4917474
Effective Visualisation of Workflow Enactment
Although most existing teamwork management systems support user-friendly interface to some extent, few of them have take into consideration of the special requirements of workflow visualisation. This paper realises the unique features of visualisation for run-time workflow, i.e., workflow enactment and execution. We present a detailed discussion of the emerging problems against the general aesthetic criteria for drawing the workflow layout. In order to support most essential workflow enactment facilities, the following three mechanisms are provided. Firstly, Sugiyama algorithm has been systematically incorporated into our prototype to create well structured workflow layout initially. Secondly, when the workflow process dynamically changes, we can adjust workflow layout by our force-scan algorithm to retain the mental maps created earlier among team members. Thirdly, we have also applied the technique of the fisheye view to offer a context focus mechanism for workflow users and to utilise the screen size more effectively. With these visualisation techniques, a better atmosphere may be facilitated for teamwork.
14447070
Achieving convergence, causality preservation, and intention preservation in real-time cooperative editing systems
Real-time cooperative editing systems allow multiple users to view and edit the same text/graphic/image/multimedia document at the same time for multiple sites connected by communication networks. Consistency maintenance is one of the most significant challenges in designing and implementing real-time cooperative editing systems. In this article, a consistency model, with properties of convergence, causality preservation, and intention preservation, is proposed as a framework for consistency maintenance in real-time cooperative editing systems. Moreover, an integrated set of schemes and algorithms, which support the proposed consistency model, are devised and discussed in detail. In particular, we have contributed (1) a novel generic operation transformation control algorithm for achieving intention preservation in combination with schemes for achieving convergence and causality preservation and (2) a pair of reversible inclusion and exclusion transformation algorithms for stringwise operations for text editing. An Internet-based prototype system has been built to test the feasibility of the proposed schemes and algorithms
16079123
Agent-Based Ontology Mapping Towards Ontology Interoperability
Globalisation of business environments on the Web has given rise to the advent of similar ontologies in which dynamic ontology mapping is called in. Ontology mapping is necessary for ontology interoperability. In this paper, a novel agent-based ontology mapping is presented for agents to operate ontology mapping flexibly in a dynamic environment regardless heterogeneous platforms and different ontology representations. The mapping mechanism is discussed by having a close look at both inherent inter-processes of mapping tasks of an agent and relevant interaction processes. The interrelated processes of agents also enable agent-based ontology mapping to take ontology changes into account whenever needed. A mapping prototype is built for verification.
4914546
Multiple temporal consistency states for dynamical verification of upper bound constraints in grid workflow systems
Conventional upper bound constraint verification in grid workflow systems is based on the key assumption that an upper bound constraint only has two states: consistency and inconsistency. However, due to complexity of grid workflows and dynamic availability of participating grid services, this assumption is too restrictive as there may be some intermediate states. Therefore, in this paper, we introduce four states for an upper bound constraint. Namely, we treat conventional consistency as strong consistency and divide conventional inconsistency into weak consistency, weak inconsistency and strong inconsistency. Correspondingly, we develop their verification methods. For weak consistency, we present some algorithms on how to adjust it to strong consistency without triggering exception handling as in conventional work. For weak inconsistency, we analyse why it can rely on less costly exception handling than conventional work. The final evaluation demonstrates that our four-state approach can achieve better cost-effectiveness than the conventional two-state approach
4924842
Assigning Local Fixed-time Constraints in Grid Workflow Systems
Many complex grid workflow processes often have only one global fixed-time constraint at the last activity. Since grid workflow execution normally lasts a long time, local control is very important to ensure the overall temporal correctness. With only one global fixed-time constraint, we cannot control grid workflow execution locally in terms of time. As a result, for any temporal violations, we must handle them globally with the consideration of all activities. This would impact the overall cost-effectiveness of grid workflow execution. Therefore, in this paper, we investigate how to assign local fixed-time constraints within the global one so that we can control grid workflow execution locally. Corresponding assigning and verification methods are developed. With local fixed-time constraints, we can achieve better cost-effectiveness
14000419
Using an experimental study to develop group awareness support for real-time distributed collaborative writing
Supporting group awareness is vital for the success of real-time, distributed, collaborative writing systems. Many awareness mechanisms have been introduced, but highly effective solutions are few. The research presented in this paper focuses on the development of awareness mechanisms using an experimental study of synchronous distributed collaborative writing. Our study has made two major contributions to research on group awareness. First, the study compares the importance of different awareness elements in supporting group awareness for collaborative writing. The results of our Wilcoxon test on awareness elements identify the five most important elements, including ‘‘Being able to comment on what other users have done,’’ ‘‘Knowing what actions other users are currently taking,’’ ‘‘Providing a communication tool when audio is not available,’’ ‘‘Knowing other user’s working areas in the document,’’ and ‘‘Knowing other user’s tasks.’’ Second, the research proposes mechanisms corresponding to the above-mentioned five awareness elements. The mechanisms include Dynamic Task List (DTL), Modification Director (MD), Advanced Chat (AC) and Split Window View (SWV). These mechanisms provide support for various aspects of group awareness, and add many enhanced features to existing awareness mechanisms. For example, DTL presents high-level information about authors’ responsibilities and the correlation between their work allocations. MD notifies users instantaneously whenever their work is modified by other authors. AC enhances communication between users by allowing them to attach document objects such as text and diagrams to a conversation message. And, SWV provides the views of other authors’ working areas and viewing areas simultaneously. � 2005 Elsevier B.V. All rights reserved.
2474873
A support vector machine approach for detection of microcalcifications
We investigate an approach based on support vector machines (SVMs) for detection of microcalcification (MC) clusters in digital mammograms, and propose a successive enhancement learning scheme for improved performance. SVM is a machine-learning method, based on the principle of structural risk minimization, which performs well when applied to data outside the training set. We formulate MC detection as a supervised-learning problem and apply SVM to develop the detection algorithm. We use the SVM to detect at each location in the image whether an MC is present or not. We tested the proposed method using a database of 76 clinical mammograms containing 1120 MCs. We use free-response receiver operating characteristic curves to evaluate detection performance, and compare the proposed algorithm with several existing methods. In our experiments, the proposed SVM framework outperformed all the other methods tested. In particular, a sensitivity as high as 94% was achieved by the SVM method at an error rate of one false-positive cluster per image. The ability of SVM to outperform several well-known methods developed for the widely studied problem of MC detection suggests that SVM is a promising technique for object detection in a medical imaging application.
4379994
Interdomain Routing as Social Choice
Interdomain routing is essential to both the stability and efficiency of the global Internet. However, most previous studies focus only on stability, and only on a special class of routing protocols, namely BGP-type, path-vector protocols. In this paper, we conduct a systematic analysis of interdomain routing considering optimality and implementation in strategic settings. We adopt the novel perspective that an interdomain routing system is one which defines a social choice rule that aggregates individual preferences of all of the autonomous systems (ASes) in a network to select interdomain routes with a set of desirable properties. An interdomain routing protocol, then, is a mechanism to implement the identified interdomain routing social choice rule, when the ASes can adopt strategic actions. By pointing out the incompatibility among the desirable properties of an interdomain routing system and the requirements for strategic implementation in distributed settings, we reveal fundamental tradeoffs that must be made when extending BGP or designing the next-generation interdomain routing system. We also provide new insights into BGP, by "reverseengineering" its behaviors from the perspective of social choice and implementation theory.
17035085
Composable process elements for developing COTS-based applications
Data collected from five years of developing e-service applications at USC-CSE reveals that an increasing fraction have been commercial-off-the-shelf (COTS)-based applications (CBA) projects: from 28% in 1997 to 60% in 2001. Data from both small and large CBA projects show that CBA effort is primarily distributed among the three activities of COTS assessments, COTS tailoring, and glue code development and integration, with wide variations in their distribution across projects. We have developed a set of data-motivated composable process elements, in terms of these three activities, for developing CBA's as well an overall decision framework for applying the process elements. We present data regarding the movement towards CBA's and effort distribution among them; we then proceed to describe the decision framework and to present a real-world example showing how it operates within the WinWin Spiral process model generator to orchestrate, execute, and adapt the process elements to changing project circumstances.
32691594
On selfish routing in internet-like environments
A recent trend in routing research is to avoid inefficiencies in network-level routing by allowing hosts to either choose routes themselves (e.g., source routing) or use overlay routing networks (e.g., Detour or RON). Such approaches result in selfish routing, because routing decisions are no longer based on system-wide criteria but are instead designed to optimize host-based or overlay-based metrics. A series of theoretical results showing that selfish routing can result in suboptimal system behavior have cast doubts on this approach. In this paper, we use a game-theoretic approach to investigate the performance of selfish routing in Internet-like environments based on realistic topologies and traffic demands in our simulations. We show that in contrast to theoretical worst cases, selfish routing achieves close to optimal average latency in such environments. However, such performance benefits come at the expense of significantly increased congestion on certain links. Moreover, the adaptive nature of selfish overlays can significantly reduce the effectiveness of traffic engineering by making network traffic less predictable.
15260186
Using recursive classification to discover predictive features
Finding most predictive features for statistical classification is a challenging problem and has important applications. Support Vector Machines (SVMs), for example, have been found successful with a recursive procedure in selecting most important genes for cancer prediction. It is not well understood, however, how much the success depends on the choice of the classifier, and how much on the recursive procedure. We answer this question by examining multiple classifiers (SVM, ridge regression and Rocchio) with feature selection in recursive and non-recursive settings, on a DNA microarray dataset (AMLALL) and a text categorization benchmark (Reuters-21578). We found recursive ridge regression most effective: its best classification performance (zero error) on the AMLALL dataset was obtained when using only 3 genes (selected from over 7000), which is more impressive than the best published result on the same benchmark - zero error of recursive SVM using 8 genes. On Reuters-21578, recursive ridge regression also achieves the best result ever published (the improvement was verified in a significance test). An in-depth analysis of the experimental results shows that the choice of classifier heavily influences the recursive feature selection process: the ridge regression classifier tends to penalize redundant features to a much larger extent than the SVM does.