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Full-Text Articles in Physical Sciences and Mathematics

Higher-Level Consistencies: Where, When, And How Much, Robert J. Woodward Sep 2018

Higher-Level Consistencies: Where, When, And How Much, Robert J. Woodward

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Determining whether or not a Constraint Satisfaction Problem (CSP) has a solution is NP-complete. CSPs are solved by inference (i.e., enforcing consistency), conditioning (i.e., doing search), or, more commonly, by interleaving the two mechanisms. The most common consistency property enforced during search is Generalized Arc Consistency (GAC). In recent years, new algorithms that enforce consistency properties stronger than GAC have been proposed and shown to be necessary to solve difficult problem instances.

We frame the question of balancing the cost and the pruning effectiveness of consistency algorithms as the question of determining where, when, and how much of a higher-level …


Effectively Enforcing Minimality During Backtrack Search, Daniel J. Geschwender May 2018

Effectively Enforcing Minimality During Backtrack Search, Daniel J. Geschwender

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Constraint Processing is an expressive and powerful framework for modeling and solving combinatorial decision problems. Enforcing consistency during backtrack search is an effective technique for reducing thrashing in a large search tree. The higher the level of the consistency enforced, the stronger the pruning of inconsistent subtrees. Recently, high-level consistencies (HLC) were shown to be instrumental for solving difficult instances. In particular, minimality, which is guaranteed to prune all inconsistent branches, is advantageous even when enforced locally. In this thesis, we study two algorithms for computing minimality and propose three new mechanisms that significantly improve performance. Then, we integrate the …


Speech Emotion Recognition Using Convolutional Neural Networks, Somayeh Shahsavarani Mar 2018

Speech Emotion Recognition Using Convolutional Neural Networks, Somayeh Shahsavarani

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Automatic speech recognition is an active field of study in artificial intelligence and machine learning whose aim is to generate machines that communicate with people via speech. Speech is an information-rich signal that contains paralinguistic information as well as linguistic information. Emotion is one key instance of paralinguistic information that is, in part, conveyed by speech. Developing machines that understand paralinguistic information, such as emotion, facilitates the human-machine communication as it makes the communication more clear and natural. In the current study, the efficacy of convolutional neural networks in recognition of speech emotions has been investigated. Wide-band spectrograms of the …


The Stance On Artificial Intelligence, Edward Gonzalez-Olmedo Jan 2018

The Stance On Artificial Intelligence, Edward Gonzalez-Olmedo

Nebraska College Preparatory Academy: Senior Capstone Projects

Mary Shelley’s novel Frankenstein brings up the question: When do we draw the line on technological Artificial Intelligence (AI) advancement? The importance of this is that we need to be able to control the technology that we produce. Humans always strive for an advancement in technology, and AI is one of the more advanced concepts. Mary Shelley introduces this problem with Frankenstein when he creates a creature which cannot be controlled by its creator. Humans have begun to tinker with this new technology, yet mankind does not fully understand AI.

● Human desire is inevitable. ● The creation of AI …


Crop Height Estimation With Unmanned Aerial Vehicles, Carrick Detweiler, David Anthony, Sebastian Elbaum Jan 2018

Crop Height Estimation With Unmanned Aerial Vehicles, Carrick Detweiler, David Anthony, Sebastian Elbaum

School of Computing: Faculty Publications

An unmanned aerial vehicle (UAV) can be configured for crop height estimation. In some examples, the UAV includes an aerial propulsion system, a laser scanner configured to face downwards while the UAV is in flight, and a control system. The laser scanner is configured to scan through a two-dimensional scan angle and is characterized by a maxi mum range. The control system causes the UAV to fly over an agricultural field and maintain, using the aerial propulsion system and the laser scanner, a distance between the UAV and a top of crops in the agricultural field to within a programmed …