Computer Sciences Commons^™

Data Persistence In Eiffel, Jimmy J. Johnson

Theses and Dissertations--Computer Science

This dissertation describes an extension to the Eiffel programming language that provides automatic object persistence (the ability of programs to store objects and later recreate those objects in a subsequent execution of a program). The mechanism is orthogonal to other aspects of the Eiffel language. The mechanism serves four main purposes: 1) it gives Eiffel programmers a needed service, filling a gap between serialization, which provides limited persistence functions and database-mapping, which is cumbersome to use; 2) it greatly reduces the coding burden incurred by the programmer when objects must persist, allowing the programmer to focus instead on the business …

An Optical Character Recognition Engine For Graphical Processing Units, Jeremy Reed

Theses and Dissertations--Computer Science

This dissertation investigates how to build an optical character recognition engine (OCR) for a graphical processing unit (GPU). I introduce basic concepts for both building an OCR engine and for programming on the GPU. I then describe the SegRec algorithm in detail and discuss my findings.

Analyzing The Geo-Dependence Of Human Face Appearance And Its Applications, Mohammad T. Islam

Theses and Dissertations--Computer Science

Human faces have been a subject of study in computer science for decades. The rich of set features from human faces have been used in solving various problems in computer vision, including person identification, facial expression analysis, and attribute classification. In this work, I explore the human facial features that depend on the geo-location using a data- driven approach. I analyze millions of public domain images to extract the geo-dependent human facial features and explore their applications. Using various machine learning and statistical techniques, I show that the geo-dependent features of human faces can be used to solve the image …

Applying Deep Learning Techniques To The Analysis Of Android Apks, Robin Andrew Nix

LSU Master's Theses

Malware targeting mobile devices is a pervasive problem in modern life and as such tools to detect and classify malware are of great value. This paper seeks to demonstrate the effectiveness of Deep Learning Techniques, specifically Convolutional Neural Networks, in detecting and classifying malware targeting the Android operating system. Unlike many current detection techniques, which require the use of relatively rigid features to aid in detection, deep neural networks are capable of automatically learning flexible features which may be more resilient to obfuscation. We present a parsing for extracting sequences of API calls which can be used to describe a …

Social Media Network Data Mining And Optimization, Neha Clare Jose

LSU Master's Theses

Many small social aid organizations could benefit from collaborating with other organizations on common causes, but may not have the necessary social relationships. We present a framework for a recommender system for the Louisiana Poverty Initiative that identifies member organizations with common causes and aims to forge connections between these organizations. Our framework employs a combination of graph and text analyses of the organizations' Facebook pages. We use NodeXL, a plugin to Microsoft Excel, to download the Facebook graph and to interface with SNAP, the Stanford Network Analysis Platform, for calculating network measurements. Our framework extends NodeXL with algorithms that …

Spest – A Tool For Specification-Based Testing, Corrigan Redford Johnson

Master's Theses

This thesis presents a tool for SPEcification based teSTing (SPEST). SPEST is designed to use well known practices for automated black-box testing to reduce the burden of testing on developers. The tool uses a simple formal specification language to generate highly-readable unit tests that embody best practices for thorough software testing. Because the specification language used to generate the assertions about the code can be compiled, it can also be used to ensure that documentation describing the code is maintained during development and refactoring.

The utility and effectiveness of SPEST were validated through several exper- iments conducted with students in …

Improving Fairness In Peer-To-Peer Networks By Separating The Role Of Seeders In Network Infrastructures, Alireza Naghizadeh

Turkish Journal of Electrical Engineering and Computer Sciences

No abstract provided.

Energy-Efficient And Environmentally Friendly Power Dispatch By Trigeneration With Renewable Energy And Energy Storage, Faisal Pazheri, Mohd Fauzi Othman, Nazar H. Malik, Abdulrehman Ali Al-Arainy

Turkish Journal of Electrical Engineering and Computer Sciences

The importance of energy-efficient power generation that effectively utilizes the available fossil fuels is increasing due to the gradual decline in fossil fuel reserves. Furthermore, concern about global warming has led to rapid growth in renewable energy and energy storage technologies. This trend is encouraging power utilities to effectively exploit the use of renewable energy resources (RESs) and energy storage facilities (ESFs) for power supply systems. In this regards, trigeneration in the presence of RESs and ESFs can play an important role for efficient and clean power dispatch. This paper discusses the optimum power dispatch using a hybrid power plant …

An Experimental Study Of Coarse-Grained Reconfigurable System-On-Chip-Based Software-Defined Radio, Janakiraman Nithiyanantham, Nirmal Kumar Palanisamy

Turkish Journal of Electrical Engineering and Computer Sciences

Software-defined radio (SDR) research deals with a mixture of hardware and software technologies, where RF operating parameters and components are to be set or altered by modifiable software or firmware. This paper describes the coarse-grained reconfigurable array (CGRA) implementations of SDR architecture. This architecture is an extension of traditional SDR in complex adaptation strategies, such as highly reliable communications and efficient utilization of the resources and spectrum upgrade, through its internal states (performance) and hardware architecture. The proposed CGRA-based SDR implementation is based on dynamic partial reconfiguration methodology, which has the capability of reusing the same hardware module to handle …

Mind The Gap: The Importance Of Pluralistic Discourse In Computing For Mental Health, R. Jordan Crouser, Morganne Ray Crouser

Computer Science: Faculty Publications

A large amount of HCI research leverages studies from psychology to try to understand how humans work. Unfortunately, there is often a disconnect between the tightly- controlled laboratory studies being referenced and the application of this knowledge in practice. At the same time, many mental health practitioners are beginning to turn toward computational tools to help stretch limited resources and support equitable access to mental healthcare. These efforts could be dramatically enhanced by leveraging what the HCI community has learned about promoting active engagement and designing unobtrusive interfaces. By facilitating collaboration between HCI researchers and practitioners in the field of …

Growingleaf: Supporting Requirements Evolution Over Time, Alicia M. Grubb, Gary Song, Marsha Chechik

Computer Science: Faculty Publications

Goal modeling and analysis techniques help stakeholders consider possible tradeoff alternatives in their requirements and answer "what if" questions about those alternatives. Software projects today exist in an ephemeral state, and current goal modeling approaches do not answer questions about model evolution and changes in actors' intentionality. We have developed a technique [8] that allows stakeholders to explicate the dynamic nature of their intentional elements, and ask questions about how this dynamicity affects project outcomes. In this paper, we present GrowingLeaf , a new web-based goal modeling and analysis tool that implements this technique for iStar models. We discuss its …

Using Natural Language Processing And Qualitative Analysis To Intervene In Gang Violence: A Collaboration Between Social Work Researchers And Data Scientists, Desmond Upton Patton, Kathleen Mckeown, Owen Rambow, Jamie C. Macbeth

Computer Science: Faculty Publications

The U.S. has the highest rate of firearm-related deaths when compared to other industrialized countries. Violence particularly affects lowincome, urban neighborhoods in cities like Chicago, which saw a 40% increase in firearm violence from 2014 to 2015 to more than 3,000 shooting victims. While recent studies have found that urban, gang-involved individuals curate a unique and complex communication style within and between social media platforms, organizations focused on reducing gang violence are struggling to keep up with the growing complexity of social media platforms and the sheer volume of data they present. In this paper, describe the Digital Urban Violence …

Penetration Testing Frameworks And Methodologies: A Comparison And Evaluation, Aleatha Shanley

Theses : Honours

Cyber security is fast becoming a strategic priority across both governments and private organisations. With technology abundantly available, and the unbridled growth in the size and complexity of information systems, cyber criminals have a multitude of targets. Therefore, cyber security assessments are becoming common practice as concerns about information security grow. Penetration testing is one strategy used to mitigate the risk of cyber-attack. Penetration testers attempt to compromise systems using the same tools and techniques as malicious attackers thus, aim to identify vulnerabilities before an attack occurs. Penetration testing can be complex depending on the scope and domain area under …

Low Budget Forensic Drive Imaging Using Arm Based Single Board Computers, Eric Olson, Narasimha Shashidhar

Journal of Digital Forensics, Security and Law

Traditional forensic analysis of hard disks and external media typically involves a powered down machine and “dead analysis” of these devices. Forensic acquisition of hard drives and external media has traditionally been by one of several means: standalone forensic duplicator; using a hardware write-blocker or dock attached to a laptop, computer, workstation, etc., forensic operating systems that live boot from a USB, CD/DVD or virtual machines with preinstalled operating systems. Standalone forensics acquisition and imaging devices generally cost thousands of dollars. In this paper, we propose the use of single board computers as forensic imaging devices. Single board computers can …

In-The-Wild Residual Data Research And Privacy, William B. Glisson, Tim Storer, Andrew Blyth, George Grispos, Matt Campbell

Journal of Digital Forensics, Security and Law

As the world becomes increasingly dependent on technology, researchers in both industry and academia endeavor to understand how technology is used, the impact it has on everyday life, the artifact life-cycle and overall integrations of digital information. In doing so, researchers are increasingly gathering 'real-world' or 'in-the-wild' residual data, obtained from a variety of sources, without the explicit consent of the original owners. This data gathering raises significant concerns regarding privacy, ethics and legislation, as well as practical considerations concerning investigator training, data storage, overall security and data disposal. This research surveys recent studies of residual data gathered in-the-wild and …

Bytewise Approximate Matching: The Good, The Bad, And The Unknown, Vikram S. Harichandran, Frank Breitinger, Ibrahim Baggili

Journal of Digital Forensics, Security and Law

Hash functions are established and well-known in digital forensics, where they are commonly used for proving integrity and file identification (i.e., hash all files on a seized device and compare the fingerprints against a reference database). However, with respect to the latter operation, an active adversary can easily overcome this approach because traditional hashes are designed to be sensitive to altering an input; output will significantly change if a single bit is flipped. Therefore, researchers developed approximate matching, which is a rather new, less prominent area but was conceived as a more robust counterpart to traditional hashing. Since the conception …

Security Analysis Of Mvhash-B Similarity Hashing, Donghoon Chang, Somitra Sanadhya, Monika Singh

Journal of Digital Forensics, Security and Law

In the era of big data, the volume of digital data is increasing rapidly, causing new challenges for investigators to examine the same in a reasonable amount of time. A major requirement of modern forensic investigation is the ability to perform automatic filtering of correlated data, and thereby reducing and focusing the manual effort of the investigator. Approximate matching is a technique to find “closeness” between two digital artifacts. mvHash-B is a well-known approximate matching scheme used for finding similarity between two digital objects and produces a ‘score of similarity’ on a scale of 0 to 100. However, no security …

An Automated Approach For Digital Forensic Analysis Of Heterogeneous Big Data, Hussam Mohammed, Nathan Clarke, Fudong Li

Journal of Digital Forensics, Security and Law

The major challenges with big data examination and analysis are volume, complex interdependence across content, and heterogeneity. The examination and analysis phases are considered essential to a digital forensics process. However, traditional techniques for the forensic investigation use one or more forensic tools to examine and analyse each resource. In addition, when multiple resources are included in one case, there is an inability to cross-correlate findings which often leads to inefficiencies in processing and identifying evidence. Furthermore, most current forensics tools cannot cope with large volumes of data. This paper develops a novel framework for digital forensic analysis of heterogeneous …

On Efficiency Of Distributed Password Recovery, Radek Hranický, Martin Holkovič, Petr Matoušek

Journal of Digital Forensics, Security and Law

One of the major challenges in digital forensics today is data encryption. Due to the leaked information about unlawful sniffing, many users decided to protect their data by encryption. In case of criminal activities, forensic experts are challenged how to decipher suspect's data that are subject to investigation. A common method how to overcome password-based protection is a brute force password recovery using GPU-accelerated hardware. This approach seems to be expensive. This paper presents an alternative approach using task distribution based on BOINC platform. The cost, time and energy efficiency of this approach is discussed and compared to the GPU-based …

Introduction To Model Spaces And Their Operators, William T. Ross, Stephan Ramon Garcia, Javad Mashreghi

Bookshelf

The study of model spaces, the closed invariant subspaces of the backward shift operator, is a vast area of research with connections to complex analysis, operator theory and functional analysis. This self-contained text is the ideal introduction for newcomers to the field. It sets out the basic ideas and quickly takes the reader through the history of the subject before ending up at the frontier of mathematical analysis. Open questions point to potential areas of future research, offering plenty of inspiration to graduate students wishing to advance further.

Towards Syntactic Approximate Matching - A Pre-Processing Experiment, Doowon Jeong, Frank Breitinger, Hari Kang, Sangjin Lee

Journal of Digital Forensics, Security and Law

Over the past few years the popularity of approximate matching algorithms (a.k.a. fuzzy hashing) has increased. Especially within the area of bytewise approximate matching, several algorithms were published, tested and improved. It has been shown that these algorithms are powerful, however they are sometimes too precise for real world investigations. That is, even very small commonalities (e.g., in the header of a le) can cause a match. While this is a desired property, it may also lead to unwanted results. In this paper we show that by using simple pre-processing, we signicantly can in uence the outcome. Although our test …

Real-Time Translation Of American Sign Language Using Wearable Technology, Jackson Taylor

Honors Theses

The goal of this work is to implement a real-time system using wearable technology for translating American Sign Language (ASL) gestures into audible form. This system could be used to facilitate conversations between individuals who do and do not communicate using ASL. We use as our source of input the Myo armband, an affordable commercially-available wearable technology equipped with on-board accelerometer, gyroscope, and electromyography sensors. We investigate the performance of two different classification algorithms in this context: linear discriminant analysis and k-Nearest Neighbors (k-NN) using various distance metrics. Using the k-NN classifier and windowed dynamic time …

Steiner Tree Games, Samuel Rossin

Honors Papers

Prize-collecting Steiner tree is a network design problem in which a utility provider located at some position in a graph attempts to construct a network (subtree) of maximum profit based on the value of the vertices in the graph and the costs of the edges. I consider three network formation games where the players represent competing providers attempting to build networks in the same market. These games seek to preserve the key feature of Prize-Collecting Steiner tree, namely that players must each build a subtree that attempts to include customers who are of high value or are easy to reach. …

Revealing Malicious Contents Hidden In The Internet, Muhammad Nazmus Sakib

Theses and Dissertations

In this age of ubiquitous communication in which we can stay constantly connected with the rest of the world, for most of the part, we have to be grateful for one particular invention - the Internet. But as the popularity of Internet connectivity grows, it has become a very dangerous place where objects of malicious content and intent can be hidden in plain sight. In this dissertation, we investigate different ways to detect and capture these malicious contents hidden in the Internet. First, we propose an automated system that mimics high-risk browsing activities such as clicking on suspicious online ads, …

Learning Human Poses From Monocular Images, Xiaochuan Fan

Theses and Dissertations

In this research, we mainly focus on the problem of estimating the 2D human pose from a monocular image and reconstructing the 3D human pose based on the 2D human pose. Here a 3D pose is the locations of the human joints in the 3D space and a 2D pose is the projection of a 3D pose on an image. Unlike many previous works that explicitly use hand-crafted physiological models, both our 2D pose estimation and 3D pose reconstruction approaches implicitly learn the structure of human body from human pose data.

This 3D pose reconstruction is an ill-posed problem without …

Survey On Remnant Data Research: The Artefacts Recovered And The Implications In A Cyber Security Conscious World, Michael James, Patryk Szewczyk

Australian Digital Forensics Conference

The prevalence of remnant data in second hand storage media is well documented. Since 2004 there have been ten separate papers released through Edith Cowan University alone. Despite numerous government agencies providing advice on securing personal and corporate information, and news articles highlighting the need for data security, the availability of personal and confidential data on second hand storage devices is continuing, indicating a systemic laissez faire attitude to data security, even in our supposedly cyber security conscious world. The research continues, but there seems to be a lack of correlation of these studies to identify trends or common themes …

Implementation Of An Air Supply Unit Control Scheme For The Uc2av (Unmanned Circulation Control Aerial Vehicle), Cameron Rosen

Electronic Theses and Dissertations

The expanded prevalence of Unmanned Aerial Vehicles (UAVs) in recent years has created many opportunities to research novel applications for their use, enabled by the reduced cost, mission flexibility, and reduced risk that small-scale unmanned platforms provide in comparison to larger aircraft. Despite the versatility of unmanned aviation, limitations on payload size and weight, fuel and power capacity, and takeoff and landing infrastructure can restrict UAV applications, and have created a need for lift augmenting technologies that can reduce the impact of these limitations. Circulation Control (CC) is an active flow technique that has been proven as a method for …

The Impact Of Technology Acceptance And Openess To Innovaion On Software Implementation, Michael Marin Bertini

Walden Dissertations and Doctoral Studies

Senior management decisions to foster innovation and adopt new technology solutions have serious implications for the success of their organization change initiatives. This project examined the issue of senior management decision or reasons of their decision to adopt new Enterprise Resource Planning (ERP) systems as a solution to solve their business problems. This project investigated the degree that perceived ease of use and usefulness of the ERP system influenced decisions made by senior managers to innovate. Roger's diffusion of innovations theory and Davis technology acceptance model theory were used to predict when senior managers were open to innovation, and whether …

Face Recognition-Based Real-Time System For Surveillance, Fahad Parvez Mahdi, Md. Mahmudul Habib, Susan Mckeever, A.S.M. Moslehuddin, Pandian Vasant

Articles

The ability to automatically recognize human faces based on dynamic facial images is important in security, surveillance and the health/independent living domains. Specific applications include access control to secure environments, identification of individuals at a particular place and intruder detection. This research proposes a real-time system for surveillance using cameras. The process is broken into two steps: (1) face detection and (2) face recognition to identify particular persons. For the first step, the system tracks and selects the faces of the detected persons. An efficient recognition algorithm is then used to recognize detected faces with a known database. The proposed …

Challenges In Developing Applications For Aging Populations, Drew Marie Williams, Md O. Gani, Ivor D. Addo, Akm Jahangir Alam Majumder, Chandana Tamma, Mong-Te Wang, Chih-Hung Chang, Sheikh Iqbal Ahamed, Cheng-Chung Chu

Mathematics, Statistics and Computer Science Faculty Research and Publications

Elderly individuals can greatly benefit from the use of computer applications, which can assist in monitoring health conditions, staying in contact with friends and family, and even learning new things. However, developing accessible applications for an elderly user can be a daunting task for developers. Since the advent of the personal computer, the benefits and challenges of developing applications for older adults have been a hot topic of discussion. In this chapter, the authors discuss the various challenges developers who wish to create applications for the elderly computer user face, including age-related impairments, generational differences in computer use, and the …