Physical Sciences and Mathematics Commons^™

Prepositional Phrase Attachment Problem Revisited: How Verbnet Can Help, Dan Bailey, Yuliya Lierler, Benjamin Susman

Yuliya Lierler

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

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.

Work Done On The Operating Software For Openorbiter, Dayln Limesand, Timothy Whitney, Jeremy Straub, Ronald Marsh

Jeremy Straub

The OpenOrbiter Program aims to develop a tem-plate for a CubeSat spacecraft that can be used world-wide to reduce spacecraft development costs1. Unlike other approaches, which may require $50,000 in upfront hardware costs2 or $250,000 in design expenses2, an OPEN-class spacecraft can be built with a parts budget of under $5,0003. This aims to enable low-cost educa-tional missions and missions in developing regions4.

Detecting Failures In Space Solar Power Systems With Pattern Recognition, Allen Mcdermott, Cameron Kerbaugh, Jeremy Straub

Jeremy Straub

This poster covers work relating to the use of expert systems and pattern recognition to attempt to identify, detect and prospectively stop patterns of activity that could potentially lead to failure of a space solar power (SSP) system. A database-based expert system has is presented to identify patterns, which can be used to determine whether a power beam could hit a unintend-ed target and potentially cause a calamity. This has been implemented via a facts-rule network via which supplied and collected facts and a rule set is used to de-termine whether the system is operating correctly (from a holistic perspective). …

An Expert System For Microwave Wireless Power Transmission Failure Prevention, Cameron Kerbaugh, Allen Mcdermott, Jeremy Straub

Jeremy Straub

Wireless power transfer (WPT) can be used to deliver space-generated power to ground stations through the use of microwave beams. WPT satellite power delivery systems have two major failure states: misdi-recting a beam and failing to send power to a station. This project has implemented an expert system to perform pattern recognition in an effort to prevent failures by analyzing the system state and predicting potential failures before they happen in support of space-based testing [1] and deployment [2].

Trajectory Generation For Lane-Change Maneuver Of Autonomous Vehicles, Ashesh Goswami

Open Access Theses

Lane-change maneuver is one of the most thoroughly investigated automatic driving operations that can be used by an autonomous self-driving vehicle as a primitive for performing more complex operations like merging, entering/exiting highways or overtaking another vehicle. This thesis focuses on two coherent problems that are associated with the trajectory generation for lane-change maneuvers of autonomous vehicles in a highway scenario: (i) an effective velocity estimation of neighboring vehicles under different road scenarios involving linear and curvilinear motion of the vehicles, and (ii) trajectory generation based on the estimated velocities of neighboring vehicles for safe operation of self-driving cars during …

Securing Communication Within The Harms Model For Use With Firefighting Robots, Maxwell D. Dewees

Open Access Theses

Humans and robots must work together in increasingly complex networks to achieve a common goal. In this research, firefighting robots are a part of a larger, decentralized system of humans, agents, robots, machines, and sensors (HARMS). Although communication in a HARMS model has been utilized in previous research, this new study looks at the security considerations of the communications layer of the HARMS model. A network attack known as a man-in-the-middle attack is successfully demonstrated in this paper. Then, a secure communications protocol is proposed to help provide confidentiality and authentication of HARMS actors. This research is applied to any …

Improving Product Design Phase For Engineer To Order (Eto) Product With Knowledge Base Engineering (Kbe), Hanhdung Thi Dinh

Open Access Theses

In industry currently Computer Aided Design (CAD) is an important tool for the modification, analysis, or optimization of the 3D virtual environment that replicates the physical product. CAD software is an efficient and reliable tool. However, as globalization increases customer demands, this process needs to be faster and more efficient to accommodate changing product design situations, especially for Engineer-to- Order (ETO) products. ^ The traditional method of product design process is to operate CAD software without argumentation. Design engineers create CAD prototypes and drawings based on available knowledge and information which comes from engineering experts, company standards, industrial practices as …

Exploring Cyberbullying And Other Toxic Behavior In Team Competition Online Games, Haewoon Kwak, Jeremy Blackburn, Seungyeop. Han

Research Collection School Of Computing and Information Systems

In this work we explore cyberbullying and other toxic behavior in team competition online games. Using a dataset of over 10 million player reports on 1.46 million toxic players along with corresponding crowdsourced decisions, we test several hypotheses drawn from theories explaining toxic behavior. Besides providing large-scale, empirical based understanding of toxic behavior, our work can be used as a basis for building systems to detect, prevent, and counter-act toxic behavior.

Reflective, Deliberative Agent-Based Information Gathering, Adam D. Eck

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

As computational devices and entities become further established as routine, omnipresent components of our everyday lives (e.g., wearable sensors, smart homes, cyber-physical systems, embodied agents, human-robot interactions), such systems face an increased pressure to perpetually understand the complex, noisy, uncertain world around them in real-time. This environmental knowledge enables computational systems to intelligently decide how to best behave in response to the current situation, adapt to the ever-changing conditions of the dynamic world, and accomplish system goals that ultimately aim to improve our daily experience. However, achieving and maintaining such knowledge is very complicated due to the complexities and challenging …

Theory Identity: A Machine-Learning Approach, Kai Larsen, Dirk Hovorka, Jevin West, James Birt, James Pfaff, Trevor Chambers, Zebula Sampedro, Nick Zager, Bruce Vanstone

Bruce Vanstone

Theory identity is a fundamental problem for researchers seeking to determine theory quality, create theory ontologies and taxonomies, or perform focused theory-specific reviews and meta-analyses. We demonstrate a novel machine-learning approach to theory identification based on citation data and article features. The multi-disciplinary ecosystem of articles which cite a theory's originating paper is created and refined into the network of papers predicted to contribute to, and thus identify, a specific theory. We provide a 'proof-of-concept' for a highly-cited theory. Implications for crossdisciplinary theory integration and the identification of theories for a rapidly expanding scientific literature are discussed.

Tactical Ai In Real Time Strategy Games, Donald A. Gruber

Theses and Dissertations

The real time strategy (RTS) tactical decision making problem is a difficult problem. It is generally more complex due to its high degree of time sensitivity. This research effort presents a novel approach to this problem within an educational, teaching objective. Particular decision focus is target selection for a artificial intelligence (AI) RTS game model. The use of multi-objective evolutionary algorithms (MOEAs) in this tactical decision making problem allows an AI agent to make fast, effective solutions that do not require modification to the current environment. This approach allows for the creation of a generic solution building tool that is …

The Unified Behavior Framework For The Simulation Of Autonomous Agents, Daniel M. Roberson

Theses and Dissertations

Since the 1980s, researchers have designed a variety of robot control architectures intending to imbue robots with some degree of autonomy. A recently developed architecture, the UBF, implements a variation of the three-layer architecture with a reactive controller to rapidly make behavior decisions. Additionally, the UBF utilizes software design patterns that promote the reuse of code and free designers to dynamically switch between behavior paradigms. This paper explores the application of the UBF to the simulation domain. By employing software engineering principles to implement the UBF architecture within an open-source simulation framework, we have extended the versatility of both. The …

Unified Behavior Framework For Discrete Event Simulation Systems, Alexander J. Kamrud

Theses and Dissertations

Intelligent agents provide simulations a means to add lifelike behavior in place of manned entities. Generally when developed, a single intelligent agent model is chosen, such as rule based, behavior trees, etc. This choice introduces restrictions into what behaviors agents can manifest, and can require significant testing in edge cases. This thesis presents the use of the UBF in the AFSIM environment. The UBF provides the flexibility to implement any and all intelligent agent models, allowing the developer to choose the model he/she feels best fits the experiment at hand. Furthermore, the UBF demonstrates several key software engineering principles through …

Learning Data-Driven Models Of Non-Verbal Behaviors For Building Rapport Using An Intelligent Virtual Agent, Reza Amini

FIU Electronic Theses and Dissertations

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight …

Dependency-Topic-Affects-Sentiment-Lda Model For Sentiment Analysis, Shunshun Yin, Jun Han, Yu Huang, Kuldeep Kumar

Kuldeep Kumar

Sentiment analysis tends to use automated approaches to mine the sentiment information expressed in text, such as reviews, blogs and forum discussions. As most traditional approaches for sentiment analysis are based on supervised learning models and need many labeled corpora as their training data which are not always easily obtained, various unsupervised models based on Latent Dirichlet Allocation (LDA) have been proposed for sentiment classification. In this paper, we propose a novel probabilistic modeling framework based on LDA, called Dependency-Topic-Affects-Sentiment-LDA (DTAS) model, which drops the ”bag of words” assumption and assumes that the topics of sentences in a document form …

Scheduling Algorithm Development For An Open Source Software Spacecraft, Calvin Bina, Jeremy Straub, Ronald Marsh

Jeremy Straub

The OpenOrbiter project at the University of North Dakota is working to develop a set of designs for a CubeSat class spacecraft as well as a working, modular collection of open source code that can be used by other CubeSat projects as a starting point for development. The availability of these designs and this codebase should foster accelerated development for other CubeSat projects, allowing those projects to focus their effort on their own application area, instead of reinventing the proverbial wheel. One aspect of this is to implement a task scheduler which will run on a Raspberry Pi flight computer …

An Overview Of The Openorbiter Autonomous Operating Software, Dayln Limesand, Timothy Whitney, Jeremy Straub, Ronald Marsh

Jeremy Straub

The OpenOrbiter spacecraft aims to demonstrate the efficacy of the Open Prototype for Educational Nanosats (OPEN) framework. Software is an important part of this framework. This paper discusses the operating software for the spacecraft (which runs on top of the Linux operating system to command spacecraft operations). It presents an overview of this software and then pays particular attention to the aspects of software design that enable onboard autonomy. It also discusses the messaging scheme that is used onboard and the testing and validation plan. Finally, it discusses system extensibility, before concluding.

Swarm Intelligence, A Blackboard Architecture And Local Decision Making For Spacecraft Command, Jeremy Straub

Jeremy Straub

Control of a multi-spacecraft constellation is a topic of significant inquiry, at present. This paper presents and evaluates a command architecture for a multi-spacecraft mission. It combines swarm techniques with a decentralized / local decision making architecture (which uses a set of shared blackboards for coordination) and demonstrates the efficacy of this approach. Under this approach, the Blackboard software architecture is used to facilitate data sharing between craft as part of a resilient hierarchy and the swarm techniques are used to coordinate activity. The paper begins with an overview of prior work on the precursor command technologies and then presents …

Using A Constellation Of Cubesats For In-Space Optical 3d Scanning, Jeremy Straub

Jeremy Straub

The assessment of in-space objects is an area of ongoing research. Characterization of resident space objects (RSOs) can be useful for assessing the operating status of operator-affiliated or non-affiliated space assets, identifying unknown objects or gathering additional details for known objects. Under the proposed approach, a ring-like constellation of CubeSats passes around the target (at a distance) collecting imagery. This imagery is then utilized to create a 3D model of the target. This paper considers several key elements of a constellation to perform this type of imaging, including the constellation design and imaging capabilities required and the astrodynamics relevant to …

Experimental Investigation Of Stochastic Parafoil Guidance Using A Graphics Processing Unit, Nathan Slegers, Andrew Brown, Jonathan Rogers

Faculty Publications - Biomedical, Mechanical, and Civil Engineering

Control of autonomous systems subject to stochastic uncertainty is a challenging task. In guided airdrop applications, random wind disturbances play a crucial role in determining landing accuracy and terrain avoidance. This paper describes a stochastic parafoil guidance system which couples uncertainty propagation with optimal control to protect against wind and parameter uncertainty in the presence of impact area obstacles. The algorithm uses real-time Monte Carlo simulation performed on a graphics processing unit (GPU) to evaluate robustness of candidate trajectories in terms of delivery accuracy, obstacle avoidance, and other considerations. Building upon prior theoretical developments, this paper explores performance of the …

Using Infrastructure-Provided Context Filters For Efficient Fine-Grained Activity Sensing, Vigneshwaran Subbaraju, Sougata Sen, Archan Misra, Satyadip Chakraborty, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

While mobile and wearable sensing can capture unique insights into fine-grained activities (such as gestures and limb-based actions) at an individual level, their energy overheads are still prohibitive enough to prevent them from being executed continuously. In this paper, we explore practical alternatives to addressing this challenge-by exploring how cheap infrastructure sensors or information sources (e.g., BLE beacons) can be harnessed with such mobile/wearable sensors to provide an effective solution that reduces energy consumption without sacrificing accuracy. The key idea is that many fine-grained activities that we desire to capture are specific to certain location, movement or background context: infrastructure …

A Proposed Model For The Approach To Augmented Reality Deployment In Marketing Communications, Stephen O'Mahony

Dept. of Marketing & International Business Conference Material

In the contemporary landscape, human interaction is characterized by the pervasive mediation of intelligent agents. Owing to advances in computer science and engineering, phenomena once limited to fixed locations are metamorphosing from extraneous entities to implicit components of the everyday. Computing power has simultaneously enhanced and miniaturized to the extent that contemporary consumer devices demonstrate power equivalent to or greater than that of personal computers of recent memory. At the same time, network connectivity has proliferated to ubiquitous levels, reflected in the fact that the amount of inanimate objects connected to the Internet has recently surpassed the human population of …

A Heuristic Evolutionary Method For The Complementary Cell Suppression Problem, Hira B. Herrington

CCE Theses and Dissertations

Cell suppression is a common method for disclosure avoidance used to protect sensitive information in two-dimensional tables where row and column totals are published along with non-sensitive data. In tables with only positive cell values, cell suppression has been demonstrated to be non-deterministic NP-hard. Therefore, finding more efficient methods for producing low-cost solutions is an area of active research.

Genetic algorithms (GA) have shown to be effective in finding good solutions to the cell suppression problem. However, these methods have the shortcoming that they tend to produce a large proportion of infeasible solutions. The primary goal of this research was …

A Defeasible Reasoning Framework For Human Mental Workload Representation And Assessment, Luca Longo

Conference papers

Human mental workload (MWL) has gained importance in the last few decades as an important design concept. It is a multifaceted complex construct mainly applied in cognitive sciences and has been defined in many different ways. Although measuring MWL has potential advantages in interaction and interface design, its formalisation as an operational and computational construct has not sufficiently been addressed. This research contributes to the body of knowledge by providing an extensible framework built upon defeasible reasoning, and implemented with argumentation theory (AT), in which MWL can be better defined, measured, analysed, explained and applied in different human–computer interactive contexts. …

A Real-Time N-Gram Approach To Choosing Synonyms Based On Context, Brian J. Moore

Electronic Thesis and Dissertation Repository

Synonymy is an important part of all natural language but not all synonyms are created equal. Just because two words are synonymous, it usually doesn’t mean they can always be interchanged. The problem that we attempt to address is that of near-synonymy and choosing the right word based purely on its surrounding words. This new computational method, unlike previous methods used on this problem, is capable of making multiple word suggestions which more accurately models human choice. It contains a large number of words, does not require training, and is able to be run in real-time. On previous testing data, …

Semtiment Analysis On Youtube: A Brief Survey, Dr. Muhammad Zubair Asghar, Fazal Masud Kundi, Afsana Khan

Dr. Muhammad Zubair Asghar

Sentiment analysis or opinion mining is the field of study related to analyze opinions, sentiments, evaluations, attitudes, and emotions of users which they express on social media and other online resources. The revolution of social media sites has also attracted the users towards video sharing sites, such as YouTube. The online users express their opinions or sentiments on the videos that they watch on such sites. This paper presents a brief survey of techniques to analyze opinions posted by users about a particular video.

Introducing Machine Learning Via Baseball's Hall Of Fame, David Hansen

Faculty Publications - Department of Electrical Engineering and Computer Science

Machine Learning via Artificial Neural Networks (ANNs) is often introduced in a one-semester course on Artificial Intelligence. Baseball’s annual Hall of Fame election provides a simple, tractable, data-rich domain for learning how to use ANNs for predictive analytics. We describe how we use the Fast Artificial Neural Network (FANN) toolkit for a course assignment that predicts which players are likely to be elected to Baseball’s Hall of Fame.

Object-Based Classification Of Earthquake Damage From High-Resolution Optical Imagery Using Machine Learning, James Bialas

Dissertations, Master's Theses and Master's Reports - Open

Object-based approaches to the segmentation and supervised classification of remotely-sensed images yield more promising results compared to traditional pixel-based approaches. However, the development of an object-based approach presents challenges in terms of algorithm selection and parameter tuning. Subjective methods and trial and error are often used, but time consuming and yield less than optimal results. Objective methods are warranted, especially for rapid deployment in time sensitive applications such as earthquake induced damage assessment.

Our research takes a systematic approach to evaluating object-based image segmentation and machine learning algorithms for the classification of earthquake damage in remotely-sensed imagery using Trimble’s eCognition …