Physical Sciences and Mathematics Commons^™

Application Of Machine Learning Techniques In Credit Card Fraud Detection, Ronish Shakya

UNLV Theses, Dissertations, Professional Papers, and Capstones

Credit card fraud is an ever-growing problem in today’s financial market. There has been a rapid increase in the rate of fraudulent activities in recent years causing a substantial financial loss to many organizations, companies, and government agencies. The numbers are expected to increase in the future, because of which, many researchers in this field have focused on detecting fraudulent behaviors early using advanced machine learning techniques. However, the credit card fraud detection is not a straightforward task mainly because of two reasons: (i) the fraudulent behaviors usually differ for each attempt and (ii) the dataset is highly imbalanced, i.e., …

Combinatorial Ant Optimization And The Flowshop Problem, Tasmin Chowdhury

UNLV Theses, Dissertations, Professional Papers, and Capstones

Researchers have developed efficient techniques, meta-heuristics to solve many Combinatorial Optimization (CO) problems, e.g., Flow shop Scheduling Problem, Travelling Salesman Problem (TSP) since the early 60s of the last century. Ant Colony Optimization (ACO) and its variants were introduced by Dorigo et al. [DBS06] in the early 1990s which is a technique to solve CO problems. In this thesis, we used the ACO technique to find solutions to the classic Flow shop Scheduling Problem and proposed a novel method for solution improvement. Our solution is composed of two phases; in the first phase, we solved TSP using ACO technique which …

Efficient And Practical Composition Of Lock-Free Data Structures, Neha Bajracharya

UNLV Theses, Dissertations, Professional Papers, and Capstones

A concurrent data object is lock-free if it guarantees that at least one, among all concurrent operations, finishes after a finite number of steps. In other words, a lock free technique guarantees that some thread always makes progress. Lock-free data objects offer several advantages over their blocking counterparts, such as being immune to deadlocks and priority inversion, and typically provide high scalability and performance, especially in shared memory multiprocessor architectures.

Composition of data structures is a powerful approach to combine simple data structures to create more complex ones. It works as a building block for many advanced useful data structures. …

Uas-Based Object Tracking Via Deep Learning, Marc Dinh

UNLV Theses, Dissertations, Professional Papers, and Capstones

Tracking is the task of identifying an object of interest and detect its position over time, and has numerous applications like surveillance, security and traffic control. In present times, unmanned aerial vehicles (UAV) have been more and more common which provides us with a new and less explored domain, with an ideal vantage point for surveillance and monitoring applications.. Aerial tracking is a particularly challenging task as it introduces new environmental variables such as rapid motion in 3D space. We propose a new deep learned tracker architecture catered to aerial tracking.

First, a study of six state-of-the-art deep learned trackers …

Scheduling Two Machines With Dissimilar Costs, Madhurupa Moitra

UNLV Theses, Dissertations, Professional Papers, and Capstones

We consider two devices, which has states ON and OFF. In the ON state, the devices use their full power whereas in the OFF state the devices consume no energy but a constant cost is associated with switching back to ON. Such two devices are configured with different run and power-up costs on which a sequence of jobs must be processed. The object is to minimize the cost. Such systems are widely used to conserve energy, for example, to speed scale CPUs, to control data centers, or to manage renewable energy.

The problems are studied in the framework of online …

Performance Analysis Of Blockchain Platforms, Pradip Singh Maharjan

UNLV Theses, Dissertations, Professional Papers, and Capstones

Blockchain technologies have drawn massive attention to the world these past few years mostly because of the burst of cryptocurrencies like Bitcoin, Etherium, Ripple and many others. A Blockchain, also known as distributed ledger technology, has demonstrated huge potential in saving time and costs. This open-source technology which generates a decentralized public ledger of transactions is widely appreciated for ensuring a high level of privacy through encryption and thus sharing the transaction details only amongst the participants involved in the transactions. The Blockchain is used not only for cryptocurrency but also by various companies to meet their business ends, such …

Application Of Machine Learning In Cancer Research, Mandana Bozorgi

UNLV Theses, Dissertations, Professional Papers, and Capstones

This dissertation revisits the problem of five-year survivability predictions for breast cancer using machine learning tools. This work is distinguishable from the past experiments based on the size of the training data, the unbalanced distribution of data in minority and majority classes, and modified data cleaning procedures. These experiments are also based on the principles of TIDY data and reproducible research. In order to fine-tune the predictions, a set of experiments were run using naive Bayes, decision trees, and logistic regression.

Of particular interest were strategies to improve the recall level for the minority class, as the cost of misclassification …

Study Of Blockchain-As-A-Service Systems With A Case Study Of Hyperledger Fabric Implementation On Kubernetes, Aniket Jalinder Yewale

UNLV Theses, Dissertations, Professional Papers, and Capstones

Blockchain is a shared, immutable, decentralized ledger to record the transaction history. Blockchain technology has changed the world, changed the way we do the business. It has transformed the commerce across every industry, which may be supply chain, IoT, financial services, banking, healthcare, agriculture and many more. It had introduced a new way of transactional applications that bring trust, security, transparency and accountability.

To develop any blockchain use case, the main task is to develop an environment for creating and deploying the application. In our case, we created an environment on IBM Cloud Kubernetes service using Kubernetes, a container orchestration …

Deep Data Locality On Apache Hadoop, Sungchul Lee

UNLV Theses, Dissertations, Professional Papers, and Capstones

The amount of data being collected in various areas such as social media, network, scientific instrument, mobile devices, and sensors is growing continuously, and the technology to process them is also advancing rapidly. One of the fundamental technologies to process big data is Apache Hadoop that has been adopted by many commercial products, such as InfoSphere by IBM, or Spark by Cloudera. MapReduce on Hadoop has been widely used in many data science applications. As a dominant big data processing platform, the performance of MapReduce on Hadoop system has a significant impact on the big data processing capability across multiple …

Advancing Community Detection Using Keyword Attribute Search, Sanket Chobe

UNLV Theses, Dissertations, Professional Papers, and Capstones

As social network structures evolve constantly, it is necessary to design an efficient mechanism to track the influential nodes and accurate communities in the networks. The attributed graph represents the information about properties of the nodes and relationships between different nodes, hence, this attribute information can be used for more accurate community detection. Current techniques of community detection do not consider the attribute or keyword information associated with the nodes in a graph. In this thesis, I propose a novel ideal of online community detection using a technique of keyword search over the attributed graph. First, the influential attributes are …

Algorithms For Tower Placement On Terrain, Binay Dahal

UNLV Theses, Dissertations, Professional Papers, and Capstones

We review existing algorithms for the placement of towers for illuminating 1.5D and 2.5D terrains. Finding the minimum number of towers of zero height to illuminate 1.5D terrain is known to be NP-Hard. We present approximation algorithms for solving two variations of the tower placement problem. In the first variation, we consider the placement of a single tower of given height to maximize visibility coverage. In the second variation, we consider the problem of placing reduced number of common height towers to cover the entire terrain. Algorithms for solving both problem variations are based on discretizing the problem domain by …

Concurrency In Blockchain Based Smartpool With Transactional Memory, Laxmi Kadariya

UNLV Theses, Dissertations, Professional Papers, and Capstones

Blockchain is the buzzword in today's modern technological world. It is an undeniably ingenious invention of the 21st century. Blockchain was first coined and used by a cryptocurrency namedBitcoin. Since then bitcoin and blockchain are so popular that every single person is taking on bitcoin these days and the price of bitcoin has leaped to a staggering price in the last year and so.Today several other cryptocurrencies have adapted the blockchain technology.

Blockchain in cryptocurrencies is formed by chaining of blocks. These blocks are created by the nodes called miners through the process called Proof of Work(PoW). Mining Pools are …

Design On High Performance Nanoscale Cmos Circuits With Low Temperature Sensitivity, Ming Zhu

UNLV Theses, Dissertations, Professional Papers, and Capstones

With the rapid development of integrated circuit (IC) design and manufacturing technology, the transistor size now can be shrunk into only couple of nanometers whereas billions of transistors can be squeezed into a square millimeter, providing unprecedented computation power. However, accompanied with continuous device miniaturization and increased integration density is the explosive growth of on-chip power dissipation and a wide range of temperature fluctuation, which can heavily and negatively affect the delay performance of the circuit, or in the worst case, the circuit may malfunction and the system can be unreliable. Therefore, improved performance resilience against temperature variations has become …

Elliptic Cryptosystem, Elizabeth Dettrey

UNLV Theses, Dissertations, Professional Papers, and Capstones

The elliptic cryptographic algorithm first presented in a paper by E. F. Dettrey and E. A. Yfantis is examined and explained in this thesis. The algorithm is based on the group operations of a set of points generated from an ellipse of arbitrary radii, and arbitrary center in the case of the generalized version, modulo a large prime. The security of the algorithm depends on the difficulty of solving a discrete logarithm in the groups used by this algorithm. While the elliptic cryptographic algorithm is not the most secure among the discrete logarithm based paradigm of cryptosystems for a given …

Machine Learning Applications In Graduation Prediction At The University Of Nevada, Las Vegas, Elliott Collin Ploutz

UNLV Theses, Dissertations, Professional Papers, and Capstones

Graduation rates of four-year institutions are an increasingly important metric to incoming students and for ranking universities. To increase completion rates, universities must analyze available student data to understand trends and factors leading to graduation. Using predictive modeling, incoming students can be assessed as to their likelihood of completing a degree. If students are predicted to be most likely to drop out, interventions can be enacted to increase retention and completion rates.

At the University of Nevada, Las Vegas (UNLV), four-year graduation rates are 15% and six-year graduation rates are 39%. To improve these rates, we have gathered seven years …

A Machine Learning Approach To Predict First-Year Student Retention Rates At University Of Nevada, Las Vegas, Aditya Rajuladevi

UNLV Theses, Dissertations, Professional Papers, and Capstones

First-year student retention rates for a four-year institution refers to the percentage of First-time Full-time students from the previous fall who return to the same institution for the following fall. First-year retention rates act as an important indicator of the student satisfaction as well as the performance of the university. Moreover, universities with low retention rates may face a decline in the admissions of talented students with a notable loss of tuition fees and contributions from alumni. Therefore, it is important for universities to formulate strategies to identify students who are at risk of not being retained and take necessary …