A associação dos métodos cinéticos de análises e dos sistemas de análises em fluxo foi demonstrada em relação à determinação espectrofotométrica de ferro e vanádio em ligas Fe-V O método se baseia na influência de Fe2+ e VO2+ na taxa de oxidação de iodeto por dicromato sob condições ácidas; por esta razão o emprego do redutor de Jones foi necessário. Um sistema de análises por injeção em fluxo (FIA) e um sistema multi-impulsão foram dimensionados e avaliados. Em ambos os sistemas, a solução da amostra era inserida no fluxo transportador / reagente iodeto, e a solução de dicromato era adicionada por confluência. Sucessivas medidas eram realizadas durante a passagem da zona de amostra processada pelo detector, cada uma relacionada a uma diferente condição para o desenvolvimento da reação. O tratamento dos dados envolveu calibração multivariada, particularmente o algorítmo PLS. O sistema FIA se mostrou pouco adequado para as determinações multi-paramétricas, uma vez que os elementos de fluído resultantes da natureza de escoamento laminar não continham informações cinéticas suficientes para compor as etapas de modelagem. Por outro lado, MPFS mostrou que a natureza do fluxo pulsado resulta em melhorias nas figuras de mérito devido ao movimento caótico dos elementos de fluído. O sistema proposto é simples e robusto, capaz de analisar 50 amostras por hora, significando em um consumo de 48 mg KI por determinação. A duas primeiras variáveis latentes contém ca 94 % da informação analítica, mostrando que a dimensionalidade dupla intrínsica ao conjunto de dados. Os resultados se apresentaram concordantes com aqueles obtidos por espectrometria de emissão optica com plasma induzido em argônio. / Differential kinetic analysis can be implemented in a flow system analyser, and this was demonstrated in designing an improved spectrophotometric catalytic determination of iron and vanadium in Fe-V alloys. The method relied on the influence of Fe2+ and VO2+ on the rate of the iodide oxidation by Cr2O7 under acidic conditions; therefore the Jones reductor was needed. To this end, a flow injection system (FIA) and a multi-pumping flow system (MPFS) were dimensioned and evaluated. In both systems, the alloy solution was inserted into an acidic KI solution that acted also as carrier stream, and a dichromate solution was added by confluence. Successive measurements were performed during sample passage through the detector, each one related to a different yet reproducible condition for reaction development. Data treatment involved multivariate calibration by the PLS algorithm. The FIA system was less recommended for multi-parametric determination, as the laminar flow regimen could not provide suitable kinetic information. On the other hand, a MPFS demonstrated that pulsed flow led to enhance figures of merit due to chaotic movement of its fluid elements. The proposed MPFS system is very simple and rugged, allowing 50 samples to be run per hour, meaning 48 mg KI per determination. The first two latent variables carry ca 94 % of the analytical information, pointing out that the intrinsic dimensionality of the data set is two. Results are in agreement with inductively coupled argon plasma – optical emission spectrometry.

Orientador: Helena Maria Andre Bolini / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia de Alimentos / Made available in DSpace on 2018-08-11T04:55:59Z (GMT). No. of bitstreams: 1 Alves_LeonardoRangel_M.pdf: 410164 bytes, checksum: eed7ffe76f347f00d0abb009ed908230 (MD5) Previous issue date: 2008 / Resumo: Este estudo objetivou Identificar direcionadores de preferência de oito amostras comerciais de néctar de uva (tradicionais e ¿light¿) utilizando metodologias estatísticas avançadas para relacionar dados de perfil sensorial, físico-químicos e aceitabilidade. Oito amostras comerciais de néctares de uva (quatro tradicionais e suas respectivas versões ¿light¿) foram analisadas. Um teste de Aceitação utilizando a escala hedônica híbrida foi realizado com 114 consumidores. Quatorze termos descritivos foram avaliados por uma equipe sensorial e seis atributos físico-químicos foram medidos. As amostras de néctar de uva A e C foram as mais aceitas e as amostras CL e DL (¿light¿) foram as mais rejeitadas. Construiu-se um Mapa de Preferência Interno e em seguida uma Análise de ¿Cluster¿ foi realizada para o atributo Impressão Global. Dois grupos de consumidores foram encontrados. A principal diferença entre os grupos foi com relação à utilização de diferentes porções da escala pelos consumidores de cada grupo. A metodologia PLSR foi utilizada para relacionar a aceitação dos consumidores com os termos descritivos e atributos físico-químicos, fornecendo correlações entre eles. Os resultados mostraram que os atributos Sabor de Uva, Sabor Residual de Uva, Acidez Total Titulável, Aroma de Uva, Cor Vinho, °Brix, Viscosidade, Acidez, Turbidez, Adstringência, Fenóis Totais e Consistência nesta ordem de importância, estavam fortemente correlacionados com a Impressão Global dos consumidores sendo portanto os direcionadores de preferência encontrados / Abstract: This study depicts the PLS regression method used to help find drivers of liking of the grape nectar. Eight commercial brands (four traditional and four lights) were analyzed. An acceptance test using hybrid hedonic scale was performed with 114 consumers. Fourteen attributes were evaluated by a sensory team of fourteen members, and six physical-chemical attributes were measured. The most accepted samples were A and C, and the less accepted ones were CL and DL (lights). An Internal Preference Mapping followed by a Cluster Analysis was performed on the consumer grades to Global Impression. Two clusters of consumers were found. The mainly difference between clusters was the use of different portions of the scale by the consumers. The PLSR methodology was used to relate the acceptance with the sensory and physical-chemical attributes giving a correlation between them. The model showed the importance of each sensory or physicalchemical attribute for the model projection. The results showed that Grape Flavor; Residual Grape Flavor, Total Sourness Titration, Grape Aroma, Wine Color, °Brix, Viscosity, Sourness, Turbidity, Astringency, Total Phenols and Consistency were positive correlated with consumer grades to Global Impression, therefore they are called drivers of liking / Mestrado / Consumo e Qualidade de Alimentos / Mestre em Alimentos e Nutrição

O presente trabalho pretende entender a dinâmica do gerenciamento de projetos no IPEN. Para tal, decidiu-se pela pesquisa junto a literatura acadêmica de modelos que pudessem servir de base e que após modificações e ajustes pudessem refletir a realidade dos projetos de Institutos Públicos Pesquisa & Desenvolvimento. Após tratamento estatístico dos dados algumas hipóteses foram validadas e demonstraram sua influência positiva no desempenho do gerenciamento do projeto, tais como a influência das pessoas que compõem as equipes, o efeito da liderança, dentre outras. O modelo, inclusive mostrou-se válido para explicar quais fatores são relevantes para o sucesso dos projetos. Um das principais objetivos, foi exatamente o uso de modelo de avaliação de gestão projetos, que fossem passíveis de validação estatística, e não utilizar um dos disponíveis no mercado, tais como P3M3 e OPM3, para que houvesse um controle e confirmação estatística dos resultados. Outro objetivo foi utilizar um modelo cujas assertivas refletissem a natureza dos projetos de Pesquisa & Desenvolvimento gerenciados pelos pesquisadores do IPEN. Aliás, as referidas assertivas foram formuladas, e enviadas via pesquisa web, e respondidas por praticamente uma centena de profissionais do IPEN, envolvidos com projetos de P&D. A presente dissertação, acrescida das recomendações, ao final, tem como proposta servir de contribuição para os trabalhos desenvolvidos pelo Escritório de Projetos do IPEN. O modelo de avaliação, contido neste trabalho, pode ser aplicado em outras Instituições de P&D brasileiras, para que avaliem a forma e a maneira como gerenciam os seus respectivos projetos. / This paper aims to understand the dynamics involved in the project management at IPEN. To reach this goal, the method chosen was research along with academic literature of models that could serve as a base that after modifications and adjustments could reflect the reality of projects from the Public Institute of Research & Development. After undergoing statistical treatment of the data, some hypotheses were validated and showed positive influence on the project management performance, such as the influence of people who make up the teams, the leadership effect, among others. In fact, the model was found to be valid in explaining which factors are relevant for the success of the projects. One of the main goals was exactly the use of the project management evaluation model, submitted to statistical validation and not to use one available on the market, such as the P3M3 and OPM3, in order to assure the statistical control and confirmation of the results. Another goal was to use a model whose statements reflected the nature of the Research & Development project managed by researchers at IPEN. In fact, the aforementioned statements were formulated and sent via a web survey and answered by almost one hundred IPEN professionals who work on R&D projects. The following dissertation, along with the recommendations at the end, was included to serve as contribution to work developed by the IPEN Project Offices. The evaluation model included in this paper can be applied in other R&D organizations in Brazil, to evaluate the way their projects are managed.

The present thesis proposes new methods for obtaining objective and accurate diagnoses in modern healthcare. Non-invasive techniques have been used to examine or diagnose three different medical conditions, namely neuropathy among diabetics, radiotherapy induced erythema (skin redness) among breast cancer patients and diagnoses of cutaneous malignant melanoma. The techniques used were Near-InfraRed spectroscopy (NIR), Multi Frequency Bio Impedance Analysis of whole body (MFBIA-body), Laser Doppler Imaging (LDI) and Digital Colour Photography (DCP). The neuropathy for diabetics was studied in papers I and II. The first study was performed on diabetics and control subjects of both genders. A separation was seen between males and females and therefore the data had to be divided in order to obtain good models. NIR spectroscopy was shown to be a viable technique for measuring neuropathy once the division according to gender was made. The second study on diabetics, where MFBIA-body was added to the analysis, was performed on males exclusively. Principal component analysis showed that healthy reference subjects tend to separate from diabetics. Also, diabetics with severe neuropathy separate from persons less affected. The preliminary study presented in paper III was performed on breast cancer patients in order to investigate if NIR, LDI and DCP were able to detect radiotherapy induced erythema. The promising results in the preliminary study motivated a new and larger study. This study, presented in papers IV and V, intended to investigate the measurement techniques further but also to examine the effect that two different skin lotions, Essex and Aloe vera have on the development of erythema. The Wilcoxon signed rank sum test showed that DCP and NIR could detect erythema, which is developed during one week of radiation treatment. LDI was able to detect erythema developed during two weeks of treatment. None of the techniques could detect any differences between the two lotions regarding the development of erythema. The use of NIR to diagnose cutaneous malignant melanoma is presented as unpublished results in this thesis. This study gave promising but inconclusive results. NIR could be of interest for future development of instrumentation for diagnosis of skin cancer.

Empirischen Studien zufolge können Patente sich positiv auf den Unternehmenserfolg auswirken. Allerdings wirkt dieser Effekt nicht automatisch, sondern Unternehmen müssen sich um den Aufbau und die gesteuerte Weiterentwicklung eines nachhaltigen und wertvollen Patentportfolios bemühen. Bisher ist jedoch nicht wissenschaftlich untersucht worden, welche Maßnahmen Unternehmen ergreifen können, um die unternehmensinternen Vorraussetzungen für eine erfolgreiche Steuerung von Patentaktivitäten zu schaffen. Um diese betrieblichen Faktoren zu identifizieren und deren Relevanz zu quantifizieren, wurden 2005 in einer breiten empirischen Untersuchung die aktiven Patentanmelder im deutschsprachigen Raum (über 1.000 Unternehmen) mit Hilfe eines standardisierten Fragebogens befragt. Auf der Basis von 325 auswertbaren Fragebögen (Ausschöpfungsquote 36,8 %) konnten zum einen Ergebnisse zum aktuellen Aufgabenspektrum der Patentabteilungen sowie zu deren organisatorischen und personellen Strukturen gewonnen werden. Ebenfalls wurde in dieser Status quo-Analyse der Bekanntheits- und Implementierungsgrad von Methoden und Systemen (z. B. Patentbewertungsmethoden, Patent-IT-Systeme) beleuchtet. Zum anderen wurden die betrieblichen Faktoren herausgestellt, auf die technologieorientierte Unternehmen achten sollten, um das Fundament für eine erfolgreiche Patentsteuerung zu legen. / Empirical studies have shown that patents can have a positive effect on corporate success. However, this effect does not occur by itself. Companies have to make an effort to create and to develop a sustainable patent portfolio. So far, no academic studies have investigated into which actions a company can take to establish the internal conditions for successful patent management. To identify and to quantify the relevance of these internal factors, a study was conducted using a standardized written questionnaire with more than 1,000 patent-oriented companies in the German-speaking countries (Germany, Austria, Switzerland, Liechtenstein). In total, 325 valid questionnaires were included in the analyses; this corresponds to an above-average response rate of 36.8 %. These analyses revealed insights into the current task profile of patent departments and their organizational and personnel structures. This status quo analysis also included the investigation into the awareness and implementation level of used methods and systems (e. g. patent evaluation methods, patent IT systems). Furthermore, the study could expose the internal determinants, which technology-oriented companies should focus on to ensure a successful patent management.

This study has been performed at Powertrain Engineering Sweden AB (PES), a fully owned subsidiary of Volvo Cars Group, which is constantly working to develop and improve internal combustion engines. As part of this work, durability tests are performed to analyse the impact of wear on the engines. At present, there is a strong focus on visual inspections after the engines have undergone durability tests. PES wants to develop a method where collected data from these tests can be used to explain how the phenomenon of knocking and the control of lambda changes over time. The study analyses one specific durability test and investigates the methodology of data analysis by using the open-source software platform Sympathy for Data, with an add-on developed by Volvo Cars Group, for data management, visualisation and analysis. To execute the analysis, engine parameters that affect these systems as well as parameters suitable to use as response variables are identified through literature studies of internal combustion engine fundamentalsas well as internal material, and knowledge acquired at the company. The result is presented in the form of an analysis generated by the node for partial least squares regression (PLSR) which is pre-programmed in Sympathy for Data as well as the images and graphs obtained as output. For knock, the signal for the final ignition angle was found to be suitable to use as the response variable in the PLSR. A suitable response variable for lambda was more difficult to identify, this is why both signals for the measured lambda and lambda adaptation are analysed. Studies of the internal material and knowledge highlighted the fact that several engine subsystems are highly dependent on each other and that even deeper research would be necessary to fully understand the process and identify the primary cause for the variations observed in the generated models. However, partial least squares regression was performed using parameters derived from literature reviews as input (predictors) in order produce regression models to explain the variance in sought response. Well-fitting models could be created with a varying number of latent variables needed for the different responses. The output obtained from the PLSR enables further studies of the specific cases as well as the methodology itself, hence, increase the use of data analysis with the help of the software used in the department for durability testing at PES. / Denna studie är utförd hos Powertrain Engineering Sweden AB (PES), vilka är ett helägt dotterbolag till Volvo Cars Group, som arbetar med att ta fram och förbättra förbränningsmotorer. En del i detta arbete är att genomföra långtidstest för att analysera hur motorernas egenskaper ändras vid förslitning över tid. I nuläget ligger stort fokus på visuella inspektioner efter att motorerna genomgått långtidstester. PES önskar utveckla en metod där redan insamlad data som registrerats i dessa tester kan förklara hur fenomenet knack och regleringen för lambda förändras över tid. Studien är genomförd i form av en fallstudie av ett specifikt långtidstest där den öppna programvaran Sympathy for Data, tillsammans med det av Volvo Cars Group utvecklade tillägget, används för datahantering, visualisering och analys. Studien undersöker också metodiken för dataanalys med nämnd programvara. För att genomföra detta identifieras motorparametrar som påverkar de undersökta systemen samt parametrar som lämpar sig att användas som responsvariabler i en regressionsmodell. Dessa parametrar togs fram genom litteraturstudier om de fundamentala delarna i en förbränningsmotor samt från företaget förvärvad intern kunskap kring systemen. Resultatet presenteras i form av en analys genomförd med den, i Sympathy for Data, förprogrammerade noden för partial least squares regression(PLSR) samt de bilder och grafer som erhålls. För knack visade det sig att den slutliga tändningsvinkeln var lämplig att använda som respons i PLSR-modellen. En lämplig responsvariabel för lambda var mer svåridentifierad, detta förklarar varför signalerna för uppmätt lambda och lambda adaption analyseras. Inläsning av internt material och grundläggande information om förbränningsmotorer visade att delsystem i ottomotorn är beroende och påverkas av varandra vilket innebär att mer ingående studier i dessa delsystem är nödvändigt för att förstå hela processen och hitta grundorsakerna till variationerna som påvisas för responssignalerna. Vidare utfördes PLSR med de parametrar som härletts från litteraturstudier som indatasignaler (prediktorer) för att skapa en regressionsmodell som förklarar variansen i sökta responssignaler. Beroende av responssignal krävdes varierande antal latenta variabler för att uppnå en tillräckligt precis modell. Resultatet från PLSR möjliggör vidare forskning inom området och metoden som använts och har på så sätt möjliggjort för fortsatt utveckling. Detta i sin tur kan öka användandet av dataanalys med hjälp av den programvara som används vid avdelningen för långtidstest hos PES.

Under high irradiation, a fourth state of matter named plasma can be obtained. Plasmas emit electromagnetic radiation that can be recorded in the form of spectra for spectroscopic elemental analysis. With the advent of lasers in the 1960s, spectroscopists realized that lasers could be used simultaneously as a source of energy and excitation to create plasmas. The use of a laser to ignite a plasma subsequently led to laser-induced breakdown spectroscopy (LIBS), an optical emission spectroscopy capable of analyzing samples in various states (solids, liquids, gases) with minimal sample preparation, rapid feedback, and endowed with in situ capability. In this dissertation, studies of LIBS for multi-elemental analysis and geological applications are reported. LIBS was applied to cosmetic powders for elemental analysis, screening and classification based on the raw material used. Principal component analysis (PCA) and internal standardization were used. The intensity ratios of Mg/Si and Fe/Si observed in talcum powder show that these two ratios could be used as indicators of the potential presence of asbestos. The feasibility of LIBS for the analysis of gasification slags was investigated and results compared with those of inductively-coupled plasma−optical emission spectrometry (ICP-OES). The limits of detection for Al, Ca, Fe, Si and V were determined. The matrix effect was studied using an internal standard and PLS-R. Apart from V, prediction results were closed to those of ICP-OES with accuracy within 10%. Elemental characterization of outcrop geological samples from the Marcellus Shale Formation was also carried out. The matrix effect was substantially reduced. The limits of detection obtained for Si, Al, Ti, Mg, Ca and C were determined. The relative errors of LIBS measurements are in the range of 1.7 to 12.6%. Gate delay and laser pulse energy, have been investigated in view of quantitative analysis of variation of trace elements in a high-pressure environment. Optimization of these parameters permits obtaining underwater plasma emission of calcium with quantitative results on the order of 30 ppm within a certain limit of increased pressure. Monitoring the variation of the trace elements can predict changes in the chemical composition in carbon sequestration reservoir.

Soil spectroscopy in the visible-to-near infrared (VNIR) and mid-infrared (MIR) is a cost-effective method to determine the soil organic carbon content (SOC) based on predictive spectral models calibrated to analytical-determined SOC reference data. The degree to which uncertainty in reference data and spectral measurements contributes to the estimated accuracy of VNIR and MIR predictions, however, is rarely addressed and remains unclear, in particular for current handheld MIR spectrometers. We thus evaluated the reproducibility of both the spectral reflectance measurements with portable VNIR and MIR spectrometers and the analytical dry combustion SOC reference method, with the aim to assess how varying spectral inputs and reference values impact the calibration and validation of predictive VNIR and MIR models. Soil reflectance spectra and SOC were measured in triplicate, the latter by different laboratories, for a set of 75 finely ground soil samples covering a wide range of parent materials and SOC contents. Predictive partial least-squares regression (PLSR) models were evaluated in a repeated, nested cross-validation approach with systematically varied spectral inputs and reference data, respectively. We found that SOC predictions from both VNIR and MIR spectra were equally highly reproducible on average and similar to the dry combustion method, but MIR spectra were more robust to calibration sample variation. The contributions of spectral variation (ΔRMSE < 0.4 g·kg−1) and reference SOC uncertainty (ΔRMSE < 0.3 g·kg−1) to spectral modeling errors were small compared to the difference between the VNIR and MIR spectral ranges (ΔRMSE ~1.4 g·kg−1 in favor of MIR). For reference SOC, uncertainty was limited to the case of biased reference data appearing in either the calibration or validation. Given better predictive accuracy, comparable spectral reproducibility and greater robustness against calibration sample selection, the portable MIR spectrometer was considered overall superior to the VNIR instrument for SOC analysis. Our results further indicate that random errors in SOC reference values are effectively compensated for during model calibration, while biased SOC calibration data propagates errors into model predictions. Reference data uncertainty is thus more likely to negatively impact the estimated validation accuracy in soil spectroscopy studies where archived data, e.g., from soil spectral libraries, are used for model building, but it should be negligible otherwise.

No description available.

This research evaluates the technological, organizational, and environmental determinants of emerging technologies adoption represented by Artificial Intelligence (AI) and Internet of Things (IoT) driving SMEs’ competitive advantage within a resource-based view (RBV) theoretical approach supported by the technological-organizational-environmental (TOE)-framework setting. Current literature on SMEs competitive advantage as outcome of emerging technologies in the technological, organisational, and environmental contexts presents models focused on these contexts individual components. There are no models in the literature to represent the TOE framework as an integrated structure with gradual levels of complexity, allowing for incremental evaluation of the business context in support of decision making towards emerging technologies adoption supporting the firm competitive advantage. This research gap is addressed with the introduction of a new concept, the IT resource-based renewal, underpinned by the RBV, and supported by the TOE framework for providing a holistic understanding of the SMEs strategic renewal decision through information technology. This is achieved through a complex measurement model with four level constructs, leading into a parsimonious structural model that evaluates the relationships between IT resource-based renewal, and emerging technologies adoption driving SMEs competitive advantage. The model confirms the positive association between the IT resource-based renewal and emerging technologies adoption, and between the IT resource-based renewal and SME competitive advantage for the SMEs managers model, with the SME owners model outcomes are found not being supportive towards emerging technologies adoption driving SME competitive advantage. As methodology, PLS-SEM is used for its capabilities of assessing complex paths among model variables. Analysis is done on three models, one for the full sample, with two subsequent ones for owners and managers, respectively, as SME decision makers, with data collected using a web-based survey in Canada, the UK, and the US, that has provided 510 usable answers. This research has a theoretical contribution represented by the introduction of the IT resource-based renewal concept, that integrates the RBV perspective and the TOE framework for supporting organization’s decision on emerging technologies adoption driving SMEs competitive advantage. As practical implications, this thesis provides SMEs with a reference framework on adopting emerging technologies, offering SME managers and owners a comprehensive model of hierarchical factors contributing to SMEs competitive advantage acquired as outcome of AI and IoT adoption. This research makes an original contribution to the enterprise management, information systems adoption, and SME competitive advantage literature, with an empirical approach that verifies a model of emerging technologies adoption determinants driving SMEs competitive advantage.