Digital Commons Network^™

Ugv Direction Control By Human Arm Gesture Recognition Via Deterministic Learning, Xiaotian Chen

Open Access Master's Theses

With the recent development of machine learning and neural networks, different applications have been developed to improve the intelligence of unmanned robotic systems. In this thesis, we present a novel method for controlling an unmanned ground vehicle (UGV) by using a new machine learning technique, called deterministic learning [1], to learn and recognize four specifically designed body language, which represent four corresponding moving directions (i.e., left, right, up, and down) of the controlled UGV. The Microsoft Kinect sensor is employed to collect the human body skeleton data, including (x, y, z) coordinates of the human arm …

Design And Performance Analysis Of A Programmable Near Field Communication Antenna On Soft Materials, Muhammad Enayetur Rahman

Open Access Master's Theses

In the era of ubiquitous computing objects connected to the Internet are increasing day by day. Near Field Communication (NFC) is a perfect example of ubiquitous computing that is secure, short-range, low powered contactless communication. Powerless, single-tapping NFC tag is growing in popularity. Massive demand for NFC requires to study implementing this fast-growing technology onto different materials and places.

In this research study, NFC implementation on flexible material is investigated with different types of materials. NFC antennas were designed with mathematical modeling. Simulation for NFC coil inductance calculation was performed and was verified with mathematical modeling. The NFC antenna was …

Effects Of Incorporating Inertial Measurements On The Localization Accuracy Of The Seaglider Auv, Wendy Snyder

Open Access Master's Theses

The Kongsberg Seaglider M1 is a commercially available autonomous under- water vehicle (AUV) primarily used as a platform for oceanographic measurements of salinity, temperature, and oxygen. The Seaglider currently uses two different dead-reckoned solutions, the glide slope model (GSM) and the hydrodynamic model (HDM), to provide a localization solution for each dive. While the accuracy of these solutions was not previously known explicitly, for the purposes of oceanographic profiling they were generally deemed sufficient. As the platform matures, there has been a growing interest in expanding its application and measurement capabilities. With some of the desired new applications, such as …

All-Solid Lithium-Ion Batteries For High Safety And Stability, Lukas Duwe

Open Access Master's Theses

Operational safety and cycle stability are important attributes for all rechargeable batteries. To meet these stringent demands specifically for biomedical applications, an all-solid lithium-ion battery (ASLIB) consisting of a polyethylene oxide\ (PEO)-based polymer electrolyte with a lithium bis(trifluoromethanesulfonyl) imide (LiTFSI) salt, lithium titanate (LTO) anode and lithium iron phosphate (LFP) cathode is proposed. This work implements fabrication methods, composition optimizations and an assembly procedure, all tailored to the unique cell chemistry and ending in the all-solid LTO-PEO/LiTFSI-LFP cells. Subsequently, these ASLIBs are tested close to body temperature at 40 °C. This assures solid-state, but augments bulk electrolyte and interfacial resistance …

System Modeling Of A Lithium-Ion Battery, Tyler Creighton

Open Access Master's Theses

Lithium Ion Batteries are widely used in today's portable world. A working model is required in order to safely maximize the output of these batteries, and to efficiently choose appropriate sized systems for any given application. A model of this battery would require parameters that are not easy to measure, and need to be estimated. This work further explored on one existing model for the lithium ion battery, the linear dynamics single particle model, and improved upon it. Data was collected then modeled through the use of several matlab functions, and the final model was then used to predict the …

Online Symptom Checker Diagnostic And Triage Accuracy For Hiv And Hepatitis C, A. C. Berry, B. D. Cash, B. Wang, M. S. Mulekar, A. B. Van Haneghan, Kyle Yuquimpo, A. Swaney, M. C. Marshall, W. K. Green

Student Publications

We sought to address the prior limitations of symptom checker accuracy by analysing the diagnostic and triage feasibility of online symptom checkers using a consecutive series of real-life emergency department (ED) patient encounters, and addressing a complex patient population - those with hepatitis C or HIV. We aimed to study the diagnostic and triage accuracy of these symptom checkers in relation to an emergency room physician-determined diagnosis. An ED retrospective analysis was performed on 8363 consecutive adult patients. Eligible patients included: 90 HIV, 67 hepatitis C, 11 both HIV and hepatitis C. Five online symptom checkers were utilised for diagnosis …

How Blockchain Could Increase The Need For And Availability Of Contractual Ordering For Companies And Their Investors, Carol R. Goforth

North Dakota Law Review

No abstract provided.

Solid Spherical Energy (Sse) Cnns For Efficient 3d Medical Image Analysis, Vincent Andrearczyk, Valentin Oreiller, Julien Fageot, Xavier Montet, Adrien Depeursinge

Session 2: Deep Learning for Computer Vision

Invariance to local rotation, to differentiate from the global rotation of images and objects, is required in various texture analysis problems. It has led to several breakthrough methods such as local binary patterns, maximum response and steerable filterbanks. In particular, textures in medical images often exhibit local structures at arbitrary orientations. Locally Rotation Invariant (LRI) Convolutional Neural Networks (CNN) were recently proposed using 3D steerable filters to combine LRI with Directional Sensitivity (DS). The steerability avoids the expensive cost of convolutions with rotated kernels and comes with a parametric representation that results in a drastic reduction of the number of …

Deep Convolutional Neural Networks For Estimating Lens Distortion Parameters, Sebastian Lutz, Mark Davey, Aljosa Smolic

Session 2: Deep Learning for Computer Vision

In this paper we present a convolutional neural network (CNN) to predict multiple lens distortion parameters from a single input image. Unlike other methods, our network is suitable to create high resolution output as it directly estimates the parameters from the image which then can be used to rectify even very high resolution input images. As our method it is fully automatic, it is suitable for both casual creatives and professional artists. Our results show that our network accurately predicts the lens distortion parameters of high resolution images and corrects the distortions satisfactory.

Multi-Person Tracking By Multi-Scale Detection In Basketball Scenarios, Adria Arbués-Sanguesa, Gloria Haro, Coloma Ballester

Session 1: Active Vision, Tracking, Motion Analysis

Tracking data is a powerful tool for basketball teams in order to extract advanced semantic information and statistics that might lead to a performance boost. However, multi-person tracking is a challenging task to solve in single-camera video sequences, given the frequent occlusions and cluttering that occur in a restricted scenario. In this paper, a novel multi-scale detection method is presented, which is later used to extract geometric and content features, resulting in a multi-person video tracking system. Having built a dataset from scratch together with its ground truth (more than 10k bounding boxes), standard metrics are evaluated, obtaining notable results …

A Decade Of Disability Depictions In Newbery Award Books, H. Grow, Sharon Black, K. Egan, Tina Taylor, K. Moss, Rachel L. Wadham, Mary Anne Prater

Faculty Publications

Newbery awards are conferred annually on books recognized as having made the most distinguished contribution to children’s literature; these books reach a wide audience, and their depictions of characters with disabilities can influence children's perceptions and attitudes toward individuals with disabilities. Eight Newbery Medal and Honor books chosen from 2010 to 2019 were identified as portraying 11 main or supporting characters with a disability. Six disabilities were represented: emotional disturbance, deafness, specific learning disability, speech/language impairment, orthopedic impairment, and traumatic brain injury. Applying the Rating Scale for Quality Characterizations of Individuals with Disabilities in Children’s Literature, we found most of …

On-Road Remote Sensing Of Automobile Emissions In The Chicago Area: Fall 2018, Gary A. Bishop

Fuel Efficiency Automobile Test Publications

No abstract provided.

Rethinking Global-Regulation: World’S Law Meets Artificial Intelligence, Nachshon Sean Goltz, Addison Cameron-Huff, Giulia Dondoli

Research outputs 2014 to 2021

This article takes a critical look at Machine Translation of legal text, especially global legislation, through the discussion of Global-Regulation, a state of the art online search engine of the world’s legislation in English. Part 2 explains the rationale for an online platform such as Global-Regulation. Part 3 provides a brief account of the history of the development of machine translation, and it describes some of the limits of the use of statistical machine translation for translating legal texts. Part 4 describes Neural Machine Translation (NMT), which is a new generation of machine translation systems. Finally, Parts 5 and 6 …

Fake News And Propaganda: Trump’S Democratic America And Hitler’S National Socialist (Nazi) Germany, David E. Allen, Michael Mcaleer

Research outputs 2014 to 2021

This paper features an analysis of President Trump’s two State of the Union addresses, which are analysed by means of various data mining techniques, including sentiment analysis. The intention is to explore the contents and sentiments of the messages contained, the degree to which they differ, and their potential implications for the national mood and state of the economy. We also apply Zipf and Mandelbrot’s power law to assess the degree to which they differ from common language patterns. To provide a contrast and some parallel context, analyses are also undertaken of President Obama’s last State of the Union address …

Entropy Analysis Of High-Definition Transcranial Electric Stimulation Effects On Eeg Dynamics, Diego C. Nascimento, Gabriela Depetri, Luiz H. Stefano, Osvaldo Anacleto, Joao P. Leite, Dylan J. Edwards, Taiza E. G. Santos, Francisco Louzada Neto

Research outputs 2014 to 2021

A foundation of medical research is time series analysis—the behavior of variables of interest with respect to time. Time series data are often analyzed using the mean, with statistical tests applied to mean differences, and has the assumption that data are stationary. Although widely practiced, this method has limitations. Here we present an alternative statistical approach with sample analysis that provides a summary statistic accounting for the non-stationary nature of time series data. This work discusses the use of entropy as a measurement of the complexity of time series, in the context of Neuroscience, due to the non-stationary characteristic of …

Optimal Allocation Of Distributed Energy Storage Systems To Improve Performance And Power Quality Of Distribution Networks, Choton K. Das, Octavian Bass, Thair S. Mahmoud, Ganesh Kothapalli, Navid Mousavi, Daryoush Habibi, Mohammad A.S. Masoum

Research outputs 2014 to 2021

The placement of grid-scale energy storage systems (ESSs) can have a significant impact on the level of performance improvements of distribution networks. This paper proposes a strategy for optimal allocation of distributed ESSs in distribution networks to simultaneously minimize voltage deviation, flickers, power losses, and line loading. The optimal ESS allocation is investigated through the PQ injection (considering a variable power factor on the dispatch of ESSs) and the results are compared in terms of performance and power quality improvements. An IEEE-33 bus distribution system (medium voltage), having a high influence of renewable (wind and solar) distributed generation, is used …

A Simheuristic Approach For Evolving Agent Behaviour In The Exploration For Novel Combat Tactics, Chiou-Peng Lam, Martin Masek, Luke Kelly, Michael Papasimeon, Lyndon Benke

Research outputs 2014 to 2021

The automatic generation of behavioural models for intelligent agents in military simulation and experimentation remains a challenge. Genetic Algorithms are a global optimization approach which is suitable for addressing complex problems where locating the global optimum is a difficult task. Unlike traditional optimisation techniques such as hill-climbing or derivatives-based methods, Genetic Algorithms are robust for addressing highly multi-modal and discontinuous search landscapes. In this paper, we outline a simheuristic GA-based approach for automatic generation of finite state machine based behavioural models of intelligent agents, where the aim is the identification of novel combat tactics. Rather than evolving states, the proposed …

Surficial And Deep Earth Material Prediction From Geochemical Compositions, Hassan Talebi, Ute Mueller, Raimon Tolosana-Delgado, Eric C. Grunsky, Jennifer M. Mckinley, Patrice De Caritat

Research outputs 2014 to 2021

Prediction of true classes of surficial and deep earth materials using multivariate spatial data is a common challenge for geoscience modelers. Most geological processes leave a footprint that can be explored by geochemical data analysis. These footprints are normally complex statistical and spatial patterns buried deep in the high-dimensional compositional space. This paper proposes a spatial predictive model for classification of surficial and deep earth materials derived from the geochemical composition of surface regolith. The model is based on a combination of geostatistical simulation and machine learning approaches. A random forest predictive model is trained, and features are ranked based …

Geographical Variations In Prostate Cancer Outcomes: A Systematic Review Of International Evidence, Paramita Dasgupta, Peter D. Baade, Joanne F. Aitken, Nicholas Ralph, Suzanne K. Chambers, Jeff Dunn

Research outputs 2014 to 2021

Background: Previous reviews of geographical disparities in the prostate cancer continuum from diagnosis to mortality have identified a consistent pattern of poorer outcomes with increasing residential disadvantage and for rural residents. However, there are no contemporary, systematic reviews summarizing the latest available evidence. Our objective was to systematically review the published international evidence for geographical variations in prostate cancer indicators by residential rurality and disadvantage.

Methods: Systematic searches of peer-reviewed articles in English published from 1/1/1998 to 30/06/2018 using PubMed, EMBASE, CINAHL, and Informit databases. Inclusion criteria were: population was adult prostate cancer patients; outcome measure was PSA testing, prostate …

Using Local Rural Knowledge To Enhance Stem Learning For Gifted And Talented Students In Australia, Julia Morris, Eileen Slater, Michael T. Fitzgerald, Geoffrey W. Lummis, Eddie Van Etten

Research outputs 2014 to 2021

In order to supply a future Science, Technology, Engineering, and Mathematics (STEM) workforce, Australia needs to engage its most capable and gifted secondary students in quality STEM learning, either within school or through extra-curricular opportunities, so that they will continue into STEM-based tertiary degrees. High-achieving students in rural communities may face additional barriers to STEM learning that can limit their ability to pursue advanced STEM studies and occupations. This small-scale research project sought to explore a group of gifted lower secondary students’ engagement and experiences in a STEM programme designed around a local rural knowledge model as reported by Avery …

Facial Identification For Digital Forensic, Hiba Al-Kawaz

School of Engineering, Computing and Mathematics Theses

Forensic facial recognition has become an essential requirement in criminal investigations as a result of the emergence of electronic devices, such as mobile phones and computers, and the huge volume of existing content. Forensic facial recognition goes beyond facial recognition in that it deals with facial images under unconstrained and non-ideal conditions, such as low image resolution, varying facial orientation, poor illumination, a wide range of facial expressions, and the presence of accessories. In addition, digital forensic challenges do not only concern identifying an individual but also include understanding the context, acknowledging the relationships between individuals, tracking, and numbers of …

Modelling Of Fatigue Crack Closure Via The Concept Of Plastic Inclusions, Ebtesam Alousta

School of Engineering, Computing and Mathematics Theses

The phenomenon of closure is one of the most important phenomena that have been linked to the deeper understanding of fatigue cracks. Various methods have been employed to model the plastic zone around the crack tip which appears to give rise to the closure phenomena. In this thesis, our goal is to model the plastic region near the crack tip by using a suitable adaptation of an Eshelby inclusion. To do this, the first task is to translate Eshelby’s solution in terms of Muskhelishvili’s complex potential functions for 2D elasticity and then solve these equations for a suitable shape of …

Computational Study Of Neuronal Oscillations In Motor Control Circuits, Andrea Ferrario

School of Engineering, Computing and Mathematics Theses

In this thesis we used mathematical and computational models to study neuronal net- works that control motor behaviours. Specifically, we modelled two neuronal circuits from two opposite ends of the brain complexity spectrum: the swimming circuit of the hatchling Xenopus tadpole and the human basal ganglia. Due to its relative simplicity, tadpole is a unique animal for studying locomotion us- ing both experiments and models. This allowed us to define three biologically-realistic spiking models to clarify the interplay between the architecture of synaptic connections (structure) and the network’s ability to generate activities that correspond to its swim- ming behaviour (function). …

Motivation To Conduct Research In A Rapidly Evolving Academic Environment: A Study Of Coimbatore’S Engineering Institutions, Venkat Prakash Bakthavatchaalam

School of Engineering, Computing and Mathematics Theses

The Indian academic system is in a period of rapid transition evidenced by the increasing number of Higher Education Institutions (HEIs), students and academics. However, very few studies have explored the Research Productivity (RP) of the academics and the various factors influencing them. Even those few studies have largely ignored the influences of indigenous factors and academic dishonesty on the RP of academics. This research explores how different factors influence the academic RP in South Indian engineering institutions founded after 1990. This study uses a mixed method approach. Quantitative data was collected from a sample of 307 engineering academics working …

Predicting Quality Attributes And Waste Of Strawberry Packed Under Modified Atmosphere Throughout The Cold Chain, Kompal Johsi, Brijesh Tiwari, Patrick J. Cullen, Jesus Maria Frias

Articles

Modified Atmosphere Packaging (MAP) is used commercially to extend the shelf life of strawberries. The attainment of desired gas (O2, CO2) concentrations inside MAP relies on the product respiration and the mass transfer through packaging and will affect the quality. The objective of this work is to build a mathematical model for strawberries to assess the effect of the uncertainties on headspace gas concentration and quality: 1) cold chain related temperature and relative humidity variations and 2) variability associated to product respiration and quality based on literature. Weight loss was more influenced by the cold chain storage conditions (temperature and …

Nuclear Frames In The Irish Media: Implications For Conversations On Nuclear Power Generation In The Age Of Climate Change, Catherine Devitt, Finbarr Brereton, Simon Mooney, David Conway, Eoin O'Neill

Articles

Keeping within the temperature limits set by the Paris Agreement on climate action will be a significant challenge. Nuclear power generation may contribute to achieving these targets, however, there are significant environmental, economic and health risks attached. Using qualitative and quantitative methods, this paper explores how nuclear power generation is framed in the Irish print media, and discusses the implications of these frames for how nuclear power is perceived within the context of climate change mitigation in Ireland. Two Irish broadsheet papers, the Irish Times and the Irish Independent were selected for data collection, focusing on Chernobyl and Fukushima incidents. …

Luminescent Calcium Carbonate Micro ‘Bow Ties’, Fearghal C. Donnelly, Finn Purcell-Milton, Peter W. Dunne, Aleksandra Rulikowska, Victor Alguacil, Yurii K. Gun’Ko

Articles

Calcium carbonate (CaCO3) is a ubiquitous material which has been studied for centuries due to its integral nature across various fields and its vast range of applications. Here we report, for the first time, a low temperature dry ice carbonation method for the production of unique rare earth-doped calcium carbonate ‘bow ties’. CaCO3 exhibits retrograde solubility, an interesting property in which its solubility increases with decreasing temperature. In this synthesis, dry ice acts not only as a CO2 source, but as a coolant, increasing the solubility of CaCO3 and CO2 and allowing specific growth to occur. The incorporation of trivalent …

Predicting Quality Attributes Of Strawberry Packed Under Modified Atmosphere Throughout The Cold Chain, Kompal Joshi, Brijesh Tiwari, P. J. Cullen, Jesus Maria Frias

Articles

Modified Atmosphere Packaging (MAP) is used commercially to extend the shelf life of strawberries. The attainment of desired gas (O2, CO2) concentrations inside MAP relies on the product respiration and the mass transfer through packaging and will affect the quality. The objective of this work is to build a mathematical model for strawberries to assess the effect of the uncertainties on headspace gas concentration and quality: 1) cold chain related temperature and relative humidity variations and 2) variability associated to product respiration and quality based on literature. Weight loss was more influenced by the cold chain storage conditions (temperature and …

Carbon Dioxide Measurement In Irish Blanket Peatlands: An Assessment Of Pool-Soil Flux Variability, Mariya Radomski, Alan Gilmer, Vivienne Byers, Eugene Mcgovern

Articles

Peatlands have been recognised as having a significant role in the mediation of atmospheric carbon dioxide (CO2) levels with direct implications for global climate change. Longitudinal in situ measurement systems for CO2 concentrations in blanket peatland ecosystems are difficult to implement where the nature of terrestrial–aquatic connectivity and hydrodynamics have a significant effect on the carbon cycle. The need for greater data on CO2 concentrations and flux monitoring in these settings has been well recognised. However, applying the most appropriate monitoring approach presents a special challenge. This paper sets out the development of a direct method for field based longitudinal …

Assessment Of Physicochemical Characteristics, Thermal Stability And Release Profile Of Ascorbic Acid Microcapsules Obtained By Complex Coacervation, Michele Cristina Rodrigues Da Cruz, João Luiz Andreotti Dagostin, Camila Augusto Perussello, Maria Lúcia Masson

Articles

The aim of this study was to determine the physicochemical characteristics, thermal stability and release profile of ascorbic acid (AA) microcapsules obtained by complex coacervation. Gelatin and gum arabic were used as wall materials in concentrations of 2.5, 5.0 and 7.5 g% (w/v). The coacervate microcapsules were freeze-dried and assessed for physicochemical characteristics, thermal behavior and stability during 60 days of storage. The release profile was evaluated at different pH values (1.1, 2.2, 5.4, 7.4, 9.6 and 12). The encapsulation efficiency ranged from 27.3 to 93.8%. The microcapsules of AA presented good characteristics for application in food matrices, such as …