Using Gleaned Computing Power To Forecast Emerging-Market Equity Returns With Machine Learning, Xida Ren
Undergraduate Honors Theses
This paper examines developing machine learning and statistic models to build forecast models for equity returns in an emergent market, with an emphasis on computing. Distributed systems were pared with random search and Bayesian optimization to find good hyperparameters for neural networks. No significant results were found.
Advances In Design Methodology In Swelling Shale Rock In Southern Ontario, 2019 The University of Western Ontario
Advances In Design Methodology In Swelling Shale Rock In Southern Ontario, Thomas R.A. Lardner
Electronic Thesis and Dissertation Repository
As infrastructure requirements increase in southern Ontario, excavations within swelling rock formations will become more frequent and larger. The objective of this study is to advance design capability for structures in swelling rock through three aspects: i) developing a practical swelling model for design engineers, ii) investigate two crushable/compressible materials for the mitigation of swelling rock effects, and iii) observe and analyze the behaviour of swelling rock to current excavation techniques.
A swelling rock constitutive model has been developed. The swelling parameters include the horizontal and vertical free swell potential, threshold stress, and critical stress as well as a ...
A Multiline Anchor Concept For Floating Offshore Wind Turbines, 2019 University of Massachusetts Amherst
A Multiline Anchor Concept For Floating Offshore Wind Turbines, Casey Fontana
Floating offshore wind turbines (FOWTs) hold great potential for the renewable energy industry, but capital costs remain high. In efforts to increase FOWT substructure efficiency and reduce costs, this thesis investigates a novel multiline anchor concept in which FOWTs share anchors instead of being moored separately. The goal of this thesis is to evaluate the force dynamics, design, and potential cost reduction of the system. Anchor forces are simulated using the NREL 5 MW reference turbine and OC4-DeepCwind semisubmersible platform, and multiline anchor force is computed as the vector sum of the contributing mooring line tensions.
The use of a ...
Recipe For Disaster, 2019 University of New Mexico
Recipe For Disaster, Zac Travis
MFA Thesis Exhibit Catalogs
Today’s rapid advances in algorithmic processes are creating and generating predictions through common applications, including speech recognition, natural language (text) generation, search engine prediction, social media personalization, and product recommendations. These algorithmic processes rapidly sort through streams of computational calculations and personal digital footprints to predict, make decisions, translate, and attempt to mimic human cognitive function as closely as possible. This is known as machine learning.
The project Recipe for Disaster was developed by exploring automation in technology, specifically through the use of machine learning and recurrent neural networks. These algorithmic models feed on large amounts of data as ...
Modern Yard Sale Application, 2019 California Polytechnic State University, San Luis Obispo
Modern Yard Sale Application, Lauren Epling, Matthew Piasecki
Computer Science and Software Engineering
YardSail is a modern application that provides users a place to post and view local Yard Sales. There is an astounding need for a safe space where users can comfortably post their yard sale address and items for all locals to easily see (without needing to drive down a specific street to find out). Currently, there does not exist an application for users that accomplishes what we set out to accomplish. As a team, we truly believe YardSail could be a popular application that helps users sail through the experience of hosting or visiting a yard sale.
Chip-Off Success Rate Analysis Comparing Temperature And Chip Type, 2019 St George Police Department
Chip-Off Success Rate Analysis Comparing Temperature And Chip Type, Choli Ence, Joan Runs Through, Gary D. Cantrell
Journal of Digital Forensics, Security and Law
Throughout the digital forensic community, chip-off analysis provides examiners with a technique to obtain a physical acquisition from locked or damaged digital device. Thermal based chip-analysis relies upon the application of heat to remove the flash memory chip from the circuit board. Occasionally, a flash memory chip fails to successfully read despite following similar protocols as other flash memory chips. Previous research found the application of high temperatures increased the number of bit errors present in the flash memory chip. The purpose of this study is to analyze data collected from chip-off analyses to determine if a statistical difference exists ...
Context-Aware Personalized Point-Of-Interest Recommendation System, 2019 Florida International University
Context-Aware Personalized Point-Of-Interest Recommendation System, Ramesh Raj Baral
FIU Electronic Theses and Dissertations
The increasing volume of information has created overwhelming challenges to extract the relevant items manually. Fortunately, the online systems, such as e-commerce (e.g., Amazon), location-based social networks (LBSNs) (e.g., Facebook) among many others have the ability to track end users' browsing and consumption experiences. Such explicit experiences (e.g., ratings) and many implicit contexts (e.g., social, spatial, temporal, and categorical) are useful in preference elicitation and recommendation. As an emerging branch of information filtering, the recommendation systems are already popular in many domains, such as movies (e.g., YouTube), music (e.g., Pandora), and Point-of-Interest (POI) (e ...
A Framework For Evaluating Model-Driven Self-Adaptive Software Systems, 2019 Technological University Dublin
A Framework For Evaluating Model-Driven Self-Adaptive Software Systems, Basel Magableh
In the last few years, Model Driven Development (MDD), Component-based Software Development (CBSD), and context-oriented software have become interesting alternatives for the design and construction of self-adaptive software systems. In general, the ultimate goal of these technologies is to be able to reduce development costs and effort, while improving the modularity, flexibility, adaptability, and reliability of software systems. An analysis of these technologies shows them all to include the principle of the separation of concerns, and their further integration is a key factor to obtaining high-quality and self-adaptable software systems. Each technology identifies different concerns and deals with them separately ...
A Deep Recurrent Q Network Towards Self-Adapting Distributed Microservices Architecture (In Press), 2019 Technological University Dublin
A Deep Recurrent Q Network Towards Self-Adapting Distributed Microservices Architecture (In Press), Basel Magableh
One desired aspect of microservices architecture is the ability to self-adapt its own architecture and behaviour in response to changes in the operational environment. To achieve the desired high levels of self-adaptability, this research implements the distributed microservices architectures model, as informed by the MAPE-K model. The proposed architecture employs a multi adaptation agents supported by a centralised controller, that can observe the environment and execute a suitable adaptation action. The adaptation planning is managed by a deep recurrent Q-network (DRQN). It is argued that such integration between DRQN and MDP agents in a MAPE-K model offers distributed microservice architecture ...
Context Oriented Software Middleware, 2019 Technological University Dublin
Context Oriented Software Middleware, Basel Magableh
This article proposes a new paradigm for building an adaptive middleware that supports software systems with self-adaptability and dependability. In this article, we wish to explore how far we can support the engineering of self- adaptive applications using a generic and platform-independent middleware architecture provided by non-specialised programming languages such as Context-Oriented Programming (COP), and Aspect-Oriented Programming (AOP), and not limited to a specific platform or framework. This gives the software developers the flexibility to construct a self-adaptive application using a generic and reusable middleware components that employ popular design patterns, instead of forcing the software developers to use a ...
Deep Q Learning For Self Adaptive Distributed Microservices Architecture (In Press), 2019 Technological University Dublin
Deep Q Learning For Self Adaptive Distributed Microservices Architecture (In Press), Basel Magableh
One desired aspect of a self-adapting microservices architecture is the ability to continuously monitor the operational environment, detect and observe anomalous behavior, and provide a reasonable policy for self-scaling, self-healing, and self-tuning the computational resources in order to dynamically respond to a sudden change in its operational environment. The behaviour of a microservices architecture is continuously changing overtime, which makes it a challenging task to use a statistical model to identify both the normal and abnormal behaviour of the services running. The performance of the microservices cluster could fluctuate around the demand to accommodate scalability, orchestration and load balancing demands ...
Experimental And Numerical Simulation Of Split Hopkinson Pressure Bar Test On Borosilicate Glass, 2019 Michigan Technological University
Experimental And Numerical Simulation Of Split Hopkinson Pressure Bar Test On Borosilicate Glass, Mayank K. Bagaria
Dissertations, Master's Theses and Master's Reports
This study is an extension to the design of ceramic materials component exposed to bullet impact. Owing to the brittle nature of ceramics upon bullet impact, shattered pieces behave as pellets flying with different velocities and directions, damaging surrounding components. Testing to study the behavior of ceramics under ballistic impact can be cumbersome and expensive. Modeling the set-up through Finite Element Analysis (FEA) makes it economical and easy to optimize. However, appropriately incorporating the material in modeling makes laboratory testing essential. Previous efforts have concentrated on simulating crack pattern developed during 0.22 caliber pellet impact on Borosilicate glass. A ...
Integrated Computational Materials Engineering (Icme) Investigation Of Electrical Conductivity And Thermodynamic Stability For Precipitation Strengthened Al-Zn-Zr And Al-Zn-Ni Ternary Alloys, 2019 Michigan Technological University
Integrated Computational Materials Engineering (Icme) Investigation Of Electrical Conductivity And Thermodynamic Stability For Precipitation Strengthened Al-Zn-Zr And Al-Zn-Ni Ternary Alloys, Oladeji Fadayomi
Dissertations, Master's Theses and Master's Reports
High electrical conductivity Al-Zn-TM (TM=Transition metals) alloys with improved mechanical properties and thermal resistance are developed with an integrated computational material engineering (ICME) strategy. From a series of ab initio density functional theory (DFT) simulations assessing combinations of ternary alloys, Al-Zn-Ni and Al-Zn-Zr are determined as alloys with relatively high electrical conductivity compared to several other ternary Al alloy combinations. The zero-temperature stable structure of precipitates formed in these alloys are determined from computed enthalpy of formation as L12, with particular focus of examining the influence of Zn on stabilizing the desired L12 precipitate phase.
Scanning transmission ...
On Learning And Visualizing Lexicographic Preference Trees, 2019 University of North Florida
On Learning And Visualizing Lexicographic Preference Trees, Ahmed S. Moussa
UNF Graduate Theses and Dissertations
Preferences are very important in research fields such as decision making, recommendersystemsandmarketing. The focus of this thesis is on preferences over combinatorial domains, which are domains of objects configured with categorical attributes. For example, the domain of cars includes car objects that are constructed withvaluesforattributes, such as ‘make’, ‘year’, ‘model’, ‘color’, ‘body type’ and ‘transmission’.Different values can instantiate an attribute. For instance, values for attribute ‘make’canbeHonda, Toyota, Tesla or BMW, and attribute ‘transmission’ can haveautomaticormanual. To this end,thisthesis studiesproblemsonpreference visualization and learning for lexicographic preference trees, graphical preference models that often are compact over complex domains of ...
Fast, Sparse Matrix Factorization And Matrix Algebra Via Random Sampling For Integral Equation Formulations In Electromagnetics, Owen Tanner Wilkerson
Theses and Dissertations--Electrical and Computer Engineering
Many systems designed by electrical & computer engineers rely on electromagnetic (EM) signals to transmit, receive, and extract either information or energy. In many cases, these systems are large and complex. Their accurate, cost-effective design requires high-fidelity computer modeling of the underlying EM field/material interaction problem in order to find a design with acceptable system performance. This modeling is accomplished by projecting the governing Maxwell equations onto finite dimensional subspaces, which results in a large matrix equation representation (Zx = b) of the EM problem. In the case of integral equation-based formulations of EM problems, the M-by-N system matrix, Z, is generally dense. For this reason, when treating large problems, it is necessary to use compression methods to store and manipulate Z. One such sparse representation is provided by so-called H^2 matrices. At low-to-moderate frequencies, H^2 matrices provide a controllably accurate data-sparse representation of Z.
The scale at which problems in EM are considered ``large'' is continuously being redefined to be larger. This growth of problem scale is not only happening in EM, but respectively across all other sub-fields of computational science as well. The pursuit of increasingly large problems is unwavering in all these sub-fields, and this drive has long outpaced the rate of advancements in processing and storage capabilities in computing. This has caused computational science communities to now face the computational limitations of standard linear algebraic methods that have been relied upon for decades to run quickly and efficiently on modern computing hardware. This common set of algorithms can only produce reliable results quickly and efficiently for small to mid-sized matrices that fit into the memory of the host computer. Therefore, the drive to pursue larger problems has even began to outpace the reasonable capabilities of these common numerical algorithms; the deterministic numerical linear algebra algorithms that have gotten matrix computation this far have proven to be inadequate for many problems of current interest. This has computational science communities focusing on improvements in their mathematical and software approaches in order to push further advancement. Randomized numerical linear algebra (RandNLA) is an emerging area that both academia and industry believe to be strong candidates to assist in overcoming the limitations faced when solving massive and computationally expensive problems.
This thesis presents results of recent work that uses a random sampling method (RSM) to implement algebraic operations ...
Approximate Analytical Solution For Mathematical Models Of Thermal Ignition And Non-Isothermal Catalytic Zero Order Reaction In A Spherical Geometry, 2019 The British University in Egypt
Approximate Analytical Solution For Mathematical Models Of Thermal Ignition And Non-Isothermal Catalytic Zero Order Reaction In A Spherical Geometry, Moustafa A. Soliman
In this paper an approximate analytical solution for the Frank-Kamenetskii equation modeling thermal ignition without the depletion of the combustibles in a spherical annulus and non-isothermal zero order reaction in spherical catalyst particle is presented. The approximate solution is compared with the numerical solution and is in good agreement with the numerical solution. The approximate solution obtained is valid for all values of the distance parameter. Multiple solutions occur for some range of Frank-Kamenetskii parameter (λ). The multiplicity is infinite for the case of a solid sphere and λ=2.Interesting relation is obtained for λ at the turning points ...
Approximate Solution For The Lane-Emden Equation Of The Second Kind In A Spherical Annulus, 2019 The British University in Egypt
Approximate Solution For The Lane-Emden Equation Of The Second Kind In A Spherical Annulus, Moustafa A. Soliman
In this paper, we derive accurate approximate solution of Lane-Emden equation of the second kind in a spherical annulus geometry. The approximate solution is obtained by analytic arguments, and perturbation methods in terms of small and large radial distance parameter. The approximate solution is compared with the numerical solution. The approximate solution obtained is valid for all values of the radial distance parameter. Our best approximation has a maximum relative error in the dependent variable of 20%. In most cases it is much less than this value. This maximum error decreases as the radius of the annulus increases.
Solar+ Microgrid Costs At Gas Station And Convenience Stores In The State Of California, 2019 Humboldt State University
Solar+ Microgrid Costs At Gas Station And Convenience Stores In The State Of California, Thalia Quinn
HSU theses and projects
This project estimates the capital costs for Solar+ microgrids for the year 2018 and forecasted out to 2030. Solar+ systems include the use of battery energy storage, solar energy, electric vehicle chargers and control systems to manage energy consumption and generation for a single building and provide islanded “microgrid” features. The capital cost includes estimates for the components: DER technologies (battery, solar PV and EV charging stations), controls (programming and hardware), and integration costs (switchgear, engineering, permitting and site work). Methods used to estimate each cost included assessing historical and projected costs for each of the components.
Five Solar+ scenarios ...
Adhesion At Solid/Liquid Interfaces, 2019 Virginia Commonwealth University
Adhesion At Solid/Liquid Interfaces, Neda Ojaghlou
Theses and Dissertations
The adhesion at solid/liquid interface plays a fundamental role in diverse fields and helps explain the structure and physical properties of interfaces, at the atomic scale, for example in catalysis, crystal growth, lubrication, electrochemistry, colloidal system, and in many biological reactions. Unraveling the atomic structure at the solid/liquid interface is, therefore, one of the major challenges facing the surface science today to understand the physical processes in the phenomena such as surface coating, self-cleaning, and oil recovery applications. In this thesis, a variety of theory/computational methods in statistical physics and statistical mechanics are used to improve understanding ...
Mechanochemical Regulation Of Epithelial Tissue Remodeling: A Multiscale Computational Model Of The Epithelial-Mesenchymal Transition Program, 2019 Virginia Commonwealth University
Mechanochemical Regulation Of Epithelial Tissue Remodeling: A Multiscale Computational Model Of The Epithelial-Mesenchymal Transition Program, Lewis Scott
Theses and Dissertations
Epithelial-mesenchymal transition (EMT) regulates the cellular processes of migration, growth, and proliferation - as well as the collective cellular process of tissue remodeling - in response to mechanical and chemical stimuli in the cellular microenvironment. Cells of the epithelium form cell-cell junctions with adjacent cells to function as a barrier between the body and its environment. By distributing localized stress throughout the tissue, this mechanical coupling between cells maintains tensional homeostasis in epithelial tissue structures and provides positional information for regulating cellular processes. Whereas in vitro and in vivo models fail to capture the complex interconnectedness of EMT-associated signaling networks, previous computational ...