Digital Commons Network^™

Design And Evaluation Of An Adventure Videogame Based In The History Of Mathematics, Mariana Rocha, Pierpaolo Dondio

Conference papers

The present paper describes the design and evaluation of an adventure videogame developed to cover the mathematics primary school curriculum. The narrative of the game is based in the history of mathematics and, to win, the player needs to travel through time, starting from the ancient Egypt and finishing at the modern world. To achieve that, the player interacts with real-life characters, such as Pythagoras of Samos, learning about their contributions to the field and using this knowledge to solve puzzles. The aim of the research presented in this paper is to understand the effects of the game on students’ …

Smpl-Based 3d Pedestrian Pose Prediction, Anil Kunchala, Bianca Schoen-Phelan, Mélanie Bouroche, Lorraine D'Arcy

Conference papers

Modeling human motion is a long-standing problem in computer vision. The rapid development of deep learning technologies for computer vision problems resulted in increased attention in the area of pose prediction due to its vital role in a multitude of applications, for example, behavior analysis, autonomous vehicles, and visual surveillance. In 3D pedestrian pose prediction, joint-rotation-based pose representation is extensively used due to the unconstrained degree of freedom for each joint and its ability to regress the 3D statistical wireframe. However, all the existing joint-rotation-based pose prediction approaches ignore the centrality of the distinct pose parameter components and are consequently …

Start Of Epidemy In A City: Short-Term Forecast Of Covid-19 With Gmdh-Based Algorithms And Official Medical Statistics, Anna Boldyreva, Mikhail Alexandrov, Olexiy Koshulko, Svetland Popova

Conference papers

The sudden onset and quick development of an unknown epidemic may lead to tragic consequences: panic of population due to victims and unpreparedness of authorities for effectively help to population. These circumstances define extremely high requirements to the tools for short-term operational forecast. Namely, such tools should provide reliable results when model of phenomenon is unknown (factors of disease spreading) and data are limited (time series of observations). GMDH-based algorithms just meet these requirements unlike modern differential or advanced statistical models. In this study we test different algorithms from GMDH Shell platform on the example of Covid-19 epidemic in Moscow …

Brexit: Psychometric Profiling The Political Salubrious Through Machine Learning: Predicting Personality Traits Of Boris Johnson Through Twitter Political Text, James Usher, Pierpaolo Dondio

Conference papers

Whilst the CIA have been using psychometric profiling for decades, Cambridge Analytica showed that people's psychological characteristics can be accurately predicted from their digital footprints, such as their Facebook or Twitter accounts. To exploit this form of psychological assessment from digital footprints, we propose machine learning methods for assessing political personality from Twitter. We have extracted the tweet content of Prime Minster Boris Johnson’s Twitter account and built three predictive personality models based on his Twitter political content. We use a Multi-Layer Perceptron Neural network, a Naive Bayes multinomial model and a Support Machine Vector model to predict the OCEAN …

Brain Disease Detection From Eegs: Comparing Spiking And Recurrent Neural Networks For Non-Stationary Time Series Classification, Hristo Stoev

Dissertations

Modeling non-stationary time series data is a difficult problem area in AI, due to the fact that the statistical properties of the data change as the time series progresses. This complicates the classification of non-stationary time series, which is a method used in the detection of brain diseases from EEGs. Various techniques have been developed in the field of deep learning for tackling this problem, with recurrent neural networks (RNN) approaches utilising Long short-term memory (LSTM) architectures achieving a high degree of success. This study implements a new, spiking neural network-based approach to time series classification for the purpose of …

Content-Based Filtering Recommendation Approach To Label Irish Legal Judgements, Sandesh Gangadhar

Dissertations

Machine learning approaches are applied across several domains to either simplify or automate tasks which directly result in saved time or cost. Text document labelling is one such task that requires immense human knowledge about the domain and efforts to review, understand and label the documents. The company Stare Decisis summarises legal judgements and labels them as they are made available on Irish public legal source www.courts.ie. This research presents a recommendation-based approach to reduce the time for solicitors at Stare Decisis by reducing many numbers of available labels to pick from to a concentrated few that potentially contains the …

Optimization Of Home Mortgage Mover Predictive Model Applying Geo-Spatial Analysis And Machine Learning Techniques, Natalia Riscovaia

Dissertations

In the last decade digital innovations and online banking services have significantly changed customers banking preferences and behaviour. Banking industry is going through the changes and developments in the provision of banking services that are affecting the structure and the organization of the bank network. However, private home loan, referred as Home Mortgage hereinafter, continue to remain among the products, that customers prefer to have personal interaction about with professional advisors prior making the decision to apply for the loan with financial institution.

Synthetic Data Generation Using Wasserstein Conditional Gans With Gradient Penalty (Wcgans-Gp), Manhar Singh Walia

Dissertations

With data protection requirements becoming stricter, the data privacy has become increasingly important and more crucial than ever. This has led to restrictions on the availability and dissemination of real-world datasets. Synthetic data offers a viable solution to overcome barriers of data access and sharing. Existing data generation methods require a great deal of user-defined rules, manual interactions and domainspecific knowledge. Moreover, they are not able to balance the trade-off between datausability and privacy. Deep learning based methods like GANs have seen remarkable success in synthesizing images by automatically learning the complicated distributions and patterns of real data. But they …

Improving Transfer Learning For Use In Multi-Spectral Data, Yuvraj Sharma

Dissertations

Recently Nasa as well as the European Space Agency have made observational satellites images public. The main reason behind opening it to public is to foster research among university students and corporations alike. Sentinel is a program by the European Space Agency which has plans to release a series of seven satellites in lower earth orbit for observing land and sea patterns. Recently huge datasets have been made public by the Sentinel program. Many advancements have been made in the field of computer vision in the last decade. Krizhevsky, Sutskever & Hinton, 2012, revolutionized the field of image analysis by …

Research And Innovation As A Catalyst For Food System Transformation, A.C.L. Den Boer, K.P.W. Kok, M. Gill, J. Breda, Jean Cahill, C. Callenius, P. Caron, Z. Damianova, M. Gurinovic, L. Lahteenmaki, T. Lang, R. Sonnino, G. Verburg, H. Westhoek, T. Cesuroglu, B.J. Regeer, J.E.W. Broerse

Research and Innovation - Other

Background Food systems are associated with severe and persistent problems worldwide. Governance approaches aiming to foster sustainable transformation of food systems face several challenges due to the complex nature of food systems.

Scope and approach In this commentary we argue that addressing these governance challenges requires the development and adoption of novel research and innovation (R&I) approaches that will provide evidence to inform food system transformation and will serve as catalysts for change. We first elaborate on the complexity of food systems (transformation) and stress the need to move beyond traditional linear R&I approaches to be able to respond to …

Β-Methylumbelliferone Surface Modification And Permeability Investigations At Pentel™ Graphite Electrodes, Susan Warren, Brian Seddon, Ruth Pilkington, Alison Crossely, Philip Holdway, Eithne Dempsey

Articles

Electrochemical and micro-imaging analysis of a commercial graphite-composite material is presented following electro-oxidation with β-methylumbelliferone. Charge-transfer surface modification was observed for the graphite electrode, presumed to have arisen from adsorbed interfacial umbelliferone moieties. The molecular permeability of the new surface towards a range of similar, yet size-variable (23 Å3–136 Å3) molecular redox probes is discussed. Red-shift fluorescence in confocal microscopy offers further support for the presence of a surface-bound umbelliferone layer. An SEM-platinum profiling technique was used as an imaging tool to map the umbelliferone surface and size-distribution of electroactive sites.

Audio Interval Retrieval Using Convolutional Neural Networks, Ievgeniia Kuzminykh, Dan Shevchuk, Stavros Shiaeles, Bogdan Ghita

School of Engineering, Computing and Mathematics

No abstract provided.

Model Comparison From Ligo-Virgo Data On Gw170817'S Binary Components And Consequences For The Merger Remnant, B. P. Abbott, R. Abbott, Marco Cavaglia, For Full List Of Authors, See Publisher's Website.

Physics Faculty Research & Creative Works

GW170817 is the very first observation of gravitational waves originating from the coalescence of two compact objects in the mass range of neutron stars, accompanied by electromagnetic counterparts, and offers an opportunity to directly probe the internal structure of neutron stars. We perform Bayesian model selection on a wide range of theoretical predictions for the neutron star equation of state. For the binary neutron star hypothesis, we find that we cannot rule out the majority of theoretical models considered. In addition, the gravitational-wave data alone does not rule out the possibility that one or both objects were low-mass black holes. …

Robustness Metric For Robust Design Optimization Under Time-And Space-Dependent Uncertainty Through Metamodeling, Xinpeng Wei, Xiaoping Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Product performance varies with respect to time and space in many engineering applications. This paper discusses how to measure and evaluate the robustness of a product or component when its quality characteristics (QCs) are functions of random variables, random fields, temporal variables, and spatial variables. At first, the existing time-dependent robustness metric is extended to the present time-and space-dependent problem. The robustness metric is derived using the extreme value of the quality characteristics with respect to temporal and spatial variables for the nominal-the-better type quality characteristics. Then, a metamodel-based numerical procedure is developed to evaluate the new robustness metric. The …

Thermal Atomic Layer Deposition Of Silver Metal Films: Synthesis And Characterization Of Thermally Stable Silver Metal Precursors, Harshani Jayabahu Arachchilage

Wayne State University Dissertations

ABSTRACT

THERMAL ATOMIC LAYER DEPOSITION OF SILVER METAL FILMS: SYNTHESIS AND CHARACTERIZATION OF THERMALLY STABLE SILVER METAL PRECURSORS

by

HARSHANI JAYABAHU ARACHCHILAGE

August 2020

Advisor: Professor Charles H. Winter

Major: Chemistry (Inorganic)

Degree: Doctor of Philosophy

Traditional film deposition techniques such as PVD and CVD are widely used in the microelectronics industry. However, the lack of thickness control and conformality requirements limit these techniques for current and future applications. By contrast, ALD offers the deposition of ultra-thin conformal films with accurate thickness control due to the self-limiting growth behavior. Ag metal has the lowest resistivity (1.59 µΩ cm) of all …

Vietnamese Punctuation Prediction Using Deep Neural Networks, Thuy Pham, Nhu Nguyen, Hong Quang Pham, Han Cao, Binh Nguyen

Research Collection School Of Computing and Information Systems

Adding appropriate punctuation marks into text is an essential step in speech-to-text where such information is usually not available. While this has been extensively studied for English, there is no large-scale dataset and comprehensive study in the punctuation prediction problem for the Vietnamese language. In this paper, we collect two massive datasets and conduct a benchmark with both traditional methods and deep neural networks. We aim to publish both our data and all implementation codes to facilitate further research, not only in Vietnamese punctuation prediction but also in other related fields. Our project, including datasets and implementation details, is publicly …

Challenges And Trends In Sustainable Corporate Finance: A Bibliometric Systematic Review, Tad Dat Bui, Mohd Helmi Ali, Feng Ming Tsai, Mohammad Iranmanesh, Ming-Lang Tseng, Ming K. Lim

Research outputs 2014 to 2021

Sustainable corporate finance is an attractive field of study in sustainability literature; however, the literature lacks systematic bibliometric analysis that provides a comprehensive review to clarify state-of-the-art sustainable corporate finance and that discusses new opportunities and potential instructions for further studies. To address this gap, this study adopts a literature review, bibliometric analysis, network analysis and co-wording technique to systematically investigate the Scopus database. In total, 30 keywords listed at least three times are used and are divided into six clusters considering six fields of research, namely, corporate finance in corporate sustainability, sustainable competitive advantages, sustainable stakeholder engagement, circular economy, …

Applications Of Polynomial Chaos-Based Cokriging To Aerodynamic Design Optimization Benchmark Problems, Jethro Nagawkar, Leifur Leifsson, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In this work, the polynomial chaos-based Cokriging (PC-Cokriging) is applied to a benchmark aerodynamic design optimization problem. The aim is to perform fast design optimization using this multifidelity metamodel. Multifidelity metamodels use information at multiple levels of fidelity to make accurate and fast predictions. Higher amount of lower fidelity data can provide important information on the trends to a limited amount of high-fidelity (HF) data. The PC-Cokriging metamodel is a multivariate version of the polynomial chaos-based Kriging (PC-Kriging) metamodel and its construction is similar to Cokriging. It combines the advantages of the interpolation-based Kriging metamodel and the regression-based polynomial chaos …

Identifying The Critical Factors Of Sustainable Manufacturing Using The Fuzzy Dematel Method, Luwei Jiang, Tenghao Zhang, Yanfei Feng

Research outputs 2014 to 2021

© 2020 Luwei Jiang et al., published by Sciendo 2020. The burgeoning trend of globalization gives rise to the formation of the manufacturing ecosystem. This study aims to identify the critical factors of sustainable manufacturing for countries and regions across the globe finding their unique ecological niches. From the perspective of the ecological niche, we develop an evaluation system of the manufacturing niche. By using the fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) method, the critical factors, and its causal relationships of the manufacturing niche can be quantified and visualized. The results indicate that: (1) the evaluation system of the …

Fusion Of 3d Lidar And Camera Data For Object Detection In Autonomous Vehicle Applications, Xiangmo Zhao, Pengpeng Sun, Zhigang Xu, Haigen Min, Hongkai Yu

Computer Science Faculty Publications

It’s critical for an autonomous vehicle to acquire accurate and real-time information of the objects in its vicinity, which will fully guarantee the safety of the passengers and vehicle in various environment. 3D LIDAR can directly obtain the position and geometrical structure of the object within its detection range, while vision camera is very suitable for object recognition. Accordingly, this paper presents a novel object detection and identification method fusing the complementary information of two kind of sensors. We first utilize the 3D LIDAR data to generate accurate object-region proposals effectively. Then, these candidates are mapped into the image space …

Daily Stream Samples Reveal Highly Complex Pesticide Occurrence And Potential Toxicity To Aquatic Life, Julia E. Norman, Barbara J. Mahler, Lisa H. Nowell, Peter C. Van Metre, Mark W. Sandstrom, Mark A. Corbin, Yaorong Qian, James F. Pankow, Wentai Luo, Nicholas B. Fitzgerald, Multiple Additional Authors

Chemistry Faculty Publications and Presentations

Transient, acutely toxic concentrations of pesticides in streams can go undetected by fixed-interval sampling programs. Here we compare temporal patterns in occurrence of current-use pesticides in daily composite samples to those in weekly composite and weekly discrete samples of surface water from 14 small stream sites. Samples were collected over 10–14 weeks at 7 stream sites in each of the Midwestern and Southeastern United States. Samples were analyzed for over 200 pesticides and degradates by direct aqueous injection liquid chromatography with tandem mass spectrometry. Nearly 2 and 3 times as many unique pesticides were detected in daily samples as in …

Synthesis Of Radioluminescent Caf2:Ln Core, Mesoporous Silica Shell Nanoparticles For Use In X-Ray Based Theranostics, Hayden Winter, Megan J. Neufeld, Lydia Makotamo, Conroy Sun, Andrea M. Goforth

Chemistry Faculty Publications and Presentations

X-ray radiotherapy is a common method of treating cancerous tumors or other malignant lesions. The side effects of this treatment, however, can be deleterious to patient quality of life if critical tissues are affected. To potentially lower the effective doses of radiation and negative side-effects, new classes of nanoparticles are being developed to enhance reactive oxygen species production during irradiation. This report presents the synthesis and radiotherapeutic efficacy evaluation of a new nanoparticle formulation designed for this purpose, composed of a CaF₂ core, mesoporous silica shell, and polyethylene glycol coating. The construct was additionally doped with Tb and Eu …

Use Of Confocal Raman Microscopy To Characterise Ethyl Cyanoacrylate Adhesive Depth Curing, Kevin Raheem, John Cassidy, Tony Betts, Bernard Ryan

Articles

In situ spatial temporal measurement of monomer conversion during adhesive bondline curing remains a challenging area. The aim of this work was to demonstrate the effectiveness of using confocal Raman microscopy in a specially configured experimental set-up, as a versatile tool for measuring monomer concentration changes as a function of both time and adhesive bond depth during ethyl cyanoacrylate polymerisation. This also allowed monitoring of the extent of polymerisation at the adhesive substrate interface independently of the bulk bondline polymerisation region. Key kinetic parameters such as inhibition time tlag, rate of reaction Rmax and extent of reaction [at]max were obtained …

Finite Lifespan Of Solutions Of The Semilinear Wave Equation In The Einstein–De Sitter Spacetime, Anahit Galstian, Karen Yagdjian

School of Mathematical & Statistical Sciences Faculty Publications

We examine the solutions of the semilinear wave equation, and, in particular, of the φq model of quantum field theory in the curved space-time. More exactly, for 1 < q < 4 we prove that the solution of the massless self-interacting scalar field equation in the Einstein-de Sitter universe has finite lifespan.

Additions To Philippine Slender Skinks Of The Brachymeles Bonitae Complex (Reptilia: Squamata: Scincidae) Iv: Resurrection And Redescription Of Brachymeles Burksi, Cameron D. Siler, Elyse S. Freitas, Jennifer A. Sheridan, Stephanie N. Maguire, Drew R. Davis, Jessa L. Watters, Kai Wang, Arvin C. Diesmos, Rafe M. Brown

School of Earth, Environmental, & Marine Sciences Faculty Publications

The diversity of Philippine amphibians and reptiles has increased over the last few decades, in part due to re-evaluation of species formerly believed to be widespread. Many of these investigations of widespread species have uncovered multiple closely related cryptic lineages comprising species complexes, each restricted to individual Pleistocene Aggregate Island Complexes (PAICs). One group in particular for which widespread cryptic diversity has been common is the clade of Philippine skinks of the genus Brachymeles. Recent phylogenetic studies of the formerly recognized widespread species Brachymeles bonitae have indicated that this species is actually a complex distributed across several major PAICs and …

New County Records Of Amphibians And Reptiles From South Texas, Usa, Clinton J. Guadiana, Padraic S. Robinson, Matthew S. Schalk, Drew R. Davis

School of Earth, Environmental, & Marine Sciences Faculty Publications

Several species of amphibians and reptiles reach their northern range limit in south Texas, USA. Herpetological research in the area, as well as frequent visits from amphibian and reptile enthusiasts, have helped to form a more complete understanding of amphibian and reptile distributions across the region. However, gaps in the recognized distribution of many species remain. Efforts to better document species occurrence are confounded by the lack of public land and the fact that most of south Texas is privately owned, making access to suitable habitat difficult (Schmidly et al. 2001)

Coral Reefs In The Gulf Of Mexico Large Marine Ecosystem: Conservation Status, Challenges, And Opportunities, Diego L. Gil-Agudelo, Carlos E. Cintra-Buenrostro, Jorge Brenner, Patricia Gonzalez-Diaz, William Kiene, Caitlin Lustic, Horacio Perez-Espana

School of Earth, Environmental, & Marine Sciences Faculty Publications

The importance of coral reefs (CR) within marine ecosystems has become widely recognized. Although shallow CR are not as abundant in the Gulf of Mexico (GoM) as in other areas such as the Caribbean, their uniqueness, singularity, isolation, and conservation status make their conservation highly important. Corals and CR, both shallow and deep, are more widely distributed throughout the GoM than previously thought, providing new venues of research but also new challenges for their sustainable management. They are widely present in the three countries circumscribing the GoM (Cuba, Mexico, and the United States). Corals are also distributed throughout different depths, …

Architectonica Karsteni Rutsch, 1934 (Gastropoda: Architectonicidae) In Seamounts Of The Nazca-Desventuradas Marine Park: First Evidence Of An Extant Population In Chilean Waters Since The Miocene, Cynthia M. Asorey, Javier Sellanes, Erin E. Easton, Rüdiger Bieler, Ariadna Mecho

School of Earth, Environmental, & Marine Sciences Faculty Publications

The presence of Architectonicidae in Chile was previously recorded only from fossil material of eight species present during the Lower Miocene, when Architectonica karsteni had a geographic range that extended from Costa Rica to central Chile (34°S). No evidence of the presence of the family in Chile after the Lower Miocene have been reported. As part of this study, we report the discovery of A. karsteni at four seamountsat ~200 m water depth in the recently created Nazca-Desventuradas Marine Park, located ~900 km west of continental Chile. Morphological identification was based on protoconch diameter, coloration patterns, and teleoconch sculpture. We …

Effects Of Integrated Application Of Plant-Based Compost And Urea On Soil Food Web, Soil Properties, And Yield And Quality Of A Processing Carrot Cultivar, A. Habteweld, D. Brainard, A. Kravchencko, Parwinder Grewal, H. Melakeberhan

School of Earth, Environmental, & Marine Sciences Faculty Publications

Soil nutrient management system characterized by reduced input of inorganic fertilizers integrated with organic amendments is one of the alternatives for reducing deleterious environmental impact of synthetic fertilizers, suppressing soil-borne pests and diseases, and improving soil health and crop yield. A hypothesis of the present study was that lower rates of urea mixed with higher rates of plant compost (PC) would improve nematode community structure, soil food web condition, soil biological, and physiochemical properties, and yield and quality of a processing carrot (Daucus carota) cultivar. Urea and PC were each applied at 135kg nitrogen (N)/ha alone or at 3:1, 1:1, …

Mitochondrial Genomes And Genetic Structure Of The Kemp's Ridley Sea Turtle (Lepidochelys Kempii), Hilary R. Frandsen, Diego F. Figueroa, Jeff A. George

School of Earth, Environmental, & Marine Sciences Faculty Publications

The Kemp's ridley (Lepidochelys kempii) is the world's most endangered sea turtle species and is primarily distributed in the Gulf of Mexico. In the United States, South Padre Island, Texas serves as a key nesting ground for the species. Genetic studies of the Kemp's ridley have been used to aid in conservation and management practices, with the mitochondrial control region as the most commonly used marker due to its perceived hypervariability and ease of sequencing. However, with the advent of next generation sequencing technology, targeting complete mitochondrial genomes is now feasible. Here, we describe a more complete mitochondrial genome for …