This PhD thesis focuses on improving the limit of detection (LOD) of Raman biosensors by using surface enhanced Raman scattering (SERS) and/or hollow core photonic crystal fibers (HC-PCF), in conjunction with statistical methods. Raman spectroscopy is a multivariate phenomenon that requires statistical analysis to identify the relationship between recorded spectra and the property of interest. The objective of this research is to improve the performance of Raman biosensors using SERS techniques and/or HC-PCF, by applying partial least squares (PLS) regression and principal component analysis (PCA). I began my research using Raman spectroscopy, PLS analysis and two different validation methods to monitor heparin, an important blood anti-coagulant, in serum at clinical levels. I achieved lower LOD of heparin in serum using the Test Set Validation (TSV) method. The PLS analysis allowed me to distinguish between weak Raman signals of heparin in serum and background noise. I then focused on using SERS to further improve the LOD of analytes, and accomplished simultaneous detection of GLU-GABA in serum at clinical levels using the SERS and PLS models. This work demonstrated the applicability of using SERS in conjunction with PLS to measure properties of samples in blood serum. I also used SERS with HC-PCF configuration to detect leukemia cells, one of the most recurrent types of pediatric cancers. This was achieved by applying PLS regression and PCA techniques. Improving LOD was the next objective, and I was able to achieve this by improving the PLS model to decrease errors and remove outliers or unnecessary variables. The results of the final optimized models were evaluated by comparing them with the results of previous models of Heparin and Leukemia cell detection in previous sections. Finally, as a clinical application of Raman biosensors, I applied the enhanced Raman technique to detect polycystic ovary syndrome (PCOS) disease, and to determine the role of chemerin in this disease. I used SERS in conjunction with PCA to differentiate between PCOS and non-PCOS patients. I also confirmed the role of chemerin in PCOS disease, measured the level of chemerin, a chemoattractant protein, in PCOS and non-PCOS patients using PLS, and further improved LOD with the PLS regression model, as proposed in previous section.

Metabolomics is a post genomic field of research concerned with the study of low molecular weight compounds within a biological system permitting the investigation of the metabolite differences between natural and perturbed systems (such as cells, organs and tissues). Rapid identification and discrimination of biological samples based upon metabolic differences and physiological status in microbiology, mammalian systems (particularly for disease diagnosis), plants and food science is highly desirable. Volatile organic compound (VOC) profiling is a novel area of research where the composition of the VOCs emitted by the biological samples can be correlated to its origin and physiological status. The aim of this project was to investigate the applicability of VOC profiling as a potential complementary tool within metabolomics.In this project the discrimination of bacteria using a novel gas phase separation method was investigated and the development of VOC-based profiling tools for the collections of VOCs emitted from biological samples was also studied. The optimisation and validation of a high throughput method for VOC analysis was achieved and this was used to assess wound healing.VOC metabolite profiling was further extended to the discrimination of S. typhimurium contaminated meat; the study was conducted in parallel with metabolite profiling analysis for the analysis of non-volatile small molecules. Finally, enhanced vibrational spectroscopic techniques were applied to the characterisation and screening of dye molecules in contaminated foodstuffs using Raman spectroscopy. This thesis clearly demonstrates that VOC metabolic profiling is a complementary tool within the metabolomics toolbox, one of its great attractions is that it permits the characterisation of biological samples in a rapid and non-invasive manner. The technique provides detailed chemical information regarding the VOC composition present above the headspace of the sample and can be used to understand its physiological status and biological origin. VOCs metabolite profiling will become a valuable tool for non-invasive analysis of many biological systems. Raman spectroscopy is a sensitive and non-destructive technique which can generate detailed chemical and structural information regarding the analyte under investigation with little or no sample preparation needed. The effect of the weak Raman signal can be significantly amplified by coupling the analyte molecule to surfaces of nanoparticles and demonstrated that it is ideal for analysing aqueous dye solutions in a quantitative manner.

Control predictivo basado en modelos (MPC) es una metodología de control ampliamente utilizada en la industria por su habilidad para controlar procesos multivariable con restricciones en sus entradas y sus salidas. Se distinguen dos fases en la implementación de MPC: identificación y control. El propósito de esta tesis es doble: realizar contribuciones en la identificación para MPC y proponer una nueva metodología de control MPC. La respuesta en bucle cerrado de una implementación de MPC depende, en gran medida, de la capacidad de predicción del modelo; luego la identificación del modelo es un punto crucial en MPC y la parte que a menudo exige la mayor parte del tiempo del proyecto. El primer objetivo que cubre la tesis es la identificación para MPC. Puesto que un modelo es una aproximación del comportamiento de un proceso, dicha aproximación se puede hacer teniendo en cuenta el fin que se le va a dar al modelo. En MPC, el modelo se utiliza para realizar predicciones dentro de una ventana futura, luego la identificación para MPC (MRI) tiene en cuenta dicho uso del modelo y considera los errores de predicción dentro de dicha ventana para el ajuste de los parámetros del modelo. En esta tesis, se cubren tres temas dentro de MRI. Primero se define MRI y las distintas formas de abordarlo. Luego se compara en términos de MRI el ajuste de un modelo con múltiples entradas y múltiples salidas con el ajuste de varios modelos con múltiples entradas y una salida concluyendo que el ajuste de un único modelo con múltiples entradas y múltiples salidas proporciona mejores resultados en términos de MRI para horizontes de predicción lo suficientemente grandes. Por último, se propone el algoritmo PLS-PH para implementar MRI con modelos paramétricos en el caso de correlación en los datos de identificación. PLS-PH es un método de optimización numérica por búsqueda lineal basado en PLS (mínimos cuadrados parciales). Se muestra en un ejemplo como PLS-PH es capaz de proporcionar mejores modelos que las técnicas convencionales de MRI en modelos paramétricos en el caso de correlación en los datos de identi ficación. Una vez obtenido el modelo se puede formular el controlador predictivo. En esta tesis se propone LV-MPC, un controlador predictivo para procesos continuos que implementa la optimización en el espacio de las componentes principales. / Laurí Pla, D. (2012). MPC: Relevant Identification and Control in the Latent Variable Space [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/15178 / Palancia

Purpose: In literature, there is not sufficient research of the impact of Enterprise Resource planning (ERP) usage on firm performance for small and medium sized Swedish companies. Therefore, the purpose of this paper is to provide clarifications regarding this topic by investigating two research questions: What factors drive ERP usage in small- and medium- sized Swedish enterprises? Does ERP usage affect Firm Performance in small- and medium- sized Swedish enterprises?  Design/Methodology/Approach: To approach our research questions 10 hypotheses are constructed based on previous studies. Further, to gather the data required to test these hypotheses, a survey was sent to 1000 Swedish small- and medium-size enterprises which generated 100 responses. The data was later analyzed using a Partial Least Square Structural Model.  Findings: The first outcome of this study is that the main drivers of ERP usage in Swedish small- and medium-sized enterprises are Top Management Support and Effective Project Management. The second outcome is that ERP usage has a significant positive impact on Firm Performance.  Contribution/implication: The main practical contribution derived from our results is that small- and medium-size firms should focus on Top management support and Effective project management in order to increase their ERP usage, which in turn could lead to greater levels of firm performance. In the theoretical spectrum, we contribute to the literature by enhancing the importance of effective project management not previously tested in the ERP usage context and by adding question marks regarding the effect of certain variables on ERP usage.

Táto diplomová práca sa zaoberá klasifikáciou kovov pomocou spektroskopie laserom indukovanej plazmy (LIBS) a chemometrických metód. Práca poskytuje prehľad o štúdiách na danú tému. Sú vybrané tri široko používané chemometrické klasifikačné metódy: "Soft Independent Modeling of Class Analogy" (SIMCA), "Partial Least Squares Discriminant Analysis" (PLS-DA) a variácia umelých neurónových sietí (ANN), "Feedforward Multilayer Perceptron". Rôzne prístupy k prieskumovej analýze su tiež preskúmané. Metódy sú stručne opísané. Následne sú klasifikátory experimentálne porovnané.

In 2011 one-third of South African organisations did not intend to adopt cloud computing services because IT decision-maker lacked understanding of the related concepts and benefits (Goldstuck, 2011). This research develops a media-oriented model to examine the adoption of these services in South Africa. The model uses the technology acceptance model (TAM) and innovation diffusion theory (IDT) to develop variables that are considered determinants of adoption including trialability, complexity of understanding, perceived risk, perceived ease of use and perceived usefulness.An electronic survey was sent to 107 IT decision-makers. Over 80% of the respondents were C-suite executives. The Partial Least Squares (PLS) method was chosen to depict and test the proposed model. PLS is superior to normal regression models and is a second generation technique. The data analysis included evaluating and modifying the model, assessing the new measurement model, testing the hypotheses of the model structure and presenting the structural model.The research found that media, experts and word of mouth mitigate perceived risks including bandwidth, connectivity and power. Furthermore, trialability and perceived usefulness were affected by social influence, as well as influencing adoption. The results enable service providers and marketers to develop product roadmaps and pinpoint media messages. / Dissertation (MBA)--University of Pretoria, 2012. / Gordon Institute of Business Science (GIBS) / unrestricted

Orientador: Alan Rodrigo Panosso / Resumo: O bioma Cerrado tem sofrido modificações nas últimas décadas, perdendo parte de sua cobertura original para culturas anuais, pastagens e florestas plantadas, tendo diferentes usos da terra. Neste trabalho, foram estudadas as interações entre os diferentes usos da terra em áreas do bioma Cerrado, bem como da dinâmica de carbono no solo e os fatores latentes formados pelos atributos físicos e químicos do solo, por meio de modelos de análise de equações estruturais, com auxílio das técnicas estatísticas multivariadas. Ensaios experimentais foram conduzidos na Fazenda de Ensino, Pesquisa e Extensão (FEPE/UNESP), localizada em Selvíria-MS: Floresta plantada de Eucalipto - Eucalyptus camaldulensis (EU); Floresta plantada de Pinus - Pinus caribaea var. hondurensis (PI); Sistema silvipastoril (SI) com uma área contendo floresta plantada de Aroeira (Myracrodruon urundeuva) e capim Braquiária (Brachiaria decumbens, e Mata Nativa (MN). Foi estudado os efeitos dos atributos físicos: densidade do solo (Ds), macroporosidade (Ma), microporosidade (Mi) e químicos com ênfase especial nas propriedades relacionadas à dinâmica do carbono no solo: matéria orgânica do solo (MO), estoque de carbono do solo (EstC), estoque de nitrogênio do solo (EstN), relação carbono e nitrogênio (C/N) e o grau de humificação da matéria orgânica do solo (HLIFS). A emissão de CO2 do solo (FCO2), umidade e temperatura do solo foram avaliados nas áreas durante três períodos distintos (definidos a partir do regime hídr... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The Cerrado biome has undergone modifications in recent decades, losing part of its original cover to annual crops, pastures and planted forests, having different land uses. In this work, the interactions between the different land uses in areas of the Cerrado biome, as well as the soil carbon dynamics and the latent factors formed by the physical and chemical attributes of the soil through structural equation analysis models were studied. with the aid of multivariate statistical techniques. Experimental tests were performed at the Teaching, Research and Extension Farm (FEPE / UNESP), located in Selvíria-MS: Eucalyptus planted forest Eucalyptus camaldulensis (EU); Planted Pine Forest - Pinus caribaea var. hondurensis (PI); Silvipastoral system (SI) with an area containing Aroeira (Myracrodruon urundeuva) and native grass (Brachiaria decumbens), and Mata Nativa (MN). The effects of physical attributes: soil density (Ds), macroporosity (Ma), microporosity (Mi) and chemicals attributes were studied with special emphasis on properties related to soil carbon dynamics: soil organic matter (MO), soil carbon stock (EstC), soil nitrogen stock (EstN), carbon and nitrogen ratio (C / N), and the degree of soil organic matter (HLIFS). Soil CO2 emission (FCO2), soil moisture and temperature were evaluated in the areas during three distinct periods (defined from the water regime observed in the areas) called P1, P2 and P3, season rainfall, drought and transition, respectively, between March... (Complete abstract click electronic access below) / Doutor

<p>QCR 20161026</p>

Bakgrund. I nio av tio byggprojekt överstiger kostnaderna budgeten. För att anpassa sig till dagens projektbaserade organisationsklimat krävs det att organisationer blir mer adaptiva för att kunna hantera förändringar orsakade av extern turbulens. På grund av den ökade förändringstakten räcker inte projektledarpraxis till för ett effektivt projekt. Tidigare forskning föreslår att psykosociala aspekter, till exempel intern arbetsmotivation, har en växande betydelse för projekteffektivitet.   Syfte. Studien ämnar utreda projekteffektivitet i byggprojekt och syftet är att bekräfta de hypoteser om att projektledarpraxis eller psykosociala aspekter som prediktorer av ett effektivt projekt som presenterats i tidigare litteratur.   Metod. Baserat på syftet användes en enkät för att skapa ramverket för analysen. Enkätundersökningen distribuerades till 230 personer i en projektledande roll på ett stort byggföretag i Sverige. Dessa personer förväntas besitta stor kunskap i projektet samt påverkar i allra största grad projektets utfall. Slutligen erhölls ett urval på 82 projektledare som användes i PLS-SEM (Partial least square – Structural equation model) analys som studien applicerar.   Resultat. Resultatet visar att det inte finns något signifikant samband mellan upplevd projektledarpraxis och projekteffektivitet, medan upplevda psykosociala aspekter visar ett positivt samband med projekteffektivitet. Upplevd projektledarpraxis visar däremot ett positivt samband med projekteffektivitet när psykosociala aspekter agerar som mediator.   Slutsats och framtida rekommendationer. En slutsats som fastställs är att fokus bör flyttas från de snarare tekniska och hårda faktorerna till de psykosociala faktorerna. Projekten är, för att uppnå projekteffektivitet, beroende av personerna i projektet och deras psykosociala tillstånd för att ge praxisaktiviteterna en mening. Slutligen konstateras det att projekteffektivitetsområdet är ett komplext område som kräver ytterligare forskning. Förslagsvis bör studien testas på fler industrier där frekvensen av samt praxisaktiviteterna skiljer sig. Organisationer förespråkar olika ramverk vilket kan ge divergens i praxisaktiviteterna och projekteffektiviteten. / Background. The costs exceed the budget in nine out of ten construction projects. To be able to adapt to internal changes, affected by external turbulence, in the project-based organization climate, the organizations has to become more adaptive. Due to the increased rate of change, the project manager practice is not enough to reach project efficiency. Former work suggests that, for example, internal work motivation has an increased importance in project efficiency.   Objective. The study aims to investigate the project efficiency in construction projects and the objective is to confirm the hypothesis that project manager practice and soft practice serves as predictors for project efficiency, as former literature suggests.   Methods. Based on the objective, a survey was used to create a framework and gather data. The survey was distributed to 230 persons with a project manager role in a large construction company in Sweden. These persons are expected to possess great knowledge in the project and does to a great extent affect the outcome of the project. A sample of 82 project leaders was used in the PLS-SEM (Partial least square – Structural equation model) analysis method that was applied in the study.   Results. The result shows that there was no significant relationship between experienced project leader practice and project efficiency, while experienced soft practice showed a positive relationship with project efficiency. However, experienced project practice showed a positive relationship when soft practice acted as a mediator.   Conclusions and future work. It is concluded that focus should be shifted from the more technical parts and factors of the project to soft practices. To achieve efficiency, projects are dependent of the individuals in the project and their social qualities to give the project practice a meaning. Finally, the study concludes that the area of project efficiency is complex and is in need of further research. A suggestion is that the study is tested on several industries where the frequency of the used practices differs. Different organizations advocate different frameworks which might give a divergence in the practice activities and project efficiency.

This thesis sets out to address the challenges with the comparison of Amphetamine material in determining whether they originate from the same source or different sources using pairwise ratios of peak areas within each chromatogram of material and then modeling the difference between the ratios for each comparison as a basis for evaluation. The evaluation of an existing method that uses these ratios to determine the sum of significant differences between each comparison of material that is provided is done. The outcome of this evaluation suggests that there the distributions for comparison of samples originating from the same source and the comparison of samples originating from different sources have an overlap leading to uncertainties in conclusions. In this work, the differences between the ratios of peak areas have been modeled using a feature-based approach. Because the feature space is quite large, Discriminant Analysis methods such as Linear Discriminant Analysis (LDA) and Partial least squares Discriminant Analysis (PLS-DA) have been implemented to perform classification by dimensionality reduction. Another popular method that works on the principle of nearest centroid classifier called as Nearest shrunken centroid is also applied that performs classification on shrunken centroids of the features. The results and analysis of all the methods have been performed to obtain the classification results for classes +1 (samples originate from the same source) and  ́1 (samples originate from different sources). Likelihood ratios of each class for each of these methods have also been evaluated using the Empirical Cross-Entropy (ECE) method to determine the robustness of the classifiers. All three models seem to have performed fairly well in terms of classification with LDA being the most robust and reliable with its predictions.