Spatial-temporal data modelling and processing for personalised decision support

The purpose of this research is to undertake the modelling of dynamic data without losing any of the temporal relationships, and to be able to predict likelihood of outcome as far in advance of actual occurrence as possible. To this end a novel computational architecture for personalised ( individualised) modelling of spatio-temporal data based on spiking neural network methods (PMeSNNr), with a three dimensional visualisation of relationships between variables is proposed. In brief, the architecture is able to transfer spatio-temporal data patterns from a multidimensional input stream into internal patterns in the spiking neural network reservoir. These patterns are then analysed to produce a personalised model for either classification or prediction dependent on the specific needs of the situation. The architecture described above was constructed using MatLab© in several individual modules linked together to form NeuCube (M1). This methodology has been applied to two real world case studies. Firstly, it has been applied to data for the prediction of stroke occurrences on an individual basis. Secondly, it has been applied to ecological data on aphid pest abundance prediction. Two main objectives for this research when judging outcomes of the modelling are accurate prediction and to have this at the earliest possible time point. The implications of these findings are not insignificant in terms of health care management and environmental control. As the case studies utilised here represent vastly different application fields, it reveals more of the potential and usefulness of NeuCube (M1) for modelling data in an integrated manner. This in turn can identify previously unknown (or less understood) interactions thus both increasing the level of reliance that can be placed on the model created, and enhancing our human understanding of the complexities of the world around us without the need for over simplification. Read less Keywords Personalised modelling; Spiking neural network; Spatial-temporal data modelling; Computational intelligence; Predictive modelling; Stroke risk predictio

Spatial-temporal data modelling and processing for personalised decision support

The purpose of this research is to undertake the modelling of dynamic data without losing any of the temporal relationships, and to be able to predict likelihood of outcome as far in advance of actual occurrence as possible. To this end a novel computational architecture for personalised ( individualised) modelling of spatio-temporal data based on spiking neural network methods (PMeSNNr), with a three dimensional visualisation of relationships between variables is proposed. In brief, the architecture is able to transfer spatio-temporal data patterns from a multidimensional input stream into internal patterns in the spiking neural network reservoir. These patterns are then analysed to produce a personalised model for either classification or prediction dependent on the specific needs of the situation. The architecture described above was constructed using MatLab© in several individual modules linked together to form NeuCube (M1). This methodology has been applied to two real world case studies. Firstly, it has been applied to data for the prediction of stroke occurrences on an individual basis. Secondly, it has been applied to ecological data on aphid pest abundance prediction. Two main objectives for this research when judging outcomes of the modelling are accurate prediction and to have this at the earliest possible time point. The implications of these findings are not insignificant in terms of health care management and environmental control. As the case studies utilised here represent vastly different application fields, it reveals more of the potential and usefulness of NeuCube (M1) for modelling data in an integrated manner. This in turn can identify previously unknown (or less understood) interactions thus both increasing the level of reliance that can be placed on the model created, and enhancing our human understanding of the complexities of the world around us without the need for over simplification. Read less Keywords Personalised modelling; Spiking neural network; Spatial-temporal data modelling; Computational intelligence; Predictive modelling; Stroke risk predictio

Avaliação da aplicabilidade dos conceitos de construtibilidade nos serviços iniciais de empreendimentos de construção

TCC (graduação) - Universidade Federal de Santa Catarina. Centro Tecnológico. Engenharia Civil.A falta da integração entre a equipe de projeto e de execução em empreendimentos na indústria da construção civil é notória. Tal situação acarreta em deficiências na execução do projeto e muitas vezes aumento do custo devido a retrabalhos. Com o intuito de amenizar tais problemas, surge o conceito de construtibilidade, que aborda a facilidade de construção de uma edificação. Este trabalho tem como base uma revisão bibliográfica que aborda variados estudos, principalmente internacionais. Estes apresentam diversos princípios e diretrizes para a aplicação da construtibilidade, levantando os benefícios dessa aplicação, como aumento de produtividade, aumento da qualidade e segurança do serviço, melhoria da relação interpessoal da equipe, entre outros. Além disso, existem métodos com o intuito de se realizar a análise da construtibilidade, sendo métodos práticos e capazes de mensurar as propriedades de construtibilidade de projetos. Dentre os métodos existentes de análise de construtibilidade na literatura, dois foram escolhidos para serem detalhados a fim de se entender quais considerações foram abordadas para a quantificação final da pontuação de construtibilidade de um projeto. Foi observado que algumas etapas presentes em obras de construção civil não foram consideradas em tal quantificação, então foi estudado o motivo para tal consideração. Foram definidas três etapas a serem abordadas pelo trabalho: canteiro de obras, movimentação de terra e fundações, sendo levantados os aspectos influentes em cada uma separadamente para uma posterior comparação com os métodos citados. Após análise entre as etapas e os métodos, foi concluído que os métodos não poderiam ser aplicados àquelas etapas em específico por apresentarem características distintas, mas que outros aspectos de construtibilidade ainda poderiam ser considerados para as mesmas. Por fim, foi sugerida a consideração de outros aspectos na quantificação de construtibilidade de projetos para essas etapas, como princípios de construtibilidade que possam ser aplicados como soluções.The lack of integration between the design and construction stages in the construction industry is remarkable. Such situation leads to deficiencies in project execution and cost increases due to rework. In order to soften such problems, the concept of constructability comes up, which addresses the ease of construction of a building. This work addresses several studies, mainly international, that present principles and guidelines for constructability application, raising the benefits of its application, such as productivity rise, service quality and safety improvement, staff interpersonal relationships improvement, among others. In addition, there are methods capable of performing a constructability analysis, being a practical way to measure the constructability properties of projects. Among the already existing methods of constructability analysis in the literature, two of them were chosen to be detailed in order to understand what was considered for the final quantification of the constructability score of a project. It was observed that some stages in civil construction works were not considered in such quantification, so the reason for such consideration was studied. Three phases were defined to be studied in this work: site layout, earthmoving and foundations, raising the influential aspects in each one separately for a later comparison with the mentioned methods. After analysis between the phases and the methods, it was concluded that the methods could not be applied to those specific phases because of their different characteristics. However, other aspects of constructability could still be considered. Finally, it was suggested to consider other aspects in the quantification of constructability of projects for these stages, such as constructability principles and guidelines that could be applied as solutions