Computer Engineering Commons^™

Emergency Landing And Guidance System, Joseph Alarid

Master's Theses

Every year there are thousands of aviation accidents along with hundreds of human deaths that happen around the world. While the data is sparse, it is well documented that many of these happen from emergency landings gone awry. While pilots can generally make great landings in clear daytime conditions, they are significantly handicapped when it comes to landing at night or amongst poor visibility conditions.

Due to the nature of this problem and some of the large scale advances in software technology we propose a solution that provides a significant improvement from the status quo. Using transfer learning on neural …

Traffic Privacy Study On Internet Of Things – Smart Home Applications, Ayan Patel

Master's Theses

Internet of Things (IoT) devices have been widely adopted in many different applications in recent years, such as smart home applications. An adversary can capture the network traffic of IoT devices and analyze it to reveal user activities even if the traffic is encrypted. Therefore, traffic privacy is a major concern, especially in smart home applications. Traffic shaping can be used to obfuscate the traffic so that no meaningful predictions can be drawn through traffic analysis. Current traffic shaping methods have many tunable variables that are difficult to optimize to balance bandwidth overheads and latencies. In this thesis, we study …

Identification Of Users Via Ssh Timing Attack, Thomas J. Flucke

Master's Theses

Secure Shell, a tool to securely access and run programs on a remote machine, is an important tool for both system administrators and developers alike. The technology landscape is becoming increasingly distributed and reliant on tools such as Secure Shell to protect information as a user works on a system remotely. While Secure Shell accounts for the abuses the security of older tools such as telnet overlook, it still has fundamental vulnerabilities which leak information about both the user and their activities through timing attacks. The OpenSSH client, the implementation included in all Linux, Mac, and Windows computers, sends each …

Flexible Fault Tolerance For The Robot Operating System, Sukhman S. Marok

Master's Theses

The introduction of autonomous vehicles has the potential to reduce the number of accidents and save countless lives. These benefits can only be realized if autonomous vehicles can prove to be safer than human drivers. There is a large amount of active research around developing robust algorithms for all parts of the autonomous vehicle stack including sensing, localization, mapping, perception, prediction, planning, and control. Additionally, some of these research projects have involved the use of the Robot Operating System (ROS). However, another key aspect of realizing an autonomous vehicle is a fault-tolerant design that can ensure the safe operation of …

Bootstrapping Massively Multiplayer Online Role Playing Games, Mitchell Miller

Master's Theses

Massively Multiplayer Online Role Playing Games (MMORPGs) are a prominent genre in today's video game industry with the most popular MMORPGs generating billions of dollars in revenue and attracting millions of players. As they have grown, they have become a major target for both technological research and sociological research. In such research, it is nearly impossible to reach the same player scale from any self-made technology or sociological experiments. This greatly limits the amount of control and topics that can be explored. In an effort to make up a lacking or non-existent player-base for custom-made MMORPG research scenarios A.I. agents, …

Dynamic Procedural Music Generation From Npc Attributes, Megan E. Washburn

Master's Theses

Procedural content generation for video games (PCGG) has seen a steep increase in the past decade, aiming to foster emergent gameplay as well as to address the challenge of producing large amounts of engaging content quickly. Most work in PCGG has been focused on generating art and assets such as levels, textures, and models, or on narrative design to generate storylines and progression paths. Given the difficulty of generating harmonically pleasing and interesting music, procedural music generation for games (PMGG) has not seen as much attention during this time.

Music in video games is essential for establishing developers' intended mood …

Decentralized, Noncooperative Multirobot Path Planning With Sample-Basedplanners, William Le

Master's Theses

In this thesis, the viability of decentralized, noncooperative multi-robot path planning algorithms is tested. Three algorithms based on the Batch Informed Trees (BIT*) algorithm are presented. The first of these algorithms combines Optimal Reciprocal Collision Avoidance (ORCA) with BIT*. The second of these algorithms uses BIT* to create a path which the robots then follow using an artificial potential field (APF) method. The final algorithm is a version of BIT* that supports replanning. While none of these algorithms take advantage of sharing information between the robots, the algorithms are able to guide the robots to their desired goals, with the …

Involuntary Signal-Based Grounding Of Civilian Unmanned Aerial Systems (Uas) In Civilian Airspace, Keith Conley

Master's Theses

This thesis investigates the involuntary signal-based grounding of civilian unmanned aerial systems (UAS) in unauthorized air spaces. The technique proposed here will forcibly land unauthorized UAS in a given area in such a way that the UAS will not be harmed, and the pilot cannot stop the landing. The technique will not involuntarily ground authorized drones which will be determined prior to the landing. Unauthorized airspaces include military bases, university campuses, areas affected by a natural disaster, and stadiums for public events. This thesis proposes an early prototype of a hardware-based signal based involuntary grounding technique to handle the problem …

An Application Of Sliding Mode Control To Model-Based Reinforcement Learning, Aaron Thomas Parisi

Master's Theses

The state-of-art model-free reinforcement learning algorithms can generate admissible controls for complicated systems with no prior knowledge of the system dynamics, so long as sufficient (oftentimes millions) of samples are available from the environ- ment. On the other hand, model-based reinforcement learning approaches seek to leverage known optimal or robust control to reinforcement learning tasks by mod- elling the system dynamics and applying well established control algorithms to the system model. Sliding-mode controllers are robust to system disturbance and modelling errors, and have been widely used for high-order nonlinear system control. This thesis studies the application of sliding mode control …

Utilizing Trajectory Optimization In The Training Of Neural Network Controllers, Nicholas Kimball

Master's Theses

Applying reinforcement learning to control systems enables the use of machine learning to develop elegant and efficient control laws. Coupled with the representational power of neural networks, reinforcement learning algorithms can learn complex policies that can be difficult to emulate using traditional control system design approaches. In this thesis, three different model-free reinforcement learning algorithms, including Monte Carlo Control, REINFORCE with baseline, and Guided Policy Search are compared in simulated, continuous action-space environments. The results show that the Guided Policy Search algorithm is able to learn a desired control policy much faster than the other algorithms. In the inverted pendulum …

Smart Dc Wall Outlet Design With Improved Load Voltage Detection, Patrick Donovon Granieri

Master's Theses

A standard home in the United States has access to the 120V AC power grid for use with home appliances. Many electronics used at home are powered by a DC power supply, which loses energy in the conversion from AC power. The DC House project avoids any conversion between AC and DC by storing energy in batteries as DC power and supplying it directly to DC appliances. While AC systems feature a standardized output voltage, no such standard exists for DC systems. The Smart DC Wall Outlet solves this by automatically adjusting its output voltage to meet any required DC …

Multi-Vector Tracking Of Wifi And Zigbee Devices, Calvin Andrew Laverty

Master's Theses

Location privacy preservation has shifted to the forefront of discussions about next generation wireless networks. While pseudonym-changing schemes have been proposed to preserve an individual's privacy, simulation has shown that new association attack models render these schemes useless. The major contribution of this thesis is the implementation of a tracking network with commodity hardware on the California Polytechnic State University campus which leverages the combination of de-anonymization strategies on captured wireless network data to show the effectiveness of a pseudonym-changing scheme for wireless identification across WiFi and Zigbee protocols.

Surveying Underwater Shipwrecks With Probabilistic Roadmaps, Amy Jeannette Lewis

Master's Theses

Almost two thirds of the Earth's surface is covered in ocean, and yet, only about 5% of it is mapped. There are an unknown amount of sunken ships, planes, and other artifacts hidden below the sea. Extensive search via boat and a sonar tow fish following a standard lawnmower pattern is used to identify sites of interest. Then, if a site has been determined to potentially be historically significant, the most common next step is a survey by either a human dive team or remotely operated vehicle. These are time consuming, error prone, and potentially dangerous options, but autonomous underwater …

Evaluating Creative Choice In K-12 Computer Science Curriculum, Kirsten L. Mork

Master's Theses

Computer Science is an increasingly important topic in K-12 education. Ever since the "computing crisis" of the early 2000s, where enrollment in CS dropped by over half in a five year span, increasing research has gone into improving and broadening enrollment in CS courses. Research shows the importance of introducing CS at a young age and the need for more exposure for younger children and young adults alike in order to work towards equity in the field. While there are many reasons for disinterest in CS courses, studies found one reason young adults do not want to study CS is …

Robot Navigation In Cluttered Environments With Deep Reinforcement Learning, Ryan Weideman

Master's Theses

The application of robotics in cluttered and dynamic environments provides a wealth of challenges. This thesis proposes a deep reinforcement learning based system that determines collision free navigation robot velocities directly from a sequence of depth images and a desired direction of travel. The system is designed such that a real robot could be placed in an unmapped, cluttered environment and be able to navigate in a desired direction with no prior knowledge. Deep Q-learning, coupled with the innovations of double Q-learning and dueling Q-networks, is applied. Two modifications of this architecture are presented to incorporate direction heading information that …

A Machine Learning Approach To Network Intrusion Detection System Using K Nearest Neighbor And Random Forest, Ilemona S. Atawodi

Master's Theses

The evolving area of cybersecurity presents a dynamic battlefield for cyber criminals and security experts. Intrusions have now become a major concern in the cyberspace. Different methods are employed in tackling these threats, but there has been a need now more than ever to updating the traditional methods from rudimentary approaches such as manually updated blacklists and whitelists. Another method involves manually creating rules, this is usually one of the most common methods to date.

A lot of similar research that involves incorporating machine learning and artificial intelligence into both host and network-based intrusion systems recently. Doing this originally presented …

Comparison Of Lqr And Lqr-Mrac For Linear Tractor-Trailer Model, Kevin Richard Gasik

Master's Theses

The United States trucking industry is immense. Employing over three million drivers and traveling to every city in the country. Semi-Trucks travel millions of miles each week and encompass roads that civilians travel on. These vehicles should be safe and allow efficient travel for all. Autonomous vehicles have been discussed in controls for many decades. Now fleets of autonomous vehicles are beginning their integration into society. The ability to create an autonomous system requires domain and system specific knowledge. Approaches to implement a fully autonomous vehicle have been developed using different techniques in control systems such as Kalman Filters, Neural …

Relevance Analysis For Document Retrieval, Eric Labouve

Master's Theses

Document retrieval systems recover documents from a dataset and order them according to their perceived relevance to a user’s search query. This is a difficult task for machines to accomplish because there exists a semantic gap between the meaning of the terms in a user’s literal query and a user’s true intentions. Even with this ambiguity that arises with a lack of context, users still expect that the set of documents returned by a search engine is both highly relevant to their query and properly ordered. The focus of this thesis is on document retrieval systems that explore methods of …

Assessing Risk In Iot Devices, David Levitsky

Master's Theses

The explosive growth of the Internet of Things ecosystem has thrust these devices into the center of our lives. Unfortunately, the desire to create these devices has been stronger than the one to secure them. Recent attacks have shown us ignoring security in Internet of Things devices can cause severe harm in both a digital and physical sense. This thesis outlines a framework for developers and managers to assess the risk of IoT devices using a weighted scoring system across five different categories. Our case studies suggest that devices with higher security considerations have a better security posture and lower …

Amplifying The Prediction Of Team Performance Through Swarm Intelligence And Machine Learning, Erick Michael Harris

Master's Theses

Modern companies are increasingly relying on groups of individuals to reach organizational goals and objectives, however many organizations struggle to cultivate optimal teams that can maximize performance. Fortunately, existing research has established that group personality composition (GPC), across five dimensions of personality, is a promising indicator of team effectiveness. Additionally, recent advances in technology have enabled groups of humans to form real-time, closed-loop systems that are modeled after natural swarms, like flocks of birds and colonies of bees. These Artificial Swarm Intelligences (ASI) have been shown to amplify performance in a wide range of tasks, from forecasting financial markets to …

Logging, Visualization, And Analysis Of Network And Power Data Of Iot Devices, Neal Huynh Nguyen

Master's Theses

There are approximately 23.14 billion IoT(Internet of Things) devices currently in use worldwide. This number is projected to grow to over 75 billion by 2025. Despite their ubiquity little is known about the security and privacy implications of IoT devices. Several large-scale attacks against IoT devices have already been recorded.

To help address this knowledge gap, we have collected a year’s worth of network traffic and power data from 16 common IoT devices. From this data, we show that we can identify different smart speakers, like the Echo Dot, from analyzing one minute of power data on a shared power …

Vehicle Pseudonym Association Attack Model, Pierson Yieh

Master's Theses

With recent advances in technology, Vehicular Ad-hoc Networks (VANETs) have grown in application. One of these areas of application is Vehicle Safety Communication (VSC) technology. VSC technology allows for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications that enhance vehicle safety and driving experience. However, these newly developing technologies bring with them a concern for the vehicular privacy of drivers. Vehicles already employ the use of pseudonyms, unique identifiers used with signal messages for a limited period of time, to prevent long term tracking. But can attackers still attack vehicular privacy even when vehicles employ a pseudonym change strategy? The major contribution …

Funqual: User-Defined, Statically-Checked Call Graph Constraints In C++, Andrew P. Nelson

Master's Theses

Static analysis tools can aid programmers by reporting potential programming mistakes prior to the execution of a program. Funqual is a static analysis tool that reads C++17 code ``in the wild'' and checks that the function call graph follows a set of rules which can be defined by the user. This sort of analysis can help the programmer to avoid errors such as accidentally calling blocking functions in time-sensitive contexts or accidentally allocating memory in heap-sensitive environments. To accomplish this, we create a type system whereby functions can be given user-defined type qualifiers and where users can define their own …

Towards Autonomous Localization Of An Underwater Drone, Nathan Sfard

Master's Theses

Autonomous vehicle navigation is a complex and challenging task. Land and aerial vehicles often use highly accurate GPS sensors to localize themselves in their environments. These sensors are ineffective in underwater environments due to signal attenuation. Autonomous underwater vehicles utilize one or more of the following approaches for successful localization and navigation: inertial/dead-reckoning, acoustic signals, and geophysical data. This thesis examines autonomous localization in a simulated environment for an OpenROV Underwater Drone using a Kalman Filter. This filter performs state estimation for a dead reckoning system exhibiting an additive error in location measurements. We evaluate the accuracy of this Kalman …

Artificial Neural Network-Based Robotic Control, Justin Ng

Master's Theses

Artificial neural networks (ANNs) are highly-capable alternatives to traditional problem solving schemes due to their ability to solve non-linear systems with a nonalgorithmic approach. The applications of ANNs range from process control to pattern recognition and, with increasing importance, robotics. This paper demonstrates continuous control of a robot using the deep deterministic policy gradients (DDPG) algorithm, an actor-critic reinforcement learning strategy, originally conceived by Google DeepMind. After training, the robot performs controlled locomotion within an enclosed area. The paper also details the robot design process and explores the challenges of implementation in a real-time system.

Corridor Navigation For Monocular Vision Mobile Robots, Matthew James Ng

Master's Theses

Monocular vision robots use a single camera to process information about its environment. By analyzing this scene, the robot can determine the best navigation direction. Many modern approaches to robot hallway navigation involve using a plethora of sensors to detect certain features in the environment. This can be laser range finders, inertial measurement units, motor encoders, and cameras.

By combining all these sensors, there is unused data which could be useful for navigation. To draw back and develop a baseline approach, this thesis explores the reliability and capability of solely using a camera for navigation. The basic navigation structure begins …

The Design, Building, And Testing Of A Constant On Discreet Jammer For The Ieee 802.15.4/Zigbee Wireless Communication Protocol, Alexandre J. Marette

Master's Theses

As wireless protocols become easier to implement, more products come with wireless connectivity. This latest push for wireless connectivity has left a gap in the development of the security and the reliability of some protocols. These wireless protocols can be used in the growing field of IoT where wireless sensors are used to share information throughout a network. IoT is being implemented in homes, agriculture, manufactory, and in the medical field. Disrupting a wireless device from proper communication could potentially result in production loss, security issues, and bodily harm. The 802.15.4/ZigBee protocol is used in low power, low data rate, …

Developing, Evaluating, And Demonstrating An Open Source Gateway And Mobile Application For The Smartfarm Decision Support System, Caleb D. Fink

Master's Theses

The purpose of this research is to design, develop, evaluate, and demonstrate an open source gateway and mobile application for the SmartFarm open source decision support system to improve agricultural stewardship, environmental conservation, and provide farmers with a system that they own. There are very limited options for an open source gateway for collecting data on the farm. The options available are: expensive, require professional maintenance, are not portable between systems, improvements are made only by the manufacturer, limited in customization options, difficult to operate, and data is owned by the company rather than the farmer. The gateway is designed …

Leave The Features: Take The Cannoli, Jonathan Joseph Catanio

Master's Theses

Programming languages like Python, JavaScript, and Ruby are becoming increasingly popular due to their dynamic capabilities. These languages are often much easier to learn than other, statically type checked, languages such as C++ or Rust. Unfortunately, these dynamic languages come at the cost of losing compile-time optimizations. Python is arguably the most popular language for data scientists and researchers in the artificial intelligence and machine learning communities. As this research becomes increasingly popular, and the problems these researchers face become increasingly computationally expensive, questions are being raised about the performance of languages like Python. Language features found in Python, more …

Automated Pruning Of Greenhouse Indeterminate Tomato Plants, Joey M. Angeja

Master's Theses

Pruning of indeterminate tomato plants is vital for a profitable yield and it still remains a manual process. There has been research in automated pruning of grapevines, trees, and other plants, but tomato plants have yet to be explored. Wage increases are contributing to the depleting profits of greenhouse tomato farmers. Rises in population are the driving force behind the need for efficient growing techniques. The major contribution of this thesis is a computer vision algorithm for detecting greenhouse tomato pruning points without the use of depth sensors. Given an up-close 2-D image of a tomato stem with the background …