Now showing items 1-20 of 45

  • ANYTIME ACTIVE LEARNING DISSERTATION 

    RAMIREZ LOAIZA, MARIA E. (2016-05)
    Machine learning is a subfield of artificial intelligence which deals with algorithms that can learn from data. These methods provide computers with the ability to learn from past data and make predictions for new data. ...
  • APPLICATION SOFTWARE DESIGN WITH THE FEATURE LANGUAGE EXTENTION 

    MARUYAMA, SHUICHI (2013-05)
    When implemented with existing mainstream programming languages, the code of interacting features will inevitably entangle in the same reusable program unit of the programming language such as a method. Interacting features ...
  • APPLICATION-AWARE OPTIMIZATIONS FOR BIG DATA ACCESS 

    YIN, YANLONG (2014-07)
    Many High-Performance Computing (HPC) applications spend a significant portion of their execution time in accessing data from les and they are becoming increasingly data-intensive. For them, I/O performance is a significant ...
  • AUTOMATED SLICING METHODS FOR LARGE EVENT TRACES 

    SMITH, RAYMOND D. (2012-05)
    Many long-running computer systems record events as they execute, resulting in a dynamic record of system behavior. In large systems, the event trace may contain thousands of entries and when faced with a problem for ...
  • AUTOMATIC SUMMARIZATION OF CLINICAL ABSTRACTS FOR EVIDENCE-BASED MEDICINE 

    SUMMERSCALES, RODNEY L. (2013-12)
    The practice of evidence-based medicine (EBM) encourages health professionals to make informed treatment decisions based on a careful analysis of current research. However, after caring for their patients, medical ...
  • BIG DATA SYSTEM INFRASTRUCTURE AT EXTREME SCALES 

    ZHAO, DONGFANG (2015-07)
    Rapid advances in digital sensors, networks, storage, and computation along with their availability at low cost is leading to the creation of huge collections of data { dubbed as Big Data. This data has the potential for ...
  • CAPACITY BOUNDS FOR LARGE SCALE WIRELESS SENSOR NETWORKS 

    TANG, SHAOJIE (2012-12)
    We study the network capacity of large scale wireless sensor networks under both Gaussian Channel model and Protocol Interference Model. To study network capacity under gaussian channel model, we assume n wireless nodes ...
  • CHARACTERIZATION AND MODELING OF A COMMERCIAL NATIONWIDE WI-FI HOTSPOT NETWORK 

    DIVGI, GAUTAM (2014-12)
    We present a thorough analysis of a commercial nationwide Wi-Fi hotspot network. The analysis is approached in two ways, characterization and modeling. First we characterize the network from a ve month long log of user ...
  • A COMPARATIVE STUDY OF FEATURE INTEGRATION WITH FLX AND ASPECTJ 

    RAMAKRISHNA REDDY, NIRANJANA SOMPURA (2014-07)
    Feature Language Extensions (FLX) and AspectJ are two sets of programming language constructs designed to enable the programmer to modularize interacting features, or equivalently crosscutting concerns, that cannot be ...
  • COMPRESSIVE SENSING AND RECONSTRUCTION : THEORY AND APPLICATIONS 

    KRISHNAMURTHY, RITVIK NADIG (2014-07)
    Conventional approach in acquisition and reconstruction of images from frequency domain strictly follow the Nyquist sampling theorem. The principle states that the sampling frequency required for complete reconstruction ...
  • COVERAGE AND CONNECTIVITY IN WIRELESS NETWORKS 

    XU, XIAOHUA (2012-05)
    The limited energy resources, instability, and lacking central control in wireless networks motivates the study of connected dominating set (CDS) which serves as rout- ing backbone to support service discovery, and area ...
  • Data used to develop #Polar scores 

    Culotta, Aron; Hemphill, Libby; Heston, Matthew (2016)
    We present a new approach to measuring political polarization, including a novel algorithm and open source Python code, which leverages Twitter content to produce measures of polarization for both users and hashtags. #Polar ...
  • DISTRIBUTED NOSQL STORAGE FOR EXTREME-SCALE SYSTEM SERVICES IN CLOUDS AND SUPERCOMPUTERS 

    LI, TONGLIN (2015-12)
    As supercomputers gain more parallelism at exponential rates, the storage infrastructure performance is increasing at a significantly lower rate due to relatively centralized management. This implies that the data ...
  • DUAL-BASED APPROXIMATION ALGORITHMS FOR MULTIPLE NETWORK DESIGN PROBLEMS 

    GRIMMER, BENJAMIN (2016-05)
    We study a variety of NP-Complete network connectivity problems. Our pri- mary results come from a novel Dual-Based approach to approximating network de- sign problems with cut-based linear programming relaxations. This ...
  • EFFICIENT ALGORITHMS FOR POWER ASSIGNMENT PROBLEMS 

    QIAO, KAN (2015-05)
    Power assignment problems take as input a directed simple graph G = (V;E) and a cost function c : E ! R+. A solution to this problem assigns every vertex a nonnegative power, p(v). We use H = (V;B(p)) to denote the ...
  • EFFICIENT SCORING AND RANKING OF EXPLANATION FOR DATA EXCHANGE ERRORS IN VAGABOND 

    WANG, ZHEN (2014-05)
    Data exchange has been widely used in big data era. One challenge for data exchange is to identify the true cause of data errors during the schema translation. The huge amount of data and schemas make it nearly impossible ...
  • THE EUML-ARC PROGRAMMING MODEL 

    MARTH, KEVIN (2014-07)
    The EUML-ARC programming model shows that the increasing parallelism available on multi-core processors requires evolutionary (not revolutionary) changes in software design. The EUML-ARC programming model combines and ...
  • EXPLOITING KNOWLEDGE IN UNSUPERVISED OPEN INFORMATION EXTRACTION 

    MERHAV, YUVAL (2012-12)
    The extraction of structured information from text is a long-standing challenge in Natural Language Processing (NLP) which has been reinvigorated with the ever- increasing availability of user-generated textual content ...
  • MATRIX: MANY-TASK COMPUTING EXECUTION FABRIC FOR EXTREME SCALES 

    RAJENDRAN, ANUPAM (2013-05)
    Scheduling large amount of jobs/tasks over large-scale distributed systems play a significant role to achieve high system utilization and throughput. Today’s state-of-the-art job management/scheduling systems have predominantly ...
  • MAXIMIZATION OF SYSTEM UTILITY VALUE FOR TIME-SENSITIVE APPLICATIONS 

    LI, SHUHUI (2014-12)
    Many applications are time-sensitive in the sense that the usefulness or the quality of their end results depends on their completion time. Examples of this type of applications are threat detections in air defense systems ...