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- Creators: Davulcu, Hasan
- Creators: Goryll, Michael
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
Genes have widely different pertinences to the etiology and pathology of diseases. Thus, they can be ranked according to their disease-significance on a genomic scale, which is the subject of gene prioritization. Given a set of genes known to be related to a disease, it is reasonable to use them as a basis to determine the significance of other candidate genes, which will then be ranked based on the association they exhibit with respect to the given set of known genes. Experimental and computational data of various kinds have different reliability and relevance to a disease under study. This work presents a gene prioritization method based on integrated biological networks that incorporates and models the various levels of relevance and reliability of diverse sources. The method is shown to achieve significantly higher performance as compared to two well-known gene prioritization algorithms. Essentially, no bias in the performance was seen as it was applied to diseases of diverse ethnology, e.g., monogenic, polygenic and cancer. The method was highly stable and robust against significant levels of noise in the data. Biological networks are often sparse, which can impede the operation of associationbased gene prioritization algorithms such as the one presented here from a computational perspective. As a potential approach to overcome this limitation, we explore the value that transcription factor binding sites can have in elucidating suitable targets. Transcription factors are needed for the expression of most genes, especially in higher organisms and hence genes can be associated via their genetic regulatory properties. While each transcription factor recognizes specific DNA sequence patterns, such patterns are mostly unknown for many transcription factors. Even those that are known are inconsistently reported in the literature, implying a potentially high level of inaccuracy. We developed computational methods for prediction and improvement of transcription factor binding patterns. Tests performed on the improvement method by employing synthetic patterns under various conditions showed that the method is very robust and the patterns produced invariably converge to nearly identical series of patterns. Preliminary tests were conducted to incorporate knowledge from transcription factor binding sites into our networkbased model for prioritization, with encouraging results. Genes have widely different pertinences to the etiology and pathology of diseases. Thus, they can be ranked according to their disease-significance on a genomic scale, which is the subject of gene prioritization. Given a set of genes known to be related to a disease, it is reasonable to use them as a basis to determine the significance of other candidate genes, which will then be ranked based on the association they exhibit with respect to the given set of known genes. Experimental and computational data of various kinds have different reliability and relevance to a disease under study. This work presents a gene prioritization method based on integrated biological networks that incorporates and models the various levels of relevance and reliability of diverse sources. The method is shown to achieve significantly higher performance as compared to two well-known gene prioritization algorithms. Essentially, no bias in the performance was seen as it was applied to diseases of diverse ethnology, e.g., monogenic, polygenic and cancer. The method was highly stable and robust against significant levels of noise in the data. Biological networks are often sparse, which can impede the operation of associationbased gene prioritization algorithms such as the one presented here from a computational perspective. As a potential approach to overcome this limitation, we explore the value that transcription factor binding sites can have in elucidating suitable targets. Transcription factors are needed for the expression of most genes, especially in higher organisms and hence genes can be associated via their genetic regulatory properties. While each transcription factor recognizes specific DNA sequence patterns, such patterns are mostly unknown for many transcription factors. Even those that are known are inconsistently reported in the literature, implying a potentially high level of inaccuracy. We developed computational methods for prediction and improvement of transcription factor binding patterns. Tests performed on the improvement method by employing synthetic patterns under various conditions showed that the method is very robust and the patterns produced invariably converge to nearly identical series of patterns. Preliminary tests were conducted to incorporate knowledge from transcription factor binding sites into our networkbased model for prioritization, with encouraging results. To validate these approaches in a disease-specific context, we built a schizophreniaspecific network based on the inferred associations and performed a comprehensive prioritization of human genes with respect to the disease. These results are expected to be validated empirically, but computational validation using known targets are very positive.
ContributorsLee, Jang (Author) / Gonzalez, Graciela (Thesis advisor) / Ye, Jieping (Committee member) / Davulcu, Hasan (Committee member) / Gallitano-Mendel, Amelia (Committee member) / Arizona State University (Publisher)
Created2011
Description
There will always be a need for high current/voltage transistors. A transistor that has the ability to be both or either of these things is the silicon metal-silicon field effect transistor (MESFET). An additional perk that silicon MESFET transistors have is the ability to be integrated into the standard silicon on insulator (SOI) complementary metal oxide semiconductor (CMOS) process flow. This makes a silicon MESFET transistor a very valuable device for use in any standard CMOS circuit that may usually need a separate integrated circuit (IC) in order to switch power on or from a high current/voltage because it allows this function to be performed with a single chip thereby cutting costs. The ability for the MESFET to cost effectively satisfy the needs of this any many other high current/voltage device application markets is what drives the study of MESFET optimization. Silicon MESFETs that are integrated into standard SOI CMOS processes often receive dopings during fabrication that would not ideally be there in a process made exclusively for MESFETs. Since these remnants of SOI CMOS processing effect the operation of a MESFET device, their effect can be seen in the current-voltage characteristics of a measured MESFET device. Device simulations are done and compared to measured silicon MESFET data in order to deduce the cause and effect of many of these SOI CMOS remnants. MESFET devices can be made in both fully depleted (FD) and partially depleted (PD) SOI CMOS technologies. Device simulations are used to do a comparison of FD and PD MESFETs in order to show the advantages and disadvantages of MESFETs fabricated in different technologies. It is shown that PD MESFET have the highest current per area capability. Since the PD MESFET is shown to have the highest current capability, a layout optimization method to further increase the current per area capability of the PD silicon MESFET is presented, derived, and proven to a first order.
ContributorsSochacki, John (Author) / Thornton, Trevor J (Thesis advisor) / Schroder, Dieter (Committee member) / Vasileska, Dragica (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2011
Description
ABSTRACT The purpose of this study is to demonstrate that stable lipid bilayers can be set up on an array of silicon micropores and can be used as sites for self-inserting ion-channel proteins which can be studied independently of each other. In course of this study an acrylic based holder was designed and machined to ensure leak-free fluidic access to the silicon micropores and physical isolation of the individual array channels. To measure the ion-channel currents, we simulated, designed and manufactured low-noise transimpedance amplifiers and support circuits based on published patch clamp amplifier designs, using currently available surface-mount components. This was done in order to achieve a reduction in size and costs as well as isolation of individual channels without the need for multiplexing of the input. During the experiments performed, stable bilayers were formed across an array of four vertically mounted 30 µm silicon micropores and OmpF porins were added for self insertion in each of the bilayers. To further demonstrate the independence of these bilayer recording sites, the antibiotic Ampicillin (2.5 mM) was added to one of the fluidic wells. The ionic current in each of the wells was recorded simultaneously. Sub-conductance states of Ompf porin were observed in two of the measurement sites. In addition, the conductance steps in the site containing the antibiotic could be clearly seen to be larger compared to those of the unmodified site. This is due to the transient blocking of ion flow through the porin due to translocation of the antibiotic. Based on this demonstration, ion-channel array reconstitution is a potential method for efficient electrophysiological characterization of different types of ion-channels simultaneously as well as for studying membrane permeation processes.
ContributorsRamakrishnan, Shankar (Author) / Goryll, Michael (Thesis advisor) / Thornton, Trevor J (Committee member) / Blain Christen, Jennifer M (Committee member) / Arizona State University (Publisher)
Created2011
Description
In the last few years, significant advances in nanofabrication have allowed tailoring of structures and materials at a molecular level enabling nanofabrication with precise control of dimensions and organization at molecular length scales, a development leading to significant advances in nanoscale systems. Although, the direction of progress seems to follow the path of microelectronics, the fundamental physics in a nanoscale system changes more rapidly compared to microelectronics, as the size scale is decreased. The changes in length, area, and volume ratios due to reduction in size alter the relative influence of various physical effects determining the overall operation of a system in unexpected ways. One such category of nanofluidic structures demonstrating unique ionic and molecular transport characteristics are nanopores. Nanopores derive their unique transport characteristics from the electrostatic interaction of nanopore surface charge with aqueous ionic solutions. In this doctoral research cylindrical nanopores, in single and array configuration, were fabricated in silicon-on-insulator (SOI) using a combination of electron beam lithography (EBL) and reactive ion etching (RIE). The fabrication method presented is compatible with standard semiconductor foundries and allows fabrication of nanopores with desired geometries and precise dimensional control, providing near ideal and isolated physical modeling systems to study ion transport at the nanometer level. Ion transport through nanopores was characterized by measuring ionic conductances of arrays of nanopores of various diameters for a wide range of concentration of aqueous hydrochloric acid (HCl) ionic solutions. Measured ionic conductances demonstrated two distinct regimes based on surface charge interactions at low ionic concentrations and nanopore geometry at high ionic concentrations. Field effect modulation of ion transport through nanopore arrays, in a fashion similar to semiconductor transistors, was also studied. Using ionic conductance measurements, it was shown that the concentration of ions in the nanopore volume was significantly changed when a gate voltage on nanopore arrays was applied, hence controlling their transport. Based on the ion transport results, single nanopores were used to demonstrate their application as nanoscale particle counters by using polystyrene nanobeads, monodispersed in aqueous HCl solutions of different molarities. Effects of field effect modulation on particle transition events were also demonstrated.
ContributorsJoshi, Punarvasu (Author) / Thornton, Trevor J (Thesis advisor) / Goryll, Michael (Thesis advisor) / Spanias, Andreas (Committee member) / Saraniti, Marco (Committee member) / Arizona State University (Publisher)
Created2011
Description
Most existing approaches to complex event processing over streaming data rely on the assumption that the matches to the queries are rare and that the goal of the system is to identify these few matches within the incoming deluge of data. In many applications, such as stock market analysis and user credit card purchase pattern monitoring, however the matches to the user queries are in fact plentiful and the system has to efficiently sift through these many matches to locate only the few most preferable matches. In this work, we propose a complex pattern ranking (CPR) framework for specifying top-k pattern queries over streaming data, present new algorithms to support top-k pattern queries in data streaming environments, and verify the effectiveness and efficiency of the proposed algorithms. The developed algorithms identify top-k matching results satisfying both patterns as well as additional criteria. To support real-time processing of the data streams, instead of computing top-k results from scratch for each time window, we maintain top-k results dynamically as new events come and old ones expire. We also develop new top-k join execution strategies that are able to adapt to the changing situations (e.g., sorted and random access costs, join rates) without having to assume a priori presence of data statistics. Experiments show significant improvements over existing approaches.
ContributorsWang, Xinxin (Author) / Candan, K. Selcuk (Thesis advisor) / Chen, Yi (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2011
Description
Data-driven applications are becoming increasingly complex with support for processing events and data streams in a loosely-coupled distributed environment, providing integrated access to heterogeneous data sources such as relational databases and XML documents. This dissertation explores the use of materialized views over structured heterogeneous data sources to support multiple query optimization in a distributed event stream processing framework that supports such applications involving various query expressions for detecting events, monitoring conditions, handling data streams, and querying data. Materialized views store the results of the computed view so that subsequent access to the view retrieves the materialized results, avoiding the cost of recomputing the entire view from base data sources. Using a service-based metadata repository that provides metadata level access to the various language components in the system, a heuristics-based algorithm detects the common subexpressions from the queries represented in a mixed multigraph model over relational and structured XML data sources. These common subexpressions can be relational, XML or a hybrid join over the heterogeneous data sources. This research examines the challenges in the definition and materialization of views when the heterogeneous data sources are retained in their native format, instead of converting the data to a common model. LINQ serves as the materialized view definition language for creating the view definitions. An algorithm is introduced that uses LINQ to create a data structure for the persistence of these hybrid views. Any changes to base data sources used to materialize views are captured and mapped to a delta structure. The deltas are then streamed within the framework for use in the incremental update of the materialized view. Algorithms are presented that use the magic sets query optimization approach to both efficiently materialize the views and to propagate the relevant changes to the views for incremental maintenance. Using representative scenarios over structured heterogeneous data sources, an evaluation of the framework demonstrates an improvement in performance. Thus, defining the LINQ-based materialized views over heterogeneous structured data sources using the detected common subexpressions and incrementally maintaining the views by using magic sets enhances the efficiency of the distributed event stream processing environment.
ContributorsChaudhari, Mahesh Balkrishna (Author) / Dietrich, Suzanne W (Thesis advisor) / Urban, Susan D (Committee member) / Davulcu, Hasan (Committee member) / Chen, Yi (Committee member) / Arizona State University (Publisher)
Created2011
Description
In very small electronic devices the alternate capture and emission of carriers at an individual defect site located at the interface of Si:SiO2 of a MOSFET generates discrete switching in the device conductance referred to as a random telegraph signal (RTS) or random telegraph noise (RTN). In this research work, the integration of random defects positioned across the channel at the Si:SiO2 interface from source end to the drain end in the presence of different random dopant distributions are used to conduct Ensemble Monte-Carlo ( EMC ) based numerical simulation of key device performance metrics for 45 nm gate length MOSFET device. The two main performance parameters that affect RTS based reliability measurements are percentage change in threshold voltage and percentage change in drain current fluctuation in the saturation region. It has been observed as a result of the simulation that changes in both and values moderately decrease as the defect position is gradually moved from source end to the drain end of the channel. Precise analytical device physics based model needs to be developed to explain and assess the EMC simulation based higher VT fluctuations as experienced for trap positions at the source side. A new analytical model has been developed that simultaneously takes account of dopant number variations in the channel and depletion region underneath and carrier mobility fluctuations resulting from fluctuations in surface potential barriers. Comparisons of this new analytical model along with existing analytical models are shown to correlate with 3D EMC simulation based model for assessment of VT fluctuations percentage induced by a single interface trap. With scaling of devices beyond 32 nm node, halo doping at the source and drain are routinely incorporated to combat the threshold voltage roll-off that takes place with effective channel length reduction. As a final study on this regard, 3D EMC simulation method based computations of threshold voltage fluctuations have been performed for varying source and drain halo pocket length to illustrate the threshold voltage fluctuations related reliability problems that have been aggravated by trap positions near the source at the interface compared to conventional 45 nm MOSFET.
ContributorsAshraf, Nabil Shovon (Author) / Vasileska, Dragica (Thesis advisor) / Schroder, Dieter (Committee member) / Goodnick, Stephen (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2011
Description
This thesis addresses the problem of online schema updates where the goal is to be able to update relational database schemas without reducing the database system's availability. Unlike some other work in this area, this thesis presents an approach which is completely client-driven and does not require specialized database management systems (DBMS). Also, unlike other client-driven work, this approach provides support for a richer set of schema updates including vertical split (normalization), horizontal split, vertical and horizontal merge (union), difference and intersection. The update process automatically generates a runtime update client from a mapping between the old the new schemas. The solution has been validated by testing it on a relatively small database of around 300,000 records per table and less than 1 Gb, but with limited memory buffer size of 24 Mb. This thesis presents the study of the overhead of the update process as a function of the transaction rates and the batch size used to copy data from the old to the new schema. It shows that the overhead introduced is minimal for medium size applications and that the update can be achieved with no more than one minute of downtime.
ContributorsTyagi, Preetika (Author) / Bazzi, Rida (Thesis advisor) / Candan, Kasim S (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2011