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Description
Currently Java is making its way into the embedded systems and mobile devices like androids. The programs written in Java are compiled into machine independent binary class byte codes. A Java Virtual Machine (JVM) executes these classes. The Java platform additionally specifies the Java Native Interface (JNI). JNI allows Java code that runs within a JVM to interoperate with applications or libraries that are written in other languages and compiled to the host CPU ISA. JNI plays an important role in embedded system as it provides a mechanism to interact with libraries specific to the platform. This thesis addresses the overhead incurred in the JNI due to reflection and serialization when objects are accessed on android based mobile devices. It provides techniques to reduce this overhead. It also provides an API to access objects through its reference through pinning its memory location. The Android emulator was used to evaluate the performance of these techniques and we observed that there was 5 - 10 % performance gain in the new Java Native Interface.
ContributorsChandrian, Preetham (Author) / Lee, Yann-Hang (Thesis advisor) / Davulcu, Hasan (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Created2011
Description
As pointed out in the keynote speech by H. V. Jagadish in SIGMOD'07, and also commonly agreed in the database community, the usability of structured data by casual users is as important as the data management systems' functionalities. A major hardness of using structured data is the problem of easily retrieving information from them given a user's information needs. Learning and using a structured query language (e.g., SQL and XQuery) is overwhelmingly burdensome for most users, as not only are these languages sophisticated, but the users need to know the data schema. Keyword search provides us with opportunities to conveniently access structured data and potentially significantly enhances the usability of structured data. However, processing keyword search on structured data is challenging due to various types of ambiguities such as structural ambiguity (keyword queries have no structure), keyword ambiguity (the keywords may not be accurate), user preference ambiguity (the user may have implicit preferences that are not indicated in the query), as well as the efficiency challenges due to large search space. This dissertation performs an expansive study on keyword search processing techniques as a gateway for users to access structured data and retrieve desired information. The key issues addressed include: (1) Resolving structural ambiguities in keyword queries by generating meaningful query results, which involves identifying relevant keyword matches, identifying return information, composing query results based on relevant matches and return information. (2) Resolving structural, keyword and user preference ambiguities through result analysis, including snippet generation, result differentiation, result clustering, result summarization/query expansion, etc. (3) Resolving the efficiency challenge in processing keyword search on structured data by utilizing and efficiently maintaining materialized views. These works deliver significant technical contributions towards building a full-fledged search engine for structured data.
ContributorsLiu, Ziyang (Author) / Chen, Yi (Thesis advisor) / Candan, Kasim S (Committee member) / Davulcu, Hasan (Committee member) / Jagadish, H V (Committee member) / Arizona State University (Publisher)
Created2011
Description
Phosphorus (P), an essential element for life, is becoming increasingly scarce, and its global management presents a serious challenge. As urban environments dominate the landscape, we need to elucidate how P cycles in urban ecosystems to better understand how cities contribute to — and provide opportunities to solve — problems of P management. The goal of my research was to increase our understanding of urban P cycling in the context of urban resource management through analysis of existing ecological and socio-economic data supplemented with expert interviews in order to facilitate a transition to sustainable P management. Study objectives were to: I) Quantify and map P stocks and flows in the Phoenix metropolitan area and analyze the drivers of spatial distribution and dynamics of P flows; II) examine changes in P-flow dynamics at the urban agricultural interface (UAI), and the drivers of those changes, between 1978 and 2008; III) compare the UAI's average annual P budget to the global agricultural P budget; and IV) explore opportunities for more sustainable P management in Phoenix. Results showed that Phoenix is a sink for P, and that agriculture played a primary role in the dynamics of P cycling. Internal P dynamics at the UAI shifted over the 30-year study period, with alfalfa replacing cotton as the main locus of agricultural P cycling. Results also suggest that the extent of P recycling in Phoenix is proportionally larger than comparable estimates available at the global scale due to the biophysical characteristics of the region and the proximity of various land uses. Uncertainty remains about the effectiveness of current recycling strategies and about best management strategies for the future because we do not have sufficient data to use as basis for evaluation and decision-making. By working in collaboration with practitioners, researchers can overcome some of these data limitations to develop a deeper understanding of the complexities of P dynamics and the range of options available to sustainably manage P. There is also a need to better connect P management with that of other resources, notably water and other nutrients, in order to sustainably manage cities.
ContributorsMetson, Genevieve (Author) / Childers, Daniel (Thesis advisor) / Aggarwal, Rimjhim (Thesis advisor) / Redman, Charles (Committee member) / Arizona State University (Publisher)
Created2011
Description
Reliable extraction of human pose features that are invariant to view angle and body shape changes is critical for advancing human movement analysis. In this dissertation, the multifactor analysis techniques, including the multilinear analysis and the multifactor Gaussian process methods, have been exploited to extract such invariant pose features from video data by decomposing various key contributing factors, such as pose, view angle, and body shape, in the generation of the image observations. Experimental results have shown that the resulting pose features extracted using the proposed methods exhibit excellent invariance properties to changes in view angles and body shapes. Furthermore, using the proposed invariant multifactor pose features, a suite of simple while effective algorithms have been developed to solve the movement recognition and pose estimation problems. Using these proposed algorithms, excellent human movement analysis results have been obtained, and most of them are superior to those obtained from state-of-the-art algorithms on the same testing datasets. Moreover, a number of key movement analysis challenges, including robust online gesture spotting and multi-camera gesture recognition, have also been addressed in this research. To this end, an online gesture spotting framework has been developed to automatically detect and learn non-gesture movement patterns to improve gesture localization and recognition from continuous data streams using a hidden Markov network. In addition, the optimal data fusion scheme has been investigated for multicamera gesture recognition, and the decision-level camera fusion scheme using the product rule has been found to be optimal for gesture recognition using multiple uncalibrated cameras. Furthermore, the challenge of optimal camera selection in multi-camera gesture recognition has also been tackled. A measure to quantify the complementary strength across cameras has been proposed. Experimental results obtained from a real-life gesture recognition dataset have shown that the optimal camera combinations identified according to the proposed complementary measure always lead to the best gesture recognition results.
ContributorsPeng, Bo (Author) / Qian, Gang (Thesis advisor) / Ye, Jieping (Committee member) / Li, Baoxin (Committee member) / Spanias, Andreas (Committee member) / Arizona State University (Publisher)
Created2011
Description
This thesis describes a synthetic task environment, CyberCog, created for the purposes of 1) understanding and measuring individual and team situation awareness in the context of a cyber security defense task and 2) providing a context for evaluating algorithms, visualizations, and other interventions that are intended to improve cyber situation awareness. CyberCog provides an interactive environment for conducting human-in-loop experiments in which the participants of the experiment perform the tasks of a cyber security defense analyst in response to a cyber-attack scenario. CyberCog generates the necessary performance measures and interaction logs needed for measuring individual and team cyber situation awareness. Moreover, the CyberCog environment provides good experimental control for conducting effective situation awareness studies while retaining realism in the scenario and in the tasks performed.
ContributorsRajivan, Prashanth (Author) / Femiani, John (Thesis advisor) / Cooke, Nancy J. (Thesis advisor) / Lindquist, Timothy (Committee member) / Gary, Kevin (Committee member) / Arizona State University (Publisher)
Created2011
Description
With the introduction of compressed sensing and sparse representation,many image processing and computer vision problems have been looked at in a new way. Recent trends indicate that many challenging computer vision and image processing problems are being solved using compressive sensing and sparse representation algorithms. This thesis assays some applications of compressive sensing and sparse representation with regards to image enhancement, restoration and classication. The first application deals with image Super-Resolution through compressive sensing based sparse representation. A novel framework is developed for understanding and analyzing some of the implications of compressive sensing in reconstruction and recovery of an image through raw-sampled and trained dictionaries. Properties of the projection operator and the dictionary are examined and the corresponding results presented. In the second application a novel technique for representing image classes uniquely in a high-dimensional space for image classification is presented. In this method, design and implementation strategy of the image classification system through unique affine sparse codes is presented, which leads to state of the art results. This further leads to analysis of some of the properties attributed to these unique sparse codes. In addition to obtaining these codes, a strong classier is designed and implemented to boost the results obtained. Evaluation with publicly available datasets shows that the proposed method outperforms other state of the art results in image classication. The final part of the thesis deals with image denoising with a novel approach towards obtaining high quality denoised image patches using only a single image. A new technique is proposed to obtain highly correlated image patches through sparse representation, which are then subjected to matrix completion to obtain high quality image patches. Experiments suggest that there may exist a structure within a noisy image which can be exploited for denoising through a low-rank constraint.
ContributorsKulkarni, Naveen (Author) / Li, Baoxin (Thesis advisor) / Ye, Jieping (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2011
Description
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.
ContributorsSchaper, Jeffery M (Author) / Kavazanjian, Edward (Thesis advisor) / Houston, Sandra L. (Committee member) / Zapata, Claudia E (Committee member) / Arizona State University (Publisher)
Created2011
Description
ABSTRACT Water resources in many parts of the world are subject to increasing stress because of (a) the growth in demand caused by population increase and economic development, (b) threats to supply caused by climate and land cover change, and (c) a heightened awareness of the importance of maintaining water supplies to other parts of the ecosystem. An additional factor is the quality of water management. The United States-Mexican border provides an example of poor water management combined with increasing demand for water resources that are both scarce and uncertain. This dissertation focuses on the problem of water management in the border city of Ciudad Juarez, Chihuahua. The city has attracted foreign investment during the last few decades, largely due to relatively low environmental and labor costs, and to a range of tax incentives and concessions. This has led to economic and population growth, but also to higher demand for public services such as water which leads to congestion and scarcity. In particular, as water resources have become scarce, the cost of water supply has increased. The dissertation analyzes the conditions that allow for the efficient use of water resources at sustainable levels of economic activity--i.e., employment and investment. In particular, it analyzes the water management strategies that lead to an efficient and sustainable use of water when the source of water is either an aquifer, or there is conjunctive use of ground and imported water. The first part of the dissertation constructs a model of the interactive effects of water supply, wage rates, inward migration of labor and inward investment of capital. It shows how growing water scarcity affects population growth through the impact it has on real wage rates, and how this erodes the comparative advantage of Ciudad Juarez--low wages--to the point where foreign investment stops. This reveals the very close connection between water management and the level of economic activity in Ciudad Juarez. The second part of the dissertation examines the effect of sustainable and efficient water management strategies on population and economic activity levels under two different settings. In the first Ciudad Juarez relies exclusively on ground water to meet demand--this reflects the current situation of Ciudad Juarez. In the second Ciudad Juarez is able both to import water and to draw on aquifers to meet demand. This situation is motivated by the fact that Ciudad Juarez is considering importing water from elsewhere to maintain its economic growth and mitigate the overdraft of the Bolson del Hueco aquifer. Both models were calibrated on data for Ciudad Juarez, and then used to run experiments with respect to different environmental and economic conditions, and different water management options. It is shown that for a given set of technological, institutional and environmental conditions, the way water is managed in a desert environment determines the long run equilibrium levels of employment, investment and output. It is also shown that the efficiency of water management is consistent with the sustainability of water use and economic activity. Importing water could allow the economy to operate at higher levels of activity than where it relies solely on local aquifers. However, at some scale, water availability will limit the level of economic activity, and the disposable income of the residents of Ciudad Juarez.
ContributorsGarduno Angeles, Gustavo Leopoldo (Author) / Perrings, Charles (Thesis advisor) / Holway, Jim (Thesis advisor) / Aggarwal, Rimjhim (Committee member) / Arizona State University (Publisher)
Created2011
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 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.
ContributorsFreeman, Emily McConnell (Author) / Eakin, Hallie (Thesis advisor) / Basile, George (Thesis advisor) / Williams, Eric D. (Committee member) / Arizona State University (Publisher)
Created2011
Description
The greatest challenge facing humanity in the twenty-first century is our ability to reconcile the capacity of natural systems to support continued improvement in human welfare around the globe. Over the last decade, the scientific community has attempted to formulate research agendas in response to what they view as the problems of sustainability. Perhaps the most prominent and wide-ranging of these efforts has been sustainability science, an interdisciplinary, problem-driven field that seeks to address fundamental questions on human-environment interactions. This project examines how sustainability scientists grapple with and bound the deeply social, political and normative dimensions of both characterizing and pursuing sustainability. Based on in-depth interviews with leading researchers and a content analysis of the relevant literature, this project first addresses three core questions: (1) how sustainability scientists define and bound sustainability; (2) how and why various research agendas are being constructed to address these notions of sustainability; (3) and how scientists see their research contributing to societal efforts to move towards sustainability. Based on these results, the project explores the tensions between scientific efforts to study and inform sustainability and social action. It discusses the implications of transforming sustainability into the subject of scientific analysis with a focus on the power of science to constrain discourse and the institutional and epistemological contexts that link knowledge to societal outcomes. Following this analysis, sustainability science is repositioned, borrowing Herbert Simon's concept, as a "science of design." Sustainability science has thus far been too focused on understanding the "problem-space"--addressing fundamental questions about coupled human-natural systems. A new set objectives and design principles are proposed that would move the field toward a more solutions-oriented approach and the enrichment of public reasoning and deliberation. Four new research streams that would situate sustainability science as a science of design are then discussed: creating desirable futures, socio-technical change, sustainability values, and social learning. The results serve as a foundation for a sustainability science that is evaluated on its ability to frame sustainability problems and solutions in ways that make them amenable to democratic and pragmatic social action.
ContributorsMiller, Thaddeus R. (Author) / Minteer, Ben A (Thesis advisor) / Redman, Charles L. (Committee member) / Sarewitz, Daniel (Committee member) / Wiek, Arnim (Committee member) / Arizona State University (Publisher)
Created2011