Other Computer Sciences Commons^™

Video Games, Grief, And The Character Link System, Nam Nguyen

University of New Orleans Theses and Dissertations

Grief can encompass more than just the loss of real-life people. It can be felt with the loss of a pet, changes in daily structure, and even the loss of video game characters. The topic of grief related to video games and video game characters comes at a time when games as a service (GaaS) continue to increase in popularity and the phenomenon where these games also inevitably terminate service. To combat this unique form of grief, the Character LINK System was created as a tool that uses simple natural language processing (NLP) techniques to offer support to the bereaved …

Machine Learning For Terminal Procedure Chart Change Detection, Anthony M. Marchiafava

University of New Orleans Theses and Dissertations

Terminal Procedure Charts are a constantly updated and necessary tool for aircraft personnel to approach and take off from airport runways safely. Detecting changes within these charts is a time-consuming and laborious process. Here machine learning techniques were used to predict regions of change in charts based on detecting the charts image regions and comparing features extracted from those regions. Outlined are methodologies to detect differences between two separate charts to produce images with changed regions clearly indicated. Both more conventional computer vision and machine learning techniques were applied. For images with minor shifts, the proposed model is able to …

The Kati Module System: Modular Design For Delivering Character Focused Dialogue In Games, Stephen J. Marcel

University of New Orleans Theses and Dissertations

The Kati Module System is an interconnected set of programming modules intended to facilitate dynamic text authoring for interactive experiences (for example, games). It is a long-standing goal for interactive experiences to dynamically adapt their textual output based on the user or player's choices and predilections, but to account for this vast possibility space requires an amount of authoring that is frequently untenable, especially for small studios. Advances in machine learning have produced incredible progress in the field of Natural Language Generation (NLG). Though this produces impressive surface level text, it does so without an internal representation that can be …

Convolutional Neural Networks For Deflate Data Encoding Classification Of High Entropy File Fragments, Nehal Ameen

University of New Orleans Theses and Dissertations

Data reconstruction is significantly improved in terms of speed and accuracy by reliable data encoding fragment classification. To date, work on this problem has been successful with file structures of low entropy that contain sparse data, such as large tables or logs. Classifying compressed, encrypted, and random data that exhibit high entropy is an inherently difficult problem that requires more advanced classification approaches. We explore the ability of convolutional neural networks and word embeddings to classify deflate data encoding of high entropy file fragments after establishing ground truth using controlled datasets. Our model is designed to either successfully classify file …

Effective Statistical Energy Function Based Protein Un/Structure Prediction, Avdesh Mishra

University of New Orleans Theses and Dissertations

Proteins are an important component of living organisms, composed of one or more polypeptide chains, each containing hundreds or even thousands of amino acids of 20 standard types. The structure of a protein from the sequence determines crucial functions of proteins such as initiating metabolic reactions, DNA replication, cell signaling, and transporting molecules. In the past, proteins were considered to always have a well-defined stable shape (structured proteins), however, it has recently been shown that there exist intrinsically disordered proteins (IDPs), which lack a fixed or ordered 3D structure, have dynamic characteristics and therefore, exist in multiple states. Based on …

Prediction Of Hierarchical Classification Of Transposable Elements Using Machine Learning Techniques, Manisha Panta

University of New Orleans Theses and Dissertations

Transposable Elements (TEs) or jumping genes are the DNA sequences that have an intrinsic capability to move within a host genome from one genomic location to another. Studies show that the presence of a TE within or adjacent to a functional gene may alter its expression. TEs can also cause an increase in the rate of mutation and can even promote gross genetic arrangements. Thus, the proper classification of the identified jumping genes is important to understand their genetic and evolutionary effects. While computational methods have been developed that perform either binary classification or multi-label classification of TEs, few studies …

Detection Of Sand Boils From Images Using Machine Learning Approaches, Aditi S. Kuchi

University of New Orleans Theses and Dissertations

Levees provide protection for vast amounts of commercial and residential properties. However, these structures degrade over time, due to the impact of severe weather, sand boils, subsidence of land, seepage, etc. In this research, we focus on detecting sand boils. Sand boils occur when water under pressure wells up to the surface through a bed of sand. These make levees especially vulnerable. Object detection is a good approach to confirm the presence of sand boils from satellite or drone imagery, which can be utilized to assist in the automated levee monitoring methodology. Since sand boils have distinct features, applying object …

Assessing Apache Spark Streaming With Scientific Data, Janak Dahal

University of New Orleans Theses and Dissertations

Processing real-world data requires the ability to analyze data in real-time. Data processing engines like Hadoop come short when results are needed on the fly. Apache Spark's streaming library is increasingly becoming a popular choice as it can stream and analyze a significant amount of data. To showcase and assess the ability of Spark various metrics were designed and operated using data collected from the USGODAE data catalog. The latency of streaming in Apache Spark was measured and analyzed against many nodes in the cluster. Scalability was monitored by adding and removing nodes in the middle of a streaming job. …

Practical Application Of Fast Disk Analysis For Selective Data Acquisition, Sergey Gorbov

University of New Orleans Theses and Dissertations

Using a forensic imager to produce a copy of the storage is a common practice. Due to the large volumes of the modern disks, the imaging may impose severe time overhead which ultimately delays the investigation process. We proposed automated disk analysis techniques that precisely identify regions on the disk that contain data. We also developed a high performance imager that produces AFFv3 images at rates exceeding 300MB/s. Using multiple disk analysis strategies we can analyze a disk within a few minutes and yet reduce the imaging time of by many hours. Partial AFFv3 images produced by our imager can …

Analysis Of Windows 8 Registry Artifacts, Jeremy M. Stormo

University of New Orleans Theses and Dissertations

Microsoft’s series of Windows operating systems represents some of the most commonly encountered technologies in the field of digital forensics. It is then fair to say that Microsoft’s design decisions greatly affect forensic efforts. Because of this, it is exceptionally important for the forensics community to keep abreast of new developments in the Windows product line. With each new release, the Windows operating system may present investigators with significant new artifacts to explore. Described by some as the heart of the Windows operating system, the Windows registry has been proven to contain many of these forensically interesting artifacts. Given the …

Categorization Of Large Corpora Of Malicious Software, Deekshit Kura

University of New Orleans Theses and Dissertations

Malware is computer software written by someone with mischievous or, more usually, malicious and/or criminal intent and specifically designed to damage data, hosts or networks. The variety of malware is increasing proportionally with the increase in computers and we are not aware of newly emerging malware. Tools are needed to categorize families of malware, so that analysts can compare new malware samples to ones that have been previously analyzed and determine steps to detect and prevent malware infections.

In this thesis, I developed a technique to catalog and characterize the behavior of malware, so that malware families, the level of …

Curated Reasoning By Formal Modeling Of Provenance, Kevin B. Shaw

University of New Orleans Theses and Dissertations

The core problem addressed in this research is the current lack of an ability to repurpose and curate scientific data among interdisciplinary scientists within a research enterprise environment. Explosive growth in sensor technology as well as the cost of collecting ocean data and airborne measurements has allowed for exponential increases in scientific data collection as well as substantial enterprise resources required for data collection. There is currently no framework for efficiently curating this scientific data for repurposing or intergenerational use.

There are several reasons why this problem has eluded solution to date to include the competitive requirements for funding and …

Forensic Analysis Of Whatsapp On Android Smartphones, Neha S. Thakur

University of New Orleans Theses and Dissertations

Android forensics has evolved over time offering significant opportunities and exciting challenges. On one hand, being an open source platform Android is giving developers the freedom to contribute to the rapid growth of the Android market whereas on the other hand Android users may not be aware of the security and privacy implications of installing these applications on their phones. Users may assume that a password-locked device protects their personal information, but applications may retain private information on devices, in ways that users might not anticipate. In this thesis we will be concentrating on one such application called 'WhatsApp', a …

Automated Timeline Anomaly Detection, Joshua M. Barone

University of New Orleans Theses and Dissertations

Digital forensics is the practice of trained investigators gathering and analyzing evidence from digital devices such as computers and smart phones. On these digital devices, it is possible to change the time on the device for a purpose other than what is intended. Currently there are no documented techniques to determine when this occurs. This research seeks to prove out a technique for determining when the time has been changed on forensic disk image by analyzing the log files found on the image. Out of this research a tool is created to perform this analysis in automated fashion. This tool …

Application Of Web Mashup Technology To Oyster Information Services, Christian Chuindja Ngniah

University of New Orleans Theses and Dissertations

Web mashup is a lightweight technology used to integrate data from remote sources without direct access to their databases. As a data consumer, a Web mashup application creates new contents by retrieving data through the Web application programming interface (API) provided by the external sources. As a data provider, the service program publishes its Web API and implements the specified functions.

In the project reported by this thesis, we have implemented two Web mashup applications to enhance the Web site oystersentinel.org: the Perkinsus marinus model and the Oil Spill model. Each model overlay geospatial data from a local database …

Volatile Memory Message Carving: A "Per Process Basis" Approach, Aisha Ibrahim Ali-Gombe

University of New Orleans Theses and Dissertations

The pace at which data and information transfer and storage has shifted from PCs to mobile devices is of great concern to the digital forensics community. Android is fast becoming the operating system of choice for these hand-held devices, hence the need to develop better forensic techniques for data recovery cannot be over-emphasized. This thesis analyzes the volatile memory for Motorola Android devices with a shift from traditional physical memory extraction to carving residues of data on a “per process basis”. Each Android application runs in a separate process within its own Dalvik Virtual Machine (JVM) instance, thus, the proposed …

Software For Estimation Of Human Transcriptome Isoform Expression Using Rna-Seq Data, Kristen Johnson

University of New Orleans Theses and Dissertations

The goal of this thesis research was to develop software to be used with RNA-Seq data for transcriptome quantification that was capable of handling multireads and quantifying isoforms on a more global level. Current software available for these purposes uses various forms of parameter alteration in order to work with multireads. Many still analyze isoforms per gene or per researcher determined clusters as well. By doing so, the effects of multireads are diminished or possibly wrongly represented. To address this issue, two programs, GWIE and ChromIE, were developed based on a simple iterative EM-like algorithm with no parameter manipulation. These …

Android Memory Capture And Applications For Security And Privacy, Joseph T. Sylve

University of New Orleans Theses and Dissertations

The Android operating system is quickly becoming the most popular platform for mobiledevices. As Android’s use increases, so does the need for both forensic and privacy toolsdesigned for the platform. This thesis presents the first methodology and toolset for acquiringfull physical memory images from Android devices, a proposed methodology for forensicallysecuring both volatile and non-volatile storage, and details of a vulnerability discovered by theauthor that allows the bypass of the Android security model and enables applications to acquirearbitrary permissions.