A large amount of research has been conducted in order to seek explanations that clarify e-commerce acceptance throughout the world; however, there is a gap in the research as to how e-commerce acceptance is attributable to national culture. Two previous studies (Yoon, 2009), (Capece, et al., 2013) used Hofstede’s five dimensions of national culture in conjunction with the Technology Acceptance Model (TAM) as a means to filling this gap with perspectives on low-acceptance populations (China in 2008 and Italy in 2013). The study presented in this paper is a continuation of the previous work, offering a perspective on a high-acceptance population (Sweden). The main research question is about investigating how Swedish e-commerce acceptance is related to national culture, and the answer is sought by probing on the Swedish perspective of e-commerce in the light of the TAM, e-commerce trust, and Hofstede’s five dimensions of national culture in an online survey. The data is analyzed using Structural Equation Modeling (SEM), and compared to the findings of the Chinese and Italian precursors. Furthermore, an attempt is made to explain the contrast between the comparably high e-commerce acceptance in Sweden to the lower degrees of acceptance in China and Italy.

For manufacturers in the wood industry, an important way to make the production more effective is to automate the process of detecting defects and different attributes on boards. One important attribute on most boards is heartwood and sapwood. This thesis project was conducted at the company MiCROTEC and aims to investigate methods to classify heartwood and sapwood on boards. The dataset used in this project consisted of oak boards. In order to increase the amount of information retrieved from the boards, hyperspectral imaging was used instead of conventional RGB cameras. Based on this data, deep learning models in the form of U-Net and U-within-U-Net architecture as well as different spectral dimensionality reduction methods were developed to segment boards in heartwood and sapwood. The performance of these deep learning models was compared to PLS-DA and SVM. PLS-DA has already been used at MiCROTEC and has been used in this work for comparison as a baseline model.   The result of the thesis work showed that a deep learning approach could increase the F1-Score from 0.730 for the baseline classifier PLS-DA to an F1-Score of 0.918, and that the different spectral reduction methods only had a small impact on the result. The increase in F1-score was mainly due to an increase in precision, since the PLS-DA had a similar recall as the deep learning models.

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With the evolution of GPU performance, the interest of using AI for all kinds of purposes has risen. Companies today put a great amount of resources to find new ways of using AI to increase the value of their products or automating processes. An area in the wood industry where AI is widely used and studied is in defect detection. In this thesis, the combination of using AI and hyperspectral images is studied and evaluated in the case of segmenting defects in hardwood with a U- Net network structure. The performance is compared to another known method usually used when dealing with high-dimensional data: PLS-DA. This thesis also compares the use of RGB image data in combination with AI, to further analyze the usefulness that the hyperspectral data provide. The results showed signs of improvement when using hyperspectral images com- pared to RGB images when detecting blue stain and red heartwood defects. De- tection of the defects rot and knots did however show no sign of improvements. Due to the annotations being more accurate in the RGB data, the results from the hyperspectral data-fed networks would suggest that blue stain and red heartwood could be of interest regarding further investigation. Computational performance is shown to vary across the different reduction meth- ods, and the results from this thesis provides some insight that might aid in the reasoning regarding how to choose an appropriate reduction method.

En sjukdom kan många gånger härledas till en kaskadereaktion mellan proteiner, co-faktorer och substrat. Denna kaskadreaktion blir många gånger målet för att behandla sjukdomen med läkemedel. För att designa nya läkemedelsmoleyler används vanligen datorbaserade verktyg. Denna design av läkemedelsmolekyler drar stor nytta av att målproteinet är känt och då framförallt dess tredimensionella (3D) struktur. Är 3D-strukturen känd kan man utföra så kallad struktur- och datorbaserad molekyldesign, 3D-geometrin (f.f.a. för inbindningsplatsen) blir en vägledning för designen av en ny molekyl. Många faktorer avgör interaktionen mellan en molekyl och bindningsplatsen, till exempel fysikalisk-kemiska egenskaper hos molekylen och bindningsplatsen, flexibiliteten i molekylen och målproteinet, och det omgivande lösningsmedlet. För att strukturbaserad molekyldesign ska fungera väl måste två viktiga steg utföras: i) 3D anpassning av molekyler till bindningsplatsen i ett målprotein (s.k. dockning) och ii) prediktion av molekylers affinitet för bindningsplatsen. Huvudsyftena med arbetet i denna avhandling var som följer: i) skapa modeler för att prediktera affiniteten mellan en molekyl och bindningsplatsen i ett målprotein; ii) förfina molekyl-protein-geometrin som skapas vid 3D-anpassning mellan en molekyl och bindningsplatsen i ett målprotein (s.k. dockning); iii) karaktärisera proteiner och framför allt deras sekundärstruktur; iv) bedöma effekten av olika matematiska beskrivningar av lösningsmedlet för förfining av 3D molekyl-protein-geometrin skapad vid dockning och prediktion av molekylers affinitet för proteiners bindningsfickor. Ett övergripande syfte var att använda kemometriska metoder för modellering och dataanalys på de ovan nämnda punkterna. För att sammanfatta så presenterar denna avhandling metoder och resultat som är användbara för strukturbaserad molekyldesign. De rapporterade resultaten visar att det är möjligt att skapa kemometriska modeler för prediktion av molekylers affinitet för bindningsplatsen i ett protein och att dessa presterade lika bra som andra vanliga metoder. Dessutom kunde kemometriska modeller skapas för att beskriva effekten av hur inställningarna för olika parametrar i dockningsprogram påverkade den 3D molekyl-protein-geometrin som dockingsprogram skapade. Vidare kunde kemometriska modeller andvändas för att öka förståelsen för deskriptorer som beskrev sekundärstrukturen i proteiner. Förfining av molekyl-protein-geometrin skapad genom dockning gav liknande och ickesignifikanta resultat oberoende av vilken matematisk modell för lösningsmedlet som användes, förutom för ett fåtal (sex av 30) fall. Däremot visade det sig att användandet av en förfinad geometri var värdefullt för prediktion av molekylers affinitet för bindningsplatsen i ett protein. Förbättringen av prediktion av affintitet var markant då en Poisson-Boltzmann beskrivning av lösningsmedlet användes; jämfört med prediktionerna gjorda med ett dockningsprogram förbättrades korrelationen mellan beräknad affintiet och uppmätt affinitet med 0,7 (R2). / A disease is often associated with a cascade reaction pathway involving proteins, co-factors and substrates. Hence to treat the disease, elements of this pathway are often targeted using a therapeutic agent, a drug. Designing new drug molecules for use as therapeutic agents involves the application of methods collectively known as computer-aided molecular design, CAMD. When the three dimensional (3D) geometry of a macromolecular target (usually a protein) is known, structure-based CAMD is undertaken and structural information of the target guides the design of new molecules and their interactions with the binding sites in targeted proteins. Many factors influence the interactions between the designed molecules and the binding sites of the target proteins, such as the physico-chemical properties of the molecule and the binding site, the flexibility of the protein and the ligand, and the surrounding solvent. In order for structure-based CAMD to be successful, two important aspects must be considered that take the abovementioned factors into account. These are; i) 3D fitting of molecules to the binding site of the target protein (like fitting pieces of a jigsaw puzzle), and ii) predicting the affinity of molecules to the protein binding site. The main objectives of the work underlying this thesis were: to create models for predicting the affinity between a molecule and a protein binding site; to refine the geometry of the molecule-protein complex derived by or in 3D fitting (also known as docking); to characterize the proteins and their secondary structure; and to evaluate the effects of different generalized-Born (GB) and Poisson-Boltzmann (PB) implicit solvent models on the refinement of the molecule-protein complex geometry created in the docking and the prediction of the molecule-to-protein binding site affinity. A further objective was to apply chemometric methodologies for modeling and data analysis to all of the above. To summarize, this thesis presents methodologies and results applicable to structure-based CAMD. Results show that predictive chemometric models for molecule-to-protein binding site affinity could be created that yield comparable results to similar, commonly used methods. In addition, chemometric models could be created to model the effects of software settings on the molecule-protein complex geometry using software for molecule-to-binding site docking. Furthermore, the use of chemometric models provided a more profound understanding of protein secondary structure descriptors. Refining the geometry of molecule-protein complexes created through molecule-to-binding site docking gave similar results for all investigated implicit solvent models, but the geometry was significantly improved in only a few examined cases (six of 30). However, using the geometry-refined molecule-protein complexes was highly valuable for the prediction of molecule-to-binding site affinity. Indeed, using the PB solvent model it yielded improvements of 0.7 in correlation coefficients (R2) for binding affinity parameters of a set of Factor Xa protein drug molecules, relative to those obtained using the fitting software.

In the production of paper, the quality of the pulp is an important factor both for the productivity and for the final quality. Reliable real-time measurements of pulp quality are therefore needed. One way is to use acoustic or vibration sensors that give information-rich signals and place the sensors at suitable locations in a pulp production line. However, these sensors are not selective for the pulp properties of interest. Therefore, advanced signal processing and multivariate calibration are essential tools. The current work has been focused on the development of calibration routes for extraction of information from acoustic sensors and on signal processing algorithms for enhancing the information-selectivity for a specific pulp property or class of properties. Multivariate analysis methods like Principal Components Analysis (PCA), Partial Least Squares (PLS) and Orthogonal Signal Correction (OSC) have been used for visualization and calibration. Signal processing methods like Fast Fourier Transform (FFT), Fast Wavelet Transform (FWT) and Continuous Wavelet Transform (CWT) have been used in the development of novel signal processing algorithms for extraction of information from vibrationacoustic sensors. It is shown that use of OSC combined with PLS for prediction of Canadian Standard Freeness (CSF) using FFT-spectra produced from vibration data on a Thermo Mechanical Pulping (TMP) process gives lower prediction errors and a more parsimonious model than PLS alone. The combination of FFT and PLS was also used for monitoring of beating of kraft pulp and for screen monitoring. When using regular FFT-spectra on process acoustic data the obtained information tend to overlap. To circumvent this two new signal processing methods were developed: Wavelet Transform Multi Resolution Spectra (WT-MRS) and Continuous Wavelet Transform Fibre Length Extraction (CWT-FLE). Applying WT-MRS gave PLS-models that were more parsimonious with lower prediction error for CSF than using regular FFT-Spectra. For a Medium Consistency (MC) pulp stream WT-MRS gave predictions errors comparable to the reference methods for CSF and Brightness. The CWT-FLE method was validated against a commercial fibre length analyzer and good agreement was obtained. The CWT-FLE-curves could therefore be used instead of other fibre distribution curves for process control. Further, the CWT-FLE curves were used for PLS modelling of tensile strength and optical parameters with good results. In addition to the mentioned results a comprehensive overview of technologies used with acoustic sensors and related applications has been performed. / Vid framställning av pappersprodukter är kvaliteten på massan en viktig faktor för produktiviteten och kvalitén på slutresultatet. Det är därför viktigt att ha tillgång till tillförlitliga mätningar av massakvalitet i realtid. En möjlighet är att använda akustik- eller vibrationssensorer i lämpliga positioner vid enhetsoperationer i massaprocessen. Selektiviteten hos dessa mätningar är emellertid relativt låg i synnerhet om mätningarna är passiva. Därför krävs avancerad signalbehandling och multivariat kalibrering. Det nu presenterade arbetet har varit fokuserat på kalibreringsmetoder för extraktion av information ur akustiska mätningar samt på algoritmer för signalbehandling som kan ge förbättrad informationsselektivitet. Multivariata metoder som Principal Component Analysis (PCA), Partial Least Squares (PLS) and Orthogonal Signal Correction (OSC) har använts för visualisering och kalibrering. Signalbehandlingsmetoderna Fast Fourier Transform (FFT), Fast Wavelet Transform (FWT) och Continuous Wavelet Transform (CWT) har använts i utvecklingen av nydanande metoder för signalbehandling anpassade till att extrahera information ur signaler från vibrations/akustiska sensorer. En kombination av OSC och PLS applicerade på FFT-spektra från raffineringen i en Termo Mechnaical Pulping (TMP) process ger lägre prediktionsfel för Canadian Standard Freeness (CSF) än enbart PLS. Kombinationen av FFT och PLS har vidare använts för monitorering av malning av sulfatmassa och monitorering av silning. Ordinära FFT-spektra av t.ex. vibrationssignaler är delvis överlappande. För att komma runt detta har två signalbehandlingsmetoder utvecklats, Wavelet Transform Multi Resolution Spectra (WT-MRS) baserat på kombinationen av FWT och FFT samt Continuous Wavelet Transform Fibre Length Extraction (CWT-FLE) baserat på CWT. Tillämpning av WT-MRS gav enklare PLS-modeller med lägre prediktionsfel för CSF jämfört med att använda normala FFT-spektra. I en annan tillämpning på en massaström med relativt hög koncentration (Medium Consistency, MC) kunde prediktioner för CSF samt ljushet erhållas med prediktionsfel jämförbart med referensmetodernas fel. Metoden CWT-FLE validerades mot en kommersiell fiberlängdsmätare med god överensstämmelse. CWT-FLE-kurvorna skulle därför kunna användas i stället för andra fiberdistributionskurvor för processtyrning. Vidare användes CWT-FLE kurvor för PLS modellering av dragstyrka samt optiska egenskaper med goda resultat. Utöver de nämnda resultaten har en omfattande litteratursammanställning gjorts över området och relaterade applikationer. / QC 20100629

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Made available in DSpace on 2016-03-15T19:30:46Z (GMT). No. of bitstreams: 1 Evelyn Seligmann Feitosa.pdf: 4150862 bytes, checksum: c2fb95c13060f06c44c6788bbbfd1fc6 (MD5) Previous issue date: 2011-11-10 / Fundo Mackenzie de Pesquisa / The allocation of resources and the constant search for competitive advantages differentiators to reach best results are always business challenges. In the contemporary context, in order to achieve superior performance, it reinforces the company's need to have, and make good use, of scarce, valuable, non-substitutable and inimitable resources. These resources include brands, customer base, knowledge, ability and competence of the work teams, corporate culture, partnerships and operational processes established, among other intangible assets, usually arising from a long and risky development process. Mergers and acquisitions (M & A) arise, then, as an important strategic action, being an alternative means to obtain and accelerate the accumulation of these resources within the companies. That is the subject of this work, which discusses the importance of existing and intangible assets disclosed, previous to the M & A transactions, their classification into various types, measurement, and impact on the resulting firm's financial performance in long term. The overall objective of this thesis was to analyze how this performance, after a minimum period of 36 months of the event, is related to the existence, level of disclosure and the nature of intangible assets in the organizations involved. One hundred-eighteen (118) companies were investigated in fifty-nine (59) cases of M & A occurred in France between 1997 and 2007; the study reflects a multi-method research, pluralistic, on qualitative and quantitative aspects. Intangible assets disclosure indicators were built by applying the content analysis technique to financial and accounting reports provided by the companies prior to the events, as well as financial indicators (proxies) for the existence of intangibles were calculated. These indicators were initially confronted with each other and later their explanatory power in relation to financial ratios of growth and profitability (for the corporation and its shareholders), which are the analyzed dimensions of financial performance. Many methods for statistical analysis were used in the multivariate data analysis (correlations and factor analysis, multiple regressions) and in the structural equation modeling (SEM), via Partial Least Squares (PLS). A total of twelve models, with statistics significance, were established to express the relationship among the constructs examined. Best results were achieved in the models developed with variables of semantic origin, in detriment of those with financial indicators only. The results obtained in this thesis leads to deduce that, in this study, there are positive relationships between the existence and the disclosure of intangible assets by firms involved in the operations of M & A and subsequent financial performance, measured by the corporate profitability and the growth of the resulting organization. This suggests that the strategic choice for business growth via M & A operations is favorable to the accumulation of intangible assets in the firms, in search for better results. / A alocação de recursos e a constante busca por diferenciais competitivos, visando melhores resultados, são grandes desafios empresariais. No contexto contemporâneo, para obter desempenho superior, reforça-se a necessidade de a empresa dispor, e fazer bom uso, de recursos raros, valiosos, não-substituíveis e de difícil imitação. Dentre estes recursos, destacam-se aspectos como as marcas, a base de clientes, o conhecimento, a capacidade e competência das equipes de trabalho, a cultura corporativa, as parcerias e os processos operacionais estabelecidos, dentre outros ativos intangíveis, geralmente decorrentes de longos e arriscados processos de desenvolvimento. As fusões e aquisições (F&A) surgem, então, como movimentos estratégicos importantes, sendo meio alternativo para obter e acelerar a acumulação destes recursos nas empresas. É essa a temática deste trabalho, que discorre sobre a importância dos ativos intangíveis existentes e divulgados previamente às operações de F&A de empresas, sobre a classificação dos seus diversos tipos, a sua mensuração e o seu impacto sobre o desempenho financeiro da firma resultante, no longo prazo. O objetivo geral desta tese foi analisar como este desempenho, após prazo mínimo de 36 meses do evento, está relacionado à existência, ao nível de divulgação e à natureza dos ativos intangíveis das organizações envolvidas. Foram investigadas 118 empresas, em 59 casos de F&A ocorridos na França entre 1997 e 2007, em uma pesquisa multi-métodos, pluralística, nas vertentes qualitativa e quantitativa. Foram construídos indicadores de divulgação (disclosure) de ativos intangíveis, mediante aplicação da técnica de análise de conteúdos aos relatórios contábil-financeiros disponibilizados pelas empresas antes do evento, e calculados indicadores financeiros (proxies) para a existência de intangíveis. Estes indicadores foram inicialmente confrontados entre si e posteriormente quanto ao seu poder explicativo em relação aos índices financeiros de crescimento e de lucratividade (empresarial e para os acionistas), que são as dimensões analisadas do desempenho financeiro. Utilizaram-se métodos de análise estatística de dados multivariados (análises de correlações, fatoriais, regressões múltiplas) e modelagem em equações estruturais, via Partial Least Squares (SEM- PLS). Foram estabelecidos, no total, doze modelos com significância estatística para expressar o relacionamento entre os construtos examinados. Alcançaram-se melhores resultados nos modelos desenvolvidos com variáveis de origem semântica, em detrimento daqueles que utilizaram indicadores exclusivamente financeiros. Os resultados obtidos nesta tese permitiram deduzir que há relações positivas entre a existência e a divulgação de ativos intangíveis pelas firmas envolvidas nas operações de F&A estudadas e o posterior desempenho financeiro, mensurado pela lucratividade empresarial e pelo crescimento, da organização resultante. Isto sugere que a opção estratégica por crescimento empresarial via operações de F&A é favorável ao acúmulo de recursos intangíveis nas firmas, na busca por melhores resultados.

Commercial mortgage-backed securitisation (CMBS) is an important development in the South African property finance field. This study explains the characteristics; structure and structuring; advantages, disadvantages and risks; and legal and regulatory aspects of CMBS. Four CMBS programmes have been launched in South Africa to date (August 2006) all of which have been originated by listed Property Loan Stock (PLS) companies. The unique features of the four programmes were examined and the impact on their originators and the listed property sector was analysed. The main participants in the South African CMBS industry were interviewed. CMBS has acted as a catalyst for greater competition between banks resulting in lower interest rates on bank debt and the creation of new property financing products. The introduction of CMBS has benefited not only the four originating PLS companies, but also had a positive impact on the entire listed property sector. / Business Management / M. Com. (Business Management)

<p>In this thesis some multivariate spectroscopic methods for the analysis of solutions are proposed. Spectroscopy and multivariate data analysis form a powerful combination for obtaining both quantitative and qualitative information and it is shown how spectroscopic techniques in combination with chemometric data evaluation can be used to obtain rapid, simple and efficient analytical methods. These spectroscopic methods consisting of spectroscopic analysis, a high level of automation and chemometric data evaluation can lead to analytical methods with a high analytical capacity, and for these methods, the term high-capacity analysis (HCA) is suggested. It is further shown how chemometric evaluation of the multivariate data in chromatographic analyses decreases the need for baseline separation. </p><p>The thesis is based on six papers and the chemometric tools used are experimental design, principal component analysis (PCA), soft independent modelling of class analogy (SIMCA), partial least squares regression (PLS) and parallel factor analysis (PARAFAC). The analytical techniques utilised are scanning ultraviolet-visible (UV-Vis) spectroscopy, diode array detection (DAD) used in non-column chromatographic diode array UV spectroscopy, high-performance liquid chromatography with diode array detection (HPLC-DAD) and fluorescence spectroscopy. The methods proposed are exemplified in the analysis of pharmaceutical solutions and serum proteins.</p><p>In Paper I a method is proposed for the determination of the content and identity of the active compound in pharmaceutical solutions by means of UV-Vis spectroscopy, orthogonal signal correction and multivariate calibration with PLS and SIMCA classification. Paper II proposes a new method for the rapid determination of pharmaceutical solutions by the use of non-column chromatographic diode array UV spectroscopy, i.e. a conventional HPLC-DAD system without any chromatographic column connected. In Paper III an investigation is made of the ability of a control sample, of known content and identity to diagnose and correct errors in multivariate predictions something that together with use of multivariate residuals can make it possible to use the same calibration model over time. In Paper IV a method is proposed for simultaneous determination of serum proteins with fluorescence spectroscopy and multivariate calibration. Paper V proposes a method for the determination of chromatographic peak purity by means of PCA of HPLC-DAD data. In Paper VI PARAFAC is applied for the decomposition of DAD data of some partially separated peaks into the pure chromatographic, spectral and concentration profiles. </p>