Computer Sciences Commons^™

A Simulator Application For Distributed Leader Election Algorithms, Sugeeswara Gurudeniya

UNLV Theses, Dissertations, Professional Papers, and Capstones

We present an application program, Distributed Algorithm Simulator, to simulate the execution of distributed leader election algorithms in a ring-network. The application was developed using Visual C# on Microsoft .NET Framework 4.5. The Distributed Algorithm Simulator consists of two major components: A Visual Simulator, which visually demonstrates the execution of the algorithms; and a Textual Simulator, which simulates the execution in text format. In both cases the end-result can be saved to a file.

The Visual Simulator displays the network in a ring orientation with circles representing the nodes, and numbers on them showing the node IDs. The user has …

A Study On Automated Process For Extracting White Blood Cellular Data From Microscopic Digital Injured Skeletal Muscle Images, Bibek Karki

UNLV Theses, Dissertations, Professional Papers, and Capstones

Skeletal muscle injury is one of the common injuries caused by high-intensity sports activities, military related works, and natural disasters. In order to discover better therapies, it is important to study muscle regeneration process. Muscle regeneration process tracking is the act of monitoring injured tissue section over time, noting white blood cell behavior and cell-fiber relations. A large number of microscopic images are taken for tracking muscle regeneration process over multiple time instances. Currently, manual approach is widely used to analyze a microscopic image of muscle cross section, which is time consuming, tedious and buggy.

Automation of this research methodology …

Analysis Of Power-Down Systems With Five States, Govind Pathak

UNLV Theses, Dissertations, Professional Papers, and Capstones

We consider a device, which has states ON, OFF and fixed number of intermediate states.In the ON state the device uses full power whereas in the OFF state the device consumes no energy but a constant cost is associated with switching back to ON. Intermediate states use some fraction of energy proportional to the usage time but switching back to the ON state has a constant setup cost depending on the current state. Such systems are widely used to conserve energy, for example to speed scale CPUs, to control data centers, or to manage renewable energy.

We analyze such a …

A Web-Based Solution For Small Unmanned Aircraft System (Suas) Traffic Management, Monetta Angelique Shaw

UNLV Theses, Dissertations, Professional Papers, and Capstones

There is currently no system in place for safely managing small unmanned aircraft systems (UAS). Small UAS (sUAS) pose a safety hazard to both manned aircraft and people on the ground. The initial solution to this problem proposed in this paper is a system that consists of a web server and an Android mobile application (app). In this solution, the server is only accessible through the Android mobile app. After evaluating the initial solution, we determine that the system in this solution would be unable to quickly adjust to changes in technology and in the sUAS industry. To solve this …

Parallel Static Object Detection, Tirambad Shiwakoti

UNLV Theses, Dissertations, Professional Papers, and Capstones

The need for parallelism is growing with the broadening of computing in the real world where computing is an integral part of any field. In the early days of computing, adding transistors to the CPU could solve computation complexity. This is not the case now, where we can no longer advance the hardware capabilities at the pace of the advancement of computing problems. One of the fields which is intensive in computation is image processing. If it were just for one frame of an image, we could cope with the computation overhead. When the need is to compute video frames, …

Mining Unstructured Log Messages For Security Threat Detection, Candace Suh-Lee

UNLV Theses, Dissertations, Professional Papers, and Capstones

As computers become larger, more powerful, and more connected, many challenges arise in implementing and maintaining a secure computing environment. Some of the challenges come from the exponential increase of unstructured messages generated by the computer systems and applications. Although these data contain a wealth of information that is useful for advanced threat detection and prediction for future anomalies, the sheer volume, variety, and complexity of data make it difficult for even well-trained analysts to extract the right information. While conventional SIEM (Security Information and Event Management) tools provide some capability to collect, correlate, and detect certain events from structured …

An Empirical Study On The Impact Of C++ Lambdas And Programmer Experience, Phillip Merlin Uesbeck

UNLV Theses, Dissertations, Professional Papers, and Capstones

Lambda functions have become prevalent in mainstream programming languages, as they are increasingly introduced to widely used object oriented programming languages such as Java and C++. Some in the scientific literature argue that this feature increases programmer productivity, ease of reading, and makes parallel programming easier. Others are less convinced, citing concerns that the use of lambdas makes debugging harder. This thesis describes the design, execution and results of an experiment to test the impact of using lambda functions compared to the iterator design pattern for iteration tasks, as a first step

in evaluating these claims. The approach is a …

Exploring Privacy Leakage From The Resource Usage Patterns Of Mobile Apps, Amin Rois Sinung Nugroho

Graduate Theses and Dissertations

Due to the popularity of smart phones and mobile apps, a potential privacy risk with the usage of mobile apps is that, from the usage information of mobile apps (e.g., how many hours a user plays mobile games in each day), private information about a user’s living habits and personal activities can be inferred. To assess this risk, this thesis answers the following research question: can the type of a mobile app (e.g., email, web browsing, mobile game, music streaming, etc.) used by a user be inferred from the resource (e.g., CPU, memory, network, etc.) usage patterns of the mobile …

Evaluation Of Topic Models For Content-Based Popularity Prediction On Social Microblogs, Axel Magnuson

Boise State University Theses and Dissertations

Online social networks are an increasingly central medium of communication in the 21st century. We have seen a proliferation of competing social networks which differentiate themselves by serving different niches of communication. Among these, Twitter has risen to prominence as a leader among microblogging communities, characterized by publicly visible 140-character messages called tweets. The wide visibility of Twitter messages has enabled some users to curate large followings, and has facilitated content creators who wish to reach as many viewers as possible. Researchers have since investigated many methods for predicting which messages will become popular or even go viral on Twitter. …

Identification Of Small Endogenous Viral Elements Within Host Genomes, Edward C. Davis Jr.

Boise State University Theses and Dissertations

A parallel string matching software architecture has been developed (incorporating several algorithms) to identify small genetic sequences in large genomes. Endogenous viral elements (EVEs) are sequences originating in the genomes of viruses that have become integrated into the chromosomes of sperm or egg cells of infected hosts, and passed to subsequent generations. EVEs have been identified in all seven classes of viruses and in the species of all kingdoms of life. Viruses from groups V and VI are considered in this thesis, including HIV and Ebola, within host genomes ranging from bacteria to humans. This database of small endogenous viral …

Activity Pattern Discovery From Network Captures, Alan C. Lin, Gilbert L. Peterson

Faculty Publications

Investigating insider threat cases is challenging because activities are conducted with legitimate access that makes distinguishing malicious activities from normal activities difficult. To assist with identifying non-normal activities, we propose using two types of pattern discovery to identify a person's behavioral patterns in network data. The behavioral patterns serve to deemphasize normal behavior so that insider threat investigations can focus attention on potentially more relevant. Results from a controlled experiment demonstrate the highlighting of a suspicious event through the reduction of events belonging to discovered patterns. Abstract © 2016 IEEE.

Privacy-Preserving Controls For Sharing Mhealth Data, Aarathi Prasad

Dartmouth College Ph.D Dissertations

Mobile devices allow people to collect and share health and health-related information with recipients such as health providers, family and friends, employers and insurance companies, to obtain health, emotional or financial benefits. People may consider certain health information sensitive and prefer to disclose only what is necessary. In this dissertation, we present our findings about factors that affect people’s sharing behavior, describe scenarios in which people may wish to collect and share their personal health-related information with others, but may be hesitant to disclose the information if necessary controls are not available to protect their privacy, and propose frameworks to …

Exploiting Self-Organization In Bioengineered Systems: A Computational Approach, Delin Davis

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Bio-reactors, also known as microbial factories are used extensively to produce various industrially valuable products. However, scalability and stability of these factories are limited as it is difficult to deliver nutrients and extract product and waste from a large system. Current solution approaches explore changes in the physical configuration of the bio-reactors. Inspired from the nutrient delivery mechanisms of large organisms in nature, this work studies the possibilities of exploiting self-organizing bio-engineered cells which are capable of organizing into a vessel network to support the producer cells in the factory.

Primary goal of this dissertation is to design a proof-of-concept …

Hidden History: A Mobile Application For Discovering Surrounding Landscapes, Sri Ram Ramineni

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

This thesis work describes the design, development and evaluation of a mobile application called Hidden History. This application lets users discover and explore three types of landscapes (Historic, Scenic and Cultural) using three different modes of discovery (Route, Explore and Tour).

Before designing Hidden History, the feature set of other applications that help users explore surrounding landscapes were identified and analyzed. Hidden History was then designed to implement the best features of these applications and offer several functionality improvements. Design began with iterative paper prototyping, following which a high fidelity, digital prototype was created. The high fidelity prototype was tested …

Fake Likers Detection On Facebook, Prudhvi Ratna Badri Satya

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

As billions of users have used online social networks such as Facebook, Twitter, and Instagram, many online services have begun adapting signals of the popularity. For example, search engines rank popular users posts in the top results. A post of a popular user is automatically delivered to the followers or likers. Popular companies in online social networks also get good reputation from people. The popularity on Facebook is measured based on the number of likes in a page. Unfortunately, some crowdsourcing websites (e.g.Microworkers.com) or supply-driven marketplaces (e.g.Fiverr.com) began offering fake liking services in which these crowd workers sent fake likes …

Interference Mitigation In Multi-Hop Wireless Networks With Advanced Physical-Layer Techniques, Yantian Hou

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

With the ever-growing number of wireless systems, the problem of spectrum scarcity is becoming more important than ever. Many devices coexist in the same frequency band, e.g., IEEE 802.11 (WiFi), 802.15.4 (ZigBee), 802.16 (WiMax), and Bluetooth in the ISM bands. Coexisting in the crowded spectrum bands inevitably leads to mutual interferences. For a wireless network, the interference could be from external sources such as microwave oven and cordless phone, or from internal nodes within multi-flow and multi-hop wireless networks. All these interferences can be detrimental to the performance of co-locating networks if they are not properly mitigated. In my dissertation, …

Cluster-Based Salient Object Detection Using K-Means Merging And Keypoint Separation With Rectangular Centers, Robert Buck

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

The explosion of internet traffic, advent of social media sites such as Facebook and Twitter, and increased availability of digital cameras has saturated life with images and videos. Never before has it been so important to sift quickly through large amounts of digital information. Salient Object Detection (SOD) is a computer vision topic that finds methods to locate important objects in pictures. SOD has proven to be helpful in numerous applications such as image forgery detection and traffic sign recognition. In this thesis, I outline a novel SOD technique to automatically isolate important objects from the background in images.

Motionscan: Towards Brain Concussion Detection With A Mobile Tablet Device, Shantanu Saxena

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

This thesis reports on a study to determine the viability of using a mobile tablet device as a brain concussion detection tool. The research builds upon the results of a prior method of collecting data for measuring motion sensitivity, where a user presses and releases a force sensor to balance a rising and falling line on a computer display. The motion sensitivity data collected using this force sensor device was shown to have less irregularity in persons with concussion. The MotionScan application, developed for this research, uses the accelerometer of a tablet device to record motor movement of a user …

Vision Based Extraction Of Nutrition Information From Skewed Nutrition Labels, Tanwir Zaman

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Vision-based extraction of nutritional information from nutrition labels (NLs) available on most product packages is critical to proactive nutrition management, because it improves the user’s ability to engage in continuous nutritional data collection and analysis. However, even users who are health conscious find it difficult to keep track of their nutrition intake due to lack of time, motivation, or training. In order to make nutrition management more proactive we present a Proactive NUTrition Management System (PNUTS), which aims to make nutrition management more user friendly and proactive using computer vision techniques running on smartphones which are ubiquitous and powerful computers …

Top-K Nodes Identification In Big Networks Based On Topology And Activity Analysis, Sweta Gurung

UNLV Theses, Dissertations, Professional Papers, and Capstones

Graphs and Networks have been the most researched topics with applications ranging from theoretical to practical fields, such as social media, genetics, and education. In many competitive environments, the most productive activities may be interacting with high-profile people, reading a much-cited article, or researching a wide range of fields such as the study on highly connected proteins. This thesis proposes two methods to deal with top-K nodes identification: centrality-based and activity-based methods for identifying top-K nodes. The first method is based on the topological structure of the network and uses the centrality measure called Katz Centrality; a path based ranking …

Algorithms For Monotone Paths With Visibility Properties, Bikash Lama Bamjan

UNLV Theses, Dissertations, Professional Papers, and Capstones

Constructing collision-free paths in Euclidean space is a well-known problem in computational geometry having applications in many fields that include robotics, VLSI, and covert surveillance. In this thesis, we investigate the development of efficient algorithms for constructing a collision-free path that satisfies directional and visibility constraints. We present algorithms for constructing monotone collision-free paths that tend to maximize the visibility of the boundary of obstacles. We also present implementation of some monotone path planning algorithms in Java Programming Language.

Efficient Algorithms For Clustering Polygonal Obstacles, Sabbir Kumar Manandhar

UNLV Theses, Dissertations, Professional Papers, and Capstones

Clustering a set of points in Euclidean space is a well-known problem having applications in pattern recognition, document image analysis, big-data analytics, and robotics. While there are a lot of research publications for clustering point objects, only a few articles have been reported for clustering a given distribution of obstacles. In this thesis we examine the development of efficient algorithms for clustering a given set of convex obstacles in the 2D plane. One of the methods presented in this work uses a Voronoi diagram to extract obstacle clusters. We also consider the implementation issues of point/obstacle clustering algorithms.

A Web Based User Interface For Machine Learning Analysis Of Health And Education Data, Chandani Shrestha

UNLV Theses, Dissertations, Professional Papers, and Capstones

The objective of this thesis is to develop a user friendly web application that will be used to analyse data sets using various machine learning algorithms. The application design follows human computer interaction design guidelines and principles to make a user friendly interface [Shn03]. It uses Linear Regression, Logistic Regression, Backpropagation machine learning algorithms for prediction. This application is built using Java, Play framework, Bootstrap and IntelliJ IDE. Java is used in the backend to create a model that maps the input and output data based on any of the above given learning algorithms while Play Framework and Bootstrap are …

Foramsim: Design And Analysis Of A Computer Simulation For Training Students To Identify Morphological Characteristics In Select Foraminifera, Kristine Michele Hooks

Departmental Honors & Graduate Capstone Projects

The purpose of this project was to develop an interactive web application to aid students in learning how to identify foraminifera, in addition to meeting the larger goal of providing accessibility of a museum collection to the public. This type of public outreach is an integral part of the Smithsonian Institution's mission to provide online access to the museum collections and research activities. The National Museum of Natural History's Department of Paleobiology seeks innovative ways to improve the connection between in-house collections and online content. This project is intended to improve science communication to the public by providing a visual …

Artificial Intelligence: Prospects, Pathways, Realities, Timur Javid '17, Tara Parkman '17, Nathaniel Smith '17

IMSAloquium Student Investigation Showcase

The specter of Artificial Intelligence (AI) looms before us, continuously growing in power, soon to match, and then exceed human capabilities. To explore this, we read and discussed books by experts, and learned about the exponential nature of technological progress and the difficulties of halting or even slowing it. Technological improvements trend towards an autonomous AI capable of replicating, if not exceeding human thought and interaction, a complex adaptive system with an input stream, isomorphic model of reality and output mechanism, fully capable of passing the Turing Test. How a system is organized is a key determinant of the processes …

Neural Networks And Machine Learning Applied To Classification Of Cancer, Sachin Govind '16

IMSAloquium Student Investigation Showcase

Using genome data to predict cancer type is an increasingly relevant practice as it provides a direct, noninvasive strategy to analyze genetic predisposition to malignant cancer types. More specifically, analysis of gene expression data across the genome can provide insight into the underlying gene interactions that propel the progression of tumors. A database containing expression levels for 16,063 genes was split into disjoint training and testing sets; these were subjected to a variety of machine learning methods and statistical analyses, including multinomial logistic regression across cancer phenotypes, k-means clustering analysis, optimization of a predictive support vector machine, and rooted random …

Enterprise Network Design And Implementation For Airports, Ashraf H. Ali

Information Technology Master Theses

The aim of this project was airports network design and implementation and the introduction of a suitable network for most airports around the world. The following project focused on three main parts: security, quality, and safety. The project has been provided with different utilities to introduce a network with a high security level for the airport. These utilities are hardware firewalls, an IP access control list, Mac address port security, a domain server and s proxy server. All of these utilities have been configured to provide a secure environment for the entire network and to prevent hackers from entering sensitive …

Blossom: A Language Built To Grow, Jeffrey Lyman

Mathematics, Statistics, and Computer Science Honors Projects

No abstract provided.

A Study Of Android Malware Detection Techniques And Machine Learning, Balaji Baskaran, Anca Ralescu

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

Android OS is one of the widely used mobile Operating Systems. The number of malicious applications and adwares are increasing constantly on par with the number of mobile devices. A great number of commercial signature based tools are available on the market which prevent to an extent the penetration and distribution of malicious applications. Numerous researches have been conducted which claims that traditional signature based detection system work well up to certain level and malware authors use numerous techniques to evade these tools. So given this state of affairs, there is an increasing need for an alternative, really tough malware …

Extended Pixel Representation For Image Segmentation, Deeptha Girish, Vineeta Singh, Anca Ralescu

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

We explore the use of extended pixel representation for color based image segmentation using the K-means clustering algorithm. Various extended pixel representations have been implemented in this paper and their results have been compared. By extending the representation of pixels an image is mapped to a higher dimensional space. Unlike other approaches, where data is mapped into an implicit features space of higher dimension (kernel methods), in the approach considered here, the higher dimensions are defined explicitly. Preliminary experimental results which illustrate the proposed approach are promising.