一种基于虚拟执行规则的工作流实例迁移方法

在基于形式化的工作流模型和具有历史执行记录的工作流实例定义基础上,给出了一个全面的、正确的工作流实例迁移判断标准,并且依据此判断标准提出了虚拟执行规则和迁移算法。与同类研究工作比较,该方法在适用性、正确性和可实现性等方面具有一定的先进性。     

一种新的B2B电子商务过程建模方法

针对当前B2B电子商务标准和跨组织的工作流过程建模语言存在的过程描述能力比较差的问题,提出了一种新的B2B电子商务过程建模方法。该方法基于ebXML的业务过程规范模型(BPSS)并将它扩充和一般化,从而有效地实现了B2B电子商务过程模型的建立。     

A declarative approach to procedural modeling of virtual worlds

With the ever increasing costs of manual content creation for virtual worlds, the potential of creating it automatically becomes too attractive to ignore. However, for most designers, traditional procedural content generation methods are complex and unintuitive to use, hard to control, and generated results are not easily integrated into a complete and consistent virtual world.We introduce a novel declarative modeling approach that enables designers to concentrate on stating what they want to create instead of on describing how they should model it. It aims at reducing the complexity of virtual world modeling by combining the strengths of semantics-based modeling with manual and procedural approaches. This article describes two of its main contributions to procedural modeling of virtual worlds: interactive procedural sketching and virtual world consistency maintenance. We discuss how these techniques, integrated in our modeling framework SketchaWorld, build up to enable designers to create a complete 3D virtual world in minutes. Procedural sketching provides a fast and more intuitive way to model virtual worlds, by letting designers interactively sketch their virtual world using high-level terrain features, which are then procedurally expanded using a variety of integrated procedural methods. Consistency maintenance guarantees that the semantics of all terrain features is preserved throughout the modeling process. In particular, it automatically solves conflicts possibly emerging from interactions between terrain features.We believe that these contributions together represent a significant step towards providing more user control and flexibility in procedural modeling of virtual worlds. It can therefore be expected that by further reducing its complexity, virtual world modeling will become accessible to an increasingly broad group of users.     

Competition and evolution in virtual plant communities: a new modeling approach

This article presents studies on plants and their communities through experiments with a multi-agent platform of generic virtual plants. Based on Artificial Life concepts, the model has been designed for long-term simulations spanning a large number of generations while emphasizing the most important morphological and physiological aspects of a single plant. The virtual plants combine a physiological transport-resistance model with a morphological model using the L-system formalism and grow in a simplified 3D artificial ecosystem. Experiments at three different scales are carried out and compared to observations on real plant species. At the individual level, single virtual plants are grown in order to examine their responses to environmental constraints. A number of emerging characteristics concerning individual plant growth can be observed. Unifying field observation, mathematical theory and computer simulation, population level experiments on intraspecific and interspecific competition for resources are related to corresponding aggregate models of population dynamics. The latter provide a more general understanding of the experiments with respect to long-term trends and equilibrium conditions. Studies at the evolutionary level aim at morphogenesis and the influence of competition on plant morphology. Among other results, it is shown how the struggle for resources induces an arms race that leads to the evolution of elongated growth in contrast to rather ample forms at ground-level when the plants evolve in isolation.     

Real-time finite element modeling for surgery simulation: an application to virtual suturing

Real-time finite element (FE) analysis can be used to represent complex deformable geometries in virtual environments. The need for accurate surgical simulation has spurred the development of many of the new real-time FE methodologies that enable haptic support and real-time deformation. These techniques are computationally intensive and it has proved to be a challenge to achieve the high modeling resolutions required to accurately represent complex anatomies. The authors present a new real-time methodology based on linear FE analysis that is appropriate for a wide range of surgical simulation applications. A methodology is proposed that is characterized by high model resolution, low preprocessing time, unrestricted multipoint surface contact, and adjustable boundary conditions. These features make the method ideal for modeling suturing, which is an element common to almost every surgical procedure. This paper describes constraints in the context of a Suturing Simulator currently being developed by the authors.     

Measuring virtual experience in a three-dimensional virtual reality interactive simulator environment: a structural equation modeling approach

With the rapid development of the VR market, virtual experience has increasingly been the object of study in recent years. A growing number of studies have reported the positive effect that virtual experience can have on a user’s mood and loyalty. However, few studies have investigated the influence of the mechanism of virtual experience on users’ mood and loyalty. To compensate for this research gap, this study aims to evaluate consumers’ virtual experience by examining the flow state in a virtual environment. A total of 368 valid questionnaires were collected, and a structural equation modeling approach was employed in the data analysis. The study reveals that forming flow involves many factors: the intrinsic characteristics of the mediated environment, the consumer’s assumptions and perceptions prior to entering the flow state, the stage at which the customer enters the flow state, and the consequences of the flow experience.     

Automating ETL processes using the domain-specific modeling approach

The development of Extract–Transform–Load (ETL) processes is the most complex, time-consuming and expensive phase of data warehouse development. Yet, the dynamics of modern business systems demand a more agile and flexible approach to their development. As a result, current research in this area is focused on ETL process conceptualization and the automation of ETL process development. This paper proposes a novel solution for automating ETL processes using the domain-specific modeling (DSM) approach. The proposed solution is based on the formal specification of ETL processes and the implementation of such formal specifications. Thus, in accordance with the DSM approach, several new domain-specific languages (DSLs) are introduced, each defining concepts relevant for a specific aspect of an ETL process. The focus of this paper is the actual implementation of the formal specification of an ETL process. To this end, a specific ETL platform (ETL-PL) is introduced to technologically support both the modeling of ETL processes (i.e., the creation of models in accordance with the introduced DSLs) and the automated transformation of the created models into the executable code of a specific application framework (representing ETL-PL’s execution environment). It should be emphasized that ETL-PL actually presumes the dynamic execution of ETL models or, more precisely, the executable code is generated at runtime. Thus the execution environment consists of code generator components and the components implementing the application framework. ETL-PL has been implemented as an extension of the .NET platform.     

A multi-channel spatio-temporal Hammerstein modeling approach for nonlinear distributed parameter processes

Modeling of distributed parameter processes is a challenging problem because of their complex spatio-temporal nature, nonlinearities and uncertainties. In this study, a spatio-temporal Hammerstein modeling approach is proposed for nonlinear distributed parameter processes. Firstly, the static nonlinear and the distributed dynamical linear parts of the Hammerstein model are expanded onto a set of spatial and temporal basis functions. In order to reduce the parametric complexity, the Karhunen–Loève decomposition is used to find the dominant spatial bases with Laguerre polynomials selected as the temporal bases. Then, using the Galerkin method, the spatio-temporal modeling will be reduced to a traditional temporal modeling problem. Finally, the unknown parameters can be easily estimated using the least squares estimation and the singular value decomposition. In the presence of unmodeled dynamics, a multi-channel modeling framework is proposed to further improve the modeling performance. The convergence of the modeling can be guaranteed under certain conditions. The simulations are presented to show the effectiveness of this modeling method and its potential to a wide range of distributed processes.     

Interactive modeling and simulation of virtual manufacturing assemblies: An agent-based approach*

In this paper, an agent-based design and development of an interactive virtual environment for a manufacturing assembly process is described. Agents in the assembly are identified through their respective responsibilities and are implemented so that they coordinate between one another to accomplish the PC assembly/disassembly process. The robot agent, crucial to the assembly operation, is designed to handle multiple failure situations, wherein it coordinates with the part agent to accommodate the failure.     

A non-intrusive stochastic Galerkin approach for modeling uncertainty propagation in deformation processes

Large deformation processes are inherently complex considering the non-linear phenomena that need to be accounted for. Stochastic analysis of these processes is a formidable task due to the numerous sources of uncertainty and the various random input parameters. As a result, uncertainty propagation using intrusive techniques requires tortuous analysis and overhaul of the internal structure of existing deterministic analysis codes. In this paper, we present an approach called non-intrusive stochastic Galerkin (NISG) method, which can be directly applied to presently available deterministic legacy software for modeling deformation processes with minimal effort for computing the complete probability distribution of the underlying stochastic processes. The method involves finite element discretization of the random support space and piecewise continuous interpolation of the probability distribution function over the support space with deterministic function evaluations at the element integration points. For the hyperelastic–viscoplastic large deformation problems considered here with varying levels of randomness in the input and boundary conditions, the NISG method provides highly accurate estimates of the statistical quantities of interest within a fraction of the time required using existing Monte Carlo methods.     

A spatio-temporal Volterra modeling approach for a class of distributed industrial processes

It is difficult to model a distributed parameter system (DPS) due to the infinite-dimensional time/space nature and unknown nonlinear uncertainties. A low-dimensional and simple nonlinear model is often required for practical applications. In this paper, a spatio-temporal Volterra model is proposed with a series of spatio-temporal kernels for modeling unknown nonlinear DPS. To estimate these kernels, they are expanded onto spatial and temporal bases with unknown coefficients. To reduce the model dimension and parametric complexity in the spatial domain, the Karhunen–Loève (KL) method is used to find the dominant spatial bases. To reduce the parametric complexity in the temporal domain, the Laguerre polynomials are selected as temporal bases. Next, using the Galerkin method, this spatio-temporal modeling becomes a linear regression problem. Then unknown parameters can be easily estimated using the least-squares method in the temporal domain. After the time/space synthesis, the spatio-temporal Volterra model can be constructed. The convergence of parameter estimation can be guaranteed under certain conditions. This model has a low-dimensional and simple nonlinear structure, which is useful for the prediction and control of the DPS. The simulation and experiment demonstrate the effectiveness of the proposed modeling method.     

JiST: an efficient approach to simulation using virtual machines

Discrete event simulators are important scientific tools and their efficient design and execution is the subject of much research. In this paper, we propose a new approach for constructing simulators that leverages virtual machines and combines advantages from the traditional systems‐based and language‐based simulator designs. We introduce JiST, a Java‐based simulation system that executes discrete event simulations both efficiently and transparently by embedding simulation semantics directly into the Java execution model. The system provides standard benefits that the modern Java runtime affords. In addition, JiST is efficient, out‐performing existing highly optimized simulation runtimes. As a case study, we illustrate the practicality of the JiST framework by applying it to the construction of SWANS, a scalable wireless ad hoc network simulator. We simulate million node wireless networks, which represents two orders of magnitude increase in scale over what existing simulators can achieve on equivalent hardware and at the same level of detail. Copyright © 2005 John Wiley & Sons, Ltd.     

Multimodal processes optimization subject to fuzzy operation time constraints: declarative modeling approach

We present an extension of the resource-constrained multi-product scheduling problem for an automated guided vehicle (AGV) served flow shop, where multiple material handling transport modes provide movement of work pieces between machining centers in the multimodal transportation network (MTN). The multimodal processes behind the multi-product production flow executed in an MTN can be seen as processes realized by using various local periodically functioning processes. The considered network of repetitively acting local transportation modes encompassing MTN’s structure provides a framework for multimodal processes scheduling treated in terms of optimization of the AGVs fleet scheduling problem subject to fuzzy operation time constraints. In the considered case, both production takt and operation execution time are described by imprecise data. The aim of the paper is to present a constraint propagation (CP) driven approach to multi-robot task allocation providing a prompt service to a set of routine queries stated in both direct and reverse way. Illustrative examples taking into account an uncertain specification of robots and workers operation time are provided.     

Designing presence for real locomotion in immersive virtual environments: an affordance-based experiential approach

This paper describes a framework for designing systems for real locomotion in virtual environments (VEs) in order to achieve an intense sense of presence. The main outcome of the present research is a list of design features that the virtual reality technology should have in order to achieve such a goal. To identify these features, an approach based on the combination of two design strategies was followed. The first was based on the theory of affordances and was utilized to design a generic VE in which the affordances of the corresponding real environment could be evoked. The second was the experiential design applied to VEs and was utilized to create an experience of locomotion corresponding to that achievable in a real environment. These design strategies were chosen because of their potential to enhance the sense of presence. The proposed list of features can be utilized as an instrument that allows VE designers to evaluate the maturity of their systems and to pinpoint directions for future developments. A survey analysis was performed using the proposed framework, which involved three case studies to determine how many features of the proposed framework were present and their status. The result of such analysis represented a measure of the completeness of the systems design, of the affordances provided to the user, and a prediction of the sense of presence.     

一种基于工况分解的热工过程非线性控制模型建立方法及应用

充分考虑大多数复杂热工控制对象非线性特性与运行工况密切相关的实际特点,采用基于工况分解的多模型建模思路,提出一种面向控制的非线性过程建模方法.将该方法应用于某电厂300MW机组锅炉过热汽温对象,实际考核结果表明采用该方法建立的模型,即使在运行工况大范围变化时也具有满意的动态预测效果,验证了提出的方法的有效性.     

水下机器人任务流程建模与管理

为实现水下机器人任务流程的快速建模与自动管理,通过改进传统的工作流理论,提出了一种实用的任务流程模型——任务工作流.介绍了作为任务工作流理论基础的传统Petri网及工作流模型,指出了原有理论的缺陷并介绍了任务工作流的基本理论.以任务工作流模型为基础,实现了一款任务流程管理系统,为其定义了完善的图形化建模手段与标准的文本化的描述语言,并建立了一套担负着运行时任务管理工作的核心应用程序,能够实现任务的描述与建模、自动运行与管理,以及任务流程的动态更改.实践表明,任务工作流建模简单快捷、方便编程实现,是机器人任务建模与管理的理想工具.     

工作流赋权性能有色Petri网建模方法

针对经典Petri网存在工作流无严格限制和定义,不同方式下变迁的托肯(Token)(包括了种类、数量、流向)绑定、后续库所到达以及对多性能描述与分析无法有效处理的问题,通过明确定义Petri网工作流结构、颜色集和加入多性能的衡量分析,提出工作流赋权性能有色Petri网。介绍了该方法的基本概念、权值向量和基本结构,并以危化品物流流程为实例,从时间和安全两个维度给出了危化品物流流程建模及性能测算方法;然后对危化品物流流程进行了建模、性能测算和分析,经测算其总体性能为3.8094;最后利用筛选模型中各路径的时间性能和危险度的差路,找出制约危化品物流流程的瓶颈,从而证明该方法是工作流多性能分析的有效方法。     

一种虚拟现实建模的新方法

介绍了OpenGL和Matlab2009a各自的特点,在结合各自特点基础上,建立了基于二者的虚拟现实三维建模开发平台;以建立的虚拟现实建模开发平台为例,对比已有的使用Matlab外部接口的方法,证明了基于OpenGL和Matlab开发方法的优越性和有效性.     

BN-LSTM-based energy consumption modeling approach for an industrial robot manipulator

Industrial robots (IRs) are widely used to increase productivity and efficiency in manufacturing industries. Therefore, it is critical to reduce the energy consumption of IRs to maximize their use in polishing, assembly, welding, and handling tasks. This study adopted a data-driven modeling approach using a batch-normalized long short-term memory (BN-LSTM) network to construct a robust energy-consumption prediction model for IRs. The adopted method applies batch normalization (BN) to the input-to-hidden transition to allow faster convergence of the model. We compared the prediction accuracy with that of the 1D-ResNet14 model in a UR (UR3e and UR10e) public database. The adopted model achieved a root mean square (RMS) error of 2.82 W compared with the error of 6.52 W achieved by 1D-ResNet14 model prediction, indicating a performance improvement of 56.74%. We also compared the prediction accuracy over the UR3e dataset using machine learning and deep learning models, such as regression trees, linear regression, ensemble trees, support vector regression, multilayer perceptron, and convolutional neural network-gated recurrent unit. Furthermore, the layers of the well-trained UR3e power model were transferred to the UR10e cobot to construct a rapid power model with 80% reduced UR10e datasets. This transfer learning approach showed an RMS error of 3.67 W, outperforming the 1D-ResNet14 model (RMS error: 4.78 W). Finally, the BN-LSTM model was validated using unseen test datasets from the Yaskawa polishing motion task, with an average prediction accuracy of 99%.     

A continuous dynamic modeling approach for an omnidirectional mobile robot

MY wheel-II is one of switch omnidirectional wheel mechanisms. The omnidirectional mobile robot based on MY wheels-II is a switched non-linear system (i.e. discontinuous system). The aim of this paper is to propose a continuous modeling approach which can be employed to derive a continuous model from any given discontinuous robot dynamic model. This approach results in a continuous non-linear parameter varying (NLPV) model, and offers one solution for model-based control design. Firstly, our previously proposed average dynamic modeling approach is analyzed. We find that this modeling approach is effective only for a specific class of robot configurations. To overcome this problem, we first derive the switching conditions of MY wheel-II. Based on derived switching conditions, we then propose a simple continuous NLPV modeling approach. The new approach replaces the real discontinuous contact radius in the discontinuous dynamic model with an adaptive continuous curve. An illustrative example of the adaptive continuous curve design is provided. Both simulation and experimental results verify the effectiveness of the proposed NLPV modeling approach against the average modeling approach.