44 resultados para Scaling-up


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This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

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This study describes the change of the ultraviolet spectral bands starting from 0.1 to 5.0 nm slit width in the spectral range of 200–400 nm. The analysis of the spectral bands is carried out by using the multidimensional scaling (MDS) approach to reach the latent spectral background. This approach indicates that 0.1 nm slit width gives higher-order noise together with better spectral details. Thus, 5.0 nm slit width possesses the higher peak amplitude and lower-order noise together with poor spectral details. In the above-mentioned conditions, the main problem is to find the relationship between the spectral band properties and the slit width. For this aim, the MDS tool is to used recognize the hidden information of the ultraviolet spectra of sildenafil citrate by using a Shimadzu UV–VIS 2550, which is in the world the best double monochromator instrument. In this study, the proposed mathematical approach gives the rich findings for the efficient use of the spectrophotometer in the qualitative and quantitative studies.

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In this paper, we apply multidimensional scaling (MDS) and parametric similarity indices (PSI) in the analysis of complex systems (CS). Each CS is viewed as a dynamical system, exhibiting an output time-series to be interpreted as a manifestation of its behavior. We start by adopting a sliding window to sample the original data into several consecutive time periods. Second, we define a given PSI for tracking pieces of data. We then compare the windows for different values of the parameter, and we generate the corresponding MDS maps of ‘points’. Third, we use Procrustes analysis to linearly transform the MDS charts for maximum superposition and to build a global MDS map of “shapes”. This final plot captures the time evolution of the phenomena and is sensitive to the PSI adopted. The generalized correlation, the Minkowski distance and four entropy-based indices are tested. The proposed approach is applied to the Dow Jones Industrial Average stock market index and the Europe Brent Spot Price FOB time-series.

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This paper studies the statistical distributions of worldwide earthquakes from year 1963 up to year 2012. A Cartesian grid, dividing Earth into geographic regions, is considered. Entropy and the Jensen–Shannon divergence are used to analyze and compare real-world data. Hierarchical clustering and multi-dimensional scaling techniques are adopted for data visualization. Entropy-based indices have the advantage of leading to a single parameter expressing the relationships between the seismic data. Classical and generalized (fractional) entropy and Jensen–Shannon divergence are tested. The generalized measures lead to a clear identification of patterns embedded in the data and contribute to better understand earthquake distributions.

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Proceedings of the 12th Conference on Dynamical Systems -Theory and Applications

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This paper studies the impact of the energy upon electricity markets using Multidimensional Scaling (MDS). Data from major energy and electricity markets is considered. Several maps produced by MDS are presented and discussed revealing that this method is useful for understanding the correlation between them. Furthermore, the results help electricity markets agents hedging against Market Clearing Price (MCP) volatility.

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This paper applies multidimensional scaling techniques and Fourier transform for visualizing possible time-varying correlations between 25 stock market values. The method is useful for observing clusters of stock markets with similar behavior.

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Health promotion in hospital environments can be improved using the most recent information and communication technologies. The Internet connectivity to small sensor nodes carried by patients allows remote access to their bio-signals. To promote these features the healthcare wireless sensor networks (HWSN) are used. In these networks mobility support is a key issue in order to keep patients under realtime monitoring even when they move around. To keep sensors connected to the network, they should change their access points of attachment when patients move to a new coverage area along an infirmary. This process, called handover, is responsible for continuous network connectivity to the sensors. This paper presents a detailed performance evaluation study considering three handover mechanisms for healthcare scenarios (Hand4MAC, RSSI-based, and Backbone-based). The study was performed by simulation using several scenarios with different number of sensors and different moving velocities of sensor nodes. The results show that Hand4MAC is the best solution to guarantee almost continuous connectivity to sensor nodes with less energy consumption.

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Atualmente, o contexto de atuação das empresas tem sido cada vez mais desafiante dado o binómio de competitividade e crise financeira. Desta forma, a exploração de novas soluções e identificação de lacunas ou desequilíbrios no mercado torna-se imperial para o desenvolvimento das novas entidades. É com base nesta premissa que emerge o conceito de Start-Up, sendo o seu propósito o desenvolvimento de novos produtos e modelos de negócios inovadores. Como resultado, estas empresas tornam-se num elemento revitalizador do tecido económico dos países em que estão inseridas. De forma a possibilitar a potenciação das atividades desenvolvidas por estas entidades é crucial a identificação das diversas fontes de recursos financeiros e as consequentes contrapartidas exigidas. No entanto, dado o seu caráter inovador obviamente que vários são os riscos lhes estão associados, pelo que estas empresas deparam-se com mais dificuldades no momento de acesso aos recursos financeiros que pretendem. Desta forma, a presente dissertação analisa as tendências de financiamento das Start-Up tendo como motivação o facto desta temática ainda não se encontrar devidamente explorada e dado o desconhecimento desta realidade em Portugal. Neste sentido, e aliando a problemática existente com a motivação para a concretização da presente dissertação foram realizados um conjunto de inquéritos os quais foram aliados com o desenvolvimento de modelos empíricos multivariados aplicados aos dados seccionais e em painel. Os resultados alcançados com a investigação empírica permitiram concluir a influência de um conjunto de variáveis bem como justificar a orientação e estrutura de financiamento das Start-Up portuguesas. Das variáveis investigadas de ressalvar a influência significativa da Dimensão da Empresa, Estrutura de Ativos e Forma Legal no financiamento das Start-Up nacionais.