Model reduction for nonlinear aeroelasticity using the Discrete Empirical Interpolation Method

A novel surrogate model is proposed in lieu of computational fluid dynamic (CFD) code for fast nonlinear aerodynamic modeling. First, a nonlinear function is identified on selected interpolation points defined by discrete empirical interpolation method (DEIM). The flow field is then reconstructed by a least square approximation of flow modes extracted by proper orthogonal decomposition (POD). The proposed model is applied in the prediction of limit cycle oscillation for a plunge/pitch airfoil and a delta wing with linear structural model, results are validate against a time accurate CFD-FEM code. The results show the model is able to replicate the aerodynamic forces and flow fields with sufficient accuracy while requiring a fraction of CFD cost.

A generalized fuzzy linguistic model for predicting component concentrations in an optical gas sensing system

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NO_x, SO₂ etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

Atratividade em Clusters Comerciais: Um Estudo Comparativo de Dois Clusters da Cidade de São Paulo

O presente trabalho teve como objetivo a identificação de atributos relacionados à atratividade de clientes em clusters comerciais, na percepção de consumidores. Partindo-se da atratividade de clientes para lojas, desenvolveu-se um construto de avaliação de atratividade de clientes para clusters comerciais. Por meio de estudo descritivo-quantitativo junto a 240 consumidores, em dois reconhecidos clusters comerciais, utilizando-se a técnica de PLS-PM (Partial Least Squares Path Modeling), avaliou-se a relação entre a atratividade de clientes (variável reflexiva) e as dimensões do mix varejista de clusters comerciais (variáveis latentes), a partir do tratamento de indicadores de efeitos observáveis. Como principais resultados, observou-se que: (1) atratividade está associada significativamente às variáveis latentes, sugerindo robustez do modelo; (2) condições de compra e preços são dimensões com maior associação à atratividade de clientes, embora lojas, produtos e atendimento apresentem relevância; e (3) localização apresentou-se como dimensão menos correlacionada à atratividade de clientes para ambos os clusters.

Analysis of the Market Potential of Syrian Organic Fruit and Vegetables for Exports to Germany

Syria has been a major producer and exporter of fresh fruit and vegetables (FFV) in the Arabic region. Prior to 2011, Syrian FFV were mainly exported to the neighbouring countries, the Gulf States and Northern Africa as well as to Eastern European countries. Although the EU is potentially one of the most profitable markets of high quality FFV (such as organic ones) in the world, Syrian exports of FFV to Western European countries like Germany have been small. It could be a lucrative opportunity for Syrian growers and exporters of FFV to export organic products to markets such as Germany, where national production is limited to a few months due to climatic conditions. Yet, the organic sector in Syria is comparatively young and only a very small area of FFV is certified according to EU organic regulations. Up to the author’s knowledge, little was known about Syrian farmers’ attitudes towards organic FFV production. There was also no study so far that explored and analysed the determining factors for organic FFV adoption among Syrian farmers as well as the exports of these products to the EU markets. The overarching aim of the present dissertation focused on exploring and identifying the market potential of Syrian exports of organic FFV to Germany. The dissertation was therefore concerned with three main objectives: (i) to explore if German importers and wholesalers of organic FFV see market opportunities for Syrian organic products and what requirements in terms of quality and quantity they have, (ii) to determine the obstacles Syrian producers and exporters face when exporting agricultural products to Germany, and (iii) to investigate whether Syrian farmers of FFV can imagine converting their farms to organic production as well as the underlying reasons why they do so or not. A twofold methodological approach with expert interviews and a farmer survey were used in this dissertation to address the abovementioned objectives. While expert interviews were conducted with German and Syrian wholesalers of (organic) FFV in 2011 (9 interviews each), the farmer survey was administrated with 266 Syrian farmers of FFV in the main region for the production of FFV (i.e. the coastal region) from November 2012 till May 2013. For modelling farmers’ decisions to adopt organic farming, the Theory of Planned Behaviour as theoretical framework and Partial Least Squares Structural Equation Modelling as the main method for data analysis were used in this study. The findings of this dissertation yield implications for the different stakeholders (governmental institutions and NGOs, farmers, exporters, wholesalers, etc.) who are interested in prompting the Syrian export of organic products. Based on the empirical results and a literature review, an action plan to promote Syrian production and export of organic products was developed which can help in the post-war period in Syria at improving the organic sector.

Job-demand for Learning and Job-related Learning: the Mediating Effect of Job Performance Improvement Initiatives

This study examined whether job-performance-improvementinitiatives mediate the relationship between individuals’ job-demand for learning and job-related learning. Data were obtained from 115 full-time employees in a diverse range of occupations. A partial least squares analysis revealed that job-performance-improvement-initiatives mediate partially the effects of job-demand for learning on job-related learning. Several implications for future research and policy are drawn from the findings.

Quantificação de açúcares com uma língua eletrónica: calibração multivariada com seleção de sensores

Este trabalho incide na análise dos açúcares majoritários nos alimentos (glucose, frutose e sacarose) com uma língua eletrónica potenciométrica através de calibração multivariada com seleção de sensores. A análise destes compostos permite contribuir para a avaliação do impacto dos açúcares na saúde e seu efeito fisiológico, além de permitir relacionar atributos sensoriais e atuar no controlo de qualidade e autenticidade dos alimentos. Embora existam diversas metodologias analíticas usadas rotineiramente na identificação e quantificação dos açúcares nos alimentos, em geral, estes métodos apresentam diversas desvantagens, tais como lentidão das análises, consumo elevado de reagentes químicos e necessidade de pré-tratamentos destrutivos das amostras. Por isso se decidiu aplicar uma língua eletrónica potenciométrica, construída com sensores poliméricos selecionados considerando as sensibilidades aos açucares obtidas em trabalhos anteriores, na análise dos açúcares nos alimentos, visando estabelecer uma metodologia analítica e procedimentos matemáticos para quantificação destes compostos. Para este propósito foram realizadas análises em soluções padrão de misturas ternárias dos açúcares em diferentes níveis de concentração e em soluções de dissoluções de amostras de mel, que foram previamente analisadas em HPLC para se determinar as concentrações de referência dos açúcares. Foi então feita uma análise exploratória dos dados visando-se remover sensores ou observações discordantes através da realização de uma análise de componentes principais. Em seguida, foram construídos modelos de regressão linear múltipla com seleção de variáveis usando o algoritmo stepwise e foi verificado que embora fosse possível estabelecer uma boa relação entre as respostas dos sensores e as concentrações dos açúcares, os modelos não apresentavam desempenho de previsão satisfatório em dados de grupo de teste. Dessa forma, visando contornar este problema, novas abordagens foram testadas através da construção e otimização dos parâmetros de um algoritmo genético para seleção de variáveis que pudesse ser aplicado às diversas ferramentas de regressão, entre elas a regressão pelo método dos mínimos quadrados parciais. Foram obtidos bons resultados de previsão para os modelos obtidos com o método dos mínimos quadrados parciais aliado ao algoritmo genético, tanto para as soluções padrão quanto para as soluções de mel, com R²ajustado acima de 0,99 e RMSE inferior a 0,5 obtidos da relação linear entre os valores previstos e experimentais usando dados dos grupos de teste. O sistema de multi-sensores construído se mostrou uma ferramenta adequada para a análise dos iii açúcares, quando presentes em concentrações maioritárias, e alternativa a métodos instrumentais de referência, como o HPLC, por reduzir o tempo da análise e o valor monetário da análise, bem como, ter um preparo mínimo das amostras e eliminar produtos finais poluentes.

Hyperspectral sensing to detect the impact of herbicide drift on cotton growth and yield

Yield loss in crops is often associated with plant disease or external factors such as environment, water supply and nutrient availability. Improper agricultural practices can also introduce risks into the equation. Herbicide drift can be a combination of improper practices and environmental conditions which can create a potential yield loss. As traditional assessment of plant damage is often imprecise and time consuming, the ability of remote and proximal sensing techniques to monitor various bio-chemical alterations in the plant may offer a faster, non-destructive and reliable approach to predict yield loss caused by herbicide drift. This paper examines the prediction capabilities of partial least squares regression (PLS-R) models for estimating yield. Models were constructed with hyperspectral data of a cotton crop sprayed with three simulated doses of the phenoxy herbicide 2,4-D at three different growth stages. Fibre quality, photosynthesis, conductance, and two main hormones, indole acetic acid (IAA) and abscisic acid (ABA) were also analysed. Except for fibre quality and ABA, Spearman correlations have shown that these variables were highly affected by the chemical. Four PLS-R models for predicting yield were developed according to four timings of data collection: 2, 7, 14 and 28 days after the exposure (DAE). As indicated by the model performance, the analysis revealed that 7 DAE was the best time for data collection purposes (RMSEP = 2.6 and R2 = 0.88), followed by 28 DAE (RMSEP = 3.2 and R2 = 0.84). In summary, the results of this study show that it is possible to accurately predict yield after a simulated herbicide drift of 2,4-D on a cotton crop, through the analysis of hyperspectral data, thereby providing a reliable, effective and non-destructive alternative based on the internal response of the cotton leaves.

Factores de correcção para os efeitos ambientais na quantidade e qualidade do leite em bovinos da raça frísia

A produção e qualidade do leite são influenciadas por factores ambientais como a nutrição, factores genéticos como a raça, e factores fisiológicos como a idade a idade ao parto ou o número de ordenhas diárias. Este trabalho teve por objectivo estimar factores de correcção para os efeitos ambientais que influenciam a quantidade e qualidade do leite com vista ao melhoramento genético dos animais. Para isso, foram utilizados os registos de 23897 contrastes leiteiros de vacas de raça Frísia, no período de 6 anos, recolhidos a partir dos dados da ANABLE. De acordo com os resultados, obtidos através do método dos quadrados mínimos, observa-se que para a produção de leite, gordura e proteína, todos os efeitos fixos de variação são significativos nas três características produtivas estudadas, pelo que se conclui que há interacção entre a idade da vaca ao parto e a produção e qualidade do leite, assim como, a época do ano em que ocorre o parto e o número de ordenhas diárias a que o animal está sujeito. ABSTRACT; Cow production and milk quality are influenced by environmental factors such as nutrition, by genetic factors as breed and physiological factors as age at calving or milking frequency. This study aimed to estimate correction parameters for environmental factors with influence on milk production and quality embodying genetic improvement. For this propose, a data base was used with information related to 23987 milk tests collected from official milk recording program. According to the results, where the at least square procedure was adopted, it shows that all the fixed effects of variation significantly affect the productive performances, so it can be concluded that there is a significant interaction between milking frequency, age at calving and season when it occurs, and milk production and quality.

Parcellation of fMRI datasets with ICA and PLS: a data driven approach

Inter-subject parcellation of functional Magnetic Resonance Imaging (fMRI) data based on a standard General Linear Model (GLM) and spectral clustering was recently proposed as a means to alleviate the issues associated with spatial normalization in fMRI. However, for all its appeal, a GLM-based parcellation approach introduces its own biases, in the form of a priori knowledge about the shape of Hemodynamic Response Function (HRF) and task-related signal changes, or about the subject behaviour during the task. In this paper, we introduce a data-driven version of the spectral clustering parcellation, based on Independent Component Analysis (ICA) and Partial Least Squares (PLS) instead of the GLM. First, a number of independent components are automatically selected. Seed voxels are then obtained from the associated ICA maps and we compute the PLS latent variables between the fMRI signal of the seed voxels (which covers regional variations of the HRF) and the principal components of the signal across all voxels. Finally, we parcellate all subjects data with a spectral clustering of the PLS latent variables. We present results of the application of the proposed method on both single-subject and multi-subject fMRI datasets. Preliminary experimental results, evaluated with intra-parcel variance of GLM t-values and PLS derived t-values, indicate that this data-driven approach offers improvement in terms of parcellation accuracy over GLM based techniques.

Desenvolvimento de método para discriminação entre marcas de uísque e identificação de adulteração por espectroscopia UV-Vis e PLS-DA

Dissertação (mestrado)—Universidade de Brasília, Instituto de Química, Programa de Pós-Graduação em Química, 2015.

O papel da partilha de conhecimento na relação entre confiança e compromisso organizacional

Mestrado em Ciências Empresariais

Quality evaluation of cortex berberidis from different geographical origins by simultaneous high performance liquid chromatography combined with statistical methods

Purpose: To develop an effective method for evaluating the quality of Cortex berberidis from different geographical origins. Methods: A simple, precise and accurate high performance liquid chromatography (HPLC) method was first developed for simultaneous quantification of four active alkaloids (magnoflorine, jatrorrhizine, palmatine, and berberine) in Cortex berberidis obtained from Qinghai, Tibet and Sichuan Provinces of China. Method validation was performed in terms of precision, repeatability, stability, accuracy, and linearity. Besides, partial least squares discriminant analysis (PLS-DA) and one-way analysis of variance (ANOVA) were applied to study the quality variations of Cortex berberidis from various geographical origins. Results: The proposed HPLC method showed good linearity, precision, repeatability, and accuracy. The four alkaloids were detected in all samples of Cortex berberidis. Among them, magnoflorine (36.46 - 87.30 mg/g) consistently showed the highest amounts in all the samples, followed by berberine (16.00 - 37.50 mg/g). The content varied in the range of 0.66 - 4.57 mg/g for palmatine and 1.53 - 16.26 mg/g for jatrorrhizine, respectively. The total content of the four alkaloids ranged from 67.62 to 114.79 mg/g. Moreover, the results obtained by the PLS-DA and ANOVA showed that magnoflorine level and the total content of these four alkaloids in Qinghai and Tibet samples were significantly higher (p < 0.01) than those in Sichuan samples. Conclusion: Quantification of multi-ingredients by HPLC combined with statistical methods provide an effective approach for achieving origin discrimination and quality evaluation of Cortex berberidis. The quality of Cortex berberidis closely correlates to the geographical origin of the samples, with Cortex berberidis samples from Qinghai and Tibet exhibiting superior qualities to those from Sichuan.

Estudo da homogeneidade e discriminação de madeiras através de espectroscopia de imagens, imagens digitais e ferramentas quimiométricas

Tese (doutorado)–Universidade de Brasília, Instituto de Química, Programa de Pós-Graduação em Química, 2016.

Interdependencies in Corporate Development: Relationship between Strategic Alliance and Acquisition Activities

A substantial amount of work in the field of strategic management has attempted to explain the antecedents and outcomes of organizational learning. Though multinational corporations simultaneously engage in various types of tasks, activities, and strategies on a regular basis, the transfer of organizational learning in a multi-task context has largely remained under-explored in the literature. To inform our understanding in this area, this dissertation aimed at synthesizing findings from two parallel research streams of corporate development activities: strategic alliances and acquisitions. Structured in the form of two empirical studies, this dissertation examines: 1) the strategic outcomes of alliance experience of previously allying partners in terms of subsequent acquisition attempts, and 2) the performance implications of prior alliance experience for acquisitions. The first study draws on the relational view of inter-organizational governance to explain how various deal-specific and dyadic characteristics of a partnership relate to partnering firms’ post-alliance acquisition attempts. This model theorizes on a variety of relational mechanisms to build a cohesive theory of inter-organizational exchanges in a multi-task setting where strategic alliances ultimately lead to a firm’s decision to commit further resources. The second study applies organizational learning theory, and specifically examines whether frequency, recency, and relatedness of different dimensions of prior alliances, beyond the dyad-level experience, relate to an acquirer’s superior post-acquisition performance. The hypotheses of the studies are tested using logistic and ordinary least square regressions, respectively. Results analyzed from a sample of cross-border alliance and acquisition deals attempted (for study I) and/or completed (for study II) during the period of 1991 to 2011 generally support the theory that relational exchange determines acquiring firms’ post alliance acquisition behavior and that organizational routines and learning from prior alliances influence a future acquirer’s financial performance. Overall, the empirical findings support our overarching theory of interdependency, and confirm the transfer effect of learning across these alternate, yet related corporate strategies of alliance and acquisition.

Internal market orientation and market/oriented behaviours

Purpose – The purpose of this empirical paper is to investigate internal marketing from a behavioural perspective. The impact of internal marketing behaviours, operationalised as an internal market orientation (IMO), on employees' marketing and other in/role behaviours (IRB) were examined. Design/methodology/approach – Survey data measuring IMO, market orientation and a range of constructs relevant to the nomological network in which they are embedded were collected from the UK retail managers. These were tested to establish their psychometric properties and the conceptual model was analysed using structural equations modelling, employing a partial least squares methodology. Findings – IMO has positive consequences for employees' market/oriented and other IRB. These, in turn, influence marketing success. Research limitations/implications – The paper provides empirical support for the long/held assumption that internal and external marketing are related and that organisations should balance their external focus with some attention to employees. Future research could measure the attitudes and behaviours of managers, employees and customers directly and explore the relationships between them. Practical implications – Firm must ensure that they do not put the needs of their employees second to those of managers and shareholders; managers must develop their listening skills and organisations must become more responsive to the needs of their employees. Originality/value – The paper contributes to the scarce body of empirical support for the role of internal marketing in services organisations. For researchers, this paper legitimises the study of internal marketing as a route to external market success; for managers, the study provides quantifiable evidence that focusing on employees' wants and needs impacts their behaviours towards the market. © 2010, Emerald Group Publishing Limited