Planar compact array with parasitic elements for MIMO systems

A compact planar array with parasitic elements is studied to be used in MIMO systems. Classical compact arrays suffer from high coupling which makes correlation and matching efficiency to be worse. A proper matching network improves these lacks although its bandwidth is low and may increase the antenna size. The proposed antenna makes use of parasitic elements to improve both correlation and efficiency. A specific software based on MoM has been developed to analyze radiating structures with several feed points. The array is optimized through a Genetic Algorithm to determine parasitic elements position in order to fulfill different figures of merit. The proposed design provides the required correlation and matching efficiency to have a good performance over a significant bandwidth.

A novel context ontology to facilitate interoperation of semantic services in environments with wearable devices

The LifeWear-Mobilized Lifestyle with Wearables (Lifewear) project attempts to create Ambient Intelligence (AmI) ecosystems by composing personalized services based on the user information, environmental conditions and reasoning outputs. Two of the most important benefits over traditional environments are 1) take advantage of wearable devices to get user information in a nonintrusive way and 2) integrate this information with other intelligent services and environmental sensors. This paper proposes a new ontology composed by the integration of users and services information, for semantically representing this information. Using an Enterprise Service Bus, this ontology is integrated in a semantic middleware to provide context-aware personalized and semantically annotated services, with discovery, composition and orchestration tasks. We show how these services support a real scenario proposed in the Lifewear project.

On a meaningful integration of web services in data-intensive biomedical environments: The DICODE approach

This paper reports on an innovative approach that aims to reduce information management costs in data-intensive and cognitively-complex biomedical environments. Recognizing the importance of prominent high-performance computing paradigms and large data processing technologies as well as collaboration support systems to remedy data-intensive issues, it adopts a hybrid approach by building on the synergy of these technologies. The proposed approach provides innovative Web-based workbenches that integrate and orchestrate a set of interoperable services that reduce the data-intensiveness and complexity overload at critical decision points to a manageable level, thus permitting stakeholders to be more productive and concentrate on creative activities.

Novel techniques for automorphism group computation

Graph automorphism (GA) is a classical problem, in which the objective is to compute the automorphism group of an input graph. In this work we propose four novel techniques to speed up algorithms that solve the GA problem by exploring a search tree. They increase the performance of the algorithm by allowing to reduce the depth of the search tree, and by effectively pruning it. We formally prove that a GA algorithm that uses these techniques correctly computes the automorphism group of the input graph. We also describe how the techniques have been incorporated into the GA algorithm conauto, as conauto-2.03, with at most an additive polynomial increase in its asymptotic time complexity. We have experimentally evaluated the impact of each of the above techniques with several graph families. We have observed that each of the techniques by itself significantly reduces the number of processed nodes of the search tree in some subset of graphs, which justifies the use of each of them. Then, when they are applied together, their effect is combined, leading to reductions in the number of processed nodes in most graphs. This is also reflected in a reduction of the running time, which is substantial in some graph families.

Contribution to Load-Frequency Regulation of a Hydropower Plant with Long Tail-Race Tunnel

In this paper, a hydroelectric power plant with long tail-race tunnel has been modelled for assessing its contribution to secondary regulation reserve. Cavitation problems, caused by the discharge conduit length, are expected downstream the turbine where low pressure appears during regulation manoeuvres. Therefore, governor's gains should be selected taking into account these phenomena. On the other hand, regulation services bidden by the plant operator should fulfil TSO (Transmission System Operator) quality requirements. A methodology for tuning governor PI gains is proposed and applied to a Hydro power plant in pre-design phase in northwest area of Spain. The PI gains adjustment proposed provides a proper plant response, according to some established indexes, while avoiding cavitation phenomena.

Towards a Flexible Internet Transport Layer Architecture

LANMAN 2016, Rome This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 644334 (NEAT). The views expressed are solely those of the authors.

Editori di Quaracchi : 100 anni dopo bilancio e prospettive : atti del colloquio internazionale, Roma 29-30 maggio 1995 : Scuola superiore de studi medievali e francescani, Pontificio Ateneo Antonianum /

Includes bibliographical references and indexes.

Relazione del pio istituto di S. Michele a Ripa Grande, eretto dalla santa memoria di PP. Innocenzo XII.

Preface signed: Giuseppe Vai, segretario e prelato deputato.