Essa tese tem como objetivo o desenvolvimento de métricas para a mensuração dos fatores determinantes da competitividade da economia de países. Parte-se de uma noção estrutural e sistêmica da competitividade, baseada nos estudos de autores relacionados à teoria evolucionária do desenvolvimento econômico, para conceituar competitividade nacional como uma capacidade de os países gerarem competências que darão suporte a seu processo competitivo dinâmico. O debate sobre a criação de métricas de competitividade nacional vem sendo travado nas ciências econômicas e de gestão, e indicam a necessidade de incorporar a mensuração de fatores relacionados à dinâmica da competição no mercado internacional e, principalmente, seus determinantes. Dessa forma, esse trabalho se insere no debate sobre a dinâmica da competitividade nacional baseada em competências para a emergência de vantagens competitivas nas economias nacionais e setores industriais. A proposta aqui desenvolvida consiste na construção de um painel de métricas de indicadores organizado em dimensões de fatores que afetam o desenvolvimento de competências nos países. Metodologias de análise estatística multivariada de dados serão utilizadas para a análise dos dados e, por fim, análises comparativas baseadas em correlações canônicas serão feitas para testar sua validade. / This thesis aims to develop metrics to measure the determinants of competitiveness of national economies. It is based on a structural and systemic notion of competitiveness, based on the studies of authors related to the evolutionary theory of economic development, to conceptualize national competitiveness as the capacity of countries to generate capabilities that will support its dynamic competitive process. The debate on the creation of national competitiveness metrics has been caught in fields of economics and management, and indicates the need to incorporate the measurement of factors related to the dynamics of competition in the international market and especially its determinants. Thus, this work is part of the debate on the dynamics of national competitiveness based on capabilities for the emergence of competitive advantages in the domestic and industrial sectors of economies. The proposal developed here involves the construction of a spreadsheet of indicators organized into dimensions of factors that affect the development of capabilities for competitiveness in countries. Multivariate statistical methods are used to analyze the data and finally comparative analysis based on canonical correlations are made to test their validity. s, multivariate statistical analysis.

The presented thesis discusses the basic analysis methods of arteriovelocitograms. The core of this work rests in classification of signals and contribution to possibilities of noninvasive diagnostic methods for evaluation patients with peripheral ischemic occlusive arterial disease. The classification employs multivariate statistical methods and principles of neural networks. The data processing works with an angiographic verified set of arteriovelocitogram dates. The digital subtraction angiography classified them into 3 separable classes in dependence on degree of vascular stenosis. Classification AVG signals are represented in the program by the 6 parameters that are measured on 3 different places on each patient’s leg. Evaluation of disease appeared to be a comprehensive approach at signals acquired from whole patient’s leg. The sensitivity of clustering method compared with angiography is between 82.75 % and 90.90 %, specificity between 80.66 % and 88.88 %. Using neural networks sensitivity is in range of 79.06 % and 96.87 %, specificity is in range of 73.07 % and 91.30 %.

Water quality monitoring (WQM) is crucial for managing and protecting riverine ecosystems. There has been a plethora of methods to select the monitoring sites, water quality parameters (WQPs), and monitoring frequencies; however, no standard method or strategy has been accepted for the river systems. Water managers have faced difficulties in adopting appropriate WQM network design methods to their local boundary conditions, monitoring objectives, monitoring costs, and legal regulations. With the elevated cost and time consumption of monitoring, approaches to evaluate and redesign the monitoring networks based on monitoring goal achievements are crucial for water managers. Hence, the overall aim of this thesis is to develop and employ a reliable yet straightforward approach to optimise and quantify the effectiveness of the WQM network in rivers. The objectives are to (i) identify the commonly used methods and the boundary conditions to apply these methods in assessing and designing of WQM networks in rivers; (ii) optimise river WQM network design based on compliance criteria; (iii) optimise river WQM network design based on the trade-offs between information provided by the monitoring network versus the monitoring expenses. A systematic review of the commonly used design methods and their resulting monitoring setups in Chapter 2 shows that multivariate statistical analysis (MVA) is a promising tool to contract the number of monitoring sites and water quality parameters. Most of the reported studies often overlook small streams and trace pollutants such as heavy metals and organic microcontaminants in the analysis. Data availability and expertise’s judgments seem to affect the selection of design methods rather than river size and the extent of the monitoring networks. The commonly found statistical methods are applied to the case study of the Freiberger Mulde (FM) river basin in eastern Germany to optimise its current monitoring network. Chapter 3 dedicates to redesign the monitoring network for compliance monitoring purposes. In Chapter 3, 82 non-biological parameters are initially screened and analysed for their violations to the environmental quality standards. The subsequent result suggests that polycyclic aromatic hydrocarbons, heavy metals, and phosphorus have been the abundant stressors that caused more than 50% of the streams in the FM river basin failing to achieve good status. The proposed approach using hierarchical cluster analysis and weighted violation factor from 22 relevant WQPs allows a reduction of 42 monitoring sites from the current 158 sites. The Mann-Kendall trend test recommends an increase in monitoring frequency of the priority substances by 12 times per annual, and a decrease in the number of sampling events for metals and general physicochemical parameters by quarterly. Overall, the results suggest that the authorities of the Saxony region should develop proper management measures targeting heavy metals and organic micropollutants to be able to achieve good WQ status by 2027 at the latest. In Chapter 4, regularly monitoring parameters with less than 15% of censored data are analysed. A combination of principal component analysis and Pearson’s correlation analysis allows the identification of 14 critical parameters that are responsible for explaining 75.1% of data variability in the FM river basin. Weathering processes, historical mining, wastewater discharges, and seasonality have been the leading causes of water quality variability. Both sampling locations and periods are observed, with the resulting mineral contents vary between locations, and the organic and oxygen content differs depending on the time period that was monitored. The monitoring costs are estimated for one monitoring event and based on laboratory, transportation, and sampling costs. The results show that under the current monitoring-intense conditions, preserving monitoring variables rather than sites seems to be more economical than the opposite practice. The current study provides and employs two statistical approaches to optimise the WQM network for the FM river basin in eastern Germany. The proposed methods can be of interests to other river basins where the historical data are available, and the monitoring costs become a constraint. The presented research also raises some concerns for future research regarding the applications of statistical methods to optimise WQM networks, which are presented in Chapter 5.

No description available.

The main goal of this thesis is to propose an evaluation method for visual interface design and more specifically for website design. The proposed visual design evaluation method is an adaptation of Preference Mapping (PM) techniques. It is based on overall preference ratings after multiple comparisons of alternative designs and on various multivariate statistical techniques for the analysis, visualization and interpretation of the resulting data. The suitability of the approach for visual interface design evaluation has been explored in four case studies involving overall 149 participants judging 51 websites. In each case study a different website domain was explored in order to examine whether the importance of certain design characteristics is context specific. Heterogeneity in preferences and perceptions was also studied showing that average construct scores are only representative for subsections of the participant sample. In order to aid the preference interpretation process additional data about study websites have been collected from three distinct sources: a) Subjective construct ratings provided by the participants after preference evaluation b) Descriptive attribute ratings obtained from trained expert panel on the same websites c) Objective measures of visual characteristics of the websites In each case study the potential of these types of measurements to explain preference variance has been investigated individually and in combination. The results showed that depending on the characteristics of each case study varying combinations of these types of data had the best explanatory power. A variety of methods (e.g. Internal and External PM) and statistical techniques (e.g. Principal Component Analysis (PCA), Generalized Procrustes Analysis (GPA) and Partial Least Squares (PLS)) have been used in order to summarize and visualize participant preference data of all case studies. In general, the method proposed in this thesis has several advantages over other visual design evaluation methods as for example use of standardized questionnaires. The method is flexible and can be used in various stages of design development but most importantly it allows for the identification of important visual design characteristics without ignoring the diversity that exist both among users and among website domains. These advantages have been demonstrated in the visual design evaluation studies presented in this thesis involving websites from four distinct domains. / Ο στόχος της παρούσας διατριβής είναι η πρόταση και ανάπτυξη μεθόδου αξιολόγησης διεπιφανειών χρήστη που θα λαμβάνει υπόψη τόσο τα αντικειμενικά χαρακτηριστικά σχεδιασμού, όσο και την υποκειμενική διάσταση που διέπει αξιολογήσεις με επίκεντρο τον χρήστη. Για την επίτευξη του στόχου αυτού αναπτύχθηκε μέθοδος αξιολόγησης, η οποία βασίζεται στην συγκριτική αξιολόγηση εναλλακτικών σχεδιασμών κατά την φάση συλλογής δεδομένων και στην χαρτογράφηση προτίμησης κατά την φάση ανάλυσης αποτελεσμάτων. Για την διερεύνηση της καταλληλότητας της προτεινόμενης μεθόδου αξιολόγησης, διεξήχθησαν τέσσερις μελέτες περίπτωσης κατά τις οποίες αξιολογήθηκαν συνολικά 51 ιστοσελίδες από 149 αξιολογητές. Κάθε μελέτη περίπτωσης διερευνούσε διαφορετική κατηγορία ιστοσελίδων και διαφορετικά σενάρια χρήσης της μεθόδου (π.χ. φάση προδιαγραφών, αξιολόγηση πρωτοτύπων κ.α.), έτσι ώστε να αξιολογηθεί η δυνατότητα της μεθόδου να εφαρμοστεί σε διαφορετικές συνθήκες. Σημαντικό πλεονέκτημα της προτεινόμενης μεθόδου είναι η δυνατότητα αναγνώρισης ετερογένειας απόψεων του δείγματος, η οποία σε άλλες μεθόδους αξιολόγησης θεωρείται θόρυβος στα δεδομένα και παραβλέπεται. Τα αποτελέσματα των αξιολογήσεων αναδεικνύουν σημαντική ετερογένεια αλλά και σχετική συμφωνία στις προτιμήσεις και αντιλήψεις των συμμετεχόντων. Με στόχο την ερμηνεία των αποτελεσμάτων από τα πειράματα αξιολόγησης διερευνήθηκαν τρεις πηγές δεδομένων πέρα από τις ταξινομήσεις προτίμησης από τους συμμετέχοντες σε όλες τις μελέτες περίπτωσης: α) αξιολογήσεις βάσει υποκειμενικών χαρακτηριστικών από τους ίδιους τους συμμετέχοντες που ταξινόμησαν τις ιστοσελίδες με βάση την προτίμηση τους β) αξιολογήσεις περιγραφικών και αντικειμενικών σχεδιαστικών χαρακτηριστικών από ομάδα εκπαιδευμένων εμπειρογνωμόνων γ) Αντικειμενικές μετρήσεις σχεδιαστικών χαρακτηριστικών με αυτόματα και ημιαυτόματα εργαλεία αναγνώρισης εικόνας Η δυνατότητα να ερμηνευτούν οι προτιμήσεις των χρηστών με την βοήθεια αυτών των πηγών δεδομένων, διερευνήθηκε ξεχωριστά αλλά και σε συνδυασμό σε κάθε μελέτη περίπτωσης. Στόχος ήταν να αποτιμηθεί η δυνατότητα συσχέτισης δεδομένων που διακατέχονται από διαφορετικά επίπεδα υποκειμενισμού με τις προτιμήσεις των συμμετεχόντων. Ιδανικά, θα αρκούσαν αντικειμενικές μετρήσεις και δεν θα επιβαρύνονταν οι χρήστες με επιπλέον βαθμολογήσεις των διεπιφανειών. Τα αποτελέσματα όμως έδειξαν ότι ένας συνδυασμός αντικειμενικών και υποκειμενικών χαρακτηριστικών ήταν ο βέλτιστος για την επιτυχή ερμηνεία των προτιμήσεων των χρηστών. Η μέθοδος αξιολόγησης που προτείνεται στα πλαίσια αυτής της διατριβής παρουσιάζει συγκριτικά πλεονεκτήματα σε σχέση με την χρήση τυποποιημένων ερωτηματολόγιων που είναι η επικρατέστερη μέθοδος στον χώρο της επικοινωνίας ανθρώπου υπολογιστή. Τα πλεονεκτήματα αυτά σχετίζονται κυρίως με την ευελιξία της μεθόδου και γίνονται εμφανή στις μελέτες αξιολόγησης που διεξήχθησαν με στόχο την εφαρμογή της μεθόδου για την αξιολόγηση ιστοσελίδων που ανήκουν σε τέσσερα διαφορετικά πεδία εφαρμογής.

Diese Dissertation konzentriert sich auf das hochdimensionale Financial Engineering, insbesondere in der Dependenzmodellierung und der sequentiellen Überwachung. Im Bereich der Dependenzmodellierung wird eine Einführung hochdimensionaler Kopula vorgestellt, die sich auf den Stand der Forschung in Kopula konzentriert. Eine komplexere Anwendung im Financial Engineering, bei der eine hochdimensionale Kopula verwendet wird, konzentriert sich auf die Bepreisung von Portfolio-ähnlichen Kreditderivaten, d. h. CDX-Tranchen (Credit Default Swap Index). In diesem Teil wird die konvexe Kombination von Kopulas in der CDX-Tranche mit Komponenten aus der elliptischen Kopula-Familie (Gaussian und Student-t), archimedischer Kopula-Familie (Frank, Gumbel, Clayton und Joe) und hierarchischer archimedischer Kopula-Familie vorgeschlagen. Im Abschnitt über finanzielle Überwachung konzentriert sich das Kapitel auf die Überwachung von hochdimensionalen Portfolios (in den Dimensionen 5, 29 und 90) durch die Entwicklung eines nichtparametrischen multivariaten statistischen Prozesssteuerungsdiagramms, d.h. eines Energietest-basierten Kontrolldiagramms (ETCC). Um die weitere Forschung und Praxis der nichtparametrischen multivariaten statistischen Prozesskontrolle zu unterstützen, die in dieser Dissertation entwickelt wurde, wird ein R-Paket "EnergyOnlineCPM" entwickelt. Dieses Paket wurde im Moment akzeptiert und veröffentlicht im Comprehensive R Archive Network (CRAN), welches das erste Paket ist, das die Verschiebung von Mittelwert und Kovarianz online überwachen kann. / This dissertation focuses on the high dimensional financial engineering, especially in dependence modeling and sequential surveillance. In aspect of dependence modeling, an introduction of high dimensional copula concentrating on state-of-the-art research in copula is presented. A more complex application in financial engineering using high dimensional copula is concentrated on the pricing of the portfolio-like credit derivative, i.e. credit default swap index (CDX) tranches. In this part, the convex combination of copulas is proposed in CDX tranche pricing with components stemming from elliptical copula family (Gaussian and Student-t), Archimedean copula family (Frank, Gumbel, Clayton and Joe) and hierarchical Archimedean copula family used in some publications. In financial surveillance part, the chapter focuses on the monitoring of high dimensional portfolios (in 5, 29 and 90 dimensions) by development of a nonparametric multivariate statistical process control chart, i.e. energy test based control chart (ETCC). In order to support the further research and practice of nonparametric multivariate statistical process control chart devised in this dissertation, an R package "EnergyOnlineCPM" is developed. At moment, this package has been accepted and published in the Comprehensive R Archive Network (CRAN), which is the first package that can online monitor the shift in mean and covariance jointly.

Despite some great success, many human diseases cannot be effectively treated, prevented or cured, yet. Moreover, prescribed drugs are often not very efficient and cause undesired side effects. Hence, there is a need to investigate the molecular basis of diseases and adverse drug reactions in more detail. For this purpose, relevant biomedical data needs to be gathered, integrated and analysed in a meaningful way. In this regard, we have developed novel integrative analysis approaches based on both perspectives, classical multivariate statistics and systems biology. A novel multilevel statistical method has been developed for exploiting molecular and pharmacological information for a set of drugs in order to investigate undesired side effects. Systems biology approaches have been used to study the genetic basis of human diseases at a global scale. For this purpose, we have developed an integrated gene-disease association database and tools for user-friendly access and analysis. We showed that modularity applies for mendelian, complex and environmental diseases and identified disease-related core biological processes. We have constructed a workflow to investigate adverse drug reactions using our gene-disease association database. A detailed study of currently available pathway data has been performed to evaluate its applicability to build network models. Finally, a strategy to integrate information about sequence variations with biological pathways has been implemented to study the effect of the sequence variations onto biological processes. In summary, the developed methods are of immense practical value for other biomedical researchers and can aid to improve the understanding of the molecular basis of diseases and adverse drug reactions.A pesar de que existen tratamientos eficaces para las enfermedades, no hay todavía una cura o un tratamiento efectivo para muchas de ellas. Asimismo los medicamentos pueden ser ineficaces o causar efectos secundarios indeseables. Por lo tanto, es necesario investigar en profundidad las bases moleculares de las enfermedades y de los efectos secundarios de los medicamentos. Para ello, es necesario identificar y analizar de forma integrada los datos biomédicos relevantes. En este sentido, hemos desarrollado nuevos métodos de análisis e integración de datos biomédicos que van desde el análisis estadístico multivariante a la biología de sistemas. En primer lugar, hemos desarrollado un nuevo método estadístico multinivel para la explotación de la información molecular y farmacológica de un conjunto de drogas a fin de investigar efectos secundarios no deseados. Luego, hemos usado métodos de biología de sistemas para estudiar las bases genéticas de enfermedades humanas a escala global. Para ello, hemos integrado en una base de datos asociaciones entre genes y enfermedades y hemos desarrollado herramientas para el fácil acceso y análisis de los datos. Mostramos que las enfermedades mendelianas, complejas y ambientales presentan modularidad e identificamos los procesos biológicos relacionados con dichas enfermedades. Hemos construido una herramienta para investigar las reacciones adversas a los medicamentos basada en nuestra base de datos de asociaciones entre genes y enfermedades. Realizamos un estudio detallado de los datos disponibles sobre los procesos biológicos para evaluar su aplicabilidad en la construcción de modelos dinámicos. Por último, desarrollamos una estrategia para integrar la información sobre las variaciones de secuencia de genes con los procesos biológicos para estudiar el efecto de dichas variaciones en los procesos biológicos. En resumen, los métodos presentados en esta tesis constituyen una herramienta valiosa para otros investigadores y pueden ayudar a mejorar la comprensión de las bases moleculares de las enfermedades y de las reacciones adversas a los medicamentos.

L’industrie microélectronique est un domaine compétitif, confronté de manière permanente à plusieurs défis. Pour évaluer les étapes de fabrication, des tests de qualité sont appliqués. Ces tests étant discontinus, une défaillance des équipements peut causer une dégradation de la qualité du produit. Des alarmes peuvent être déclenchées pour indiquer des problèmes. D’autre part, on dispose d’une grande quantité de données des équipements obtenues à partir de capteurs. Une gestion des alarmes, une interpolation de mesures de qualité et une réduction de données équipements sont nécessaires. Il s’agit dans notre travail à développer des méthodes génériques d’analyse multi-variée permettant d’agréger toutes les informations disponibles sur les équipements pour prédire la qualité de produit en prenant en compte la qualité des différentes étapes de fabrication. En se basant sur le principe de reconnaissance de formes, nous avons proposé une approche pour prédire le nombre de produits restant à produire avant les pertes de performance liée aux spécifications clients en fonction des indices de santé des équipement. Notre approche permet aussi d'isoler les équipements responsables de dégradation. En plus, une méthodologie à base de régression régularisée est développée pour prédire la qualité du produit tout en prenant en compte les relations de corrélations et de dépendance existantes dans le processus. Un modèle pour la gestion des alarmes est construit où des indices de criticité et de similarité sont proposés. Les données alarmes sont ensuite utilisées pour prédire le rejet de produits. Une application sur des données industrielles provenant de STMicroelectronics est fournie. / The microelectronics industry is a highly competitive field, constantly confronted with several challenges. To evaluate the manufacturing steps, quality tests are applied during and at the end of production. As these tests are discontinuous, a defect or failure of the equipment can cause a deterioration in the product quality and a loss in the manufacturing Yield. Alarms are setting off to indicate problems, but periodic alarms can be triggered resulting in alarm flows. On the other hand, a large quantity of data of the equipment obtained from sensors is available. Alarm management, interpolation of quality measurements and reduction of correlated equipment data are required. We aim in our work to develop generic methods of multi-variate analysis allowing to aggregate all the available information (equipment health indicators, alarms) to predict the product quality taking into account the quality of the various manufacturing steps. Based on the pattern recognition principle, data of the degradation trajectory are compared with health indices for failing equipment. The objective is to predict the remaining number of products before loss of the performance related to customer specifications, and the isolation of equipment responsible for degradation. In addition, regression- ased methods are used to predict the product quality while taking into account the existing correlation and the dependency relationships in the process. A model for the alarm management is constructed where criticality and similarity indices are proposed. Then, alarm data are used to predict the product scrap. An application to industrial data from STMicroelectronics is provided.

<p>Volatile organic compounds (VOCs) are endogenous byproducts of metabolic pathways that can be altered by a disease or condition, leading to an associated and unique VOC profile or signature. Current methodologies for VOC detection include canines, gas chromatography-mass spectrometry (GC-MS), and electronic nose (eNose). Some of the challenges for canines and GC-MS are cost-effectiveness, extensive training, expensive instrumentation. On the other hand, a significant downfall of the eNose is low selectivity. This thesis proposes to design a breathalyzer using chemiresistive gas sensors that detects VOCs from human breath, and subsequently create an interface to process and deliver the results via Bluetooth Low Energy (BLE). Breath samples were collected from patients with hypoglycemia, COVID-19, and healthy controls for both. Samples were processed, analyzed using GC-MS and probed through statistical analysis. A panel of 6 VOC biomarkers distinguished between hypoglycemia (HYPO) and Normal samples with a training AUC of 0.98 and a testing AUC of 0.93. For COVID-19, a panel of 3 VOC biomarkers distinguished between COVID-19 positive symptomatic (COVID-19) and healthy Control samples with a training area under the curve (AUC) of receiver operating characteristic (ROC) of 1.0 and cross-validation (CV) AUC of 0.99. The model was validated with COVID-19 Recovery samples. The discovery of these biomarkers enables the development of selective gas sensors to detect the VOCs. </p><p><br></p><p>Polyethylenimine-ether functionalized gold nanoparticle (PEI-EGNP) gas sensors were designed and fabricated in the lab and metal oxide (MOX) semiconductor gas sensors were obtained from Nanoz (Chip 1: SnO₂ and Chip 2: WO₃). These sensors were tested at different relative humidity (RH) levels, and VOC concentrations. Contact angle which measures hydrophobicity, was 84° and the thickness of the PEI-EGNP coating was 11 µ m. The PEI-EGNP sensor response at RH 85% had a signal 10x higher than at RH 0%. Optimization of the MOX sensor was performed by changing the heater voltage and concentration of VOCs. At RH 85% and heater voltage of 2500 mV, the performance of the sensors increased. Chip 2 had higher sensitivity towards VOCs especially for one of the VOC biomarkers identified for COVID-19. PCA distinguished VOC biomarkers of HYPO, COVID-19, and healthy human breath using the Nanoz. A sensor interface was created to integrate the PEI-EGNP sensors with the printed circuit board (PCB) and Bluno Nano to perform machine learning. The sensor interface can currently process and make decisions from the data whether the breath is HYPO (-) or Normal (+). This data is then sent via BLE to the Hypo Alert app to display the decision.</p>