Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- China Simulation Federation (3305)
- Old Dominion University (42)
- Singapore Management University (27)
- University of Nevada, Las Vegas (22)
- Western University (21)
-
- SelectedWorks (20)
- Selected Works (14)
- University of Denver (14)
- University of Nebraska - Lincoln (14)
- Fordham University (12)
- University of Arkansas, Fayetteville (12)
- University of South Florida (10)
- Chulalongkorn University (9)
- Embry-Riddle Aeronautical University (8)
- Purdue University (8)
- University of Louisville (8)
- University of Massachusetts Amherst (8)
- Missouri University of Science and Technology (6)
- New Jersey Institute of Technology (6)
- University of Central Florida (6)
- University of Tennessee, Knoxville (6)
- Air Force Institute of Technology (5)
- Southern Methodist University (5)
- California State University, San Bernardino (4)
- City University of New York (CUNY) (4)
- Kennesaw State University (4)
- Michigan Technological University (4)
- University of New Orleans (4)
- University of Texas at El Paso (4)
- California Polytechnic State University, San Luis Obispo (3)
- Keyword
-
- Simulation (136)
- Deep learning (60)
- Machine learning (48)
- Virtual reality (44)
- Genetic algorithm (39)
-
- Numerical simulation (39)
- Robotics (36)
- Modeling (35)
- Modeling and simulation (34)
- Particle swarm optimization (34)
- Path planning (34)
- Artificial intelligence (31)
- Machine Learning (28)
- Fault diagnosis (27)
- Neural network (27)
- Digital twin (24)
- Multi-objective optimization (24)
- Deep Learning (22)
- Optimization (22)
- Reinforcement learning (22)
- Simulation model (22)
- System simulation (22)
- Visualization (21)
- System dynamics (19)
- Complex network (17)
- Scheduling (17)
- UAV (17)
- Virtual simulation (17)
- Permanent magnet synchronous motor (16)
- Augmented reality (15)
- Publication Year
- Publication
-
- Journal of System Simulation (3305)
- Research Collection School Of Computing and Information Systems (24)
- Jeremy Straub (22)
- Electronic Theses and Dissertations (20)
- UNLV Theses, Dissertations, Professional Papers, and Capstones (20)
-
- Doctoral Dissertations (13)
- Faculty Publications (13)
- Electrical and Computer Engineering Publications (12)
- Electrical & Computer Engineering Theses & Dissertations (10)
- Chulalongkorn University Theses and Dissertations (Chula ETD) (9)
- Electronic Thesis and Dissertation Repository (9)
- Theses and Dissertations (9)
- USF Tampa Graduate Theses and Dissertations (9)
- Department of Computer Science and Engineering: Dissertations, Theses, and Student Research (7)
- Dissertations (7)
- Masters Theses (7)
- Computer Science and Computer Engineering Undergraduate Honors Theses (6)
- Human-Machine Communication (6)
- Cybersecurity Undergraduate Research Showcase (5)
- Graduate Theses and Dissertations (5)
- SMU Data Science Review (5)
- Dissertations, Master's Theses and Master's Reports (4)
- Electrical & Computer Engineering Faculty Publications (4)
- Faculty Scholarship (4)
- Ole J Mengshoel (4)
- Open Access Theses & Dissertations (4)
- Publications (4)
- University of New Orleans Theses and Dissertations (4)
- Computational Modeling & Simulation Engineering Theses & Dissertations (3)
- Computer Science: Faculty Publications and Other Works (3)
- Publication Type
- File Type
Articles 3601 - 3630 of 3695
Full-Text Articles in Computer Engineering
Explorations Into Machine Learning Techniques For Precipitation Nowcasting, Aditya Nagarajan
Explorations Into Machine Learning Techniques For Precipitation Nowcasting, Aditya Nagarajan
Masters Theses
Recent advances in cloud-based big-data technologies now makes data driven solutions feasible for increasing numbers of scientific computing applications. One such data driven solution approach is machine learning where patterns in large data sets are brought to the surface by finding complex mathematical relationships within the data. Nowcasting or short-term prediction of rainfall in a given region is an important problem in meteorology. In this thesis we explore the nowcasting problem through a data driven approach by formulating it as a machine learning problem.
State-of-the-art nowcasting systems today are based on numerical models which describe the physical processes leading to …
Performance Verification For Robot Missions In Uncertain Environments, Damian Lyons, Ron Arkin, Shu Jiang, Matt O'Brien, Feng Tang, Peng Tang
Performance Verification For Robot Missions In Uncertain Environments, Damian Lyons, Ron Arkin, Shu Jiang, Matt O'Brien, Feng Tang, Peng Tang
Faculty Publications
Abstract—Certain robot missions need to perform predictably in a physical environment that may have significant uncertainty. One approach is to leverage automatic software verification techniques to establish a performance guarantee. The addition of an environment model and uncertainty in both program and environment, however, means the state-space of a model-checking solution to the problem can be prohibitively large. An approach based on behavior-based controllers in a process-algebra framework that avoids state-space combinatorics is presented here. In this approach, verification of the robot program in the uncertain environment is reduced to a filtering problem for a Bayesian Network. Validation results …
Establishing A-Priori Performance Guarantees For Robot Missions That Include Localization Software, Damian Lyons, Ron Arkin, Shu Jiang, Matt O'Brien, Feng Tang, Peng Tang
Establishing A-Priori Performance Guarantees For Robot Missions That Include Localization Software, Damian Lyons, Ron Arkin, Shu Jiang, Matt O'Brien, Feng Tang, Peng Tang
Faculty Publications
One approach to determining whether an automated system is performing correctly is to monitor its performance, signaling when the performance is not acceptable; another approach is to automatically analyze the possible behaviors of the system a-priori and determine performance guarantees. Thea authors have applied this second approach to automatically derive performance guarantees for behaviorbased, multi-robot critical mission software using an innovative approach to formal verification for robotic software. Localization and mapping algorithms can allow a robot to navigate well in an unknown environment. However, whether such algorithms enhance any specific robot mission is currently a matter for empirical validation. Several …
2d Vector Map And Database Design For Indoor Assisted Navigation, Luciano Caraciolo Albuquerque
2d Vector Map And Database Design For Indoor Assisted Navigation, Luciano Caraciolo Albuquerque
Dissertations and Theses
In this paper we implemented a 2D Vector Map, map editor and Database design intended to provide an efficient way to convert cad files from indoor environments to a set of vectors representing hallways, doors, exits, elevators, and other entities embedded in a floor plan, and save them in a database for use by other applications, such as assisted navigation for blind people.
A graphical application as developed in C++ to allow the user to input a CAD DXF file, process the file to automatically obtain nodes and edges, and save the nodes and edges to a database for posterior …
An Ensemble Learning Framework For Anomaly Detection In Building Energy Consumption, Daniel B. Araya, Katarina Grolinger, Hany F. Elyamany, Miriam Am Capretz, Girma T. Bitsuamlak
An Ensemble Learning Framework For Anomaly Detection In Building Energy Consumption, Daniel B. Araya, Katarina Grolinger, Hany F. Elyamany, Miriam Am Capretz, Girma T. Bitsuamlak
Electrical and Computer Engineering Publications
During building operation, a significant amount of energy is wasted due to equipment and human-related faults. To reduce waste, today's smart buildings monitor energy usage with the aim of identifying abnormal consumption behaviour and notifying the building manager to implement appropriate energy-saving procedures. To this end, this research proposes a new pattern-based anomaly classifier, the collective contextual anomaly detection using sliding window (CCAD-SW) framework. The CCAD-SW framework identifies anomalous consumption patterns using overlapping sliding windows. To enhance the anomaly detection capacity of the CCAD-SW, this research also proposes the ensemble anomaly detection (EAD) framework. The EAD is a generic framework …
Deep Models For Engagement Assessment With Scarce Label Information, Feng Li, Guangfan Zhang, Wei Wang, Roger Xu, Tom Schnell, Jonathan Wen, Frederic Mckenzie, Jiang Li
Deep Models For Engagement Assessment With Scarce Label Information, Feng Li, Guangfan Zhang, Wei Wang, Roger Xu, Tom Schnell, Jonathan Wen, Frederic Mckenzie, Jiang Li
Electrical & Computer Engineering Faculty Publications
Task engagement is defined as loadings on energetic arousal (affect), task motivation, and concentration (cognition) [1]. It is usually challenging and expensive to label cognitive state data, and traditional computational models trained with limited label information for engagement assessment do not perform well because of overfitting. In this paper, we proposed two deep models (i.e., a deep classifier and a deep autoencoder) for engagement assessment with scarce label information. We recruited 15 pilots to conduct a 4-h flight simulation from Seattle to Chicago and recorded their electroencephalograph (EEG) signals during the simulation. Experts carefully examined the EEG signals and labeled …
Towards Building A Review Recommendation System That Trains Novices By Leveraging The Actions Of Experts, Shilpa Khanal
Towards Building A Review Recommendation System That Trains Novices By Leveraging The Actions Of Experts, Shilpa Khanal
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Online reviews increase consumer visits, increase the time spent on the website, and create a sense of community among the frequent shoppers. Because of the importance of online reviews, online retailers such as Amazon.com and eOpinions provide detailed guidelines for writing reviews. However, though these guidelines provide instructions on how to write reviews, reviewers are not provided instructions for writing product-specific reviews. As a result, poorly-written reviews are abound and a customer may need to scroll through a large number of reviews, which could be up to 6000 pixels down from the top of the page, in order to find …
On Path Consistency For Binary Constraint Satisfaction Problems, Christopher G. Reeson
On Path Consistency For Binary Constraint Satisfaction Problems, Christopher G. Reeson
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Constraint satisfaction problems (CSPs) provide a flexible and powerful framework for modeling and solving many decision problems of practical importance. Consistency properties and the algorithms for enforcing them on a problem instance are at the heart of Constraint Processing and best distinguish this area from other areas concerned with the same combinatorial problems. In this thesis, we study path consistency (PC) and investigate several algorithms for enforcing it on binary finite CSPs. We also study algorithms for enforcing consistency properties that are related to PC but are stronger or weaker than PC.
We identify and correct errors in the literature …
Perceptions Of Planned Versus Unplanned Malfunctions: A Human-Robot Interaction Scenario, Theresa T. Kessler, Keith R. Macarthur, Manuel Trujillo-Silva, Thomas Macgillivray, Chris Ripa, Peter A. Hancock
Perceptions Of Planned Versus Unplanned Malfunctions: A Human-Robot Interaction Scenario, Theresa T. Kessler, Keith R. Macarthur, Manuel Trujillo-Silva, Thomas Macgillivray, Chris Ripa, Peter A. Hancock
Keith Reid MacArthur
Formal Performance Guarantees For Behavior-Based Localization Missions, Damian Lyons, Ron Arkin, Shu Jiang, Matt O'Brien, Feng Tang, Peng Tang
Formal Performance Guarantees For Behavior-Based Localization Missions, Damian Lyons, Ron Arkin, Shu Jiang, Matt O'Brien, Feng Tang, Peng Tang
Faculty Publications
Abstract— Localization and mapping algorithms can allow a robot to navigate well in an unknown environment. However, whether such algorithms enhance any specific robot mission is currently a matter for empirical validation. In this paper we apply our MissionLab/VIPARS mission design and verification approach to an autonomous robot mission that uses probabilistic localization software.
Two approaches to modeling probabilistic localization for verification are presented: a high-level approach, and a sample-based approach which allows run-time code to be embedded in verification. Verification and experimental validation results are presented for two different missions, each using each method, demonstrating the accuracy …
Landmark Detection With Surprise Saliency Using Convolutional Neural Networks, Feng Tang, Damian Lyons, Daniel Leeds
Landmark Detection With Surprise Saliency Using Convolutional Neural Networks, Feng Tang, Damian Lyons, Daniel Leeds
Faculty Publications
Abstract—Landmarks can be used as reference to enable people or robots to localize themselves or to navigate in their environment. Automatic definition and extraction of appropriate landmarks from the environment has proven to be a challenging task when pre-defined landmarks are not present. We propose a novel computational model of automatic landmark detection from a single image without any pre-defined landmark database. The hypothesis is that if an object looks abnormal due to its atypical scene context (what we call surprise saliency), it then may be considered as a good landmark because it is unique and easy to spot by …
Interactive Logical Analysis Of Planning Domains, Rajesh Kalyanam
Interactive Logical Analysis Of Planning Domains, Rajesh Kalyanam
Open Access Dissertations
Humans exhibit a significant ability to answer a wide range of questions about previously unencountered planning domains, and leverage this ability to construct “general-purpose'' solution plans for the domain.
The long term vision of this research is to automate this ability, constructing a system that utilizes reasoning to automatically verify claims about a planning domain. The system would use this ability to automatically construct and verify a generalized plan to solve any planning problem in the domain. The goal of this thesis is to start with baseline results from the interactive verification of claims about planning domains and develop the …
Vision-Based Motion For A Humanoid Robot, Khalid Abdullah Alkhulayfi
Vision-Based Motion For A Humanoid Robot, Khalid Abdullah Alkhulayfi
Dissertations and Theses
The overall objective of this thesis is to build an integrated, inexpensive, human-sized humanoid robot from scratch that looks and behaves like a human. More specifically, my goal is to build an android robot called Marie Curie robot that can act like a human actor in the Portland Cyber Theater in the play Quantum Debate with a known script of every robot behavior. In order to achieve this goal, the humanoid robot need to has degrees of freedom (DOF) similar to human DOFs. Each part of the Curie robot was built to achieve the goal of building a complete humanoid …
Climbing Up Cloud Nine: Performance Enhancement Techniques For Cloud Computing Environments, Mohamed Abusharkh
Climbing Up Cloud Nine: Performance Enhancement Techniques For Cloud Computing Environments, Mohamed Abusharkh
Electronic Thesis and Dissertation Repository
With the transformation of cloud computing technologies from an attractive trend to a business reality, the need is more pressing than ever for efficient cloud service management tools and techniques. As cloud technologies continue to mature, the service model, resource allocation methodologies, energy efficiency models and general service management schemes are not yet saturated. The burden of making this all tick perfectly falls on cloud providers. Surely, economy of scale revenues and leveraging existing infrastructure and giant workforce are there as positives, but it is far from straightforward operation from that point. Performance and service delivery will still depend on …
Inferring Intrinsic Beliefs Of Digital Images Using A Deep Autoencoder, Seok H. Lee
Inferring Intrinsic Beliefs Of Digital Images Using A Deep Autoencoder, Seok H. Lee
Computer Science and Computer Engineering Undergraduate Honors Theses
Training a system of artificial neural networks on digital images is a big challenge. Often times digital images contain a large amount of information and values for artificial neural networks to understand. In this work, the inference model is proposed in order to absolve this problem. The inference model is composed of a parameterized autoencoder that endures the loss of information caused by the rescaling of images and transition model that predicts the effect of an action on the observation. To test the inference model, the images of a moving robotic arm were given as the data set. The inference …
Efficient Algorithms For Clustering Polygonal Obstacles, Sabbir Kumar Manandhar
Efficient Algorithms For Clustering Polygonal Obstacles, Sabbir Kumar Manandhar
UNLV Theses, Dissertations, Professional Papers, and Capstones
Clustering a set of points in Euclidean space is a well-known problem having applications in pattern recognition, document image analysis, big-data analytics, and robotics. While there are a lot of research publications for clustering point objects, only a few articles have been reported for clustering a given distribution of obstacles. In this thesis we examine the development of efficient algorithms for clustering a given set of convex obstacles in the 2D plane. One of the methods presented in this work uses a Voronoi diagram to extract obstacle clusters. We also consider the implementation issues of point/obstacle clustering algorithms.
Front Matter: Proceedings Of The Maics 2016 Conference, University Of Dayton
Front Matter: Proceedings Of The Maics 2016 Conference, University Of Dayton
Content presented at the MAICS conference
Front matter contains:
- A list of program chairs and committee members
- Foreword to the proceedings by James P. Buckley, conference chair; Saverio Perugini, general chair
Editors: Phu H. Phung, University of Dayton; Ju Shen, University of Dayton; Michael Glass, Valparaiso University
Learning In Vision And Robotics, Daniel P. Barrett
Learning In Vision And Robotics, Daniel P. Barrett
Open Access Dissertations
I present my work on learning from video and robotic input. This is an important problem, with numerous potential applications. The use of machine learning makes it possible to obtain models which can handle noise and variation without explicitly programming them. It also raises the possibility of robots which can interact more seamlessly with humans rather than only exhibiting hard-coded behaviors. I will present my work in two areas: video action recognition, and robot navigation. First, I present a video action recognition method which represents actions in video by sequences of retinotopic appearance and motion detectors, learns such models automatically …
Grounding Robot Motion In Natural Language And Visual Perception, Scott Alan Bronikowski
Grounding Robot Motion In Natural Language And Visual Perception, Scott Alan Bronikowski
Open Access Dissertations
The current state of the art in military and first responder ground robots involves heavy physical and cognitive burdens on the human operator while taking little to no advantage of the potential autonomy of robotic technology. The robots currently in use are rugged remote-controlled vehicles. Their interaction modalities, usually utilizing a game controller connected to a computer, require a dedicated operator who has limited capacity for other tasks.
I present research which aims to ease these burdens by incorporating multiple modes of robotic sensing into a system which allows humans to interact with robots through a natural-language interface. I conduct …
Pedestrian Detection Using Basic Polyline: A Geometric Framework For Pedestrian Detection, Liang Gongbo
Pedestrian Detection Using Basic Polyline: A Geometric Framework For Pedestrian Detection, Liang Gongbo
Masters Theses & Specialist Projects
Pedestrian detection has been an active research area for computer vision in recently years. It has many applications that could improve our lives, such as video surveillance security, auto-driving assistance systems, etc. The approaches of pedestrian detection could be roughly categorized into two categories, shape-based approaches and appearance-based approaches. In the literature, most of approaches are appearance-based. Shape-based approaches are usually integrated with an appearance-based approach to speed up a detection process.
In this thesis, I propose a shape-based pedestrian detection framework using the geometric features of human to detect pedestrians. This framework includes three main steps. Give a static …
Human-Robot Versus Human-Human Relationship Impact On Comfort Levels Regarding In Home Privacy, Keith R. Macarthur, Thomas G. Macgillivray, Eva L. Parkhurst, Peter A. Hancock
Human-Robot Versus Human-Human Relationship Impact On Comfort Levels Regarding In Home Privacy, Keith R. Macarthur, Thomas G. Macgillivray, Eva L. Parkhurst, Peter A. Hancock
Keith Reid MacArthur
Representation And Analysis Of Multi-Modal, Nonuniform Time Series Data: An Application To Survival Prognosis Of Oncology Patients In An Outpatient Setting, Jennifer Winikus
Representation And Analysis Of Multi-Modal, Nonuniform Time Series Data: An Application To Survival Prognosis Of Oncology Patients In An Outpatient Setting, Jennifer Winikus
Dissertations, Master's Theses and Master's Reports
The representation of nonuniform, multi-modal, time-limited time series data is complex and explored through the use of discrete representation, dimensionality reduction with segmentation based techniques, and with behavioral representation approaches. These explorations are done with a focus on an outpatient oncology setting with the classification and regression analysis being used for length of survival prognosis. Each decision of representation and analysis is not independent, with implications of each decision in method for how the data is represented and then which analysis technique is used. One unique aspect of the work is the use of outpatient clinical data for patients, which …
Neuron Clustering For Mitigating Catastrophic Forgetting In Supervised And Reinforcement Learning, Benjamin Frederick Goodrich
Neuron Clustering For Mitigating Catastrophic Forgetting In Supervised And Reinforcement Learning, Benjamin Frederick Goodrich
Doctoral Dissertations
Neural networks have had many great successes in recent years, particularly with the advent of deep learning and many novel training techniques. One issue that has affected neural networks and prevented them from performing well in more realistic online environments is that of catastrophic forgetting. Catastrophic forgetting affects supervised learning systems when input samples are temporally correlated or are non-stationary. However, most real-world problems are non-stationary in nature, resulting in prolonged periods of time separating inputs drawn from different regions of the input space.
Reinforcement learning represents a worst-case scenario when it comes to precipitating catastrophic forgetting in neural networks. …
Using Eye And Head Movements As A Control Mechanism For Tele-Operating A Ground-Based Robot And Its Payload, Kathryn C. Hicks
Using Eye And Head Movements As A Control Mechanism For Tele-Operating A Ground-Based Robot And Its Payload, Kathryn C. Hicks
Computational Modeling & Simulation Engineering Theses & Dissertations
To date, eye and head tracking has been used to indicate users' attention patterns while performing a task or as an aid for disabled persons, to allow hands-free interaction with a computer. The increasing accuracy and the reduced cost of eye- and head-tracking equipment make utilizing this technology feasible for explicit control tasks, especially in cases where there is confluence between the visual task and control.
The goal of this research was to investigate the use of eye-tracking as a more natural interface for the control of a camera-equipped, remotely operated robot in tasks that require the operator to simultaneously …
An Intelligent Attitude Determination And Control System Concept For A Cubesat Class Spacecraft, Jeremy Straub
An Intelligent Attitude Determination And Control System Concept For A Cubesat Class Spacecraft, Jeremy Straub
Jeremy Straub
An attitude determination and control system (ADCS) is used to orient a spacecraft for a wide variety of purposes (e.g., to keep a camera facing Earth or orient the spacecraft for propulsion system use). The proposed intelligent ADCS has several key features: first, it can be used in multiple modes, spanning from passive stabilization of two axes and unconstrained spin on a third to three-axis full active stabilization. It also includes electromagnetic components to ‘dump’ spin from the reaction wheels. Second, the ADCS utilizes an incorporated autonomous control algorithm to characterize the effect of actuation of the system components and, …
Towards Real-Time, On-Board, Hardware-Supported Sensor And Software Health Management For Unmanned Aerial Systems, Johann M. Schumann, Kristin Y. Rozier, Thomas Reinbacher, Ole J. Mengshoel, Timmy Mbaya, Corey Ippolito
Towards Real-Time, On-Board, Hardware-Supported Sensor And Software Health Management For Unmanned Aerial Systems, Johann M. Schumann, Kristin Y. Rozier, Thomas Reinbacher, Ole J. Mengshoel, Timmy Mbaya, Corey Ippolito
Ole J Mengshoel
Two Correspondence Problems Easier Than One, Aaron Michaux, Zygmunt Pizlo
Two Correspondence Problems Easier Than One, Aaron Michaux, Zygmunt Pizlo
MODVIS Workshop
Computer vision research rarely makes use of symmetry in stereo reconstruction despite its established importance in perceptual psychology. Such stereo reconstructions produce visually satisfying figures with precisely located points and lines, even when input images have low or moderate resolution. However, because few invariants exist, there are no known general approaches to solving symmetry correspondence on real images. The problem is significantly easier when combined with the binocular correspondence problem, because each correspondence problem provides strong non-overlapping constraints on the solution space. We demonstrate a system that leverages these constraints to produce accurate stereo models from pairs of binocular images …
Supervisory Control And Data Acquisition (Scada) Control Optimization, Garrett Johnson, Jeremy Straub, Eunjin Kim
Supervisory Control And Data Acquisition (Scada) Control Optimization, Garrett Johnson, Jeremy Straub, Eunjin Kim
Jeremy Straub
SCADA systems are generally used to monitor and control multiple systems of the same type to allow them to be remotely controlled and monitored. Water plants, for example, could be controlled and monitored by a SCADA system. This project seeks to optimize a SCADA system using Artificial Intelligence. A constraint satisfaction / optimization algorithm is used to maximize performance relative to weighted system goals.
An Onboard Distributed Multiprocessing System For A Cubesat Spacecraft Created From Gumstix Computer-On-Module Units, Michael Wegerson, Jeremy Straub, Ronald Marsh
An Onboard Distributed Multiprocessing System For A Cubesat Spacecraft Created From Gumstix Computer-On-Module Units, Michael Wegerson, Jeremy Straub, Ronald Marsh
Jeremy Straub
The OpenOrbiter Small Spacecraft Development Initiative at the University of North Dakota [1] aims to make ac-cess to space for research and educational purposes easier by enabling the creation of low-cost CubeSats. It is creating the Open Prototype for Educational Nanosats (OPEN), a framework for developing a 1-U CubeSat space-craft with a parts cost of less than $5,000 [2]. The designs [3], documentation and computer code from this will be made publically available to enable the development of programs at other institutions.
Considering Scheduling Algorithms For An Open Source Software Spacecraft, Calvin Bina, Jeremy Straub, Ronald Marsh
Considering Scheduling Algorithms For An Open Source Software Spacecraft, Calvin Bina, Jeremy Straub, Ronald Marsh
Jeremy Straub
The OpenOrbiter Small Satellite Development Initiative at the University of North Dakota [1] is working make space research and education more accessible world-wide [2], through the design and public release of a complete set of plans, software and other documents (see [3]) for a 1-U CubeSat. This design targets a parts cost of no more than $5,000 [4]. These lowered costs, combined with the efficiencies of the CubeSat form fac-tor [5] and free-to-qualified-developer launch services [6, 7] should facilitate greater access to space for the ed-ucational, research and other communities.