Other Computer Engineering Commons^™

Cpu Db Data Visualization, Ruchita Patel, Marek Moreno

Computer Engineering

Given the CPU database from Stanford, we wanted to create something that portrayed the data in a more visually pleasing way. The CPU database website wanted a web page that would allow users to create graphs based on the processor data from the database. The web page would allow users to select different data from the database and create the graphs they wanted to gain insight into the decades of processor data.

Design And Implementation Of An Archetype Based Interoperable Knowledge Eco-System For Data Buoys, Paul Stacey, Damon Berry

Conference papers

This paper describes the ongoing work of the authors in translating two-level system design techniques used in Health Informatics to the Earth Systems Science domain. Health informaticians have developed a sophisticated two-level systems design approach for electronic health documentation over many years, and with the use of archetypes, have shown how knowledge interoperability among heterogeneous systems can be achieved. Translating two-level modelling techniques to a new domain is a complex task. A proof-of-concept archetype enabled data buoy eco-system is presented. The concept of operational templates-as-a service is proposed. Design recommendations and implementation experiences of re-working the proposed architecture to run …

Improving A Particle Swarm Optimization-Based Clustering Method, Sharif Shahadat

LSU New Orleans Theses and Dissertations

This thesis discusses clustering related works with emphasis on Particle Swarm Optimization (PSO) principles. Specifically, we review in detail the PSO clustering algorithm proposed by Van Der Merwe & Engelbrecht, the particle swarm clustering (PSC) algorithm proposed by Cohen & de Castro, Szabo’s modified PSC (mPSC), and Georgieva & Engelbrecht’s Cooperative-Multi-Population PSO (CMPSO). In this thesis, an improvement over Van Der Merwe & Engelbrecht’s PSO clustering has been proposed and tested for standard datasets. The improvements observed in those experiments vary from slight to moderate, both in terms of minimizing the cost function, and in terms of run time.

Real Time Learning Level Assessment Using Eye Tracking, Saurin S. Parikh, Hari Kalva

MODVIS Workshop

E-Learning is emerging as a convenient and effective learning tool. However, the challenge with eLearning is the lack of effective tools to assess levels of learning. Ability to predict difficult content in real time enables eLearning systems to dynamically provide supplementary content to meet learners’ needs. Recent developments have made possible low-cost eye trackers, which enables a new class of applications based on eye response. In comparison to past attempts using bio-metrics in learning assessments, with eye tracking, we can have access to the exact stimulus that is causing the response. A key aspect of the proposed approach is the …

Source Anonymization Of Digital Images: A Counter–Forensic Attack On Prnu Based Source Identification Techniques, Prithviraj Sengupta, Venkata Udaya Sameer, Ruchira Naskar, Ezhil Kalaimannan

Annual ADFSL Conference on Digital Forensics, Security and Law

A lot of photographers and human rights advocates need to hide their identity while sharing their images on the internet. Hence, source–anonymization of digital images has become a critical issue in the present digital age. The current literature contains a number of digital forensic techniques for “source–identification” of digital images, one of the most efficient of them being Photo–Response Non–Uniformity (PRNU) sensor noise pattern based source detection. PRNU noise pattern being unique to every digital camera, such techniques prove to be highly robust way of source–identification. In this paper, we propose a counter–forensic technique to mislead this PRNU sensor noise …

An Accidental Discovery Of Iot Botnets And A Method For Investigating Them With A Custom Lua Dissector, Max Gannon, Gary Warner, Arsh Arora

Annual ADFSL Conference on Digital Forensics, Security and Law

This paper presents a case study that occurred while observing peer-to-peer network communications on a botnet monitoring station and shares how tools were developed to discover what ultimately was identified as Mirai and many related IoT DDOS Botnets. The paper explains how researchers developed a customized protocol dissector in Wireshark using the Lua coding language, and how this enabled them to quickly identify new DDOS variants over a five month period of study.

Classification Of Images Based On Pixels That Represent A Small Part Of The Scene. A Case Applied To Microaneurysms In Fundus Retina Images, Pablo F. Ordonez, Pablo F. Ordonez

Master of Science in Computer Science Theses

Convolutional Neural Networks (CNNs), the state of the art in image classification, have proven to be as effective as an ophthalmologist, when detecting Referable Diabetic Retinopathy (RDR). Having a size of less than 1\% of the total image, microaneurysms are early lesions in DR that are difficult to classify. The purpose of this thesis is to improve the accuracy of detection of microaneurysms using a model that includes two CNNs with different input image sizes, 60x60 and 420x420 pixels. These models were trained using the Kaggle and Messidor datasets and tested independently against the Kaggle dataset, showing a sensitivity of …

A Study Of Activation Functions For Neural Networks, Meenakshi Manavazhahan

Computer Science and Computer Engineering Undergraduate Honors Theses

Artificial neural networks are function-approximating models that can improve themselves with experience. In order to work effectively, they rely on a nonlinearity, or activation function, to transform the values between each layer. One question that remains unanswered is, “Which non-linearity is optimal for learning with a particular dataset?” This thesis seeks to answer this question with the MNIST dataset, a popular dataset of handwritten digits, and vowel dataset, a dataset of vowel sounds. In order to answer this question effectively, it must simultaneously determine near-optimal values for several other meta-parameters, including the network topology, the optimization algorithm, and the number …

Uncovering Exceptional Predictions Using Exploratory Analysis Of Second Stage Machine Learning., Aneseh Alvanpour

Electronic Theses and Dissertations

Nowadays, algorithmic systems for making decisions are widely used to facilitate decisions in a variety of fields such as medicine, banking, applying for universities or network security. However, many machine learning algorithms are well-known for their complex mathematical internal workings which turn them into black boxes and makes their decision-making process usually difficult to understand even for experts. In this thesis, we try to develop a methodology to explain why a certain exceptional machine learned decision was made incorrectly by using the interpretability of the decision tree classifier. Our approach can provide insights about potential flaws in feature definition or …

Data Driven Discovery Of Materials Properties., Fadoua Khmaissia

Electronic Theses and Dissertations

The high pace of nowadays industrial evolution is creating an urgent need to design new cost efficient materials that can satisfy both current and future demands. However, with the increase of structural and functional complexity of materials, the ability to rationally design new materials with a precise set of properties has become increasingly challenging. This basic observation has triggered the idea of applying machine learning techniques in the field, which was further encouraged by the launch of the Materials Genome Initiative (MGI) by the US government since 2011. In this work, we present a novel approach to apply machine learning …

Software Updates To A Multiple Autonomous Quadcopter Search System (Maqss), Jared Speck, Toby Chan

Computer Engineering

A series of performance-based and feature implementation software updates to an existing multiple vehicle autonomous target search system is outlined in this paper. The search system, MAQSS, is designed to address a computational power constraint found on modern autonomous aerial platforms by separating real-time and computationally expensive tasks through delegation to multiple multirotor vehicles. A Ground Control Station (GCS) is also described as part of the MAQSS system to perform the delegation and provide a low workload user interface. Ultimately, the changes to MAQSS noted in this paper helped to improve the performance of the autonomous search mission, the accuracy …

Feature Selection And Improving Classification Performance For Malware Detection, Carlos A. Cepeda Mora

Master of Science in Computer Science Theses

The ubiquitous advance of technology has been conducive to the proliferation of cyber threats, resulting in attacks that have grown exponentially. Consequently, researchers have developed models based on machine learning algorithms for detecting malware. However, these methods require significant amount of extracted features for correct malware classification, making that feature extraction, training, and testing take significant time; even more, it has been unexplored which are the most important features for accomplish the correct classification.

In this Thesis, it is created and analyzed a dataset of malware and clean files (goodware) from the static and dynamic features provided by the online …

A Usability Study For Electronic Flight Bag (Efb) Flight Planning Applications On Tablet Devices For Ab-Initio Pilots, Jeff Schwartzentruber

International Journal of Aviation, Aeronautics, and Aerospace

The proliferation of mobile technology has prompted the use of tablet devices in the cockpit and during ground operations in general aviation. Due to the increase in affordable and reliable hardware (i.e. iPads etc.), the development of pilot-specific software has led to the creation of a commercial-of-the-shelf (COTS), electronic flight bag (EFB) market. EFBs have many advantages, such as reducing the space requirements for flight documents, enabling faster searching and indexing of files, providing useful tools for flight planning, and providing automatic updates. The increase in availability of mobile technology and flight applications has allowed general aviation enthusiast and ab-initio …

Propagating Degrees Of Truth On An Argumentation Framework: An Abstract Account Of Fuzzy Argumentation, Pierpaolo Dondio

Conference papers

This paper proposes a computational framework to reason with conflicting and gradual evidence. The framework is a synthesis of Dung’s seminal work in argumentation semantics with multi-valued logic. Abstract grounded semantics is used to identify the conditions under which a conclusion can be accepted, while multi-valued logic operators are used to quantify the degree of truth of such conditions. We propose a truth-compositional recursive computation based on the notion of irrelevant arguments, and we discuss examples using the major multi-valued logics: Godel’s, Zadeh’s and Łukasiewicz's logic.

Cyber Security Risks In Public High Schools, Ion Goran

Student Theses

Today, just like other organizations, schools are vulnerable to cyber-attacks. This vulnerability has vividly revealed itself in recent years, with the number of attacks on public schools increasing and taking ever-changing forms. Today, the student’s grades, disciplinary notes, learning diagnoses, phone numbers, addresses, and another identifying information is all at risk of being exposed. Moreover, poor network security poses a dire threat to parents of school children whose personal records contain sensitive or dangerous information. The practical implications of these attacks require intervention or remedy to increase cyber security. Cyberattacks may take place when storage facilities or infected devices are …

Small Fixed-Wing Aerial Positioning Using Inter-Vehicle Ranging Combined With Visual Odometry, Benjamin M. Fain

Theses and Dissertations

There has been increasing interest in developing the ability for small unmanned aerial systems (SUAS) to be able to operate in environments where GPS is not available. This research considers the case of a larger aircraft loitering above a smaller GPS-denied SUAS. This larger aircraft is assumed to have greater resources which can overcome the GPS jamming and provide range information to the SUAS flying a mission below. This research demonstrates that using a ranging update combined with an aircraft motion model and visual odometry can greatly improve the accuracy of a SUASs estimated position in a GPS-denied environment.

A Hierarchical Learning Model For Extracting Public Health Data From Social Media, Elham Rastegari

UNO Student Research and Creative Activity Fair

In decision making processes, particularly when it comes to health-related decisions, each relevant piece of information is important. This is particularly important when it comes to health conditions for which there remains a high degree of non-determinism as far as diagnosis and treatment. Online social media, are places in which people feel free to share their opinions about numerous topics, including public health issues and how individuals have responded to different types of treatments associated with diseases. social media could represent a secondary source that can be used as a supplement to other data sources. This would allow individuals as …

Evergreen: A Senior Project, Ashley Grover

Computer Engineering

No abstract provided.

Corgi: Compute Oriented Recumbent Generation Infrastructure, Christopher Allen Hunt

Master's Theses

Creating a bicycle with a rideable geometry is more complicated than it may appear, with today’s mainstay designs having evolved through years of iteration. This slow evolution coupled with the bicycle’s intricate mechanical system has lead most builders to base their new geometries off of previous work rather than expand into new design spaces. This crutch can lead to slow bicycle iteration rates, often causing bicycles to all look about the same. To combat this, several bicycle design models have been created over the years, with each attempting to define a bicycle’s handling characteristics given its physical geometry. However, these …

Normalizer: Augmenting Code Clone Detectors Using Source Code Normalization, Kevin Ly

Master's Theses

Code clones are duplicate fragments of code that perform the same task. As software code bases increase in size, the number of code clones also tends to increase. These code clones, possibly created through copy-and-paste methods or unintentional duplication of effort, increase maintenance cost over the lifespan of the software. Code clone detection tools exist to identify clones where a human search would prove unfeasible, however the quality of the clones found may vary. I demonstrate that the performance of such tools can be improved by normalizing the source code before usage. I developed Normalizer, a tool to transform C …