Experiment of Digital Directional Modulation Transmitters

A digital directional modulation (DM) transmitter structure is proposed from a practical implementation point of view in this paper. This digital DM architecture is built with the help of several off-the-shelf physical layer wireless experiment platform hardware boards. When compared with previous analogue DM transmitter architectures, the digital means offers more precise and fast control on the updates of the array excitations. More importantly, it is an ideal physical arrangement to implement the most universal DM synthesis algorithm, i.e., the orthogonal vector approach. The practical issues in digital DM system calibrations are described and solved. The bit error rates (BERs) are measured via real-time data transmissions to illustrate the DM advantages, in terms of secrecy performance, over conventional non-DM beam-steering transmitters.

Performance and Fault Tolerance of Preconditioned Iterative Solvers on Low-Power ARM Architectures

As the complexity of computing systems grows, reliability and energy are two crucial challenges asking for holistic solutions. In this paper, we investigate the interplay among concurrency, power dissipation, energy consumption and voltage-frequency scaling for a key numerical kernel for the solution of sparse linear systems. Concretely, we leverage a task-parallel implementation of the Conjugate Gradient method, equipped with an state-of-the-art pre-conditioner embedded in the ILUPACK software, and target a low-power multi core processor from ARM.In addition, we perform a theoretical analysis on the impact of a technique like Near Threshold Voltage Computing (NTVC) from the points of view of increased hardware concurrency and error rate.

Prevalence, Nature, Severity and Risk Factors for Prescribing Errors in Hospital Inpatients: Prospective Study in 20 UK Hospitals

Introduction: It has been suggested that doctors in their first year of post-graduate training make a disproportionate number of prescribing errors.

Obkective: This study aimed to compare the prevalence of prescribing errors made by first-year post-graduate doctors with that of errors by senior doctors and non-medical prescribers and to investigate the predictors of potentially serious prescribing errors.

Methods: Pharmacists in 20 hospitals over 7 prospectively selected days collected data on the number of medication orders checked, the grade of prescriber and details of any prescribing errors. Logistic regression models (adjusted for clustering by hospital) identified factors predicting the likelihood of prescribing erroneously and the severity of prescribing errors.

Results: Pharmacists reviewed 26,019 patients and 124,260 medication orders; 11,235 prescribing errors were detected in 10,986 orders. The mean error rate was 8.8 % (95 % confidence interval [CI] 8.6-9.1) errors per 100 medication orders. Rates of errors for all doctors in training were significantly higher than rates for medical consultants. Doctors who were 1 year (odds ratio [OR] 2.13; 95 % CI 1.80-2.52) or 2 years in training (OR 2.23; 95 % CI 1.89-2.65) were more than twice as likely to prescribe erroneously. Prescribing errors were 70 % (OR 1.70; 95 % CI 1.61-1.80) more likely to occur at the time of hospital admission than when medication orders were issued during the hospital stay. No significant differences in severity of error were observed between grades of prescriber. Potentially serious errors were more likely to be associated with prescriptions for parenteral administration, especially for cardiovascular or endocrine disorders.

Conclusions: The problem of prescribing errors in hospitals is substantial and not solely a problem of the most junior medical prescribers, particularly for those errors most likely to cause significant patient harm. Interventions are needed to target these high-risk errors by all grades of staff and hence improve patient safety.

Investigation into DCT Feature Selection for Visual Lip-Based Biometric Authentication

This paper investigated using lip movements as a behavioural biometric for person authentication. The system was trained, evaluated and tested using the XM2VTS dataset, following the Lausanne Protocol configuration II. Features were selected from the DCT coefficients of the greyscale lip image. This paper investigated the number of DCT coefficients selected, the selection process, and static and dynamic feature combinations. Using a Gaussian Mixture Model - Universal Background Model framework an Equal Error Rate of 2.20% was achieved during evaluation and on an unseen test set a False Acceptance Rate of 1.7% and False Rejection Rate of 3.0% was achieved. This compares favourably with face authentication results on the same dataset whilst not being susceptible to spoofing attacks.

Characterization of proteotoxic stress in zebrafish

A fidelidade da síntese proteica é fundamental para a estabilidade do proteoma e para a homeostasia celular. Em condições fisiológicas normais as células têm uma taxa de erro basal associada e esta muitas vezes aumenta com o envelhecimento e doença. Problemas na síntese das proteínas estão associados a várias doenças humanas e aos processos de envelhecimento. De facto, a incorporação de erros nas proteínas devido a tRNAs carregados pelas aminoacil-tRNA sintetases com o amino ácido errado causa doenças neurodegenerativas em humanos e ratos. Ainda não é claro como é que estas doenças se desenvolvem e se são uma consequência directa da disrupção do proteoma ou se são o resultado da toxicidade produzida pela acúmulação de proteínas mal traduzidas ao nível do ribossoma. Para elucidar como é que as células eucarióticas lidam com proteínas aberrantes e agregados proteicos (stress proteotóxico) desenvolvemos uma estratégia para destabilizar o proteoma. Para isso estabelecemos um sistema de erros de tradução em embriões de peixe zebra que assenta em tRNAs mutantes capazes de incorporar erradamente serina nas proteínas. As proteínas produzidas neste sistema despoletam as vias de resposta ao stress, nomeadamente a via da ubiquitina-proteassoma (UPP – “ubiquitin protesome pathway”) e a via do retículo endoplasmático (UPR – “unfolded protein response”). O stress proteotóxico gerado pelos erros de tradução altera a expressão génica e perfis de expressão de miRNAs, o desenvolvimento embrionário e viabilidade, aumenta a produção de espécies reactivas de oxigénio (ROS), leva ainda à acumulação de agregados proteicos e à disfunção mitocondrial. As malformações embrionárias e fenótipos de viabilidade que observámos foram revertidos por antioxidantes, o que sugere que os ROS desempenham papéis importantes nos fenótipos degenerativos celulares induzidos pela produção de proteínas aberrantes e agregação proteica. Estabelecemos ainda uma linha de peixe zebra transgénica para o estudo do stress proteotóxico. Este trabalho mostra que a destabilização do proteoma em embriões de peixe zebra com tRNAs mutantes é uma boa metodologia para estudar a biologia do stress proteotóxico visto que permite a agregação controlada do proteoma, mimetizando os processos de agregação de proteínas que ocorrem naturalmente durante o envelhecimento e em doenças conformacionais humanas.

Análise comparativa das técnicas de transmissão com modulação exterma PDSB, OSSB e OCS

Dissertação de Mestrado, Engenharia Eléctrica e Electrónica, Ramo de Tecnologias de Informação e Telecomunicações, Instituto Superior de Engenharia, Universidade do Algarve, 2009

Agrupamento multi-orador

Actualmente tem-se observado um aumento do volume de sinais de fala em diversas aplicações, que reforçam a necessidade de um processamento automático dos ficheiros. No campo do processamento automático destacam-se as aplicações de “diarização de orador”, que permitem catalogar os ficheiros de fala com a identidade de oradores e limites temporais de fala de cada um, através de um processo de segmentação e agrupamento. No contexto de agrupamento, este trabalho visa dar continuidade ao trabalho intitulado “Detecção do Orador”, com o desenvolvimento de um algoritmo de “agrupamento multi-orador” capaz de identificar e agrupar correctamente os oradores, sem conhecimento prévio do número ou da identidade dos oradores presentes no ficheiro de fala. O sistema utiliza os coeficientes “Mel Line Spectrum Frequencies” (MLSF) como característica acústica de fala, uma segmentação de fala baseada na energia e uma estrutura do tipo “Universal Background Model - Gaussian Mixture Model” (UBM-GMM) adaptado com o classificador “Support Vector Machine” (SVM). No trabalho foram analisadas três métricas de discriminação dos modelos SVM e a avaliação dos resultados foi feita através da taxa de erro “Speaker Error Rate” (SER), que quantifica percentualmente o número de segmentos “fala” mal classificados. O algoritmo implementado foi ajustado às características da língua portuguesa através de um corpus com 14 ficheiros de treino e 30 ficheiros de teste. Os ficheiros de treino dos modelos e classificação final, enquanto os ficheiros de foram utilizados para avaliar o desempenho do algoritmo. A interacção com o algoritmo foi dinamizada com a criação de uma interface gráfica que permite receber o ficheiro de teste, processá-lo, listar os resultados ou gerar um vídeo para o utilizador confrontar o sinal de fala com os resultados de classificação.

Acompanhamento da construção de um edifício multifuncional e de duas moradias unifamiliares

Relatório de estágio para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização em Edificações

Sistema de reconhecimento de impressões digitais baseado em FPGA

Trabalho de Projeto para obtenção do grau de Mestre em Engenharia de Eletrónica e Telecomunicações

On the development of an automatic voice pleasantness classification and intensity estimation system

In the last few years, the number of systems and devices that use voice based interaction has grown significantly. For a continued use of these systems, the interface must be reliable and pleasant in order to provide an optimal user experience. However there are currently very few studies that try to evaluate how pleasant is a voice from a perceptual point of view when the final application is a speech based interface. In this paper we present an objective definition for voice pleasantness based on the composition of a representative feature subset and a new automatic voice pleasantness classification and intensity estimation system. Our study is based on a database composed by European Portuguese female voices but the methodology can be extended to male voices or to other languages. In the objective performance evaluation the system achieved a 9.1% error rate for voice pleasantness classification and a 15.7% error rate for voice pleasantness intensity estimation.

An automatic voice pleasantness classification system based on prosodic and acoustic patterns of voice preference

In the last few years the number of systems and devices that use voice based interaction has grown significantly. For a continued use of these systems the interface must be reliable and pleasant in order to provide an optimal user experience. However there are currently very few studies that try to evaluate how good is a voice when the application is a speech based interface. In this paper we present a new automatic voice pleasantness classification system based on prosodic and acoustic patterns of voice preference. Our study is based on a multi-language database composed by female voices. In the objective performance evaluation the system achieved a 7.3% error rate.

IFN stimulated gene expression in the liver is a better predictor of treatment response in chronic hepatitis c than the IL28b (IFN lambda 3) genotype

Background: Therapy of chronic hepatitis C (CHC) with pegIFNa/ribavirin achieves sustained virologic response (SVR) in ~55%. Pre-activation of the endogenous interferon system in the liver is associated non-response (NR). Recently, genome-wide association studies described associations of allelic variants near the IL28B (IFNλ3) gene with treatment response and with spontaneous clearance of the virus. We investigated if the IL28B genotype determines the constitutive expression of IFN stimulated genes (ISGs) in the liver of patients with CHC. Methods: We genotyped 93 patients with CHC for 3 IL28B single nucleotide polymorphisms (SNPs, rs12979860, rs8099917, rs12980275), extracted RNA from their liver biopsies and quantified the expression of IL28B and of 8 previously identified classifier genes which discriminate between SVR and NR (IFI44L, RSAD2, ISG15, IFI22, LAMP3, OAS3, LGALS3BP and HTATIP2). Decision tree ensembles in the form of a random forest classifier were used to calculate the relative predictive power of these different variables in a multivariate analysis. Results: The minor IL28B allele (bad risk for treatment response) was significantly associated with increased expression of ISGs, and, unexpectedly, with decreased expression of IL28B. Stratification of the patients into SVR and NR revealed that ISG expression was conditionally independent from the IL28B genotype, i.e. there was an increased expression of ISGs in NR compared to SVR irrespective of the IL28B genotype. The random forest feature score (RFFS) identified IFI27 (RFFS = 2.93), RSAD2 (1.88) and HTATIP2 (1.50) expression and the HCV genotype (1.62) as the strongest predictors of treatment response. ROC curves of the IL28B SNPs showed an AUC of 0.66 with an error rate (ERR) of 0.38. A classifier with the 3 best classifying genes showed an excellent test performance with an AUC of 0.94 and ERR of 0.15. The addition of IL28B genotype information did not improve the predictive power of the 3-gene classifier. Conclusions: IL28B genotype and hepatic ISG expression are conditionally independent predictors of treatment response in CHC. There is no direct link between altered IFNλ3 expression and pre-activation of the endogenous system in the liver. Hepatic ISG expression is by far the better predictor for treatment response than IL28B genotype.

Streamlining the medication process improves safety in the intensive care unit.

BACKGROUND: Multiple interventions were made to optimize the medication process in our intensive care unit (ICU). 1 Transcriptions from the medical order form to the administration plan were eliminated by merging both into a single document; 2 the new form was built in a logical sequence and was highly structured to promote completeness and standardization of information; 3 frequently used drug names, approved units, and fixed routes were pre-printed; 4 physicians and nurses were trained with regard to the correct use of the new form. This study was aimed at evaluating the impact of these interventions on clinically significant types of medication errors. METHODS: Eight types of medication errors were measured by a prospective chart review before and after the interventions in the ICU of a public tertiary care hospital. We used an interrupted time-series design to control the secular trends. RESULTS: Over 85 days, 9298 lines of drug prescription and/or administration to 294 patients, corresponding to 754 patient-days were collected and analysed for the three series before and three series following the intervention. Global error rate decreased from 4.95 to 2.14% (-56.8%, P < 0.001). CONCLUSIONS: The safety of the medication process in our ICU was improved by simple and inexpensive interventions. In addition to the optimization of the prescription writing process, the documentation of intravenous preparation, and the scheduling of administration, the elimination of the transcription in combination with the training of users contributed to reducing errors and carried an interesting potential to increase safety.

Frontal Lobe Function and Performance Monitoring following Total Sleep Deprivation

Imaging studies have shown reduced frontal lobe resources following total sleep deprivation (TSD). The anterior cingulate cortex (ACC) in the frontal region plays a role in performance monitoring and cognitive control; both error detection and response inhibition are impaired following sleep loss. Event-related potentials (ERPs) are an electrophysiological tool used to index the brain's response to stimuli and information processing. In the Flanker task, the error-related negativity (ERN) and error positivity (Pe) ERPs are elicited after erroneous button presses. In a Go/NoGo task, NoGo-N2 and NoGo-P3 ERPs are elicited during high conflict stimulus processing. Research investigating the impact of sleep loss on ERPs during performance monitoring is equivocal, possibly due to task differences, sample size differences and varying degrees of sleep loss. Based on the effects of sleep loss on frontal function and prior research, it was expected that the sleep deprivation group would have lower accuracy, slower reaction time and impaired remediation on performance monitoring tasks, along with attenuated and delayed stimulus- and response-locked ERPs. In the current study, 49 young adults (24 male) were screened to be healthy good sleepers and then randomly assigned to a sleep deprived (n = 24) or rested control (n = 25) group. Participants slept in the laboratory on a baseline night, followed by a second night of sleep or wake. Flanker and Go/NoGo tasks were administered in a battery at 1O:30am (i.e., 27 hours awake for the sleep deprivation group) to measure performance monitoring. On the Flanker task, the sleep deprivation group was significantly slower than controls (p's <.05), but groups did not differ on accuracy. No group differences were observed in post-error slowing, but a trend was observed for less remedial accuracy in the sleep deprived group compared to controls (p = .09), suggesting impairment in the ability to take remedial action following TSD. Delayed P300s were observed in the sleep deprived group on congruent and incongruent Flanker trials combined (p = .001). On the Go/NoGo task, the hit rate (i.e., Go accuracy) was significantly lower in the sleep deprived group compared to controls (p <.001), but no differences were found on false alarm rates (i.e., NoGo Accuracy). For the sleep deprived group, the Go-P3 was significantly smaller (p = .045) and there was a trend for a smaller NoGo-N2 compared to controls (p = .08). The ERN amplitude was reduced in the TSD group compared to controls in both the Flanker and Go/NoGo tasks. Error rate was significantly correlated with the amplitude of response-locked ERNs in control (r = -.55, p=.005) and sleep deprived groups (r = -.46, p = .021); error rate was also correlated with Pe amplitude in controls (r = .46, p=.022) and a trend was found in the sleep deprived participants (r = .39, p =. 052). An exploratory analysis showed significantly larger Pe mean amplitudes (p = .025) in the sleep deprived group compared to controls for participants who made more than 40+ errors on the Flanker task. Altered stimulus processing as indexed by delayed P3 latency during the Flanker task and smaller amplitude Go-P3s during the Go/NoGo task indicate impairment in stimulus evaluation and / or context updating during frontal lobe tasks. ERN and NoGoN2 reductions in the sleep deprived group confirm impairments in the monitoring system. These data add to a body of evidence showing that the frontal brain region is particularly vulnerable to sleep loss. Understanding the neural basis of these deficits in performance monitoring abilities is particularly important for our increasingly sleep deprived society and for safety and productivity in situations like driving and sustained operations.

AutoFACT: An Automatic Functional Annotation and Classification Tool

Affiliation: Centre Robert-Cedergren de l'Université de Montréal en bio-informatique et génomique & Département de biochimie, Université de Montréal