12957954
Agents and Web Services Supported Business Exception Management
The unpredictability of business processes requires that business applications support exception management with the ability to dynamically adapt to the changing environment. Exception management is a kind of complex process, in which multiple organizations and mixture of human activities and automated tasks may be involved. For a competitive solution to exception management, a web services and agents supported approach is elaborated in this paper. Agent technology is applied to deal with the dynamic, complex, and distributed processes in exception management; web services techniques are proposed for more scalability and interoperability in network-based business environment. By integrating knowledge-based agents with web services to make use of the advantages from both, this approach leads to more intelligence, flexibility and collaboration in business exception management. A case of exception management in securities trading is developed to demonstrate the validity and benefits of this approach.
17954201
Dynamic Supply Chain Integration through Intelligent Agents
The success of supply chains depends on the match between the requirements and offerings that deliver the services. It can be ensured by separating requirements from the means of realization as well as dynamically assigning available resources to requests. To achieve this, we need coordinate the flow of information among the services and link their business processes under various constraints. Existing approaches to this problem have relied on complete information of services and resources, and have failed to adequately address the dynamics and uncertainties of the operating environments. The problem is complicated as a result of undetermined requirements of decomposed individual services and unpredictable solutions contributed by service providers. This paper examines an agent-mediated coordination approach to dynamic supply chain integration. Each agent works as a broker for each service involved in the chain, exploring service requests as well as identifying suitable resources for achieving compatibility and coherence among the decisions of individual services. Based on the approach, a prototype has been implemented with simulated experiments highlighting the effectiveness of the approach
12211000
Intelligent Agent Supported Business Process Management
The complex business environment requires managing business processes with the ability to adapt to changes and to collaborate in activities. Conventional workflow approaches based on predefined logical procedure offer little support for the dynamic business environment. A cognitive agent-based approach is proposed to manage business activities based on situational awareness and real-time decisions on activities. Business activities are delegated to a number of cognitive and collaborative problem-solving agents. Each software agent perceives its environment by capturing events and monitoring the state of tasks and resources. Based on the continuous perception of environment, business rules concerning process routing, operational constraint, exception handling and business strategy are used by such software agents to perform appropriate actions. The mechanism of this approach is investigated, and a case application of exception management in securities trading is developed to demonstrate the validity and benefits of this approach.
7446737
A web-service agent-based decision support system for securities exception management
Abstract With rising trading volumes and increasing risks in securities transactions, the securities industry is making an effort to shorten the trade lifecycle and minimize transaction risks. While attempting to achieve this, exception management is crucial to pass trade information within the trade lifecycle in a timely and accurate fashion. For a competitive solution to exception management, a web-service-agent-based decision support system is developed in this paper. Agent technology is applied to deal with the dynamic, complex, and distributed processes in exception management; web services techniques are proposed for more scalability and interoperability in network-based business environment. By integrating agent technology with web services to make use of the advantages from both, this approach leads to more intelligence, flexibility and collaboration in business exception management. The effectiveness of this approach is evaluated through a use case and demonstration feedback.
7484569
The design of intelligent workflow monitoring with agent technology
In recent years, workflow technology has been widely used in business process management. With the increased complexity, uncertainty and risks in business operations, workflow monitoring is gaining growing attention in business process controlling and supervision. However, monitoring functions provided in traditional workflow systems lack flexibility, and provide little support for managing complex and dynamical changes in business process. In this paper, we propose a novel workflow monitoring approach, in which various intelligent agents work together to perform flexible monitoring tasks in an autonomous and collaborative way. By using customized monitoring plan and proactive monitoring process, the workflow monitoring activities can be executed flexibly and efficiently. The application of intelligent agents for such flexible, adaptive and collaborative workflow monitoring is investigated through an intelligent monitoring system in securities trading.
231152
Capturing the spatio-temporal behavior of real traffic data
Traffic data, such as disk and memory accesses, typically exhibits burstiness, temporal locality, and spatial locality. However, except for qualitative speculations, it is not even known how to measure the spatio-temporal correlation, let alone how to re-produce it realistically. In this paper, we propose the "entropy plots" to quantify the correlation and develop a new statistical model, the "PQRS" model, to capture the burstiness and correlation of the real spatio-temporal traffic. Moreover, the model requires very few parameters and offers linear scalability. Experiments with multiple real data sets show that our model can mimic real traces very well.
39861836
A Novel Method for Eye Features Extraction
Extraction of the eye features, like the pupil center and radius, eye corners and eyelid contours from the frontal face images often provides us useful cues in many important applications, such as face recognition, facial expression recognition and 3D face modeling from 2D images. Assuming the rough eye window is known, the color information, Gabor features are extracted from the eye window and then these two features and their mutual relationship have been incorporated into the design of our algorithm. Firstly, after the pupil center is detected in H channel of HSV color space, the pupil radius is estimated and refined. Secondly, eye corners are localized using eye-corner filter based on Gabor feature space. Finally, eyelid curves are fitted by spline function. The new algorithm has been tested on our SJTU database and some other pictures taken from the web. The experimental results show that our algorithm has high accuracy and is robust under different conditions.
5446179
Declarative Agent Programming Support for a FIPA-Compliant Agent Platform
Multi-agent system(MAS) is a blooming research area, which exhibits a new paradigm for the design, modeling and implementation of complex systems. A significant amount of effort has been made in establishing standards for agent communication and MAS platforms. However, communication is not the only difficulty faced by agent researchers. Research is also directed towards the formal aspects of agents and declarative approaches to model agents. This paper explores the bonding between high-level reasoning engines and low-level agent platforms in the practical setting of using three formal agent reasoning implementations together with an existing agent platform, OPAL, that supports the FIPA standards. We focus our discussion in this paper on our approach to provide declarative agent programming support in connection with the OPAL platform, and show how declarative goals can be used to glue the internal micro agents together to form the hierarchical architecture of the platform.
15805455
SciPort: An Adaptable Scientific Data Integration Platform for Collaborative Scientific Research
Scientific data are posing new challenges to data management due to the large volume, complexity and heterogeneity of the data. Meanwhile, scientific collaboration becomes increasingly important, which relies on integrating and sharing data from distributed institutions. In this demo, we present SciPort, a Web-based platform on supporting scientific data management and integration based on peer-to-peer architectures, where researchers can easily collect, publish, and share their complex scientific data across multi-institutions. SciPort provides a general metadata based data model to capture the context description of experiments and link experiment data into comprehensive metadata documents, and supports a hierarchical organization of the overall data space for data browsing. SciPort takes two alternative "peer"-to-"peer" (or peer-database-to-peer-database) based approaches to integrate scientific data: pure peer-to-peer architecture and central server based peer-to-peer architecture. The later provides a virtual view of all published data from multiple local sites and supports complex queries with XQuery. The system provides a unified framework for adaptable architectures and customizable schemas, and supplies comprehensive tool set to manage and share scientific data. SciPort was first prototyped in Siemens Corporate Research, and now becomes a mature product and has been successfully used in both biomedical research and clinical trials for scientific research communities.
3479382
Semantic Data Management: Towards Querying Data with their Meaning
Relational database management systems are constantly being extended and augmented to accommodate data in different domains. Recently, with the increasing use of ontology in various applications, the need to support ontology, especially the related inferencing operation, in DBMS has become more concrete and urgent. However, manipulating knowledge along with relational data in DBMSs is not a trivial undertaking due to the mismatch in data models. In this paper, we introduce a framework for managing relational data and hierarchical domain knowledge together. Our framework persists taxonomies contained in ontologies by leveraging XML support in hybrid relational-XML DBMSs (e.g., IBM's DB2 v9) and rewrites ontology-based semantic matching queries using the industry-standard query languages, SQL/XML and XQuery. Compared with previous approaches, our approach does not materialize transitive closures of ontological relationships to support inferencing. Consequently, our method has wide applicability and good performance.