Other Computer Engineering Commons^™

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 …

Mastering The Game Of Gomoku Without Human Knowledge, Yuan Wang

Master's Theses

Gomoku, also called Five in a row, is one of the earliest checkerboard games invented by humans. For a long time, it has brought countless pleasures to us. We humans, as players, also created a lot of skills in playing it. Scientists normalize and enter these skills into the computer so that the computer knows how to play Gomoku. However, the computer just plays following the pre-entered skills, it doesn’t know how to develop these skills by itself. Inspired by Google’s AlphaGo Zero, in this thesis, by combining the technologies of Monte Carlo Tree Search, Deep Neural Networks, and Reinforcement …

Polycommit: Building Better Habits Through Gamification, Elliot Fiske

Master's Theses

Computer-assisted learning is older than Turing machines, and constantly evolves as technology improves. While some teachers are resistant to using technology in the classroom, “e-learning” techniques are becoming more common in almost every school, from K-12 to universities. As technology becomes more widespread, it becomes crucial to examine the various methodologies of computer-assisted learning and find the techniques that are most effective.

This paper explores the effectiveness of one such methodology, spaced repetition. This technique applies to homework assignments available to students online. We include an exploration of several existing apps that use this technique, and introduce our own novel …

Improving System-On-Chip Test Networks For: Bandwidth, Security, And Power, Saurabh Gupta

Computer Science and Engineering Theses and Dissertations

Modern System-on-Chips (SoCs) provide benefits such as reduction in overall system cost, and size, increased performance, and lower power consumption. Increasing complexity of these Integrated Circuits (ICs) has resulted in a higher probability of manufacturing defects. Manufacturing defects can result in the faulty operation of a system. Thus, it is essential to test an IC after it is manufactured to detect any possible faults in it. These SoCs include on-chip embedded instruments that can be used for test, debug, diagnosis, validation, monitoring, characterization, configuration, or functional purposes. IEEE 1687 Std. (IJTAG) provides a standard interface for the reconfigurable access and …

Discovering The Needs Of People At The 10/40 Window With Data Science, Germán H. Alférez, Ceila M. González

Adventist Human-Subject Researchers Association

Abstract: We propose an approach to discover the needs of people in particular areas of Iraq, a country located at the 10/40 Window, by means of Data Science applied to Open Big Data. The resulting model predicts refugee crises and artillery attacks with high accuracy even in areas with scarce data.

Tolerance Sensitivity Analysis And Robust Optimal Design Method Of A Surface-Mounted Permanent Magnet Motor By Using A Hybrid Response Surface Method Considering Manufacturing Tolerances, Cha-Seung Jun, Byung-Il Kwon, Ohbong Kwon

Publications and Research

This paper presents a robust optimal design method using a hybrid response surface method (H-RSM) which directly finds an optimal point satisfying a target Z-value or a probability of failure. Through three steps, this paper achieves the goal that is to increase the open-circuit airgap flux (OCAF) in a surface-mounted permanent magnet motor and decrease its variation caused by variations of the airgap lengths including an additional one between permanent magnets and rotor back yoke. First, the OCAF equation is derived from the magnetic equivalent circuit (MEC) considering the additional airgap. Then, the equation is validated by comparing its results …

Solar And Rain Catching Canopy. Urban Oasis, Afolabi Ibitoye, Langston Clark, Elena Zimareva, Evan Banks, Alexander Aptekar

Publications and Research

The Urban Oasis is designed to work within existing “pocket parks” in New York City as a combined rainwater collector, personal electronics charging station and resting designation for New Yorkers. Intended to not only lessen the demand on the city power grid by using renewable energy to charge devices, the urban oasis is also intended to mitigate grey water overfill in New York’s combined sewer system and, in general, serve as a model for responsible environmental stewardship in urban areas.

The important technical aspects of the canopy specifically analyzed were:

a) how much rainwater could the canopy be expected to …

Security Attacks On Reckless-Apps: "Remote Car Keyless Applications" For New Semi Autonomous Vehicles, Mohamed El-Tawab

Masters Theses, 2010-2019

Rapid technological advancements of vehicle manufacturing and the modern wireless technology opens the door for several new Intelligent Transportation applications. Remote Keyless system in vehicles is considered one of the famous applications that has been developed recently, which is susceptible to many cyberattacks. Remote Keyless applications on smartphones were developed in the past few years to perform the functionality of keyless fob and are expected to replace the physical keyless fobs in the next few years, which can open the door to many cyberattacks. In this research, we implemented a simulation that represents the REmote Car KeyLESS Applications (RECKLESS-apps) on …

Comparison Of Google Image Search And Resnet Image Classification Using Image Similarity Metrics, David Smith

Computer Science and Computer Engineering Undergraduate Honors Theses

In this paper, we compare the results of ResNet image classification with the results of Google Image search. We created a collection of 1,000 images by performing ten Google Image searches with a variety of search terms. We classified each of these images using ResNet and inspected the results. The ResNet classifier predicted the category that matched the search term of the image 77.5% of the time. In our best case, with the search term “forklift”, the classifier categorized 92 of the 100 images as forklifts. In the worst case, for the category “hammer”, the classifier matched the search term …

The 3d Abstract Tile Assembly Model Is Intrinsically Universal, Aaron Koch, Daniel Hader, Matthew J. Patitz

Computer Science and Computer Engineering Undergraduate Honors Theses

In this paper, we prove that the three-dimensional abstract Tile Assembly Model (3DaTAM) is intrinsically universal. This means that there is a universal tile set in the 3DaTAM which can be used to simulate any 3DaTAM system. This result adds to a body of work on the intrinsic universality of models of self-assembly, and is specifically motivated by a result in FOCS 2016 showing that any intrinsically universal tile set for the 2DaTAM requires nondeterminism (i.e. undirectedness) even when simulating directed systems. To prove our result we have not only designed, but also fully implemented what we believe to be …

Training Machine Learning Agents In A 3d Game Engine, Diego Calderon

Computer Science and Computer Engineering Undergraduate Honors Theses

Artificial intelligence (AI) and video games benefit from each other. Games provide a challenging domain for testing learning algorithms, and AI provides a framework to designing and implementing intelligent behavior, which reinforces meaningful play. Medium and small studios, and independent game developers, have limited resources to design, implement, and maintain agents with reactive behavior. In this research, we trained agents using machine learning (ML), aiming to find an alternative to expensive traditional algorithms for intelligent behavior used in video games. We use Unity as a game engine to implement the environments and TensorFlow for the neural network training.

Maintainability Analysis Of Mining Trucks With Data Analytics., Abdulgani Kahraman

Electronic Theses and Dissertations

The mining industry is one of the biggest industries in need of a large budget, and current changes in global economic challenges force the industry to reduce its production expenses. One of the biggest expenditures is maintenance. Thanks to the data mining techniques, available historical records of machines’ alarms and signals might be used to predict machine failures. This is crucial because repairing machines after failures is not as efficient as utilizing predictive maintenance. In this case study, the reasons for failures seem to be related to the order of signals or alarms, called events, which come from trucks. The …

Comparative Study Of Deep Learning Models For Network Intrusion Detection, Brian Lee, Sandhya Amaresh, Clifford Green, Daniel Engels

SMU Data Science Review

In this paper, we present a comparative evaluation of deep learning approaches to network intrusion detection. A Network Intrusion Detection System (NIDS) is a critical component of every Internet connected system due to likely attacks from both external and internal sources. A NIDS is used to detect network born attacks such as Denial of Service (DoS) attacks, malware replication, and intruders that are operating within the system. Multiple deep learning approaches have been proposed for intrusion detection systems. We evaluate three models, a vanilla deep neural net (DNN), self-taught learning (STL) approach, and Recurrent Neural Network (RNN) based Long Short …

Distributed Iterative Graph Processing Using Nosql With Data Locality, Ayam Pokhrel

LSU Master's Theses

A tremendous amount of data is generated every day from a wide range of sources such as social networks, sensors, and application logs. Among them, graph data is one type that represents valuable relationships between various entities. Analytics of large graphs has become an essential part of business processes and scientific studies because it leads to deep and meaningful insights into the related domain based on the connections between various entities. However, the optimal processing of large-scale iterative graph computations is very challenging due to the issues like fault tolerance, high memory requirement, parallelization, and scalability. Most of the contemporary …

A Route Less Traveled: Principals’ Perceptions Of Alternative Licensed Cte Teachers, Scott R. Bartholomew, Emma P. Bullock, Louis S. Nadelson

Faculty Publications

The shortage of teachers prepared to teach career and technical education (CTE) courses, or willing to work in certain locations (e.g. inner city, rural), has motivated the desire to explore solutions such as alternative routes to teacher licensure (ARL). Most ARL programs bypass colleges of education and provide a different approach to preparing individuals to teach, leaving many to wonder about the quality and knowledge of these teachers. Specific areas, such as CTE, have seen a large influx of ARL teachers in recent years. We sought to determine school principals’ perceptions of ARL CTE teachers. We found principal support for …

Degradation Modeling And Rul Prediction Using Wiener Process Subject To Multiple Change Points And Unit Heterogeneity, Yuxin Wen, Jianguo Wu, Devashish Das, Tzu-Liang Bill Tseng

Engineering Faculty Articles and Research

Degradation modeling is critical for health condition monitoring and remaining useful life prediction (RUL). The prognostic accuracy highly depends on the capability of modeling the evolution of degradation signals. In many practical applications, however, the degradation signals show multiple phases, where the conventional degradation models are often inadequate. To better characterize the degradation signals of multiple-phase characteristics, we propose a multiple change-point Wiener process as a degradation model. To take into account the between-unit heterogeneity, a fully Bayesian approach is developed where all model parameters are assumed random. At the offline stage, an empirical two-stage process is proposed for model …

Image Processing Applications In Real Life: 2d Fragmented Image And Document Reassembly And Frequency Division Multiplexed Imaging, Houman Kamran Habibkhani

LSU Doctoral Dissertations

In this era of modern technology, image processing is one the most studied disciplines of signal processing and its applications can be found in every aspect of our daily life. In this work three main applications for image processing has been studied.

In chapter 1, frequency division multiplexed imaging (FDMI), a novel idea in the field of computational photography, has been introduced. Using FDMI, multiple images are captured simultaneously in a single shot and can later be extracted from the multiplexed image. This is achieved by spatially modulating the images so that they are placed at different locations in the …

The E-Agriculture Research Landscape In South Africa: A Systematic Literature Review, Alain Nzuzi Kintoki

The African Journal of Information Systems

Despite the growing interest in e-agriculture research in South Africa, academic studies have not sufficiently and deeply investigated the current e-agriculture research trends in the South African context. It is unclear how primary e-agriculture research in South Africa will aid both current and future generations to create new and better ways to transform agricultural development using this modern technology. This study sought to determine the current status of e-agriculture research in the South African context. A systematic literature review was used to gather and analyze data. The results indicate that 17 papers (26.5%) were published during the first two years …

A Sketch-Based Rapid Modeling Method For Crime Scene Presentation, Pu Ren, Wuyang Shui, Jin Liu, Yachun Fan, Wenshuo Zhao, Mingquan Zhou

Journal of Digital Forensics, Security and Law

The reconstruction of crime scene plays an important role in digital forensic application. This article integrates computer graphics, sketch-based retrieval and virtual reality (VR) techniques to develop a low-cost and rapid 3D crime scene presentation approach, which can be used by investigators to analyze and simulate the criminal process. First, we constructed a collection of 3D models for indoor crime scenes using various popular techniques, including laser scanning, image-based modeling and geometric modeling. Second, to quickly obtain an object of interest from the 3D model database, a sketch-based retrieval method was proposed. Finally, a rapid modeling system that integrates our …

Evaluating Classifiers' Optimal Performances Over A Range Of Misclassification Costs By Using Cost-Sensitive Classification, Ramy Al-Saffar

LSU Master's Theses

We believe that using the classification accuracy is not enough to evaluate the performances of classification algorithms. It can be misleading due to overlooking an important element which is the cost if classification is inaccurate. Furthermore, the Receiver Operational Characteristic (ROC) is one of the most popular graphs used to evaluate classifiers performances. However, one of the biggest ROC’s shortcomings is the assumption of equal costs for all misclassified data. Therefore, our goal is to reduce the total cost of decision making by selecting the classifier that has the least total misclassification cost. Nevertheless, the exact misclassification cost is usually …