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Full-Text Articles in Other Computer Engineering

Integrated Environment And Proximity Sensing For Uav Applications, Shawn S. Brackett Aug 2017

Integrated Environment And Proximity Sensing For Uav Applications, Shawn S. Brackett

Electronic Theses and Dissertations

As Unmanned Aerial Vehicle (UAV), or “drone” applications expand, new methods for sensing, navigating and avoiding obstacles need to be developed. The project applies an Extended Kalman Filter (EKF) to a simulated quadcopter vehicle though Matlab in order to estimate not only the vehicle state but the world state around the vehicle. The EKF integrates multiple sensor readings from range sensors, IMU sensors, and radiation sensors and combines this information to optimize state estimates. The result is an estimated world map to be used in vehicle navigation and obstacle avoidance.

The simulation handles the physics behind the vehicle flight. As …


Research On Improving Navigation Safety Based On Big Data And Cloud Computing Technology For Qiongzhou Strait, Rui Wang Aug 2017

Research On Improving Navigation Safety Based On Big Data And Cloud Computing Technology For Qiongzhou Strait, Rui Wang

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.


Dynamic Adversarial Mining - Effectively Applying Machine Learning In Adversarial Non-Stationary Environments., Tegjyot Singh Sethi Aug 2017

Dynamic Adversarial Mining - Effectively Applying Machine Learning In Adversarial Non-Stationary Environments., Tegjyot Singh Sethi

Electronic Theses and Dissertations

While understanding of machine learning and data mining is still in its budding stages, the engineering applications of the same has found immense acceptance and success. Cybersecurity applications such as intrusion detection systems, spam filtering, and CAPTCHA authentication, have all begun adopting machine learning as a viable technique to deal with large scale adversarial activity. However, the naive usage of machine learning in an adversarial setting is prone to reverse engineering and evasion attacks, as most of these techniques were designed primarily for a static setting. The security domain is a dynamic landscape, with an ongoing never ending arms race …


Distributed Knowledge Discovery For Diverse Data, Hossein Hamooni Jul 2017

Distributed Knowledge Discovery For Diverse Data, Hossein Hamooni

Computer Science ETDs

In the era of new technologies, computer scientists deal with massive data of size hundreds of terabytes. Smart cities, social networks, health care systems, large sensor networks, etc. are constantly generating new data. It is non-trivial to extract knowledge from big datasets because traditional data mining algorithms run impractically on such big datasets. However, distributed systems have come to aid this problem while introducing new challenges in designing scalable algorithms. The transition from traditional algorithms to the ones that can be run on a distributed platform should be done carefully. Researchers should design the modern distributed algorithms based on the …


Underwater Computer Vision - Fish Recognition, Spencer Chang, Austin Otto Jun 2017

Underwater Computer Vision - Fish Recognition, Spencer Chang, Austin Otto

Computer Engineering

The Underwater Computer Vision – Fish Recognition project includes the design and implementation of a device that can withstand staying underwater for a duration of time, take pictures of underwater creatures, such as fish, and be able to identify certain fish. The system is meant to be cheap to create, yet still able to process the images it takes and identify the objects in the pictures with some accuracy. The device can output its results to another device or an end user.


Multispectral Identification Array, Zachary D. Eagan Jun 2017

Multispectral Identification Array, Zachary D. Eagan

Computer Engineering

The Multispectral Identification Array is a device for taking full image spectroscopy data via the illumination of a subject with sixty-four unique spectra. The array combines images under the illumination spectra to produce an approximate reflectance graph for every pixel in a scene. Acquisition of an entire spectrum allows the array to differentiate objects based on surface material. Spectral graphs produced are highly approximate and should not be used to determine material properties, however the output is sufficiently consistent to allow differentiation and identification of previously sampled subjects. While not sufficiently advanced for use as a replacement to spectroscopy the …


Gridiron-Gurus Final Report: Fantasy Football Performance Prediction, Kyle Tanemura, Michael Li, Erica Dorn, Ryan Mckinney Jun 2017

Gridiron-Gurus Final Report: Fantasy Football Performance Prediction, Kyle Tanemura, Michael Li, Erica Dorn, Ryan Mckinney

Computer Science and Software Engineering

Gridiron Gurus is a desktop application that allows for the creation of custom AI profiles to help advise and compete against in a Fantasy Football setting. Our AI are capable of performing statistical prediction of players on both a season long and week to week basis giving them the ability to both draft and manage a fantasy football team throughout a season.


Micro-Spi Sediment Profile Imaging Micro-Inspector, Andrew P. Corvin, Caleb T. Davies, Matt R. Ferrari Jun 2017

Micro-Spi Sediment Profile Imaging Micro-Inspector, Andrew P. Corvin, Caleb T. Davies, Matt R. Ferrari

Mechanical Engineering

This project was proposed by Dr. Brian Paavo through a desire to more easily study the benthic sediment layers of the ocean. To do so, he asked us to build a simple and compact machine for use in sediment profile imagery (SPI). Although devices like this already exist, they are all large scale devices that require a ship with a crane to deploy, which is expensive and time consuming. Instead, he desired a “micro” SPI, which is capable of being deployed from a small vessel that can easily navigate shallow waters. Our interpretation of these requirements was as follows: a …


Explorations Into Machine Learning Techniques For Precipitation Nowcasting, Aditya Nagarajan Mar 2017

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 …