Artificial Intelligence and Robotics Commons^™

An Unmanned Aerial System For Prescribed Fires, Evan M. Beachly

School of Computing: Dissertations, Theses, and Student Research

Prescribed fires can lessen wildfire severity and control invasive species, but some terrains may be difficult, dangerous, or costly to burn with existing tools. This thesis presents the design of an unmanned aerial system that can ignite prescribed fires from the air, with less cost and risk than with aerial ignition from a manned aircraft. The prototype was evaluated in-lab and successfully used to ignite interior areas of two prescribed fires. Additionally, we introduce an approach that integrates a lightweight fire simulation to autonomously plan safe flight trajectories and suggest effective fire lines. Both components are unique in that they …

Geometry-Based Mass Grading Of Mango Fruits Using Image Processing, M. A. Momin, Md Towfiqur Rahman, M. S. Sultana, C. Igathinathane, A. T. M. Ziauddin, T. E. Grift

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Mango (Mangifera indica) is an important, and popular fruit in Bangladesh. However, the post-harvest processing of it is still mostly performed manually, a situation far from satisfactory, in terms of accuracy and throughput. To automate the grading of mangos (geometry and shape), we developed an image acquisition and processing system to extract projected area, perimeter, and roundness features. In this system, images were acquired using a XGA format color camera of 8-bit gray levels using fluorescent lighting. An image processing algorithm based on region based global thresholding color binarization, combined with median filter and morphological analysis was developed …

Hierarchical Active Learning Application To Mitochondrial Disease Protein Dataset, James D. Duin

School of Computing: Dissertations, Theses, and Student Research

This study investigates an application of active machine learning to a protein dataset developed to identify the source of mutations which give rise to mitochondrial disease. The dataset is labeled according to the protein's location of origin in the cell; whether in the mitochondria or not, or a specific target location in the mitochondria's outer or inner membrane, its matrix, or its ribosomes. This dataset forms a labeling hierarchy. A new machine learning approach is investigated to learn the high-level classifier, i.e., whether the protein is a mitochondrion, by separately learning finer-grained target compartment concepts and combining the results. This …

Aerial Water Sampler, Carrick Detweiler, John-Paul Ore, Baoliang Zhao, Sebastian Elbaum

School of Computing: Faculty Publications

In one aspect, a vehicle includes an aerial propulsion system, an altitude sensor system, a water sampling system, and a control system. The water sampling system includes a water sampling extension configured to extend away from the vehicle, one or more water sample receptacles, and a water pump. The control system is configured to perform operations including: guiding, using the aerial propulsion system, the vehicle over a water Source; causing, using sensor data from the altitude sensor system, the vehicle to descend towards the water source so that the water sampling extension contacts the water source; and causing, using the …

On Path Consistency For Binary Constraint Satisfaction Problems, Christopher G. Reeson

School of Computing: 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 …

Towards Building A Review Recommendation System That Trains Novices By Leveraging The Actions Of Experts, Shilpa Khanal

School of Computing: 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 …

A Visual Analysis Of Articulated Motion Complexity Based On Optical Flow And Spatial-Temporal Features, Beau Michael Christ

School of Computing: Dissertations, Theses, and Student Research

The understanding of motion is an important problem in computer vision with applications including crowd-flow analysis, video surveillance, and estimating three-dimensional structure. A less-explored problem is the visual characterization and quantification of motion complexity. An important motion class that is prevalent in living beings is articulated motion (segments connected by joints). At present, no known standardized measure for quantifying the complexity of articulated motion exists. Such a measure could facilitate advanced motion analysis with applications including video indexing, motion comparison, and advanced biological study of visual signals in organisms.

This dissertation presents an in-depth study of the development of several …

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

School of Computing: 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 …

A Comparative Study Of Underwater Robot Path Planning Algorithms For Adaptive Sampling In A Network Of Sensors, Sreeja Banerjee

School of Computing: Dissertations, Theses, and Student Research

Monitoring lakes, rivers, and oceans is critical to improving our understanding of complex large-scale ecosystems. We introduce a method of underwater monitoring using semi-mobile underwater sensor networks and mobile underwater robots in this thesis. The underwater robots can move freely in all dimension while the sensor nodes are anchored to the bottom of the water column and can move only up and down along the depth of the water column. We develop three different algorithms to optimize the path of the underwater robot and the positions of the sensors to improve the overall quality of sensing of an area of …

Understanding Human Learning Using A Multiagent Based Unified Learning Model Simulation, Vlad T. Chiriacescu

School of Computing: Dissertations, Theses, and Student Research

Within cognitive science, computational modeling based on cognitive architectures has been an important approach to addressing questions of human cognition and learning. Modeling issues such as limited expressivity in representing knowledge and lack of appropriate selection of model structure represent a challenge for existing architectures. Furthermore, latest research shows that the concepts of long-term memory, motivation and working memory are critical cognitive aspects but a unifying cognitive paradigm integrating those concepts hasn’t been previously achieved.

Derived from a synthesis of neuroscience, cognitive science, psychology, and education, the Unified Learning Model (ULM) provides this integration by merging a statistical learning mechanism …

Practical Tractability Of Csps By Higher Level Consistency And Tree Decomposition, Shant Karakashian

School of Computing: Dissertations, Theses, and Student Research

Constraint Satisfaction is a flexible paradigm for modeling many decision problems in Engineering, Computer Science, and Management. Constraint Satisfaction Problems (CSPs) are in general NP-complete and are usually solved with search. Research has identified various islands of tractability, which enable solving certain CSPs with backtrack-free search. For example, one sufficient condition for tractability relates the consistency level of a CSP to treewidth of the CSP's constraint network. However, enforcing higher levels of consistency on a CSP may require the addition of constraints, thus altering the topology of the constraint network and increasing its treewidth. This thesis addresses the following question: …

Identification Of Tcp Protocols, Juan Shao

School of Computing: Dissertations, Theses, and Student Research

Recently, many new TCP algorithms, such as BIC, CUBIC, and CTCP, have been deployed in the Internet. Investigating the deployment statistics of these TCP algorithms is meaningful to study the performance and stability of the Internet. Currently, there is a tool named Congestion Avoidance Algorithm Identification (CAAI) for identifying the TCP algorithm of a web server and then for investigating the TCP deployment statistics. However, CAAI using a simple k-NN algorithm can not achieve a high identification accuracy. In this thesis, we comprehensively study the identification accuracy of five popular machine learning models. We find that the random forest model …

Chatbots In The Library: Is It Time?, Deeann Allison

University of Nebraska-Lincoln Libraries: Faculty Publications

This paper describes a pilot at the University of Nebraska-Lincoln for a chatbot that answers questions about the library and library resources. The chatbot was developed using a SQL database to store the question and answers using Artificial Intelligence Mark-up Language metadata. The user interface was built using PHP, adapted from Program-O. The open source PHP program was modified to support better display and the launching of URLs within the chatbot screen. Database content was created by “mining” library websites for information, and analyzing chat logs.

The chatbot answers questions from a variety of users from around the world. It …

Multiagent Coalition Formation In Uncertain Environments With Type-Changing Influences And Its Application Towards Forming Human Coalitions, Nobel A. Khandaker

School of Computing: Dissertations, Theses, and Student Research

We aim to solve the problem forming multiagent coalitions in uncertain environments where the coalition members’ capability of solving tasks change due to their learning. The MCFP-Mproblem for the agents refers to forming or joining coalitions on behalf of a set of human users so that those human users can solve tasks and improve their types (expertise) to improve their performances over time. MCFP-A problem for a set of agents refers to their forming or joining coalitions so that they are able to solve a set of assigned tasks while optimize their performance over time. We propose the Integrated Human …

Agent Sensing With Stateful Resources, Adam D. Eck

School of Computing: Dissertations, Theses, and Student Research

In many real-world applications of multi-agent systems, agent reasoning suffers from bounded rationality caused by both limited resources and limited knowledge. When agent sensing also requires resource use, the agent’s knowledge revision is affected due to its inability to always sense when and as accurately as needed, further leading to poor decision making. In this research, we consider what happens when sensing activities require the use of stateful resources, which we define as resources whose state-dependent behavior changes over time based on usage. Specifically, sensing itself can change the state of a resource, and thus its behavior, which affects both …

Is Competition Making A Comeback? Discovering Methods To Keep Female Adolescents Engaged In Stem: A Phenomenological Approach, Kathryn B. Notter

College of Education and Human Sciences: Dissertations, Theses, and Student Research

The decreasing number of women who are graduating in the Science, Technology, Engineering and Mathematics (STEM) fields continues to be a major concern. Despite national support in the form of grants provided by National Science Foundation, National Center for Information and Technology and legislation passed such as the Deficit Reduction Act of 2005 that encourages women to enter the STEM fields, the number of women actually graduating in these fields is surprisingly low. This research study focuses on a robotics competition and its ability to engage female adolescents in STEM curricula. Data have been collected to help explain why young …

A First Practical Algorithm For High Levels Of Relational Consistency, Shant Karakashian, Robert J. Woodward, Christopher Reesons, Berthe Y. Choueiry, Christian Bessiere

School of Computing: Conference and Workshop Papers

Consistency properties and algorithms for achieving them are at the heart of the success of Constraint Programming. In this paper, we study the relational consistency property R(∗,m)C, which is equivalent to m-wise consistency proposed in relational databases. We also define wR(∗,m)C, a weaker variant of this property. We propose an algorithm for enforcing these properties on a Constraint Satisfaction Problem by tightening the existing relations and without introducing new ones. We empirically show that wR(∗,m)C solves in a backtrack-free manner all the instances of some CSP benchmark classes, thus hinting at the tractability of those classes.

Cataloging Expert Systems: Optimism And Frustrated Reality, William Olmstadt

E-JASL: Electronic Journal of Academic and Special Librarianship (1999-2009, Volumes 1-10)

There is little question that computers have profoundly changed how information professionals work. The process of cataloging and classifying library materials was one of the first activities transformed by information technology. The introduction of the MARC format in the 1960s and the creation of national bibliographic utilities in the 1970s had a lasting impact on cataloging. In the 1980s, the affordability of microcomputers made the computer accessible for cataloging, even to small libraries. This trend toward automating library processes with computers parallels a broader societal interest in the use of computers to organize and store information. Following World War II, …