Cross-Layer Admission Control to Enhance the Support of Real-Time Applications in WSN

Real-time monitoring applications may be used in a wireless sensor network (WSN) and may generate packet flows with strict quality of service requirements in terms of delay, jitter, or packet loss. When strict delays are imposed from source to destination, the packets must be delivered at the destination within an end-to-end delay (EED) hard limit in order to be considered useful. Since the WSN nodes are scarce both in processing and energy resources, it is desirable that they only transport useful data, as this contributes to enhance the overall network performance and to improve energy efficiency. In this paper, we propose a novel cross-layer admission control (CLAC) mechanism to enhance the network performance and increase energy efficiency of a WSN, by avoiding the transmission of potentially useless packets. The CLAC mechanism uses an estimation technique to preview packets EED, and decides to forward a packet only if it is expected to meet the EED deadline defined by the application, dropping it otherwise. The results obtained show that CLAC enhances the network performance by increasing the useful packet delivery ratio in high network loads and improves the energy efficiency in every network load.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Enhancing Agent Mediated Electronic Markets with Ontology Matching Services and Social Network Support

Os Mercados Eletrónicos atingiram uma complexidade e nível de sofisticação tão elevados, que tornaram inadequados os modelos de software convencionais. Estes mercados são caracterizados por serem abertos, dinâmicos e competitivos, e constituídos por várias entidades independentes e heterogéneas. Tais entidades desempenham os seus papéis de forma autónoma, seguindo os seus objetivos, reagindo às ocorrências do ambiente em que se inserem e interagindo umas com as outras. Esta realidade levou a que existisse por parte da comunidade científica um especial interesse no estudo da negociação automática executada por agentes de software [Zhang et al., 2011]. No entanto, a diversidade dos atores envolvidos pode levar à existência de diferentes conceptualizações das suas necessidades e capacidades dando origem a incompatibilidades semânticas, que podem prejudicar a negociação e impedir a ocorrência de transações que satisfaçam as partes envolvidas. Os novos mercados devem, assim, possuir mecanismos que lhes permitam exibir novas capacidades, nomeadamente a capacidade de auxiliar na comunicação entre os diferentes agentes. Pelo que, é defendido neste trabalho que os mercados devem oferecer serviços de ontologias que permitam facilitar a interoperabilidade entre os agentes. No entanto, os humanos tendem a ser relutantes em aceitar a conceptualização de outros, a não ser que sejam convencidos de que poderão conseguir um bom negócio. Neste contexto, a aplicação e exploração de relações capturadas em redes sociais pode resultar no estabelecimento de relações de confiança entre vendedores e consumidores, e ao mesmo tempo, conduzir a um aumento da eficiência da negociação e consequentemente na satisfação das partes envolvidas. O sistema AEMOS é uma plataforma de comércio eletrónico baseada em agentes que inclui serviços de ontologias, mais especificamente, serviços de alinhamento de ontologias, incluindo a recomendação de possíveis alinhamentos entre as ontologias dos parceiros de negociação. Este sistema inclui também uma componente baseada numa rede social, que é construída aplicando técnicas de análise de redes socias sobre informação recolhida pelo mercado, e que permite melhorar a recomendação de alinhamentos e auxiliar os agentes na sua escolha. Neste trabalho são apresentados o desenvolvimento e implementação do sistema AEMOS, mais concretamente: • É proposto um novo modelo para comércio eletrónico baseado em agentes que disponibiliza serviços de ontologias; • Adicionalmente propõem-se o uso de redes sociais emergentes para captar e explorar informação sobre relações entre os diferentes parceiros de negócio; • É definida e implementada uma componente de serviços de ontologias que é capaz de: • o Sugerir alinhamentos entre ontologias para pares de agentes; • o Traduzir mensagens escritas de acordo com uma ontologia em mensagens escritas de acordo com outra, utilizando alinhamentos previamente aprovados; • o Melhorar os seus próprios serviços recorrendo às funcionalidades disponibilizadas pela componente de redes sociais; • É definida e implementada uma componente de redes sociais que: • o É capaz de construir e gerir um grafo de relações de proximidade entre agentes, e de relações de adequação de alinhamentos a agentes, tendo em conta os perfis, comportamento e interação dos agentes, bem como a cobertura e utilização dos alinhamentos; • o Explora e adapta técnicas e algoritmos de análise de redes sociais às várias fases dos processos do mercado eletrónico. A implementação e experimentação do modelo proposto demonstra como a colaboração entre os diferentes agentes pode ser vantajosa na melhoria do desempenho do sistema e como a inclusão e combinação de serviços de ontologias e redes sociais se reflete na eficiência da negociação de transações e na dinâmica do mercado como um todo.

Hopelessness and Related Variables among Cancer Patients in the Southern European Psycho-Oncology Study (SEPOS).

BACKGROUND: Although hopelessness has been studied in cancer, no data are available in non-English-speaking countries. OBJECTIVE: The authors sought to amass data from Southern European countries (Italy, Portugal, Spain, and Switzerland) in order to fill this void. METHOD: A group of 312 cancer patients completed the Mini-MAC Hopelessness subscale, the Hospital Anxiety and Depression Scale (HADS), the Cancer Worry Inventory (CWI), and a six-item Visual Analog scale (VAS) to measure intensity of physical symptoms, general well-being, difficulty in coping with cancer, intensity of social support from close relationships, leisure activity, and support from religious beliefs. RESULTS: Regression analysis indicated that HADS-Depression, VAS Maladaptive Coping and Well-Being, and the CWI explained 42% of the variance. CONCLUSION: Hopelessness in cancer patients seems not exclusively to correspond to depression, but is related to various other psychosocial factors, such as maladaptive coping, as well.

A Communication Intervention for Training Southern European Oncologists to Recognize Psychosocial Morbidity in Cancer. I - Development of the Model and Preliminary Results on Physicians' Satisfaction

BACKGROUND: The detection of psychosocial distress is a significant communication problem in Southern Europe and other countries. Work in this area is hampered by a lack of data. Because not much is known about training aimed at improving the recognition of psychosocial disorders in cancer patients, we developed a basic course model for medical oncology professionals. METHODS: A specific educational and experiential model (12 hours divided into 2 modules) involving formal teaching (ie, journal articles, large-group presentations), practice in small groups (ie, small-group exercises and role playing), and discussion in large groups was developed with the aim of improving the ability of oncologists to detect emotional disturbances in cancer patients (ie, depression, anxiety, and adjustment disorders). RESULTS: A total of 30 oncologists from 3 Southern European countries (Italy, Portugal, and Spain) participated in the workshop. The training course was well accepted by most participants who expressed general satisfaction and a positive subjective perception of the utility of the course for clinical practice. Of the total participants, 28 physicians (93.3%) thought that had they been exposed to this material sooner, they would have incorporated the techniques received in the workshop into their practices; 2 participants stated they would likely have done so. Half of the doctors (n = 15) believed that their clinical communication techniques were improved by participating in the workshop, and the remaining half thought that their abilities to communicate with cancer patients had improved. CONCLUSIONS: This model is a feasible approach for oncologists and is easily applicable to various oncology settings. Further studies will demonstrate the effectiveness of this method for improving oncologists skills in recognizing emotional disorders in their patients with cancer.

Risk-based decision support system for life cycle management of industrials plants

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores

Adding SOS Core & transactional profiles support to a web thin client

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Territorial Strategic Planning as a support instrument for Regional and Local Development : a comparative analysis between Lisbon and Barcelona metropolitan areas - a first approach

Trabalho de Projecto apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Metropolização, Planeamento Estratégico e Sustentabilidade.

Membrane structural changes support the involvement of mitochondria in the bile salt-induced apoptosis of rat hepatocytes

Clin Sci (Lond). 2002 Nov;103(5):475-85

Psychosocial Determinants of Quality of Life 6 Months After Transplantation: Longitudinal Prospective Study

OBJECTIVES: We sought to investigate the psychosocial determinants of quality of life at 6 months after transplantation. METHODS: A sample of liver transplant candidates (n = 60), composed of consecutive patients (25% with familial amyloid polyneuropathy [FAP]) attending outpatient clinics was assessed in the pretransplant period using the Neo Five Factor Inventory, Hospital Anxiety and depression Scale (HADS), Brief COPE, and SF-36, a quality-of-life, self-rating questionnaire. Six months after transplantation, these patients were assessed by means of the SF-36. RESULTS: Psychosocial predictors where found by means of multiple regression analysis. The physical component of quality of life at 6 months after transplantation was determined based upon coping strategies and physical quality of life in the pretransplant period (this model explained 32% of variance). The mental component at 6 months after transplantation was determined by depression in the pretransplant period and by clinical diagnoses of patients. Because FAP patients show a lower mental component of quality of life, this diagnosis explained 25% of the variance. CONCLUSIONS: Our findings suggested that coping strategies and depression measured in the pretransplant period are important determinants of quality of life at 6 months after liver transplantation.

The Support Role in Clinical Supervision of Nursing Students: Determinant in the Development of Emotional Skills

The problematic situation faced by clients, associated to the processes of health and disease, is expressed through emotions that nursing students have to deal with in the course of care and their formative experiences in clinical teaching. Students have learning needs not only to manage emotions in the context of customer care, but also in terms of their own internal world, emotional conflicts, emotional stress and burn-out. With the present literature review, we intend to explore existing evidence regarding the ways in which the nurse supervisor's support towards nursing students potentiates the development of their competences for the performance of emotional labour. These skills prove to be the key in the ability to manage the emotionally intense situations of care practice and the support function of the nursing supervisor contributes to the development of such competences.

UsaGame – A new methodology to support user- centered design of touchscreen game applications

Dissertação para Obtenção do Grau de Mestre em Engenharia e Gestão Industrial

An ANP model to support decision-making in a Portuguese pharmaceutical supply chain

Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial

Multi-GPU support on the marrow algorithmic skeleton framework

Dissertação para obtenção do Grau de Mestre em Engenharia Informática