A Clinical Support System Based on Quality of Life Estimation

Quality of life is a concept influenced by social, economic, psychological, spiritual or medical state factors. More specifically, the perceived quality of an individual's daily life is an assessment of their well-being or lack of it. In this context, information technologies may help on the management of services for healthcare of chronic patients such as estimating the patient quality of life and helping the medical staff to take appropriate measures to increase each patient quality of life. This paper describes a Quality of Life estimation system developed using information technologies and the application of data mining algorithms to access the information of clinical data of patients with cancer from Otorhinolaryngology and Head and Neck services of an oncology institution. The system was evaluated with a sample composed of 3013 patients. The results achieved show that there are variables that may be significant predictors for the Quality of Life of the patient: years of smoking (p value 0.049) and size of the tumor (p value < 0.001). In order to assign the variables to the classification of the quality of life the best accuracy was obtained by applying the John Platt's sequential minimal optimization algorithm for training a support vector classifier. In conclusion data mining techniques allow having access to patients additional information helping the physicians to be able to know the quality of life and produce a well-informed clinical decision.

Quality-of-service aware routing for static and mobile IPv6-based low-power and lossy sensor networks using RPL

The Internet of Things (IoT) has emerged as a paradigm over the last few years as a result of the tight integration of the computing and the physical world. The requirement of remote sensing makes low-power wireless sensor networks one of the key enabling technologies of IoT. These networks encompass several challenges, especially in communication and networking, due to their inherent constraints of low-power features, deployment in harsh and lossy environments, and limited computing and storage resources. The IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) [1] was proposed by the IETF ROLL (Routing Over Low-power Lossy links) working group and is currently adopted as an IETF standard in the RFC 6550 since March 2012. Although RPL greatly satisfied the requirements of low-power and lossy sensor networks, several issues remain open for improvement and specification, in particular with respect to Quality of Service (QoS) guarantees and support for mobility. In this paper, we focus mainly on the RPL routing protocol. We propose some enhancements to the standard specification in order to provide QoS guarantees for static as well as mobile LLNs. For this purpose, we propose OF-FL (Objective Function based on Fuzzy Logic), a new objective function that overcomes the limitations of the standardized objective functions that were designed for RPL by considering important link and node metrics, namely end-to-end delay, number of hops, ETX (Expected transmission count) and LQL (Link Quality Level). In addition, we present the design of Co-RPL, an extension to RPL based on the corona mechanism that supports mobility in order to overcome the problem of slow reactivity to frequent topology changes and thus providing a better quality of service mainly in dynamic networks application. Performance evaluation results show that both OF-FL and Co-RPL allow a great improvement when compared to the standard specification, mainly in terms of packet loss ratio and average network latency. 2015 Elsevier B.V. Al

Trace Elements in Ambient Air at Porto Metropolitan Area—Checking for Compliance with New European Union (Eu) Air Quality Standards

Because of the scientific evidence showing that arsenic (As), cadmium (Cd), and nickel (Ni) are human genotoxic carcinogens, the European Union (EU) recently set target values for metal concentration in ambient air (As: 6 ng/m3, Cd: 5 ng/m3, Ni: 20 ng/m3). The aim of our study was to determine the concentration levels of these trace elements in Porto Metropolitan Area (PMA) in order to assess whether compliance was occurring with these new EU air quality standards. Fine (PM2.5) and inhalable (PM10) air particles were collected from October 2011 to July 2012 at two different (urban and suburban) locations in PMA. Samples were analyzed for trace elements content by inductively coupled plasma–mass spectrometry (ICP-MS). The study focused on determination of differences in trace elements concentration between the two sites, and between PM2.5 and PM10, in order to gather information regarding emission sources. Except for chromium (Cr), the concentration of all trace elements was higher at the urban site. However, results for As, Cd, Ni, and lead (Pb) were well below the EU limit/target values (As: 1.49 ± 0.71 ng/m3; Cd: 1.67 ± 0.92 ng/m3; Ni: 3.43 ± 3.23 ng/m3; Pb: 17.1 ± 10.1 ng/m3) in the worst-case scenario. Arsenic, Cd, Ni, Pb, antimony (Sb), selenium (Se), vanadium (V), and zinc (Zn) were predominantly associated to PM2.5, indicating that anthropogenic sources such as industry and road traffic are the main source of these elements. High enrichment factors (EF > 100) were obtained for As, Cd, Pb, Sb, Se, and Zn, further confirming their anthropogenic origin.

Unemployment, technological revolution and competition from developing countries

Unemployment is probably the most important social problem of our times in the rich industrial world. There are 35 million people unemployed in OECD countries(about 8,5%): the situation however differs between the USA and Europe. In this paper we will discuss the reasons for suche a difference.

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.

Adaptive filtering for high quality HMM based speech synthesis

In this work an adaptive filtering scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for Hidden Markov Model (HMM) based speech synthesis quality enhancement. The objective is to improve signal smoothness across HMMs and their related states and to reduce artifacts due to acoustic model's limitations. Both speech and artifacts are modelled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. Themodel parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The quality enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. The system's performance has been evaluated using mean opinion score tests and the proposed technique has led to improved results.

Microbiological quality of drinking rainwater in the inland region of Pajeú, Pernambuco, Northeast Brazil

Despite all efforts to store and reduce its consumption, water is becoming less inexhaustible and its quality is falling faster. Considering that water is essential to animal life, it is necessary to adopt measures to ensure its sanitary conditions in order to be fit for consumption. The aim of this study was to analyze the microbiological quality of drinking rainwater used by rural communities of Tuparetama, a small town located in Northeast Brazil. The study covered seven rural communities, totaling 66 households. In each household two samples were collected, one from a tank and the other from a clay pot located inside the home, resulting in 132 samples (tank plus clay pot). Approximately 90% of samples were below the standard recommended by the current legislation, being considered unfit for human consumption. Part of this high microbiological contamination of drinking rainwater could be related to the lack of sanitary education and of an adequate sewerage sanitation system.

Gestão de recursos humanos na indústria do turismo em Portugal: tendências futuras do capital humano: um estudo exploratório em unidades hoteleiras no Distrito de Coimbra

No setor do turismo, devido a evolução social e tecnológica, surgiram exigências relativamente ao conhecimento, inovação, informação e qualidade, que resultaram numa maior procura de perfis profissionais adaptados às necessidades a médio prazo (Eurico, 2012). Assim, as unidades hoteleiras têm sentido uma forte necessidade de recrutar e reter pessoas qualificadas e capazes de antecipar múltiplos fatores decisivos na satisfação do cliente. Neste sentido, o presente estudo procura explorar e compreender as tendências futuras ao nível do Capital Humano na indústria do Turismo, mais especificamente no que respeita as unidades hoteleiras, tendo como amostra unidades localizadas no distrito de Coimbra. A análise incidiu nas competências específicas requeridas no setor, qualificações, formação profissional, recrutamento e seleção, sistema de remuneração e recompensa e do sistema de progressão na carreira. Assim, foi escolhido para o presente estudo a metodologia qualitativa, em que os dados foram recolhidos a partir do inquérito por entrevista realizado a sete Diretores e um assistente de direção de oito unidades hoteleiras no Distrito de Coimbra. Para o tratamento dos dados foi aplicada a análise do conteúdo através do processo de preparação das entrevistas transcritas, que, após uma leitura exaustiva, foram transformados em unidades de análise que permitiram a criação de categorias dessas unidades. Após a criação de categorias de análise foi possível realizar a descrição através de uma síntese dos dados fazendo uso de citações diretas dos dados recolhidos. Por fim, foi realizada a interpretação dos dados que traduz-se na relação das categorias das unidades de análise e a fundamentação teórica presente neste estudo (Santos, 2012). Os resultados obtidos a partir deste estudo revelam que os requisitos exigidos para os colaboradores e para determinadas práticas de gestão de recursos humanos nas unidades hoteleiras atualmente e num futuro próximo serão essencialmente os mesmos. Todavia, foi possível estabelecer o perfil ideal dos futuros colaboradores das unidades hoteleiras e tendências de práticas de gestão de recursos humanos como formação e desenvolvimento, recrutamento e seleção, planos de progressão na carreira e sistemas de remuneração e recompensa. Foi igualmente possível verificar que a maioria das unidades hoteleiras analisadas é de pequena e média dimensão não dispõe de um departamento de Recursos Humanos, sendo aplicada pelos gestores de topo.