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Artificial Intelligence and Robotics Commons

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Real-Time Vision-Based Lane Detection With 1d Haar Wavelet Transform On Raspberry Pi, Vikas Reddy Sudini 2017 Utah State University

Real-Time Vision-Based Lane Detection With 1d Haar Wavelet Transform On Raspberry Pi, Vikas Reddy Sudini

All Graduate Theses and Dissertations

Rapid progress is being made towards the realization of autonomous cars. Since the technology is in its early stages, human intervention is still necessary in order to ensure hazard-free operation of autonomous driving systems. Substantial research efforts are underway to enhance driver and passenger safety in autonomous cars. Toward that end GreedyHaarSpiker, a real-time vision-based lane detection algorithm is proposed for road lane detection in different weather conditions. The algorithm has been implemented in Python 2.7 with OpenCV 3.0 and tested on a Raspberry Pi 3 Model B ARMv8 1GB RAM coupled to a Raspberry Pi camera board ...


Detection And Recognition Of Traffic Signs Inside The Attentional Visual Field Of Drivers, Seyedjamal Zabihi 2017 The University of Western Ontario

Detection And Recognition Of Traffic Signs Inside The Attentional Visual Field Of Drivers, Seyedjamal Zabihi

Electronic Thesis and Dissertation Repository

Traffic sign detection and recognition systems are essential components of Advanced Driver Assistance Systems and self-driving vehicles. In this contribution we present a vision-based framework which detects and recognizes traffic signs inside the attentional visual field of drivers. This technique takes advantage of the driver's 3D absolute gaze point obtained through the combined use of a front-view stereo imaging system and a non-contact 3D gaze tracker. We used a linear Support Vector Machine as a classifier and a Histogram of Oriented Gradient as features for detection. Recognition is performed by using Scale Invariant Feature Transforms and color information. Our ...


Vision-Based Mobile Robotic Platform For Autonomous Landing Of Quadcopters, Timothy R. Joe 2017 University of Nebraska at Omaha

Vision-Based Mobile Robotic Platform For Autonomous Landing Of Quadcopters, Timothy R. Joe

Student Research and Creative Activity Fair

This project deals with the development of a vision-based control algorithm to assist quadcopters in the landing process. For demonstration purposes, the approach has been implemented in a mobile robotic platform (turtlebot). In this project, the objective is to use the mobile robot as a landing platform. The camera on-board the mobile robot detects the quadcopter (AprilTag attached to the flying robot) and keeps track of it. Based on this idea, the proposed approach estimates in real-time the landing zone. Once this zone is calculated, the mobile robot moves towards this area, stops under the quadcopter, and acts as a ...


Passive Chemical Detection System For Uavs, John Hare 2185222 2017 University of Nebraska at Omaha

Passive Chemical Detection System For Uavs, John Hare 2185222

Student Research and Creative Activity Fair

In this project we address the problem of autonomously detecting airborne gas particles using gas sensors that are mobilized using unmanned aerial vehicles (UAVs). The main hypothesis we investigate is whether a commercially available, off-the-shelf gas sensor can be suitably integrated on a UAV platform to detect ambient gas particles. The main challenges in this problem include addressing the weight constraints of the UAV’s payload and registering a consistent reading on the gas sensor in the presence of the turbulence in the air caused by the UAV’s rotors. To verify our hypothesis, we designed a passive funneling mechanism ...


A Modular Robotic System For Assessment And Exercise Of Human Movement, Mohan Sai Ambati 2017 University of Nebraska at Omaha

A Modular Robotic System For Assessment And Exercise Of Human Movement, Mohan Sai Ambati

Student Research and Creative Activity Fair

This project targets the problem of developing a wearable modular robotic system, for assessing human movement and providing different types of exercises for the user. The system attempts to provide not only a variety of exercises (concentric, eccentric, assisted and resisted), but also to assess the change in variability of the movement as the subject shows functional improvement. The system will not only be useful for patients with sensorimotor problem such as stroke, Parkinson’s, cerebral palsy, but also for special populations such as astronauts who spend long periods of time in space and experience muscle atrophy. In this work ...


Using Supervised Learning To Compensate For High Latency In Planetary Exploration, Andrew Jones, Jeremy Straub 2017 North Dakota State University--Fargo

Using Supervised Learning To Compensate For High Latency In Planetary Exploration, Andrew Jones, Jeremy Straub

Jeremy Straub

Planetary exploration utilizes orbital, aerial, surface and potentially sub-surface vehicles at remote locations. At present, many of these vehicles must be teleoperated or commanded from Earth, requiring data to be transmitted over significant distances (taking several minutes or longer). This problem gets progressively more pronounced as vehicles are operated further and further from the Earth. While missions to send humans to deep space and increased autonomy both prospectively present partial solutions to this challenge, human controllers may wish to operate the vehicle with an experience more akin to in-situ exploration.

Typically, using remotely operated vehicles for exploring planets entails dealing ...


Exploring Algorithms To Recognize Similar Board States In Arimaa, Malik Khaleeque Ahmed 2017 Rowan University

Exploring Algorithms To Recognize Similar Board States In Arimaa, Malik Khaleeque Ahmed

Theses and Dissertations

The game of Arimaa was invented as a challenge to the field of game-playing artificial intelligence, which had grown somewhat haughty after IBM's supercomputer Deep Blue trounced world champion Kasparov at chess. Although Arimaa is simple enough for a child to learn and can be played with an ordinary chess set, existing game-playing algorithms and techniques have had a difficult time rising up to the challenge of defeating the world's best human Arimaa players, mainly due to the game's impressive branching factor. This thesis introduces and analyzes new algorithms and techniques that attempt to recognize similar board ...


Malware Detection Using The Index Of Coincidence, Bhavna Gurnani 2017 San Jose State University

Malware Detection Using The Index Of Coincidence, Bhavna Gurnani

Master's Projects

In this research, we apply the Index of Coincidence (IC) to problems in malware analysis. The IC, which is often used in cryptanalysis of classic ciphers, is a technique for measuring the repeat rate in a string of symbols. A score based on the IC is applied to a variety of challenging malware families. We nd that this relatively simple IC score performs surprisingly well, with superior results in comparison to various machine learning based scores, at least in some cases.


Return On Investment Of The Cftp Framework With And Without Risk Assessment, Anne Lim Lee 2017 Walden University

Return On Investment Of The Cftp Framework With And Without Risk Assessment, Anne Lim Lee

Walden Dissertations and Doctoral Studies

In recent years, numerous high tech companies have developed and used technology roadmaps when making their investment decisions. Jay Paap has proposed the Customer Focused Technology Planning (CFTP) framework to draw future technology roadmaps. However, the CFTP framework does not include risk assessment as a critical factor in decision making. The problem addressed in this quantitative study was that high tech companies are either losing money or getting a much smaller than expected return on investment when making technology investment decisions. The purpose of this research was to determine the relationship between returns on investment before and after adding risk ...


Explorations Into Machine Learning Techniques For Precipitation Nowcasting, Aditya Nagarajan 2017 University of Massachusetts - Amherst

Explorations Into Machine Learning Techniques For Precipitation Nowcasting, Aditya Nagarajan

Masters Theses May 2014 - current

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 ...


On Relation Between Constraint Answer Set Programming And Satisfiability Modulo Theories, Yuliya Lierler, Benjamin Susman 2016 University of Nebraska at Omaha

On Relation Between Constraint Answer Set Programming And Satisfiability Modulo Theories, Yuliya Lierler, Benjamin Susman

Yuliya Lierler

Constraint answer set programming is a promising research direction that integrates answer set programming with constraint processing. It is often informally related to the field of Satisfiability Modulo Theories. Yet, the exact formal link is obscured as the terminology and concepts used in these two research areas differ. In this paper, by connecting these two areas, we begin the cross-fertilization of not only of the theoretical foundations of both areas but also of the existing solving technologies.


Constraint Answer Set Solver Ezcsp And Why Integration Schemas Matter, 2016 Selected Works

Constraint Answer Set Solver Ezcsp And Why Integration Schemas Matter

Yuliya Lierler

Researchers in answer set programming and constraint programming have spent significant efforts in the development of hybrid languages and solving algorithms combining the strengths of these traditionally separate fields. These efforts resulted in a new research area: constraint answer set programming. Constraint answer set programming languages and systems proved to be successful at providing declarative, yet efficient solutions to problems involving hybrid reasoning tasks. One of the main contributions of this paper is the first comprehensive account of the constraint answer set language and solver EZCSP, a mainstream representative of this research area that has been used in various successful ...


Rationality, Parapsychology, And Artificial Intelligence In Military And Intelligence Research By The United States Government In The Cold War, Guy M. LoMeo 2016 CUNY Hunter College

Rationality, Parapsychology, And Artificial Intelligence In Military And Intelligence Research By The United States Government In The Cold War, Guy M. Lomeo

School of Arts & Sciences Theses

A study analyzing the roles of rationality, parapsychology, and artificial intelligence in military and intelligence research by the United States Government in the Cold War. An examination of the methodology behind the decisions to pursue research in two fields that were initially considered irrational.


Evaluating Machine Learning Classifiers For Defensive Cyber Operations, Michael D. Rich, Robert F. Mills, Thomas E. Dube, Steven K. Rogers 2016 Air Force Institute of Technology

Evaluating Machine Learning Classifiers For Defensive Cyber Operations, Michael D. Rich, Robert F. Mills, Thomas E. Dube, Steven K. Rogers

Military Cyber Affairs

Today’s defensive cyber sensors are dominated by signature-based analytical methods that require continuous maintenance and lack the ability to detect unknown threats. Anomaly detection offers the ability to detect unknown threats, but despite over 15 years of active research, the operationalization of anomaly detection and machine learning for Defensive Cyber Operations (DCO) is lagging. This article provides an introduction to machine learning concepts with a focus on the unique challenges to using machine learning for DCO. Traditional machine learning evaluation methods are challenged in favor of a value-focused evaluation method that incorporates evaluator-specific weights for classifier and sensitivity threshold ...


Real-Time Online Chinese Character Recognition, Wenlong Zhang 2016 San Jose State University

Real-Time Online Chinese Character Recognition, Wenlong Zhang

Master's Projects

In this project, I built a web application for handwritten Chinese characters recognition in real time. This system determines a Chinese character while a user is drawing/writing it. The techniques and steps I use to build the recognition system include data preparation, preprocessing, features extraction, and classification. To increase the accuracy, two different types of neural networks ared used in the system: a multi-layer neural network and a convolutional neural network.


Artificially Intelligent Robots Modelled After Ants, Haley L. Fletcher 2016 Loyola Marymount University

Artificially Intelligent Robots Modelled After Ants, Haley L. Fletcher

Research & Exhibition

In the field of computer science I propose to create three artificially intelligent robots that are able to find food in the same way that ants do. I want the robots to have the capability to communicate with each other, to recognize food, and to be able to find food from solely communication with the other robots.


On Path Consistency For Binary Constraint Satisfaction Problems, Christopher G. Reeson 2016 University of Nebraska - Lincoln

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

Computer Science and Engineering: Theses, Dissertations, 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 2016 University of Nebraska-Lincoln

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

Computer Science and Engineering: Theses, Dissertations, 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 ...


Indoor Scene Localization To Fight Sex Trafficking In Hotels, Abigail Stylianou 2016 Washington University in St. Louis

Indoor Scene Localization To Fight Sex Trafficking In Hotels, Abigail Stylianou

Engineering and Applied Science Theses & Dissertations

Images are key to fighting sex trafficking. They are: (a) used to advertise for sex services,(b) shared among criminal networks, and (c) connect a person in an image to the place where the image was taken. This work explores the ability to link images to indoor places in order to support the investigation and prosecution of sex trafficking. We propose and develop a framework that includes a database of open-source information available on the Internet, a crowd-sourcing approach to gathering additional images, and explore a variety of matching approaches based both on hand-tuned features such as SIFT and learned ...


Investigating High Speed Localization Microscopy Through Experimental Methods, Data Processing Methods, And Applications Of Localization Microscopy To Biological Questions, Andrew J. Nelson 2016 University of Maine

Investigating High Speed Localization Microscopy Through Experimental Methods, Data Processing Methods, And Applications Of Localization Microscopy To Biological Questions, Andrew J. Nelson

Electronic Theses and Dissertations

Fluorescence Photoactivation Localization Microscopy(FPALM) and other super resolution localization microscopy techniques can resolve structures with nanoscale resolution. Unlike techniques of electron microscopy, they are also compatible with live cell and live animal studies, making FPALM and related techniques ideal for answering questions about the dynamic nature of molecular biology in living systems. Many processes in biology occur on rapid sub second time scales requiring the imaging technique to be capable of resolving these processes not just with a high enough spatial resolution, but with an appropriate temporal resolution. To that end, this Dissertation in part investigates high speed FPALM ...


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