An Agent-Based E-engineering Services Framework for Engineering Design and Optimization

title: An agent-based Web service workflow model for inter-enterprise collaboration
abstract: The service-orientated computing paradigm is transforming traditional workflow management from a close and centralized control system into a worldwide dynamic business process. A complete workflow serving inter-enterprise collaboration should include both internal processes and ad hoc external processes. This paper presents an agent-based workflow model to address this challenge. In the proposed model, agent-based technology provides the workflow coordination at both inter- and intra-enterprise levels while Web service-based technology provides infrastructures for messaging, service description and workflow enactment. A proof-of-concept prototype system simulating the order entry, partner search and selection, and contracting in a virtual enterprise creation scenario is implemented to demonstrate the dynamic workflow definition and execution for inter-enterprise collaboration.

title: Agent Based Dynamic Information Gathering And Organization For Distributed Product Development
abstract: The concept of Web-based Visualized Product Structure Tree (VPST) has been proposed to realize a platform-independent, visualized and integrated product information sharing. This paper extends this concept by developing an agent based dynamic information gathering and organization framework to support updating the VPST dynamically. The objective is to enable different users to perform real time collaboration over the Web. The proposed framework is composed of three modules: Information Gathering, Information Organization Server and Information Sharing Server. Each of them is composed of a number of agents. The paper presents a detailed design and implementation of the proposed framework and its three modules.

title: Multi-Model Driven Collaborative Development Platform for Service-Oriented e-Business Systems
abstract: Service-oriented architecture can improve e-business applications to be integrated and flexible. This paper proposes a multi-model driven collaborative development platform for service-oriented e-business systems. The platform provides three views, i.e., business view, process view, and service view to support service-oriented software engineering, top-down business planning and bottom-up service-oriented application development. Business and technical consultants can collaborate from distributed sites of, e.g., clients and IT vendors to provide their clients' with rapid development and demonstration. The proposed platform is driven by three models, i.e., service meta model, process model and business model. All of the three models support semantic description and rational operations, and facilitate intelligent service discovery, process execution and business-business integration. Concepts and implementation issues about the proposed platform has been presented in this paper. The platform has been developed and deployed in an innovation centre to be evaluated by visiting customers

title: A multi-resolution collaborative architecture for web-centric global manufacturing
abstract: We propose a recursive multi-resolution collaborative architecture (MRCA), based on multi-agent coordination mechanisms as a solid foundation for the development of web-centric cooperative applications in global manufacturing. The architecture consists of three layers: a low-level internetworking communication-support layer; a coordination layer ‐ managing inter-agent cooperation through intelligent conversation/communication mechanisms; and an agent layer consisting of five categories of agents: interface, collaboration, knowledge management, application and resource agents. From a functional perspective, two distinctive hierarchies shape the multi-dimensionality of this architecture: a vertical hierarchy of agents and a horizontal hierarchical communication‐coordination platform. The versatility of the proposed architecture (which supports practically any kind of collaborative application) and its recursive replication at all levels of resolution within the collaborative application are illustrated on a supply-chain example. ” 2000 Elsevier Science Inc. All rights reserved.

title: Distributed Manufacturing Scheduling Using Intelligent Agents
abstract: Manufacturing scheduling is an optimization process that allocates limited manufacturing resources over time among parallel and sequential manufacturing activities. This allocation must obey a set of rules or constraints that reflect the temporal relationships between manufacturing activities and the capacity limitations of a set of shared resources. The allocation also affects a schedule's optimality with respect to criteria such as cost, lateness, or throughput. The globalization of manufacturing makes such optimization increasingly important. To survive in this competitive market, manufacturing enterprises must increase their productivity and profitability through greater shop floor agility. Agent-based manufacturing scheduling systems are a promising way to provide this optimization.

title: Constraint-Based Entity Matching
abstract: Entity matching is the problem of deciding if two given mentions in the data, such as "Helen Hunt" and "H. M. Hunt", refer to the same real-world entity. Numerous solutions have been developed, but they have not considered in depth the problem of exploiting integrity constraints that frequently exist in the domains. Examples of such constraints include "a mention with age two cannot match a mention with salary 200K" and "if two paper citations match, then their authors are likely to match in the same order". In this paper we describe a probabilistic solution to entity matching that exploits such constraints to improve matching accuracy. At the heart of the solution is a generative model that takes into account the constraints during the generation process, and provides well-defined interpretations of the constraints. We describe a novel combination of EM and relaxation labeling algorithms that efficiently learns the model, thereby matching mentions in an unsupervised way, without the need for annotated training data. Experiments on several real-world domains show that our solution can exploit constraints to significantly improve matching accuracy, by 3-12% F-1, and that the solution scales up to large data sets.

title: Declarative Information Extraction Using Datalog with Embedded Extraction Predicates
abstract: In this paper we argue that developing information extraction (IE) programs using Datalog with embedded procedural extraction predicates is a good way to proceed. First, compared to current ad-hoc composition using, e.g., Perl or C++, Datalog provides a cleaner and more powerful way to compose small extraction modules into larger programs. Thus, writing IE programs this way retains and enhances the important advantages of current approaches: programs are easy to understand, debug, and modify. Second, once we write IE programs in this framework, we can apply query optimization techniques to them. This gives programs that, when run over a variety of data sets, are more efficient than any monolithic program because they are optimized based on the statistics of the data on which they are invoked. We show how optimizing such programs raises challenges specific to text data that cannot be accommodated in the current relational optimization framework, then provide initial solutions. Extensive experiments over real-world data demonstrate that optimization is indeed vital for IE programs and that we can effectively optimize IE programs written in this proposed framework.

title: Segmentation and Evaluation of Adipose Tissue from Whole Body MRI Scans
abstract: Accurate quantification of total body and the distribution of regional adipose tissue using manual segmentation is a challenging problem due to the high variation between manual delineations. Manual segmentation also requires highly trained experts with knowledge of anatomy. We present a hybrid segmentation method that provides robust delineation results for adipose tissue from whole body MRI scans. A formal evaluation of accuracy of the segmentation method is performed. This semi-automatic segmentation algorithm reduces significantly the time required for quantification of adipose tissue, and the accuracy measurements show that the results are close to the ground truth obtained from manual segmentations.

title: Source-aware Entity Matching: A Compositional Approach
abstract: Entity matching (a.k.a. record linkage) plays a crucial role in integrating multiple data sources, and numerous matching solutions have been developed. However, the solutions have largely exploited only information available in the mentions and employed a single matching technique. We show how to exploit information about data sources to significantly improve matching accuracy. In particular, we observe that different sources often vary substantially in their level of semantic ambiguity, thus requiring different matching techniques. In addition, it is often beneficial to group and match mentions in related sources first, before considering other sources. These observations lead to a large space of matching strategies, analogous to the space of query evaluation plans considered by a relational optimizer. We propose viewing entity matching as a composition of basic steps into a "match execution plan". We analyze formal properties of the plan space, and show how to find a good match plan. To do so, we employ ideas from social network analysis to infer the ambiguity and related-ness of data sources. We conducted extensive experiments on several real-world data sets on the Web and in the domain of personal information management (PIM). The results show that our solution significantly outperforms current best matching methods.

title: Community Information Management
abstract: We introduce Cimple, a joint project between the University of Illinois and the University of Wisconsin. Cimple aims to develop a software platform that can be rapidly deployed and customized to manage data-rich online communities. We first describe the envisioned working of such a software platform and our prototype, DBLife, which is a community portal being developed for the database research community. We then describe the technical challenges in Cimple and our solution approach. Finally, we discuss managing uncertainty and provenance, a crucial task in making our software platform practical.