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- Genre: Masters Thesis
- Creators: Li, Baoxin
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
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
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
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.
ContributorsGupta, Sidharth (Author) / Kim, Seungchan (Thesis advisor) / Welfert, Bruno (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Created2011
Description
Since the Convention on Biological Diversity was established in 1992, more importance has been given to the conservation of genetic resources in the international community. In 2001, the International Treaty on Plant Genetic Resources for Food and Agriculture (PGRFA) focused on conserving plant genetic resources, including crop wild relatives (CWR). Some of these genetic resources hold desirable traits--such as transfer of plant disease resistance, improvement of nutritional content, or increased resistance to climate change--that can improve commercial crops. For many years, ex situex situ conservation was the prevalent form of protecting plant genetic resources. However, after PGRFA was published in 1998, in situ techniques have increasingly been applied to conserve wild relatives and enhance domesticated crops.In situ techniques are preferred when possible, since they allow for continued evolution of traits through natural selection, and viability of seed stock through continuous germination and regeneration. In my research, I identified regions in Bolivia and rated them according to their potential for successful programs of iin situ conservation of wild crop relatives. In particular, I analyzed areas according to the following criteria: a) The prevalence of CWRs. b) The impacts of climate change, land use change, population growth, and economic development on the continued viability of CWRs in an area. c) The socio-political and economic conditions that might impede or facilitate successful conservation programs and outcomes. This work focuses on three genera of particular importance in Bolivia: Peanut (Arachis spp.), Potato (Solanum spp.) and Quinoa (Chenopodium spp.). I analyzed the above factors for each municipality in Bolivia (the smallest scale for which appropriate data were available). The results indicate which municipalities are most likely to successfully engage in CWR conservation projects. Finally, I present guidelines for the creation of conservation projects that pinpoint some of the potential risks and difficulties with in situ conservation programs in Bolivia and more generally.
ContributorsGonzalez-Paredes, Cecilia (Author) / Kinzig, Ann (Thesis advisor) / Aggarwal, Rimjhim (Committee member) / Chhetri, Netra (Committee member) / Arizona State University (Publisher)
Created2011
Description
Slum development and growth is quite popular in developing countries. Many studies have been done on what social and economic factors are the drivers in establishment of informal settlements at a single cross-section of time, however limited work has been done in studying their spatial growth patterns over time. This study attempts to study a sample of 30 informal settlements that exist in the National Capital Territory of India over a period of 40 years and identify relationships between the spatial growth rates and relevant factors identified in previous socio-economic studies of slums using advanced statistical methods. One of the key contributions of this paper is indicating the usefulness of satellite imagery or remote sensing data in spatial-longitudinal studies. This research utilizes readily available LANDSAT images to recognize the decadal spatial growth from 1970 to 2000, and also in extension, calculate the BI (transformed NDVI) as a proxy for the intensity of development for the settlements. A series of regression models were run after processing the data, and the levels of significance were then studied and compared to see which relationships indicated the highest levels of significance. It was observed that the change in BI had a higher strength of relationships with the change in independent variables than the settlement area growth. Also, logarithmic and cubic models showed the highest R-Square values than any other tested models.
ContributorsPrakash, Mihir (Author) / Guhathakurta, Subhrajit (Thesis advisor) / Myint, Soe W. (Committee member) / Aggarwal, Rimjhim (Committee member) / Arizona State University (Publisher)
Created2011
Description
Haiti has witnessed high deforestation rates in recent decades, caused largely by the fuel needs of a growing population. The resulting soil loss is estimated to have contributed towards a decline in agricultural productivity of 0.5% -1.2% per year since 1997. Recent studies show the potential of biochar use through pyrolysis technology to increase crop yields and improve soil health. However, the appropriateness of this technology in the context of Haiti remains unexplored. The three objectives of this research were to identify agricultural- and fuel-use-related needs and gaps in rural Haitian communities; determine the appropriateness of biochar pyrolyzer technology, used to convert agricultural biomass into a carbon-rich charcoal; and develop an action-oriented plan for use by development organizations, communities, and governmental institutions to increase the likelihood of adoption. Data were collected using participatory rural appraisal techniques involving 30 individual interviews and three focus-group discussions in the villages of Cinquantin and La Boule in the La Coupe region of central Haiti. Topics discussed include agricultural practices and assets, fuel use and needs, technology use and adoption, and social management practices. The Sustainable Livelihoods framework was used to examine the assets of households and the livelihood strategies being employed. Individual and focus group interviews were analyzed to identify specific needs and gaps. E.M. Rogers' Diffusion of Innovations theory was used to develop potential strategies for the introduction of pyrolysis technology. Preliminary results indicate biochar pyrolysis has potential to address agricultural and fuel needs in rural Haiti. Probable early adopters of biochar technology include households that have adopted new agricultural techniques in the past, and those with livestock. Education about biochar, and a variety of pyrolysis technology options from which villagers may select, are important factors in successful adoption of biochar use. A grain mill as an example in one of the study villages provides a model of ownership and use of pyrolysis technology that may increase its likelihood of successful adoption. Additionally, women represent a group that may be well suited to control a new local biochar enterprise, potentially benefiting the community.
ContributorsDelaney, Michael Ryan (Author) / Aggarwal, Rimjhim (Thesis advisor) / Chhetri, Nalini (Committee member) / Henderson, Mark (Committee member) / Arizona State University (Publisher)
Created2011
Description
Real-world environments are characterized by non-stationary and continuously evolving data. Learning a classification model on this data would require a framework that is able to adapt itself to newer circumstances. Under such circumstances, transfer learning has come to be a dependable methodology for improving classification performance with reduced training costs and without the need for explicit relearning from scratch. In this thesis, a novel instance transfer technique that adapts a "Cost-sensitive" variation of AdaBoost is presented. The method capitalizes on the theoretical and functional properties of AdaBoost to selectively reuse outdated training instances obtained from a "source" domain to effectively classify unseen instances occurring in a different, but related "target" domain. The algorithm is evaluated on real-world classification problems namely accelerometer based 3D gesture recognition, smart home activity recognition and text categorization. The performance on these datasets is analyzed and evaluated against popular boosting-based instance transfer techniques. In addition, supporting empirical studies, that investigate some of the less explored bottlenecks of boosting based instance transfer methods, are presented, to understand the suitability and effectiveness of this form of knowledge transfer.
ContributorsVenkatesan, Ashok (Author) / Panchanathan, Sethuraman (Thesis advisor) / Li, Baoxin (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2011
Description
Typically, the complete loss or severe impairment of a sense such as vision and/or hearing is compensated through sensory substitution, i.e., the use of an alternative sense for receiving the same information. For individuals who are blind or visually impaired, the alternative senses have predominantly been hearing and touch. For movies, visual content has been made accessible to visually impaired viewers through audio descriptions -- an additional narration that describes scenes, the characters involved and other pertinent details. However, as audio descriptions should not overlap with dialogue, sound effects and musical scores, there is limited time to convey information, often resulting in stunted and abridged descriptions that leave out many important visual cues and concepts. This work proposes a promising multimodal approach to sensory substitution for movies by providing complementary information through haptics, pertaining to the positions and movements of actors, in addition to a film's audio description and audio content. In a ten-minute presentation of five movie clips to ten individuals who were visually impaired or blind, the novel methodology was found to provide an almost two time increase in the perception of actors' movements in scenes. Moreover, participants appreciated and found useful the overall concept of providing a visual perspective to film through haptics.
ContributorsViswanathan, Lakshmie Narayan (Author) / Panchanathan, Sethuraman (Thesis advisor) / Hedgpeth, Terri (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Created2011
Description
Drosophila melanogaster, as an important model organism, is used to explore the mechanism which governs cell differentiation and embryonic development. Understanding the mechanism will help to reveal the effects of genes on other species or even human beings. Currently, digital camera techniques make high quality Drosophila gene expression imaging possible. On the other hand, due to the advances in biology, gene expression images which can reveal spatiotemporal patterns are generated in a high-throughput pace. Thus, an automated and efficient system that can analyze gene expression will become a necessary tool for investigating the gene functions, interactions and developmental processes. One investigation method is to compare the expression patterns of different developmental stages. Recently, however, the expression patterns are manually annotated with rough stage ranges. The work of annotation requires professional knowledge from experienced biologists. Hence, how to transfer the domain knowledge in biology into an automated system which can automatically annotate the patterns provides a challenging problem for computer scientists. In this thesis, the problem of stage annotation for Drosophila embryo is modeled in the machine learning framework. Three sparse learning algorithms and one ensemble algorithm are used to attack the problem. The sparse algorithms are Lasso, group Lasso and sparse group Lasso. The ensemble algorithm is based on a voting method. Besides that the proposed algorithms can annotate the patterns to stages instead of stage ranges with high accuracy; the decimal stage annotation algorithm presents a novel way to annotate the patterns to decimal stages. In addition, some analysis on the algorithm performance are made and corresponding explanations are given. Finally, with the proposed system, all the lateral view BDGP and FlyFish images are annotated and several interesting applications of decimal stage value are revealed.
ContributorsPan, Cheng (Author) / Ye, Jieping (Thesis advisor) / Li, Baoxin (Committee member) / Farin, Gerald (Committee member) / Arizona State University (Publisher)
Created2012