Submitted by Erika Demachki (erikademachki@gmail.com) on 2014-10-23T18:20:00Z No. of bitstreams: 2 Dissertação - Murillo Batista Ferreira - 2013.pdf: 2726162 bytes, checksum: b4ad5f67e5b5eff91f35b0296db5a36e (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Approved for entry into archive by Jaqueline Silva (jtas29@gmail.com) on 2014-10-23T18:46:59Z (GMT) No. of bitstreams: 2 Dissertação - Murillo Batista Ferreira - 2013.pdf: 2726162 bytes, checksum: b4ad5f67e5b5eff91f35b0296db5a36e (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Made available in DSpace on 2014-10-23T18:46:59Z (GMT). No. of bitstreams: 2 Dissertação - Murillo Batista Ferreira - 2013.pdf: 2726162 bytes, checksum: b4ad5f67e5b5eff91f35b0296db5a36e (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2013-04-29 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Among lots of pathologies that attack the concrete structures stands out the corrosion of the reinforcements, that may be triggered by the phenomenon of carbonation of the concrete, which consists in a physico-chemical process between the carbon dioxide (CO2) from the atmosphere and the cement paste compounds, which has as main result the calcium carbonate precipitation (CaCO3) in a region of the concrete cover, with the formation of a layer that has less alkalinity than that not affected by this phenomenon. The carbonation moves from outside to inside the concrete through a carbonated front, that when it reaches the depth of the reinforcement causes destabilization of the protective passive layer, providing the onset of the corrosion. How many researches are conducted by accelerated carbonation tests, it is of paramount importance that the evaluation process by comparing it with data obtained from samples that have suffered natural carbonation. Facing this reality, this research is conducted based on samples that are exposed in the natural environment (external housed) for a period of ten years, with the general objective of evaluating the results (coefficients and carbonation depths) of natural carbonation process of concrete with different mineral additions, water/binder ratios and curing conditions (moist and dry) over this period. For this realization, samples of concrete produced in 2002, produced in Castro's dissertation (2003). The variables included in the experimental program are: concretes with five types of mineral additions (silica fume (10%), rice husk ash (10%), metakaolin (10%), fly ash (25%), blast furnace slag (65%), these amounts being in partial replacement of cement mass) and the reference concrete, without mineral addition; three water/binder relationships (0.40 , 0.55 and 0.70) and two curing conditions (moist and dry). Measurements were made of natural carbonation through of pH indicator based on phenolphthalein, elaborating a database along time, through measurements with periods of exposure of 0.25 years (91 days), 0.50 years (182 days), 0.82 years (301 days), 3 years, 7 years, 9 years and 10 years, allowing comparative performance evaluation of various concrete containing mineral additions, taking as a base carbonated depths and natural carbonation coefficients data. The results showed that there are significant differences of behavior between different concretes studied and that in the overall analysis of the carbonation natural coefficients, the reference concrete showed the best alone performance, showing that the alkaline reserve is still the predominant effect in terms of against carbonation, but the microstructure refinement provided by additions (physical effect) approaches such chemical aspect, as detected, for example, in concrete with metakaolin. In the correlation between the accelerated carbonation coefficients and the natural carbonation ones, was verified a relation of direct proportionality between the coefficients found for the two procedures, with the coefficient signifying accelerated approximately 7.4 times the natural ratio. The useful life predictions showed periods of time until the carbonation front reaches the cover thickness ranging from 4 years up to 241 years, for the different concretes and situations analyzed. / Dentre as diversas patologias que atacam as estruturas de concreto destaca-se a corrosão das armaduras, que pode ser desencadeada pelo fenômeno da carbonatação do concreto, que consiste em um processo físico-químico entre o gás carbônico (CO2) presente na atmosfera e os compostos da pasta de cimento, tendo como resultado principal a precipitação do carbonato de cálcio (CaCO3) em uma região do cobrimento, com a constituição de uma camada que passa a ter uma alcalinidade significativamente menor do aquela não afetada por esse fenômeno. A carbonatação avança de fora para dentro do concreto, por meio de uma frente carbonatada, que quando atinge a profundidade das armaduras provoca desestabilização da camada passiva protetora, propiciando assim o início da corrosão. Como muitas pesquisas são conduzidas por ensaios de carbonatação acelerada, é de suma importância a avaliação desse processo confrontando-o com dados obtidos de amostras que sofreram cabonatação natural. Diante dessa realidade, esta pesquisa se conduz baseada em amostras que estão expostas no ambiente natural (abrigado externo) por um período de dez anos, com o objetivo geral de avaliar os resultados obtidos (profundidades e coeficientes de carbonatação) do processo de carbonatação natural de concretos com diferentes adições minerais, relações água/aglomerante e processos de cura (úmida e seca) ao longo desse período. Para sua realização, foram utilizados corpos de prova de concreto armado produzidos no ano de 2002, fruto da dissertação de Castro (2003). As variáveis contempladas no programa experimental são: concretos com cinco tipos de adições minerais (sílica ativa (10%), cinza de casca de arroz (10%), metacaulim (10%), cinza volante (25%) e escória alto forno (65%), sendo estes teores em substituição parcial da massa de cimento) e mais o concreto de referência, sem adição mineral; três relações água/aglomerante (0,40; 0,55 e 0,70) e dois procedimentos de cura (úmida e seca). Foram realizadas medidas de carbonatação natural por meio de indicador de pH à base de fenolftaleína, elaborando-se um banco de dados ao longo do tempo, por meio de medidas realizadas com os tempos de exposição de 0,25 anos (91 dias), 0,50 anos (182 dias), 0,82 anos (301 dias), 3 anos, 7 anos, 9 anos e 10 anos, permitindo assim uma avaliação comparativa de desempenho dos diversos concretos contendo adições minerais, tendo-se como base os valores de profundidade carbonatada e os coeficientes de carbonatação natural. Os resultados mostraram que existem diferenças significativas de comportamento entre os diversos concretos estudados e que na análise global dos coeficientes de carbonatação natural, o concreto de referência apresentou isoladamente o melhor desempenho, demonstrando que a reserva alcalina ainda é o efeito preponderante em termos de combate à carbonatação, mas que o refinamento da microestrutura proporcionado pelas adições (efeito físico) se aproxima desse aspecto químico, como se tem, por exemplo, nos concretos com metacaulim. Na correlação entre os coeficientes de carbonatação acelerado e natural, verificou-se uma relação de direta proporcionalidade entre os coeficientes encontrados para os dois procedimentos, com o coeficiente acelerado significando aproximadamente 7,4 vezes o coeficiente natural. Os prognósticos de vida útil mostraram períodos de tempo estimado até a frente de carbonatação atingir a espessura de cobrimento variando desde 4 anos até 241 anos, para os diversos concretos e situações analisadas.

Esse estudo investigou se as notas explicativas às demonstrações financeiras, preparadas de acordo com as International Financial Reporting Standards (IFRS), cumprem seu objetivo principal de fornecer informações úteis a investidores e credores no mercado brasileiro. A análise foi desenvolvida a partir de dados obtidos junto a usuários externos, investidores e credores, de informações financeiras divulgadas em notas explicativas às demonstrações financeiras de companhias abertas brasileiras, listadas na BM&FBovespa, no período de 1º de outubro de 2013 a 28 de fevereiro de 2014. Foram identificadas, também, as opiniões de preparadores de informações financeiras e contrapostas às dos usuários externos quanto às características da informação financeira útil, emanadas do The Conceptual Framework for Financial Reporting IASB (2010); foi ainda analisada a influência do processo adotado pelo IASB para definir requerimentos de divulgação incluídos em suas normas e pronunciamentos contábeis associado à confiabilidade trazida por auditores independentes (Big four) quanto ao enforcement à aderência a esses requerimentos, no âmbito da utilidade da informação financeira. De forma geral, os resultados indicaram que as notas explicativas às demonstrações financeiras atingem parcialmente seu objetivo principal de fornecer informações úteis a investidores e credores no mercado brasileiro, uma vez que preparadores da informação financeira norteiam-se pelos requerimentos de divulgação definidos nos IFRS de forma bastante literal, inclusive com auxílio de disclosure check list, propiciando a inclusão de informações imateriais em notas explicativas devido à ausência de orientação específica sobre determinação de materialidade nas normas do IASB. / In this study we have examined whether the explanatory notes to financial statements prepared in accordance with International Financial Reporting Standards (IFRS) achieve their main objective of providing useful information to investors and creditors in the Brazilian market. The analysis was based on data obtained from external users, investors and creditors with respect to financial information disclosed in the explanatory notes of financial statements of Brazilian public companies listed on the BM&FBovespa, during the period from October 1, 2013 to February 28, 2014. It was identified the opinions of the preparers of financial information and compared them with those of external users regarding the characteristics of useful financial information described in The Conceptual Framework for Financial Reporting IASB (2010). It was also analyzed the influence of IASB´s process to define the disclosure requirements in their accounting standards and pronouncements, together with the reliability resulting from independent auditors (Big Four) regarding the enforcement of compliance with these requirements, as they relate to the usefulness of financial information. Overall, the results revealed that the explanatory notes to the financial statements partially achieve their main goal of providing useful information to investors and creditors in the Brazilian market, since preparers of financial information are guided by the disclosure requirements defined in the IFRS quite literally, sometimes with the assistance of a disclosure checklist, resulting in the inclusion of immaterial information in the notes, due to the lack of specific guidance in the IFRS regarding materiality.

The thesis deals with determining the quotient of usable area and the built-up area for houses in a specific location and analyzes the influence over size of quotient according to variables in process of determining.

Tato práce se zabývá vytvořením simulačního modelu dvojčinného pneumatického pístu s mechanickou sestavou, včetně modelů snímačů, s následujícím odhadem parametrů a aproximací chování demonstračního zařízení. Dalším cílem je prezentace různých přístupů prediktivní údržby na datové sadě měřené na demonstračním zařízení. Na měřený datový soubor se aplikovaly signal-based techniky bez použití simulačního modelu a model-based metody, které vyžadují použití simulačního modelu. Výsledkem této práce je ověření možnosti monitorování stavu zařízení pomocí nainstalovaných senzorů a vyhodnocení efektivity senzorů z hlediska přesnosti a finančních nákladů.

As a result of new information technology and globalization, there has never before been a time when people have had better access to information, than nowadays. The potential overload of information builds the basis for the research questions of this cumulative dissertation, which relates to the extensively discussed 'disclosure overload problem'. Special focus is put on decision-useful information in voluntary reporting of capital market-oriented companies. In this context the first manuscript investigates the quality of information in voluntary strategy reporting and formulates qualitative principles. Based thereon, the second manuscript examines determinants influencing the quality of strategy reporting. The third manuscript is focusing on Corporate Social Responsibility (CSR) reporting and investigates the relation of transparency in CSR reports and external assurance. The prior discussed topics as well as financial reporting and new reporting concepts, like integrated reporting, are put into context in the fourth manuscript. In this educational case study special emphasis is placed on the determination of material information, which is of high importance for future decision leaders.

There are three ways to deal with component failure: reactive maintenance, preventive maintenance, and predictive maintenance. Reactive maintenance is to repair only once something breaks. Preventive maintenance is to repair before it breaks, independent of actual wear. Predictive maintenance is performed on the basis of real time operational data, repairing when components cross a certain degradation threshold.  With classification models one can determine the health state of a component. Regression models, on the other hand, allow the user to calculate a more precise estimate of remaining useful life. Previous research on regression models have exclusively used sensory data while classification models have used both sensory data as well as log-data. Research on predictive maintenance using regression models have found most success using SVM regression, decision trees, random forest regression, artificial neural networks and LSTM models.  Companies have more and more data to their disposal about the performance of their machines, but usually in the form of log-data. The goal of this research is to find if it is possible to use log-data for regression models. If this is the case, more sophisticated regression models can be used to apply predictive maintenance more accurately on a broader scale than is currently the case. The project was performed through a case study at a company in the semiconductor industry in the Netherlands, with years of log-data of their product that are gradually degrading over time. After quantifying the log-data and trying all kinds of different regression models in combination with different time scales, the results were unilaterally abysmal and were unable to make any decent prediction.  The reason for this according to several experts in the field of data science is that there was no in depth understanding of the data. They say it is required to have an integral understanding of the log-data and to closely collaborate with field engineers who know the data in and out. If a field engineer can say something about the degradation of a machine using only the log-data, a machine learning model can do it too. If a machine learning model is unable to purposefully overfit on the training data and the results are bad, there is no signal in the dataset and the task is impossible. It does not matter if the data was originally sensory or log-based, the only thing that matters is understanding what the data means and the presence of the degradation signal within.

TikTok är en snabbt växande plattform som främst används av generation Z. Innehållet på plattformen har förändrats de senaste åren, där det har gått från att i störst del bestå av dans och musik till att numera även beröra ämnen som politik, aktivism och nyheter. Detta kräver ett källkritiskt förhållningssätt av användarna eftersom det tenderar att spridas desinformation. Därför syftar studien till att undersöka hur källkritiska generation Z är till samhällsnyttig information på TikTok samt deras förmåga att källkritiskt granska innehållet. Vidare diskuterar studien hur plattformens funktioner påverkar generation Z och deras förmåga att avgöra vad som är sant eller falskt.  Studien baseras på en kvantitativ och kvalitativ metodansats i form av enkät- och intervjuundersökningar. Intervjun genomfördes med sju personer inom generation Z fördelat på tre åldersgrupper, 16–19 år, 20–23 år och 24–27 år. Resultatet visade att generation Z har kännedom om innebörden av källkritik, men att de inte utnyttjar deras källkritiska kunskaper på plattformen. Respondenterna uppgav även att de sällan granskar innehåll på TikTok och att de tenderar att referera till innehållet i samtal med andra. Studien konstaterar även att generation Z använder TikTok framför allt för underhållning och tidsfördriv vilket bidrar till att det dels saknas intresse av att ifrågasätta innehåll som bekräftar deras egna övertygelser. Dels saknas det förutsättningar för att de ska kunna vara källkritiska på grund av det korta videoformatet och avsaknad av bakgrundsinformation från avsändaren. Utifrån studiens resultat kan slutsatsen dras att ansvaret gällande att vara källkritisk enbart ligger på användaren, men det krävs även ansvar från avsändare. Vidare visade även resultatet från intervjuerna att TikToks funktioner i form av gilla-markeringar, kommentarsfält och tillägg av bilder har en påverkan på generation Z:s tillförlitlighet till innehållet, både positivt och negativt. / TikTok is a rapidly growing platform used mainly by Generation Z. The content of the platform has changed in recent years, moving from a predominantly dance and music content to topics such as politics, activism and news. This requires a source-critical approach from the users as there is a tendency to spread misinformation. Therefore, the study aims to investigate how source-critical Generation Z is to socially useful information on TikTok and their ability to critically review the content. Furthermore, the study discusses how the platform's functions affect generation z's trustworthiness of TikTok content.  The study is based on a quantitative and qualitative methodological approach in the form of surveys and interviews. The interviews were conducted with seven people in Generation Z divided into three age groups, 16-19 years, 20-23 years and 24-27 years. The results showed that Generation Z is aware of the meaning of source criticism, but that they do not utilize their source criticism knowledge on the platform. The respondents also stated that they rarely review content on TikTok and that they tend to refer to the content in conversations with others. The study also notes that Generation Z uses TikTok mainly for entertainment and amusement, which contributes to a lack of interest in questioning content that confirms their own beliefs. On the other hand, there are no conditions for them to be critical of the source due to the short video format and the lack of background information from the creator. Based on the results of the study, it can be concluded that the responsibility for being source-critical lies solely with the user, but responsibility is also required from the creators. Furthermore, the results from the interviews also showed that TikTok's functions in the form of likes, the comment section and the addition of images have an impact on generation Z's credibility to the content, both positively and negatively.

Assessment of machine health and prediction of future failures are critical for maintenance decisions. Many of the existing methods use unsupervised techniques to construct health indicators by measuring the disparity between the current state and either the healthy or the faulty states of the system. This approach can work well, but if the resulting health indicators are insufficient there is no easy way to steer the algorithm towards better ones. In this thesis a new method for health indicator construction is investigated that aims to solve this issue. It is based on measuring distance after transforming the sensor data into a new space using a feed-forward neural network. The feed-forward neural network is trained using a multi-objective optimization algorithm, NSGA-II, to optimize criteria that are desired in a health indicator. Thereafter the constructed health indicator is passed into a gated recurrent unit for remaining useful life prediction. The approach is compared to benchmarks on the NASA Turbofan Engine Degradation Simulation dataset and in regard to the size of the neural networks, the model performs relatively well, but does not outperform the results reported by a few of the more recent methods. The method is also investigated on a simulated dataset based on elevator weights with two independent failures. The method is able to construct a single health indicator with a desirable shape for both failures, although the latter estimates of time until failure are overestimated for the more rare failure type. On both datasets the health indicator construction method is compared with a baseline without transformation function and does in both cases outperform it in terms of the resulting remaining useful life prediction error using the gated recurrent unit. Overall, the method is shown to be flexible in generating health indicators with different characteristics and because of its properties it is adaptive to different remaining useful life prediction methods. / Estimering av maskinhälsa och prognos av framtida fel är kritiska steg för underhållsbeslut. Många av de befintliga metoderna använder icke-väglett (unsupervised) lärande för att konstruera hälsoindikatorer som beskriver maskinens tillstånd över tid. Detta sker genom att mäta olikheter mellan det nuvarande tillståndet och antingen de friska eller fallerande tillstånden i systemet. Det här tillvägagångssättet kan fungera väl, men om de resulterande hälsoindikatorerna är otillräckliga så finns det inget enkelt sätt att styra algoritmen mot bättre. I det här examensarbetet undersöks en ny metod för konstruktion av hälsoindikatorer som försöker lösa det här problemet. Den är baserad på avståndsmätning efter att ha transformerat indatat till ett nytt vektorrum genom ett feed-forward neuralt nätverk. Nätverket är tränat genom en multi-objektiv optimeringsalgoritm, NSGA-II, för att optimera kriterier som är önskvärda hos en hälsoindikator. Därefter används den konstruerade hälsoindikatorn som indata till en gated recurrent unit (ett neuralt nätverk som hanterar sekventiell data) för att förutspå återstående livslängd hos systemet i fråga. Metoden jämförs med andra metoder på ett dataset från NASA som simulerar degradering hos turbofan-motorer. Med avseende på storleken på de använda neurala nätverken så är resultatet relativt bra, men överträffar inte resultaten rapporterade från några av de senaste metoderna. Metoden testas även på ett simulerat dataset baserat på elevatorer som fraktar säd med två oberoende fel. Metoden lyckas skapa en hälsoindikator som har en önskvärd form för båda felen. Dock så överskattar den senare modellen, som använde hälsoindikatorn, återstående livslängd vid estimering av det mer ovanliga felet. På båda dataseten jämförs metoden för hälsoindikatorkonstruktion med en basmetod utan transformering, d.v.s. avståndet mäts direkt från grund-datat. I båda fallen överträffar den föreslagna metoden basmetoden i termer av förutsägelsefel av återstående livslängd genom gated recurrent unit- nätverket. På det stora hela så visar sig metoden vara flexibel i skapandet av hälsoindikatorer med olika attribut och p.g.a. metodens egenskaper är den adaptiv för olika typer av metoder som förutspår återstående livslängd.

Predictive maintenance plays a crucial role in preventing unexpected equipment failures and maintaining assets in good operating conditions in various systems. One such scenario where predictive maintenance has been widely used is in battery management systems for electronic vehicles based on lithium batteries, where the risk of failure can be reduced by predicting the remaining useful life of the lithium battery. This project developed a DL model based on Long Short-Term Memory networks which was able to generalize new and various kinds of battery. The model was implemented on a low-cost, low-power using embedded artifcial intelligence, which enables local model execution, reducing costs, time, and risks associated with transferring data to the cloud. To further optimize the model and reduce its memory usage, quantization was applied before porting it to an embedded system based on the STM32 MCU. The results show that the model migration was successful, with low memory cost and no signifcant degradation in accuracy. Finally, the memory usage of the prediction model was also analyzed. / Predictiv underhåll har en avgörande roll för att förebygga oväntade utrustningsfel och bibehålla tillgångar i god driftsvillkor i olika system. Ett scenario där predictivt underhåll har använts mycket är i batterihanteringssystem för elfordon baserade på litiumbatterier, där risken för fel kan reduceras genom att förutsäga den återstående användbarhetsperioden för litiumbatteriet. I det här projektet utvecklades djupinlärningsprediktiva modeller med hjälp av Keras sekventiella modell för att representera en ferlagersneural nätverk och en Lång Korttidsminne modell för tidserieprediktion. Dessa modeller implementerades på en lågkostnad, låglägesmikrokontroller med inbyggd artifcial intelligence, vilket möjliggör lokal modellkörning, vilket reducerar kostnader, tid och risker med att överföra data till molnet. För att ytterligare optimera modellen och minska dess minnesfotavtryck tillämpades kvantisering innan den portades till en inbyggd system baserat på STM32 mikrokontroller. Resultaten visar att modellmigrationen var framgångsrik, med låg minneskostnad och ingen signifkant försämring av precisionen. Slutligen analyserades även minnesanvändningen av prediktionsmodellen.

Andelen av produkter med integrerad artificiell intelligens och tjänster som bygger på AI har ökat de senaste åren. Implementering och användning av tekniken är en snabbt växande marknad där tillväxten sker inom privata bolag och offentlig sektor. AI-verktyg lockar verksamheter för att kunna effektivisera processer, förbättra produkter och tjänster med hjälp av chatbotar som integreras i applikationer och webbplatser. En chatbot är en programvara som använder olika tekniker och modeller för att förstå och svara på frågor, simulera mänsklig konversation och hantera olika uppgifter. Trots alla fördelar som AI-drivna chatbotar medför, har vissa utmaningar framkommit. Användare har blivit mer tveksamma till de synliga och osynliga tillämpningarna av AI och hur de påverkar ens interaktioner och beslutsfattande. Det är viktigt för utvecklare och designers av AI-drivna chatbotar att ta hänsyn till användarnas upplevelser och reflektera över användarvänligheten under hela processen. Därför syftar denna studie till att undersöka användandet av gränssnitt i applikationer som är baserade på AI-drivna chatbotar för att identifiera faktorer som optimerar upplevelser ur ett människocentrerat perspektiv. Studiens fokus ligger på chatbotar som används i mobilapplikationer och webbplatser, och som integrerar med användare genom text i ett digitalt gränssnitt. Genom kvalitativa forskningsmetoder, intervjuer och observation, med teoretisk bakgrund från litteraturen, samlades information in om användares erfarenheter och preferenser. Undersökningen genomfördes med totalt sju deltagare, där fem slutanvändare utvärderade två gränssnitt i applikationer som bygger på AI-drivna chatbotar och två apputvecklare delade med sig av sina erfarenheter. Det resulterade i att datainsamlingen identifierade tolv kvalitativa faktorer inom fyra problemområden: kommunikation, mänsklig kontroll, transparens i systemfunktioner och visuell presentation, som har en påverkan på användarupplevelsen. Utifrån undersökningen har rekommendationer formulerats som beskriver vad som bör beaktas vid design av AI-baserade applikationer. Detta arbete bidrar till framtida arbete med utveckling av användbara applikationer baserade på artificiell intelligens. / Implementing artificial intelligence in products and services has increased significantly in recent years. AI tools, such as chatbots integrated into applications and websites, have become popular among companies to simplify work-related tasks and improve user satisfaction. “Chatbot” is software that uses different techniques and models to understand and answer users' questions, simulate human conversation and handle various tasks. However, users have become more doubtful about AI using implicit and explicit in products and services and how it affects interaction and decision-making. It is important that developers and designers of AI-powered chatbots consider user experiences and reflect on the usability and user experience of the chatbots. Therefore, this work aims to investigate the use of interfaces in applications based on AI-powered chatbots to identify factors that optimise the user experience. To reach this purpose, the researcher of this bachelor thesis collected information about users' experiences and preferences through qualitative research methods, interviews and observation. The research involved seven participants, two developers sharing their expertise, and five users evaluating two chatbots where users interacted with chatbots through text in a digital interface. As a result, the collected data identified twelve qualitative factors within four problem areas: communication, human control, transparency in system functions and visual presentation, which impact the user experience. This study suggests recommendations considering these factors that can increase user satisfaction and contribute to future work in developing applications based on artificial intelligence.