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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
The Magnetoplasmadynamic (MPD) thruster is an electromagnetic thruster that produces a higher specific impulse than conventional chemical rockets and greater thrust densities than electrostatic thrusters, but the well-known operational limit---referred to as ``onset"---imposes a severe limitation efficiency and lifetime. This phenomenon is associated with large fluctuations in operating voltage, high rates of electrode erosion, and three-dimensional instabilities in the plasma flow-field which cannot be adequately represented by two-dimensional, axisymmetric models. Simulations of the Princeton Benchmark Thruster (PBT) were conducted using the three-dimensional version of the magnetohydrodynamic (MHD) code, MACH. Validation of the numerical model is partially achieved by comparison to equivalent simulations conducted using the well-established two-dimensional, axisymmetric version of MACH. Comparisons with available experimental data was subsequently performed to further validate the model and gain insights into the physical processes of MPD acceleration. Thrust, plasma voltage, and plasma flow-field predictions were calculated for the PBT operating with applied currents in the range $6.5kA < J < 23.25kA$ and mass-flow rates of $1g/s$, $3g/s$, and $6g/s$. Comparisons of performance characteristics between the two versions of the code show excellent agreement, indicating that MACH3 can be expected to be as predictive as MACH2 has demonstrated over multiple applications to MPD thrusters. Predicted thrust for operating conditions within the range which exhibited no symptoms of the onset phenomenon experimentally also showed agreement between MACH3 and experiment well within the experimental uncertainty. At operating conditions beyond such values , however, there is a discrepancy---up to $\sim20\%$---which implies that certain significant physical processes associated with onset are not currently being modeled. Such processes are also evident in the experimental total voltage data, as is evident by the characteristic ``voltage hash", but not present in predicted plasma voltage. Additionally, analysis of the predicted plasma flow-field shows no breakdown in azimuthal symmetry, which is expected to be associated with onset. This implies that perhaps certain physical processes are modeled by neither MACH2 nor MACH3; the latter indicating that such phenomenon may not be inherently three dimensional and related to the plasma---as suggested by other efforts---but rather a consequence of electrode material processes which have not been incorporated into the current models.
ContributorsParma, Brian (Author) / Mikellides, Pavlos G (Thesis advisor) / Squires, Kyle (Committee member) / Herrmann, Marcus (Committee member) / Arizona State University (Publisher)
Created2011
Description
ABSTRACT Research has shown that the manner in which people are treated in their interactions with agents of the criminal justice system matters. People expect criminal justice officials to treat them fairly and with honesty and respect, which is the basis for procedural justice. When people are treated in a procedurally just and equitable manner they will view the system as legitimate and will be more likely to voluntarily comply and cooperate with legal system directives. People who have personal or vicarious experiences of unfair or unjust interactions with the legal system tend to view the system as less legitimate and are less likely to comply and cooperate when they have contact with representatives of the system. This study examines a random sample of 337 arrestees in Maricopa County, Arizona who have been interviewed as a part of the Arizona Arrestee Reporting Information Network. Descriptive statistics and regression analysis are used to examine views of the procedural justice experienced by arrestees during arrest, perceptions of police legitimacy by arrestees, voluntary compliance to the law, and voluntary cooperation with police. Results of the study show that perceptions of legitimacy work through procedural justice, and that procedurally just interactions with police mediate racial effects on views of legitimacy. Views of procedural justice and legitimacy increase cooperation. No variables in this study were significantly related to compliance.
ContributorsJorgensen, Cody (Author) / Ready, Justin (Thesis advisor) / White, Michael (Committee member) / Katz, Charles (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
The high strength to weight ratio of woven fabric offers a cost effective solution to be used in a containment system for aircraft propulsion engines. Currently, Kevlar is the only Federal Aviation Administration (FAA) approved fabric for usage in systems intended to mitigate fan blade-out events. This research builds on an earlier constitutive model of Kevlar 49 fabric developed at Arizona State University (ASU) with the addition of new and improved modeling details. Latest stress strain experiments provided new and valuable data used to modify the material model post peak behavior. These changes reveal an overall improvement of the Finite Element (FE) model's ability to predict experimental results. First, the steel projectile is modeled using Johnson-Cook material model and provides a more realistic behavior in the FE ballistic models. This is particularly noticeable when comparing FE models with laboratory tests where large deformations in projectiles are observed. Second, follow-up analysis of the results obtained through the new picture frame tests conducted at ASU provides new values for the shear moduli and corresponding strains. The new approach for analysis of data from picture frame tests combines digital image analysis and a two-level factorial optimization formulation. Finally, an additional improvement in the material model for Kevlar involves checking the convergence at variation of mesh density of fabrics. The study performed and described herein shows the converging trend, therefore validating the FE model.
ContributorsMorea, Mihai I (Author) / Rajan, Subramaniam D. (Thesis advisor) / 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
Prior research has found links between family environment and criminal outcomes, but research is lacking on why these factors often occur together within families. Parental criminality, family size, and family disruption have been analyzed as risk factors for juvenile delinquency, but their relationships with each other have gone largely unexplored. This thesis explores the relationship between parental criminality, having children, number of children, and patterns of residence with children. Data from the National Longitudinal Survey of Youth '97 are used to associate likelihood of having children, likelihood of having any children out of residence, percent of children in residence, and number of children with arrest prevalence and self-reported offending. Results were generally supportive. Moderate effect sizes were found for likelihood of having children, with large effects on likelihood of having any children out of residence. Moderate effects were found for percentage of children in residence, and large effects were found for number of children.
ContributorsLouton, Brooks (Author) / Sweeten, Gary A (Thesis advisor) / Wang, Xia (Committee member) / Rodriguez, Nancy (Committee member) / Arizona State University (Publisher)
Created2011
Description
The link between victimization and offending is well established in the literature, yet an unexplored causal pathway within this relationship is concerned with why some individuals engage in maladaptive coping in response to victimization. In particular, those with low self-control may be attracted to problematic yet immediately gratifying forms of coping post-victimization (e.g., substance use), which may increase their likelihood of violent offending in the future. Using three waves of adolescent panel data from the Gang Resistance Education and Training (GREAT) program, this research examines: (1) whether individuals with low-self control are more likely to engage in substance use coping following violent victimization, and (2) whether victims with low self-control who engage in substance use coping are more likely to commit violent offenses in the future. The results from negative binomial regressions support these hypotheses, even after controlling for prior offending, peer influences, prior substance abuse, and other forms of offending. The implications for integrating general strain and self-control theories, as well as for our understanding of the victimization-offending overlap, are discussed.
ContributorsTuranovic, Jillian (Author) / Pratt, Travis C. (Thesis advisor) / Reisig, Michael D (Committee member) / Fornango, Robert J (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