10,896 research outputs found

    Supporting adaptiveness of cyber-physical processes through action-based formalisms

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    Cyber Physical Processes (CPPs) refer to a new generation of business processes enacted in many application environments (e.g., emergency management, smart manufacturing, etc.), in which the presence of Internet-of-Things devices and embedded ICT systems (e.g., smartphones, sensors, actuators) strongly influences the coordination of the real-world entities (e.g., humans, robots, etc.) inhabitating such environments. A Process Management System (PMS) employed for executing CPPs is required to automatically adapt its running processes to anomalous situations and exogenous events by minimising any human intervention. In this paper, we tackle this issue by introducing an approach and an adaptive Cognitive PMS, called SmartPM, which combines process execution monitoring, unanticipated exception detection and automated resolution strategies leveraging on three well-established action-based formalisms developed for reasoning about actions in Artificial Intelligence (AI), including the situation calculus, IndiGolog and automated planning. Interestingly, the use of SmartPM does not require any expertise of the internal working of the AI tools involved in the system

    A Framework for Semi-automated Web Service Composition in Semantic Web

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    Number of web services available on Internet and its usage are increasing very fast. In many cases, one service is not enough to complete the business requirement; composition of web services is carried out. Autonomous composition of web services to achieve new functionality is generating considerable attention in semantic web domain. Development time and effort for new applications can be reduced with service composition. Various approaches to carry out automated composition of web services are discussed in literature. Web service composition using ontologies is one of the effective approaches. In this paper we demonstrate how the ontology based composition can be made faster for each customer. We propose a framework to provide precomposed web services to fulfil user requirements. We detail how ontology merging can be used for composition which expedites the whole process. We discuss how framework provides customer specific ontology merging and repository. We also elaborate on how merging of ontologies is carried out.Comment: 6 pages, 9 figures; CUBE 2013 International Conferenc

    Reactive Rules for Emergency Management

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    The goal of the following survey on Event-Condition-Action (ECA) Rules is to come to a common understanding and intuition on this topic within EMILI. Thus it does not give an academic overview on Event-Condition-Action Rules which would be valuable for computer scientists only. Instead the survey tries to introduce Event-Condition-Action Rules and their use for emergency management based on real-life examples from the use-cases identified in Deliverable 3.1. In this way we hope to address both, computer scientists and security experts, by showing how the Event-Condition-Action Rule technology can help to solve security issues in emergency management. The survey incorporates information from other work packages, particularly from Deliverable D3.1 and its Annexes, D4.1, D2.1 and D6.2 wherever possible

    What does it take to make integrated care work? A ‘cookbook’ for large-scale deployment of coordinated care and telehealth

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    The Advancing Care Coordination & Telehealth Deployment (ACT) Programme is the first to explore the organisational and structural processes needed to successfully implement care coordination and telehealth (CC&TH) services on a large scale. A number of insights and conclusions were identified by the ACT programme. These will prove useful and valuable in supporting the large-scale deployment of CC&TH. Targeted at populations of chronic patients and elderly people, these insights and conclusions are a useful benchmark for implementing and exchanging best practices across the EU. Examples are: Perceptions between managers, frontline staff and patients do not always match; Organisational structure does influence the views and experiences of patients: a dedicated contact person is considered both important and helpful; Successful patient adherence happens when staff are engaged; There is a willingness by patients to participate in healthcare programmes; Patients overestimate their level of knowledge and adherence behaviour; The responsibility for adherence must be shared between patients and health care providers; Awareness of the adherence concept is an important factor for adherence promotion; The ability to track the use of resources is a useful feature of a stratification strategy, however, current regional case finding tools are difficult to benchmark and evaluate; Data availability and homogeneity are the biggest challenges when evaluating the performance of the programmes

    Knowledge based economy –technological perspective: implications and solutions for agility improvement and innovation achievement in higher education

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    Nowadays, the universities, as driving forces of innovative economy and as components of modern society, based on knowledge and collaboration, face a number of challenges and difficulties. In order to overcome them and to create/ensure the bases of eScience education and research activities, universities have to change culturally, strategically, and operationally. The paper highlights the need for ICT (Information and Communications Technology) use and its implications for higher education. In addition, the study places the theoretical aspects into a specific context, combining technologies through interfunctionality in order to ensure academic education agility and innovation. This involves the use of knowledge, process management, service oriented architectures, and Cloud solutions, exemplifying on the Academy of Economic Studies, Bucharest case. The integrated approach is extended using the SharePoint 2010 platform to improve academic management and achieve harmonization of teaching and research and development content and methods with European Union standards. The platform has been implemented and tested within two AES departments and the Master’s Degree Studies in Computer Economics. The results have encouraged the integration of the proposed solution within the institution. The study was based on the authors' competences in the areas addressed and was joined with a rigorous analysis of technology trends and various EU countries (Italy, Germany France, Belgium, Netherlands etc.) universities outputs regarding knowledge economy implications for economic higher education studies.knowledge-based economy, information and communications technology, university studies in economics, university management, agility, innovation, SharePoint 2010

    Automatically attaching web pages to an ontology

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    This paper describes a proposed system for automatically attaching material from the world wide web to concepts in an ontology. The motivation for this research stems from the Diogene project, which requires the project's own databases of learning objects to be augmented with additional resources from the web. Two main approaches to this problem are being taken: one using ontology mapping, and another based on the conventional text search facilities of the web, covered in this paper. By generating queries based on the concepts in the ontology, the aim is to retrieve material from the web, and then filter it to ensure its proper correspondence with a concept. The Diogene system will be briefly outlined, before the query-generation system is described. A small pilot experiment, designed to provide some initial results and insight into the problem, is then presented

    Machine Learning-Based Elastic Cloud Resource Provisioning in the Solvency II Framework

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    The Solvency II Directive (Directive 2009/138/EC) is a European Directive issued in November 2009 and effective from January 2016, which has been enacted by the European Union to regulate the insurance and reinsurance sector through the discipline of risk management. Solvency II requires European insurance companies to conduct consistent evaluation and continuous monitoring of risks—a process which is computationally complex and extremely resource-intensive. To this end, companies are required to equip themselves with adequate IT infrastructures, facing a significant outlay. In this paper we present the design and the development of a Machine Learning-based approach to transparently deploy on a cloud environment the most resource-intensive portion of the Solvency II-related computation. Our proposal targets DISAR®, a Solvency II-oriented system initially designed to work on a grid of conventional computers. We show how our solution allows to reduce the overall expenses associated with the computation, without hampering the privacy of the companies’ data (making it suitable for conventional public cloud environments), and allowing to meet the strict temporal requirements required by the Directive. Additionally, the system is organized as a self-optimizing loop, which allows to use information gathered from actual (useful) computations, thus requiring a shorter training phase. We present an experimental study conducted on Amazon EC2 to assess the validity and the efficiency of our proposal

    Closing the loop: assisting archival appraisal and information retrieval in one sweep

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    In this article, we examine the similarities between the concept of appraisal, a process that takes place within the archives, and the concept of relevance judgement, a process fundamental to the evaluation of information retrieval systems. More specifically, we revisit selection criteria proposed as result of archival research, and work within the digital curation communities, and, compare them to relevance criteria as discussed within information retrieval's literature based discovery. We illustrate how closely these criteria relate to each other and discuss how understanding the relationships between the these disciplines could form a basis for proposing automated selection for archival processes and initiating multi-objective learning with respect to information retrieval
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