Search Constraints

Start Over
Filtering by: Creator Benjamin, Namrod David Remove constraint Creator: Benjamin, Namrod David Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science

Search Results

  • Usable and Scalable Querying of Scientific Datasets

    Creator:
    McCamish, Benjamin J.
    Abstract:
    Scientists and engineers have to analyze and query multiple large databases. Analysis over databases created by phasor measurement units can provide insight into the health of the grid, thereby improving control over operations. Realizing this data-driven control, however, requires validating, processing and storing massive amounts of PMU data efficiently, which...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Benjamin John McCamish

  • Bitmap Indexing : Energy Applications and Improvements

    Creator:
    McCamish, Benjamin
    Abstract:
    Large databases and data warehouses are becoming prevalent for the storage and management of energy data. Accelerating the rates at which data can be retrieved is beneficial not only to allow for more efficient search of the data, but also to be integrated with other energy system tools. In this...
    Resource Type:
    Masters Thesis
    Full Text:
    ABSTRACT OF THE THESIS OF Benjamin McCamish for the degree of Master of Science in Computer Science

  • Structuring Teachable Knowledge through Program-Concept Classifications

    Creator:
    Wilson, Benjamin F.
    Abstract:
    Teaching CS is a challenging task, especially for those without prior programming experience. Even for veteran educators, having to learn CS concepts while also trying to teach those same concepts is difficult; as is the case for many K-12 CS instructors. Unfortunately, there is often no formalized order with CS...
    Resource Type:
    Masters Thesis
    Full Text:
    AN ABSTRACT OF THE THESIS OF Benjamin Friedman Wilson

  • Computational methods for protein-protein interface prediction

    Creator:
    Tribelhorn, Benjamin
    Abstract:
    Protein-protein interactions underlie all biological processes and are a field of study that has wide implications throughout many other fields including medicine, genetics, biology, and ecology. Proteins are the building blocks and primary actors of life. They work together to accomplish virtually every task within a cell, including, metabolism, signal...
    Resource Type:
    Dissertation

  • Computational Approaches for RNA Structure Prediction with Dynamic Programming and Deep Neural Networks

    Creator:
    Deng, Dezhong
    Abstract:
    Our goal is to build a system to model the RNA sequences that reveals their structural information by using efficient dynamic programming algorithms and deep learning approaches. We aim to 1) achieve linear-time for RNA secondary structure prediction based on existing minimum free energy models; 2) utilize deep neural networks...
    Resource Type:
    Dissertation
    Full Text:
    Abstract approved: David A. Hendrix Our goal is to build a system to model the RNA sequences that reveals

  • Prediction of gene transcription start sites and initiation patterns from DNA sequence content

    Creator:
    Morton, Taj H.
    Abstract:
    The computational identification of gene Transcription Start Sites (TSSs) can provide insights into the regulation and function of genes without performing expensive experiments, particularly in organisms with incomplete annotations. High-resolution general-purpose TSS prediction remains a challenging problem, with little recent progress on the identification and differentiation of TSSs which are...
    Resource Type:
    Masters Thesis
    Full Text:
    . I would also like to thank my committee for their time and guidance: Dr. David Hendrix and Dr

  • Simulation and modeling of substrate noise generation from synchronous and asynchronous digital logic circuits

    Creator:
    Hanken, Christopher
    Abstract:
    Efficient methods for simulating the substrate noise generated by complex synchronous and asynchronous digital logic circuits are presented. By simulating digital logic at the gate level, and precharacterizing the gates, the substrate noise generation can be predicted and used in a transistor level simulation of the sensitive analog blocks. This...
    Resource Type:
    Masters Thesis
    Full Text:
    like to thank my brothers Joel and Benjamin, my mother Diane, and my father David, for their love and

  • Exploration of regression models for cancer noncoding mutation recurrence

    Creator:
    Xu, Tanjin
    Abstract:
    An important impact of the genome technology revolution will be the elucidation of mechanisms of cancer pathogenesis, leading to improvements in the diagnosis of cancer and the selection of cancer treatment. Integrated with current well-studied massive knowledge and findings about the role of protein-coding mutations in cancer, demystifying the functional...
    Resource Type:
    Masters Thesis
    Full Text:
    . Xiaoli Fern, Prof. David Hendrix and Prof. Hector A. Vergara for their insights, suggestions and their

  • 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:
    committee members – Prof. David Cann, Prof. Alan Wang, Prof. John Labram – have all provided key

  • Knowledge Base Completion Leveraging Natural Language Data

    Creator:
    Shahbazi, Hamed
    Abstract:
    Information about named entities (real-world objects) is usually harvested from different sources and organized as a multiple relational directed graph in Knowledge Bases (KBs). KBs play essential roles in many NLP modules including question answering, fact-checking, search engines, etc. KBs are big but still incomplete: relational information among entities is...
    Resource Type:
    Dissertation

  • Multiagent learning for locomotion and coordination in tensegrity robotics

    Creator:
    Iscen, Atil
    Abstract:
    Tensegrity structures are composed of pure compressional elements that are connected via a network of pure tensional elements. The concept of tensegrity promises numerous advantages to the field of robotics. Tensegrity robots are, however, notoriously difficult to control due to their oscillatory nature and nonlinear interaction between the components. Multiagent...
    Resource Type:
    Dissertation

  • Magnetic bead detection with ferromagnetic resonance for use in immuno-biosensor application

    Creator:
    Ghionea, Simon
    Abstract:
    The objective of this thesis is to introduce and demonstrate a novel magnetic bead detector based on inductive detection at the ferromagnetic resonance (FMR) frequency for use in bio-sensing applications. Detection ability is demonstrated through theoretical arguments, numerical computer simulations, and experimental characterization of micro-fabricated detectors. The detector is composed...
    Resource Type:
    Masters Thesis

  • Computational Elucidation of the Regulatory SNPs in the Non-Coding Regions of the Human Genome

    Creator:
    Yao, Yao
    Abstract:
    We describe a series of novel computational models, CERENKOV (Computational Elucidation of the REgulatory NonKOding Variome) and its successors CERENKOV2, CERENKOV3, and Convolutional CERENKOV3, for discriminating regulatory single nucleotide polymorphisms (rSNPs) from non-regulatory SNPs within non-coding genetic loci. The CERENKOV models are designed for recognizing rSNPs in the context of...
    Resource Type:
    Dissertation

  • Partitioning-Guided K-Means for Effective Empty Cluster Resolution in Extreme Model Compression

    Creator:
    Huang, Tianhong
    Abstract:
    Compactness in deep learning can be critical to a model’s viability in low-resource applications, and a common approach to extreme model compression is quantization. We consider Iterative Product Quantization (iPQ) with Quant-Noise [Fan et al., 2020] to be state-of-the-art in this area, but this quantization framework suffers from preventable inference...
    Resource Type:
    Masters Thesis
    Full Text:
    , Yoshua Bengio, and Jean-Pierre David. Binaryconnect: Training deep neural networks with binary weights

  • Region based image matching for 3D object recognition

    Creator:
    Liu, Tian
    Abstract:
    3D object recognition is a very difficult and important problem in computer vision, arising in a wide range of applications. Typically in 3D object recognition, interest points are extracted from images and then matched. A shortcoming of this approach is that points only carry local visual information. Therefore, there could...
    Resource Type:
    Masters Thesis

  • Information-theoretic Approach to Design and Evaluate Privacy-preserving and Fair Frameworks for Continuous High-dimensional Data

    Creator:
    Alsulaimawi, Zahir Ahmed Hussein
    Abstract:
    Deep learning is becoming the latest trend in sensitive applications, such as healthcare, criminal justice, and finance. As these new applications emerge, adversaries are circumventing them. Further, there have been concerns about the possibility of bias and discrimination in predictive applications. In order to address these issues, we propose an...
    Resource Type:
    Dissertation

  • Uncertainty in Deep Learning with Implicit Neural Networks

    Creator:
    Ratzlaff, Neale
    Abstract:
    The ability to extract uncertainties from predictions is crucial for the adoption of deep learning systems to safety-critical applications. Uncertainty estimates can be used as a failure signal, which is necessary for automating complex tasks where safety is a concern. Furthermore, current deep learning systems do not provide uncertainty estimates,...
    Resource Type:
    Dissertation

  • How Should A Deaf Car Drive?

    Creator:
    Grant, Denue, Jr.
    Abstract:
    This thesis seeks to determine whether a self-driving car's behavior should depend on the hearing status of its passengers: namely, hard-of-hearing (including deaf) or hearing. It is believed that auditory deprivation provokes adaptations in visual attention. These adaptations may lead to atypical movement patterns that can translate to different driving...
    Resource Type:
    Masters Thesis
    Full Text:
    for On-Road Motor Vehicles, jun 2018. [3] Benjamin Wilson, Judy Hoffman, and Jamie Morgenstern

  • Open Set Learning with Counterfactual Images

    Creator:
    Neal, Lawrence W.
    Abstract:
    In open set recognition, a classifier must label instances of known classes while detecting instances of unknown classes not encountered during training. To detect unknown classes while still generalizing to new instances of existing classes, this thesis introduces a dataset augmentation technique called counterfactual image generation. This approach, based on...
    Resource Type:
    Masters Thesis
    Full Text:
    the IEEE conference on computer vision and pattern recognition, pages 1563–1572, 2016. [3] David

  • Hybrid visualization of asymmetric tensor fields : glyphs and hyperstreamlines

    Creator:
    Palke, Darrel
    Abstract:
    Asymmetric tensor fields are useful for understanding fluid flow and solid deformation. They present new challenges, however, for traditional tensor field visualization techniques such as hyperstreamline placement and glyph packing. This is because the physical behavior of tensors inside real domains where eigenvalues are real is fundamentally different from the...
    Resource Type:
    Masters Thesis

  • Improving User Mental Models of XAI Systems with Inclusive Design Approaches

    Creator:
    Hamid, Md Montaser
    Abstract:
    Explainable Artificial Intelligence (XAI) systems aim to improve users’ understanding of AI but rarely consider the inclusivity aspects of XAI. Without inclusive approaches, improving explanations might not work well for everyone. This study investigates leveraging users’ diverse problem-solving styles as an inclusive strategy to fix an XAI prototype, with the...
    Resource Type:
    Masters Thesis

  • Computing Bounded Chains and Surfaces in a Simplicial Complex with Bounded-treewidth 1-skeleton

    Creator:
    Black, Mitchell
    Abstract:
    We consider three problems on simplicial complexes: the Optimal Bounded Chain Problem, the Optimal Homologous Chain Problem, and 2-Dim-Bounded-Surface. The Optimal Bounded Chain Problem asks to find the minimum weight d-chain in a simplicial complex K bounded by a given (d−1)-chain, if such a d-chain exists. The Optimal Homologous Chain...
    Resource Type:
    Masters Thesis

  • Optimizing performance/watt of embedded SIMD multiprocessors through a priori application guided power scheduling

    Creator:
    Albright, Ryan K.
    Abstract:
    A method for improving performance/watt of an embedded single-instruction multiple-data (SIMD) architecture using application-guided a priori scheduling of hardware resources is presented. A multi-core architectural simulator is adopted that accurately estimates power, performance, and utilization of various processor components (logic, interconnect and memory). A greedy search is then performed on...
    Resource Type:
    Masters Thesis
    Full Text:
    exploration done by Benjamin Goska and Thomas Ruggeri as well as the work on Synctium done by Robert

  • Deep Segmentation in Plant Phenomics

    Creator:
    Kaur, Damanpreet
    Abstract:
    The abilities of plant biologists to characterize the genetic basis of physiological traits are limited by their abilities to obtain quantitative data representing precise details of trait variation and mainly to collect this data on a high-throughput scale at low cost. Deep learning-based methods have demonstrated unprecedented potential to automate...
    Resource Type:
    Masters Thesis

  • Leveraging Structures of the Data in Deep Learning

    Creator:
    Li, Xingyi
    Abstract:
    The performance of deep learning frameworks could be significantly improved through considering the particular underlying structures for each dataset. In this thesis, I summarize our three work about boosting the performance of deep learning models through leveraging structures of the data. In the first work, we theoretically justify that, for...
    Resource Type:
    Dissertation

  • Towards Direct Simultaneous Speech Translation

    Creator:
    Chen, Junkun
    Abstract:
    Simultaneous speech translation (SimulST) is widely useful in many cross-lingual communication scenarios, including multinational conferences and international traveling. Since text-based simultaneous machine translation (SimulMT) has achieved great success in recent years. The conventional cascaded approach for SimulST uses a pipeline of streaming ASR followed by simultaneous MT but suffers from...
    Resource Type:
    Dissertation

  • Toward Disentangling the Activations of the Deep Networks via Low-dimensional Embedding and Non-negative Factorization

    Creator:
    Khorram, Saeed
    Abstract:
    In this thesis, we introduce a novel Explanation Neural Network (XNN) to explain the predictions made by a deep network. The XNN works by embedding a high-dimensional activation vector of a deep network layer non-linearly into a low-dimensional explanation space while retaining faithfulness i.e., the original deep learning predictions can...
    Resource Type:
    Masters Thesis

  • 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

  • Quantum dot plasmon coupling : Fundamental study and applications

    Creator:
    Kannegulla, Akash
    Abstract:
    The dissertation focuses on the engineering of light-matter interaction using plasmonic nanoparticles and metamaterials to achieve enhanced luminescence and based on which to improve the performance of biosensing and light-emitting technologies. We designed and fabricated a spectrum of nanostructures to exhibit particular dispersion relations capable of controlling the spontaneous emission...
    Resource Type:
    Dissertation

  • Fine-Grained Object Recognition Under Limited Training Data

    Creator:
    Lam, Michael Q.
    Abstract:
    This dissertation addresses object recognition in challenging settings, where distinct object classes are visually very similar (e.g., species of birds and insects) and/or access to training examples of object classes is limited (e.g., due to the associated high costs of data annotation). In this dissertation, we present a variety of...
    Resource Type:
    Dissertation

  • Poisoning machine learning models to increase membership inference risks

    Creator:
    Le, Hoang
    Abstract:
    Deep learning is now being utilized widely in applications where sensitive data is being used for model training, for example, in health care. In this scenario, any data leakage will cause privacy concerns to whose data records are used to train the model. An attacker can actively cause privacy leakage...
    Resource Type:
    Masters Thesis
    Full Text:
    arXiv:2112.02918, 2021. [3] Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Ka- plan

  • Using Web Services for Image Processing in a Desktop Widgets Engine

    Creator:
    Le, Hien
    Abstract:
    Desktop widget engines have emerged as an alternative for completing simple tasks without the need for a full-blown application or constant user interaction. Widgets can simply display data in a compact and visually appealing manner (such as stock tickers, weather forecasts, and news notifications), or go so far as to...
    Resource Type:
    Capstone Project
    Full Text:
    ://www.greenbuildingstudio.com/gbsinc/gbs-web.aspx. [37] Benjamin Joffe. Canvascape - 3D Walker. http://www.abrahamjoffe.com.au

  • A high power emulation of a wind farm

    Creator:
    Lalla, Chelsea
    Abstract:
    As more wind farms are connected to the grid, the variable nature of wind energy begins to influence grid stability. Energy storage could help smooth the variable nature of wind energy. Laboratory demonstration and exploration of the interaction between different energy storage devices and wind energy could help improve and...
    Resource Type:
    Masters Thesis
    Full Text:
    an improvement on this experimental situation. 49 BIBLIOGRAPHY [1] David Milborrow

  • Formative Work Toward a Mixed-Initiative Programming Language

    Creator:
    Abbott, Keeley
    Abstract:
    Mixed-initiative programming entails collaboration between a computer system, and a human to achieve some desired goal or set of goals. Often these goals change or are amended in real time during the course of program execution. As such, the plans these programs are based on must adapt and evolve to...
    Resource Type:
    Masters Thesis

  • Elucidating Computational Narratives to Facilitate Code Comprehension

    Creator:
    Chattopadhyay, Souti
    Abstract:
    Programming is integrated across the workflow of multiple domains where end-user programmers, those who need to program as a means to an end, regularly need to code. In the modern setting of collaborative development, end-user programmers have to interpret the intentions behind existing code to contribute and build solutions to...
    Resource Type:
    Dissertation

  • Robust and Efficient Classification of Videos in the Wild

    Creator:
    Mahasseni, Behrooz
    Abstract:
    Recognizing human actions in videos is a long-standing problem in computer vision with a wide range of applications including video surveillance, content retrieval, and sports analysis. This thesis focuses on addressing efficiency and robustness of video classification in unconstrained real-world settings. The thesis work can be broadly divided into four...
    Resource Type:
    Dissertation

  • Machine learning methods for public policy : simulation, optimization, and visualization

    Creator:
    McGregor, Sean
    Abstract:
    Society faces many complex management problems, particularly in the area of shared public resources such as ecosystems. Existing decision making processes are often guided by personal experience and political ideology rather than state-of-the-art scientific understanding. This dissertation envisions a future in which multiple stakeholders are provided with computational tools for...
    Resource Type:
    Dissertation

  • Video Analysis : Techniques for Semi-Supervised Video Object Instance Segmentation and Tracking-by-Detection in the Wild

    Creator:
    Firl, Alrik K.
    Abstract:
    This thesis consists of two major components. The first part is concerned with video object instance segmentation (VOS), which is the task of assigning per-pixel labels perframe of a video sequence to indicate foreground object instance membership, given the first frame ground truth mask. VOS has myriad applications, from video...
    Resource Type:
    Masters Thesis

  • How does AAR/AI Support Problem Solvers with Diverse Behaviors and Cognitive Styles?

    Creator:
    Dikkala, Rupika
    Abstract:
    "What’s wrong with this AI?" Explainable AI (XAI) researchers are moving beyond explaining an AI’s actions, to helping users detect an AI’s failures. However this detection may not be enough—for actionability, we often need to pinpoint which part failed. We investigate how AAR/AI, a structured assessment process, supports users with...
    Resource Type:
    Masters Thesis

  • Pixel- and Frame-level Video Labeling using Spatial and Temporal Convolutional Networks

    Creator:
    Lei, Peng
    Abstract:
    This dissertation addresses the problem of video labeling at both the frame and pixel levels using deep learning. For pixel-level video labeling, we have studied two problems: i) Spatiotemporal video segmentation and ii) Boundary detection and boundary flow estimation. For the problem of spatiotemporal video segmentation, we have developed recurrent...
    Resource Type:
    Dissertation

  • A Decade of Linux Kernel Vulnerabilities, their Mitigation and Open Problems

    Creator:
    Raj, Abhilash
    Abstract:
    The aim of this thesis is to study past 10 years of security vulnerabilities reported against Linux Kernel and all existing mitigation techniques that prevent the exploitation of those vulnerabilities. To systematically study the security vulnerabilities, they were categorized into classes and sub-classes based on their type. This thesis first...
    Resource Type:
    Masters Thesis

  • Analytical Methods for Improving Causal Inference

    Creator:
    Sinha, Meghamala
    Abstract:
    Causal inference is an important analytical tool to bridge the gap between prediction and decision-making. However, learning a causal network solely from data is a challenging task. In this work, various techniques have been explored for a better and improved causal network learning from data. Firstly, the problem of learning...
    Resource Type:
    Dissertation

  • Guided Translation of Algorithmic Notation into Functional Programs

    Creator:
    Fedorin, Danila
    Abstract:
    The use of board games for teaching introductory computer science is a promising recent avenue of research. The goal is to introduce computing concepts through their use in the implementations of simple games, thereby keeping students engaged through their learning process. However, there is a gap between students' algorithmic descriptions...
    Resource Type:
    Masters Thesis

  • Integrating learning and search for structured prediction

    Creator:
    Doppa, Janardhan Rao
    Abstract:
    We are witnessing the rise of the data-driven science paradigm, in which massive amounts of data - much of it collected as a side-effect of ordinary human activity - can be analyzed to make sense of the data and to make useful predictions. To fully realize the promise of this...
    Resource Type:
    Dissertation

  • Simulator-Defined MDP Planning with Applications in Natural Resource Management

    Creator:
    Alkaee Taleghan, Majid
    Abstract:
    This work is inspired by problems in natural resource management centered on the challenge of invasive species. Computing optimal management policies for maintaining ecosystem sustainable is challenging. Many ecosystem management problems can be formulated as MDP (Markov Decision Process) planning problems. In a simulator-defined MDP, the Markovian dynamics and rewards...
    Resource Type:
    Dissertation

  • Object Tracking-by-Segmentation in Videos

    Creator:
    Chen, Sheng
    Abstract:
    This thesis focuses on the problem of object tracking. Given a video, the general objective of tracking is to track the location over time of one or more targets in the image sequence. This is a very challenging task as algorithms need to deal with problems such as appearance variations,...
    Resource Type:
    Dissertation

  • Machine Learning Methods for Computational Sustainability

    Creator:
    Liu, Liping
    Abstract:
    Maintaining the sustainability of the earth’s ecosystems has attracted much attention as these ecosystems are facing more and more pressure from human activities. Machine learning can play an important role in promoting sustainability as a large amount of data is being collected from ecosystems. There are at least three important...
    Resource Type:
    Dissertation

  • Learning Based Anomaly Detection for Industrial Arm Applications

    Creator:
    Narayanan, Vedanth
    Abstract:
    Smart Manufacturing (SM) is envisioned to make manufacturing processes more efficient through automation and integration of networked information systems. Robotic arms are integral to this vision. However the benefits of SM, enabled by automation and networking, also come with cyber risks. In this work, we propose an anomaly detection framework...
    Resource Type:
    Capstone Project

  • 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

  • Understanding Software-2.0: A Study of Machine Learning library usage and evolution

    Creator:
    Dilhara, Malinda, Ketkar, Ameya, and Dig, Danny
    Abstract:
    Enabled by a rich ecosystem of Machine Learning (ML) libraries, programming using learned models, i.e., Software-2.0, has gained substantial adoption. However, we do not know what challenges developers encounter when they use ML libraries. With this knowledge gap, researchers miss opportunities to contribute to new research directions, tool builders do...
    Resource Type:
    Research Paper