Digitally programmable delay-locked-loop with adaptive charge pump current for UWB radar system

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e Computadores

Comparative analysis of time-frequency methods estimating the time-varying microstructure of sleep EEG spindles

Proceedings of the Information Technology Applications in Biomedicine, Ioannina - Epirus, Greece, October 26-28, 2006

On performance of distributed model predictive control in power system frequency regulation

This paper describes the implementation of a distributed model predictive approach for automatic generation control. Performance results are discussed by comparing classical techniques (based on integral control) with model predictive control solutions (centralized and distributed) for different operational scenarios with two interconnected networks. These scenarios include variable load levels (ranging from a small to a large unbalance generated power to power consumption ratio) and simultaneously variable distance between the interconnected networks systems. For the two networks the paper also examines the impact of load variation in an island context (a network isolated from each other).

Adaptive learning in agents behaviour: A framework for electricity markets simulation

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. This paper presents a methodology to provide decision support to electricity market negotiating players. This model allows integrating different strategic approaches for electricity market negotiations, and choosing the most appropriate one at each time, for each different negotiation context. This methodology is integrated in ALBidS (Adaptive Learning strategic Bidding System) – a multiagent system that provides decision support to MASCEM's negotiating agents so that they can properly achieve their goals. ALBidS uses artificial intelligence methodologies and data analysis algorithms to provide effective adaptive learning capabilities to such negotiating entities. The main contribution is provided by a methodology that combines several distinct strategies to build actions proposals, so that the best can be chosen at each time, depending on the context and simulation circumstances. The choosing process includes reinforcement learning algorithms, a mechanism for negotiating contexts analysis, a mechanism for the management of the efficiency/effectiveness balance of the system, and a mechanism for competitor players' profiles definition.

Low frequency of TERT promoter mutations in gastrointestinal stromal tumors (GISTs)

Somatic mutations in the promoter region of telomerase reverse transcriptase (TERT) gene, mainly at positions c.-124 and c.-146 bp, are frequent in several human cancers; yet its presence in gastrointestinal stromal tumor (GIST) has not been reported to date. Herein, we searched for the presence and clinicopathological association of TERT promoter mutations in genomic DNA from 130 bona fide GISTs. We found TERT promoter mutations in 3.8% (5/130) of GISTs. The c.-124C>T mutation was the most common event, present in 2.3% (3/130), and the c.-146C>T mutation in 1.5% (2/130) of GISTs. No significant association was observed between TERT promoter mutation and patient's clinicopathological features. The present study establishes the low frequency (4%) of TERT promoter mutations in GISTs. Further studies are required to confirm our findings and to elucidate the hypothetical biological and clinical impact of TERT promoter mutation in GIST pathogenesis.

Additive adaptive thinking in 1st and 2nd grades pupils

This paper is part of the Project “Adaptive thinking and flexible computation: Critical issues”. It discusses what is meant by adaptive thinking and presents the results of individual interviews with four pupils. The main goal of the study is to understand pupils’ reasoning when solving numerical tasks involving additive situations, and identify features associated with adaptive thinking. The results show that, in the case of first grade pupils, the semantic aspects of the problem are involved in its resolution and the pupils’ performance appears to be related to the development of number sense. The 2nd grade pupils seem to see the quantitative difference as an invariant numerical relationship.

The frequency of blood-born viral infections in a population of multitransfused Brazilian patients

The frequency of viral markers for hepatitis B (HBV) and C (HCV), human immunodeficiency virus-1 (HIV-1) and human T-lymphotropic virus-1 (HTLV-1) was evaluated in 32 Brazilian ß-thalassemia multitransfused patients. Additionaly the serum concentrations of ferritin and alanine aspartate transaminase (ALAT) were determined. The results show a high prevalence of markers of infection by HBV (25.0%) and HCV (46.8%) and a low prevalence of markers for HIV-1 and HTLV-1. No correlations were demonstrated between the presence of the hepatitis markers and the number of units transfused or the serum concentrations of ferritin and ALAT.

Complementary filter design with three frequency bands: robot attitude estimation

This paper extents the by now classic sensor fusion complementary filter (CF) design, involving two sensors, to the case where three sensors that provide measurements in different bands are available. This paper shows that the use of classical CF techniques to tackle a generic three sensors fusion problem, based solely on their frequency domain characteristics, leads to a minimal realization, stable, sub-optimal solution, denoted as Complementary Filters3 (CF3). Then, a new approach for the estimation problem at hand is used, based on optimal linear Kalman filtering techniques. Moreover, the solution is shown to preserve the complementary property, i.e. the sum of the three transfer functions of the respective sensors add up to one, both in continuous and discrete time domains. This new class of filters are denoted as Complementary Kalman Filters3 (CKF3). The attitude estimation of a mobile robot is addressed, based on data from a rate gyroscope, a digital compass, and odometry. The experimental results obtained are reported.

Establishment of optimal physical assets inspection frequency based on risk principles

Risk Based Inspection (RBI) is a risk methodology used as the basis for prioritizing and managing the efforts for an inspection program allowing the allocation of resources to provide a higher level of coverage on physical assets with higher risk. The main goal of RBI is to increase equipment availability while improving or maintaining the accepted level of risk. This paper presents the concept of risk, risk analysis and RBI methodology and shows an approach to determine the optimal inspection frequency for physical assets based on the potential risk and mainly on the quantification of the probability of failure. It makes use of some assumptions in a structured decision making process. The proposed methodology allows an optimization of inspection intervals deciding when the first inspection must be performed as well as the subsequent intervals of inspection. A demonstrative example is also presented to illustrate the application of the proposed methodology.

An adaptive IoT management infrastructure for eco transport networks

The complexity associated with fast growing of B2B and the lack of a (complete) suite of open standards makes difficulty to maintain the underlying collaborative processes. Aligned to this challenge, this paper aims to be a contribution to an open architecture of logistics and transport processes management system. A model of an open integrated system is being defined as an open computational responsibility from the embedded systems (on-board) as well as a reference implementation (prototype) of a host system to validate the proposed open interfaces. Embedded subsystem can, natively, be prepared to cooperate with other on-board units and with IT-systems in an infrastructure commonly referred to as a center information system or back-office. In interaction with a central system the proposal is to adopt an open framework for cooperation where the embedded unit or the unit placed somewhere (land/sea) interacts in response to a set of implemented capabilities.

Estimation of rotational frequency response functions

As it is widely known, in structural dynamic applications, ranging from structural coupling to model updating, the incompatibility between measured and simulated data is inevitable, due to the problem of coordinate incompleteness. Usually, the experimental data from conventional vibration testing is collected at a few translational degrees of freedom (DOF) due to applied forces, using hammer or shaker exciters, over a limited frequency range. Hence, one can only measure a portion of the receptance matrix, few columns, related to the forced DOFs, and rows, related to the measured DOFs. In contrast, by finite element modeling, one can obtain a full data set, both in terms of DOFs and identified modes. Over the years, several model reduction techniques have been proposed, as well as data expansion ones. However, the latter are significantly fewer and the demand for efficient techniques is still an issue. In this work, one proposes a technique for expanding measured frequency response functions (FRF) over the entire set of DOFs. This technique is based upon a modified Kidder's method and the principle of reciprocity, and it avoids the need for modal identification, as it uses the measured FRFs directly. In order to illustrate the performance of the proposed technique, a set of simulated experimental translational FRFs is taken as reference to estimate rotational FRFs, including those that are due to applied moments.

Adaptive Learning in Games: Defining Profiles of Competitor Players

Artificial Intelligence has been applied to dynamic games for many years. The ultimate goal is creating responses in virtual entities that display human-like reasoning in the definition of their behaviors. However, virtual entities that can be mistaken for real persons are yet very far from being fully achieved. This paper presents an adaptive learning based methodology for the definition of players’ profiles, with the purpose of supporting decisions of virtual entities. The proposed methodology is based on reinforcement learning algorithms, which are responsible for choosing, along the time, with the gathering of experience, the most appropriate from a set of different learning approaches. These learning approaches have very distinct natures, from mathematical to artificial intelligence and data analysis methodologies, so that the methodology is prepared for very distinct situations. This way it is equipped with a variety of tools that individually can be useful for each encountered situation. The proposed methodology is tested firstly on two simpler computer versus human player games: the rock-paper-scissors game, and a penalty-shootout simulation. Finally, the methodology is applied to the definition of action profiles of electricity market players; players that compete in a dynamic game-wise environment, in which the main goal is the achievement of the highest possible profits in the market.

Relative Frequency of Nosocomial Microorganisms at Unicamp University Hospital from 1987 to 1994

The frequency of microorganisms identified in nosocomial infections at Unicamp University Hospital from 1987 to 1994 was analysed. The most common microorganism was S. aureus (20.9%), which was found in surgical wound, bloodstream and arterial-venous infections. In urinary tract infections (UTI), gram-negative rods (56.5%) and yeasts (9%) predominated. A. baumannii isolates were observed to have increased in the last three years. There was a gradual increase in the frequency of coagulase-negative staphylococci and A. baumannii in bloodstream infections but there wasn’t any change in Candida sp

Frequency of dermatophytes in the metropolitan area of Porto Alegre, RS, Brazil

In order to evaluate the distribution of dermatophytes in Porto Alegre, the capital of the state of Rio Grande do Sul, Brazil, they were isolated from the skin, hairs and nails samples and retrospectively analyzed from June 1981 to June 1995, in two different institutions in the city of Porto Alegre: (i) the Serviço de Micologia do Instituto de Pesquisas Biológicas Jandyr Maya Faillace, da Secretaria de Saúde e Meio Ambiente do Rio Grande do Sul which attends the low income population (low and middle classes) and, (ii) Laboratório Weinmann, a clinical pathology laboratory which attends predominantly the higher income population (middle and upper classes), both which attend in the metropolitan area of Porto Alegre. The dermatophyte predominance of Trichophyton rubrum was confirmed (55.33%) followed by T. mentagrophytes (21.46%). The data obtained were compared with the existing prevalence data which were collected in the interior of the state over a period of 32 years (1960-1992). T. verrucosum, T. simii, Microsporum persicolor, T. schöenleinii, M. nanum and M. cookei were isolated in the interior and have not been found in the capital so far. On the other side, T. violaceum was, isolated in the capital and has not been found in the interior so far.