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- Genre: Masters Thesis
- Creators: Arizona State University
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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
Intimate coupling of Ti2 photocatalysis and biodegradation (ICPB) offers potential for degrading biorecalcitrant and toxic organic compounds much better than possible with conventional wastewater treatments. This study reports on using a novel sponge-type, Ti2-coated biofilm carrier that shows significant adherence of Ti2 to its exterior and the ability to accumulate biomass in its interior (protected from UV light and free radicals). First, this carrier was tested for ICPB in a continuous-flow photocatalytic circulating-bed biofilm reactor (PCBBR) to mineralize biorecalcitrant organic: 2,4,5-trichlorophenol (TCP). Four mechanisms possibly acting of ICPB were tested separately: TCP adsorption, UV photolysis/photocatalysis, and biodegradation. The carrier exhibited strong TCP adsorption, while photolysis was negligible. Photocatalysis produced TCP-degradation products that could be mineralized and the strong adsorption of TCP to the carrier enhanced biodegradation by relieving toxicity. Validating the ICPB concept, biofilm was protected inside the carriers from UV light and free radicals. ICPB significantly lowered the diversity of the bacterial community, but five genera known to biodegrade chlorinated phenols were markedly enriched. Secondly, decolorization and mineralization of reactive dyes by ICPB were investigated on a refined Ti2-coated biofilm carrier in a PCBBR. Two typical reactive dyes: Reactive Black 5 (RB5) and Reactive Yellow 86 (RY86), showed similar first-order kinetics when being photocatalytically decolorized at low pH (~4-5), which was inhibited at neutral pH in the presence of phosphate or carbonate buffer, presumably due to electrostatic repulsion from negatively charged surface sites on Ti2, radical scavenging by phosphate or carbonate, or both. In the PCBBR, photocatalysis alone with Ti2-coated carriers could remove RB5 and COD by 97% and 47%, respectively. Addition of biofilm inside macroporous carriers maintained a similar RB5 removal efficiency, but COD removal increased to 65%, which is evidence of ICPB despite the low pH. A proposed ICPB pathway for RB5 suggests that a major intermediate, a naphthol derivative, was responsible for most of the residual COD. Finally, three low-temperature sintering methods, called O, D and DN, were compared based on photocatalytic efficiency and Ti2 adherence. The DN method had the best Ti2-coating properties and was a successful carrier for ICPB of RB5 in a PCBBR.
ContributorsLi, Guozheng (Author) / Rittmann, Bruce E. (Thesis advisor) / Halden, Rolf (Committee member) / Krajmalnik-Brown, Rosa (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 goal of the study was twofold: (i) to investigate the synthesis of hematite-impregnated granular activated carbon (Fe-GAC) by hydrolysis of Fe (III) and (ii) to assess the effectiveness of the fabricated media in removal of arsenic from water. Fe-GAC was synthesized by hydrolysis of Fe(III) salts under two Fe (III) initial dosages (0.5M and 2M) and two hydrolysis periods (24 hrs and 72 hrs). The iron content of the fabricated Fe-GAC media ranged from 0.9% to 4.4% Fe/g of the dry media. Pseudo-equilibrium batch test data at pH = 7.7±0.2 in 1mM NaHCO3 buffered ultrapure water and challenge groundwater representative of the Arizona Mexico border region were fitted to a Freundlich isotherm model. The findings suggested that the arsenic adsorption capacity of the metal (hydr)oxide modified GAC media is primarily controlled by the surface area of the media, while the metal content exhibited lesser effect. The adsorption capacity of the media in the model Mexican groundwater matrix was significantly lower for all adsorbent media. Continuous flow short bed adsorber tests (SBA) demonstrated that the adsorption capacity for arsenic in the challenge groundwater was reduced by a factor of 3 to 4 as a result of the mass transport effects. When compared on metal basis, the iron (hydr)oxide modified media performed comparably well as existing commercial media for treatment of arsenic. On dry mass basis, the fabricated media in this study removed less arsenic than their commercial counterparts because the metal content of the commercial media was significantly higher.
ContributorsJain, Arti (Author) / Hristovski, Kiril (Thesis advisor) / Olson, Larry (Committee member) / Madar, David (Committee member) / Edwards, David (Committee member) / Arizona State University (Publisher)
Created2011
Description
Advancements in computer vision and machine learning have added a new dimension to remote sensing applications with the aid of imagery analysis techniques. Applications such as autonomous navigation and terrain classification which make use of image classification techniques are challenging problems and research is still being carried out to find better solutions. In this thesis, a novel method is proposed which uses image registration techniques to provide better image classification. This method reduces the error rate of classification by performing image registration of the images with the previously obtained images before performing classification. The motivation behind this is the fact that images that are obtained in the same region which need to be classified will not differ significantly in characteristics. Hence, registration will provide an image that matches closer to the previously obtained image, thus providing better classification. To illustrate that the proposed method works, naïve Bayes and iterative closest point (ICP) algorithms are used for the image classification and registration stages respectively. This implementation was tested extensively in simulation using synthetic images and using a real life data set called the Defense Advanced Research Project Agency (DARPA) Learning Applied to Ground Robots (LAGR) dataset. The results show that the ICP algorithm does help in better classification with Naïve Bayes by reducing the error rate by an average of about 10% in the synthetic data and by about 7% on the actual datasets used.
ContributorsMuralidhar, Ashwini (Author) / Saripalli, Srikanth (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2011
Description
This thesis proposed a novel approach to establish the trust model in a social network scenario based on users' emails. Email is one of the most important social connections nowadays. By analyzing email exchange activities among users, a social network trust model can be established to judge the trust rate between each two users. The whole trust checking process is divided into two steps: local checking and remote checking. Local checking directly contacts the email server to calculate the trust rate based on user's own email communication history. Remote checking is a distributed computing process to get help from user's social network friends and built the trust rate together. The email-based trust model is built upon a cloud computing framework called MobiCloud. Inside MobiCloud, each user occupies a virtual machine which can directly communicate with others. Based on this feature, the distributed trust model is implemented as a combination of local analysis and remote analysis in the cloud. Experiment results show that the trust evaluation model can give accurate trust rate even in a small scale social network which does not have lots of social connections. With this trust model, the security in both social network services and email communication could be improved.
ContributorsZhong, Yunji (Author) / Huang, Dijiang (Thesis advisor) / Dasgupta, Partha (Committee member) / Syrotiuk, Violet (Committee member) / Arizona State University (Publisher)
Created2011
Description
S-Taliro is a fully functional Matlab toolbox that searches for trajectories of minimal robustness in hybrid systems that are implemented as either m-functions or Simulink/State flow models. Trajectories with minimal robustness are found using automatic testing of hybrid systems against user specifications. In this work we use Metric Temporal Logic (MTL) to describe the user specifications for the hybrid systems. We then try to falsify the MTL specification using global minimization of robustness metric. Global minimization is carried out using stochastic optimization algorithms like Monte-Carlo (MC) and Extended Ant Colony Optimization (EACO) algorithms. Irrespective of the type of the model we provide as an input to S-Taliro, the user needs to specify the MTL specification, the initial conditions and the bounds on the inputs. S-Taliro then uses this information to generate test inputs which are used to simulate the system. The simulation trace is then provided as an input to Taliro which computes the robustness estimate of the MTL formula. Global minimization of this robustness metric is performed to generate new test inputs which again generate simulation traces which are closer to falsifying the MTL formula. Traces with negative robustness values indicate that the simulation trace falsified the MTL formula. Traces with positive robustness values are also of great importance because they indicate how robust the system is against the given specification. S-Taliro has been seamlessly integrated into the Matlab environment, which is extensively used for model-based development of control software. Moreover the toolbox has been developed in a modular fashion and therefore adding new optimization algorithms is easy and straightforward. In this work I present the architecture of S-Taliro and its working on a few benchmark problems.
ContributorsAnnapureddy, Yashwanth Singh Rahul (Author) / Fainekos, Georgios (Thesis advisor) / Lee, Yann-Hang (Committee member) / Gupta, Sandeep (Committee member) / Arizona State University (Publisher)
Created2011
Description
A recent joint study by Arizona State University and the Arizona Department of Transportation (ADOT) was conducted to evaluate certain Warm Mix Asphalt (WMA) properties in the laboratory. WMA material was taken from an actual ADOT project that involved two WMA sections. The first section used a foamed-based WMA admixture, and the second section used a chemical-based WMA admixture. The rest of the project included control hot mix asphalt (HMA) mixture. The evaluation included testing of field-core specimens and laboratory compacted specimens. The laboratory specimens were compacted at two different temperatures; 270 °F (132 °C) and 310 °F (154 °C). The experimental plan included four laboratory tests: the dynamic modulus (E*), indirect tensile strength (IDT), moisture damage evaluation using AASHTO T-283 test, and the Hamburg Wheel-track Test. The dynamic modulus E* results of the field cores at 70 °F showed similar E* values for control HMA and foaming-based WMA mixtures; the E* values of the chemical-based WMA mixture were relatively higher. IDT test results of the field cores had comparable finding as the E* results. For the laboratory compacted specimens, both E* and IDT results indicated that decreasing the compaction temperatures from 310 °F to 270 °F did not have any negative effect on the material strength for both WMA mixtures; while the control HMA strength was affected to some extent. It was noticed that E* and IDT results of the chemical-based WMA field cores were high; however, the laboratory compacted specimens results didn't show the same tendency. The moisture sensitivity findings from TSR test disagreed with those of Hamburg test; while TSR results indicated relatively low values of about 60% for all three mixtures, Hamburg test results were quite excellent. In general, the results of this study indicated that both WMA mixes can be best evaluated through field compacted mixes/cores; the results of the laboratory compacted specimens were helpful to a certain extent. The dynamic moduli for the field-core specimens were higher than for those compacted in the laboratory. The moisture damage findings indicated that more investigations are needed to evaluate moisture damage susceptibility in field.
ContributorsAlossta, Abdulaziz (Author) / Kaloush, Kamil (Thesis advisor) / Witczak, Matthew W. (Committee member) / Mamlouk, Michael S. (Committee member) / Arizona State University (Publisher)
Created2011
Description
Query Expansion is a functionality of search engines that suggest a set of related queries for a user issued keyword query. In case of exploratory or ambiguous keyword queries, the main goal of the user would be to identify and select a specific category of query results among different categorical options, in order to narrow down the search and reach the desired result. Typical corpus-driven keyword query expansion approaches return popular words in the results as expanded queries. These empirical methods fail to cover all semantics of categories present in the query results. More importantly these methods do not consider the semantic relationship between the keywords featured in an expanded query. Contrary to a normal keyword search setting, these factors are non-trivial in an exploratory and ambiguous query setting where the user's precise discernment of different categories present in the query results is more important for making subsequent search decisions. In this thesis, I propose a new framework for keyword query expansion: generating a set of queries that correspond to the categorization of original query results, which is referred as Categorizing query expansion. Two approaches of algorithms are proposed, one that performs clustering as pre-processing step and then generates categorizing expanded queries based on the clusters. The other category of algorithms handle the case of generating quality expanded queries in the presence of imperfect clusters.
ContributorsNatarajan, Sivaramakrishnan (Author) / Chen, Yi (Thesis advisor) / Candan, Selcuk (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2011