面向业务协作的本体协同编辑系统

为提高本体编辑工具的群体协作支持功能,发挥本体编辑必需的群体智慧作用,针对当前本体编辑工具不能较好满足协同性需求的实际情况,将网格的技术理念应用到本体编辑系统的构建之中,提出基于资源动态集成与协同交互技术的网格化虚拟协同本体编辑系统,并介绍了系统的体系结构与关键技术.     

A randomised algorithm for computing static-output-feedbacks for large-scale systems

ABSTRACT

A randomised algorithm is proposed for computing globally optimal static-output-feedbacks for large-scale systems. The algorithm is based on the Ray-Shooting Method and involves some heuristics to accelerate the search. We also improve the basic Ray-Shooting Algorithm and make the search in the controller parameter-space (which generally, is much more smaller than the certificate parameter-space), thus enabling its efficient use for large-scale systems.     

基于对象复制的协同绘图并发控制算法

全复制模式下的基于对象的实时协同图形编辑系统支持不同地域的设计人员通过网络同步高效地浏览、操作和修改共享文档和文档中的各种对象，包括图形、图象和文本等，其中操作意愿保证及其并发控制成为复杂而又关键的问题之一，其研究具有挑战性．文中讨论了基于图形对象的并发操作的冲突，提出直接依赖和对象状态概念确定操作的候选对象和相容集合，并改进了对象复制算法．基于此，给出了一个有效的并发控制算法。     

A bidirectional-transformation-based framework for software visualization and visual editing

Software visualization and visual editing are important and practical techniques to improve the development of complex software systems. A challenge when applying the two technologies is how to realize the correspondence, a bidirectional relationship, between the data and its visual representation correctly. Although many tools and frameworks have been developed to support the construction of visual tools, it is still compli- cated and error-prone to realize the bidirectional relationship. In this paper, we propose a model-driven and bidirectional-transformation-based framework for data visualization and visual editing. Our approach mainly focuses on 1） how to define and manage graphical symbols in the model form and 2） how to specify and im- plement the bidirectional relationship based on the technique of bidirectional model transformation. Then, a prototype tool and four case studies are presented to evaluate the feasibility of our work.     

基于多核的并行操作转换算法

操作转换算法是实时协同编辑系统首选的并发控制算法,它不仅能提供不受限的交互,而且维护分布式操作的意图一致性。然而随着操作数目的增多,操作的响应时间也会延长。结合多核多线程技术的发展,提出了第一个并行的操作转换算法,其能减少远程操作集成到本地站点的时间开销。对传统的串行算法进行了改造,使得具有计算依赖的过程能够并行化。实验结果表明,提出的算法相较于传统算法具有较大的优势,在处理较大操作历史的情况下依然能够保证操作合理的响应时间。     

混合式协作共享对象模型及其实现技术

为满足协作应用系统对用户操作的响应性和协作应用参与者的动态性要求,提出混合式的协作共享对象模型,集中的对象注册器协助动态管理共享对象组状态信息,复制式的共享对象副本将按快速串行化的事务处理方式执行．着重介绍了共享对象新的乐观并发控制和一致性维护技术,特别是将操作位置转换方法结合到复合对象的两阶段提交算法中,提高了用户操作的响应性;对象组采用动态管理,满足了协作参与者的动态性要求．     

A recursive algorithm for identification and control of large-scale systems

The paper presents new recursive algorithms for identification and control of linear time invariant discrete time systems of large size. A variant of the observable canonical form (Weinert and Anton 1972) of the state model is chosen for developing solution of the identification problem. The proposed solution turns out to be computationally much simpler than the existing solutions. It is also shown that centralized and decentralized output feedback controllers can be found by a simple extension of the identification algorithms. The results are illustrated for a system obtained by interconnecting three smaller subsystems.     

A model driven architecture for the development of smart card software

Smart cards are portable integrated devices that store and process data. Speed, security and portability properties enable smart cards to have a widespread usage in various fields including telecommunication, transportation and the credit card industry. However, the development of smart card applications is a difficult task due to hardware and software constraints. The necessity of the knowledge of both a very low-level communication protocol and a specific hardware causes smart card software development to be a big challenge for the developers. Written codes tend to be error-prone and hard to debug because of the limited memory resources. Hence, in this study, we introduce a model driven architecture which aims to facilitate smart card software development by both providing an easy design of smart card systems and automatic generation of the required smart card software from the system models. Differentiating from the previous work, the study in here contributes to the field by both providing various smart card metamodels in different abstraction layers and defines model-to-model transformations between the instances of these metamodels in order to support the realization of the same system on different smart card platforms. Applicability of the proposed methodology is shown for rapid and efficient application development in two major smart card frameworks: Java Card and ZeitControl Basic Card. Lessons learned during the industrial usage of the architecture are also reported in the paper. Finally, we discuss how the components of the architecture can be integrated in order to provide a domain-specific language for smart card software.     

A text editing interface: Definition and use

A simple yet flexible method of editing text is described which is applicable to all forms of character based command processing applications. The technique greatly increases the friendliness of a text driven interface but does not interfere with most existing command conventions; it can also be generalised to form the basis of a powerful and easy to use text editor. This paper describes the details and basic philosophy of the editing interface and describes its successful use in two applications (command processor and calculator) which are not normally associated with text editing requirements.     

A novel initial ranging algorithm for OFDMA systems using smart antenna

To improve the capacity of initial ranging （IR） users simultaneously accessing into network and enhance the performance of the IR, a novel IR algorithm is presented for the orthogonal frequency division multiple access systems with the smart antenna. The beamforming weight vectors provided by the antenna array are introduced for the IR users, and the procedures of the multiuser parameter estimation and the interference cancellation are designed. The proposed method can improve the accuracy of the channel estimation of active paths and efficiently reduce the residual multiple access interference. Simulation results show that the proposed method has a much better performance than the available successive multiuser detection and interference cancellation algorithm and accommodates more active ranging users simultaneously accessing into a cell.     

The role of communication systems in smart grids: Architectures,technical solutions and research challenges

The purpose of this survey is to present a critical overview of smart grid concepts, with a special focus on the role that communication, networking and middleware technologies will have in the transformation of existing electric power systems into smart grids. First of all we elaborate on the key technological, economical and societal drivers for the development of smart grids. By adopting a data-centric perspective we present a conceptual model of communication systems for smart grids, and we identify functional components, technologies, network topologies and communication services that are needed to support smart grid communications. Then, we introduce the fundamental research challenges in this field including communication reliability and timeliness, QoS support, data management services, and autonomic behaviors. Finally, we discuss the main solutions proposed in the literature for each of them, and we identify possible future research directions.     

A segmentation-based algorithm for large-scale partially ordered monotonic regression

Monotonic regression (MR) is an efficient tool for estimating functions that are monotonic with respect to input variables. A fast and highly accurate approximate algorithm called the GPAV was recently developed for efficient solving large-scale multivariate MR problems. When such problems are too large, the GPAV becomes too demanding in terms of computational time and memory. An approach, that extends the application area of the GPAV to encompass much larger MR problems, is presented. It is based on segmentation of a large-scale MR problem into a set of moderate-scale MR problems, each solved by the GPAV. The major contribution is the development of a computationally efficient strategy that produces a monotonic response using the local solutions. A theoretically motivated trend-following technique is introduced to ensure higher accuracy of the solution. The presented results of extensive simulations on very large data sets demonstrate the high efficiency of the new algorithm.     

Parallel history matching and associated forecast at the center for interactive smart oilfield technologies

We have developed a parallel and distributed computing framework to solve an inverse problem, which involves massive data sets and is of great importance to petroleum industry. A Monte Carlo method, combined with proxies to avoid excessive data processing, is employed to identify reservoir simulation models that best match the oilfield production history. Subsequently, the selected models are used to forecast future productions with uncertainty estimates. The parallelization framework combines: (1) message passing for tightly coupled intra-simulation decomposition; and (2) scheduler/Grid remote procedure calls for model parameter sweeps. A preliminary numerical test has included 3,159 simulations on a 256-processor Intel Xeon cluster at the USC-CACS. The results provide uncertainty estimates of unprecedented precision.     

A solution of multidisciplinary collaborative simulation for complex engineering systems in a distributed heterogeneous environment

This paper presents an integrated approach to multidisciplinary collaborative simulation for complex engineering systems. The formulized paradigm of multidisciplinary collaborative simulation for com- plex engineering systems is principally analyzed. An IEEE HLA and web services based framework is proposed to provide a heterogeneous, distributed and collaborative running environment where multidisciplinary modeling, running management and post-processing of collaborative simulation are undertaken. The mecha...     

A framework for the design and integration of collaborative classroom games

The progress registered in the use of video games as educational tools has not yet been successfully transferred to the classroom. In an attempt to close this gap, a framework was developed that assists in the design and classroom integration of educational games. The framework addresses both the educational dimension and the ludic dimension. The educational dimension employs Bloom’s revised taxonomy to define learning objectives and applies the classroom multiplayer presential game (CMPG) pedagogical model while the ludic dimension determines the gaming elements subject to constraints imposed by the educational dimension. With a view to validating the framework, a game for teaching electrostatics was designed and experimentally implemented in a classroom context. An evaluation based on pre/post testing found that the game increased the average number of correct answers by students participating in the experiment from 6.11 to 10.00, a result found to be statistically significant. Thus validated, the framework offers a promising basis for further exploration through the development of other games and fine-tuning of its components.     

A middleware framework for application-aware and user-specific energy optimization in smart mobile devices

Mobile battery-operated devices are becoming an essential instrument for business, communication, and social interaction. In addition to the demand for an acceptable level of performance and a comprehensive set of features, users often desire extended battery lifetime. In fact, limited battery lifetime is one of the biggest obstacles facing the current utility and future growth of increasingly sophisticated “smart” mobile devices. This paper proposes a novel application-aware and user-interaction aware energy optimization middleware framework (AURA) for pervasive mobile devices. AURA optimizes CPU and screen backlight energy consumption while maintaining a minimum acceptable level of performance. The proposed framework employs a novel Bayesian application classifier and management strategies based on Markov Decision Processes and Q-Learning to achieve energy savings. Real-world user evaluation studies on Google Android based HTC Dream and Google Nexus One smartphones running the AURA framework demonstrate promising results, with up to 29% energy savings compared to the baseline device manager, and up to 5×savings over prior work on CPU and backlight energy co-optimization.     

CLPL: Providing software infrastructure for the systematic and effective construction of complex collaborative learning systems

Over the last decade, e-Learning and in particular Computer-Supported Collaborative Learning (CSCL) needs have been evolving accordingly with more and more demanding pedagogical and technological requirements. As a result, high customization and flexibility are a must in this context, meaning that collaborative learning practices need to be continuously adapted, adjusted, and personalized to each specific target learning group. These very demanding needs of the CSCL domain represent a great challenge for the research community on software development to satisfy.This contribution presents and evaluates a previous research effort in the form of a generic software infrastructure called Collaborative Learning Purpose Library (CLPL) with the aim of meeting the current and demanding needs found in the CSCL domain. To this end, we experiment with the CLPL in order to offer an advanced reuse-based service-oriented software engineering methodology for developing CSCL applications in an effective and timely fashion. A validation process is provided by reporting on the use of the CLPL platform as the primary resource for the Master's thesis courses at the Open University of Catalonia when developing complex software applications in the CSCL domain.The ultimate aim of the whole research is to yield effective CSCL software systems capable of supporting and enhancing the current on-line collaborative learning practices.     

Adaptive fuzzy decentralised fault-tolerant control for nonlinear large-scale systems with actuator failures and unmodelled dynamics

This paper discusses the adaptive fuzzy decentralised fault-tolerant control (FTC) problem for a class of nonlinear large-scale systems in strict-feedback form. The systems under study contain the unknown nonlinearities, unmodelled dynamics, actuator faults and without the direct measurements of state variables. With the help of fuzzy logic systems identifying the unknown functions and a fuzzy adaptive observer is designed to estimate the unmeasured states. By using the backstepping design technique and the dynamic surface control approach and combining with the changing supply function technique, a fuzzy adaptive FTC scheme is developed. The main features of the proposed control approach are that it can guarantee the closed-loop system to be input–to-state practically stable, and also has the robustness to the unmodelled dynamics. Moreover, it can overcome the so-called problem of ‘explosion of complexity’ existing in the previous literature. Finally, simulation studies are provided to illustrate the effectiveness of the proposed approach.     

A high performance framework for modeling and simulation of large-scale complex systems

Due to the quick advances in the scale of problem domain of complex systems under investigation, the complexity of multi-input component models used to construct logical processes (LP) has significantly increased. High-performance computing technologies have therefore been extensively used to enable parallel simulation execution. However, the traditional multi-process parallel method (MPM) executes LPs in parallel on multi-core platforms, which ignores the intrinsic parallel capabilities of multi-input component models. In this study, a vectorized component model (VCM) framework has been proposed. The design aims to better utilize the parallelism of multi-input component models. A two-level composite parallel method (CPM) has then been constructed within the framework, which can sustain complex system simulation applications consisting of multi-input component models. CPM first employs MPM to dispatch LPs onto a multi-core computing platform. It then maps VCMs to the multiple-core platform for parallel execution. Experimental results indicate that (1) the proposed VCM framework can better utilize the parallelism of multi-input component models, and (2) CPM can significantly improve the performance comparing to the traditional MPM. The results also show that CPM can effectively cope with the size and complexity of complex simulation applications with multi-input component models.