Computer Sciences Commons^™

Learning Universal Network Representation Via Link Prediction By Graph Convolutional Neural Network, Weiwei Gu, Fei Gao, Ruiqi Li, Jiang Zhang

Journal of Social Computing

Network representation learning algorithms, which aim at automatically encoding graphs into low-dimensional vector representations with a variety of node similarity definitions, have a wide range of downstream applications. Most existing methods either have low accuracies in downstream tasks or a very limited application field, such as article classification in citation networks. In this paper, we propose a novel network representation method, named Link Prediction based Network Representation (LPNR), which generalizes the latest graph neural network and optimizes a carefully designed objective function that preserves linkage structures. LPNR can not only learn meaningful node representations that achieve competitive accuracy in node ...

Using Twitter Bios To Measure Changes In Self-Identity: Are Americans Defining Themselves More Politically Over Time?, Nick Rogers, Jason J. Jones

Journal of Social Computing

Are Americans weaving their political views more tightly into the fabric of their self-identity over time? If so, then we might expect partisan disagreements to continue becoming more emotional, tribal, and intractable. Much recent scholarship has speculated that this politicization of Americans’ identity is occurring, but there has been little compelling attempt to quantify the phenomenon, largely because the concept of identity is notoriously difficult to measure. We introduce here a methodology, Longitudinal Online Profile Sampling (LOPS), which affords quantifiable insights into the way individuals amend their identity over time. Using this method, we analyze millions of "bios" on the ...

How To Better Identify Venture Capital Network Communities: Exploration Of A Semi-Supervised Community Detection Method, Hong Xiong, Ying Fan

Journal of Social Computing

In the field of Venture Capital (VC), researchers have found that VC companies are more likely to jointly invest with other VC companies. This paper attempts to realize a semi-supervised community detection of the VC network based on the data of VC networking and the list of industry leaders. The main research method is to design the initial label of community detection according to the evolution of components of the VC industry leaders. The results show that the community structure of the VC network has obvious distinguishing characteristics, and the aggregation of these communities is affected by the type of ...

Statistical Analysis Of Eclipse Refactoring Bug Reports, Lipika Chandrashekar, Jasmine Howard, Akash Kumar, Eric Lacker, Srilaxmi Paramaiahgari

Computer Science Student Work

Software refactoring is the process of making code changes to a program to improve its structure, design, and implementation, in such a way that it does not change the original program behavior. One example is the “rename” refactoring that changes program elements to new names that are easier to understand. Many software development tools, including Eclipse, offer various built-in refactorings such as rename, move, extract, etc. However, we discovered that over four thousand bugs related to Eclipse refactorings were reported as of January 2021. Many of these bugs get fixed after they are reported on the Eclipse bug report website ...

Quantum Simulation Using High-Performance Computing, Collin Beaudoin, Christian Trefftz, Zachary Kurmas

Masters Theses

Hermitian matrix multiplication is one of the most common actions that is performed on quantum matrices, for example, it is used to apply observables onto a given state vector/density matrix.

ρ→Hρ

Our goal is to create an algorithm to perform the matrix multiplication within the constraints of QuEST [1], a high-performance simulator for quantum circuits. QuEST provides a system-independent platform for implementing and simulating quantum algorithms without the need for access to quantum machines. The current implementation of QuEST supports CUDA, MPI, and OpenMP, which allows programs to run on a wide variety of systems.

Mapping Renewal: How An Unexpected Interdisciplinary Collaboration Transformed A Digital Humanities Project, Elise Tanner, Geoffrey Joseph

Digital Initiatives Symposium

Funded by a National Endowment for Humanities (NEH) Humanities Collections and Reference Resources Foundations Grant, the UA Little Rock Center for Arkansas History and Culture’s “Mapping Renewal” pilot project focused on creating access to and providing spatial context to archival materials related to racial segregation and urban renewal in the city of Little Rock, Arkansas, from 1954-1989. An unplanned interdisciplinary collaboration with the UA Little Rock Arkansas Economic Development Institute (AEDI) has proven to be an invaluable partnership. One team member from each department will demonstrate the Mapping Renewal website and discuss how the collaborative process has changed and ...

Generating Effective Sentence Representations: Deep Learning And Reinforcement Learning Approaches, Mahtab Ahmed

Electronic Thesis and Dissertation Repository

Natural language processing (NLP) is one of the most important technologies of the information age. Understanding complex language utterances is also a crucial part of artificial intelligence. Many Natural Language applications are powered by machine learning models performing a large variety of underlying tasks. Recently, deep learning approaches have obtained very high performance across many NLP tasks. In order to achieve this high level of performance, it is crucial for computers to have an appropriate representation of sentences. The tasks addressed in the thesis are best approached having shallow semantic representations. These representations are vectors that are then embedded in ...

Gc-28 Modern Web Scraping, Kenny Randolph, Joselyn Giron, Denise Tucker, Justin B Bridges, Sandhya Bantu

C-Day Computing Showcase

This project was developed for the IT7993 Capstone class in the May semester of 2021.The goal of the project is to scrape all names of key professionals of organizations in the open990.org website and insert that information into a structured database for query and analysis. The Key Professionals dataset aims to include global coverage of key investor and consultant professionals, beginning with US-based companies, involved in making an investment decision.   The overarching aim of this project is to create a one-stop center for institutional asset management distribution intelligence; the one spot to go for mandates, documentation and profiles ...

Gc-47 Key Professional Dataset - Dataspider, Janell Westmoreland, Vy Duong, Nyong Nkereuwem, Kajal S Vaghani, Ritu Choudhary

C-Day Computing Showcase

The purpose of this project is to build a Web Crawler to extract personal information from a public website like Reddit and LinkedIn. We completed the Instagram crawling as a bonus for the project. The team will be using MySQL or any other open source relational database to organize the data and conduct a quantitative data analysis on it.Advisors(s): Dr. Han - Professor IT7993 Capstone Jing Wang -Project SponsorTopic(s): Data/Data AnalyticsIT7993

Gc-52 Ksu Spring Capstone - It Security Solution For Small Business – Group 1, William Simmons, Olajumoke Giwa, Beau Beard, Collin Peters

C-Day Computing Showcase

For this project, we decided to use the nopCommerce open-source eCommerce solution for our simulated small business. Leveraging the pre-configured web server provide to our group, we installed the nopCommerce solution package and built our security program around the web site. Our security program consists of nginx configured web server and load balancer, SSL certificate for encryption, firewall and a secure backend SQL server.Advisors(s): Project Sponsor: Dr. Lei Li Course Professor: Dr. Meng HanTopic(s): SecurityIT 7993

Gr-1 Compare Two Off Angle Normalization, Emily Ehrlich

C-Day Computing Showcase

This work investigates different iris normalization techniques to compare their performance including elliptical normalization and circular normalization after frontal projection of off-angle iris recognition. Elliptical normalization samples the iris texture using elliptical segmentation parameters. For circular unwrapping, we first estimate the gaze deviation using ellipse parameters and the image will be projected back to frontal view using perspective transformation. Then, we segment the transformed image and normalize using circular parameters. We further investigate if: (i) elliptical normalization or circular unwrapping recognition performance is higher, and (ii) the two segmentations methods in circular unwrapping increase the recognition efficiency. Based on the ...

Gr-29 Wrist Intent Recognition For Stroke Rehabilitation, Suman Bharti

C-Day Computing Showcase

Abstract Hand mentor robotic device is beneficial for stroke patients . This is rehabilitation technique used in stroke therapy. It strengthens and improves the range of motion which ultimately improves the quality of life for severely impaired stroke patients. It is easy to use without assistance and most importantly stroke survivors able to use independently. Usage of hand mentor device is quite expensive for stroke patients on hourly basis . Coming up with most efficient deep learning algorithm for sensor data is motivation to cut down the cost and easy availability usage for stroke patients. EMG signal is recorded using relevant sensors ...

Gr-23 Machine Learning Techniques For Malware Network Traffic Detection, Jermaine Cameron

C-Day Computing Showcase

Persistent malware variants are a constant threat to computing infrastructure across all regions and business sectors. Traditional detection systems focus primarily on signature-based analysis but this approach cannot adequately keep pace with the velocity and volume of new malware variants that are continuously deployed onto the internet. Most network traffic detection techniques are focused on analyzing raw packets and have not deterred the surge of persistent malware. Therefore, it is important to develop new research techniques that are focused on optimized metadata from malware network traffic to effectively identify an ever-increasing expanse of malicious software. Recent research efforts by Letteri ...

Gr-34 Defensive Neural Network, Hongkyu Lee

C-Day Computing Showcase

Machine learning (ML) algorithms require a massive amount of data. Firms such as Google and Facebook exploit user's data to deliver a more precise ML-based service. However, collecting users' data is a risky action because their private data can be leaked through the transmission. As a remedy, federated learning is introduced. In federated learning, a central server distributes a machine learning model to users. Each user trains the model to its data, and send the model back. Later the models are aggregated and distributed again. Federated learning is more secure in that it emancipates users from the risk of ...

Gr-33 Efficient Yet Robust Privacy Preservation \\For Mpeg-Dash Based Video Streaming, Luke A Cranfill

C-Day Computing Showcase

MPEG-DASH is a video streaming standard that outlines protocols for sending audio and video content from a server to a client over HTTP. However, it creates an opportunity for an adversary to invade users' privacy. While a user is watching a video, information is leaked in the form of meta-data, the size and time that the server sent data to the user. After a fingerprint of this data is created, the adversary can use this to identify whether a target user is watching the corresponding video. Only one defense strategy has been proposed to deal with this problem: differential privacy ...

Gr-38 Energy Cost And Efficiency On Edge Computing: Challenges And Vision, Kousalya Banka

C-Day Computing Showcase

The Internet of Things (IoT) has been the key for many advancements in next-generation technologies for the past few years. With a conceptual grouping of ecosystem elements such as sensors, actuators, and smart objects connected to perform complex operations to perform environmental monitoring, intelligent transport system, smart building, smart cities, and endless other possibilities. Edge computing helps the IoT’s reach even further and be more robust by connecting multiple censored devices through the internet and forming powerful computational capabilities. Unfortunately, this computation level comes at a cost as the devices are constantly being used to communicate and perform specific ...

Gr-40 Design And Implementation Of A Microservices Web-Based Architecture For Code Deployment And Testing, Soin Abdoul Kassif Baba M Traore

C-Day Computing Showcase

Many tech stars like Netflix, Amazon, PayPal, eBay, and Twitter are evolving from monolithic to a microservice architecture due to the benefits for Agile and DevOps teams. Microservices architecture can be applied to multiple industries, like IoT, using containerization. Virtual containers give an ideal environment for developing and testing IoT technologies. Since the IoT industry has exponential growth, it is the responsibility of universities to teach IoT with hands-on labs to minimize the gap between what the students learn and what is on-demand in the job market. That can be done by using containerization. There are many approaches in the ...

Gr-44 An Efficient Intrusion Detection Framework Based On Federated Learning For Iot Networks., Osama Shahid

C-Day Computing Showcase

There are abundant number of IoT devices that are connected on over multiple networks. These devices can be exposed to multiple different types of network threats. Though, these devices do have security and software that does act as a wall of protection we purpose a Federated Learning (FL) approach that would allow detection of threats of a network for IoT devices. Federated Learning can be best described as decentralized training. Adhering to the GDPR rules that prevent data from being distributed, FL addressed the challenge by bringing the ML model to the data rather than the traditional method where the ...

Gr-45 Framework For Collecting Data From Specialized Iot Devices., Md Saiful Islam

C-Day Computing Showcase

The Internet of Things (IoT) is the most significant and blooming technology in the 21st century. IoT has rapidly developed by covering hundreds of applications in the civil, health, military, and agriculture areas. IoT is based on the collection of sensor data through an embedded system, and this embedded system uploads the data on the internet. Devices and sensor technologies connected over a network can monitor and measure data in real-time. The main challenge is to collect data from IoT devices, transmit them to store in the Cloud, and later retrieve them at any time for visualization and data analysis ...

Gr-50 Predicting Users' Engagement During Interviews With Biofeedback, Voice, And Supervised Machine Learning, Thaide Huichapa

C-Day Computing Showcase

Studies show that the quality of the information collected during an elicitation interview, and consequently the quality of the software product that needs to be developed, highly depends on the interviewee's engagement. Because of social expectations, interviewees tend to hide if they are bored or not engaged. To overcome this problem and support the analyst during the interviews, this research uses biometric data and voice features, together with supervised machine learning algorithms, to predict the interviewee's engagement. We built our solution on an experiment consisted of interviewing 31 participants. We collected the data using an Empatica wristband and ...