Opportunistic packet scheduling in body area networks

Significant research efforts are being devoted to Body Area Networks (BAN) due to their potential for revolutionizing healthcare practices. Energy-efficiency and communication reliability are critically important for these networks. In an experimental study with three different mote platforms, we show that changes in human body shadowing as well as those in the relative distance and orientation of nodes caused by the common human body movements can result in significant fluctuations in the received signal strength within a BAN. Furthermore, regular movements, such as walking, typically manifest in approximately periodic variations in signal strength. We present an algorithm that predicts the signal strength peaks and evaluate it on real-world data. We present the design of an opportunistic MAC protocol, named BANMAC, that takes advantage of the periodic fluctuations of the signal strength to achieve high reliability even with low transmission power.

F-LQE: a Fuzzy Link Quality Estimator for wireless sensor networks

Radio Link Quality Estimation (LQE) is a fundamental building block for Wireless Sensor Networks, namely for a reliable deployment, resource management and routing. Existing LQEs (e.g. PRR, ETX, Fourbit, and LQI ) are based on a single link property, thus leading to inaccurate estimation. In this paper, we propose F-LQE, that estimates link quality on the basis of four link quality properties: packet delivery, asymmetry, stability, and channel quality. Each of these properties is defined in linguistic terms, the natural language of Fuzzy Logic. The overall quality of the link is specified as a fuzzy rule whose evaluation returns the membership of the link in the fuzzy subset of good links. Values of the membership function are smoothed using EWMA filter to improve stability. An extensive experimental analysis shows that F-LQE outperforms existing estimators.

Incremental filter and wrapper approaches for feature discretization

Discrete data representations are necessary, or at least convenient, in many machine learning problems. While feature selection (FS) techniques aim at finding relevant subsets of features, the goal of feature discretization (FD) is to find concise (quantized) data representations, adequate for the learning task at hand. In this paper, we propose two incremental methods for FD. The first method belongs to the filter family, in which the quality of the discretization is assessed by a (supervised or unsupervised) relevance criterion. The second method is a wrapper, where discretized features are assessed using a classifier. Both methods can be coupled with any static (unsupervised or supervised) discretization procedure and can be used to perform FS as pre-processing or post-processing stages. The proposed methods attain efficient representations suitable for binary and multi-class problems with different types of data, being competitive with existing methods. Moreover, using well-known FS methods with the features discretized by our techniques leads to better accuracy than with the features discretized by other methods or with the original features. (C) 2013 Elsevier B.V. All rights reserved.

Light-activated amplification in SiC Tandem devices: A capacitive active filter model

Characteristics of tunable wavelength pi'n/pin filters based on a-SiC:H multilayered stacked cells are studied both experimentally and theoretically. Results show that the device combines the demultiplexing operation with the simultaneous photodetection and self amplification of the signal. An algorithm to decode the multiplex signal is established. A capacitive active band-pass filter model is presented and supported by an electrical simulation of the state variable filter circuit. Experimental and simulated results show that the device acts as a state variable filter. It combines the properties of active high-pass and low-pass filter sections into a capacitive active band-pass filter using a changing capacitance to control the power delivered to the load.

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.

Anti-phenolic glycolipid-I (PGL-I) determination using blood collection on filter paper in leprosy patients

The authors studied 70 leprosy patients and 20 normal individuals, comparing the traditional sera collection method and the finger prick blood with the conservation on filter paper for specific antibodies against the native phenolic glycolipid-I (PGL-I) from Mycobacterium leprae. The finger prick blood dried on filter paper was eluated in phosphate buffer saline (PBS) containing 0.5% gelatin. The classical method for native PGL-I was performed for these eluates, and compared with the antibody determination for sera. It was observed that there is a straight correlation comparing these two methods; although the titles found for the eluates were lower than those obtained for serology. This blood collection method could be useful for investigation of new leprosy cases in field, specially in contacts individuals.

A Random Access Protocol incorporating Multi-Packet Reception, Retransmission Diversity and Successive Interference Cancellation

8th International Workshop on Multiple Access Communications (MACOM2015), Helsinki, Finland.

A filter algorithm: comparison with NLP solvers

The purpose of this work is to present an algorithm to solve nonlinear constrained optimization problems, using the filter method with the inexact restoration (IR) approach. In the IR approach two independent phases are performed in each iteration—the feasibility and the optimality phases. The first one directs the iterative process into the feasible region, i.e. finds one point with less constraints violation. The optimality phase starts from this point and its goal is to optimize the objective function into the satisfied constraints space. To evaluate the solution approximations in each iteration a scheme based on the filter method is used in both phases of the algorithm. This method replaces the merit functions that are based on penalty schemes, avoiding the related difficulties such as the penalty parameter estimation and the non-differentiability of some of them. The filter method is implemented in the context of the line search globalization technique. A set of more than two hundred AMPL test problems is solved. The algorithm developed is compared with LOQO and NPSOL software packages.

A filter inexact-restoration method for nonlinear programming

A new iterative algorithm based on the inexact-restoration (IR) approach combined with the filter strategy to solve nonlinear constrained optimization problems is presented. The high level algorithm is suggested by Gonzaga et al. (SIAM J. Optim. 14:646–669, 2003) but not yet implement—the internal algorithms are not proposed. The filter, a new concept introduced by Fletcher and Leyffer (Math. Program. Ser. A 91:239–269, 2002), replaces the merit function avoiding the penalty parameter estimation and the difficulties related to the nondifferentiability. In the IR approach two independent phases are performed in each iteration, the feasibility and the optimality phases. The line search filter is combined with the first one phase to generate a “more feasible” point, and then it is used in the optimality phase to reach an “optimal” point. Numerical experiences with a collection of AMPL problems and a performance comparison with IPOPT are provided.

Inferior Vena Cava Filter Placement During Pregnancy: an Adjuvant Option When Medical Therapy Fails

The authors present a case of a 27-year-old multiparous woman, with multiple thrombophilia, whose pregnancy was complicated with deep venous thrombosis requiring placement of a vena cava filter. At 15th week of gestation, following an acute deep venous thrombosis of the right inferior limb, anticoagulant therapy with low-molecular-weight heparin (LMWH) was instituted without improvement in her clinical status. Subsequently, at 18 weeks of pregnancy, LMWH was switched to warfarin. At 30th week of gestation, the maintenance of high thrombotic risk was the premise for placement of an inferior vena cava filter for prophylaxis of pulmonary embolism during childbirth and postpartum. There were no complications and a vaginal delivery was accomplished at 37 weeks of gestation. Venal placement of inferior vena cava filters is an attractive option as prophylaxis for pulmonary embolism during pregnancy.

Evaluation of three different DNA extraction methods from blood samples collected in dried filter paper in Plasmodium subpatent infections from the Amazon region in Brazil

Asymptomatic Plasmodium infection is a new challenge for public health in the American region. The polymerase chain reaction (PCR) is the best method for diagnosing subpatent parasitemias. In endemic areas, blood collection is hampered by geographical distances and deficient transport and storage conditions of the samples. Because DNA extraction from blood collected on filter paper is an efficient method for molecular studies in high parasitemic individuals, we investigated whether the technique could be an alternative for Plasmodium diagnosis among asymptomatic and pauciparasitemic subjects. In this report we compared three different methods (Chelex®-saponin, methanol and TRIS-EDTA) of DNA extraction from blood collected on filter paper from asymptomatic Plasmodium-infected individuals. Polymerase chain reaction assays for detection of Plasmodium species showed the best results when the Chelex®-saponin method was used. Even though the sensitivity of detection was approximately 66% and 31% for P. falciparum and P. vivax, respectively, this method did not show the effectiveness in DNA extraction required for molecular diagnosis of Plasmodium. The development of better methods for extracting DNA from blood collected on filter paper is important for the diagnosis of subpatent malarial infections in remote areas and would contribute to establishing the epidemiology of this form of infection.

Three transducers for one photodetector: essays for optical communications

Dissertation presented to obtain the PhD degree in Electrical and Computer Engineering - Electronics

Multipath policy routing in packet switched networks

Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Structural time series models and the Kalman filter: A concise review

The continued increase in availability of economic data in recent years and, more importantly, the possibility to construct larger frequency time series, have fostered the use (and development) of statistical and econometric techniques to treat them more accurately. This paper presents an exposition of structural time series models by which a time series can be decomposed as the sum of a trend, seasonal and irregular components. In addition to a detailled analysis of univariate speci fications we also address the SUTSE multivariate case and the issue of cointegration. Finally, the recursive estimation and smoothing by means of the Kalman filter algorithm is described taking into account its different stages, from initialisation to parameter s estimation.