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Articles 1 - 6 of 6
Full-Text Articles in Engineering
Solar Data Analysis, Mike C. T. Ray
Solar Data Analysis, Mike C. T. Ray
Dissertations and Theses
The solar industry has grown considerably in the last few years. This larger scale has introduced more problems as well as possibilities. One of those possibilities is analyzing the data coming from the sites that are now being monitored, and using the information to answer a variety of questions.
We have four questions which are of prime importance identified in this thesis:
1. Can data from customers be trusted?
2. Can we use data from existing sites to determine which sites need the most improvement?
3. Can we implement a location-based algorithm to reduce the amount of false positives for …
A Parabolic Equation Analysis Of The Underwater Noise Radiated By Impact Pile Driving, Nathan Laws
A Parabolic Equation Analysis Of The Underwater Noise Radiated By Impact Pile Driving, Nathan Laws
Dissertations and Theses
Impact pile driving can produce extremely high underwater sound levels, which are of increasing environmental concern due to their deleterious effects on marine wildlife. Prediction of underwater sound levels is important to the assessment and mitigation of the environmental impacts caused by pile driving. Current prediction methods are limited and do not account for the dynamic pile driving source, inhomogeneities in bathymetry and sediment, or physics-based sound wave propagation.
In this thesis, a computational model is presented that analyzes and predicts the underwater noise radiated by pile driving and is suitable for shallow, inhomogeneous environments and long propagation ranges. The …
Computer Aided Design Of Permutation, Linear, And Affine-Linear Reversible Circuits In The General And Linear Nearest-Neighbor Models, Ben Schaeffer
Computer Aided Design Of Permutation, Linear, And Affine-Linear Reversible Circuits In The General And Linear Nearest-Neighbor Models, Ben Schaeffer
Dissertations and Theses
With the probable end of Moore's Law in the near future, and with advances in nanotechnology, new forms of computing are likely to become available. Reversible computing is one of these possible future technologies, and it employs reversible circuits. Reversible circuits in a classical form have the potential for lower power consumption than existing technology, and in a quantum form permit new types of encryption and computation.
One fundamental challenge in synthesizing the most general type of reversible circuit is that the storage space for fully specifying input-output descriptions becomes exponentially large as the number of inputs increases linearly. Certain …
Methods For Efficient Synthesis Of Large Reversible Binary And Ternary Quantum Circuits And Applications Of Linear Nearest Neighbor Model, Maher Mofeid Hawash
Methods For Efficient Synthesis Of Large Reversible Binary And Ternary Quantum Circuits And Applications Of Linear Nearest Neighbor Model, Maher Mofeid Hawash
Dissertations and Theses
This dissertation describes the development of automated synthesis algorithms that construct reversible quantum circuits for reversible functions with large number of variables. Specifically, the research area is focused on reversible, permutative and fully specified binary and ternary specifications and the applicability of the resulting circuit to the physical limitations of existing quantum technologies.
Automated synthesis of arbitrary reversible specifications is an NP hard, multiobjective optimization problem, where 1) the amount of time and computational resources required to synthesize the specification, 2) the number of primitive quantum gates in the resulting circuit (quantum cost), and 3) the number of ancillary qubits …
A Survey Of Systems For Predicting Stock Market Movements, Combining Market Indicators And Machine Learning Classifiers, Jeffrey Allan Caley
A Survey Of Systems For Predicting Stock Market Movements, Combining Market Indicators And Machine Learning Classifiers, Jeffrey Allan Caley
Dissertations and Theses
In this work, we propose and investigate a series of methods to predict stock market movements. These methods use stock market technical and macroeconomic indicators as inputs into different machine learning classifiers. The objective is to survey existing domain knowledge, and combine multiple techniques into one method to predict daily market movements for stocks. Approaches using nearest neighbor classification, support vector machine classification, K-means classification, principal component analysis and genetic algorithms for feature reduction and redefining the classification rule were explored. Ten stocks, 9 companies and 1 index, were used to evaluate each iteration of the trading method. The classification …
Joint Angle Tracking With Inertial Sensors, Mahmoud Ahmed El-Gohary
Joint Angle Tracking With Inertial Sensors, Mahmoud Ahmed El-Gohary
Dissertations and Theses
The need to characterize normal and pathological human movement has consistently driven researchers to develop new tracking devices and to improve movement analysis systems. Movement has traditionally been captured by either optical, magnetic, mechanical, structured light, or acoustic systems. All of these systems have inherent limitations. Optical systems are costly, require fixed cameras in a controlled environment, and suffer from problems of occlusion. Similarly, acoustic and structured light systems suffer from the occlusion problem. Magnetic and radio frequency systems suffer from electromagnetic disturbances, noise and multipath problems. Mechanical systems have physical constraints that limit the natural body movement. Recently, the …