Time-domain optimization of amplifiers based on distributed genetic algorithms

Thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Electrical and Computer Engineering

Parallel GPU architecture for hyperspectral unmixing based on augmented Lagrangian method

Hyperspectral imaging has become one of the main topics in remote sensing applications, which comprise hundreds of spectral bands at different (almost contiguous) wavelength channels over the same area generating large data volumes comprising several GBs per flight. This high spectral resolution can be used for object detection and for discriminate between different objects based on their spectral characteristics. One of the main problems involved in hyperspectral analysis is the presence of mixed pixels, which arise when the spacial resolution of the sensor is not able to separate spectrally distinct materials. Spectral unmixing is one of the most important task for hyperspectral data exploitation. However, the unmixing algorithms can be computationally very expensive, and even high power consuming, which compromises the use in applications under on-board constraints. In recent years, graphics processing units (GPUs) have evolved into highly parallel and programmable systems. Specifically, several hyperspectral imaging algorithms have shown to be able to benefit from this hardware taking advantage of the extremely high floating-point processing performance, compact size, huge memory bandwidth, and relatively low cost of these units, which make them appealing for onboard data processing. In this paper, we propose a parallel implementation of an augmented Lagragian based method for unsupervised hyperspectral linear unmixing on GPUs using CUDA. The method called simplex identification via split augmented Lagrangian (SISAL) aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The efficient implementation of SISAL method presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory.

Intelligent Remuneration and Tariffs for Virtual Power Players

Power systems have been through deep changes in recent years, namely due to the operation of competitive electricity markets in the scope the increasingly intensive use of renewable energy sources and distributed generation. This requires new business models able to cope with the new opportunities that have emerged. Virtual Power Players (VPPs) are a new type of player that allows aggregating a diversity of players (Distributed Generation (DG), Storage Agents (SA), Electrical Vehicles (V2G) and consumers) to facilitate their participation in the electricity markets and to provide a set of new services promoting generation and consumption efficiency, while improving players’ benefits. A major task of VPPs is the remuneration of generation and services (maintenance, market operation costs and energy reserves), as well as charging energy consumption. This paper proposes a model to implement fair and strategic remuneration and tariff methodologies, able to allow efficient VPP operation and VPP goals accomplishment in the scope of electricity markets.

Constrained Consumption Shifting Management in the Distributed Energy Resources Scheduling Considering Demand Response

Demand response concept has been gaining increasing importance while the success of several recent implementations makes this resource benefits unquestionable. This happens in a power systems operation environment that also considers an intensive use of distributed generation. However, more adequate approaches and models are needed in order to address the small size consumers and producers aggregation, while taking into account these resources goals. The present paper focuses on the demand response programs and distributed generation resources management by a Virtual Power Player that optimally aims to minimize its operation costs taking the consumption shifting constraints into account. The impact of the consumption shifting in the distributed generation resources schedule is also considered. The methodology is applied to three scenarios based on 218 consumers and 4 types of distributed generation, in a time frame of 96 periods.

A study on parallel versus sequential relational fuzzy clustering methods

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Distributed Sensing of Fluid Dynamic Phenomena with the XDense Sensor Grid Network

IEEE International Conference on Cyber Physical Systems, Networks and Applications (CPSNA'15), Hong Kong, China.

XDense: A Dense Grid Sensor Network for Distributed Feature Extraction

XXXIII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos (SBRC 2015). 15 to 19, May, 2015, III Workshop de Comunicação em Sistemas Embarcados Críticos. Vitória, Brasil.

Semi-Partitioned Scheduling of Fork-Join Tasks using Work-Stealing

13th IEEE/IFIP International Conference on Embedded and Ubiquitous Computing (EUC 2015). 21 to 23, Oct, 2015, Session W1-A: Multiprocessing and Multicore Architectures. Porto, Portugal.

Quality-of-service aware routing for static and mobile IPv6-based low-power and lossy sensor networks using RPL

The Internet of Things (IoT) has emerged as a paradigm over the last few years as a result of the tight integration of the computing and the physical world. The requirement of remote sensing makes low-power wireless sensor networks one of the key enabling technologies of IoT. These networks encompass several challenges, especially in communication and networking, due to their inherent constraints of low-power features, deployment in harsh and lossy environments, and limited computing and storage resources. The IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) [1] was proposed by the IETF ROLL (Routing Over Low-power Lossy links) working group and is currently adopted as an IETF standard in the RFC 6550 since March 2012. Although RPL greatly satisfied the requirements of low-power and lossy sensor networks, several issues remain open for improvement and specification, in particular with respect to Quality of Service (QoS) guarantees and support for mobility. In this paper, we focus mainly on the RPL routing protocol. We propose some enhancements to the standard specification in order to provide QoS guarantees for static as well as mobile LLNs. For this purpose, we propose OF-FL (Objective Function based on Fuzzy Logic), a new objective function that overcomes the limitations of the standardized objective functions that were designed for RPL by considering important link and node metrics, namely end-to-end delay, number of hops, ETX (Expected transmission count) and LQL (Link Quality Level). In addition, we present the design of Co-RPL, an extension to RPL based on the corona mechanism that supports mobility in order to overcome the problem of slow reactivity to frequent topology changes and thus providing a better quality of service mainly in dynamic networks application. Performance evaluation results show that both OF-FL and Co-RPL allow a great improvement when compared to the standard specification, mainly in terms of packet loss ratio and average network latency. 2015 Elsevier B.V. Al

Personalization platform for multimodal ubiquitous computing applications

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Reflux esophagitis and gastroesophageal reflux disease: a cross-sectional study of gastroesophageal reflux disease patients by age group

The purpose of this study was to explore the relationship between the intensity of acid reflux and severity of esophageal tissue damage in a cross-sectional study of patients with gastroesophageal reflux disease (GERD). Seventy-eight patients with were selected in accordance with the strict 24-hour ambulatory esophageal pHmetry (24h-pHM) criteria and distributed into three age groups: Group A: 14 - 24 years of age. Group B: 25 - 54; and Group C: 55 - 64. The 24h-pHM was carried out in accordance with DeMeester standardization, and the Savary-Miller classification for the diagnosis of reflux esophagitis was used. The groups were similar in 24h-pHM parameters (p > 0.05), having above normal values. For the study group as a whole, there was no correlation between age group and intensity of acid reflux, and there was no correlation between intensity of acid reflux and severity of esophageal tissue damage. However, when the same patients were sub-grouped in accordance with the depth of their epithelial injury and then distributed into age groups, there was a significant difference in esophagitis without epithelial discontinuity. Younger patients had less epithelial damage than older patients. Additionally, although there was a significant progression from the least severe to the moderate stages of epithelial damage among the age groups, there was no apparent difference among the age groups in the distribution between the moderate stages and most severe stages. The findings support the conclusion that the protective response of individuals to acid reflux varies widely. Continued aggression by acid reflux appears to lead to the exhaustion of individual mechanisms of epithelial protection in some patients, but not others, regardless of age or duration of the disease. Therefore, the diagnosis and follow-up of GERD should include both measurements of the quantity of refluxed acid and an assessment of the damage to the esophageal epithelium.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational intelligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two illustrative Traffic Engineering methods are described, allowing to attain routing configurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.

Psychosocial adjustment and physical health in children of divorce

Objective: To review the literature on the effects of parental divorce over the psychological maladjustment and physical health problems in children of divorced parents, thus contributing to the integration of existing scientific knowledge based on the biopsychosocial model of the impact of divorce on children’s physical health as proposed by Troxel and Matthews (2004). Sources: Review of the literature using MEDLINE and PsycInfo (1980-2007) databases, selecting the most representative articles on the subject. Special attention was paid to contributions by internationally renowned investigators on the subject. Summary of the findings: Divorce may be responsible for a decline of physical and psychological health in children. The developmental maladjustment of children is not triggered by divorce itself, but rather by other risk factors associated with it, such as interparental conflict, parental psychopathology, decline in socio-economic level, inconsistency in parenting styles, a parallel and conflicting co-parenting relationship between parents and low levels of social support. Such risk factors trigger maladjusted developmental pathways, marked by psychopathological symptoms, poor academic performance, worst levels of physical health, risk behavior, exacerbated psychophysiological responses to stress and weakening of the immune system. Conclusions: Clear links were observed between experiencing parental divorce and facing problems of physical and psychological maladjustment in children. Divorce is a stressor that should be considered by health professionals as potentially responsible for maladjusted neuropsychobiological responses and for decline in children’s physical health.

Càlcul distribuït en BOINC per el trencament de l'algorisme RC5

Aquest projecte té com a objectiu participar en el desafiament d'RSA Laboratories corresponent a trencar el criptosistema RC5-32-12-9 proposat. Per realitzar-ho s'ha triat realitzar un atac per força bruta, mitjançant el càlcul distribuït i, més concretament, utilitzant la Public Resource Computing. La plataforma escollida és la Berkeley Open Infrastructure for Network Computing (BOINC), coneguda per la seva utilització en grans projectes com ara SETI@home. En aquest projecte es posa en funcionament la infraestructura i es desenvolupen les aplicacions necessàries per iniciar els càlculs que haurien de permetre el trencament del criptosistema.

Alineamiento múltiple de secuencias con T-Coffee: una aproximación paralela

Las aplicaciones de alineamiento múltiple de secuencias son prototipos de aplicaciones que requieren elevada potencia de cómputo y memoria. Se destacan por la relevancia científica que tienen los resultados que brindan a investigaciones científicas en el campo de la biomedicina, genética y farmacología. Las aplicaciones de alineamiento múltiple tienen la limitante de que no son capaces de procesar miles de secuencias, por lo que se hace necesario crear un modelo para resolver la problemática. Analizando el volumen de datos que se manipulan en el área de las ciencias biológica y la complejidad de los algoritmos de alineamiento de secuencias, la única vía de solución del problema es a través de la utilización de entornos de cómputo paralelos y la computación de altas prestaciones. La investigación realizada por nosotros tiene como objetivo la creación de un modelo paralelo que le permita a los algoritmos de alineamiento múltiple aumentar el número de secuencias a procesar, tratando de mantener la calidad en los resultados para garantizar la precisión científica. El modelo que proponemos emplea como base la clusterización de las secuencias de entrada utilizando criterios biológicos que permiten mantener la calidad de los resultados. Además, el modelo se enfoca en la disminución del tiempo de cómputo y consumo de memoria. Para presentar y validar el modelo utilizamos T-Coffee, como plataforma de desarrollo e investigación. El modelo propuesto pudiera ser aplicado a cualquier otro algoritmo de alineamiento múltiple de secuencias.