Computer Sciences Commons^™

Krahasimi I Autentifikimit Me Shumë Faktorë Të Tre Platformave Cloud, Alban Gojani

Theses and Dissertations

Qëllimi i këtij punimi është krahasimi i autentifikimit me shumë faktorë (MFA) të tre platformave cloud më të përdorura: Microsot Azure, Amazon Web Services dhe Google Cloud Platform. MFA-ja është ndër metodat më të sigurta për autentifikim që përdoret në sisteme kompjuterike. Materiali i përdorur për këtë punim është marrë nga burime të ndryshme, gjegjësisht nga dokumentacionet e platformave cloud të lartëpërmendura, hulumtime shkencore me tema të ngjajshme, artikuj dhe publikime shkencore në internet dhe nga enciklopedia. Fillimisht është shtjelluar MFA-ja si mekanizëm në vete dhe historia e tij, pastaj janë përshkruar MFA-të e këtyre platformave dhe në fund është …

Aplikimi I Sistemeve Te Informacionit E-Health Care Në Kosovë, Ardit Imeri

Theses and Dissertations

Gjithkush flet për eHealth këto ditë, por pak njerëz kanë dalë me një përkufizim të qartë të këtij termi relativisht të ri. Pak në përdorim para vitit 1999, ky term tani duket se shërben si një fjalë e përgjithshme, që përdoret për të karakterizuar jo vetëm "mjekësinë e digjitalizuar", por gjithashtu pothuajse çdo gjë që lidhet me kompjuterët dhe mjekësinë. Termi eHealth është krijuar dhe pëdorur duke u bazuar në fjalët tjera “e-fjal” si përshembull “e-commerce, e-business, e-mail”, me të cilën fjalë do të mund ti referoheshim mundësive të reja që interneti po i hap në fushën e kujdesit mjeksor. …

Analiza E Sentimentit Të Opinionit Duke Përdorur Qasjen Naïve Bayes Dhe Entropinë Maksimale, Armir Bahtiri

Theses and Dissertations

Teknologjia e informacionit ka bërë të mundshme të kemi qasje në informata më lehtë se kurdo herë më parë. Më rritjen e numrit ta pajisje mobile, njerëzit kanë qasje në llogaritë e tyre në çdo kohë dhe thuajse çdo vend. Shfrytëzuesit e shërbimeve të internetit shprehin mendimet dhe pikëpamjet e tyre të ndryshme publikisht me shkrime të ndryshme. Pjesë e lartë e këtyre të dhënave është subjektive, që paraqet opinion të njerëzve rreth dukurive dhe proceseve të ndryshme.

Këto informata, të qasshme për ne, mund të merren dhe me një procesim të mëtejmë të analizohen për të kuptuar të dhëna …

Artificial Intelligence The Use Of Knowledge Graphs, Besar Mehmeti

Theses and Dissertations

In this digital age, an overwhelming amount of unstructured data found in the web is increasing at an unprecedented rate. In response, information extraction techniques have been developed to automatically extract information from unstructured text and populate knowledge bases. This thesis will introduce the reader to the idea of Knowledge Graphs, the history of how they were first experimented on and later developed, and in particular, this thesis is going to elaborate how Diffbot, Wikidata and IBM Watson technologies are modeled, stored and queried. By having this information at our fingertips, we believe that we can make smarter decisions, keep …

Roli I I Marketingut Digjital Në Agjensionet Turistike Në Kosovë, Fetije Braha

Theses and Dissertations

Marketingu digjital sot konsiderohet si një ndër format më të rëndësishme të promocionit,e cila me kërkimet më të reja paraqet një rëndësi strategjike për bizneset që kanë bërë përpjekjet e tyre drejt tregut elektronik. Ideja e marketingut digjital dhe cilësia e shërbimeve elektronike përbën sfidën për agjensionet turistike sot dhe në të ardhmen. Sipas publikimit të Eurostat-it , në vitin 2018, Kosova ka përqindjen e familjeve që kanë qasje në internet në shtëpi më të lartën në Rajon (93%), kjo përqindje është më e lartë se edhe në vetë vendet e BE-së (89%). Për një kohë të shkurtër, marketingu në …

Cloud Computing Adoption In Public Sector, Krenare Hoxha

Theses and Dissertations

Teknologjia e Cloud Computing është zhvillimi në kuadër të teknologjisë informative që kërkon një shqyrtim të kujdesshëm. Cloud Computing është projektuar për të qenë një teknologji efektive për kompanitë e organizatat të ndryshme përmes avantazheve që ajo ofron, siç janë: fleksibiliteti, shkallëzueshmëria, elasticiteti dhe reduktimi i shpenzimeve. Ajo ofron metodën “pay as you go” përmes së cilës paguhet vetëm për shërbimin që shfrytëzohet duke mos bërë shpenzime shtesë. Të dhënat transferohen, përpunohen dhe ruhen në infrastrukturat e shërbimeve Cloud për të cilat shërbime përgjegjës janë ofruesit Cloud.

Krahas benefiteve të Cloud Computing, organizatat e sektorit publik në fillim kanë pasur …

Publication And Evaluation Challenges In Games & Interactive Media, Elizabeth L. Lawley

Presentations and other scholarship

Faculty in the fields of games and interactive media face significant challenges in publishing and documenting their scholarly work for evaluation in the tenure and promotion process. These challenges include selecting appropriate publication venues and assigning authorship for works spanning multiple disciplines; archiving and accurately citing collaborative digital projects; and redefining “peer review,” impact, and dissemination in the context of creative digital works. In this paper I describe many of these challenges, and suggest several potential solutions.

Convex And Non-Convex Optimization Methods For Machine Learning, Fariba Zohrizadeh

Computer Science and Engineering Dissertations - Archive

This dissertation is concerned with modeling fundamental and challenging machine learning tasks as convex/non-convex optimization problems and designing a mechanism that could solve them in a cost and time-effective manner. Extensive theoretical and practical studies are carried out to give deeper insights into the robustness and effectiveness of the formulated problems. In what follows, we investigate some well-known tasks that frequently arise in machine learning applications. Image Segmentation: Image segmentation is a fundamental and challenging task in computer vision with diverse applications in various areas. One of the major challenges in image segmentation is to determine the optimal number of …

A Novel Adaptive Lbp-Based Descriptor For Color Image Retrieval, Mohammad Sotoodeh, Mohammad Reza Moosavi, Reza Boostani

Computer Science Student Research

In this paper, we present two approaches to extract discriminative features for color image retrieval. The proposed local texture descriptors, based on Radial Mean Local Binary Pattern (RMLBP), are called Color RMCLBP (CRMCLBP) and Prototype Data Model (PDM). RMLBP is a robust to noise descriptor which has been proposed to extract texture features of gray scale images for texture classification.

For the first descriptor, the Radial Mean Completed Local Binary Pattern is applied to channels of the color space, independently. Then, the final descriptor is achieved by concatenating the histogram of the CRMCLBP_S/M/C component of each channel. Moreover, to enhance …

Pose Based Human Activity Recognition, Wenbo Li

Legacy Theses & Dissertations (2009 - 2024)

Pose based human activity recognition is an important step towards video understanding. The last decade has witnessed the great progress in this field which is driven by multiple technical innovations, i.e., kinect, pose estimation techniques, deep learning, etc.

Wrinkles In Time : An Exploration Of Non-Uniform Temporal Resolution In Network Data, Daniel John Ditursi

Legacy Theses & Dissertations (2009 - 2024)

The continued proliferation of timestamped network data demands increasing sophistication in the analysis of that data. In particular, the literature amply demonstrates that the choice of temporal resolution has a profound impact on the solutions produced by many different methods in this domain -- answers differ when data is viewed second-by-second as opposed to week-by-week. Additionally, research also shows quite clearly that the rates at which network events happen are not constant -- some times are "faster" or "slower" than others, and these variations are not necessarily predictable. Given the above, it is clear that there must be problem settings …

A Survey On Bluetooth 5.0 And Mesh: New Milestones Of Iot, Juenjie Yin, Zheng Yang, Hao Cao, Tongtong Liu, Zimu Zhou, Chenshu Wu

Research Collection School Of Computing and Information Systems

No abstract provided.

Towards Robust Resnet: A Small Step But A Giant Leap, Jingfeng Zhang, Bo Han, Laura Wynter, Bryan Kian Hsiang Low, Mohan Kankanhalli

Research Collection School Of Computing and Information Systems

This paper presents a simple yet principled approach to boosting the robustness of the residual network (ResNet) that is motivated by a dynamical systems perspective. Namely, a deep neural network can be interpreted using a partial differential equation, which naturally inspires us to characterize ResNet based on an explicit Euler method. This consequently allows us to exploit the step factor h in the Euler method to control the robustness of ResNet in both its training and generalization. In particular, we prove that a small step factor h can benefit its training and generalization robustness during backpropagation and forward propagation, respectively. …

Impact Of Robotic Challenges On Fifth Grade Problem Solving, Julie Rankin

Department of Teaching, Learning, and Teacher Education: Theses and Other Student Research

This action research project was designed to investigate the impact of educational robotics in a fifth grade rural classroom. The integration of science, technology, engineering, and math in education (STEM) has sparked an increase of robotics in the classroom. The purpose of the study was to determine if problem-solving skills can be impacted through continuing involvement with challenges using various educational robotics and programming tools. The study sought to answer two research questions: (1) How does the introduction of robotics challenges in a fifth-grade classroom impact students’ problem solving skills? (2) How do robotics in the classroom impact student interest …

Distributed Edge Bundling For Large Graphs, Yves Tuyishime

School of Computing: Dissertations, Theses, and Student Research

Graphs or networks are widely used to depict the relationships between data entities in diverse scientific and engineering applications. A direct visualization (such as node-link diagram) of a graph with a large number of nodes and edges often incurs visual clutter. To address this issue, researchers have developed edge bundling algorithms that visually merge similar edges into curved bundles and can effectively reveal high-level edge patterns with reduced visual clutter. Although the existing edge bundling algorithms achieve appealing results, they are mostly designed for a single machine, and thereby the size of a graph they can handle is limited by …

Structural Bot Detection In Social Networks, Lale Madahali

Interdisciplinary Informatics Faculty Proceedings & Presentations

Social network platforms are a major part of toady’s life. They are usually used for entertainment, news, advertisements, and branding for businesses and individuals alike. However, use of automated accounts, also known as bots, pollute this environment and avoid having a reliable clean online world. In this work, I address the problem of detecting bots in online social networks.

Attack Detection In Linear Networked Control Systems By Using Learning Methodology, Haifeng Niu, A. Sahoo, C. Bhowmick, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

A novel learning-based attack detection scheme for linear networked control systems (NCS) is introduced. The class of attacks considered here tends to increase network induced delays and packet losses which affects the physical system dynamics. For the network side, an adaptive observer is proposed to generate the attack detection residual, which in turn is utilized to determine the onset of an attack when it exceeds a predefined threshold. The uncertain stochastic physical system dynamics as a result of network-induced delays of packet losses require an optimal Q-learning based event-triggered controller that optimizes the control policy and the event-triggering instants simultaneously. …

Investigating The Effects Of Social And Temporal Dynamics In Fitness Games On Children's Physical Activity, Ankita Samariya

Boise State University Theses and Dissertations

Obesity in children has more than doubled in the last four decades. A variety of fitness technologies such as activity trackers, exergames, and mobile applications are available to promote physical activity, but few are designed adequately to meet children's specific needs. In my initial research, I found that children prefer having social interaction, a narrative, and flexibility while interacting with such technologies. Other research has shown that persuasive displays encouraged adults towards physical activity. As a part of this work, a collection of mobile applications, collectively known as KidFit Suite were developed. These applications encourage children to be physically active …

Suitability Of Finite State Automata To Model String Constraints In Probablistic Symbolic Execution, Andrew Harris

Boise State University Theses and Dissertations

Probabilistic Symbolic Execution (PSE) extends Symbolic Execution (SE), a path-sensitive static program analysis technique, by calculating the probabilities with which program paths are executed. PSE relies on the ability of the underlying symbolic models to accurately represent the execution paths of the program as the collection of input values following these paths. While researchers established PSE for numerical data types, PSE for complex data types such as strings is a novel area of research.

For string data types SE tools commonly utilize finite state automata to represent a symbolic string model. Thus, PSE inherits from SE automata-based symbolic string models …

Predicting The Complexity Of Locality Patterns In Loop Nests In C Scientific Programs, Nasser M. Alsaedi

Dissertations

On modern computer systems, the performance of an application depends on its locality. Most existing locality measurements performed by compiler static analysis mainly target analyzing regular array references in loop nests. Measurements based on compiler static analysis have limited applicability when the loop bounds are unknown at compile time, when the control flow is dynamic, or when index arrays or pointer operations are used. In addition, compiler static analysis cannot adapt to input change.

Training-based locality analysis predicts the data reuse change across program inputs to provide run-time information. This analysis quantifies the number of unique memory locations accessed between …

Social Media Use During Crisis Events: A Mixed-Method Analysis Of Information Sources And Their Trustworthiness, Apoorva Chauhan

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

This dissertation consists of three studies that examine online communications during crisis events. The first study identified and examined the information sources that provided official information online during the 2014 Carlton Complex Wildfire. Specifically, after the wildfire, a set of webpages and social media accounts were discovered that were named after the wildfire—called Crisis Named Resources (or CNRs). CNRs shared the highest percentage of wildfire-relevant information. Because CNRs are named after a crisis event, they are easier to find and appear to be dedicated and/or official sources around an event. They can, however, be created and deleted in a short …

Deep Learning For Crack-Like Object Detection, Kaige Zhang

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Cracks are common defects on surfaces of man-made structures such as pavements, bridges, walls of nuclear power plants, ceilings of tunnels, etc. Timely discovering and repairing of the cracks are of great significance and importance for keeping healthy infrastructures and preventing further damages. Traditionally, the cracking inspection was conducted manually which was labor-intensive, time-consuming and costly. For example, statistics from the Central Intelligence Agency show that the world’s road network length has reached 64,285,009 km, of which the United States has 6,586,610 km. It is a huge cost to maintain and upgrade such an immense road network. Thus, fully automatic …

Bee Shadow Recognition In Video Analysis Of Omnidirectional Bee Traffic, Laasya Alavala

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Over a decade ago, beekeepers noticed that the bees were dying or disappearing without any prior health disorder. Colony Collapse Disorder(CCD) has been a major threat to bee colonies around the world which affects vital human crop pollination. Possible instigators of CCD include viral and fungal diseases, decreased genetic diversity, pesticides and a variety of other factors. The interaction among any of these potential facets may be resulting in immunity loss for honey bees and the increased likelihood of collapse. It is essential to rescue honey bees and improve the health of bee colony.

Monitoring the traffic of bees helps …

Managing Iot Data On Hyperledger Blockchain, Akhil David

UNLV Theses, Dissertations, Professional Papers, and Capstones

Blockchain is a rapidly evolving technology known for its security, immutability and decentralized nature. At its heart, it’s used for storing various kinds of data like transactions. But it is not limited to just the transactions or the cryptocurrency. It can also be used to store many other things like assets, IoT data or even multimedia data like songs, pictures, and videos.

The number of IoT devices being connected to the internet is increasing day by day. In fact, Garter (Analyst Firm) predicts there will be 20.4 Billion IoT devices by the end of 2020 [IOTb]. With the increase in …

Coarse-Grained, Fine-Grained, And Lock-Free Concurrency Approaches For Self-Balancing B-Tree, Edward R. Jorgensen Ii

UNLV Theses, Dissertations, Professional Papers, and Capstones

This dissertation examines the concurrency approaches for a standard, unmodified B-Tree which is one of the more complex data structures. This includes the coarse grained, fine-grained locking, and the lock-free approaches. The basic industry standard coarse-grained approach is used as a base-line for comparison to the more advanced fine-grained and lock-free approaches. The fine-grained approach is explored and algorithms are presented for the fine-grained B-Tree insertion and deletion. The lock-free approach is addressed and an algorithm for a lock-free B- Tree insertion is provided. The issues associated with a lock-free deletion are discussed. Comparison trade-offs are presented and discussed. As …

Improving Ocr Post Processing With Machine Learning Tools, Jorge Ramon Fonseca Cacho

UNLV Theses, Dissertations, Professional Papers, and Capstones

Optical Character Recognition (OCR) Post Processing involves data cleaning steps for documents that were digitized, such as a book or a newspaper article. One step in this process is the identification and correction of spelling and grammar errors generated due to the flaws in the OCR system. This work is a report on our efforts to enhance the post processing for large repositories of documents.

The main contributions of this work are:

• Development of tools and methodologies to build both OCR and ground truth text correspondence for training and testing of proposed techniques in our experiments. In particular, we …

Static Malware Detection Using Deep Neural Networks On Portable Executables, Piyush Aniruddha Puranik

UNLV Theses, Dissertations, Professional Papers, and Capstones

There are two main components of malware analysis. One is static malware analysis and the other is dynamic malware analysis. Static malware analysis involves examining the basic structure of the malware executable without executing it, while dynamic malware analysis relies on examining malware behavior after executing it in a controlled environment. Static malware analysis is typically done by modern anti-malware software by using signature-based analysis or heuristic-based analysis.

This thesis proposes the use of deep neural networks to learn features from a malware’s portable executable (PE) to minimize the occurrences of false positives when recognizing new malware. We use the …

Performance Comparison Of Message Queue Methods, Sanika Raje

UNLV Theses, Dissertations, Professional Papers, and Capstones

Message queues are queues of messages that facilitate communication between applications. A queue is a line of messages or events waiting to be handled in a sequential manner. A message queue is a queue of messages sent between applications. It includes a sequence of work objects that are waiting to be processed. For a distributed system to work, it needs to pass information between various machines. No single machine is responsible for the entire system, but all information is interrelated. Hence a major concern of distributed systems is this transfer of data. Which also proves to be one of the …

Law Library Blog (August 2019): Legal Beagle's Blog Archive, Roger Williams University School Of Law

Law Library Newsletters/Blog

No abstract provided.

Krylov Subspace Spectral Methods With Non-Homogenous Boundary Conditions, Abbie Hendley

Master's Theses

For this thesis, Krylov Subspace Spectral (KSS) methods, developed by Dr. James Lambers, will be used to solve a one-dimensional, heat equation with non-homogenous boundary conditions. While current methods such as Finite Difference are able to carry out these computations efficiently, their accuracy and scalability can be improved. We will solve the heat equation in one-dimension with two cases to observe the behaviors of the errors using KSS methods. The first case will implement KSS methods with trigonometric initial conditions, then another case where the initial conditions are polynomial functions. We will also look at both the time-independent and time-dependent …