The recent growth in wireless communications presents a new challenge to multimedia communications. Digital image transmission is a very common form of multimedia communication. Due to limited bandwidth and broadcast nature of the wireless medium, it is necessary to compress and encrypt images before they are sent. On the other hand, it is important to efficiently utilize the limited energy in wireless devices. In a wireless device, two major sources of energy consumption are energy used for computation and energy used for transmission. Computation energy can be reduced by minimizing the time spent on compression and encryption. Transmission energy can be reduced by sending a smaller image file that is obtained by compressing the original highest quality image. Image quality is often sacrificed in the compression process. Therefore, users should have the flexibility to control the image quality to determine whether such a tradeoff is acceptable. It is also desirable for users to have control over image quality in different areas of the image so that less important areas can be compressed more, while retaining the details in important areas. To reduce computations for encryption, a partial encryption scheme can be employed to encrypt only the critical parts of an image file, without sacrificing security. This thesis proposes a scalable and secure image representation scheme that allows users to select different image quality and security levels. The binary space partitioning (BSP) tree presentation is selected because this representation allows convenient compression and scalable encryption. The Advanced Encryption Standard (AES) is chosen as the encryption algorithm because it is fast and secure. Our experimental result shows that our new tree construction method and our pruning formula reduces execution time, hence computation energy, by about 90%. Our image quality prediction model accurately predicts image quality to within 2-3dB of the actual image PSNR.

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This study used the socio-eco efficiency framework as an application tool to resilience the green environment at Kombolecha industrial zone by balancing the water consumption growth and green environmental tradeoffs. In addition, it aimed to determine the significant indicators, which associated with the water consumption and recycling efficiency. The consumers (factories and households) socio-eco efficiency practices were limited and then caused groundwater degradation and green environmental depletion. Previous studies, for instance, BASF (2009), ESCAP (2011) eco-efficiency, and Sailing et al., (2013) SEE balance (socio-eco efficiency) analysis targeted the company’s product portfolio and quality improvement. This study, however, considered both factories and household’s consumption activities that were proven to manifest in a complex water consumption compared to the production process. The study integrated social, economic and environmental indicators and determined the socio-eco efficiency effects on theresource consumption growth and green environment tradeoffs; water consumption and recycling efficiency. Subsequently, the study then developed a socio-eco efficiency model that used to balance the gaps between water consumption and recycling intensity inefficiency. The socio- eco efficiency indicators could, thus, be an applied tool that could be measured by employing the binary logistic regression, instrumental variable model, simultaneous equation model and the propensity score matching estimation. Based on this, this study results indicated that the household’s awareness, perception and consumption behaviours concerning the green mind adoption, product, market, technology and jobs use were strongly associated and influenced by the water resource consumption growth and green environment tradeoffs at the 5 percent significance level. Particularly, the household’s social aspects, consumer’s culture, behaviour and poverty; economic (monthly income) and environmental aspects (waterquantity limit and waste recycle) were found to bestatistically significant and strongly altered the water resource consumption and recycling efficiency by 0.000 values at the 95 percent confidence level. This study implication was thesocio-eco efficiency framework, which was key the finding of the study that holds the three key indicators, did directly associate and significant determine the factories and household’s groundwater consumption and recycling intensity differently by 0.000 values at the 95 percent confidence level. The socio- eco efficiency model could thus be an analytical tool that could be applied into groundwater consumption and recycling process. The socio-eco efficiency resource model, which is a key tool to resilient the green environment, optimized the water consumption and recycling efficiency and could be incorporated into the groundwater and green environment protection policy of Ethiopia. This study, in a circular fashion, proved socio-eco efficiency application and resolved some of the consumption paradox in the factories and household’s groundwater consumption and recycling processes. Thenon-integrated indicators and inapplicability of the socio-eco efficiency framework, nonetheless, made the green environment cautiously. So that a tactical integrative socio-eco efficiency resource model, particularly, green finances, such as green water tax, lease, paymenhave to be incorporated during the groundwater consumption that recovers the green environment attainments in Kombolecha and at large in Ethiopia. / Environmental Sciences / Ph. D. (Environment Management)

A indústria da construção civil é considerada como uma das grandes causadoras de impactos negativos ao meio ambiente, desde a extração de matéria prima, até o fim de vida de seus empreendimentos. Dentre os principais impactos ambientais ocasionados pelo setor, destacase a geração de resíduos de construção civil (RCC), a qual é intensificada em função do desenvolvimento de grandes centros urbanos e a consequente necessidade de implantação de empreendimentos de infraestrutura. Nesse contexto, uma das estratégias mais eficientes para redução de RCC está associada à realização de escolhas adequadas na fase de projeto, com enfoque de prevenção na fonte geradora. No entanto, é complexa a inclusão de fatores de sustentabilidade, tais como os de minimização de RCC, em projetos da construção civil. Logo, torna-se relevante a adoção de métodos e ferramentas de suporte ao processo decisório. Contudo, os métodos existentes são direcionados, em sua maioria, a projetos de edificações, havendo uma importante lacuna associada a projetos de infraestrutura urbana. Assim sendo, esta pesquisa objetiva a proposição de mecanismos de apoio à tomada de decisão, para a minimização de RCC, em projetos de infraestrutura urbana, com dois diferentes enfoques: controle e avaliação; e estrutura de orientação. Para a composição dos mecanismos de controle e avaliação, foram identificadas boas práticas para redução da geração de RCC na fase de projeto, a partir de pesquisa bibliográfica, análise documental de projetos, e pesquisa quali-quantitativa junto a especialistas. Essas boas práticas deram origem a demandas ambientais a serem atendidas pelos projetos de infraestrutura urbana, motivando a elaboração de um método estruturado para gerenciamento de requisitos ambientais e de trade-offs, como apoio à tomada de decisão projetual. O método teve como base a ferramenta Quality Function Deployment (QFD), no qual foi desdobrada a Matriz da Qualidade, a partir da opinião de especialistas atuantes em diferentes etapas do desenvolvimento de projetos de infraestrutura urbana. Como principais contribuições da pesquisa, focada na minimização de RCC, podem ser consideradas: (i) a obtenção de um checklist, como instrumento de controle e avaliação da qualidade dos projetos a serem desenvolvidos; (ii) a identificação de requisitos e de indicadores ambientais prioritários associados a esses projetos; e (iii) a elaboração de uma sistemática para gerenciamento de trade-offs existentes em projetos de infraestrutura urbana menos impactantes ambientalmente. / The construction industry is considered as one of the great causes of negative impacts to the environment, from the extraction of raw material, until the end-of-life of its projects. Among the main environmental impacts caused by the sector, can be highlighted the generation of construction waste (CW), which is intensified due to the development of large urban centers and the consequent need to implement infrastructure projects. In that context, one of the most efficient strategies to reduce CW is associated with making adequate choices in the design phase, with a focus on prevention at the source. However, it is complex to include sustainability factors, such as CW minimization, in construction designs. Therefore, it is relevant to adopt methods and tools to support the decision-making process. However, the existing methods are mostly directed to building designs, with an important gap associated with urban infrastructure designs. Thus, this research aims at proposing mechanisms to support decision making for the CW minimization in urban infrastructure projects, with two different approaches: control and evaluation; and guidance structure. For the composition of the control and the evaluation mechanisms, best practices were identified to reduce the CW generation in the design phase, based on literature review, documentary analysis of projects, and qualitative and quantitative surveys with specialists. Those best practices have given rise to environmental demands to be met by urban infrastructure projects, motivating the elaboration of a structured method for managing environmental requirements and trade-offs, as a support for the decision making design. The method was based on the Quality Function Deployment (QFD) tool, in which the quality matrix deployment, based on the opinion of specialists working in different stages of the development of urban designs. The main contributions of the research, focused on the CW minimization, can be considered: (i) obtaining a checklist, as an instrument to control and evaluate the quality of the designs to be developed; (ii) identification of requirements and of priority environmental indicators associated with those projects; and (iii) the development of a systematic for managing tradeoffs in urban infrastructure projects that are less environmentally impacting.

Network Utility Maximization (NUM) provides a key conceptual framework to study reward allocation amongst a collection of users/entities in disciplines as diverse as economics, law and engineering. However when the available resources and/or users' utilities vary over time, reward allocations will tend to vary, which in turn may have a detrimental impact on the users' overall satisfaction or quality of experience. In this thesis, we introduce a generalization of the NUM framework which incorporates the detrimental impact of temporal variability in a user's allocated rewards and explicitly incorporates Mean-Variability-Fairness tradeoffs, i.e., tradeoffs amongst the mean and variability in users' reward allocations, as well as fairness across users. We propose a simple online algorithm to realize these tradeoffs, which, under stationary ergodic assumptions, is shown to be asymptotically optimal, i.e., achieves a long term performance equal to that of an offline algorithm with knowledge of the future variability in the system. This substantially extends work on NUM to an interesting class of relevant problems where users/entities are sensitive to temporal variability in their service or allocated rewards. We extend the theoretical framework and tools developed for realizing Mean-Variability-Fairness tradeoffs to develop a simple online algorithm to solve the problem of optimizing video delivery in networks. The tremendous increase in mobile video traffic projected for the future along with insufficiency of available wireless network capacity makes this one of the most important networking problems today. Specifically, we consider a network supporting video clients streaming stored video, and focus on the problem of jointly optimizing network resource allocation and video clients' video quality adaptation. Our objective is to fairly maximize video clients' video Quality of Experience (QoE) realizing Mean-Variability-Fairness tradeoffs, incorporating client preferences on rebuffering time and the cost of video delivery. We present a simple asymptotically optimal online algorithm NOVA (Network Optimization for Video Adaptation) to solve the problem. Our algorithm uses minimal communication, 'distributes' the tasks of network resource allocation to a centralized network controller, and video clients' video quality adaptation to the respective video clients. Further, the quality adaptation is also optimal for standalone video clients, and is an asynchronous algorithm well suited for use in the Dynamic Adaptive Streaming over HTTP (DASH) framework. We also extend NOVA for use with more general video QoE models, and study NOVA accounting for practical considerations like time varying number of video clients, sharing with other types of traffic, performance under legacy resource allocation policies, videos with variable sized segments etc. / text

xvii, 160 p. : ill. (some col.) A print copy of this thesis is available through the UO Libraries. Search the library catalog for the location and call number. / Restoring oak habitats is an emerging conservation priority in Oregon's Willamette Valley. Both private and public landowners face multiple challenges to conservation and restoration of oak habitats, including a lack of knowledge about the potential tradeoffs and constraints for achieving multiple priorities on a given site. This study simulated 25 alternative oak habitat restoration scenarios to develop estimates of outcomes related to six different restoration priorities: costs, income potential, habitat value, scenic quality, fire hazard reduction potential, and time requirements. Model results indicated that initial land conditions strongly influence a landowner's ability to optimize among these different priorities. To assist landowners with decision-making, model estimates were organized into a digital decision matrix that communicates advantages and tradeoffs associated with each alternative scenario. In doing so, it aims to help landowners choose restoration goals that better meet their broader needs and objectives. / Committee in Charge: Dr. Bart Johnson, Chair; Dr. Robert Ribe

A indústria da construção civil é considerada como uma das grandes causadoras de impactos negativos ao meio ambiente, desde a extração de matéria prima, até o fim de vida de seus empreendimentos. Dentre os principais impactos ambientais ocasionados pelo setor, destacase a geração de resíduos de construção civil (RCC), a qual é intensificada em função do desenvolvimento de grandes centros urbanos e a consequente necessidade de implantação de empreendimentos de infraestrutura. Nesse contexto, uma das estratégias mais eficientes para redução de RCC está associada à realização de escolhas adequadas na fase de projeto, com enfoque de prevenção na fonte geradora. No entanto, é complexa a inclusão de fatores de sustentabilidade, tais como os de minimização de RCC, em projetos da construção civil. Logo, torna-se relevante a adoção de métodos e ferramentas de suporte ao processo decisório. Contudo, os métodos existentes são direcionados, em sua maioria, a projetos de edificações, havendo uma importante lacuna associada a projetos de infraestrutura urbana. Assim sendo, esta pesquisa objetiva a proposição de mecanismos de apoio à tomada de decisão, para a minimização de RCC, em projetos de infraestrutura urbana, com dois diferentes enfoques: controle e avaliação; e estrutura de orientação. Para a composição dos mecanismos de controle e avaliação, foram identificadas boas práticas para redução da geração de RCC na fase de projeto, a partir de pesquisa bibliográfica, análise documental de projetos, e pesquisa quali-quantitativa junto a especialistas. Essas boas práticas deram origem a demandas ambientais a serem atendidas pelos projetos de infraestrutura urbana, motivando a elaboração de um método estruturado para gerenciamento de requisitos ambientais e de trade-offs, como apoio à tomada de decisão projetual. O método teve como base a ferramenta Quality Function Deployment (QFD), no qual foi desdobrada a Matriz da Qualidade, a partir da opinião de especialistas atuantes em diferentes etapas do desenvolvimento de projetos de infraestrutura urbana. Como principais contribuições da pesquisa, focada na minimização de RCC, podem ser consideradas: (i) a obtenção de um checklist, como instrumento de controle e avaliação da qualidade dos projetos a serem desenvolvidos; (ii) a identificação de requisitos e de indicadores ambientais prioritários associados a esses projetos; e (iii) a elaboração de uma sistemática para gerenciamento de trade-offs existentes em projetos de infraestrutura urbana menos impactantes ambientalmente. / The construction industry is considered as one of the great causes of negative impacts to the environment, from the extraction of raw material, until the end-of-life of its projects. Among the main environmental impacts caused by the sector, can be highlighted the generation of construction waste (CW), which is intensified due to the development of large urban centers and the consequent need to implement infrastructure projects. In that context, one of the most efficient strategies to reduce CW is associated with making adequate choices in the design phase, with a focus on prevention at the source. However, it is complex to include sustainability factors, such as CW minimization, in construction designs. Therefore, it is relevant to adopt methods and tools to support the decision-making process. However, the existing methods are mostly directed to building designs, with an important gap associated with urban infrastructure designs. Thus, this research aims at proposing mechanisms to support decision making for the CW minimization in urban infrastructure projects, with two different approaches: control and evaluation; and guidance structure. For the composition of the control and the evaluation mechanisms, best practices were identified to reduce the CW generation in the design phase, based on literature review, documentary analysis of projects, and qualitative and quantitative surveys with specialists. Those best practices have given rise to environmental demands to be met by urban infrastructure projects, motivating the elaboration of a structured method for managing environmental requirements and trade-offs, as a support for the decision making design. The method was based on the Quality Function Deployment (QFD) tool, in which the quality matrix deployment, based on the opinion of specialists working in different stages of the development of urban designs. The main contributions of the research, focused on the CW minimization, can be considered: (i) obtaining a checklist, as an instrument to control and evaluate the quality of the designs to be developed; (ii) identification of requirements and of priority environmental indicators associated with those projects; and (iii) the development of a systematic for managing tradeoffs in urban infrastructure projects that are less environmentally impacting.

A indústria da construção civil é considerada como uma das grandes causadoras de impactos negativos ao meio ambiente, desde a extração de matéria prima, até o fim de vida de seus empreendimentos. Dentre os principais impactos ambientais ocasionados pelo setor, destacase a geração de resíduos de construção civil (RCC), a qual é intensificada em função do desenvolvimento de grandes centros urbanos e a consequente necessidade de implantação de empreendimentos de infraestrutura. Nesse contexto, uma das estratégias mais eficientes para redução de RCC está associada à realização de escolhas adequadas na fase de projeto, com enfoque de prevenção na fonte geradora. No entanto, é complexa a inclusão de fatores de sustentabilidade, tais como os de minimização de RCC, em projetos da construção civil. Logo, torna-se relevante a adoção de métodos e ferramentas de suporte ao processo decisório. Contudo, os métodos existentes são direcionados, em sua maioria, a projetos de edificações, havendo uma importante lacuna associada a projetos de infraestrutura urbana. Assim sendo, esta pesquisa objetiva a proposição de mecanismos de apoio à tomada de decisão, para a minimização de RCC, em projetos de infraestrutura urbana, com dois diferentes enfoques: controle e avaliação; e estrutura de orientação. Para a composição dos mecanismos de controle e avaliação, foram identificadas boas práticas para redução da geração de RCC na fase de projeto, a partir de pesquisa bibliográfica, análise documental de projetos, e pesquisa quali-quantitativa junto a especialistas. Essas boas práticas deram origem a demandas ambientais a serem atendidas pelos projetos de infraestrutura urbana, motivando a elaboração de um método estruturado para gerenciamento de requisitos ambientais e de trade-offs, como apoio à tomada de decisão projetual. O método teve como base a ferramenta Quality Function Deployment (QFD), no qual foi desdobrada a Matriz da Qualidade, a partir da opinião de especialistas atuantes em diferentes etapas do desenvolvimento de projetos de infraestrutura urbana. Como principais contribuições da pesquisa, focada na minimização de RCC, podem ser consideradas: (i) a obtenção de um checklist, como instrumento de controle e avaliação da qualidade dos projetos a serem desenvolvidos; (ii) a identificação de requisitos e de indicadores ambientais prioritários associados a esses projetos; e (iii) a elaboração de uma sistemática para gerenciamento de trade-offs existentes em projetos de infraestrutura urbana menos impactantes ambientalmente. / The construction industry is considered as one of the great causes of negative impacts to the environment, from the extraction of raw material, until the end-of-life of its projects. Among the main environmental impacts caused by the sector, can be highlighted the generation of construction waste (CW), which is intensified due to the development of large urban centers and the consequent need to implement infrastructure projects. In that context, one of the most efficient strategies to reduce CW is associated with making adequate choices in the design phase, with a focus on prevention at the source. However, it is complex to include sustainability factors, such as CW minimization, in construction designs. Therefore, it is relevant to adopt methods and tools to support the decision-making process. However, the existing methods are mostly directed to building designs, with an important gap associated with urban infrastructure designs. Thus, this research aims at proposing mechanisms to support decision making for the CW minimization in urban infrastructure projects, with two different approaches: control and evaluation; and guidance structure. For the composition of the control and the evaluation mechanisms, best practices were identified to reduce the CW generation in the design phase, based on literature review, documentary analysis of projects, and qualitative and quantitative surveys with specialists. Those best practices have given rise to environmental demands to be met by urban infrastructure projects, motivating the elaboration of a structured method for managing environmental requirements and trade-offs, as a support for the decision making design. The method was based on the Quality Function Deployment (QFD) tool, in which the quality matrix deployment, based on the opinion of specialists working in different stages of the development of urban designs. The main contributions of the research, focused on the CW minimization, can be considered: (i) obtaining a checklist, as an instrument to control and evaluate the quality of the designs to be developed; (ii) identification of requirements and of priority environmental indicators associated with those projects; and (iii) the development of a systematic for managing tradeoffs in urban infrastructure projects that are less environmentally impacting.