. These models can be inspected, measured, and validated against a given set of criteria. Some of the features of the environment are shown by means of an example. Various stages of requirements analysis are covered, from initial sketches to pseudo-code and UML models.     

Synchronous structures

Synchronous languages have been designed to ease the development of reactive systems, by providing a methodological framework for assisting system designers from the early stages of requirement specifications to the final stages of code generation or circuit production. Synchronous languages enable a very high-level specification and an extremely modular design of complex reactive systems by structural decomposition of them into elementary processes. We define an order-theoretical model that gives a unified mathematical formalisation of all the above aspects of the synchronous methodology and characterises the essentials of the synchronous paradigm.     

Guided curation of semistructured data in collaboratively-built knowledge bases

The collaborative curation of semistructured knowledge has become a popular paradigm on the web and also within enterprises. In such knowledge bases a common structure of the stored information is crucial for providing efficient and precise search facilities. However, the task of refining, extending and homogenizing knowledge and its structure is very complex. In this article we present two paradigms for the simplification of this task by providing guidance mechanisms to the user. Both paradigms aim at combining the power of automated extraction algorithms with the semantic awareness of human users to accomplish this refinement task.     

Multi-layered interactive energy space modeling for near-optimal electrification of terrestrial,shipboard and aircraft systems

In this paper, we introduce a basic multi-layered modeling framework for posing the problem of safe, robust and efficient design and control that may lend itself to ripping potential benefits from electrification. The proposed framework establishes dynamic relations between physical concepts such as stored energy, useful work, and wasted energy, on one hand; and modeling, simulation, and control of interactive modular complex dynamical systems, on the other. In particular, our recently introduced energy state-space modeling approach for electric energy systems is further interpreted using fundamental laws of physics in multi-physical systems, such as terrestrial energy-systems, aircrafts and ships. The interconnected systems are modeled as dynamically interacting modules. This approach is shown to be particularly well-suited for scalable optimization of large-scale complex systems. Instead of having to use simpler models, the proposed multi-layered modeling of system dynamics in energy space offers a promising basic method for modeling and controlling inter-dependencies across multi-physics subsystems for both ensuring feasible and near-optimal operation. It is illustrated how this approach can be used for understanding fundamental physical causes of inefficiencies created either at the component level or are a result of poor matching of their interactions.     

A data/knowledge paradigm for the modeling and design of operationssupport systems

The paper develops the Smart Object paradigm and its instantiation, which provide a new conceptualization for the modeling, design, and development of an important but little researched class of information systems, operations support systems (OSS). OSS is the authors' term for systems which provide interactive support for the management of large, complex operations environments, such as manufacturing plants, military operations, and large power generation facilities. The most salient feature of an OSS is its dynamic nature. The number and kind of elements composing the system as well as the mode of control of those elements change frequently in response to the environment. The abstraction of control and the ease with which complex dynamic control behavior can be modeled and simulated is one of the important aspects of the paradigm. The framework for the Smart Object paradigm is the fusion of object-oriented design models with declarative knowledge representation and active inferencing from AI models. Additional defining concepts from data/knowledge models, semantic data models, active databases, and frame based systems, are added to the synthesis as justified by their contribution to the ability to naturally model OSS at a high level of abstraction. The model assists in declaratively representing domain data/knowledge and its structure, and task or process knowledge, in addition to modeling multilevel control and interobject coordination