A Meteorological and Snow observational data set from Snoqualmie Pass (921 m), Washington Cascades, U.S.

We introduce a quality controlled observational atmospheric, snow, and soil data set from Snoqualmie Pass, Washington, U.S.A., to enable testing of hydrometeorological and snow process representations within a rain-snow transitional climate where existing observations are sparse and limited. Continuous meteorological forcing (including air temperature, total precipitation, wind speed, specific humidity, air pressure, short- and longwave irradiance) are provided at hourly intervals for a 24-year historical period (water years 1989-2012) and at half-hourly intervals for a more-recent period (water years 2013-2015), separated based on the availability of observations. Additional observations include 40-years of snow board new snow accumulation, multiple measurements of total snow depth, and manual snow pits, while more recent years include sub-daily surface temperature, snowpack drainage, soil moisture and temperature profiles, and eddy co-variance derived turbulent heat flux. This data set is ideal for testing hypotheses about energy balance, soil and snow processes in the rain-snow transition zone. Plots of live data can be found here: http://depts.washington.edu/mtnhydr/cgi/plot.cgi

A quarter century of creative chaos: Xinhua News Agency 1980-2005

Chinese media in the context of China's rise have puzzled many scholars who used to understand media and communications phenomena by employing the theories generated from a few affluent Western democracies, notably the US. As a result, a complex but more accurate picture has been ignored. Under numerous theoretical polarizations, the contemporary social world seems little changed but polarized. This thesis aims to propose a different approach endeavoring to 'de-Westernize' or 'internationalize' media and communications studies. As a starting point, this study focuses on the globalization debate, Chinese media and news agency studies. The thesis has investigated the Chinese news agency, Xinhua, by employing Fuzzy Logic which captures the complexity of the change in the agency's business structure and journalistic practices over last 25 years. The change is also examined by scrutinizing the role of journalists in the interrelations of Xinhua with its news sources, media and nonmedia clients, and other news agencies. A combination of archive study and 94 semistructured interviews conducted in Beijing, Shanghai, Guangzhou, Hong Kong, Macau and London provides an inclusive account of the Chinese news institution. The key research findings drawn from the empirical research into Xinhua have justified the central argument of this thesis: Crisp Logic or the 'either/or' approach has failed to explain the dynamics of the change to the media system based in a 'non-Western' society. The numerous theoretical polarizations generated by Crisp Logic to a large extent have distorted the understanding of the contemporary social world by polarizing it. Fuzzy Logic serves better(though it is not the only choice)than the traditional approach to reflect on the set of variables existing between the two poles created by Crisp Logic. This thesis is the first doctorate research in the UK and other English-speaking countries to investigate Xinhua by 'going inside' the news institution's headquarters, local branches and overseas bureaus. This is the first comprehensive academic study of the agency, which not only examines the agency's recent change in business structure and journalistic practices, but also provides a historical account of the agency and its relationship with other social institutions. This is the first media study that employs Fuzzy Logic to understand the globalization theory, Chinese media and news agencies.

Energy-aware Workflow Scheduling and Fuzzy Logic Based Capacity Provisioning in Cloud Environment

Thesis (Master's)--University of Washington, 2015

A Fuzzy-Wavelet Neural Network Model for the Detection of Meat Spoilage using an Electronic Nose

Food product safety is one of the most promising areas for the application of electronic noses. The performance of a portable electronic nose has been evaluated in monitoring the spoilage of beef fillet stored aerobically at different storage temperatures (0, 4, 8, 12, 16 and 20°C). This paper proposes a fuzzy-wavelet neural network model which incorporates a clustering pre-processing stage for the definition of fuzzy rules. The dual purpose of the proposed modeling approach is not only to classify beef samples in the respective quality class (i.e. fresh, semi-fresh and spoiled), but also to predict their associated microbiological population directly from volatile compounds fingerprints. Comparison results indicated that the proposed modeling scheme could be considered as a valuable detection methodology in food microbiology

A Rapid Detection of Meat Spoilage using an Electronic Nose and Fuzzy-Wavelet systems

Freshness and safety of muscle foods are generally considered as the most important parameters for the food industry. To address the rapid detection of meat spoilage microorganisms during aerobic or modified atmosphere storage, an electronic nose with the aid of fuzzy wavelet network has been considered in this research. The proposed model incorporates a clustering pre-processing stage for the definition of fuzzy rules. The dual purpose of the proposed modelling approach is not only to classify beef samples in the respective quality class (i.e. fresh, semi-fresh and spoiled), but also to predict their associated microbiological population directly from volatile compounds fingerprints. Comparison results against neural networks and neurofuzzy systems indicated that the proposed modelling scheme could be considered as a valuable detection methodology in food microbiology

Neuro-Fuzzy based Identification of Meat Spoilage using an Electronic Nose

Freshness and safety of muscle foods are generally considered as the most important parameters for the food industry. The performance of a portable electronic nose has been evaluated in monitoring the spoilage of beef fillet stored aerobically at different storage temperatures (0, 4, 8, 12, 16 and 20°C). An adaptive fuzzy logic system model that utilizes a prototype defuzzification scheme has been developed to classify beef samples in their respective quality class and to predict their associated microbiological population directly from volatile compounds fingerprints. Results confirmed the superiority of the adopted methodology and indicated that volatile information in combination with an efficient choice of a modeling scheme could be considered as an alternative methodology for the accurate evaluation of meat spoilage

Elements of a methodology to assess the alignment of core-values in collaborative networks

Collaborative networks are typically formed by heterogeneous and autonomous entities, and thus it is natural that each member has its own set of core-values. Since these values somehow drive the behaviour of the involved entities, the ability to quickly identify partners with compatible or common core-values represents an important element for the success of collaborative networks. However, tools to assess or measure the level of alignment of core-values are lacking. Since the concept of 'alignment' in this context is still ill-defined and shows a multifaceted nature, three perspectives are discussed. The first one uses a causal maps approach in order to capture, structure, and represent the influence relationships among core-values. This representation provides the basis to measure the alignment in terms of the structural similarity and influence among value systems. The second perspective considers the compatibility and incompatibility among core-values in order to define the alignment level. Under this perspective we propose a fuzzy inference system to estimate the alignment level, since this approach allows dealing with variables that are vaguely defined, and whose inter-relationships are difficult to define. Another advantage provided by this method is the possibility to incorporate expert human judgment in the definition of the alignment level. The last perspective uses a belief Bayesian network method, and was selected in order to assess the alignment level based on members' past behaviour. An example of application is presented where the details of each method are discussed.

Application of adaptive neuro-fuzzy inference for wind power short-term forecasting

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. In this paper, an adaptive neuro-fuzzy inference approach is proposed for short-term wind power forecasting. Results from a real-world case study are presented. A thorough comparison is carried out, taking into account the results obtained with other approaches. Numerical results are presented and conclusions are duly drawn. (C) 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Increase of the delivered energy probability in DES using a fuzzy probabilistic modeling

The paper proposes a methodology to increase the probability of delivering power to any load point by identifying new investments in distribution energy systems. The proposed methodology is based on statistical failure and repair data of distribution components and it uses a fuzzy-probabilistic modeling for the components outage parameters. The fuzzy membership functions of the outage parameters of each component are based on statistical records. A mixed integer nonlinear programming optimization model is developed in order to identify the adequate investments in distribution energy system components which allow increasing the probability of delivering power to any customer in the distribution system at the minimum possible cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 180 bus distribution network.

Logic programming and fuzzy Monte Carlo for distribution network reconfiguration

This paper present a methodology to choose the distribution networks reconfiguration that presents the lower power losses. The proposed methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modeling for system component outage parameters. The proposed hybrid method using fuzzy sets and Monte Carlo simulation based on the fuzzyprobabilistic models allows catching both randomness and fuzziness of component outage parameters. A logic programming algorithm is applied, once obtained the system states by Monte Carlo Simulation, to get all possible reconfigurations for each system state. To evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation an AC load flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 115 buses distribution network.

Crianças com défices no controlo motor: contributo para a elaboração do core set da Classificação Internacional de Funcionalidade, Incapacidade e Saúde (CIF)

A CIF é um sistema de classificação adotado pela OMS, que serve de referência universal para descrever, avaliar e medir saúde e incapacidade, a nível individual e ao nível da população. Contudo, apesar do interesse internacional gerado em torno da CIF, esta é considerada uma classificação complexa e extensa, fato que despoletou a criação de core sets – listas de itens da CIF especificamente selecionados pela sua relevância na descrição e qualificação de uma determinada condição de saúde – como resposta a esta problemática. Até à data, foram desenvolvidos core sets para várias patologias comuns. Contudo, apesar do controlo motor ser uma área de investigação muito reconhecida nos últimos 20 anos, ainda não possui um core set próprio. Assim, o objetivo deste estudo é contribuir para o desenvolvimento de um core set, com base na CIF-CJ, dirigido para uma descrição abrangente das competências inerentes a crianças, dos 6 aos 18 anos de idade, com défices no controlo motor. Deste modo, recorreu-se a uma revisão da literatura sobre a temática em estudo, de modo a reunir informação para a construção de uma proposta a core set, posteriormente sujeita ao escrutínio de peritos, através do recurso ao método de Delphi. Após várias rondas, foi alcançado um consenso acerca da lista final de códigos CIF que constituem o core set final.

Contributo para a construção de um code set da classificação internacional de funcionalidade, incapacidade e saúde, para terapeutas ocupacionais, em unidades de cuidados continuados integrados

A CIF é uma ferramenta universal desenvolvida pela OMS que permite a classificação de funcionalidade e incapacidade, através de uma visualização global do que condiciona o desempenho do indivíduo na concretização de atividades e na participação em ocupações. A ideologia da CIF e os seus componentes interrelacionam-se com a essência da TO, indo ao encontro dos modelos da profissão. As UCCI constituem uma atualidade em Portugal e o terapeuta ocupacional é um dos profissionais obrigatórios na equipa multidisciplinar destas unidades. Atendendo à relevância internacional da CIF, à sua ligação com a TO e à necessidade de tornar a CIF operacional na prática clínica diária dado que é uma ferramenta complexa e extensa, é objetivo deste estudo contribuir para a construção de um code set da CIF para terapeutas ocupacionais que exercem funções em UCCI, especificamente em UC, UMDR e ULDM. Para a concretização desta investigação, utilizou-se a técnica de Delphi, que envolveu duas rondas. Na primeira ronda foi possível contar com a participação de 37 terapeutas ocupacionais experientes na área, uma vez que exercem funções em UCCI, e na segunda ronda contou-se com a participação de 20 elementos. Obtiveram consenso na última ronda de Delphi um total de 96 categorias, constituindo esta listagem uma proposta de code set para UCCI. No que se refere às tipologias de unidades, 69 categorias obtiveram consenso em UC, 91 em UMDR e 41 em ULDM. Concluiu-se que a criação de code sets poderá constituir uma mais-valia em contexto de equipa multidisciplinar das UCCI, sendo uma forma de tornar a CIF operacional na prática clínica diária.

An integrated recycling approach for GFRP pultrusion wastes: recycling and reuse assessment into new composite materials using Fuzzy Boolean Nets

In this study, efforts were made in order to put forward an integrated recycling approach for the thermoset based glass fibre reinforced polymer (GPRP) rejects derived from the pultrusion manufacturing industry. Both the recycling process and the development of a new cost-effective end-use application for the recyclates were considered. For this purpose, i) among the several available recycling techniques for thermoset based composite materials, the most suitable one for the envisaged application was selected (mechanical recycling); and ii) an experimental work was carried out in order to assess the added-value of the obtained recyclates as aggregates and reinforcement replacements into concrete-polymer composite materials. Potential recycling solution was assessed by mechanical behaviour of resultant GFRP waste modified concrete-polymer composites with regard to unmodified materials. In the mix design process of the new GFRP waste based composite material, the recyclate content and size grade, and the effect of the incorporation of an adhesion promoter were considered as material factors and systematically tested between reasonable ranges. The optimization process of the modified formulations was supported by the Fuzzy Boolean Nets methodology, which allowed finding the best balance between material parameters that maximizes both flexural and compressive strengths of final composite. Comparing to related end-use applications of GFRP wastes in cementitious based concrete materials, the proposed solution overcome some of the problems found, namely the possible incompatibilities arisen from alkalis-silica reaction and the decrease in the mechanical properties due to high water-cement ratio required to achieve the desirable workability. Obtained results were very promising towards a global cost-effective waste management solution for GFRP industrial wastes and end-of-life products that will lead to a more sustainable composite materials industry.

A fuzzified systematic adjustment of the robotic Darwinian PSO

The Darwinian Particle Swarm Optimization (DPSO) is an evolutionary algorithm that extends the Particle Swarm Optimization using natural selection to enhance the ability to escape from sub-optimal solutions. An extension of the DPSO to multi-robot applications has been recently proposed and denoted as Robotic Darwinian PSO (RDPSO), benefiting from the dynamical partitioning of the whole population of robots, hence decreasing the amount of required information exchange among robots. This paper further extends the previously proposed algorithm adapting the behavior of robots based on a set of context-based evaluation metrics. Those metrics are then used as inputs of a fuzzy system so as to systematically adjust the RDPSO parameters (i.e., outputs of the fuzzy system), thus improving its convergence rate, susceptibility to obstacles and communication constraints. The adapted RDPSO is evaluated in groups of physical robots, being further explored using larger populations of simulated mobile robots within a larger scenario.