A spectrum-driven damage Identification technique : application and validation through the numerical simulation of the Z24 Bridge

The present paper focuses on a damage identification method based on the use of the second order spectral properties of the nodal response processes. The explicit dependence on the frequency content of the outputs power spectral densities makes them suitable for damage detection and localization. The well-known case study of the Z24 Bridge in Switzerland is chosen to apply and further investigate this technique with the aim of validating its reliability. Numerical simulations of the dynamic response of the structure subjected to different types of excitation are carried out to assess the variability of the spectrum-driven method with respect to both type and position of the excitation sources. The simulated data obtained from random vibrations, impulse, ramp and shaking forces, allowed to build the power spectrum matrix from which the main eigenparameters of reference and damage scenarios are extracted. Afterwards, complex eigenvectors and real eigenvalues are properly weighed and combined and a damage index based on the difference between spectral modes is computed to pinpoint the damage. Finally, a group of vibration-based damage identification methods are selected from the literature to compare the results obtained and to evaluate the performance of the spectral index.

Assessing the production of jet mix columns using alkali activated waste based on mechanical and financial performance and CO2 (eq) emissions

Recent research has proved the potential of alkaline activated fly-ash for soil stabilisation. However, such studies have not focused on the link between financial, mechanical and environmental aspects of this solution, but only on their absolute mechanical properties. The present paper characterises the mechanical behaviour of a large spectrum of activator-ash-soil combinations used to build jet mixing columns, analysing also the cost and CO2 (eq) emissions. The concern with these two vectors forced a decrease in the quantity of stabilising agent added to the soil, relatively to previous research, and the effects of such low quantities have not yet been published. However, the results clearly showed a significant improve in strength, still well above the average values expected when improving the stressstrain behaviour of a weak soil. Uniaxial compressive strength tests were used to assess the effects of the fly-ash percentage, the alkalieash ratio and the water content. The carbon calculator recently developed by the European Federation of Foundation Contractors and the Deep Foundations Institute was used to quantify the CO2 (eq) emissions associated with this technique. The financial cost was estimated based on the experience of a major Portuguese contractor. For comparison purposes, soil cement mixtures were also analysed, using similar conditions and tools used for the soil-ash analysis. Results showed that the cement and ash solutions are very similar in terms of overall performance, with some advantage of the former regarding financial cost, and a significant advantage of the latter regarding the CO2 (eq) emissions. This new grout, although it is in an embryonic stage, it has the potential for broader developments in the field.

A hybrid MAC Scheme to improve the transmission performance in body sensor networks

Wireless body sensor networks (WBSNs) constitute a key technology for closing the loop between patients and healthcare providers, as WBSNs provide sensing ability, as well as mobility and portability, essential characteristics for wide acceptance of wireless healthcare technology. However, one important and difficult aspect of WBSNs is to provide data transmissions with quality of service, among other factors due to the antennas being small size and placed close to the body. Such transmissions cannot be fully provided without the assumption of a MAC protocol that solves the problems of the medium sharing. A vast number of MAC protocols conceived for wireless networks are based on random or scheduled schemes. This paper studies firstly the suitability of two MAC protocols, one using CSMA and the other TDMA, to transmit directly to the base station the signals collected continuously from multiple sensor nodes placed on the human body. Tests in a real scenario show that the beaconed TDMA MAC protocol presents an average packet loss ratio lower than CSMA. However, the average packet loss ratio is above 1.0 %. To improve this performance, which is of vital importance in areas such as e-health and ambient assisted living, a hybrid TDMA/CSMA scheme is proposed and tested in a real scenario with two WBSNs and four sensor nodes per WBSN. An average packet loss ratio lower than 0.2 % was obtained with the hybrid scheme. To achieve this significant improvement, the hybrid scheme uses a lightweight algorithm to control dynamically the start of the superframes. Scalability and traffic rate variation tests show that this strategy allows approximately ten WBSNs operating simultaneously without significant performance degradation.

Quantifying, generating and mitigating radio interference in Low-Power Wireless Networks

Doctoral Programme in Telecommunication - MAP-tele

Quality of life assessment of patients with schizophrenic spectrum disorders from Psychosocial Care Centers

OBJECTIVE: Assessing the quality of life and the clinical and social-demographic factors associated in schizophrenic spectrum patients (ICD-10 F20-F29) attending CAPS at the programmatic area 3.0. METHODS: A cross-sectional study was carried out in a sample of schizophrenic spectrum patients who have been enrolled in 2008 in CAPS in programmatic area (AP) 3 at Rio de Janeiro city, using MINIPLUS to assess schizophrenia spectrum disorder and use of psychoactive substances, Positive and Negative Symptoms Scale (PANSS) to assess psychiatric symptoms and Quality of Life Scale (QLS-BR) to assess the quality of life. RESULTS: Seventy nine patients were included, of whom 74 (93.7%) presented some impairment in quality of life. The most frequently affected area was occupational performance. Variables that showed a significant association with severe impairment of quality of life were: marital status, race, occupation, who patients lived with, homelessness, having children, previous psychiatric hospitalization, negative symptoms and symptoms designated as not applicable (being characterized by a lack of typical positive and negative symptoms). CONCLUSION: The knowledge of these factors should be crucial to implement health policies and psychosocial rehabilitation programs focused on improving the quality of life of these patients.

Fatigue et réduction de la performance motrice chez le sportif, syndrome de surentraînement [Fatigue and reduction in motor performance in sportspeople or overtraining syndrome].

The main goal of training activities is to improve motor performance. After strenuous workouts, it is physiological to experience fatigue, which relieves within two weeks, and then induce an improvement in motor capacities. An overtraining syndrome is diagnosed when fatigue is postponed beyond two weeks, and affects mainly endurance athletes. It is a condition of chronic fatigue, underperformance and an increased vulnerability to infection leading to recurrent infections. The whole observed spectrum of symptoms is physiological, psychological, endocrinogical and immunological. All play a role in the failure to recover. Monitoring of athletes activities helps to prevent the syndrome with days with no sports. Rest, patience and empathy are the only ways of treatment options.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

Accelerated MR imaging with spread spectrum encoding

We advocate the use of a novel compressed sensing technique for accelerating the magnetic resonance image acquisition process, coined spread spectrum MR imaging or simply s2MRI. The method resides in pre-modulating the signal of interest by a linear chirp, resulting from the application of quadratic phase profiles, before random k-space under-sampling with uniform average density. The effectiveness of the procedure is theoretically underpinned by the optimization of the coherence between the sparsity and sensing bases. The application of the technique for single coil acquisitions is thoroughly studied by means of numerical simulations as well as phantom and in vivo experiments on a 7T scanner. The corresponding results suggest a favorable comparison with state-of-the-art variable density k-space under-sampling approaches.

Comprehensive evaluation of the IEEE 802.15.4 MAC layer performance with retransmissions

Supported by IEEE 802.15.4 standardization activities, embedded networks have been gaining popularity in recent years. The focus of this paper is to quantify the behavior of key networking metrics of IEEE 802.15.4 beacon-enabled nodes under typical operating conditions, with the inclusion of packet retransmissions. We corrected and extended previous analyses by scrutinizing the assumptions on which the prevalent Markovian modeling is generally based. By means of a comparative study, we singled out which of the assumptions impact each of the performance metrics (throughput, delay, power consumption, collision probability, and packet-discard probability). In particular, we showed that - unlike what is usually assumed - the probability that a node senses the channel busy is not constant for all the stages of the backoff procedure and that these differences have a noticeable impact on backoff delay, packet-discard probability, and power consumption. Similarly, we showed that - again contrary to common assumption - the probability of obtaining transmission access to the channel depends on the number of nodes that is simultaneously sensing it. We evidenced that ignoring this dependence has a significant impact on the calculated values of throughput and collision probability. Circumventing these and other assumptions, we rigorously characterize, through a semianalytical approach, the key metrics in a beacon-enabled IEEE 802.15.4 system with retransmissions.

Variability of voriconazole plasma levels measured by new high-performance liquid chromatography and bioassay methods.

Voriconazole (VRC) is a broad-spectrum antifungal triazole with nonlinear pharmacokinetics. The utility of measurement of voriconazole blood levels for optimizing therapy is a matter of debate. Available high-performance liquid chromatography (HPLC) and bioassay methods are technically complex, time-consuming, or have a narrow analytical range. Objectives of the present study were to develop new, simple analytical methods and to assess variability of voriconazole blood levels in patients with invasive mycoses. Acetonitrile precipitation, reverse-phase separation, and UV detection were used for HPLC. A voriconazole-hypersusceptible Candida albicans mutant lacking multidrug efflux transporters (cdr1Delta/cdr1Delta, cdr2Delta/cdr2Delta, flu1Delta/flu1Delta, and mdr1Delta/mdr1Delta) and calcineurin subunit A (cnaDelta/cnaDelta) was used for bioassay. Mean intra-/interrun accuracies over the VRC concentration range from 0.25 to 16 mg/liter were 93.7% +/- 5.0%/96.5% +/- 2.4% (HPLC) and 94.9% +/- 6.1%/94.7% +/- 3.3% (bioassay). Mean intra-/interrun coefficients of variation were 5.2% +/- 1.5%/5.4% +/- 0.9% and 6.5% +/- 2.5%/4.0% +/- 1.6% for HPLC and bioassay, respectively. The coefficient of concordance between HPLC and bioassay was 0.96. Sequential measurements in 10 patients with invasive mycoses showed important inter- and intraindividual variations of estimated voriconazole area under the concentration-time curve (AUC): median, 43.9 mg x h/liter (range, 12.9 to 71.1) on the first and 27.4 mg x h/liter (range, 2.9 to 93.1) on the last day of therapy. During therapy, AUC decreased in five patients, increased in three, and remained unchanged in two. A toxic encephalopathy probably related to the increase of the VRC AUC (from 71.1 to 93.1 mg x h/liter) was observed. The VRC AUC decreased (from 12.9 to 2.9 mg x h/liter) in a patient with persistent signs of invasive aspergillosis. These preliminary observations suggest that voriconazole over- or underexposure resulting from variability of blood levels might have clinical implications. Simple HPLC and bioassay methods offer new tools for monitoring voriconazole therapy.

Spread spectrum magnetic resonance imaging.

We propose a novel compressed sensing technique to accelerate the magnetic resonance imaging (MRI) acquisition process. The method, coined spread spectrum MRI or simply s(2)MRI, consists of premodulating the signal of interest by a linear chirp before random k-space under-sampling, and then reconstructing the signal with nonlinear algorithms that promote sparsity. The effectiveness of the procedure is theoretically underpinned by the optimization of the coherence between the sparsity and sensing bases. The proposed technique is thoroughly studied by means of numerical simulations, as well as phantom and in vivo experiments on a 7T scanner. Our results suggest that s(2)MRI performs better than state-of-the-art variable density k-space under-sampling approaches.

Parallelizing remote sensing image geometric correction

Remote sensing spatial, spectral, and temporal resolutions of images, acquired over a reasonably sized image extent, result in imagery that can be processed to represent land cover over large areas with an amount of spatial detail that is very attractive for monitoring, management, and scienti c activities. With Moore's Law alive and well, more and more parallelism is introduced into all computing platforms, at all levels of integration and programming to achieve higher performance and energy e ciency. Being the geometric calibration process one of the most time consuming processes when using remote sensing images, the aim of this work is to accelerate this process by taking advantage of new computing architectures and technologies, specially focusing in exploiting computation over shared memory multi-threading hardware. A parallel implementation of the most time consuming process in the remote sensing geometric correction has been implemented using OpenMP directives. This work compares the performance of the original serial binary versus the parallelized implementation, using several multi-threaded modern CPU architectures, discussing about the approach to nd the optimum hardware for a cost-e ective execution.

A multi-center study: intra-scan and inter-scan variability of diffusion spectrum imaging.

The objective of this study was to investigate whether it is possible to pool together diffusion spectrum imaging data from four different scanners, located at three different sites. Two of the scanners had identical configuration whereas two did not. To measure the variability, we extracted three scalar maps (ADC, FA and GFA) from the DSI and utilized a region and a tract-based analysis. Additionally, a phantom study was performed to rule out some potential factors arising from the scanner performance in case some systematic bias occurred in the subject study. This work was split into three experiments: intra-scanner reproducibility, reproducibility with twin-scanner settings and reproducibility with other configurations. Overall for the intra-scanner and twin-scanner experiments, the region-based analysis coefficient of variation (CV) was in a range of 1%-4.2% and below 3% for almost every bundle for the tract-based analysis. The uncinate fasciculus showed the worst reproducibility, especially for FA and GFA values (CV 3.7-6%). For the GFA and FA maps, an ICC value of 0.7 and above is observed in almost all the regions/tracts. Looking at the last experiment, it was found that there is a very high similarity of the outcomes from the two scanners with identical setting. However, this was not the case for the two other imagers. Given the fact that the overall variation in our study is low for the imagers with identical settings, our findings support the feasibility of cross-site pooling of DSI data from identical scanners.

Evaluating effects of spectral training data distribution on continuous field mapping performance

Continuous field mapping has to address two conflicting remote sensing requirements when collecting training data. On one hand, continuous field mapping trains fractional land cover and thus favours mixed training pixels. On the other hand, the spectral signature has to be preferably distinct and thus favours pure training pixels. The aim of this study was to evaluate the sensitivity of training data distribution along fractional and spectral gradients on the resulting mapping performance. We derived four continuous fields (tree, shrubherb, bare, water) from aerial photographs as response variables and processed corresponding spectral signatures from multitemporal Landsat 5 TM data as explanatory variables. Subsequent controlled experiments along fractional cover gradients were then based on generalised linear models. Resulting fractional and spectral distribution differed between single continuous fields, but could be satisfactorily trained and mapped. Pixels with fractional or without respective cover were much more critical than pure full cover pixels. Error distribution of continuous field models was non-uniform with respect to horizontal and vertical spatial distribution of target fields. We conclude that a sampling for continuous field training data should be based on extent and densities in the fractional and spectral, rather than the real spatial space. Consequently, adequate training plots are most probably not systematically distributed in the real spatial space, but cover the gradient and covariate structure of the fractional and spectral space well. (C) 2009 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.

An approach to predicting bowing control parameter contours in violin performance

We present a machine learning approach to modeling bowing control parametercontours in violin performance. Using accurate sensing techniqueswe obtain relevant timbre-related bowing control parameters such as bowtransversal velocity, bow pressing force, and bow-bridge distance of eachperformed note. Each performed note is represented by a curve parametervector and a number of note classes are defined. The principal componentsof the data represented by the set of curve parameter vectors are obtainedfor each class. Once curve parameter vectors are expressed in the new spacedefined by the principal components, we train a model based on inductivelogic programming, able to predict curve parameter vectors used for renderingbowing controls. We evaluate the prediction results and show the potentialof the model by predicting bowing control parameter contours from anannotated input score.