Engineering Commons^™

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.

Engineers Without Borders, Katherine Villacis, Brandon Kreusch, Robert Schablik, Joseph Jackson, Karen Tayar, Samantha Struble, Bernard Bogus, Jessie Bundtz, John Anderson, Melanie Ware, Trevor Stebbins

STEM Student Research Symposium Posters

Engineers Without Borders (EWB) chapter at Rowan University is a multidisciplinary team of students and faculty that work towards providing sustainable solutions to real world problems. During the academic year of 2018-2019, the team has worked on one international project located in India and three different local projects located in New Jersey. The projects for the academic year of 2018-2019 were:

• Ranshet Ashram School, Maharashtra, India
• Resilient Roots Garden, Camden NJ
• Ronald McDonald House, Camden, NJ
• Cedar Run Wildlife Refuge, Medford, NJ

Automated Segmentation Of Brain Ventricles Using 3d U-Net, Robert Sandor, Anish P. Dalal

Creative Activity and Research Day - CARD

Neuro-radiologists currently use qualitative volumetric change of brain ventricles after surgery to assess the safety of removing a ventriculoperitoneal (VP) shunt which is a medical device that relieves pressure on the brain caused by fluid accumulation. Following safe removal of the VP shunt, patients can be released from the hospital. The need for accurate and quick measurement of brain ventricular volumetric change makes automatic 3D segmentation software an ideal candidate to aid decisions after surgery. In this paper, we propose an approach to estimate the ventricular volume variation using segmentation in brain MRI and CT images. Our approach consists of …

Proceedings, Msvscc 2019, Old Dominion University, Department Of Modeling, Simulation & Visualization Engineering, Old Dominion University, Virginia Modeling, Analysis And Simulation Center

Modeling, Simulation and Visualization Student Capstone Conference

Old Dominion University Department of Modeling, Simulation & Visualization Engineering (MSVE) and the Virginia Modeling, Analysis and Simulation Center (VMASC) held the 13th annual Modeling, Simulation & Visualization (MSV) Student Capstone Conference on April 18, 2019.

The Conference featured student research and student projects that are central to MSV. Also participating in the conference were faculty members who volunteered their time to impart direct support to their students’ research, facilitated the various conference tracks, served as judges for each of the tracks, and provided overall assistance to the conference.

Appreciating the purpose of the conference and working in a cohesive, …

Computational Prediction Of Host-Pathogen Protein Interactions Between Melioidosis Pathogen Burkholderia Pseudomallei And Human, Chathumadavi Ediriweera

Student Research Symposium

Background:

Burkholderia pseudomallei (Bp) is a critical biothreat agent, causes Melioidosis: a disease associated with high case-fatality rates in animals and humans; even with treatment, its mortaility is up to 50%. It also infects plants. Yet few effector proteins have been functionally characterized to date and little work has been carried out to understand the host-pathogen protein-protein interactions (PPI) which are important to develop efficient prevention measures. To address these issues, we deployed diverse in-silico methodologies to identify virulence factors and their interactions with host proteins to characterize bacterial infection mechanisms.

Fair Resource Allocation In An Mec-Enabled Ultra-Dense Iot Network With Noma, Qun Wang

Student Research Symposium

Ultra-dense Internet of Things (IoT) network has greatly facilitated the development of smart environments and the realization of diverse sophisticated applications. Power constrained and resource-limited IoT devices often need to perform computation-intensive and delay-sensitive tasks in such a network. Mobile edge computing and non-orthogonal multiple access are two promising techniques to address the corresponding challenges. In order to improve the fairness and resource efficiency among IoT users, resource allocation problems are formulated in ultra-dense MEC-enabled IoT networks with NOMA considered. An iterative algorithm based on successive convex approximation technique is proposed to solve those challenging non-convex problems.

Exploiting Wall Street: An Algorithmic Approach To Investing, Sterling Lemon

Student Research Symposium

Technology has advanced dramatically over the years, yet the old investment strategy of "buy and hold" has remained prevalent. While this strategy performed well historically, it serves as a stark contrast to modern investing which, by utilizing machine learning and advanced data analytics, is generating unprecedented returns This research project will demonstrate the strength behind algorithmic investing and how the investment strategy of "buy and hold" will become a thing of the past.

Propulsion Unit Optimization For Small Uas, Cory Goates

Student Research Symposium

Selection of a propulsion system for unmanned aerial vehicles (UAV) is a complex and iterative process. Attempts have been made to provide effective modelling of propulsion systems. However, due to the discrete nature of the design space, effective optimization tools have yet to be developed. We present an optimizer which presents designers with feasible propulsion systems based on given parameters. This optimizer also allows designers to view trend in the design space and more quickly determine an optimum solution.

Augmenting Anaerobic Digestion Of Microalgal Biomass, Anna Doloman

Student Research Symposium

Anaerobic digestion of microalgal biomass cannot be achieved without specialized hydrolytic microorganisms. Potentially algalytic bacteria belonging to Citrobacter and Alcaligenes species were isolated from a wastewater lagoon system. A combination of two potentially algalytic bacteria was successfully incorporated into the granular anaerobic consortia. A series of anaerobic cultures were prepared with different microbial combinations to test the methane production from algal biomass collected from a local wastewater treating trickling filter. The anaerobic microbial community mixed with two algalytic bacteria produced 10% more methane when compared to the methane produced by a native granular consortium. The presence of the algalytic bacteria …

Autonomous Watercraft Simulation And Programming, Nicholas J. Savino

Student Scholar Showcase

Automation of various modes of transportation is thought to make travel more safe and efficient. Over the past several decades, advances to semi-autonomous and autonomous vehicles have led to advanced autopilot systems on planes and boats, and an increasing popularity of self-driving cars. We predicted the motion of an autonomous vehicle using simulations in Python. The simulation models the motion of a small scale watercraft, which can then be built and programmed using an Arduino Microcontroller. We examined different control methods for a simulated rescue craft to reach a target. We also examined the effects of different factors, such as …

Robust Structured Group Local Sparse Tracker Using Convolutional Neural Network Features, Mohammadreza Javanmardi

Student Research Symposium

Sparse representation has recently been successfully applied in visual tracking. It utilizes a set of templates to represent target candidates and find the best one with the minimum reconstruction error as the tracking result. In this presentation, we propose a robust deep features-based structured group local sparse tracker, which exploits the convolutional neural network (CNN) features of local patches inside target candidates and represents them by a set of templates in the particle filter framework. To extract the local CNN features, we first set the size of each target candidate to 64 by 64 pixels to contain sufficient object-level information …

12th Annual Research Week--Event Proceedings, Office Of Research And Sponsored Projects Operations

Excellence Summit (Research Week) Archived Proceedings

12th Annual Research Week

"A Celebration of Student Research"

Performance Analysis Of Voting Algorithms In Wireless Sensor Networks, Aditi Mishra

Computer Science Graduate Research Workshop

No abstract provided.

Consensus-Based Robotic Formation Control, Satish Reddy Modugu

Computer Science Graduate Research Workshop

No abstract provided.

Simulator For Qubit Measurement Using Augmented Reality, Sai Pradeep Koneti

Computer Science Graduate Research Workshop

No abstract provided.

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

Computer Science Graduate Research Workshop

No abstract provided.

Fluoride Removal From Water Using A 3d Printed Calcium Carbonate Filter, Sophia Bakar, David Kahler, Benjamin S. Goldschmidt

Undergraduate Research and Scholarship Symposium

Groundwater containing high concentrations of fluoride is the most common source of drinking water in rural areas in parts of east Africa, India, and China. The elevated levels of fluoride cause skeletal and dental fluorosis, which is the weakening and decay of bone structures due to the leeching of calcium from the body as calcium and fluoride bond by the process of adsorption. Over 150 million people are suffering from some form of fluorosis due to the consumption of groundwater. Calcium carbonate has been demonstrated to influence fluoride removal in several forms. To make fluoride removal a cost-effective and user-friendly …

Quantifying Iron Overload Using Mri, Active Contours, And Convolutional Neural Networks, Andrea Sajewski, Stacey Levine

Undergraduate Research and Scholarship Symposium

Iron overload, a complication of repeated blood transfusions, can cause tissue damage and organ failure. The body has no regulatory mechanism to excrete excess iron, so iron overload must be closely monitored to guide therapy and measure treatment response. The concentration of iron in the liver is a reliable marker for total body iron content and is now measured noninvasively with magnetic resonance imaging (MRI). MRI produces a diagnostic image by measuring the signals emitted from the body in the presence of a constant magnetic field and radiofrequency pulses. At each pixel, the signal decay constant, T2*, can be calculated, …

Influence Of Sonication Parameters On The Morphology Of Nanocellulose Aerogels, Dexter Cox, Tim Kidd

Research in the Capitol

Nanocellulose is a renewable and biocompatible material that has a tensile strength similar to aluminum, is stiffer than Kevlar, and has a strength to weight ratio eight times that of stainless steel. There has been a range of studies on nanocellulose materials for potential use as a low-calorie food substitute, biomedical wound dressings, and as a structural component for buildings. Throughout this research experiment, nanocellulose aerogels of different mass compositions were created through a mechanical process using an ultrasonic processor with a titanium probe attachment. The purpose of this study was to develop a method that reduces the amount titanium …

(Poster) A Bird's-Eye View Of What Learners Like And Dislike About Stem Moocs Using Topic Modeling, Abigail Gentry

ASEE IL-IN Section Conference

Massive Open Online Courses (MOOCs) are offered for many different subject areas such as STEM, Arts, Medicine, and Business, with differences in each subject area. In this study, we focus on STEM MOOCs and their unique challenges. In order to design better MOOCs to encourage engagement, it is important to understand learners expectations and preferences based on the subject area by analyzing end-of-course evaluation surveys of STEM MOOCs. We analyzed open-ended learner feedback for two post-survey questions for 110 unique STEM MOOCs (some with multiple re-runs) with a total of 8100 responses, offered on the FutureLearn platform. The end-of-course survey …

(Poster) Freshman Engineering Student Engagement Through Sport’S Data Analytics, Adam Tennant

ASEE IL-IN Section Conference

Instructors of engineering for the last quarter of a century have attempted to engage undergraduates through project based learning. Often these topics can fall short due to a lack of interest by the students. Faculty-lead student research experiences addressing pop-culture topics of interest can often stimulate student engagement and have the possibility to positively impact student-retention rates. This presentation reports on the preliminary findings of a sport’s data analytics approach for faculty-led student investigations and increased engagement. Freshman engineering students will rank teams or individuals through the PageRank algorithm creating a model of the complexity of sports. The specifics of …

(Poster) Deepening Engineering Design Experience: A Novel Approach To Senior Design, Donald Peterson, Mansour Tahernezhadi, Abul Azad

ASEE IL-IN Section Conference

This poster advances a new framework for the senior design course in order to deepen engineering design experience for engineering students. The proposed framework for the new senior design course while retains the traditional topics such as problem identification, conceptual design and analysis, prototyping and the preparation of a work schedule required to carry out the project, it fosters an early in the cycle start, typically after week 6, towards the design conceptualization and prototyping in the first academic semester. This is in stark contrast with traditional practices where the design conceptualization and prototyping largely takes place in the second …

Ascending The Data Usability Gap In Mountainous Regions Through Scientist-Stakeholder Co-Production, Alan Rhoades

Spring Runoff Conference

No abstract provided.

Water Challenges In The Lower Colorado River Basin And The Drought Contingency Plan, Sharon Megdal

Spring Runoff Conference

No abstract provided.

Water Management In The West—A Federal Perspective, Brent Esplin

Spring Runoff Conference

No abstract provided.

Harmful Algae Blooms In Utah, Scott Daly

Spring Runoff Conference

No abstract provided.

An Update On Water Legislation From The 2019 Utah Legislative Session, Tim Hawkes

Spring Runoff Conference

No abstract provided.

Spring Runoff Conference 2019: Water Challenges In The West, Spring Runoff Conference

Spring Runoff Conference

The Spring Runoff Conference, hosted by the USU Water Initiative, is held annually on the campus of Utah State University. The conference provides a forum for interdisciplinary sharing and exchange of ideas on water-related issues in Utah and the lntermountain Region

Session 3a: Drinking Water, Kentucky Water Resources Research Institute, University Of Kentucky

Kentucky Water Resources Annual Symposium

• Evaluating Potential Health Threats from Untreated Karst Springs as Community Drinking Water Sources, Monroe County, Kentucky
• Benefits of Energy Savings Performance Contracting for Water and Wastewater Treatment Facilities
• Self-Cleaning Nanocomposite Membranes with Phosphorene-Based Pore Fillers for Water Treatment

Session 3b: Pollutant Removal, Kentucky Water Resources Research Institute, University Of Kentucky

Kentucky Water Resources Annual Symposium

• Investigation of PlarClean and Gamma-Valerolactone as Solvents for Polysulfone Membrane Fabrication
• Selenium Removal Using Bacteria Entrapped Alginate Gel Beads in a Packed-Bed Reactor
• Nanotechnology and Membranes: Water detoxification from Lab Scale to Real Site Applications