The act of reading has benefits for individuals and societies, yet studies show that reading declines, especially among the young. Recommender systems (RSs) can help stop such decline. There is a lot of research regarding literary books using natural language processing (NLP) methods, but the analysis of textual book content to improve recommendations is relatively rare. We propose content-based recommender systems that extract elements learned from book texts to predict readers’ future interests. One factor that influences reading preferences is writing style; we propose a system that recommends books after learning their authors’ writing style. To our knowledge, this is the first work that transfers the information learned by an author-identification model to a book RS. Another approach that we propose uses over a hundred lexical, syntactic, stylometric, and fiction-based features that might play a role in generating high-quality book recommendations. Previous book RSs include very few stylometric features; hence, our study is the first to include and analyze a wide variety of textual elements for book recommendations. We evaluated both approaches according to a top-k recommendation scenario. They give better accuracy when compared with state-of-the-art content and collaborative filtering methods. We highlight the significant factors that contributed to the accuracy of the recommendations using a forest of randomized regression trees. We also conducted a qualitative analysis by checking if similar books/authors were annotated similarly by experts. Our content-based systems suffer from the new user problem, well-known in the field of RSs, that hinders their ability to make accurate recommendations. Therefore, we propose a Topic Model-Based book recommendation component (TMB) that addresses the issue by using the topics learned from a user’s shared text on social media, to recognize their interests and map them to related books. To our knowledge, there is no literature regarding book RSs that exploits public social networks other than book-cataloging websites. Using topic modeling techniques, extracting user interests can be automatic and dynamic, without the need to search for predefined concepts. Though TMB is designed to complement other systems, we evaluated it against a traditional book CB. We assessed the top k recommendations made by TMB and CB and found that both retrieved a comparable number of books, even though CB relied on users’ rating history, while TMB only required their social profiles.

As emissões de poluentes atmosféricos decorrentes de veículos automotores representam um grave problema ambiental. O modo de operação do veículo influencia diretamente a quantidade de poluentes emitidos. Quando um veículo inicia sua operação com motor frio, efeito denominado de partida a frio, a quantidade de poluentes emitidos torna-se consideravelmente maior em comparação às condições estabilizadas de temperatura do motor. O efeito da partida a frio é bastante representativo em viagens de curta duração, como é o caso dos deslocamentos urbanos. Este estudo propõe um método para a determinação e distribuição espacial do adicional de emissões de poluentes em partida a frio. Este método foi aplicado em Porto Alegre, utilizando informações de tráfego e da frota local coletados na pesquisa de entrevistas domiciliares, realizada no ano de 2003. Os fatores de emissão utilizados embasaram-se em um estudo realizado com veículos brasileiros. Os resultados da aplicação do método indicaram que a maior parte das partidas a frio ocorre na região central de Porto Alegre e suas adjacências, sendo maior no período matinal. Observou-se também que os maiores responsáveis pelo adicional por partida a frio são os veículos equipados com conversores catalíticos e injeção eletrônica de combustível. Entretanto, os veículos mais antigos, sem conversor catalítico e equipados com carburador, são os maiores responsáveis pela emissão total, adicional por partida a frio e emissão estabilizada de CO e HC nos períodos analisados. Através do método proposto neste estudo foi possível identificar áreas críticas que necessitam de ações de controle de emissões em partida a frio. Os resultados deste estudo podem subsidiar o planejamento e gerenciamento das condições ambientais provocadas pelas emissões veiculares em áreas urbanas. / Atmospheric pollution from vehicle emissions is a serious environmental problem. The vehicle operation mode influences directly in the amount of emitted pollutants. When a vehicle begins its operation with the cold engine, called as cold start effect, the amount of emitted pollutant becomes considerably higher than when in stabilized conditions of engine’s temperature. Cold start effect are very representative in short travels, such as urban trips. This study proposes a method to estimate the amount and spacial distribution of the additional cold start pollutant emissions. This method was applied to Porto Alegre, Brazil, using traffic and local fleet data from a household travel survey of 2003. Emissions factors were based on a study of Brazilian fleet. The results from the method application showed that cold start emissions in Porto Alegre are higher in the morning peak and most of the cold start emissions are concentrated in the town center and its adjacencies. The results also showed that the catalyst fuel injection vehicles are the main responsible for the additional cold start emissions. However, old vehicles, without catalyst and equipped with carburetor, are the main responsible for the total, cold start and running emissions, CO and HC emissions in both analyses periods. Through the proposed method, it was possible to identify critical areas that need control actions of cold start emissions. The results from this study can assist planning and management of the environmental conditions deriving from vehicular emissions in urban areas.

The polymer electrolyte membrane fuel cell (PEMFC) is an electrochemical device used for the production of power, which is a key for the transition towards green and renewable power delivery devices for mobile, stationary and back-up power applications. PEMFCs consume hydrogen and oxygen to produce power, water and heat. The transient start-up from sub-zero freezing temperature conditions is a problem for the successful, undamaged and unhindered operation. The generation and presence of water in the PEMFC stack in such an environment leads to the formation of ice that hinders the flow of gases, causes morphological changes in the membrane electrode assembly (MEA) leading to reversible and irreversible degradation of stack performance. Start-up performance is highly dependent on start-up operational conditions and procedures. The previous state of the stack will influence the ability to perform upon the next start-up and operation. Water generated during normal operation is vital and improves performance when properly managed. Liquid water present at shut-down can form ice and cause unwanted start-up effects. This phase change may cause damage to the MEA and gas diffusion media due to volume expansion. Removal of high water content at shutdown decreases proton conductivity which can delay start-up times. The United States Department of Energy (DOE) has established a set of criteria that will make fuel cell technology viable when attained. As specified by DOE, an 80 kWe fuel cell will be required by 2015 to reach 50% power in 30 seconds from start-up at an ambient temperature of -20°C. This work investigates freeze start-up in a multi-kilowatt stack approaching both shut-down conditioning and start-up operations to improve performance, moderate fuel cell damage and determine the limits of current stack technology. The investigation involved a Hydrogenics Corporation 5 kW 506 series fuel cell stack. The investigation is completed through conditioning the fuel cell start-up performance at various temperatures ranging from -5°C to below -20°C. The control of system start-up temperature is achieved with an environmental chamber that maintains the desired set point during dwell time and start-up. The supply gases for the experiment are conditioned at ambient stack temperature to create a realistic environment that could be experienced in colder weather climates. Temperature controls aim to maintain steady ambient temperatures during progressive start-up in order to best simulate ambient conditions. The control and operation of the fuel cell is maintained by the use of a fuel cell automated test station (FCATS™). FCATS supplies gas feeds, coolant medium and can control temperature and reactant humidity in reactants according to a prescribed procedure for continuous operation. The iv collection of data occurs by the same system recording cell voltage, temperatures, pressures, flow rates and current densities. A procedural start-up and characterization are conducted in order improve start-of performance and examine reactant flows, coolant activation time, stack conditioning and the effects by freezing temperatures. The resulting degradation is investigated by polarization curves and various ex-situ measurements. In this work, it was found that freeze start-up of a fuel cell stack can be aided and managed by conditioning the stack at shut-down and applying a procedure to successfully start-up and mitigate the damage that freezing can cause.

The polymer electrolyte membrane fuel cell (PEMFC) is an electrochemical device used for the production of power, which is a key for the transition towards green and renewable power delivery devices for mobile, stationary and back-up power applications. PEMFCs consume hydrogen and oxygen to produce power, water and heat. The transient start-up from sub-zero freezing temperature conditions is a problem for the successful, undamaged and unhindered operation. The generation and presence of water in the PEMFC stack in such an environment leads to the formation of ice that hinders the flow of gases, causes morphological changes in the membrane electrode assembly (MEA) leading to reversible and irreversible degradation of stack performance. Start-up performance is highly dependent on start-up operational conditions and procedures. The previous state of the stack will influence the ability to perform upon the next start-up and operation. Water generated during normal operation is vital and improves performance when properly managed. Liquid water present at shut-down can form ice and cause unwanted start-up effects. This phase change may cause damage to the MEA and gas diffusion media due to volume expansion. Removal of high water content at shutdown decreases proton conductivity which can delay start-up times. The United States Department of Energy (DOE) has established a set of criteria that will make fuel cell technology viable when attained. As specified by DOE, an 80 kWe fuel cell will be required by 2015 to reach 50% power in 30 seconds from start-up at an ambient temperature of -20°C. This work investigates freeze start-up in a multi-kilowatt stack approaching both shut-down conditioning and start-up operations to improve performance, moderate fuel cell damage and determine the limits of current stack technology. The investigation involved a Hydrogenics Corporation 5 kW 506 series fuel cell stack. The investigation is completed through conditioning the fuel cell start-up performance at various temperatures ranging from -5°C to below -20°C. The control of system start-up temperature is achieved with an environmental chamber that maintains the desired set point during dwell time and start-up. The supply gases for the experiment are conditioned at ambient stack temperature to create a realistic environment that could be experienced in colder weather climates. Temperature controls aim to maintain steady ambient temperatures during progressive start-up in order to best simulate ambient conditions. The control and operation of the fuel cell is maintained by the use of a fuel cell automated test station (FCATS™). FCATS supplies gas feeds, coolant medium and can control temperature and reactant humidity in reactants according to a prescribed procedure for continuous operation. The iv collection of data occurs by the same system recording cell voltage, temperatures, pressures, flow rates and current densities. A procedural start-up and characterization are conducted in order improve start-of performance and examine reactant flows, coolant activation time, stack conditioning and the effects by freezing temperatures. The resulting degradation is investigated by polarization curves and various ex-situ measurements. In this work, it was found that freeze start-up of a fuel cell stack can be aided and managed by conditioning the stack at shut-down and applying a procedure to successfully start-up and mitigate the damage that freezing can cause.

The explosive growth of the World-Wide-Web and the emergence of ecommerce are the major two factors that have led to the development of recommender systems (Resnick and Varian, 1997). The main task of recommender systems is to learn from users and recommend items (e.g. information, products or books) that match the users’ personal preferences. Recommender systems have been an active research area for more than a decade. Many different techniques and systems with distinct strengths have been developed to generate better quality recommendations. One of the main factors that affect recommenders’ recommendation quality is the amount of information resources that are available to the recommenders. The main feature of the recommender systems is their ability to make personalised recommendations for different individuals. However, for many ecommerce sites, it is difficult for them to obtain sufficient knowledge about their users. Hence, the recommendations they provided to their users are often poor and not personalised. This information insufficiency problem is commonly referred to as the cold-start problem. Most existing research on recommender systems focus on developing techniques to better utilise the available information resources to achieve better recommendation quality. However, while the amount of available data and information remains insufficient, these techniques can only provide limited improvements to the overall recommendation quality. In this thesis, a novel and intuitive approach towards improving recommendation quality and alleviating the cold-start problem is attempted. This approach is enriching the information resources. It can be easily observed that when there is sufficient information and knowledge base to support recommendation making, even the simplest recommender systems can outperform the sophisticated ones with limited information resources. Two possible strategies are suggested in this thesis to achieve the proposed information enrichment for recommenders: • The first strategy suggests that information resources can be enriched by considering other information or data facets. Specifically, a taxonomy-based recommender, Hybrid Taxonomy Recommender (HTR), is presented in this thesis. HTR exploits the relationship between users’ taxonomic preferences and item preferences from the combination of the widely available product taxonomic information and the existing user rating data, and it then utilises this taxonomic preference to item preference relation to generate high quality recommendations. • The second strategy suggests that information resources can be enriched simply by obtaining information resources from other parties. In this thesis, a distributed recommender framework, Ecommerce-oriented Distributed Recommender System (EDRS), is proposed. The proposed EDRS allows multiple recommenders from different parties (i.e. organisations or ecommerce sites) to share recommendations and information resources with each other in order to improve their recommendation quality. Based on the results obtained from the experiments conducted in this thesis, the proposed systems and techniques have achieved great improvement in both making quality recommendations and alleviating the cold-start problem.

Particulate number (PN) standards in current and future emissions legislation pose a challenge for designers and calibrators during the warm-up phases of cold direct injection spark ignition (DISI) engines. To achieve catalyst light-off conditions in the shortest time, engine strategies are often employed that inherently use more fuel to attain higher exhaust temperatures. These can lead to the generation of locally fuel-rich regions within the combustion chamber and hence the formation and emission of particulates. To meet these emissions requirements, further understanding of the DISI in-cylinder processes during cold-start are required. This thesis investigates the effect of cooling an optical research engine to temperatures as low as -7°C, one of the legislative test conditions. A high-speed 9 kHz optical investigation of the in-cylinder combustion and fuel spray along with in-cylinder pressure measurements was completed with the engine motored and fired at 1500 rpm during combustion conditions that were essentially homogeneous and stoichiometric. Results showed significant differences between the flame growth structures at various operating temperature conditions with the notable presence of fuel-rich regions, which are understood to be prominent areas of particulate formation. Measured engine performance parameters such as indicated mean effective pressure (IMEP) and mass fraction burned (MFB) times correlated with the observed differences in combustion characteristics and flame growth speed. It was shown that flash boiling of the fuel spray was present in the fully heated engine case and significantly reduced the penetration of the spray plume and the likelihood of piston crown and cylinder liner impingement. The flow and combustion processes of a transient production cold start-up strategy were analysed using high-speed particle image velocimetry (HSPIV). Results highlighted a broad range of flame structures and contrasting flame stoichiometry occurring at different times in the start-up process. Turbulent flow structures were identified that have an effect on the fuel spray development and combustion process as well as providing a path for cold-start emissions reduction. PN and transient hydrocarbon (HC) emissions were measured at cold conditions to further elucidate the effect of operating temperature and correlate emissions data with in-cylinder measurements. A clear link between the quantity and size range of particulate and HC emissions and operating temperature was shown and the precise in-cylinder location of HC emissions, caused by fuel impingement, was inferred from the HC emissions data.

As emissões de poluentes atmosféricos decorrentes de veículos automotores representam um grave problema ambiental. O modo de operação do veículo influencia diretamente a quantidade de poluentes emitidos. Quando um veículo inicia sua operação com motor frio, efeito denominado de partida a frio, a quantidade de poluentes emitidos torna-se consideravelmente maior em comparação às condições estabilizadas de temperatura do motor. O efeito da partida a frio é bastante representativo em viagens de curta duração, como é o caso dos deslocamentos urbanos. Este estudo propõe um método para a determinação e distribuição espacial do adicional de emissões de poluentes em partida a frio. Este método foi aplicado em Porto Alegre, utilizando informações de tráfego e da frota local coletados na pesquisa de entrevistas domiciliares, realizada no ano de 2003. Os fatores de emissão utilizados embasaram-se em um estudo realizado com veículos brasileiros. Os resultados da aplicação do método indicaram que a maior parte das partidas a frio ocorre na região central de Porto Alegre e suas adjacências, sendo maior no período matinal. Observou-se também que os maiores responsáveis pelo adicional por partida a frio são os veículos equipados com conversores catalíticos e injeção eletrônica de combustível. Entretanto, os veículos mais antigos, sem conversor catalítico e equipados com carburador, são os maiores responsáveis pela emissão total, adicional por partida a frio e emissão estabilizada de CO e HC nos períodos analisados. Através do método proposto neste estudo foi possível identificar áreas críticas que necessitam de ações de controle de emissões em partida a frio. Os resultados deste estudo podem subsidiar o planejamento e gerenciamento das condições ambientais provocadas pelas emissões veiculares em áreas urbanas. / Atmospheric pollution from vehicle emissions is a serious environmental problem. The vehicle operation mode influences directly in the amount of emitted pollutants. When a vehicle begins its operation with the cold engine, called as cold start effect, the amount of emitted pollutant becomes considerably higher than when in stabilized conditions of engine’s temperature. Cold start effect are very representative in short travels, such as urban trips. This study proposes a method to estimate the amount and spacial distribution of the additional cold start pollutant emissions. This method was applied to Porto Alegre, Brazil, using traffic and local fleet data from a household travel survey of 2003. Emissions factors were based on a study of Brazilian fleet. The results from the method application showed that cold start emissions in Porto Alegre are higher in the morning peak and most of the cold start emissions are concentrated in the town center and its adjacencies. The results also showed that the catalyst fuel injection vehicles are the main responsible for the additional cold start emissions. However, old vehicles, without catalyst and equipped with carburetor, are the main responsible for the total, cold start and running emissions, CO and HC emissions in both analyses periods. Through the proposed method, it was possible to identify critical areas that need control actions of cold start emissions. The results from this study can assist planning and management of the environmental conditions deriving from vehicular emissions in urban areas.

As emissões de poluentes atmosféricos decorrentes de veículos automotores representam um grave problema ambiental. O modo de operação do veículo influencia diretamente a quantidade de poluentes emitidos. Quando um veículo inicia sua operação com motor frio, efeito denominado de partida a frio, a quantidade de poluentes emitidos torna-se consideravelmente maior em comparação às condições estabilizadas de temperatura do motor. O efeito da partida a frio é bastante representativo em viagens de curta duração, como é o caso dos deslocamentos urbanos. Este estudo propõe um método para a determinação e distribuição espacial do adicional de emissões de poluentes em partida a frio. Este método foi aplicado em Porto Alegre, utilizando informações de tráfego e da frota local coletados na pesquisa de entrevistas domiciliares, realizada no ano de 2003. Os fatores de emissão utilizados embasaram-se em um estudo realizado com veículos brasileiros. Os resultados da aplicação do método indicaram que a maior parte das partidas a frio ocorre na região central de Porto Alegre e suas adjacências, sendo maior no período matinal. Observou-se também que os maiores responsáveis pelo adicional por partida a frio são os veículos equipados com conversores catalíticos e injeção eletrônica de combustível. Entretanto, os veículos mais antigos, sem conversor catalítico e equipados com carburador, são os maiores responsáveis pela emissão total, adicional por partida a frio e emissão estabilizada de CO e HC nos períodos analisados. Através do método proposto neste estudo foi possível identificar áreas críticas que necessitam de ações de controle de emissões em partida a frio. Os resultados deste estudo podem subsidiar o planejamento e gerenciamento das condições ambientais provocadas pelas emissões veiculares em áreas urbanas. / Atmospheric pollution from vehicle emissions is a serious environmental problem. The vehicle operation mode influences directly in the amount of emitted pollutants. When a vehicle begins its operation with the cold engine, called as cold start effect, the amount of emitted pollutant becomes considerably higher than when in stabilized conditions of engine’s temperature. Cold start effect are very representative in short travels, such as urban trips. This study proposes a method to estimate the amount and spacial distribution of the additional cold start pollutant emissions. This method was applied to Porto Alegre, Brazil, using traffic and local fleet data from a household travel survey of 2003. Emissions factors were based on a study of Brazilian fleet. The results from the method application showed that cold start emissions in Porto Alegre are higher in the morning peak and most of the cold start emissions are concentrated in the town center and its adjacencies. The results also showed that the catalyst fuel injection vehicles are the main responsible for the additional cold start emissions. However, old vehicles, without catalyst and equipped with carburetor, are the main responsible for the total, cold start and running emissions, CO and HC emissions in both analyses periods. Through the proposed method, it was possible to identify critical areas that need control actions of cold start emissions. The results from this study can assist planning and management of the environmental conditions deriving from vehicular emissions in urban areas.

Submitted by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2017-12-21T18:03:56Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertação - Janiel M. dos Santos.pdf: 1303124 bytes, checksum: 92eab239c46bd44d736df8430f688f9c (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2017-12-21T18:04:15Z (GMT) No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertação - Janiel M. dos Santos.pdf: 1303124 bytes, checksum: 92eab239c46bd44d736df8430f688f9c (MD5) / Made available in DSpace on 2017-12-21T18:04:15Z (GMT). No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertação - Janiel M. dos Santos.pdf: 1303124 bytes, checksum: 92eab239c46bd44d736df8430f688f9c (MD5) Previous issue date: 2017-10-02 / FAPEAM - Fundação de Amparo à Pesquisa do Estado do Amazonas / The growing production of multimedia content on the web has stimulated studies related to the improvement of the strategies responsible for the organization and recovery of this content in the applications. Among the several strategies, the assignment of a set of tags to an object expressing its content, called the tagging process, has been the subject of recent studies, mainly associative methods that are based on the exploration of co-occurrence patterns of tags. Although associative methods present state of the art results, few investigate the behavior of this type of recommendation in a state in which the object is being inserted into the system and has no previously associated information, characterized as cold start problem. To investigate the behavior of strategies in a cold start, its main motivation is to improve the quality of the recommendations, especially when the strategies are dependent on the information provided by the publishers of the content. This work presents an associative tags recommendation strategy that explores the concept of context graphs through the integration of co-occurrence and tags relevance metrics with the collaborative knowledge of existing relationships between concepts found in Wikipedia articles. With the balance in the valorization of the candidate tags for the recommendation, the proposed strategy obtained improvement in the quality of the re-commendation of the tags in videos that have a median number of tags. / A crescente produção de conteúdo multimídia na web tem estimulado estudos relacionados ao aprimoramento das estratégias responsáveis pela organização e recuperação desse conteúdo nas aplicações. Dentre as diversas estratégias existentes, a atribuição de um conjunto de etiquetas a um objeto expressando o seu conteúdo, denominada de processo de etiquetagem, têm sido objeto de estudos recentes, principalmente os métodos associativos que exploram padrões de coocorrência. Apesar dos métodos associativos apresentarem resultados estado da arte, poucos exploram o comportamento desse tipo de recomendação em um estado em que o objeto está sendo inserido no sistema e não possui informações previamente associadas, caracterizado como problema de cold start. Investigar o comportamento das estratégias, em um estado de cold start, tem como motivação principal melhorar a qualidade das recomendações, principalmente quando as estratégias ficam dependentes das informações fornecidas pelos publicadores do conteúdo. Nesta dissertação apresenta-se uma estratégia de recomendação associativa de etiquetas que explora o conceito de grafos de contexto, por meio da integração da coocorrência e métricas de relevância de etiquetas com o conhecimento colaborativo dos relacionamentos existentes entre conceitos presentes nos artigos da Wikipédia. Com o equilíbrio na valorização das etiquetas candidatas a recomendação, a estratégia proposta obteve melhoria na qualidade da recomendação das etiquetas em vídeos que possuem uma quantidade mediana de etiquetas.

Advertisers setting up search engine advertising campaigns for the first time need to place bids on keywords, but typically lack experience and data to determine ranks that maximize a keyword's profit (generally referred to as a cold-start problem). This article aims at solving the problem of bidding on keywords in newly set-up search engine advertising campaigns. We suggest that advertisers collect data from the Google Keyword Planner to obtain precise estimates of the percentage increases in prices per click and clickthrough rates, which are needed to calculate optimal bids (exact approach). Together with the profit contribution per conversion and the conversion rate, the advertiser might then set bids that maximize profit. In case advertisers cannot afford to collect the required data, we suggest two proxy approaches and evaluate their performance using the exact approach as a benchmark. The empirical study shows that both proxy approaches perform reasonably well-the easier approach to implement (proxy 2) sometimes performs even better than the more sophisticated one (proxy 1). As a consequence, advertisers might just use this very simple proxy when bidding on keywords in newly set-up SEA campaigns. This research extends the stream of literature on how to determine optimal bids, which so far focuses on campaigns that are already running and where the required data to calculate bids is already available. This research offers a novel approach of determining bids when advertisers lack the aforementioned information.