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Articles 61 - 66 of 66
Full-Text Articles in Engineering
Neural Network Pruning For Ecg Arrhythmia Classification, Isaac E. Labarge
Neural Network Pruning For Ecg Arrhythmia Classification, Isaac E. Labarge
Master's Theses
Convolutional Neural Networks (CNNs) are a widely accepted means of solving complex classification and detection problems in imaging and speech. However, problem complexity often leads to considerable increases in computation and parameter storage costs. Many successful attempts have been made in effectively reducing these overheads by pruning and compressing large CNNs with only a slight decline in model accuracy. In this study, two pruning methods are implemented and compared on the CIFAR-10 database and an ECG arrhythmia classification task. Each pruning method employs a pruning phase interleaved with a finetuning phase. It is shown that when performing the scale-factor pruning …
Neca Ghana Project, Michael T. Klee
Neca Ghana Project, Michael T. Klee
Construction Management
Cal Poly’s motto is, “Learn by Doing" and for Cal Poly’s NECA Chapter, this isn’t simply a motto, but a directive for proactive change. For my senior project I will be leading the Cal Poly NECA chapter in the design, pre- fabrication and construction of a 5-7kw solar array, community center, ice production room and technology room in the remote fishing village of Agbokpa, Ghana. The solar array will power multiple industrial DC freezers, high efficiency LED lighting and charging stations while additionally powering water filtration and irrigation systems. Like many other fishing villages around the world, Agbokpa has no …
Optimizing Llrf Parameters In The Electron-Ion Collider, William M. Bjorndahl
Optimizing Llrf Parameters In The Electron-Ion Collider, William M. Bjorndahl
Physics
To improve particle interaction in the future Electron-Ion Collider (EIC), we investigated different feedback implementations to control the accelerating voltage and examined the power and beam phase for each instance. Using MATLAB, we studied three feedback mechanisms: Direct, One Turn, and Feedforward. Enacting feedforward yielded the best performance. To minimize the klystron power consumption, we analyzed different Low-Level Radio Frequency (LLRF) parameters such as detuning. Combining theory and simulated results, we found the optimal detuning value that minimizes klystron power consumption.
Pulsed Electrical Field Ablation Modulation, Camille Lousie Dozois, Jason Tyler Arias, Courtnee Lin Madsen
Pulsed Electrical Field Ablation Modulation, Camille Lousie Dozois, Jason Tyler Arias, Courtnee Lin Madsen
Biomedical Engineering
This document comprises the steps taken by the senior project team to create a Proof-of-Concept Review for a Variable Pulsed Electric Field Ablation Catheter. First, the team did a significant amount of background research on related literature to better understand the current status of the project topic. After sufficient background information was obtained, project objectives and deliverables were finalized. Once customer requirements and the indications for use were completed, engineering specifications for the product and project were documented. All key customer requirements and engineering specs were related to the variable pulse functionality, maneuverability, as well as overall dimensioning of the …
Decentralized, Noncooperative Multirobot Path Planning With Sample-Basedplanners, William Le
Decentralized, Noncooperative Multirobot Path Planning With Sample-Basedplanners, William Le
Master's Theses
In this thesis, the viability of decentralized, noncooperative multi-robot path planning algorithms is tested. Three algorithms based on the Batch Informed Trees (BIT*) algorithm are presented. The first of these algorithms combines Optimal Reciprocal Collision Avoidance (ORCA) with BIT*. The second of these algorithms uses BIT* to create a path which the robots then follow using an artificial potential field (APF) method. The final algorithm is a version of BIT* that supports replanning. While none of these algorithms take advantage of sharing information between the robots, the algorithms are able to guide the robots to their desired goals, with the …
Electricity Price Forecasting Using A Convolutional Neural Network, Elliott Winicki
Electricity Price Forecasting Using A Convolutional Neural Network, Elliott Winicki
Master's Theses
Many methods have been used to forecast real-time electricity prices in various regions around the world. The problem is difficult because of market volatility affected by a wide range of exogenous variables from weather to natural gas prices, and accurate price forecasting could help both suppliers and consumers plan effective business strategies. Statistical analysis with autoregressive moving average methods and computational intelligence approaches using artificial neural networks dominate the landscape. With the rise in popularity of convolutional neural networks to handle problems with large numbers of inputs, and convolutional neural networks conspicuously lacking from current literature in this field, convolutional …