Web service composition enables seamless and dynamic integration of business applications on the web. The performance of the composed application is determined by the performance of the involved web services. Therefore, non-functional, quality of service (QoS) aspects (e.g. response time, availability, etc.) are crucial for selecting the web services to take part in the composition. The problem of identifying the best candidate web services from a set of functionally-equivalent services is a multi-criteria decision making problem. The selected services should optimize the overall QoS of the composed application, while satisfying all the constraints specified by the client on individual QoS parameters. In this paper, we propose an approach based on the notion of skyline to effectively and efficiently select services for composition, reducing the number of candidate services to be considered. We also discuss how a provider can improve its service to become more competitive and increase its potential of being included in composite applications. We evaluate our approach experimentally using both real and synthetically generated datasets.

One of the main tasks in the early stages of a Data Warehouse project is the identification of the appropriate transformations and the specification of inter-schema mappings from the data sources to the Data Warehouse. In this paper, we propose an ontology-based approach to facilitate the conceptual design of the back stage of a Data Warehouse. A graph-based representation is used as a conceptual model for the datastores, so that both structured and semi-structured data are supported and handled in a uniform way. The proposed approach is based on the use of Semantic Web technologies to semantically annotate the data sources and the Data Warehouse, so that mappings between them can be inferred, thereby resolving the issue of heterogeneity. Specifically, a suitable application ontology is created and used to annotate the datastores. The language used for describing the ontology is OWL-DL. Based on the provided annotations, a DL reasoner is employed to infer semantic correspondences and conflicts among the datastores and propose a set of conceptual operations for transforming data from the source datastores to the Data Warehouse.

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This study aimed to examine the rates and risk factors for ipsilateral re-amputation in 121 patients with diabetic foot and prior amputation. Twenty-six (21.5%) patients required re-amputation during a mean follow-up of 18 months. Most re-amputations were performed within the first 6 months of the initial amputation. Re-amputation was more common among patients in whom the initial amputation had only affected one or two toes. Age (hazard ratio: 1.06) and heel lesions (hazard ratio: 2.69) were significantly associated with re-amputation. There is a high risk of re-amputation in the diabetic foot, especially within the first 6 months of the initial amputation, mainly due to poor selection of the original amputation level in an effort to save a greater part of the lower extremity. Patients 70 years and those with heel lesions are at greatest risk of re-amputation.

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