Physical Sciences and Mathematics Commons^™

A Fortified Extension Of The Aes And Its Implementation, Ashby Mullin

UNLV Theses, Dissertations, Professional Papers, and Capstones

With the advancement of quantum computing (QC), the integrity of cryptography has been called into question. For example, two QC algorithms have been developed that can break asymmetric encryption (i.e., Grover’s, Shor’s), which also poses a threat to symmetric encryption. Asymmetric encryption efforts addressing this threat include lattice-based cryptography, which uses lattice problems to reduce efficiency of cryptanalysis. Symmetric encryption security can be bolstered by increasing the key length, allowing for additional permutations a key could have; known as keyspace. This thesis seeks to expand the keyspace of symmetric encryption in order to create more possibilities. This fortification to the …

The Processj C++ Runtime System And Code Generator, Alexander Christian Thomason

UNLV Theses, Dissertations, Professional Papers, and Capstones

ProcessJ is a modern Process-Oriented language that builds on previous work from other languages like occam and occam-pi. However, the only readily-available runtime system is built on top of the Java Virtual Machine (JVM). This is not a choice made intentionally, but simply out of a lack of other implementations -- until now. This thesis introduces the new C++-based runtime system for ProcessJ, coupled with a new C++ code generator for the ProcessJ compiler. This thesis later examines the implementation details of the runtime system, including the components that make it up. We also examine the ability to cooperatively schedule …

A Divide And Conquer With Semi-Global Failover For Software Defined Networks, Kasra Goravanchi

UNLV Theses, Dissertations, Professional Papers, and Capstones

Nowadays, many service providers need to provide many other functions than just a network connectivity. They also need to provide network functions such as network address translation, firewall, encryption, Domain Name Service (DNS), caching, routing and many other services. Usually these functions come with the hardware at the user or customer’s premises. This can increase the revenue of the revenue, but also can cost a lot and also be extremely difficult to maintain. Moreover, it is important to be able to configure the network and later modify the configuration to create fault tolerance and to prepare the system for future …

Analysis Of Blockchain-Based Storage Systems, Phillipe Austria

UNLV Theses, Dissertations, Professional Papers, and Capstones

Increasing storage needs has driven cloud storage to become a prevalent choice to store data for both business and personal use. Cloud service providers, such as Google, offer advantages over storing personal hard drives; however, customers lose privacy and require trust in the provider to act honestly with their data. This thesis explores an alternative to cloud storage using Blockchain technology. I focus on Sia, a blockchain-based storage platform that allows users to rent storage from other users.

In this study, I evaluate the security, performance and costs between the Sia and traditional cloud storage. I assessed security based on …

An Investigation Into Multi-View Error Correcting Output Code Classifiers Applied To Organ Tissue Classification, Daniel Alvarez

UNLV Theses, Dissertations, Professional Papers, and Capstones

Large amounts of data is being generated constantly each day, so much data that it is difficult to find patterns in order to predict outcomes and make decisions for both humans and machines alike. It would be useful if this data could be simplified using machine learning techniques. For example, biological cell identity is dependent on many factors tied to genetic processes. Such factors include proteins, gene transcription, and gene methylation. Each of these factors are highly complex mechanism with immense amounts of data. Simplifying these can then be helpful in finding patterns in them. Error-Correcting Output Codes (ECOC) does …

A Framework For Vector-Weighted Deep Neural Networks, Carter Chiu

UNLV Theses, Dissertations, Professional Papers, and Capstones

The vast majority of advances in deep neural network research operate on the basis of a real-valued weight space. Recent work in alternative spaces have challenged and complemented this idea; for instance, the use of complex- or binary-valued weights have yielded promising and fascinating results. We propose a framework for a novel weight space consisting of vector values which we christen VectorNet. We first develop the theoretical foundations of our proposed approach, including formalizing the requisite theory for forward and backpropagating values in a vector-weighted layer. We also introduce the concept of expansion and aggregation functions for conversion between real …

A Machine Learning Approach To Predict Retention Of Computer Science Students At University Of Nevada, Las Vegas, Sudhir Deshmukh

UNLV Theses, Dissertations, Professional Papers, and Capstones

Student retention is an important measure when in determining student success. Retention refers to the first-time full-time student from previous fall term who returned to the same university for the following fall term. Decline in retention rate have adverse effect on stakeholders, parents, and students view about the institution, revenue generated from tuition cost and obtaining outside funds. In an effort to increase retention rates, universities have started analyzing the factors that correlate with students dropping out. Many universities have identified some of these factors and are working on developing intervention programs to help students to elevate their academic performance …

Machine Learning For Prediction Of Trabecular And Cortical Bone Mineral Density, Partha Chudal

UNLV Theses, Dissertations, Professional Papers, and Capstones

Osteoporosis becomes very common problem for people after a certain age, which results in fragility fractures without any previous symptoms. One of the primary predictors of osteoporosis is bone mineral density (BMD). BMD is the mineral content of bone, at the optimal levels, that makes the bone strong enough to bear the regular load and elastic enough to handle the irregular twisting load. Two of the major parts of the bone that help to acquire such property are trabecular and cortical bone. This thesis focuses on predicting the BMDs of trabecular and cortical bone for men. For this purpose we …

Toward Productivity Improvements In Programming Languages Through Behavioral Analytics, Patrick Daleiden

UNLV Theses, Dissertations, Professional Papers, and Capstones

Computer science knowledge and skills have become foundational for success in virtually every professional field. As such, productivity in programming and computer science education is of paramount economic and strategic importance for innovation, employment and economic growth. Much of the research around productivity and computer science education has centered around improving notoriously difficult compiler error messages, with a noted surge in new studies in the last decade. In developing an original research plan for this area, this dissertation begins with an examination of the Case for New Instrumentation, draw- ing inspiration from automated data mining innovations and corporate marketing techniques …

Machine Learning Approach For Predicting Cancer Using Gene Expression, Aashi Maharjan

UNLV Theses, Dissertations, Professional Papers, and Capstones

Cancer has become one of the major factors responsible for global deaths, due to late diagnoses and lack of proper treatment. It involves the abnormal and uncontrolled growth of cells inside the body, which might spread from one place to different parts. Ribonucleic acid (RNA) sequencing can detect the changes occurring inside cells and helps to analyze the transcriptome of gene expression patterns inside RNA. Machine learning techniques can assist in the prediction of cancer at an early stage, if data is available. The objective of this thesis is to build models and classify different types of cancer. For this …

Towards Multi-Modal Data Classification, Henry Ng

UNLV Theses, Dissertations, Professional Papers, and Capstones

A feature fusion multi-modal neural network (MMN) is a network that combines different modalities at the feature level to perform a specific task. In this paper, we study the problem of training the fusion procedure for MMN. A recent study has found that training a multi-modal network that incorporates late fusion produces a network that has not learned the proper parameters for feature extraction. These late fusion models perform very well during training but fall short to its single modality counterpart when testing. We hypothesize that jointly trained MMN have weight space that is too large for effective training. To …

Studies On Kernels Of Simple Polygons, Jason Mark

UNLV Theses, Dissertations, Professional Papers, and Capstones

The kernel of a simple polygon is the set of points in its interior from which all points inside the polygon are visible. We formally establish that for a given convex polygon Q we can always construct a larger simple polygon with many reflex vertices such that Q is the kernel of P. We present algorithms for decomposing a strongly monotone polygon into star-polygons. This decomposition is applied for developing an efficient algorithm for placing a small number of vertical towers to cover the entire given 1.5D terrain. We also present an experimental investigation of the proposed algorithm. The implementation …

Detection Of Snps Associated With Bone Loss Rate By Using Machine Learning Approaches, Avinash Yaganapu

UNLV Theses, Dissertations, Professional Papers, and Capstones

Osteoporosis is one of the most common diseases seen in postmenopausal women, it decreases the bone density and quality, and later causes bone loss. Generally, bone loss occurs when bone losses its content and become porous: a sponge like substance. In most Genome Wide Association Studies (GWAS), researchers perform experiments with genomic data that contains some millions of numbers of single nucleotide polymorphisms (SNPs) and checks their association with the trait or disease. In this thesis, we performed two separate analyses with 2207 (of bone loss and bone gain) and 645 (of bone loss) instances separately. For predicting the SNPs …