A Framework for the Evaluation of Semantics-based Service Composition Approaches

The benefits of service composition are being largely acknowledged in the literature nowadays. However, as the amount of available services increases, it becomes difficult to manage, discover, select and compose them, so that automation is required in these processes. This can be achieved by using semantic information represented in ontologies. Currently there are many different approaches that support semantics-based service composition. However, still little effort has been spent on creating a common methodology to evaluate and compare such approaches. In this paper we present our initial ideas to create an evaluation framework for semantics-based service composition approaches. We use a collection of existing services, and define a set of evaluation metrics, confusion matrix-based and time-based. Furthermore, we present how composition evaluation scenarios are generated from the collection of services and specify the strategy to be used in the evaluation process. We demonstrate the proposed framework through an example. Currently there are mechanisms and initiatives to address the evaluation of the semantics-based service discovery and matchmaking approaches. However, still few efforts have been spent on the creation of comprehensive evaluation mechanisms for semantics-based service composition approaches

Supporting Dynamic Service Composition at Runtime based on End-user Requirements

Network-based software application services are receiving a lot of attention in recent years, as observed in developments as Internet of Services, Software as a Service and Cloud Computing. A service-oriented computing ecosystem is being created where the end-user is having an increasingly more active role in the service creation process. However, supporting end-users in the creation process, at runtime, is a difficult undertaking. Users have different requirements and preferences towards application services, use services in different situations and expect highly abstract mechanisms in the creation process. Furthermore, there are different types of end-users: some can deliver more detailed requirements or can be provided with more advanced request interface, while others can not. To tackle these issues and provide end-users with personalised service delivery, we claim that runtime automated service composition mechanisms are required. In this paper we present the DynamiCoS framework, which aims at supporting the different phases required to provide end-users with automatic service discovery, selection and composition process. In this paper we also present the developed prototype and its evaluation

Towards runtime discovery, selection and composition of semantic services

Service-orientation is gaining momentum in distributed software applications, mainly because it facilitates interoperability and allows application designers to abstract from underlying implementation technologies. Service composition has been acknowledged as a promising approach to create composite services that are capable of supporting service user needs, possibly by personalising the service delivery through the use of context information or user preferences. In this paper we discuss the challenges of automatic service composition, and present DynamiCoS, which is a novel framework that aims at supporting service composition on demand and at runtime for the benefit of service end-users. We define the DynamiCoS framework based on a service composition life-cycle. Framework mechanisms are introduced to tackle each of the phases and requirements of this life-cycle. Semantic services are used in our framework to enable reasoning on the service requests issued by end users, making it possible to automate service discovery, selection and composition. We validate our framework with a prototype that we have built in order to experiment with the mechanisms we have designed. The prototype was evaluated in a testing environment using some use case scenarios. The results of our evaluation give evidences of the feasibility of our approach to support runtime service composition. We also show the benefits of semantic-based frameworks for service composition, particularly for end-users who will be able to have more control on the service composition process

Imagens em movimento e representações: desembrulhando imaginários coloniais

Este texto explora a relação entre imagens em movimento e suas formas de representação. Partindo do diálogo entre os campos da antropologia e da sociologia, contribuímos para a discussão acerca da conexão entre imagens, suas formas de representar e educação, através de um exercício de desconstrução crítica de imaginários coloniais. Propomos em seguida uma reflexão localizada em Heidegger, no modo como este observa o trabalho de Kant na Crítica da Razão Pura, particularmente no que ao representar da imagem diz respeito. // This text explores the relationship between moving images and its forms of representation. Starting from a dialogue between the fields of anthropology and sociology, we contribute to the discussion about the connection of images, its forms of representing and education, within an exercise in deconstructing colonial imaginary. We then propose a reflection on Heidegger in the way he looks at the work of Kant in the Critique of Pure Reason, especially in what concerns the representing ways of the image. Keywords: colonial imagery; imperial power rituals; image; representation

Knowledge Transfer for Melanoma Screening with Deep Learning

Knowledge transfer impacts the performance of deep learning -- the state of the art for image classification tasks, including automated melanoma screening. Deep learning's greed for large amounts of training data poses a challenge for medical tasks, which we can alleviate by recycling knowledge from models trained on different tasks, in a scheme called transfer learning. Although much of the best art on automated melanoma screening employs some form of transfer learning, a systematic evaluation was missing. Here we investigate the presence of transfer, from which task the transfer is sourced, and the application of fine tuning (i.e., retraining of the deep learning model after transfer). We also test the impact of picking deeper (and more expensive) models. Our results favor deeper models, pre-trained over ImageNet, with fine-tuning, reaching an AUC of 80.7% and 84.5% for the two skin-lesion datasets evaluated.Comment: 4 page

Recovery of metals from MSW fly ash by leaching and liquid-liquid extraction

Tese de mestrado integrado. Engenharia Química. Faculdade de Engenharia. Universidade do Porto, Chalmers University of Technology. 200

Intervencionismo estatal durante el franquismo tardío : un análisis del condicionamiento industrial

El presente estudio analiza la expansión internacional de la actividad de I+D de las empresas multinacionales estadounidenses a lo largo del periodo 1977-94. En él se argumenta que se ha producido un cambio fundamental en la forma en la que dichas empresas organizan su actividad innovadora entre las distintas unidades del grupo, lo que obliga a reconsiderar el enfoque adoptado hasta ahora por los estudios sobre localización de la I+D. Superada la incertidumbre de las primeras fases de la expansión internacional, las redes de innovación siguen ahora pautas independientes de las redes de producción. Su estructura viene determinada por características del proceso de innovación como la base de conocimiento, oportunidades tecnológicas o apropiabilidad y en ellas se llevan a cabo todo tipo de actividades independientemente de la especialización tecnológica del país de origen. Finalmente, se destaca la importancia de los factores de demanda locales no sólo para atraer la I+D adaptativa o de apoyo técnico como ha venido sugiriendo la literatura sino también las investigaciones encaminadas a desarrollar nuevos productos o procesos, por lo que el dinamismo del mercado podría estar reflejando la existencia de redes locales de innovación activas tal y como se desprende del enfoque de aprendizaje interactivo. ABSTRACT This paper examines the international expansion of R&D by US multinational enterprises (MNE) during the period 1977-1994. The empirical results indicate that there has been a fundamental shift in the way MNEs organize their innovatory activity between the different corporate units which requires the traditional approach of R&D locational studies to be reconsidered. Once the uncertainty of the first stages has been overcame, innovation networks follow their own path independent from the production network ones. Its structure is determined by characteristics of the innovation process such as knowledge base, technological opportunities or appropiability and they carry out all kind of activities independently of the technological specialisation of MNE home country. Finally, this paper stress the importance of demand-side factors not only to attract adaptative R&D or technical support R&D -as the previous literature has suggested- but also research aimed to develop new products and processes, so market dynamism could be reflecting the existence of active local innovative networks as it is infered from the interactive learning approach