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Full-Text Articles in Engineering
Efficient Numerical Optimization For Parallel Dynamic Optimal Power Flow Simulation Using Network Geometry, Rylee Sundermann
Efficient Numerical Optimization For Parallel Dynamic Optimal Power Flow Simulation Using Network Geometry, Rylee Sundermann
Electronic Theses and Dissertations
In this work, we present a parallel method for accelerating the multi-period dynamic optimal power flow (DOPF). Our approach involves a distributed-memory parallelization of DOPF time-steps, use of a newly developed parallel primal-dual interior point method, and an iterative Krylov subspace linear solver with a block-Jacobi preconditioning scheme. The parallel primal-dual interior point method has been implemented and distributed in the open-source PETSc library and is currently available. We present the formulation of the DOPF problem, the developed primal dual interior point method solver, the parallel implementation, and results on various multi-core machines. We demonstrate the effectiveness our proposed block-Jacobi …
Study On Performance Of Pruned Cnn-Based Classification Models, Mengling Deng
Study On Performance Of Pruned Cnn-Based Classification Models, Mengling Deng
Electronic Theses and Dissertations
Convolutional Neural Network (CNN) is a neural network developed for processing image data. CNNs have been studied extensively and have been used in numerous computer vision tasks such as image classification and segmentation, object detection and recognition, etc. [1] Although, the CNNs-based approaches showed humanlevel performances in these tasks [2], they require heavy computation in both training and inference stages, and the models consist of millions of parameters. This hinders the development and deployment of CNN-based models for real world applications. Neural Network Pruning and Compression techniques have been proposed [3, 4] to reduce the computation complexity of trained CNNs …
Superhalogen-Based Li-Rich Anti-Perovskite Superionic Conductors, Md Mominul Islam
Superhalogen-Based Li-Rich Anti-Perovskite Superionic Conductors, Md Mominul Islam
Electronic Theses and Dissertations
Solid-state batteries are being widely explored to meet next-generation energy storage demand with a great potentiality of achieving high energy and power densities at All-solidstate Lithium-ion batteries (LIBs). In recent years, electronically inverted lithium-rich antiperovskite (LiRAP) solid electrolytes with the formula Li3OX, where X is a halogen or mixture of halogens have appeared as a prospective alternative of the commercially available flammable and corrosive organic liquid electrolytes because of their high ionic conductivity, structural variety, and wide electrochemical window. Here, For the first time, we have successfully formulated and synthesized a completely new class of super halogen based double anti-perovskite …
Artificial Solid Electrolyte Interface With Superhalogen-Based Double Antiperovskite Li6os(Bh4)2 Materials For Dentrite-Free And Stable Lithium Metal Batteries, Gazi Mahfujul Alam
Artificial Solid Electrolyte Interface With Superhalogen-Based Double Antiperovskite Li6os(Bh4)2 Materials For Dentrite-Free And Stable Lithium Metal Batteries, Gazi Mahfujul Alam
Electronic Theses and Dissertations
Lithium ion batteries -- Materials.
Electrolytes.
Solid state batteries.
Sentiment Without Sentiment Analysis: Using The Recommendation Outcome Of Steam Game Reviews As Sentiment Predictor, Anqi Zhang
Electronic Theses and Dissertations
This paper presents and explores a novel way to determine the sentiment of a Steam game review based on the predicted recommendation of the review, testing different regression models on a combination of Term Frequency-Inverse Document Frequency (TF-IDF) and Latent Dirichlet Allocation (LDA) features. A dataset of Steam game reviews extracted from the Programming games genre consisting of 21 games along with other significant features such as the number of helpful likes on the recommendation, number of hours played, and others. Based on the features, they are grouped into three datasets: 1) either having keyword features only, 2) keyword features …
Relative Radiometric Correction Of Pushbroom Satellites Using The Yaw Maneuver, Christopher Begeman
Relative Radiometric Correction Of Pushbroom Satellites Using The Yaw Maneuver, Christopher Begeman
Electronic Theses and Dissertations
Earth imaging satellites commonly acquire multispectral imagery using linear array detectors formatted as a pushbroom scanner. Landsat 8, a well-known example, uses pushbroom scanning and thus has 73,000 individual detectors. These 73,000 detectors are split among 14 different focal plane modules (FPM), and each detector and FPM exhibit unique behavior when monitoring a uniform radiance value. To correct for each detectors differences in sensor measurement a novel technique of relative gain estimation that employs an optimized modified Signal-to-Noise Ratio through a 90˚ yaw maneuver, also known as side slither, is presented that allows for both FPM and detector level relative …
Using Long Short-Term Memory Networks To Make And Train Neural Network Based Pseudo Random Number Generator, Aditya Harshvardhan
Using Long Short-Term Memory Networks To Make And Train Neural Network Based Pseudo Random Number Generator, Aditya Harshvardhan
Electronic Theses and Dissertations
Neural Networks have been used in many decision-making models and been employed in computer vision, and natural language processing. Several works have also used Neural Networks for developing Pseudo-Random Number Generators [2, 4, 5, 7, 8]. However, despite great performance in the National Institute of Standards and Technology (NIST) statistical test suite for randomness, they fail to discuss how the complexity of a neural network affects such statistical results. This work introduces: 1) a series of new Long Short- Term Memory Network (LSTM) based and Fully Connected Neural Network (FCNN – baseline [2] + variations) Pseudo Random Number Generators (PRNG) …
Optimization Based Parameter And State Estimation Framework For Remote Microgrid Frequency Dynamics Modeling Using Probing Signals From Energy Storage Systems, Manisha Rauniyar
Optimization Based Parameter And State Estimation Framework For Remote Microgrid Frequency Dynamics Modeling Using Probing Signals From Energy Storage Systems, Manisha Rauniyar
Electronic Theses and Dissertations
The primary aim of this thesis is to deliver an efficient design and selection of probing signal needed to estimate state and parameters representing the power system frequency dynamics with the proposed estimation technique in real-time with minimum computational time and cost. These test cases are designed for power system researchers that need to estimate and control analysis at the remote microgrid level. Case studies are presented that can be simulated at the transmission and distribution level in power grids, and in remote isolated microgrids where the independent system operator (ISO) has control. Increasing utilization of renewable energy sources and …