Aging and leaking water infrastructure wastes water resources and creates public health risks. Upgrading of potable water systems represents a large financial burden for water utilities and private property owners. The conventional approaches of repair, rehabilitation and replacement are very effective, but will take decades to implement even if a financial commitment to do so was made immediately. A novel approach of in-situ remediation of leaks, achieved by harnessing the ability of water or pipe to repair leaks via clogging, could potentially reduce leak rates and extend the lifetime of existing infrastructure at relatively low cost and inconvenience. Physical clogging, precipitation and metallic corrosion were identified as major mechanisms of in-situ leak remediation in potable water pipelines. Autogenous repair (i.e., self-repair without added particles) of small leak-holes (150–"1000 μm) in copper and iron was validated in the laboratory at water pHs of 3.0–11.0, operating water pressures of 20–60 psi, upward and downward leak orientations, and for a range of water chemistries. In bench scale experiments, the time to repair of iron pipe leaks increased with leak size to the power of 0.89–1.89, and decreased with pipe wall thickness to the power of -1.9 to -1.0. The time to repair of copper pipe leaks increased with water pressure to the power of 1.7. Additionally, the waters with a higher DO and corrosivity as measured by RSI, significantly decreased the time to repair of carbon steel 400 μm leaks by 50–70%. The presence of chlorine dioxide significantly increased the fraction of repaired 200 μm copper pipe leaks by 3 times when compared to the control without any disinfectant. In the building scale study, the fraction of repaired iron pipe leaks decreased with the logarithmic leak size with a slope of -0.65 after one-year duration of experiments, while leak orientation and water pressure were not influential in time to or likelihood of repair for iron pipe leaks. Addition of calcium carbonate particles (~8.8 μ]m), silica particles (~29 μm) and wood ash particles (~160 μm) in Blacksburg, VA tap water at a water pressure of 10 psi increased the fraction of remediated iron pipe leaks of 280–1000 μm diameter sizes. Although the control condition with no added particles for 58 days resulted in remediation of 0/12 leaks, remediation rate increased to 1/12 with calcium carbonate particles, to 10/12 with silica particles and to 10/12 with wood ash particles. Leak size and particle size played an important role in controlling the remediation success rate. The strength of the in-situ leak repair was sometimes very strong and resilient. The sealing materials of leak-holes repaired at 20–60 psi could sometimes withstand a 100 psi water pressure without failure, demonstrating the potential of the approach to sustain aging and leaking infrastructure. In-situ leak repair can also occur naturally, and the success rate might be unintentionally altered by adjustment of chemistry or treatments that decrease or increase particulates. / Ph. D.

This thesis extends the literature on institutional accounting by providing a new channel---proprietary information leakage between competitors---through which institutions affect accounting attributes and information disclosure. Weak property rights protection exacerbates outflow of proprietary information on operation, thus reduces managers' incentive to disclose financial information and other operation related information since the disclosed information will be helpful for competitors to learn more about proprietary information on operation of the firm. The channel is built with two links. One is the link between property rights protection and R&D spillovers, which proxy for proprietary information disclosure, and the other is the link between R&D spillovers and transparency. Empirical results show that R&D spillovers are negatively associated with regional property rights protection. In addition, I find that innovation output depends less on in house R&D investment and more on R&D spillovers from competitors in regions with weak property rights protection than in regions with strong protection and that the level of R&D expenditures is positively associated with property rights protection. Some evidence is found that firms with more R&D spillovers are more likely to have opaque earnings and disclose less firm-specific information. The relationship is stronger in regions with weak property rights protection than in regions with strong protection, indicating that firms are more likely to utilize opacity to prevent proprietary information leakage when R&D spillovers are large. / Yu, Xin. / Adviser: Joseph P. H. Fan. / Source: Dissertation Abstracts International, Volume: 70-06, Section: A, page: 2123. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 72-79). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

O controle de perdas em sistemas de distribuição de água para abastecimento é uma preocupação constante, e uma tarefa fundamental para a solução do problema é a detecção rápida e confiável dos vazamentos que frequentemente iniciam em qualquer ponto da rede. Uma abordagem promissória é a detecção de vazamentos baseada na análise de sinais adquiridos pelo monitoramento das redes durante sua operação, e dentro dela se enquadra este trabalho. É desenvolvido um sistema de reconhecimento de padrões para análise de sinais de pressão e vazão que permite identificar se durante a aquisição do sinal aconteceu um vazamento ou não. Para a conformação desse sistema diversas técnicas são exploradas, incluindo a extração de características no domínio do tempo (energia, entropia, número de cruzamentos por zero) e na decomposição wavelet (distribuição da energia nas componentes). Também é explorado o uso de algoritmos para classificação de diferentes tipos (vizinhos mais próximos, árvore de decisão, regra de decisão, Naive Bayes, máquina de vetor suporte e rede neural artificial com funções de base radial). Sinais são adquiridos junto ao circuito hidráulico experimental, que permitiu a simulação da ocorrência de um vazamento na rede, para constituir uma amplia base de dados com sinais de exemplo. Além da revisão bibliográfica e os conceitos relativos às metodologias exploradas, são apresentadas neste documento as análises que conduzem à criação do sistema de reconhecimento de padrões mais apropriado para o problema. Das análises dos diferentes métodos considerados é definido o sistema de reconhecimento de padrões, em suas etapas de segmentação e padronização, extração de características e classificação. A avaliação do sistema proposto mostra um desempenho totalmente satisfatório, com reconhecimento acertado de sinais vinculados ou não a um vazamento em mais de 95% dos testes. / Control of losses in water supply systems is a constant concern, and a key to the solution of this problem is the rapid and reliable detection of leaks that often begin anywhere on the network. A promising approach to solve the problem is the leak detection based on the analysis of signals acquired by monitoring the network in operation, and this research fits with that approach. Its developed a pattern recognition system for the analysis of pressure and flow signals, which identifies whether a leak happened during signal acquisition. Several techniques are exploited for forming this system, including the feature extraction in the time domain (energy, entropy, zero crossings count) and in the wavelet decomposition (energy distribution in the components). Also, the use of different types of algorithms for classification (nearest neighbors, decision tree, decision rule, Naive Bayes, support vector machine and artificial neural network with radial basis functions) is explored. Signals are acquired from the experimental hydraulic circuit, allowing the simulation of the onset of a leak in the network, to form a big database of example signals. Besides the literature review and the concepts relating to the considered methods, in this document are shown the analyses leading to the creation of the pattern recognition system most appropriate for the problem. The analysis of the methods considered allows defining the pattern recognition system, which is composed by segmentation and standardization, feature extraction and classification. The evaluation of the proposed system shows a completely satisfactory performance, recognizing rightly the signals as linked or not to a leak in more than 95% of the tests.

O trabalho apresenta uma proposta de metodologia para diagnóstico de sistemas de distribuição de água através da elaboração, passo a passo, e de uso de simuladores hidráulicos apoiados por aplicativos de geoprocessamento. Utilizando-se de dados reais como o histórico operacional de vazamentos dentro da região adotada num intervalo de tempo, espera-se fornecer ao analista um instrumento de análise visual do comportamento hidráulico do setor em função de uma escala progressiva de ocorrências, mapeada através de cores, permitindo avaliar a qualidade do modelo hidráulico como um todo, corrigindo desvios para que o mesmo reproduza eficientemente o comportamento real da rede de distribuição. Através deste, esperase avaliar as consequências da variação das pressões e vazões durante o dia, subsidiando tomadas de decisão, permitindo avaliação das opções e a redução de riscos e investimentos desnecessários. / The work presents a proposed methodology for diagnosis of water distribution systems through the development, step-by-step and hydraulic simulators use supported by geoprocessing applications. Using real data and operational history of leaks within the region adopted a time interval, is expected to provide the analyst a tool for visual analysis of the hydraulic behavior of the sector according to a progressive scale of occurrences, mapped through colors, in order to evaluate the quality of hydraulic model as a whole, correcting deviations so that it efficiently reproduces the actual behavior of the distribution network. Through this, it is expected to evaluate the consequences of variation of pressure and flows during the day, supporting decision-making, allowing the evaluation of the options and the reduction of unnecessary risks and investments.

O trabalho apresenta uma proposta de metodologia para diagnóstico de sistemas de distribuição de água através da elaboração, passo a passo, e de uso de simuladores hidráulicos apoiados por aplicativos de geoprocessamento. Utilizando-se de dados reais como o histórico operacional de vazamentos dentro da região adotada num intervalo de tempo, espera-se fornecer ao analista um instrumento de análise visual do comportamento hidráulico do setor em função de uma escala progressiva de ocorrências, mapeada através de cores, permitindo avaliar a qualidade do modelo hidráulico como um todo, corrigindo desvios para que o mesmo reproduza eficientemente o comportamento real da rede de distribuição. Através deste, esperase avaliar as consequências da variação das pressões e vazões durante o dia, subsidiando tomadas de decisão, permitindo avaliação das opções e a redução de riscos e investimentos desnecessários. / The work presents a proposed methodology for diagnosis of water distribution systems through the development, step-by-step and hydraulic simulators use supported by geoprocessing applications. Using real data and operational history of leaks within the region adopted a time interval, is expected to provide the analyst a tool for visual analysis of the hydraulic behavior of the sector according to a progressive scale of occurrences, mapped through colors, in order to evaluate the quality of hydraulic model as a whole, correcting deviations so that it efficiently reproduces the actual behavior of the distribution network. Through this, it is expected to evaluate the consequences of variation of pressure and flows during the day, supporting decision-making, allowing the evaluation of the options and the reduction of unnecessary risks and investments.

<p>Excessive memory use may cause severe performance problems and system crashes. Without appropriate tools, it may be difficult or impossible to determine why a program is using too much memory. This applies even though Python provides automatic memory management --- garbage collection can help avoid many memory allocation bugs, but only to a certain extent due to the lack of information during program execution. There is still a need for tools helping the programmer to understand the memory behaviour of programs, especially in complicated situations. The primary motivation for Heapy is that there has been a lack of such tools for Python.</p><p>The main questions addressed by Heapy are how much memory is used by objects, what are the objects of most interest for optimization purposes, and why are objects kept in memory. Memory leaks are often of special interest and may be found by comparing snapshots of the heap population taken at different times. Memory profiles, using different kinds of classifiers that may include retainer information, can provide quick overviews revealing optimization possibilities not thought of beforehand. Reference patterns and shortest reference paths provide different perspectives of object access patterns to help explain why objects are kept in memory.</p>

Les nouvelles technologies introduisent de nouveaux problèmes et risques. Par exemple, les internautes sont constamment tracés et profilés sur l'Internet. Ce profilage permet aux divers sites de personaliser et ainsi d'améliorer le service qu'ils fournissent à chaque internaute. Cependant ce profilage introduit aussi des problèmes d'intimité et de protection de la vie privée. Il est d'ailleurs reconnu que ces données personnelles sont souvent échangées, voire vendues, et qu'il existe une vraie economie des données personnelles. Cet thèse étudie comment ces données personnelles, et en particulier les historique Web - c'est à dire la liste des sites Internet visités par un internaute-, sont collectées, échangées et vendues. Elle propose une analyse de la vie privée des systèmes de vente aux enchères des publicités ciblés. Elle montre comment les différents acteurs de la publicité en ligne collectent et s'echangent les données personnelles, et étudie les risques pour les Internautes. Elle propose également une analyse économique et montre, notamment, que les données sont bradées pour quelques millièmes de dollars. / New medias introduce new problems and risks. There are important security and privacy considerations related to online interactions. Users browsing the Web leave a constant trail of traces referring to their Web actions. A large number of entities take advantage of this data to constantly improve how the Web services function, often offering rich personalization capabilities -- to achieve this, user data is needed. To obtain user data, Web users are being tracked and profiled. Having user data may help enhancing functionality and usability, but it also has the potential of introducing complex privacy problems, related to data collection, storing and processing. The incentives to gather user data are of economical nature: user data is monetized. We start with a description of privacy problems and risks, highlighting their roots in technology changes; users must constantly struggle to adapt to changes. The legal frameworks relating to privacy are about to change: Web companies will have to adopt to new realities. First part of this thesis is devoted to measuring the consequences of private data leaks and tracking. We show how Web browsing history convey insight relating to user interests. We study the risks of Web browsing history leaks. We point out that browsing history is to large extent unique; we perform this basing on a dataset of more than 350k partial history fingerprints. The consequence here is that if browsing histories are personally identifiable information (PII), the upcoming European privacy legal frameworks could potentially result in strict guidelines for their collection, storing and processing. The tracking measurement of third-party resources confirms the popular notion that most of the tracking is carried by US-based companies. This creates interesting information asymmetries, which are of great importance, especially if user data could be simply equated to financial and economical benefits. Second part discusses value of privacy. We study the emerging technology of Real-Time Bidding (RTB), online real-time auctions of ad spaces. We highlight that during the auction phase, bidders in RTB obtain user information such as the visited Web site or user location and they pay for serving ads. In other words, user data flows are strictly related to financial flows. User data is thus monetized. We expose an interesting design characteristic of RTB which allows us to monitor a channel with winning bids -- dynamically established fees bidders pay for displaying their ads. We perform a detailed measurement of RTB and study how this price for user information varies according to such aspects like time of day, user location and type of visited Web site. Using data obtained from real users, we also study the effect of user profiles. Users are indeed treated differently, based on their previously visited Web sites (browsing history). We observed variability in prices of RTB ads, based on those traits. The price for user information in RTB is volatile and typically is in the range of $0.0001-$0.001. This study also had a decidedly important transparency part. We introduced a Web browser extension allowing to discover the price that bidders in RTB pay. This demonstrates how the user awareness could be improved. In part three, we continue the transparency trail. We point out that Web browsers allow every Web site (or third-party resources they include) to record the mouse movements of their visitors. We point out that recent advances in mouse movement analysis points to the notion that mouse movements can potentially be used to recognize and track Web users across the Web; mouse movement analysis can also be used to infer users' demographics data such as age. We highlight the existence of mouse movement analytics -- third-party scripts specializing in mouse movement collections. We also suggest that Web browser vendors should consider including permissions for accessing the API enabling these kind of recordings.

Made available in DSpace on 2014-10-09T12:48:28Z (GMT). No. of bitstreams: 0 / Made available in DSpace on 2014-10-09T13:57:39Z (GMT). No. of bitstreams: 1 09064.pdf: 3638993 bytes, checksum: 8325a415e5861bfd1f85383134e3dcee (MD5) / Dissertacao (Mestrado Profissionalizante em Lasers em Odontologia) / IPEN/D-MPLO / Intituto de Pesquisas Energeticas e Nucleares, IPEN/CNEN-SP; Faculdade de Odontologia, Universidade de Sao Paulo

Les nouvelles technologies introduisent de nouveaux problèmes et risques. Par exemple, les internautes sont constamment tracés et profilés sur l'Internet. Ce profilage permet aux divers sites de personaliser et ainsi d'améliorer le service qu'ils fournissent à chaque internaute. Cependant ce profilage introduit aussi des problèmes d'intimité et de protection de la vie privée. Il est d'ailleurs reconnu que ces données personnelles sont souvent échangées, voire vendues, et qu'il existe une vraie economie des données personnelles. Cet thèse étudie comment ces données personnelles, et en particulier les historique Web - c'est à dire la liste des sites Internet visités par un internaute-, sont collectées, échangées et vendues. Elle propose une analyse de la vie privée des systèmes de vente aux enchères des publicités ciblés. Elle montre comment les différents acteurs de la publicité en ligne collectent et s'echangent les données personnelles, et étudie les risques pour les Internautes. Elle propose également une analyse économique et montre, notamment, que les données sont bradées pour quelques millièmes de dollars. / New medias introduce new problems and risks. There are important security and privacy considerations related to online interactions. Users browsing the Web leave a constant trail of traces referring to their Web actions. A large number of entities take advantage of this data to constantly improve how the Web services function, often offering rich personalization capabilities -- to achieve this, user data is needed. To obtain user data, Web users are being tracked and profiled. Having user data may help enhancing functionality and usability, but it also has the potential of introducing complex privacy problems, related to data collection, storing and processing. The incentives to gather user data are of economical nature: user data is monetized. We start with a description of privacy problems and risks, highlighting their roots in technology changes; users must constantly struggle to adapt to changes. The legal frameworks relating to privacy are about to change: Web companies will have to adopt to new realities. First part of this thesis is devoted to measuring the consequences of private data leaks and tracking. We show how Web browsing history convey insight relating to user interests. We study the risks of Web browsing history leaks. We point out that browsing history is to large extent unique; we perform this basing on a dataset of more than 350k partial history fingerprints. The consequence here is that if browsing histories are personally identifiable information (PII), the upcoming European privacy legal frameworks could potentially result in strict guidelines for their collection, storing and processing. The tracking measurement of third-party resources confirms the popular notion that most of the tracking is carried by US-based companies. This creates interesting information asymmetries, which are of great importance, especially if user data could be simply equated to financial and economical benefits. Second part discusses value of privacy. We study the emerging technology of Real-Time Bidding (RTB), online real-time auctions of ad spaces. We highlight that during the auction phase, bidders in RTB obtain user information such as the visited Web site or user location and they pay for serving ads. In other words, user data flows are strictly related to financial flows. User data is thus monetized. We expose an interesting design characteristic of RTB which allows us to monitor a channel with winning bids -- dynamically established fees bidders pay for displaying their ads. We perform a detailed measurement of RTB and study how this price for user information varies according to such aspects like time of day, user location and type of visited Web site. Using data obtained from real users, we also study the effect of user profiles. Users are indeed treated differently, based on their previously visited Web sites (browsing history). We observed variability in prices of RTB ads, based on those traits. The price for user information in RTB is volatile and typically is in the range of $0.0001-$0.001. This study also had a decidedly important transparency part. We introduced a Web browser extension allowing to discover the price that bidders in RTB pay. This demonstrates how the user awareness could be improved. In part three, we continue the transparency trail. We point out that Web browsers allow every Web site (or third-party resources they include) to record the mouse movements of their visitors. We point out that recent advances in mouse movement analysis points to the notion that mouse movements can potentially be used to recognize and track Web users across the Web; mouse movement analysis can also be used to infer users' demographics data such as age. We highlight the existence of mouse movement analytics -- third-party scripts specializing in mouse movement collections. We also suggest that Web browser vendors should consider including permissions for accessing the API enabling these kind of recordings.

Made available in DSpace on 2014-10-09T12:51:53Z (GMT). No. of bitstreams: 0 / Made available in DSpace on 2014-10-09T14:06:43Z (GMT). No. of bitstreams: 0 / Tese (Doutoramento) / IPEN/T / Instituto de Pesquisas Energeticas e Nucleares - IPEN/CNEN-SP