Computer Sciences Commons^™

Machine Learning To Support An Interactive Theorem Prover, Salman Haider, Andy Le, Echo Wu, Brian T. Howard

Annual Student Research Poster Session

An Interactive Theorem Prover (ITP) is a computer program that can assist a human in creating a proof of a mathematical theorem or the correctness of a piece of software. At each step in the proof, the human has the computer apply a chosen "tactic" to attempt to make progress toward the goal. We are exploring the possibility of using Machine Learning (ML) to assist in this tactic selection. Building on recent work at UC Berkeley and Princeton, where they adapted the Coq ITP so that it could interface with ML libraries via the Python scripting language, we have been …

Visualizing The Mean And The Standard Deviation Using R/Rstudio Shiny Package, Rachel Hufnagel, Ziyi (Amy) Chen, Mamunur Rashid

Annual Student Research Poster Session

Many of us have experienced an unpleasant situation in which only the mean and the standard deviation of a data set are reported, but we are expected to know everything about the dataset as if those two values were all we needed to know. We would learn so much more if there were easy ways to create and share graphical representations and interpretations of the entire raw data. Here we not only explain what the mean and the standard deviation tell us about a data set, but also describe how to include additional information on the data. We utilize the …

Experiences Of Using Intelligent Virtual Assistants By Visually Impaired Students In Online Higher Education, Michele R. Forbes

USF Tampa Graduate Theses and Dissertations

In today’s world, the attainment of higher education impacts the acquisition of competitive employment and, thus, quality of life. As a group, persons with disabilities continually fall behind others in such academic progress, requiring new efforts to support their earning of advanced credentials. Though highly beneficial for these individuals, obtaining a degree comes with elevated levels of stress. As enrollment of students with disabilities grows in all formats of higher education, those involved must understand the stress endured by these students and how to diminish it. Theories speculate that technology, such as intelligent virtual assistants, may be a viable tool …

Cybersecurity Framework And Algorithms For Prioritized Vulnerability Mitigation (Cyfer): An Adoption To Blockchain Systems, Sri Nikhil Gupta Gourisetti

Theses and Dissertations

Cybersecurity vulnerability assessment tools, frameworks, methodologies, and processes are commonly used to understand the cybersecurity maturity and posture of a system or a facility. Those tools are strictly developed based on standards defined by organizations such as the National Institute of Standards and Technology (NIST) and the U.S. Department of Energy, and the majority of these tools and frameworks do not provide a platform to prioritize the requirements to reach a desired cybersecurity maturity. To address that challenge, we used multi-criteria decision analysis (MCDA) techniques to develop a framework and a software application family called the Cybersecurity Framework and Algorithms …

Multi-User Virtual Reality With Lenticular Lenses, Juan Sebastian Munoz Arango

Theses and Dissertations

One of the all time issues with Virtual Reality systems regardless if they are head-mounted or projection based is that they can only provide perspective correctness to one user. This limitation not only affects collaborative work which is nowadays the standard, but it has also been shown that not having a perspective correct views increases collaboration times. Different approaches have been presented throughout the past years for generating perspective correct images to several users. One of such approaches relies on bending the light to generate perspective correct images. Lenticular printing is a technique that uses the properties of small lenses …

Artificial Intelligence, Real Impact, Singapore Management University

Perspectives@SMU

AI use in China continues to push innovation envelopes, but technology must be utilised and updated with expert advice

Why A Classification Based On Linear Approximation To Dynamical Systems Often Works Well In Nonlinear Cases, Julio Urenda, Vladik Kreinovich

Departmental Technical Reports (CS)

It can be proven that linear dynamical systems exhibit either stable behavior, or unstable behavior, or oscillatory behavior, or transitional behavior. Interesting, the same classification often applies to nonlinear dynamical systems as well. In this paper, we provide a possible explanation for this phenomenon, i.e., we explain why a classification based on linear approximation to dynamical systems often works well in nonlinear cases.

Development Of An Autonomous Aerial Toolset For Agricultural Applications, Terrance Life

Mahurin Honors College Capstone Experience/Thesis Projects

According to the United Nations, the world population is expected to grow from its current 7 billion to 9.7 billion by the year 2050. During this time, global food demand is also expected to increase by between 59% and 98% due to the population increase, accompanied by an increasing demand for protein due to a rising standard of living throughout developing countries. [1] Meeting this increase in required food production using present agricultural practices would necessitate a similar increase in farmland; a resource which does not exist in abundance. Therefore, in order to meet growing food demands, new methods will …

Multilevel Combinatorial Optimization Across Quantum Architectures, Hayato Ushijima-Mwesigwa, Ruslan Shaydulin, Christian F.A. Negre, Susan M. Mniszewski, Yuri Alexeev, Ilya Safro

Publications

Emerging quantum processors provide an opportunity to explore new approaches for solving traditional problems in the Post Moore's law supercomputing era. However, the limited number of qubits makes it infeasible to tackle massive real-world datasets directly in the near future, leading to new challenges in utilizing these quantum processors for practical purposes. Hybrid quantum-classical algorithms that leverage both quantum and classical types of devices are considered as one of the main strategies to apply quantum computing to large-scale problems. In this paper, we advocate the use of multilevel frameworks for combinatorial optimization as a promising general paradigm for designing hybrid …

Adaptive Feature Engineering Modeling For Ultrasound Image Classification For Decision Support, Hatwib Mugasa

Doctoral Dissertations

Ultrasonography is considered a relatively safe option for the diagnosis of benign and malignant cancer lesions due to the low-energy sound waves used. However, the visual interpretation of the ultrasound images is time-consuming and usually has high false alerts due to speckle noise. Improved methods of collection image-based data have been proposed to reduce noise in the images; however, this has proved not to solve the problem due to the complex nature of images and the exponential growth of biomedical datasets. Secondly, the target class in real-world biomedical datasets, that is the focus of interest of a biopsy, is usually …

Feature Space Modeling For Accurate And Efficient Learning From Non-Stationary Data, Ayesha Akter

Doctoral Dissertations

A non-stationary dataset is one whose statistical properties such as the mean, variance, correlation, probability distribution, etc. change over a specific interval of time. On the contrary, a stationary dataset is one whose statistical properties remain constant over time. Apart from the volatile statistical properties, non-stationary data poses other challenges such as time and memory management due to the limitation of computational resources mostly caused by the recent advancements in data collection technologies which generate a variety of data at an alarming pace and volume. Additionally, when the collected data is complex, managing data complexity, emerging from its dimensionality and …

A Comparative Study Of Recommendation Systems, Ashwini Lokesh

Masters Theses & Specialist Projects

Recommendation Systems or Recommender Systems have become widely popular due to surge of information at present time and consumer centric environment. Researchers have looked into a wide range of recommendation systems leveraging a wide range of algorithms. This study investigates three popular recommendation systems in existence, Collaborative Filtering, Content-Based Filtering, and Hybrid recommendation system. The famous MovieLens dataset was utilized for the purpose of this study. The evaluation looked into both quantitative and qualitative aspects of the recommendation systems. We found that from both the perspectives, the hybrid recommendation system performs comparatively better than standalone Collaborative Filtering or Content-Based Filtering …

Ndikimi I Iot (Internet Of Things) Në Rritjen E Kualitetit Të Produkteve Bujqësore Si Dhe Në Racionalizimin E Shfrytzimit Të Resursëve Bujqësore, Arbër Suka

Theses and Dissertations

Duke pasur parasyshë qe tekonologjia gjithnjë e me shumë po sofistikohet, dhe qe tashme pothuajse çdo informat mundet me u gjet në internet atëher këtë temë do të trajtohet se si ndikon aplikimi i internetit të gjerave apo internet of things (IOT) në bujqësin përkatësisht në rritjen e qualitetit të produkteve , rritjen e sasisë së produkteve dhe ate duke perdorur sa më pak resurse. Duke pas parasysh që pothuaj se qdo fermer rradhë her hyn në internet për të shikuar se cila është rruga më e leht dhe më e mirë për të rritur nje bimë dhe për të …

Shqyrtimi I Sulmeve Kibernetike Metasploit, Fitim Kastrati

Theses and Dissertations

Në ditët e sotme , zhvillimi i teknologjisë informative ka sjell ndryshime radikale në çdo aspekt të jetës së njerëzve , dhe kjo padyshim e ka bërë jetën tonë të ketë shumë qasje në informacione . Këto zhvillime teknologjike dhe komunikuese krahas benifiteve të tyre kanë edhe rreziqet .

Shfrytëzuesit duhet të jenë shumë të vëmndshëm gjatë përdorimit të rrjeteve sociale, aplikacioneve të ndryshme dhe surfimit në botën e internetit sepse rreziku nga sulmet kibernetike nga persona të papërgjegjshëm me qëllime dashakeqe dinë të jenë shumë të shpeshta.

Pra web aplikaconet e bëjnë të mundur që vizituesit e web faqeve …

Privacidad Digital En Ecuador: El Papel De La Vigilancia, La Jurisprudencia Y Los Derechos Humanos, Giselle Valdez

Independent Study Project (ISP) Collection

Este documento es un estudio de caso sobre la privacidad digital en Ecuador, cómo se protege y cómo se debe mejorar las protecciones. Comienzo presentando la falta de privacidad de la persona en Ecuador, a través de la reciente violación de datos y las tecnologías de vigilancia en todo el país desde China. Luego, para analizar la jurisprudencia y la falta de protección de la privacidad en la ley, hago la transición a un análisis legal de la privacidad de datos en Ecuador a través de la Constitución de 2008. Cuando establezco que falta privacidad digital en Ecuador, demuestro una …

Paper-Based Flexible Electrode Using Chemically-Modified Graphene And Functionalized Multiwalled Carbon Nanotube Composites For Electrophysiological Signal Sensing, Md Faruk Hossain, Jae Sang Heo, John Nelson, Insoo Kim

Bioelectrics Publications

Flexible paper-based physiological sensor electrodes were developed using chemically-modified graphene (CG) and carboxylic-functionalized multiwalled carbon nanotube composites (f@MWCNTs). A solvothermal process with additional treatment was conducted to synthesize CG and f@MWCNTs to make CG-f@MWCNT composites. The composite was sonicated in an appropriate solvent to make a uniform suspension, and then it was drop cast on a nylon membrane in a vacuum filter. A number of batches (0%~35% f@MWCNTs) were prepared to investigate the performance of the physical characteristics. The 25% f@MWCNT-loaded composite showed the best adhesion on the paper substrate. The surface topography and chemical bonding of the proposed CG-f@MWCNT …

A Study Of Existing Cross-Site Scripting Detection And Prevention Techniques Using Xampp And Virtualbox, Jalen Mack, Yen-Hung (Frank) Hu, Mary Ann Hoppa

Virginia Journal of Science

Most operating websites experience a cyber-attack at some point. Cross-site Scripting (XSS) attacks are cited as the top website risk. More than 60 percent of web applications are vulnerable to them, and they ultimately are responsible for over 30 percent of all web application attacks. XSS attacks are complicated, and they often are used in conjunction with social engineering techniques to cause even more damage. Although prevention techniques exist, hackers still find points of vulnerability to launch their attacks. This project explored what XSS attacks are, examples of popular attacks, and ways to detect and prevent them. Using knowledge gained …

Reachnn: Reachability Analysis Of Neural-Network Controlled Systems, Chao Huang, Jiameng Fan, Wenchao Li, Xin Chen, Qi Zhu

Computer Science Faculty Publications

Applying neural networks as controllers in dynamical systems has shown great promises. However, it is critical yet challenging to verify the safety of such control systems with neural-network controllers in the loop. Previous methods for verifying neural network controlled systems are limited to a few specific activation functions. In this work, we propose a new reachability analysis approach based on Bernstein polynomials that can verify neural-network controlled systems with a more general form of activation functions, i.e., as long as they ensure that the neural networks are Lipschitz continuous. Specifically, we consider abstracting feedforward neural networks with Bernstein polynomials for …

On The Yellow Brick Road, A Path To Enterprise Architecture Maturity, Avsharn Bachoo

The African Journal of Information Systems

This study concentrated on the relationship between the Enterprise Architecture (EA) maturity of an organization and the business value associated with it in the South African financial services environment. It was developed within the critical realism philosophy, which states that mechanisms generate events by accentuating the underlying EA mechanisms that lead to business value, as well as provide insights into the opportunities and challenges organizations experienced as they progressed to higher levels of maturity. Constructed using the resource-based view of the firm as the underlying theoretical framework, this research examined EA as an intangible resource and maturity as a source …

Factors Influencing Knowledge Transfer In Onshore Information Systems Outsourcing In Ethiopia, Solomon A. Nurye, Alem Molla, Temtim Assefa Desta

The African Journal of Information Systems

Knowledge transfer in onshore information systems (IS) outsourcing projects in Africa is an important but under-researched phenomenon. This study focuses on the client-vendor perspective and examines the factors that influence knowledge transfer in onshore information systems outsourcing in Ethiopia. Conceptually, knowledge-based perspectives of IS outsourcing is used to identify an initial set of factors to frame the empirical study. This is followed by semi-structured interviews with ten project managers. The findings indicate that five key factors, namely mutual absorptive capacity, mutual learning intent, mutual trust, mutual disseminative capacity and project staff turnover influence knowledge transfer in outsourced IS projects. The …

Csci49379: Intro To Blockchain (Syllabus), Wendy Mock, Nyc Tech-In-Residence Corps

Open Educational Resources

Syllabus for the course: CSCI 49397 - Blockchain. Delivered at Hunter College in Fall 2019 by Wendy Mock as part of the Tech-in-Residence Corps program.

Comprehending Test Code: An Empirical Study, Chak Shun Yu, Christoph Treude, Maurício Aniche

Research Collection School Of Computing and Information Systems

Developers spend a large portion of their time and effort on comprehending source code. While many studies have investigated how developers approach these comprehension tasks and what factors influence their success, less is known about how developers comprehend test code specifically, despite the undisputed importance of testing. In this paper, we report on the results of an empirical study with 44 developers to understand which factors influence developers when comprehending Java test code. We measured three dependent variables: the total time spent reading a test suite, the ability to identify the overall purpose of a test suite, and the ability …

Automatic Fashion Knowledge Extraction From Social Media, Yunshan Ma, Lizi Liao, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Fashion knowledge plays a pivotal role in helping people in their dressing. In this paper, we present a novel system to automatically harvest fashion knowledge from social media. It unifies three tasks of occasion, person and clothing discovery from multiple modalities of images, texts and metadata. A contextualized fashion concept learning model is applied to leverage the rich contextual information for improving the fashion concept learning performance. At the same time, to counter the label noise within training data, we employ a weak label modeling method to further boost the performance. We build a website to demonstrate the quality of …

Person Identification With Convolutional Neural Networks, Kang Zheng

Theses and Dissertations

Person identification aims at matching persons across images or videos captured by different cameras, without requiring the presence of persons’ faces. It is an important problem in computer vision community and has many important real-world applica- tions, such as person search, security surveillance, and no-checkout stores. However, this problem is very challenging due to various factors, such as illumination varia- tion, view changes, human pose deformation, and occlusion. Traditional approaches generally focus on hand-crafting features and/or learning distance metrics for match- ing to tackle these challenges. With Convolutional Neural Networks (CNNs), feature extraction and metric learning can be combined in …

Semantic Segmentation Considering Image Degradation, Global Context, And Data Balancing, Dazhou Guo

Theses and Dissertations

Recently, semantic segmentation – assigning a categorical label to each pixel in an im- age – plays an important role in image understanding applications, e.g., autonomous driving, human-machine interaction and medical imaging. Semantic segmentation has made progress by using the deep convolutional neural networks, which are sur- passing the traditional methods by a large margin. Despite the success of the deep convolutional neural networks (CNNs), there remain three major challenges.

The first challenge is how to segment the degraded images semantically, i.e., de- graded image semantic segmentation. In general, image degradations increase the difficulty of semantic segmentation, usually leading to …

Phylogenetic Reconstruction Analysis On Gene Order And Copy Number Variation, Ruofan Xia

Theses and Dissertations

Genome rearrangement is known as one of the main evolutionary mechanisms on the genomic level. Phylogenetic analysis based on rearrangement played a crucial role in biological research in the past decades, especially with the increasing avail- ability of fully sequenced genomes. In general, phylogenetic analysis aims to solve two problems: Small Parsimony Problem (SPP) and Big Parsimony Problem (BPP). Maximum parsimony is a popular approach for SPP and BPP which relies on itera- tively solving a NP-hard problem, the median problem. As a result, current median solvers and phylogenetic inference methods based on the median problem all face se- rious …

Stacked Modelling Framework, Kareem Abdelfatah

Theses and Dissertations

The thesis develops a predictive modeling framework based on stacked Gaussian processes and applies it to two main applications in environmental and chemical en- gineering. First, a network of independently trained Gaussian processes (StackedGP) is introduced to obtain analytical predictions of quantities of interest (model out- puts) with quantified uncertainties. StackedGP framework supports component- based modeling in different fields such as environmental and chemical science, en- hances predictions of quantities of interest through a cascade of intermediate predic- tions usually addressed by cokriging, and propagates uncertainties through emulated dynamical systems driven by uncertain forcing variables. By using analytical first and …

Properties, Learning Algorithms, And Applications Of Chain Graphs And Bayesian Hypergraphs, Mohammad Ali Javidian

Theses and Dissertations

Probabilistic graphical models (PGMs) use graphs, either undirected, directed, or mixed, to represent possible dependencies among the variables of a multivariate probability distri- bution. PGMs, such as Bayesian networks and Markov networks, are now widely accepted as a powerful and mature framework for reasoning and decision making under uncertainty in knowledge-based systems. With the increase of their popularity, the range of graphical models being investigated and used has also expanded. Several types of graphs with dif- ferent conditional independence interpretations - also known as Markov properties - have been proposed and used in graphical models.

The graphical structure of a …

Cybersecurity Issues In The Context Of Cryptographic Shuffling Algorithms And Concept Drift: Challenges And Solutions, Hatim Alsuwat

Theses and Dissertations

In this dissertation, we investigate and address two kinds of data integrity threats. We first study the limitations of secure cryptographic shuffling algorithms regarding preservation of data dependencies. We then study the limitations of machine learning models regarding concept drift detection. We propose solutions to address these threats.

Shuffling Algorithms have been used to protect the confidentiality of sensitive data. However, these algorithms may not preserve data dependencies, such as functional de- pendencies and data-driven associations. We present two solutions for addressing these shortcomings: (1) Functional dependencies preserving shuffle, and (2) Data-driven asso- ciations preserving shuffle. For preserving functional dependencies, …

Preface To Ieee Vast 2019 Conference Track And Vast Challenge, Remco Chang, Daniel Keim, Ross Maciejewski, Kristin Cook, R. Jordan Crouser

Computer Science: Faculty Publications

No abstract provided.