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Filtering by: Creator Simionato, C. G. Remove constraint Creator: Simionato, C. G. Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science Decade 2020-2029 Remove constraint Decade: 2020-2029

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  • Low-Power 12-bit Quasi-Passive Segmented DAC Implemented in 130nm CMOS Technology

    Creator:
    Pierce, Alexander G.
    Abstract:
    This thesis work proposes a low-power 12-bit digital-to-analog converter (DAC) designed in a 130nm process. The DAC to be presented is of a segmented design where the architecture is split into pipelined and thermometer coded segments. This allows for high linearity and low distortion while maintaining high speed and low...
    Resource Type:
    Masters Thesis
    Full Text:
    Gabor C. Temes This thesis work proposes a low-power 12-bit digital-to-analog converter (DAC

  • Exploratory Study to Uncover Student Mental Models of Singly Linked Lists in the C Programming Language

    Creator:
    Almadhoun, Eman
    Abstract:
    In computer science, learning abstract fundamental programming concepts requiring students to understand memory management can be very difficult and lead to misunderstandings that carry on into advanced topics. This is especially true in data structures with abstract data types. Understanding how novice students think and reason about data structures is...
    Resource Type:
    Dissertation
    Full Text:
    : Exploratory Study to Uncover Student Mental Models of Singly Linked Lists in the C Programming Language

  • Electronic Stability of Metal Halide Perovskites

    Creator:
    Hong, Min Ji
    Abstract:
    Despite near unanimous opinion on the consequences of climate change by scientific community, the rate at which carbon is emitted into the atmosphere continues to increase. The need for a clean and sustainable source of energy is therefore one of humankind's most urgent challenges. Solar energy is the most abundant...
    Resource Type:
    Dissertation
    Full Text:
    ) 70°C, (g) 100°C, (h) pristine PbI2

  • Anomaly Detection and Probabilistic Diagnosis for Automated Data Quality Control

    Creator:
    Zemicheal, Tadesse H.
    Abstract:
    Advances in sensor technology are greatly expanding the range of quantities that can be measured while simultaneously reducing the cost. However, deployed sensors drift out of calibration and fail, so every sensor network requires quality control procedures to promptly detect these failures. To address these problems, we propose a two-level...
    Resource Type:
    Dissertation
    Full Text:
    : Thomas G. Dietterich Advances in sensor technology are greatly expanding the range of quantities that

  • A Benchmarking Study of Unsupervised Anomaly Detection Algorithms

    Creator:
    Emmott, Andrew F.
    Abstract:
    It is common practice in the unsupervised anomaly detection literature to create experimental benchmarks by sampling from existing supervised learning datasets. We seek to improve this practice by identifying four dimensions important to real-world anomaly detection applications --- point difficulty, clusteredness of anomalies, relevance of features, and relative frequency of...
    Resource Type:
    Masters Thesis
    Full Text:
    assesses the impact of our identified problems dimensions on experimental outcomes. c©Copyright by

  • The Familiarity Hypothesis: Explaining the Behavior of Deep Learning Methods in Out-of-Distribution Detection

    Creator:
    Guyer, Alexander
    Abstract:
    Many object recognition applications require detecting and responding to objects drawn from a different distribution from that of the training data. This task is referred to as out-of-distribution (OOD) detection, and it is often formulated as an outlier detection problem wherein the probability distribution of the known data P(X) is...
    Resource Type:
    Masters Thesis
    Full Text:
    : ______________________________________________________ Thomas G. Dietterich Many object recognition applications require detecting and

  • Switched Capacitor Circuit Techniques for High Performance CMOS Analog Circuits

    Creator:
    Kareppagoudr, Manjunath
    Abstract:
    Switched capacitor (SC) circuits are the main building blocks in many structures such as filters, data converters, sampling circuits and sampled-data amplifiers. The key challenge is to design such circuits which are the prime components of any IoT system with low power consumption without compromising on the performance. In this...
    Resource Type:
    Dissertation
    Full Text:
    Abstract approved: ______________________________________________________ Gabor C Temes Switched

  • 5th-Order Elliptic LPF Using Passive Charge Compensation Technique (PCC) Design

    Creator:
    Tsai, Cheng H.
    Abstract:
    The passive charge compensation (PCC) technique was introduced for switched capacitor (SC) circuit to increase the slew rate and enhance the linearity performance, as PCC techniques are used on the Delta-Sigma modulator (DSM) in ADC circuitry. The PCC technique of the project was applied to the design of a SC...
    Resource Type:
    Masters Thesis
    Full Text:
    : ______________________________________________________ Gabor C. Temes The passive charge compensation (PCC) technique was introduced for

  • Explanations and Processes to Enable Humans to Assess AI with Respect to Manipulable Properties

    Creator:
    Dodge, Jonathan E.
    Abstract:
    Assessing AI systems is difficult. Humans rely on AI systems in increasing ways, both visible and invisible, meaning a variety of stakeholders need a variety of assessment tools (e.g., a professional auditor, a developer, and an end user all have different needs). We posit that it is possible to provide...
    Resource Type:
    Dissertation
    Full Text:
    . . . . . . . . . . . . . . . . . . 147 B Design evolution of explanations in Chapter 4 and 5 . . . . . . . . . . . . . 148 C More about

  • Learning and Improving Policies for Probabilistic Planning Problems

    Creator:
    Issakkimuthu, Murugeswari
    Abstract:
    In this work, we study the problem of learning and improving policies for probabilistic planning problems. In the first part, we train neural network policies for probabilistic planning problems modeled as factored Markov decision problems. The objective is to train problem-specific neural networks via supervised learning to imitate the action...
    Resource Type:
    Dissertation
    Full Text:
    variable, i.e., o(z0i ) = xi. Layers 1 through L−1 are hidden layers each containing C×n nodes, where C