Low-Complexity and Robust Hybrid Beamforming Design for Multi-Antenna Communication Systems

This paper proposes a low-complexity hybrid beamforming design for multi-antenna communication systems. The hybrid beamformer is comprised of a baseband digital beamformer and a constant modulus analog beamformer in the radio frequency (RF) part of the system. As in singular-value-decomposition (SVD)-based beamforming, hybrid beamforming design aims to generate parallel data streams in multi-antenna systems, however, due to the constant modulus constraint of the analog beamformer, the problem cannot be solved similarly. To address this problem, mathematical expressions of the parallel data streams are derived in this paper and desired and interfering signals are specified per stream. The analog beamformers are designed by maximizing the power of desired signal while minimizing the sum-power of interfering signals. Finally, digital beamformers are derived by defining the equivalent channel observed by the transmitter/receiver. Regardless of the number of the antennas or type of channel, the proposed approach can be applied to a wide range of MIMO systems with hybrid structure wherein the number of the antennas is more than the number of the RF chains. In particular, the proposed algorithm is verified for sparse channels that emulate mm-wave transmission as well as rich scattering environments. In order to validate the optimality, the results are compared with those of the state-of-the-art and it is demonstrated that the performance of the proposed method outperforms state-of-the-art techniques, regardless of type of the channel and/or system configuration

PREDON Scientific Data Preservation 2014

LPSC14037Scientific data collected with modern sensors or dedicated detectors exceed very often the perimeter of the initial scientific design. These data are obtained more and more frequently with large material and human efforts. A large class of scientific experiments are in fact unique because of their large scale, with very small chances to be repeated and to superseded by new experiments in the same domain: for instance high energy physics and astrophysics experiments involve multi-annual developments and a simple duplication of efforts in order to reproduce old data is simply not affordable. Other scientific experiments are in fact unique by nature: earth science, medical sciences etc. since the collected data is "time-stamped" and thereby non-reproducible by new experiments or observations. In addition, scientific data collection increased dramatically in the recent years, participating to the so-called "data deluge" and inviting for common reflection in the context of "big data" investigations. The new knowledge obtained using these data should be preserved long term such that the access and the re-use are made possible and lead to an enhancement of the initial investment. Data observatories, based on open access policies and coupled with multi-disciplinary techniques for indexing and mining may lead to truly new paradigms in science. It is therefore of outmost importance to pursue a coherent and vigorous approach to preserve the scientific data at long term. The preservation remains nevertheless a challenge due to the complexity of the data structure, the fragility of the custom-made software environments as well as the lack of rigorous approaches in workflows and algorithms. To address this challenge, the PREDON project has been initiated in France in 2012 within the MASTODONS program: a Big Data scientific challenge, initiated and supported by the Interdisciplinary Mission of the National Centre for Scientific Research (CNRS). PREDON is a study group formed by researchers from different disciplines and institutes. Several meetings and workshops lead to a rich exchange in ideas, paradigms and methods. The present document includes contributions of the participants to the PREDON Study Group, as well as invited papers, related to the scientific case, methodology and technology. This document should be read as a "facts finding" resource pointing to a concrete and significant scientific interest for long term research data preservation, as well as to cutting edge methods and technologies to achieve this goal. A sustained, coherent and long term action in the area of scientific data preservation would be highly beneficial

CityIOT: Air quality in the city supported by an IoT ecosystem

Air pollution is a worldwide problem, which affects millions of people and can have serious consequences for public health, economy and for social issues. Constant emissions of gaseous pollutants, as a result of industrial operations, combustion of fossil fuels and forest fires, affect air quality and contribute to an increase in this type of pollution. Internet of Things (IoT) has emerged as a response to the creation of intelligent monitoring systems that can be used for management and identification of pollution sources, and for health protection. The development of new equipment and communication technologies has allowed the creation of real-time air quality monitoring applications. This dissertation presents an implementation of an IoT system for monitoring outdoor air quality, based on a multisensory system with LoRa communication capabilities. The system incorporates low-cost sensors capable of detecting different air pollutants, as well as atmospheric parameters, such as temperature and relative humidity. To achieve a long-distance transmission of readings with low energy consumption, the use of LoRa technology was adopted. The frequency of sending readings to the network is based on the level of urban traffic in a certain location. Furthermore, a web/mobile application is presented, which allows the user to monitor in real time and to carry out a temporal analysis of the measurements taken by the system.A poluição do ar representa um problema global, que afeta milhões de pessoas, podendo trazer graves consequências para a saúde pública, para a economia e também sociais. A constante emissão de poluentes em estado gasoso, resultante de operações industriais, combustão de combustíveis fósseis e fogos florestais, afetam a qualidade do ar e contribuem para o aumento deste tipo de poluição. A Internet das Coisas (IoT) emergiu como resposta para a criação de sistemas inteligentes de monitorização que podem ser usados para a gestão e identificação de fontes de poluição e para a proteção da saúde pública. O desenvolvimento de novos equipamentos e tecnologias de comunicação, têm vindo a permitir a criação de aplicações de monitorização da qualidade do ar, em tempo real. Esta dissertação apresenta uma implementação de um sistema IoT de monitorização de qualidade do ar exterior, baseado num sistema multisensor com capacidade de comunicação LoRa. O sistema incorpora sensores de baixo custo capazes de detetar diferentes poluentes atmosféricos, como também parâmetros atmosféricos, como temperatura e humidade relativa. De modo a ser obtida uma transmissão de leituras em longa distância e com baixo consumo energético, o uso da tecnologia LoRa foi adotado. A frequência do envio de leituras para a rede, é feita com base no nível de tráfego urbano, numa certa localização. Ainda é apresentada uma aplicação web/móvel, que permite ao utilizador acompanhar em tempo real e proceder a uma análise temporal, das medições efetuadas pelo sistema

Coronectomy of deeply impacted lower third molar : incidence of outcomes and complications after one year follow-up

Objectives: The purpose of present study was to assess the surgical management of impacted third molar with proximity to the inferior alveolar nerve and complications associated with coronectomy in a series of patients undergoing third molar surgery. Material and Methods: The position of the mandibular canal in relation to the mandibular third molar region and mandibular foramen in the front part of the mandible (i.e., third molar in close proximity to the inferior alveolar nerve [IAN] or not) was identified on panoramic radiographs of patients scheduled for third molar extraction. Results: Close proximity to the IAN was observed in 64 patients (35 females, 29 males) with an impacted mandibular third molar. Coronectomy was performed in these patients. The most common complication was tooth migration away from the mandibular canal (n = 14), followed by root exposure (n = 5). Re-operation to remove the root was performed in cases with periapical infection and root exposure. Conclusions: The results indicate that coronectomy can be considered a reasonable and safe treatment alternative for patients who demonstrate elevated risk for injury to the inferior alveolar nerve with removal of the third molars. Coronectomy did not increase the incidence of damage to the inferior alveolar nerve and would be safer than complete extraction in situations in which the root of the mandibular third molar overlaps or is in close proximity to the mandibular canal

Resource discovery for distributed computing systems: A comprehensive survey

Large-scale distributed computing environments provide a vast amount of heterogeneous computing resources from different sources for resource sharing and distributed computing. Discovering appropriate resources in such environments is a challenge which involves several different subjects. In this paper, we provide an investigation on the current state of resource discovery protocols, mechanisms, and platforms for large-scale distributed environments, focusing on the design aspects. We classify all related aspects, general steps, and requirements to construct a novel resource discovery solution in three categories consisting of structures, methods, and issues. Accordingly, we review the literature, analyzing various aspects for each category