Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 44 for “"network methods"”.
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Network methods for inventory management in capacity constrained retail stores
… demand by testing three inventory management methods. The first method creates a virtual cost in the inventory redistribution algorithm, which decreases the likelihood that an over-capacity store will hold an item. This method decreased the amount of post transfer inventory by 15 % in capacity …
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Understanding compound-induced histopathology in rat liver using gene expression network methods
… chemical variety of the databases, data-driven methods led to the novel creation of histopathology signatures, which accounts for dependence between histopathology observations (Chapter 2). Six toxic groups were determined for DrugMatrix and 13 for Open TG-GATEs, and were analysed with a view to …
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Breaking Down the Monolith: Using Network Methods to Identify and Analyze Chicago’s Largest Landlords
… by linking large, administrative datasets in a network model. I identify 48 landlords who each own 1,000 or more units in MFR buildings (as of 2024). These 48 landlords collectively own 17.3% of MFR units in Chicago. </p><p dir="ltr">After identifying these actors, I describe them, especially in …
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Predictive Modeling of Sugarbeet Quality Using Vegetative Index, Statistical, and Artificial Neural Network Methods
… of using statistical, artificial neural network (ANN) and vegetative canopy models to predict whole-field sucrose concentration in sugarbeet fields using canopy spectral reflectance and sugarbeet field production data. The data consisted of five years of Landsat 5 and Landsat 7 Thematic …
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Neural Network Methods for Improving Signal Processing in High-Purity Germanium Detectors for Rare Event Searches
… especially in low-energy analyses. While the methods developed in this work are applied to high-purity germanium p-type point contact detectors, they are broadly applicable to other detector technologies and can be used to improve signal processing in other rare event searches. More generally, …
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Comparison of Random Forests, Support Vector Machine and Artificial Neural Network Methods for Agriculture Land Cover Classification
… Vector Machines (SVM) and Artificial Neural Networks (ANN) can be applied in land cover classification. However, putting a machine learning categorization system in place is not easy, especially in the field of agricultural land classifications. Very limited research can be found using the …
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Extracting room acoustic parameters from received speech signals using artificial neural networks
… in-situ measurements. A set of artificial neural networks, associated pre-processors and machine learning regimes are developed to extract Reverberation Time (RT), Early Decay Time (EDT) and Speech Transmission Index (STI) from received speech signals. Utilising naturalistic sounds - speech - as …
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A study on the relationship between personality type, sense of humor and creativity
… sense of humor style. Artificial Neural Network methods were employed to further map inputs of humor style and personality type to creativity. The thinking personality subtype was found to have greatest impact on creative achievement, though affiliative humor style also was noted as the …
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Application of neural networks techniques to military pharmaceutical ordering problems
… method of data mining is the use of neural networks. Neural networks have the ability to learn inventory needs based on past situations which are expected to occur again. Using neural networks to data mine government pharmaceutical supply necessities will enable the reduction of inventory …
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The Internet of things applied to command and control networks
… has the ability to transform any organizations network capabilities. The Air Force has a unique set of requirements centered on cyberspace superiority and the ability to command and control people and things. This paper leverages the traditional systems engineering "'V" model as a framework to …
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Beyond the Sum: A Network Analysis of Adverse Childhood Experiences and Behavioral Outcomes in Justice-Involved Youth
… (ACEs) among justice-involved youth using network analysis. Despite experiencing higher rates of childhood adversity, female youth show lower recidivism rates than males, presenting an empirical paradox. Using a sample of 19,454 justice-involved youth (75% male), this study applies novel …
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The broader social network of community planning: a diagnostic tool for communities to assess their planning capacity
… examined the relationship between social networks of a community and its planning capacity. Nine common patterns (traits) of effective planning efforts were identified and aligned with social network methods. This provided the framework from which to develop a tool determining the ability …
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An analysis of international transportation network
This thesis discusses a network design problem based on a case study with a footwear company, which intends to minimize total supply chain costs by establishing a distribution network which bypasses its primary distribution center (DC). Through the new network, called the DC bypass network, the …
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The Effects of Caching on Reconfigurable Adaptive Computing Systems
… the reconfiguration process is slow. Therefore, methods of decreasing reconfiguration time are desirable. Another method of implementing large algorithms on small hardware is to use multiple configurable computing platforms connected via a communication network. RTR techniques can be used in …
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Altered Brain Networks In Patients with Psychogenic Non-Epileptic Seizures (PNES) Using Ultra High Field MRI
… of PNES by helping better understand brain networks in patients with PNES. This study examines brain networks in patients with PNES with a focus on the default mode network and salience network. Methods: Twelve patients with PNES between the ages of 18-56 and twelve age- and sex- matched …
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Dataset and Evaluation of Self-Supervised Learning for Panoramic Depth Estimation
… is self driving cars. Currently, the best methods for depth detection are either very expensive, like LIDAR, or require precise calibration, like stereo cameras. These costs have given rise to attempts to detect depth from a monocular camera (a single camera). While this is possible, it is …
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Nearest neighbor search for cyro-electron microscopy images
… locality sensitive hashing (LSH) and some neural network methods are taken into consideration. The LSH method maps similar items into the same cell in a hash table, which effectively shortens the query time of searching for k-nearest neighbors, while the neural network methods are able to capture …
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Exploring Definitional Power in the Digital Age: A Case Study of Right to be Forgotten Framing
… is a recently codified yet controversial network privacy concept: the Right to be Forgotten (RTBF). I use a research framework informed by concepts of media and symbolic power, as well as Hall’s ‘primary definers’ thesis. I employ a necessarily mixed methods approach, which has allowed me …
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Valuing energy storage in electricity grids : a machine learning approach
… this thesis, state-of-the-art Machine Learning methods in the field of electricity price forecasting were used to accurately predict electricity prices. An improvement on existing recurrent neural network methods was introduced, using contextual knowledge of nodal prices and information such as …
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