On-line transformer condition monitoring through diagnostics and anomaly detection

This paper describes the end-to-end components of an on-line system for diagnostics and anomaly detection. The system provides condition monitoring capabilities for two in- service transmission transformers in the UK. These transformers are nearing the end of their design life, and it is hoped that intensive monitoring will enable them to stay in service for longer. The paper discusses the requirements on a system for interpreting data from the sensors installed on site, as well as describing the operation of specific diagnostic and anomaly detection techniques employed. The system is deployed on a substation computer, collecting and interpreting site data on-line

Integrating E-Commerce and Data Mining: Architecture and Challenges

We show that the e-commerce domain can provide all the right ingredients for successful data mining and claim that it is a killer domain for data mining. We describe an integrated architecture, based on our expe-rience at Blue Martini Software, for supporting this integration. The architecture can dramatically reduce the pre-processing, cleaning, and data understanding effort often documented to take 80% of the time in knowledge discovery projects. We emphasize the need for data collection at the application server layer (not the web server) in order to support logging of data and metadata that is essential to the discovery process. We describe the data transformation bridges required from the transaction processing systems and customer event streams (e.g., clickstreams) to the data warehouse. We detail the mining workbench, which needs to provide multiple views of the data through reporting, data mining algorithms, visualization, and OLAP. We con-clude with a set of challenges.Comment: KDD workshop: WebKDD 200

Web-enabled Data Warehouse and Data Webhouse

In this paper, our objectives are to understanding what data warehouse means examine the reasons for doing so, appreciate the implications of the convergence of Web technologies and those of the data warehouse and examine the steps for building a Web-enabled data warehouse. The web revolution has propelled the data warehouse out onto the main stage, because in many situations the data warehouse must be the engine that controls or analysis the web experience. In order to step up to this new responsibility, the data warehouse must adjust. The nature of the data warehouse needs to be somewhat different. As a result, our data warehouses are becoming data webhouses. The data warehouse is becoming the infrastructure that supports customer relationship management (CRM). And the data warehouse is being asked to make the customer clickstream available for analysis. This rebirth of data warehousing architecture is called the data webhouse.data warehouse, web-enabled, data mart, Internet, intranet, extranet

Modeling and Execution of Multienterprise Business Processes

We discuss a fully featured multienterprise business process plattform (ME-BPP) based on the concepts of agent-based business processes. Using the concepts of the subject-oriented business process (S-BPM) methodology we developed an architecture to realize a platform for the execution of distributed business processes. The platform is implemented based on cloud technology using commercial services. For our discussion we used the well known Service Interaction Patterns, as they are empirically developed from typical business-to-business interactions. We can demonstrate that all patterns can be easily modeled and executed based on our architecture. We propose therefore a change from a control flow based to an agent based view to model and enact business processes.Comment: arXiv admin note: substantial text overlap with arXiv:1404.273

Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes