The objective of this project was to apply machine learning methods to determine protein secondary structure content and protein fold class from ROA and Raman vibrational spectral data. Raman and ROA are sensitive to biomolecular structure with the bands of each spectra corresponding to structural elements in proteins and when combined give a fingerprint of the protein. However, there are many bands of which little is known. There is a need, therefore, to find ways of extrapolating information from spectral bands and investigate which regions of the spectra contain the most useful structural information. Support Vector Machines (SVM) classification and Random Forests (RF) trees classification were used to mine protein fold class information and Partial Least Squares (PLS) regression was used to determine secondary structure content of proteins. The classification methods were used to group proteins into α-helix, β-sheet, α/β and disordered fold classes. The PLS regression was used to determine percentage protein structural content from Raman and ROA spectral data. The analyses were performed on spectral bin widths of 10cm-1 and on the spectral amide regions I, II and III. The full spectra and different combinations of the amide regions were also analysed. The SVM analyses, classification and regression, generally did not perform well. SVM classification models for example, had low Matthew Correlation Coefficient (MCC) values below 0.5 but this is better than a negative value which would indicate a random chance prediction. The SVM regression analyses also showed very poor performances with average R2 values below 0.5. R2 is the Pearson's correlations coefficient and shows how well predicted and observed structural content values correlate. An R2 value 1 indicates a good correlation and therefore a good prediction model. The Partial Least Squares regression analyses yielded much improved results with very high accuracies. Analyses of full spectrum and the spectral amide regions produced high R2 values of 0.8-0.9 for both ROA and Raman spectral data. This high accuracy was also seen in the analysis of the 850-1100 cm-1 backbone region for both ROA and Raman spectra which indicates that this region could have an important contribution to protein structure analysis. 2nd derivative Raman spectra PLS regression analysis showed very improved performance with high accuracy R2 values of 0.81-0.97. The Random Forest algorithm used here for classification showed good performance. The 2-dimensional plots used to visualise the classification clusters showed clear clusters in some analyses, for example tighter clustering was observed for amide I, amide I & III and amide I & II & III spectral regions than for amide II, amide III and amide II&III spectra analysis. The Random Forest algorithm also determines variable importance which showed spectral bins were crucial in the classification decisions. The ROA Random Forest analyses performed generally better than Raman Random Forest analyses. ROA Random Forest analyses showed 75% as the highest percentage of correctly classified proteins while Raman analyses reported 50% as the highest percentage. The analyses presented in this thesis have shown that Raman and ROA vibrational spectral contains information about protein secondary structure and these data can be extracted using mathematical methods such as the machine learning techniques presented here. The machine learning methods applied in this project were used to mine information about protein secondary structure and the work presented here demonstrated that these techniques are useful and could be powerful tools in the determination protein structure from spectral data.

[EN] After-sales services have become very important in the automobile industry. However, this area has not been sufficiently researched, particularly with regard to China, the most important car market globally. In this respect, German manufacturers play a leading role because they dominate the premium market segment. When it comes to services, the one thing that is especially important in China is culture. At the same time, this is exactly where a scientific gap exists because the cultural aspect in automotive services has been mostly neglected in the research literature. Thus, specific knowledge with regard to Chinese service demand behaviour is lacking, which could become a crucial issue because of the enormous differences between Chinese and Western cultures. This paper addresses this limitation by providing a guideline for how the entire process chain of after-sales services could be researched in China. In addition, it also introduces Schwartz's individual level value theory as a beneficial operationalisation approach to culture. Thereby, values are modelled as exogenous variables in order to show which ones are really causal. This significant advantage cannot be provided by national comparison studies, which are the ones that are most often conducted. A total of 301 Chinese workshop customers of Audi, BMW and Mercedes-Benz were surveyed in order to assess the critical success factors of after-sales services via partial least squares structural equation modelling. / [ES] Los servicios post venta en el sector del automóvil se han convertido en un elemento esencial en su mercadotecnia global. Sin embargo, no se han investigado suficientemente y, especialmente en países emergentes con mercados crecientes como China, el mercado más relevante a nivel mundial. Aquí, los fabricantes alemanes juegan un rol fundamental al dominar el segmento premium (o de cuasi lujo) del mercado. Cuando analizamos los servicios, un factor importante en China es la cultura. Sin embargo existe, en este campo un hueco en la investigación académica ya que en la literatura de investigación del sector automóvil, la cultura es un elemento poco analizado. Por ello, no se pueden aplicar conocimientos de mercadotecnia específicos en relación con el comportamiento de la demanda de servicios en China, en un tema esencial, como es la cultura China, muy diferente a la occidental. Esta tesis trata de enfocar las limitaciones mencionadas; en primer lugar, proporcionando una guía de cómo la cadena de proceso de servicios postventa puede ser investigada en países emergentes como China. Y en segundo lugar, porque se utiliza la teoría de cultura de Schwartz como un enfoque útil de instrumentación de los valores culturales. Así, estos se modelan como variables externas, para mostrar claramente cuáles son los valores realmente relevantes en su conjunto. Para ello se encuestaron a 301 clientes de talleres post venta chinos de las marcas Audi, BMW y Mercedes-Benz, con el fin de evaluar los factores críticos de éxito mediante modelos de ecuaciones estructurales de mínimos cuadrados parciales (PLS). / [CAT] Els serveis post venda en el sector de l'automòbil s'han convertit en un element essencial del màrqueting global. No obstant això, no s'han investigat prou i, especialment en països emergents amb mercats creixents com la Xina, el mercat més rellevant a nivell mundial. Aquí, els fabricants alemanys juguen un paper fonamental en dominar el segment premium (o de quasi luxe) del mercat. Quan analitzem els serveis, un factor important a la Xina és la cultura. No obstant això existeix, en aquest camp un buit en la investigació acadèmica ja que en la literatura de recerca del sector automòbil, la cultura és un element poc analitzat. Per això, no es poden aplicar coneixements de màrqueting específics en relació amb el comportament de la demanda de serveis a la Xina, en un tema essencial, com és la cultura Xina, molt diferent a l'occidental. Aquesta tesis tracta d'enfocar les limitacions esmentades; en primer lloc, proporcionant una guia de com la cadena de procés de serveis postvenda pot ser investigada en països emergents com la Xina. I en segon lloc, perquè s'utilitza la teoria de cultura de Schwartz com un enfocament útil d'instrumentació dels valors culturals. Així, aquests es modelen com a variables externes, per mostrar clarament quins són els valors realment rellevants en el seu conjunt. Per a això es van enquestar a 301 clients de tallers post venda xinesos de les marques Audi, BMW i Mercedes-Benz, per tal d'avaluar els factors crítics d'èxit mitjançant models d'equacions estructurals de mínims quadrats / Frass, A. (2015). Impact of After-Sales Performances of German Automobile Manufacturers in China in Service Satisfaction and Loyalty. With a Particular Focus on the Influences of Cultural Determinants [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/59251 / TESIS

[ES] El aumento de la esperanza de vida en la población con edad por encima de 50 años está generando un mayor número de casos detectados de cáncer de próstata (CaP). Por este motivo, los recursos se destinan al diagnóstico en etapas tempranas y al tratamiento efectivo. A pesar de la multitud de estudios basados en biomarcadores y discriminación histológica, es difícil diferenciar con efectividad los casos de CaP con baja agresividad de aquellos que progresarán y acabarán produciendo mortalidad o una disminución en la esperanza de vida del paciente. Con el objetivo de mejorar el diagnostico, localización y gradación de los tumores malignos, las técnicas de imagen por Resonancia Magnética (MRI) son las más adecuadas para el estudio del cáncer, proporcionando métodos de diagnóstico no-invasivos, sensibles y específicos, basados en secuencias morfológicas (T2w) y funcionales (perfusión de la sangre y difusión del agua). Las diferentes características y parámetros extraídos de estas secuencias, conocidos como biomarcadores de imagen, pueden evaluar las diferencias asociadas al desarrollo de los procesos tumorales, como los modelos farmacocinéticos para estudiar angiogénesis (perfusión) y los modelos mono- y bi-exponenciales para estudiar la caída de la señal en difusión con el objetivo de estudiar la celularización. Normalmente, estos biomarcadores de imagen se analizan de forma "univariante", sin aprovechar la información de las estructuras de correlación interna que existen entre ellos. Una manera de mejorar este análisis es mediante la aplicación de las técnicas estadísticas que ofrece el Análisis Multivariante de Imágenes (MIA), obteniendo estructuras (latentes) simplificadas que ayudan a entender la relación entre los parámetros (variables) y sus propios procesos fisiológicos, además de reducir la incertidumbre en la estimación de los biomarcadores. En esta tesis, se han desarrollado nuevos biomarcadores de imagen para perfusión y difusión con la aplicación de alguna de las herramientas de MIA como la Resolución Multivariante de Curvas con Mínimos Cuadrados Alternos (MCR-ALS), obteniendo parámetros que tienen interpretación clínica directa. A continuación, los métodos basados en mínimos cuadrados parciales (PLS) se aplicaron para estudiar la capacidad de clasificación de estos biomarcadores. En primer lugar, los biomarcadores de perfusión se utilizaron para la detección de tumores (control vs lesión). Posteriormente, la combinación de perfusión + difusión + T2 se empleó para estudiar agresividad tumoral con la aplicación de métodos PLS multibloque, en concreto (secuencial) SMB-PLS. Los resultados mostrados indican que los biomarcadores de perfusión obtenidos mediante MCR son mejores que los parámetros farmacocinéticos en la diferenciación de la lesión. Con lo que respecta al estudio de la agresividad tumoral, la combinación de los biomarcadores de difusión (empleando ambos métodos: modelos paramétricos y MCR) y los valores de T2w normalizados proporcionaron los mejores resultados. En conclusión, MIA se puede aplicar a las secuencias morfológicas y funcionales de resonancia magnética para mejorar el diagnóstico y el estudio de la agresividad de los tumores en próstata. Obteniendo nuevos parámetros cuantitativos y combinándolos con los biomarcadores más ampliamente utilizados en el ambiente clínico. / [CAT] El increment de la esperança de vida en la població per damunt dels 50 anys està generant un major nombre de casos detectats de càncer de pròstata (CaP). Per aquest motiu, els recursos es destinen al diagnòstic en etapes primerenques i al tractament efectiu. Tot i la multitud de estudis basats en biomarcadors y discriminació histològica, es difícil diferenciar amb efectivitat els casos de CaP que tenen baixa agressivitat dels que progressaran y acabaran produint mortalitat o una disminució en la esperança de vida del pacient. Amb el objectiu de millorar el diagnòstic, localització y gradació dels tumors malignes, les tècniques de imatge per Ressonància Magnètica (MRI) son els mètodes més adequats per al estudi del càncer, proporcionant metodologies de diagnòstic no-invasius, sensibles y específiques basades en seqüències morfològiques (T2w) y funcionals (perfusió de la sang y difusió del aigua). Les diferents característiques i paràmetres extrets de aquestes seqüències, coneguts com biomarcadors d'imatge, poden avaluar les diferències associades al desenvolupament dels processos tumorals. Primer, amb els models farmacocinétics per a estudiar angiogènesis (perfusió) y segon, amb els models mono- i bi-exponencials per a estudiar la caiguda de la senyal en difusió amb el objectiu de estudiar la cel·lularització. Normalment, aquests biomarcadors d'imatge s'analitzen de forma "univariant", sense aprofitar la informació de las estructures de correlació interna que existeixen entre ells. Una forma de millorar aquest anàlisis es mitjançant la aplicació de las tècniques estadístiques aportades pel Anàlisis Multivariant de Imatges (MIA), obtenint estructures (latents) simplificades què ajuden a entendre la relació entre els paràmetres (variables) i els seus processos fisiològics, a més de reduir la incertesa en la estimació dels biomarcadors. En aquesta tesis, s'han desenvolupat nous biomarcadors d'imatge per a perfusió i difusió amb la aplicació de alguna de las ferramentes de MIA com la Resolució Multivariant de Corbes i Mínims Quadrats Alterns (MCR-ALS), obtenint paràmetres què tenen interpretació clínica directa. A continuació, els mètodes basats en mínims quadrats parcials (PLS) s'han aplicat per a estudiar la capacitat de classificació d'aquests biomarcadors. En primer lloc, els biomarcadors de perfusió s'han utilitzat per a la detecció de tumors (control contra lesió). Posteriorment, la combinació de perfusió + difusió + T2 s'ha utilitzat per a estudiar agressivitat tumoral amb la aplicació de mètodes PLS multi-bloc, en concret (seqüencial) SMB-PLS. Els resultats mostren què els biomarcadors de perfusió obtinguts mitjançant MCR són millors què els paràmetres farmacocinètics en la diferenciació de la lesió. En lo què es refereix al estudi de la agressivitat tumoral, la combinació dels biomarcadors de difusió (utilitzant els dos mètodes: models paramètrics i MCR) i els valors de T2w normalitzats proporcionaren els millors resultats. En conclusió, MIA es pot aplicar a les seqüències morfològiques i funcionals de ressonància magnètica per a millorar el diagnòstic i el estudi de l'agressivitat dels tumors en pròstata. Obtenint nous paràmetres quantitatius y combinant-los amb els biomarcadors més utilitzats en el ambient clínic. / [EN] The increase in life expectancy and population with age higher than 50 years is producing a major number of detected cases of prostate cancer (PCa). For this reason, the resources are focused in the early diagnosis and effective treatment. In spite of multiple studies with histologic discriminant biomarkers, it is hard to clearly differentiate the low aggressiveness PCa cases from those that will progress and produce mortality or rather a decrease in the life expectancy. With the objective of improving the diagnosis, location and gradation of the malignant tumors, Magnetic Resonance Imaging (MRI) has come up as the most appropriate image acquisition technique for cancer studies, which provides a non-invasive, sensitive and specific diagnosis, based on morphological and functional (blood perfusion and water diffusion) sequences. The different characteristics and parameters extracted from these sequences, known as imaging biomarkers, can evaluate the different processes associated to tumor development, like pharmacokinetic modeling for angiogenesis assessment (perfusion) or mono- and bi-exponential signal decay modeling for cellularization (diffusion). Normally, these imaging biomarkers are analyzed in a "univariate" way, without taking advantage of the internal correlation structures among them. One way to improve this analysis is by applying Multivariate Image Analysis (MIA) statistical techniques, obtaining simplified (latent) structures that help to understand the relation between parameters (variables) and the inner physiological processes, moreover reducing the uncertainty in the estimation of the biomarkers. In this thesis, new imaging biomarkers are developed for perfusion and diffusion by applying MIA tools like Multivariate Curve Resolution Alternating Least Squares (MCR-ALS), obtaining parameters with direct clinical interpretation. Partial Least Squares (PLS) based methods are then used for studying the classification capability of these biomarkers. First, perfusion imaging biomarkers have been tested for tumor detection (control vs lesion). Then, diffusion + perfusion have been combined to study tumor aggressiveness by applying PLS-multiblock methods (SMB-PLS). The results showed that MCR-based perfusion biomarkers performed better than state-of-the-art pharmacokinetic parameters for lesion differentiation. Regarding the assessment of tumor aggressiveness, the combination of diffusion-based imaging biomarkers (using both the parametric models and MCR) and normalized T2-weighted measurements provided the best discriminating outcome, while perfusion was not needed as it did not supply additional information. In conclusion, MIA can be applied to morphologic and functional MRI to improve the diagnosis and aggressiveness assessment of prostate tumors by obtaining new quantitative parameters and combining them with state-of-the-art imaging biomarkers. / Aguado Sarrió, E. (2019). Application of multivariate image analysis to prostate cancer for improving the comprehension of the related physiological phenomena and the development and validation of new imaging biomarkers [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/134023 / TESIS

Although there is research about the use of enterprise resource planning (ERP) from a management perspective, the research is not clear as to whether the ERP benefits justify the costs, not only in dollars, but also in effort, from the end user's perspective. Using the theory of diffusion of innovation (DOI), the purpose of this quantitative research was to identify the set of postimplementation sustainability factors that maximized ERP user value, which are major issues for management, and measured their relative significance. The study's structural model incorporated the technology-organization-environment (TOE) framework, which is a conceptualization of the theory of diffusion of innovation, to predict the postimplementation sustainability factors from the ERP user's point of view. The partial least squares structure equation modeling (PLS-SEM) approach provided the needed explanatory analysis to test the predictive power of the structural model. The target population was organizational employees who had used an operational ERP system for at least 4 years in the state of Colorado. A convenience sample of 163 cases responded to the online questionnaire. Hypotheses testing indicated that the independent variables of ERP information quality, ERP system quality, ERP knowledge and learning, shared beliefs, job relevance, and coordination significantly impacted the dependent variable ERP user value. The positive social change implications of this study include a better understanding of ERP postimplementation sustainability factors from the users' perspectives and their social impact on organizational performance, which could lead to increased employee effectiveness, productivity, efficiency, and individual satisfaction due to ERP usage.

Streaming blir dagligen en allt mer populär form av musikkonsumtion. Denna typ av medium har gjort det allt mer enkelt för individer att lyssna på musik. Diskussioner om de villkor som kreatörerna som bidrar med värde till dessa medium påpekar dock tuffa arbetsförhållanden. Kreatörer tenderar att få låg ersättning och dålig översikt över den data som relaterar till artistens lyssnare. I och med Web3:s framfart har det påbörjats en diskussion om decentraliserade musikplattformar som ett alternativ till de traditionella streamingtjänsterna. Det är inom detta område som studien ämnar att utforska acceptansen kreatörerna har av detta alternativa sätt att distribuera musik. Utifrån ramverket TAM (Technology acceptance model) skapades en modell. För att testa denna modell genomfördes sedan en enkätstudie. Det insamlade materialet användes sedan för att utföra en univariat, bivariat samt multivariat analys med hjälp av frekvenstabeller, Spearmans korrelationskoefficient och PLS-SEM-verktyg. Resultatet visade på möjliga problemområden, bland annat validiteten hos enkätfrågorna, men även lämpligheten hos studiens ramverk i förhållande till den typen av system som faktiskt undersöktes. Det var dock tydligt att urvalets användning av plattformen i fråga var en direkt effekt av hur deras avsikt till att använda densamma såg ut. Denna användaravsikt berodde sedan på deras attityd till plattformen som i sin tur berodde på den nytta de upplevde att plattformen genererade. / Music streaming is growing in popularity on a daily basis. This type of medium has made listening to music more accessible to its users. Discussions regarding tough working conditions for the creators that bring value to the platforms are becoming more common. Creators tend to get low compensation and insufficient data regarding its listeners. In regards to the growing interest with Web3 technology, discussions are being held about decentralized music platforms potential of being an alternative to the traditional streaming platforms. It’s within this field the study aims to shed some light in regards to the acceptance creators have toward this alternative way of distributing music. With regards to the theoretical framework TAM (Technology acceptance model), a model was constructed. In order to evaluate this model a survey was conducted. The data collected was then used to perform a univariate, bivariate and multivariate analysis. These were possible with the help of frequency tables, Spearmans correlation coefficient as well as PLS-SEM tools. The results brought light to several possible problem areas, amongst these the validity of the questionnaire, but also the adequacy of the theoretical framework with regards to the a type of system the study actually concerns itself with. It was, however, clear that the creators’ actual use of the platform was a direct product of their intention to use it. This intention was a result of their attitude towards the platform, which in turn depended on the usefulness the creator perceived the platform to generate.

Through the use of multiple methodologies and analytical approaches, this dissertation combines (1) sales control; (2) call center service; and (3) motivational theory to extend sales control literature beyond its current state, to consider the conflicting motivational perspectives an inside sales agent has to experience. To achieve this unification, this dissertation consists of three essays intended to: (1) identify the influence of autonomous and controlled motivation on operational sales outcome controls and performance; (2) explore the influence these motivators have on sales controls and sales performance; and, (3) understand the impact of autonomous and controlled motivation on sales agent tenure.

Contamination of peanuts by secondary metabolites of certain fungi, namely aflatoxins present a great health hazard when exposed either at low levels for prolonged times (carcinogenic) or at high levels at once (poisonous). It is important to develop an accurate and rapid measurement technique to trace the aflatoxin and/or source fungi presence in peanuts. Thus, current research focused on development of vibrational spectroscopy based methods for detection and separation of contaminated peanut samples. Aflatoxin incidence, as a chemical contaminant in peanut paste samples, was investigated, in terms of spectral characteristics using FTIR-ATR. The effects of spectral pre-processing steps such as mean-centering, smoothing the 1st derivative and normalizing were studied. Logarithmic method was the best normalization technique describing the exponentially distributed spectral data. Spectral windows giving the best correlation with respect to increasing aflatoxin amount led to selection of fat associated spectral bands. Using the multivariate analysis tools, structural contributions of aflatoxins in peanut matrix were detected. The best region was decided as 3028-2752, 1800-1707, 1584-1424, and 1408-1127 cm-1 giving correlation coefficient for calibration (R2C), root mean square error for calibration (RMSEC) and root mean square error for prediction (RMSEP) of 98.6%, 7.66ppb and 19.5ppb, respectively. Applying the constructed partial least squares model, 95% of the samples were correctly classified while the percentage of false negative and false positive identifications were 16% and 0%, respectively. Aspergillus species of section Flavi and the black fungi, A. niger are the most common colonists of peanuts in nature and the majority of the aflatoxin producing strains are from section Flavi. Seed colonization by selected Aspergillus spp. was investigated by following the chemical alterations as a function of fungal growth by means of spectral readouts. FTIR-ATR was utilized to correlate spectral characteristics to mold density, and to separate Aspergillus at section, species and strain levels, threshold mold density values were established. Even far before the organoleptic quality changes became visually observable (~10,000 mold counts), FTIR distinguished the species of same section. Besides, the analogous secondary metabolites produced increased the similarity within the spectra even their spectral contributions were mostly masked by bulk peanut medium; and led to grouping of species producing the same mycotoxins together. Aflatoxigenic and non-aflatoxigenic strains of A. flavus and A. parasiticus were further studied for measurement capability of FTIR-ATR system in discriminating the toxic streams from just moldy and clean samples. Owing to increased similarity within the collected spectral data due to aflatoxin presence, clean samples (having aflatoxin level lower than 20 ppb, n=44), only moldy samples (having aflatoxin level lower than 300 ppb, n=28) and toxic samples (having aflatoxin level between 300-1200 ppb, n=23) were separated into appropriate classes (with a 100% classification accuracy). Photoacoustic spectroscopy (PAS) is a non-invasive technique and offers many advantages over more traditional ATR system, specifically, for in-field measurements. Even though the sample throughput time is longer compared to ATR measurements, intact seeds can be directly loaded into sample compartment for analysis. Compared to ATR, PAS is more sensitive to high moisture in samples, which in our case was not a problem since peanuts have water content less than 10%. The spectral ranges between: 3600-2750, 1800-1480, 1200-900 cm-1 were assigned as the key bands and full separation between Aspergillus spp. infected and healthy peanuts was obtained. However, PAS was not sensitive as ATR either in species level classification of Aspergillus invasion or toxic-moldy level separation. When run for separation of aflatoxigenic versus non-aflatoxigenic batches of samples, 7 out of 54 contaminated samples were misclassified but all healthy peanuts were correctly identified (15 healthy/ 69 total peanut pods). This study explored the possibility of using vibrational spectroscopy as a tool to understand chemical changes in peanuts and peanut products to Aspergillus invasion or aflatoxin contamination. The overall results of current study proved the potential of FTIR, equipped with either ATR or PAS, in identification, quantification and classification at varying levels of mold density and aflatoxin concentration. These results can be used to develop quality control laboratory methods or in field sorting devices. / Ph. D.

Wastewater treatment plants (WWTPs) face increasingly stringent effluent quality constraints as a result of rising environmental concerns. Efficient operation of the secondary clarification process is essential to be able to meet these strict regulations. Treatment plants can benefit greatly from making better use of available resources through improved automation and implementing more process systems engineering techniques to enhance plant performance. As such, the primary objective of this research is to utilize data-driven modeling techniques to obtain a representative model of a simplified secondary clarification unit in a WWTP. First, a deterministic subspace-based identification approach is used to estimate a linear state-space model of the secondary clarification process that can accurately predict process dynamics, with the ultimate objective of motivating the use of the subspace model in a model predictive control (MPC) framework for closed-loop control of the clarification process. To this end, a low-order subspace model which relates a set of typical measured outputs from a secondary clarifier to a set of typical inputs is identified and subsequently validated on simulated data obtained via Hydromantis's WWTP simulation software, GPS-X. Results illustrate that the subspace model is able to approximate the nonlinear process behaviour well and can effectively predict the dynamic output trajectory for various candidate input profiles, thus establishing its candidacy for use in MPC. Subsequently, a framework for forecasting the occurrence of sludge bulking--and consequently clarification failure--based on an engineered interaction variable that aims to capture the relationship between key input variables is proposed. Partial least squares discriminant analysis (PLS-DA) is used to discriminate between process conditions associated with clarification failure versus effective clarification. Preliminary results show that PLS-DA models augmented with the interaction variable demonstrate improved predictions and higher classification accuracy. / Thesis / Master of Applied Science (MASc)

No description available.

The purpose of this research was to identify key determinants of service provider effectiveness and how it impacts outsourced security success. As environments have become more robust and dynamic, many organizations have made the decision to leverage external security expertise and have outsourced many of their information technology security functions to Managed Security Service Providers (MSSPs). Information Systems Outsourcing, at its core, is when a customer chooses to outsource certain information technology functions or services to a service provider and engages in a legally binding agreement. While legal contracts govern many aspects of an outsourcing arrangement, it cannot serve as the sole source of determining the outcome of a project. Organizations are viewing outsourcing success as an attainment of net benefits achieved through the use of a service provider. The effectiveness of the service provider has an impact on a company’s ability to meet business objectives and adhere to service level agreements. Many empirical studies have focused on outsourcing success, but few have focused on service provider effectiveness, which can serve as a catalyst to outsourcing success. For this research, Agency Theory (AT) was proposed as a foundation for developing the research model which included key areas of focus in information asymmetry, the outsourcing contract, moral hazard, trust, service provider effectiveness, and security outsourcing success. Agency Theory helped uncover several hypotheses deemed germane to service provider effectiveness and provided insight into helping understand the principal-agent paradigm that exists with security outsourcing. Confirmatory Factor Analysis (CFA) and Partial Least Squares-Structured Equation Modeling (PLS-SEM) were used with SmartPLS to analyze the data and provided clarity and validation for the research model and helped uncover key determinants of service provider effectiveness. The statistical results showed support for information asymmetry, contract, and trust, all of which were mediated through service provider effectiveness. The results also showed that service provider effectiveness is directly correlated to increasing security outsourcing success. This concluded that the research model showed significant results to support 4 of the 5 hypotheses proposed and helped uncover key findings on how security outsourcing success can be impacted. This research served as an original contribution to information security while viewing outsourcing success from the perspective of the client, security services, and customer expectations.