Engineering Commons^™

Receptive Fields Optimization In Deep Learning For Enhanced Interpretability, Diversity, And Resource Efficiency., Babajide Odunitan Ayinde

Electronic Theses and Dissertations

In both supervised and unsupervised learning settings, deep neural networks (DNNs) are known to perform hierarchical and discriminative representation of data. They are capable of automatically extracting excellent hierarchy of features from raw data without the need for manual feature engineering. Over the past few years, the general trend has been that DNNs have grown deeper and larger, amounting to huge number of final parameters and highly nonlinear cascade of features, thus improving the flexibility and accuracy of resulting models. In order to account for the scale, diversity and the difficulty of data DNNs learn from, the architectural complexity and …

University Of Rhode Island Course Information Assistant, Daniel Gauthier

Senior Honors Projects

Personal voice-interactive systems have become ubiquitous in daily life. There are many of these digital assistants such as Siri, Alexa, and Google Assistant. The chances are high you have access to one right now. This technology has reached a point where the context of a conversation can be maintained, which is a vast improvement over earlier technology. Interactions without conversational context can limit interactions greatly and this was the case for previous digital assistants. Every time someone would say something to an assistant, it was like they were constantly changing operators on a customer service line. The assistants can now …

Forecasting Model For Disease Propensity Using Ehr Data, Soodabeh Sarafrazi, Omar Sharif, Matthew Domingo, Jie Han, Michael Chang, Omid Khazaie, Anil Kemisetti

Creative Activity and Research Day - CARD

Many diseases such as diabetes and cardiovascular diseases are actionable, i.e. they are preventable by early intervention. One to two years of early warning would represent a huge advance in dealing with these conditions and could help prevent further complications such as heart disease, stroke, kidney failure, blindness, and amputation. In this project, we are developing an extensible condition forecasting model to assess the risk of diabetes and heart problems in patients in advance. Using TensorFlow, Elastic MapReduce (EMR), and AWS Sagemaker, we are training a Wide and Deep Neural Network on a dataset of more than 170 million electronic …

Deep Learning, Medical Physics And Cargo Cult Science., Miguel Romero Phd, Gilmer Valdes Phd, Timothy Solberg Phd, Yannet Interian Phd

Creative Activity and Research Day - CARD

Deep learning algorithms have become widely popular, with considerable success in fields where datasets have hundreds of thousands or million points. As deep learning is increasingly applied to the fields of medical physics and radiation oncology, a reasonable question follows: are these techniques the best approach, given the unique conditions in our field? In this study, we investigate the dependence of dataset size on the performance of deep learning algorithms compared with more traditional radiomics-based methods.

Multi-Objective Bayesian Optimization Of Super Hydrophobic Coatings On Asphalt Concrete Surfaces, Ali Nahvi, Mohammad Kazem Sadoughi, Ali Arabzadeh, Alireza Sassani, Chao Hu, Halil Ceylan, Sunghwan Kim

Ali Nahvi

Conventional snow removal strategies add direct and indirect expenses to the economy through profit lost due to passenger delays costs, pavement durability issues, contaminating the water runoff, and so on. The use of superhydrophobic (super-water-repellent) coating methods is an alternative to conventional snow and ice removal practices for alleviating snow removal operations issues. As an integrated experimental and analytical study, this work focused on optimizing superhydrophobicity and skid resistance of hydrophobic coatings on asphalt concrete surfaces. A layer-by-layer (LBL) method was utilized for spray depositing polytetrafluoroethylene (PTFE) on an asphalt concrete at different spray times and variable dosages of PTFE. …

Using Principle Component Analysis To Analyze Tertiary And Quaternary Spectral Mixtures, David Burnett

Scholar Week 2016 - present

CRISM images from Mars are expected to contain carbonates such as magnesite. Prior research has been successfully able to determine the approximate percent composition of phyllosilicates in binary lab mixtures using Principle Component Analysis (PCA). In order to expand this model to work on CRISM images, one of preliminary steps is allowing the algorithm to work on mixtures with more than two components, which was the primary purpose of this research.

An Application Of Artificial General Intelligence In Board Games, Nathan Skalka

Computer Science Graduate Research Workshop

No abstract provided.

Underground Environment Aware Mimo Design Using Transmit And Receive Beamforming In Internet Of Underground Things, Abdul Salam

Faculty Publications

In underground (UG) multiple-input and multiple-output (MIMO), the transmit beamforming is used to focus energy in the desired direction. There are three different paths in the underground soil medium through which the waves propagates to reach at the receiver. When the UG receiver receives a desired data stream only from the desired path, then the UG MIMO channel becomes three path (lateral, direct, and reflected) interference channel. Accordingly, the capacity region of the UG MIMO three path interference channel and degrees of freedom (multiplexing gain of this MIMO channel requires careful modeling). Therefore, expressions are required derived the degrees of …

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 “pseudo-Poisson’s …

A Multiline Anchor Concept For Floating Offshore Wind Turbines, Casey Fontana

Doctoral Dissertations

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, 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 a …

Ordinary Differential Equation Neuralnetworks: Mathematics And Application Using Diffeqflux.Jl, Muhammad Moiz Saeed

Senior Capstone Theses

This paper has two objectives. 1. It simplifies the Mathematics behind a simple Neural Network. Furthermore, it explores how Neural Networks can be modeled using Ordinary Differential Equations(ODE). 2. It implements a simple example of an ODE Neural network using diffeqflux.jl library. My paper is based on the paper "Neural Ordinary Differential equations"[1] paper and contains multiple extracts from this paper and hence the work in chapter 4 should not be considered original work as it aims to explain the mathematics in the original paper and all credit is due to the authors of the paper [1]. This paper[1] was …

Space Defense: Creating A 2d Game With 3d Assets Using Unity Game Engine, Jeevan Vase

Computer Science and Software Engineering

The goal of this senior project was to learn and use the skills necessary for one person to make a complete game. The 3D assets that were used were downloaded from the Unity Store. I used Unity Game Engine to create the logic for the game. This document explains the technologies that I used, design choices I made, feedback from player-testing, and work that I want to complete for the project in the future. The final game demo features three levels, a start screen, and a combat system that allows players to gain additional ships to help defend their planet.

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, 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, 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.g., Yelp).

The POI domain has many …

A Framework For Evaluating Model-Driven Self-Adaptive Software Systems, Basel Magableh

Articles

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), Basel Magableh

Articles

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 …

Deep Q Learning For Self Adaptive Distributed Microservices Architecture (In Press), Basel Magableh

Articles

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. …

Context Oriented Software Middleware, Basel Magableh

Articles

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 …

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 major …

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 …

Immunity-Based Framework For Autonomous Flight In Gps-Challenged Environment, Mohanad Al Nuaimi

Graduate Theses, Dissertations, and Problem Reports

In this research, the artificial immune system (AIS) paradigm is used for the development of a conceptual framework for autonomous flight when vehicle position and velocity are not available from direct sources such as the global navigation satellite systems or external landmarks and systems. The AIS is expected to provide corrections of velocity and position estimations that are only based on the outputs of onboard inertial measurement units (IMU). The AIS comprises sets of artificial memory cells that simulate the function of memory T- and B-cells in the biological immune system of vertebrates. The innate immune system uses information about …

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 objects built of …

Content-Based Music Recommendation Using Deep Learning, Ryan Whitell

Regis University Student Publications (comprehensive collection)

Music streaming services use recommendation systems to improve the customer experience by generating favorable playlists and by fostering the discovery of new music. State of the art recommendation systems use both collaborative filtering and content-based recommendation methods. Collaborative filtering suffers from the cold start problem; it can only make recommendations for music for which it has enough user data, so content-based methods are preferred. Most current content-based recommendation systems use convolutional neural networks on the spectrograms of track audio. The architectures are commonly borrowed directly from the field of computer vision. It is shown in this study that musically-motivated convolutional …

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, …

Solar+ Microgrid Costs At Gas Station And Convenience Stores In The State Of California, Thalia Quinn

Cal Poly Humboldt 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 …

Foundations For A Game Theoretic Framework For Agile Acquisition, Scott Rosen, Kelly Horinek, Alexander Odeh, Les Servi, Andreas Tolk

VMASC Publications

This article investigates the concept of developing a game theoretic framework that is based on the application of buyer and seller utility functions to support the bidding process in government acquisition. The results of a literature survey of utility function approaches, with potential to provide a suitable foundation to a game theory framework for acquisition, are presented. The utility function methods found most promising were further adapted and tested: the Best-Worst method, the Multi-Swing Method, and Functional Dependency for Network Analysis. To test the scalability of the approach, the Best-Worst method is applied to a larger problem to show the …

Pawnee Dam Inflow Design Flood (Idf) Update And Stage-Frequency Curve Development Using Rmcrfa, Jennifer P. Christensen, Joshua J. Melliger

United States Geological Survey: Water Reports and Publications

Pawnee Dam is one of the ten Salt Creek Dams designed and built in the 1960s to mitigate flooding in Lincoln, Nebraska. This short paper illustrates the update of the Pawnee Dam inflow design flood (IDF) through calibration to recent high flow events and the development of its stage-frequency or hydrologic loading curve with the U.S. Army Corps of Engineers’ Risk Management Center Reservoir Frequency Analysis (RMC-RFA) model. The IDF update follows Engineering Regulation 1110-8-2, Inflow Design Flood for Dams and Reservoirs, including unit hydrograph peaking and two antecedent pool elevations. Background information on the original design of the dam …

Global Aviation System: Towards Sustainable Development, Marina P. Bonser Dr.

International Journal of Aviation, Aeronautics, and Aerospace

Aviation around the world has integrated into a global system. As the integration process continues, more aspects and levels of it need to be lead towards the sustainable development of the whole system via advancing strategic management, global communication proficiency, and technological expertise. It becomes essential to enrich global language (English) proficiency with cross-cultural communication competence not only for communication in the air but also for airport security, passenger and cargo services, aircraft and equipage engineering, building, and maintenance. Nowadays lower levels of management need more advanced strategic thinking and problem solving skills, and higher levels of management need global …