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- All Subjects: Computer Science
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- Genre: Masters Thesis
- Creators: Arizona State University
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
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
This thesis explores concept of "global bioethics" in both its development as well as its current state in an effort to understand exactly where it fits into the larger field of bioethics. Further, the analysis poses specific questions regarding what it may contribute to this field and related fields, and the possibility and scope associated with the continued development of global bioethics as its own discipline. To achieve this, the piece addresses questions regarding current opinions on the subject, the authorities and their associated publications related to global bioethics, and what the aims of the subject should be given its current state. "Global Bioethics" is a term that, while seen frequently in bioethics literature, is difficult to define succinctly. While many opinions are provided on the concept, little consensus exists regarding its application and possible contributions and, in some cases, even its very possibility. Applying ethical principles of health and medicine globally is undoubtedly complicated by the cultural, social, and geographical considerations associated with understanding health and medicine in different populations, leading to a dichotomy between two schools of thought in relation to global bioethics. These two sides consist of those who think that universality of bioethics is possible whereas the opposing viewpoint holds that relativism is the key to applying ethics on a global scale. Despite the aforementioned dichotomy in addressing applications of global bioethics, this analysis shows that the goals of the subject should be more focused on contributing to ethical frameworks and valuable types of thinking related to the ethics health and medicine on a global scale. This is achieved through an exploration of bioethics in general, health as a function of society and culture, the history and development of global bioethics itself, and an exploration of pertinent global health topics. While primarily descriptive in nature, this analysis critiques some of the current discussions and purported goals surrounding global bioethics, recommending that the field focus on fostering valuable discussion and framing of issues rather than the pursuit of concrete judgments on moral issues in global health and medicine.
ContributorsRuffenach, Stephen Charles (Author) / Robert, Jason S (Thesis advisor) / Maienschein, Jane (Committee member) / Hruschka, Daniel J (Committee member) / Arizona State University (Publisher)
Created2011
Description
Infections caused by the Hepatitis C Virus (HCV) are very common worldwide, affecting up to 3% of the population. Chronic infection of HCV may develop into liver cirrhosis and liver cancer which is among the top five of the most common cancers. Therefore, vaccines against HCV are under intense study in order to prevent HCV from harming people's health. The envelope protein 2 (E2) of HCV is thought to be a promising vaccine candidate because it can directly bind to a human cell receptor and plays a role in viral entry. However, the E2 protein production in cells is inefficient due to its complicated matured structure. Folding of E2 in the endoplasmic reticulum (ER) is often error-prone, resulting in production of aggregates and misfolded proteins. These incorrect forms of E2 are not functional because they are not able to bind to human cells and stimulate antibody response to inhibit this binding. This study is aimed to overcome the difficulties of HCV E2 production in plant system. Protein folding in the ER requires great assistance from molecular chaperones. Thus, in this study, two molecular chaperones in the ER, calreticulin and calnexin, were transiently overexpressed in plant leaves in order to facilitate E2 folding and production. Both of them showed benefits in increasing the yield of E2 and improving the quality of E2. In addition, poorly folded E2 accumulated in the ER may cause stress in the ER and trigger transcriptional activation of ER molecular chaperones. Therefore, a transcription factor involved in this pathway, named bZIP60, was also overexpressed in plant leaves, aiming at up-regulating a major family of molecular chaperones called BiP to assist protein folding. However, our results showed that BiP mRNA levels were not up-regulated by bZIP60, but they increased in response to E2 expression. The Western blot analysis also showed that overexpression of bZIP60 had a small effect on promoting E2 folding. Overall, this study suggested that increasing the level of specific ER molecular chaperones was an effective way to promote HCV E2 protein production and maturation.
ContributorsHong, Fan (Author) / Mason, Hugh (Thesis advisor) / Gaxiola, Roberto (Committee member) / Chang, Yung (Committee member) / Chen, Qiang (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
In the last few decades, the rapid development of electronic music technologies has changed the way society interacts with music, which in turn impacts the profession of music therapy. Except for a few cases, music therapy has not extensively explored the integration of new technology. However, current research trends show a willingness and excitement to explore the possibilities (Nagler, 2011; Ramsey, 2011; Magee, et al., 2011; Magee & Burland, 2008; Magee 2006). The project described in this paper intends to demonstrate one of these possibilities by combining modern technologies to create an interactive musical system with practical applications in music therapy. In addition to designing a practical tool, the project aims to question the role of technology in music therapy and to initiate dialogue between technologists and music therapists. The project, entitled MIST: A Musical Interactive Space for Therapy, uses modern gestural technology (the Microsoft® Kinect®) to capture body movements and turn them into music. It is intended for use in a clinical setting with children with mild to moderate disabilities. The system is a software/hardware package that is inexpensive, user-friendly, and portable. There are two functional modes of the system: the first sonifies specific movement tasks of reaching and balancing; the second is an interactive musical play space in which an entire room becomes responsive to presence and movement, creating a sonic playground. The therapeutic goals of the system are to motivate and train physical movement, encourage exploration of space and the body, and allow for musical expression, play, auditory perception, and social interaction.
ContributorsHeadlee, Kimberlee (Author) / Ingalls, Todd M (Thesis advisor) / Crowe, Barbara J. (Thesis advisor) / Stauffer, Sandra L (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
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