Prototype of assignment intelligent adaptive of service providers inside of ESB with data mining

The SOA philosophy can address new business challenges, become more competitive and provide integrated information systems. In addition, technologies such as BPM, BAM and Web Services are essential complements to SOA. This work aims to use several of these technologies integrated into a single application that will allow in a phase of a previously defined business process, to perform the analysis of input suppliers to the company through the generation of a decision tree using embedded code of the free tool Weka for data mining in order to feedback the business process and evaluate these results to improve the process. For the realization of this prototype we worked with the jBPM suite, the API from Weka to get the J48 algorithm, the postgresql database, the format for data exchange JSON and the web service

From Management Information Systems to Business Intelligence: The Development of Management Information Needs

Despite the advances in IT, information systems intended for management informing did not uniformly fulfil the increased expectations of users; this can be said mostly about complex information needs. Although some of the technologies for supporting complicated insights, like management decision support systems and technologies, experienced reduction in interest both from researchers and practitioners, this did not reduce the importance of well-supported business informing and decision making. Being attributed to the group of intelligent systems and technologies, decision support (DS) technologies have been largely supplemented by business intelligence (BI) technologies. Both types of technologies are supported by respective information technologies, which often appear to be quite closely related. The objective of this paper is to define relations between simple and complex informing intended to satisfy different sets of needs and provided by different sets of support tools. The paper attempts to put together decision support and business intelligence technologies, based on common goals of sense-making and use of advanced analytical tools. A model of two interconnected cycles has been developed to relate the activities of decision support and business intelligence. Empirical data from earlier research is used to direct possible further insights into this area

High-Performance Near-Time Processing of Bulk Data

Enterprise Systems like customer-billing systems or financial transaction systems are required to process large volumes of data in a fixed period of time. Those systems are increasingly required to also provide near-time processing of data to support new service offerings. Common systems for data processing are either optimized for high maximum throughput or low latency. This thesis proposes the concept for an adaptive middleware, which is a new approach for designing systems for bulk data processing. The adaptive middleware is able to adapt its processing type fluently between batch processing and single-event processing. By using message aggregation, message routing and a closed feedback-loop to adjust the data granularity at runtime, the system is able to minimize the end-to-end latency for different load scenarios. The relationship of end-to-end latency and throughput of batch and message-based systems is formally analyzed and a performance evaluation of both processing types has been conducted. Additionally, the impact of message aggregation on throughput and latency is investigated. The proposed middleware concept has been implemented with a research prototype and has been evaluated. The results of the evaluation show that the concept is viable and is able to optimize the end-to-end latency of a system. The design, implementation and operation of an adaptive system for bulk data processing differs from common approaches to implement enterprise systems. A conceptual framework has been development to guide the development process of how to build an adaptive software for bulk data processing. It defines the needed roles and their skills, the necessary tasks and their relationship, artifacts that are created and required by different tasks, the tools that are needed to process the tasks and the processes, which describe the order of tasks

Virtual learning process environment (VLPE): a BPM-based learning process management architecture

E-learning systems have significantly impacted the way that learning takes place within universities, particularly in providing self-learning support and flexibility of course delivery. Virtual Learning Environments help facilitate the management of educational courses for students, in particular by assisting course designers and thriving in the management of the learning itself. Current literature has shown that pedagogical modelling and learning process management facilitation are inadequate. In particular, quantitative information on the process of learning that is needed to perform real time or reflective monitoring and statistical analysis of students’ learning processes performance is deficient. Therefore, for a course designer, pedagogical evaluation and reform decisions can be difficult. This thesis presents an alternative e-learning systems architecture - Virtual Learning Process Environment (VLPE) - that uses the Business Process Management (BPM) conceptual framework to design an architecture that addresses the critical quantitative learning process information gaps associated with the conventional VLE frameworks. Within VLPE, course designers can model desired education pedagogies in the form of learning process workflows using an intuitive graphical flow diagram user-interface. Automated agents associated with BPM frameworks are employed to capture quantitative learning information from the learning process workflow. Consequently, course designers are able to monitor, analyse and re-evaluate in real time the effectiveness of their chosen pedagogy using live interactive learning process dashboards. Once a course delivery is complete the collated quantitative information can also be used to make major revisions to pedagogy design for the next iteration of the course. An additional contribution of this work is that this new architecture facilitates individual students in monitoring and analysing their own learning performances in comparison to their peers in a real time anonymous manner through a personal analytics learning process dashboard. A case scenario of the quantitative statistical analysis of a cohort of learners (10 participants in size) is presented. The analytical results of their learning processes, performances and progressions on a short Mathematics course over a five-week period are also presented in order to demonstrate that the proposed framework can significantly help to advance learning analytics and the visualisation of real time learning data

S-BPM in the Wild

This is the first book to present field studies on the application of subject-oriented business process management (S-BPM). Each case presents a specific story and focuses on an essential modeling or implementation issue, and most end with implications or suggestions for further studies. Significant variables and success factors are identified that were discovered during the respective study and lead to suggesting S-BPM novelties. For each case, the authors explain step-by-step how the story develops, and provide readers guidance by detailing the respective rationale. The studies covered are clustered according to three main S-BPM themes: Part I “Business Operation Support” documents approaches to the practical development of S-BPM solutions in various application domains and organizational settings, while Part II “Consultancy and Education Support” highlights cases that can help to train readers in S-BPM modeling and knowledge acquisition for S-BPM lifecycle iterations. It also refers to architecting S-BPM solutions for application cases based on hands-on experience. Part III “Technical Execution Support” focuses on concepts for utilizing specific theories and technologies to execute S-BPM models. It also addresses how to create reference models for certain settings in the field. Lastly, the appendix covers all relevant aspects needed to grasp S-BPM modeling and apply it based on fundamental examples. Its format reconciles semantic precision with syntactic rigor.>Addressing the needs of developers, educators and practitioners, this book will help companies to learn from the experiences of first-time users and to develop systems that fit their business processes, explaining the latest key methodological and technological S-BPM developments in the fields of training, research and application

An effective services framework for sharing educational resources

Nowadays, the growing number of software tools to support e-learning and the data they rely upon are valuable resources, supporting different aspects of the complex learning and teaching processes, including designing learning content, delivering learning activities, and evaluating students’ learning performance. However, sharing these educational resources efficiently and effectively is a challenge: there are many resources, these have not been described accurately and in general they do not interoperate, and it is common for the tools to rely on different technologies. This thesis explores a solution – a novel educational services framework – to improve the sharing of current e-resources, by applying the latest service technologies in the context of higher education. Our findings suggest that the proposed framework is effective to deal with the technical and educational issues in resource discovery, interoperability and reusability, however, there are still technical challenges remaining for implementing this service framework. This research is divided into 3 phases. The first phase investigates the sharing of elearning resources through a literature survey, and identifies limitations on current developments. In the second phase, the current problems relating to resource sharing are addressed by a proposed educational service framework, which contains both educational and technical components. Through a case study, nine e-learning services and their dataflows are identified. To determine the technical components of the framework, a novel Educational Service Architecture is proposed, which allows resources to be better described, structured and connected, by following the principles of discoverability, interoperability and reusability in service technologies. In the third phase, part of the framework is implemented and evaluated by two studies. In the first study, users’ experiences were collected via a simulation experiment, to compare the effectiveness of a service prototype with that of the use of current technologies. During the second part of the evaluation, technical challenges for implementing the services framework were identified via a case study, involving the implementation of another service prototype

Model-Driven Data Integration for Emergency Response : Doctoral Dissertation for the Degree Philosophiae Doctor (PhD) at the Faculty of Engineering and Science, Specialization in Information and Communication Technology

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CHOReOS Middleware Specification (D3.1)

This deliverable specifies the main concepts of the CHOReOS middleware architecture. Starting from the Future Internet (FI) challenges for scalability, heterogeneity, mobility, awareness, and adaptation that have been investigated in prior work done in WP1, we introduce the aforementioned concepts to deal with the requirements derived from the FI challenges. In particular, we propose an extensible and scalable service discovery approach for the organization and discovery of services that relies on multiple service discovery protocols. Moreover, we introduce an extensible and scalable approach, based on the service bus paradigm, for service access that features the integration and adaptation of multiple interaction protocols. Furthermore, we propose solutions that enable the execution of FI service compositions that range from compositions of choreographed services, developed according to the CHOReOS development process, to massive compositions of things. Finally, we detail the Cloud & Grid middleware facilities that support the overall middleware and the choreographies that are built on it, via a unified API that provides access to multiple cloud infrastructures (e.g., Amazon EC2, HP Open Cirrus, private clouds)

Brain-Inspired Computing

This open access book constitutes revised selected papers from the 4th International Workshop on Brain-Inspired Computing, BrainComp 2019, held in Cetraro, Italy, in July 2019. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They deal with research on brain atlasing, multi-scale models and simulation, HPC and data infra-structures for neuroscience as well as artificial and natural neural architectures