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Creep characteristics and shear strength of recycled asphalt blends

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The trend towards using recycled materials on new construction projects is growing as the cost for construction materials are ever increasing and the awareness of the responsibility we have to be good stewards of our environment is heightened. While recycled

The trend towards using recycled materials on new construction projects is growing as the cost for construction materials are ever increasing and the awareness of the responsibility we have to be good stewards of our environment is heightened. While recycled asphalt is sometimes used in pavements, its use as structural fill has been hindered by concern that it is susceptible to large long-term deformations (creep), preventing its use for a great many geotechnical applications. While asphalt/soil blends are often proposed as an alternative to 100% recycled asphalt fill, little data is available characterizing the geotechnical properties of recycled asphalt soil blends. In this dissertation, the geotechnical properties for five different recycled asphalt soil blends are characterized. Data includes the particle size distribution, plasticity index, creep, and shear strength for each blend. Blends with 0%, 25%, 50%, 75% and 100% recycled asphalt were tested. As the recycled asphalt material used for testing had particles sizes up to 1.5 inches, a large 18 inch diameter direct shear apparatus was used to determine the shear strength and creep characteristics of the material. The results of the testing program confirm that the creep potential of recycled asphalt is a geotechnical concern when the material is subjected to loads greater than 1500 pounds per square foot (psf). In addition, the test results demonstrate that the amount of soil blended with the recycled asphalt can greatly influence the creep and shear strength behavior of the composite material. Furthermore, there appears to be an optimal blend ratio where the composite material had better properties than either the recycled asphalt or virgin soil alone with respect to shear strength.

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2011

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Community supported agriculture membership: characterizing food and sustainability behaviors

Description

Community Supported Agriculture programs (CSAs) have become a viable local source of fresh agricultural goods and represent a potentially new way to improve fruit and vegetable consumption among individuals and families. Studies concerning CSAs have focused mainly on characteristics of

Community Supported Agriculture programs (CSAs) have become a viable local source of fresh agricultural goods and represent a potentially new way to improve fruit and vegetable consumption among individuals and families. Studies concerning CSAs have focused mainly on characteristics of the typical CSA member and motivations and barriers to join a CSA program. The purpose of this study was to examine whether behavior and attitudinal differences existed between current CSA members and a nonmember control group. Specifically, ecological attitudes, eating out behaviors, composting frequency, and family participation in food preparation were assessed. This study utilized an online survey comprising items from previous survey research as well as newly created items. A total of 115 CSA member and 233 control survey responses were collected. CSA members were more likely to be older, have more education, and have a higher income than the control group. The majority of CSA members surveyed were female, identified as non-Hispanic and Caucasian, earned a higher income, and reported being the primary food shopper and preparer. The majority of members also noted that the amount and variety of fruits and vegetables they ate and served their family increased as a result of joining a CSA. CSA members were more ecologically minded compared to the control group. Frequency of eating out was not significantly different between groups. However, eating out behaviors were different between income categories. CSA members spent significantly more money at each meal eaten away from home and spent significantly more money on eating out each week. In both cases, controlling for income attenuated differences between groups. CSA members composted at a significantly higher rate and took part in other eco-friendly behaviors more often than the control group. Finally, no significant difference was evident between the two groups when analyzing family involvement in food preparation and meal decision-making. Overall, some significant attitudinal and behavioral differences existed between CSA members and non-CSA members. Further research is necessary to examine other distinctions between the two groups and whether these differences occur as a result of CSA membership.

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2011

Robust margin based classifiers for small sample data

Description

In many classication problems data samples cannot be collected easily, example in drug trials, biological experiments and study on cancer patients. In many situations the data set size is small and there are many outliers. When classifying such data, example

In many classication problems data samples cannot be collected easily, example in drug trials, biological experiments and study on cancer patients. In many situations the data set size is small and there are many outliers. When classifying such data, example cancer vs normal patients the consequences of mis-classication are probably more important than any other data type, because the data point could be a cancer patient or the classication decision could help determine what gene might be over expressed and perhaps a cause of cancer. These mis-classications are typically higher in the presence of outlier data points. The aim of this thesis is to develop a maximum margin classier that is suited to address the lack of robustness of discriminant based classiers (like the Support Vector Machine (SVM)) to noise and outliers. The underlying notion is to adopt and develop a natural loss function that is more robust to outliers and more representative of the true loss function of the data. It is demonstrated experimentally that SVM's are indeed susceptible to outliers and that the new classier developed, here coined as Robust-SVM (RSVM), is superior to all studied classier on the synthetic datasets. It is superior to the SVM in both the synthetic and experimental data from biomedical studies and is competent to a classier derived on similar lines when real life data examples are considered.

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2011

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Constructing a model for small scale fish farmers

Description

Fish farming is a fast growing industry, which, although necessary to feed an ever growing worldwide population, has its share of negative environmental consequences, including the release of drugs and other waste into the ocean, the use of fish caught

Fish farming is a fast growing industry, which, although necessary to feed an ever growing worldwide population, has its share of negative environmental consequences, including the release of drugs and other waste into the ocean, the use of fish caught from the ocean to feed farm raised fish, and the escape of farm raised fish into natural bodies of water. However, the raising of certain types of fish, such as tilapia, seems to be an environmentally better proposition than raising other types of fish, such as salmon. This paper will explore the problems associated with fish farming, as well as offer a model, based on the literature, and interviews with fish farmers, to make small-scale fish farming both more environmentally, and more economically, sustainable. This paper culminates with a model for small-scale, specifically semi-subsistence, fish farmers. This model emphasizes education of the fish farmers, as well as educators learning from the fish farmers they interact with. The goal of this model is to help these fish farmers become both more environmentally and economically sustainable.

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2011

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Stereo based visual odometry

Description

The exponential rise in unmanned aerial vehicles has necessitated the need for accurate pose estimation under any extreme conditions. Visual Odometry (VO) is the estimation of position and orientation of a vehicle based on analysis of a sequence of images

The exponential rise in unmanned aerial vehicles has necessitated the need for accurate pose estimation under any extreme conditions. Visual Odometry (VO) is the estimation of position and orientation of a vehicle based on analysis of a sequence of images captured from a camera mounted on it. VO offers a cheap and relatively accurate alternative to conventional odometry techniques like wheel odometry, inertial measurement systems and global positioning system (GPS). This thesis implements and analyzes the performance of a two camera based VO called Stereo based visual odometry (SVO) in presence of various deterrent factors like shadows, extremely bright outdoors, wet conditions etc... To allow the implementation of VO on any generic vehicle, a discussion on porting of the VO algorithm to android handsets is presented too. The SVO is implemented in three steps. In the first step, a dense disparity map for a scene is computed. To achieve this we utilize sum of absolute differences technique for stereo matching on rectified and pre-filtered stereo frames. Epipolar geometry is used to simplify the matching problem. The second step involves feature detection and temporal matching. Feature detection is carried out by Harris corner detector. These features are matched between two consecutive frames using the Lucas-Kanade feature tracker. The 3D co-ordinates of these matched set of features are computed from the disparity map obtained from the first step and are mapped into each other by a translation and a rotation. The rotation and translation is computed using least squares minimization with the aid of Singular Value Decomposition. Random Sample Consensus (RANSAC) is used for outlier detection. This comprises the third step. The accuracy of the algorithm is quantified based on the final position error, which is the difference between the final position computed by the SVO algorithm and the final ground truth position as obtained from the GPS. The SVO showed an error of around 1% under normal conditions for a path length of 60 m and around 3% in bright conditions for a path length of 130 m. The algorithm suffered in presence of shadows and vibrations, with errors of around 15% and path lengths of 20 m and 100 m respectively.

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2010

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Operationalizing neighborhood resiliency: a grass-roots approach

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This research addresses the ability for neighborhoods to assess resiliency as it applies to their respective local areas. Two demographically and economically contrasting neighborhoods in Glendale, Arizona were studied to understand what residents' value and how those values link to

This research addresses the ability for neighborhoods to assess resiliency as it applies to their respective local areas. Two demographically and economically contrasting neighborhoods in Glendale, Arizona were studied to understand what residents' value and how those values link to key principles of resiliency. Through this exploratory research, a community-focused process was created to use these values in order to link them to key principles of resiliency and potential measureable indicators. A literature review was conducted to first assess definitions and key principles of resiliency. Second, it explored cases of neighborhoods or communities that faced a pressure or disaster and responded resiliently based on these general principles. Each case study demonstrated that resiliency at the neighborhood level was important to its ability to survive its respective pressure and emerge stronger. The Heart of Glendale and Thunderbird Palms were the two neighborhoods chosen to test the ability to operationalize neighborhood resiliency in the form of indicators. First, an in-depth interview was conducted with a neighborhood expert to understand each area's strengths and weaknesses and get a context for the neighborhood and how it has developed. Second, a visioning session was conducted with each neighborhood consisting of seven participants to discuss its values and how they relate to key principles of resiliency. The values were analyzed and used to shape locally relevant indicators. The results of this study found that the process of identifying participants' values and linking them to key principles of resiliency is a viable methodology for measuring neighborhood resiliency. It also found that indicators and values differed between the Heart of Glendale, a more economically vulnerable yet ethnically diverse area, than Thunderbird Palms, a more racially homogenous, middle income neighborhood. The Heart of Glendale valued the development of social capital more than Thunderbird Palms which placed a higher value on the condition of the built environment as a vehicle for stimulating vibrancy and resiliency in the neighborhood. However, both neighborhoods highly valued public education and providing opportunities for children to be future leaders in their local communities.

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2011

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Community food resource assessment in Central City South, Phoenix: a study of community capacity building

Description

Many studies have shown that access to healthy food in the US is unevenly distributed and that supermarkets and other fresh food retailers are less likely to be located in low-income minority communities, where convenience and dollar stores are more

Many studies have shown that access to healthy food in the US is unevenly distributed and that supermarkets and other fresh food retailers are less likely to be located in low-income minority communities, where convenience and dollar stores are more prevalent grocery options. I formed a partnership with Phoenix Revitalization Corporation, a local community development organization engaged in Central City South, Phoenix, to enhance the community's capacity to meet its community health goals by improving access to healthy food. I used a community-based participatory approach that blended qualitative and quantitative elements to accommodate collaboration between both academic and non-academic partners. Utilizing stakeholder interviews, Nutrition Environment Measures Surveys (NEMS), and mapping to analyze the community's food resources, research revealed that the community lacks adequate access to affordable, nutritious food. Community food stores (n=14) scored an average of 10.9 out of a possible 54 points using the NEMS scoring protocol. The community food assessment is an essential step in improving access to healthy food for CCS residents and provides a baseline for tracking progress to improve residents' food access. Recommendations were drafted by the research partnership to equip and empower the community with strategic, community-specific interventions based on the research findings.

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2011

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Restaurant industry sustainability: barriers and solutions to sustainable practice indicators

Description

Restaurants have a cumulative impact on the environment, economy, and society. The majority of restaurants are small-to-medium enterprises (SMEs). Review of sustainability and industry literature revealed that considering restaurants as businesses with sustainable development options is the most appropriate way

Restaurants have a cumulative impact on the environment, economy, and society. The majority of restaurants are small-to-medium enterprises (SMEs). Review of sustainability and industry literature revealed that considering restaurants as businesses with sustainable development options is the most appropriate way to evaluate their sustainable practices or lack thereof. Sustainable development is the means by which a company progresses towards achieving an identified set of sustainability goals and harnesses competitive advantage. The purpose of this thesis is to identify barriers to implementing sustainable practices in restaurants, and explore ways that restaurateurs can incorporate sustainable business practices. Energy consumption, water use, waste production, and food throughput are the four sustainability indicators addressed in this thesis. Interviews were conducted with five Tempe, Arizona restaurants, two of which consider their operations to be sustainable, and three of which are traditional restaurants. Results show that for traditional restaurants, the primary barriers to implementing sustainable business practices are cost, lack of awareness, and space. For sustainability-marketed restaurants, the barriers included a lack of knowledge or legal concerns. The sustainability-marketed restaurants have energy-efficient equipment and locally source a majority of their food purchases. There is a marked difference between the two types of restaurants in perception of barriers to sustainable business practices. I created a matrix to identify whether each indicator metric was applicable and present at a particular restaurant, and the potential barriers to implementing sustainable practices in each of the four indicator areas. Restaurants can use the assessment matrix to compare their current practices with sustainable practices and find ways to implement new or enhance existing sustainable practices. Identifying the barriers from within restaurants increases our understanding of the reasons why sustainable practices are not automatically adopted by SMEs. The assessment matrix can help restaurants overcome barriers to achieving sustainability by highlighting how to incorporate sustainable business practices.

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2011

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An ontology-based approach to attribute management in ABAC environment

Description

Attribute Based Access Control (ABAC) mechanisms have been attracting a lot of interest from the research community in recent times. This is especially because of the flexibility and extensibility it provides by using attributes assigned to subjects as the basis

Attribute Based Access Control (ABAC) mechanisms have been attracting a lot of interest from the research community in recent times. This is especially because of the flexibility and extensibility it provides by using attributes assigned to subjects as the basis for access control. ABAC enables an administrator of a server to enforce access policies on the data, services and other such resources fairly easily. It also accommodates new policies and changes to existing policies gracefully, thereby making it a potentially good mechanism for implementing access control in large systems, particularly in today's age of Cloud Computing. However management of the attributes in ABAC environment is an area that has been little touched upon. Having a mechanism to allow multiple ABAC based systems to share data and resources can go a long way in making ABAC scalable. At the same time each system should be able to specify their own attribute sets independently. In the research presented in this document a new mechanism is proposed that would enable users to share resources and data in a cloud environment using ABAC techniques in a distributed manner. The focus is mainly on decentralizing the access policy specifications for the shared data so that each data owner can specify the access policy independent of others. The concept of ontologies and semantic web is introduced in the ABAC paradigm that would help in giving a scalable structure to the attributes and also allow systems having different sets of attributes to communicate and share resources.

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2014

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Cluster metrics and temporal coherency in pixel based matrices

Description

In this thesis, the application of pixel-based vertical axes used within parallel coordinate plots is explored in an attempt to improve how existing tools can explain complex multivariate interactions across temporal data. Several promising visualization techniques are combined, such as:

In this thesis, the application of pixel-based vertical axes used within parallel coordinate plots is explored in an attempt to improve how existing tools can explain complex multivariate interactions across temporal data. Several promising visualization techniques are combined, such as: visual boosting to allow for quicker consumption of large data sets, the bond energy algorithm to find finer patterns and anomalies through contrast, multi-dimensional scaling, flow lines, user guided clustering, and row-column ordering. User input is applied on precomputed data sets to provide for real time interaction. General applicability of the techniques are tested against industrial trade, social networking, financial, and sparse data sets of varying dimensionality.

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2014