Adaptive modeling and high quality spectral estimation for speech enhancement

In this work an adaptive modeling and spectral estimation scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for speech enhancement. Both speech and noise signals are modeled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. The model parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The speech enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. This approach is particularly useful as a pre-processing module for parametric based speech recognition systems that rely on spectral time dependent models. The system performance has been evaluated by a set of human listeners and by spectral distances. In both cases the use of this pre-processing module has led to improved results.

Effects of home environment and center-based child care quality on children’s

This study examined the joint effects of home environment and center-based child care quality on children’s language, communication, and early literacy development, while also considering prior developmental level. Participants were 95 children (46 boys), assessed as toddlers (mean age = 26.33 months;Time 1) and preschoolers (mean age = 68.71 months; Time 2) and their families. At both times, children attended center-based child care classrooms in the metropolitan area of Porto, Portugal. Results from hierarchical linear models indicated that home environment and preschool quality, but not center-based toddler child care quality, were associated with children’s language and literacy outcomes at Time 2. Moreover, the quality of preschool classrooms moderated the association between home environment quality and children’s language and early literacy skills – but not communication skills – at Time 2, suggesting the positive cumulative effects of home environment and preschool quality. Findings further support the existence of a detrimental effect of low preschool quality on children’s language and early literacy outcomes: positive associations among home environment quality and children’s developmental outcomes were found to reduce substantially when children attended low-quality preschool classrooms.

Optimization of River Water Quality Surveys by Multivariate Analysis of Physicochemical, Bacteriological and Ecotoxicological Data

This study aims to optimize the water quality monitoring of a polluted watercourse (Leça River, Portugal) through the principal component analysis (PCA) and cluster analysis (CA). These statistical methodologies were applied to physicochemical, bacteriological and ecotoxicological data (with the marine bacterium Vibrio fischeri and the green alga Chlorella vulgaris) obtained with the analysis of water samples monthly collected at seven monitoring sites and during five campaigns (February, May, June, August, and September 2006). The results of some variables were assigned to water quality classes according to national guidelines. Chemical and bacteriological quality data led to classify Leça River water quality as “bad” or “very bad”. PCA and CA identified monitoring sites with similar pollution pattern, giving to site 1 (located in the upstream stretch of the river) a distinct feature from all other sampling sites downstream. Ecotoxicity results corroborated this classification thus revealing differences in space and time. The present study includes not only physical, chemical and bacteriological but also ecotoxicological parameters, which broadens new perspectives in river water characterization. Moreover, the application of PCA and CA is very useful to optimize water quality monitoring networks, defining the minimum number of sites and their location. Thus, these tools can support appropriate management decisions.

B-learning quality: dimensions, criteria and pedagogical approach

Measuring the quality of a b-learning environment is critical to determine the success of a b-learning course. Several initiatives have been recently conducted on benchmarking and quality in e-learning. Despite these efforts in defining and examining quality issues concerning online courses, a defining instrument to evaluate quality is one of the key challenges for blended learning, since it incorporates both traditional and online instruction methods. For this paper, six frameworks for quality assessment of technological enhanced learning were examined and compared regarding similarities and differences. These frameworks aim at the same global objective: the quality of e-learning environment/products. They present different perspectives but also many common issues. Some of them are more specific and related to the course and other are more global and related to institutional aspects. In this work we collected and arrange all the quality criteria identified in order to get a more complete framework and determine if it fits our b-learning environment. We also included elements related to our own b-learning research and experience, acquired during more than 10 years of experience. As a result we have create a new quality reference with a set of dimensions and criteria that should be taken into account when you are analyzing, designing, developing, implementing and evaluating a b-learning environment. Besides these perspectives on what to do when you are developing a b-learning environment we have also included pedagogical issues in order to give directions on how to do it to reach the success of the learning. The information, concepts and procedures here presented give support to teachers and instructors, which intend to validate the quality of their blended learning courses.

From quality gurus and TQM to ISO 9001:2015: a review of several quality paths

A revision of several paths for the Quality journey is presented: from Quality Gurus and Total Quality Management (TQM) models to the ISO 9000 International Standards Series. Since ISO 9001:2008 is now in the revision process to the expected ISO 9001:2015 version, an analysis is made of he proposed changes and the underlying reasons and the impacts foreseen on the more than 1.3 Million certified organizations. This revision should be a step towards TQM and reflect the changes of an increasingly complex, demanding and dynamic environment, while assuring that complying organizations are able to provide conformity products and services that satisfy their customers. Major benefits are expected such as less emphasis on documentation and new/reinforced approaches: consideration of Organizational Context and (relevant) Stakeholders, Risk Based thinking and Knowledge Management.

Utilization of Quality Tools: does sector and size matter?

This research focuses on the influence of company sector and size on the level of utilization of Basic and Advanced Quality Tools. The paper starts with a literature review and then presents the methodology used for the survey. Based on the responses from 202 managers of Portuguese ISO 9001:2008 Quality Management System certified organizations, statistical tests were performed. Results show, with 95% confidence level, that industry and services have a similar proportion of use of Basic and Advanced Quality Tools. Concerning size, bigger companies show a higher trend to use Advanced Quality Tools than smaller ones. For Basic Quality Tools, there was no statistical significant difference at a 95% confidence level for different company sizes. The three basic Quality tools with higher utilization were Check sheets, Flow charts and Histograms (for Services) or Control Charts/ (for Industry), however 22% of the surveyed organizations reported not using Basic Quality Tools, which highlights a major improvement opportunity for these companies. Additional studies addressing motivations, benefits and barriers for Quality Tools application should be undertaken for further validation and understanding of these results.

Language and trade: the (new) route of portuguese in the 21st century

Globalisation has eliminated frontiers and in the case of Europe helped the crossing of borders and changed forever the concept of social (and I would also say individual) geography: the rest of the world is out there; we can pretend not to see it, but we cannot avoid it. Moreover, Europe is undergoing a serious crisis, also economic, and new markets and business partners are welcome. In this context, cultural bonds like a common language can open new investment paths and give rise to successful stories. In this paper we intend to present an example of how low linguistic distance can lead to good business, even if a) in the internationalization process of the companies’ language is often forgotten as a management element and b) consumers of language products (like User Guides) are also not stimulating investment in language by the companies. Through the results of 2 studies carried out in 2010 and 2011 we will show how a pluricentric language like Portuguese is managed in multinational companies (MC) and Small and medium Enterprises (SMEs). The second study is based on an online survey questioning the effectiveness, efficiency and general quality of User Guides and the reaction of consumers to language. Results show that although playing a role in the internationalization process of companies in the same linguistic space, language is opportunistically used. On the other hand, Portuguese and Brazilian consumers show a very functional perception of the Portuguese language...

A data-mining-based methodology for transmission expansion planning

In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.

Radiographic outcomes and evaluation of developmental dysplasia of the hip in children

The Developmental Dysplasia of the Hip (DDH), also know as Congenital Dislocation of the Hip, is common in infants and children and may persist into adulthood. The radiographic interpretation is highly conditioned by appropriate patient positioning and image quality criteria. The main goal of this study is to demonstrate the value of radiographic evaluation of DDH. Through the retrospective analysis of 65 radiographs of the hips, only 2 (3.1%) female patients with 1-2 years of age presented radiographic findings of DDH. The inappropriate field size and the improper placement and size of the gonadal shields, were the most common errors observed.

Reliability of nasal auscultation and their relation to middle ear condition – a clinical interest to pediatrics respiratory physiotherapy

Background: Acute respiratory infections are usual in children under three years old occurring in upper respiratory tract, having an impact on child and caregiver’s quality of life predisposing to otitis media or bronchiolitis. There are few valid and reliable measures to determine the child’s respiratory condition and to guide the physiotherapy intervention. Aim: To assess the intra and inter rater reliability of nasal auscultation, to analyze the relation between sounds’ classification and middle ear’s pressure and compliance as well as with the Clinical Severity Score. Methods: A cross-sectional observational study was composed by 125 nursery children aged up to three years old. Tympanometry, pulmonary and nasal auscultation and application of Clinical Severity Score were performed to each child. Nasal auscultation sounds’ were recorded and sent to 3 blinded experts, that classified, as “obstructed” and “unobstructed”, with a 48 hours interval, in order to analyze inter and intra rater reliability. Results: Nasal auscultation revealed a substantial inter and intra rater reliability (=0,749 and evaluator A - K= 0,691; evaluator B - K= 0,605 and evaluator C - K= 0,724, respectively). Both ears’ pressure was significantly lower in children with an "unobstructed" nasal sound when compared with an “obstructed” nasal sound (t=-3,599, p<0,001 in left ear; t=-2,258, p=0,026 in right ear). Compliance in both ears was significantly lower in children with an "obstructed" nasal sound when compared with “unobstructed” nasal sound (t=-2,728, p=0,007 in left ear; t=-3,830, p<0,001 in right ear). There was a statistically significant association between sounds’ classification and tympanograms types in both ear’s (=11,437, p=0,003 in left ear; =13,535, p=0,001 in right ear). There was a trend to children with an "unobstructed" nasal sound that had a lower clinical severity score when compared with “obstructed” children. Conclusion: It was observed a good intra and substantial inter reliability for nasal auscultation. Nasal auscultation sounds’ classification was related to middle ears’ pressure and compliance.

QoS-based surrogates selection and service proposal formulation in offloading environments

Resource constraints are becoming a problem as many of the wireless mobile devices have increased generality. Our work tries to address this growing demand on resources and performance, by proposing the dynamic selection of neighbor nodes for cooperative service execution. This selection is in uenced by user's quality of service requirements expressed in his request, tailoring provided service to user's speci c needs. In this paper we improve our proposal's formulation algorithm with the ability to trade o time for the quality of the solution. At any given time, a complete solution for service execution exists, and the quality of that solution is expected to improve overtime.

A feedback-based decentralised coordination model for distributed open real-time systems

Moving towards autonomous operation and management of increasingly complex open distributed real-time systems poses very significant challenges. This is particularly true when reaction to events must be done in a timely and predictable manner while guaranteeing Quality of Service (QoS) constraints imposed by users, the environment, or applications. In these scenarios, the system should be able to maintain a global feasible QoS level while allowing individual nodes to autonomously adapt under different constraints of resource availability and input quality. This paper shows how decentralised coordination of a group of autonomous interdependent nodes can emerge with little communication, based on the robust self-organising principles of feedback. Positive feedback is used to reinforce the selection of the new desired global service solution, while negative feedback discourages nodes to act in a greedy fashion as this adversely impacts on the provided service levels at neighbouring nodes. The proposed protocol is general enough to be used in a wide range of scenarios characterised by a high degree of openness and dynamism where coordination tasks need to be time dependent. As the reported results demonstrate, it requires less messages to be exchanged and it is faster to achieve a globally acceptable near-optimal solution than other available approaches.

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.

Fresh-cut aromatic herbs: Nutritional quality stability during shelf-life

Fresh-cut vegetables are a successful convenient healthy food. Nowadays, the presence of new varieties of minimally processed vegetables in the market is common in response to the consumers demand for new flavours and high quality products. Within the most recent fresh-cut products are the aromatic herbs. In this work, the objective was to evaluate the nutritional quality and stability of four fresh-cut aromatic herbs. Several physicochemical quality characteristics (colour, pH, total soluble solids, and total titratable acidity) were monitored in fresh-cut chives, coriander, spearmint and parsley leaves, stored under refrigeration (3 ± 1 ºC) during 10 days. Their nutritional composition was determined, including mineral composition (phosphorous, potassium, sodium, calcium, magnesium, iron, zinc, manganese and copper) and fat- and water-soluble vitamin contents. Total soluble phenolics, flavonoids and the antioxidant capacity were determined by spectrophotometric methods. The aromatic herbs kept their fresh appearance during the storage, maintaining their colour throughout shelf-life. Their macronutrient composition and mineral content were stable during storage. Coriander had the highest mineral and fatsoluble vitamin content, while spearmint showed the best scores in the phenolic, flavonoid and antioxidant capacity assays. Vitamins and antioxidant capacity showed some variation during storage, with a differential behaviour of each compound according to the sample.

Previsão do Diagrama de Carga de Subestações da REN utilizando Redes Neuronais

A presente dissertação apresenta o estudo de previsão do diagrama de carga de subestações da Rede Elétrica Nacional (REN) utilizando redes neuronais, com o intuito de verificar a viabilidade do método utilizado, em estudos futuros. Atualmente, a energia elétrica é um bem essencial e desempenha um papel fundamental, tanto a nível económico do país, como a nível de conforto e satisfação individual. Com o desenvolvimento do setor elétrico e o aumento dos produtores torna-se importante a realização da previsão de diagramas de carga, contribuindo para a eficiência das empresas. Esta dissertação tem como objetivo a utilização do modelo das redes neuronais artificiais (RNA) para criar uma rede capaz de realizar a previsão de diagramas de carga, com a finalidade de oferecer a possibilidade de redução de custos e gastos, e a melhoria de qualidade e fiabilidade. Ao longo do trabalho são utilizados dados da carga (em MW), obtidos da REN, da subestação da Prelada e dados como a temperatura, humidade, vento e luminosidade, entre outros. Os dados foram devidamente tratados com a ajuda do software Excel. Com o software MATLAB são realizados treinos com redes neuronais, através da ferramenta Neural Network Fitting Tool, com o objetivo de obter uma rede que forneça os melhores resultados e posteriormente utiliza-la na previsão de novos dados. No processo de previsão, utilizando dados reais das subestações da Prelada e Ermesinde referentes a Março de 2015, comprova-se que com a utilização de RNA é possível obter dados de previsão credíveis, apesar de não ser uma previsão exata. Deste modo, no que diz respeito à previsão de diagramas de carga, as RNA são um bom método a utilizar, uma vez que fornecem, à parte interessada, uma boa previsão do consumo e comportamento das cargas elétricas. Com a finalização deste estudo os resultados obtidos são no mínimo satisfatórios. Consegue-se alcançar através das RNA resultados próximos aos valores que eram esperados, embora não exatamente iguais devido à existência de uma margem de erro na aprendizagem da rede neuronal.