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Filtering by: Funding statement This work was supported by NSF under NSF CAREER award CNS-0846044. Remove constraint Funding statement: This work was supported by NSF under NSF CAREER award CNS-0846044. Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science

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  • Extending the TekBots [superscript TM] Platform for Learning [superscript TM] to upper division ECE courses

    Creator:
    Smit, Adriaan
    Abstract:
    In April of 1997 it was pointed out at an NSF Engineering Education Innovators conference that “… education appears to ignore the need for connections and for integration – which should be at the core of an engineering education.” In order to solve this problem a group named ‘TekBotsTM’ was...
    Resource Type:
    Masters Thesis
    Full Text:
    born. This concept has now become the cornerstone for all the work that is being done by the TekBots

  • Understanding and supporting end-user debugging strategies

    Creator:
    Grigoreanu, Valentina I.
    Abstract:
    End users' programs are fraught with errors, costing companies millions of dollars. One reason may be that researchers and tool designers have not yet focused on end-user debugging strategies. To investigate this possibility, this dissertation presents eight empirical studies and a new strategy-based end-user debugging tool for Excel, called StratCel....
    Resource Type:
    Dissertation
    Full Text:
    energy and enthusiasm have been inspiring. This work was supported in part by Microsoft Research, by

  • Co-channel Blocker and Self-Interferer Tolerant Receiver Architectures for MIMO and Full-Duplex MIMO Receivers

    Creator:
    Jain, Sanket
    Abstract:
    This research focuses on receiver architectures which enable better spectral eciency by handling blockers in the same spectral range as the signal. The presence of such blockers, without the use of blocker cancelling/ ltering techniques leads to gain compression and hence, consequent performance degradation of receivers leading to reduced spectrum...
    Resource Type:
    Dissertation
    Full Text:
    technical discussions when we were collaborating on a project. A portion of this work was supported by the

  • End user software engineering features for both genders

    Creator:
    Sorte, Shraddha
    Abstract:
    Previous research has revealed gender differences that impact females’ willingness to adopt software features in end users’ programming environments. Since these features have separately been shown to help end users problem solve, it is important to female end users’ productivity that we find ways to make these features more acceptable...
    Resource Type:
    Masters Thesis
    Full Text:
    career. Nothing that I have accomplished would have been possible without them. This work was

  • Digital library software architectures : TeachEngineering case study

    Creator:
    Suryadevara, Venkata Satya Gokul
    Abstract:
    Digital libraries are digitally accessible, organized collections of knowledge. Although under this broad definition any digitally accessible data set might be considered a digital library, the term is generally reserved for collections whose structures are carefully documented and made available in the form of so-called metadata. There is no specific...
    Resource Type:
    Capstone Project
    Full Text:
    TeachEngineering is funded by NSF-NSDL award# 0226322. The architecture, document collection and metadata

  • HiNoVa: A Novel Open-Set Detection Method for Automating RF Device Authentication

    Creator:
    Puppo, Luke
    Abstract:
    New capabilities in wireless network security are now possible through deep learning, which can identify and leverage patterns in radio frequency (RF) data. One area of deep learning, known as open set detection, is focused on detecting data instances from new devices encountered during deployment that were not previously seen...
    Resource Type:
    Masters Thesis
    Full Text:
    learning models. 25 Chapter 7: Acknowledgements This work is supported in part by Intel/NSF Award No

  • Machine Learning for Architectural Design Space Exploration and Resource Control

    Creator:
    Penney, Drew D.
    Abstract:
    Machine learning has enabled significant advancements in diverse fields, yet, with a few exceptions, has had limited impact on computer architecture. Recent work, however, has begun to explore broader application to design, optimization, and simulation. Notably, machine-learning-based strategies often surpass prior state-of-the-art analytical, heuristic, and human-expert approaches. This thesis first...
    Resource Type:
    Masters Thesis
    Full Text:
    by the National Science Foundation (NSF) grant #1750047. The work presented in Chapter 5 was

  • Atomic Layer Processing for Next-Generation Microelectronic Materials

    Creator:
    Holden, Konner E. K.
    Abstract:
    Atomic layer deposition (ALD) is an enabling technique for many new micro- and nanoscale technologies. The self-limiting surface chemical reactions by which ALD fundamentally operates give rise to uniquely high precision (atomic) control over deposited film thickness, uniformity over large areas, and conformality over complex and extreme topographies. One such...
    Resource Type:
    Dissertation
    Full Text:
    study. In this dissertation work, ALD processes are developed for Co3O4 and NiO, two shallow band

  • Complex patterns in gender HCI : a data mining study of factors leading to end-user debugging success for females and males

    Creator:
    Grigoreanu, Valentina I.
    Abstract:
    Most of the work so far in the subfield of Gender HCI has followed a theory-driven approach. Established theories, however, do not take into account specific issues that arise in end-user debugging. We suspected that there may be important information that we were overlooking. We therefore employed a methodology change:...
    Resource Type:
    Masters Thesis
    Full Text:
    and deeds. This work was supported in part by Microsoft Research, by NSF grant CNS-0420533, by an

  • Active learning of constraints for semi-supervised clustering

    Creator:
    Xiong, Sicheng
    Abstract:
    Semi-supervised clustering aims to improve clustering performance by considering user supervision in the form of pairwise constraints. In this paper, we study the active learning problem of selecting pairwise must-link and cannot-link constraints for semisupervised clustering. We consider active learning in an iterative manner where in each iteration queries are...
    Resource Type:
    Masters Thesis
    Full Text:
    the NSF for funding this research under Career Award 1055113. TABLE OF CONTENTS Page 1