Computer Sciences Commons^™

Uc-6 Covid-19 Data Analysis - Regression, Noah Druss

C-Day Computing Showcase

Covid-19 has been arguably the most impactful event in the past century. SARS-Cov-2 is a viral respiratory illness discovered in late 2019 that has spread to almost every country in the world. It has directly or indirectly affected just about everybody in the world greatly, causing over 117 million cases and 2.59 million deaths as of March 2021. This project has focused on the use of different types of linear regression to both analyze and predict Covid-19 infection data based on different features. First, simple linear regression was used to predict total deaths based on infections both globally and by …

Uc-62 Machine Learning: Twitter Bots In Disguise, Matthew Joseph Scheer, Nicolas Vasquez, James C Andersen, Joshua Tiangco, Justin Van, Cody R Walicek, Daniel Rimmel

C-Day Computing Showcase

This project was designed to help fight against misinformation spread by bots(computers), the goal assigned to us was to find and inform Twitter users of bots that follow and are being followed by the user.Advisors(s): Dr. Reza PariziTopic(s): Artificial IntelligenceSWE 4724

Uc-69 Team 10b Bchain, Jonathan D Lashgari, Carlos A Diaz, Jeffery Erhunse, Caleb T Goff, Giang T Nguyen

C-Day Computing Showcase

BChain is a new P2P file sharing system that is fully private, anonymous, globally self-verifying, and utilizes an automatic peer-maintained network of trust in data, accomplished through new methods of routing content over the whole network, encrypted, rather than per torrent download. Verification is done by adding file metadata to a blockchain giving the network consistent knowledge of each file it can transfer, and how to verify file received against the network. This enables a policy of zero trust against peers. This system is implemented by an app that interfaces with the network using the protocol, using it for upload, …

Ur-41 The Accessibility Of The Mobile Gaming Platform For The Visually Impaired, Christian Thomas Jansen

C-Day Computing Showcase

The motivation for this project is to research mobile gaming interfaces with the goal of conceptualizing practices in game design that would create more accessible interfaces for the visual impairment community. Thus far, the project has focused on practices that mobile game designers can use to make their games more accessible to the visually impaired. These includes the use of plain text rather than graphics to be scannable by screen readers, the inclusion of audio-oriented support and instruction, the use of contrasting colors to make options more recognizable to those with partial visual impairments, and the implementation of game mechanics …

Ur-46 Breastnet;, Cora L Meador, Ryan Deem

C-Day Computing Showcase

In the United states, 13% of women are diagnosed with breast cancer in their lifetime, and it is the second leading cause of death by cancer in women. Early detection and screening can result in an increase of life expectancy by 10 years on average. Unfortunately, breast cancer can be challenging to detect, since it can appear anywhere in the breast. Cancer that is detected in its early stages can give patients more options and save thousands of dollars in medical costs. Some of the most recent developments in computer science and machine learning are in the biomedical field, especially …

Cognitive Radio Spectrum Sensing And Prediction Using Deep Reinforcement Learning, Syed Qaisar Jalil, Mubashir Husain Rehmani, Stephan Chalup

Preprints

In this paper, we propose to use deep reinforcement learning (DRL) for the task of cooperative spectrum sensing (CSS) in a cognitive radio network. We selected a recently proposed offline DRL method called conservative Q-learning (CQL) due to its ability to learn complex data distributions efficiently. The task of CSS is performed as follows. Each secondary user (SU) performs local sensing and using CQL algorithm, determines the presence of licensed user for current and k-1 future timeslots. These results are forwarded to the fusion centre where another CQL algorithm is operating that generates a global decision for the current and …

Comparative Study Of Virtual Reality Vs Augmented Reality For Training Oriented Applications, Ramiro Serrano Vergel

Theses and Dissertations

The usability of interactive applications based on virtual environments for training in 3D simulations needs to be reviewed and evaluated to identify which of these technologies fit better for a specific context. The study of these systems can be complex, considering that there are diverse characteristics in the applications proposed. Additionally, there are countless contexts in which these technologies could be applied. Therefore, this study provides a first approach to the analysis of the differences between AR and VR for the specific case of 3D object manipulation. This study is oriented on the analysis of the effects of latency, field …

Control Over Skies: Survivability, Coverage, And Mobility Laws For Hierarchical Aerial Base Stations, Vishal Sharma, Navuday Sharma, Mubashir Husain Rehmani, Haris Pervaiz

Publications

Aerial Base Stations (ABSs) have gained significant importance in the next generation of wireless networks for accommodating mobile ground users and flash crowds with high convenience and quality. However, to achieve an efficient ABS network, many factors pertaining to ABS flight, governing laws and information transmissions must be studied. In this article, multi-drone communications are studied in three major aspects, survivability, coverage, and mobility laws, which optimize the multitier ABS network to avoid issues related to inter-cell interference, deficient energy, frequent handovers, and lifetime. The article includes simulation results of hierarchical ABS allocations for handling a set of users over …

Using Information Theory To Extract Patterns From Categorical Raster Data, David Percy

Complex Systems Faculty Publications and Presentations

Information theory -- Reconstructability Analysis (RA) implemented in the Occam software -- was used to extract patterns from National Land Cover Data. The aim was to predict temporal change in evergreen forests from time-lagged and spatially adjacent states. The NLCD satellite data were preprocessed with Python and submitted to Occam for analysis, and Occam output was also explored with R-studio. The effectiveness of RA methodology for the analysis of this type of categorical space-time grid data was demonstrated.

Building A Data Washing Machine For Unsupervised Entity Resolution Of Unstandardized References Sources, Awaad K. Al Sarkhi

Theses and Dissertations

This dissertation describes a first attempt to build a data washing machine, a system able to take dirty data and through an unsupervised process, output clean data. The washing machine design described here focuses on two main aspects of the data curation process, token correction and data redundancy. It aims to simplify and automate the preparation of data used to create information products. In this approach, all these steps would be automated, thus saving the time and effort of the data analysts who ordinarily perform these actions. In other words, this is the opposite of the current approach to first …

Mlatticeabc: Generic Lattice Constant Prediction Of Crystal Materials Using Machine Learning, Yuxin Li, Wenhui Yang, Rongzhi Dong, Jianjun Hu

Faculty Publications

Lattice constants such as unit cell edge lengths and plane angles are important parameters of the periodic structures of crystal materials. Predicting crystal lattice constants has wide applications in crystal structure prediction and materials property prediction. Previous work has used machine learning models such as neural networks and support vector machines combined with composition features for lattice constant prediction and has achieved a maximum performance for cubic structures with an average coefficient of determination (R2) of 0.82. Other models tailored for special materials family of a fixed form such as ABX3 perovskites can achieve much higher performance due …

Exploring Ai And Multiplayer In Java, Ronni Kurtzhals

Student Academic Conference

I conducted research into three topics: artificial intelligence, package deployment, and multiplayer servers in Java. This research came together to form my project presentation on the implementation of these topics, which I felt accurately demonstrated the various things I have learned from my courses at Moorhead State University. Several resources were consulted throughout the project, including the work of W3Schools and StackOverflow as well as relevant assignments and textbooks from previous classes. I found this project relevant to computer science and information systems for several reasons, such as the AI component and use of SQL data tables; but it was …

Student Academic Conference, Caitlin Brooks

Student Academic Conference

No abstract provided.

Poker Chip Calculator Application, Ryan Illies

Student Academic Conference

Application to help start up in person poker games with friends.

Edmms Temperature Controller, Anthony Kirkland

Honors Theses

Temperature control systems in consumer appliances like that of a thermostat interfacing with HVAC systems, refrigerators and ovens are oscillatory in nature. There is a temperature at which the machine that causes the change in the system comes on and a different temperature at which it comes off. While sufficient for humans, welding, metal casting, and other metallurgical processes require precise temperature control, more precise than the hysteresis of a consumer system.

Proportional integral derivative (PID) provides a better way of monitoring the way temperature changes when the entity that changes the environment comes on and renders changes in system …

Viability Of Consumer Grade Hardware For Learning Computer Forensics Principles, Lazaro A. Herrera

Journal of Digital Forensics, Security and Law

We propose utilizing budget consumer hardware and software to teach computer forensics principles and for non-case work, research and developing new techniques. Consumer grade hardware and free / open source software is more easily accessible in most developing markets and can be used as a first purchase for education, technique development and even when developing new techniques. These techniques should allow for small forensics laboratories or classroom settings to have the tooling and framework for trying existing forensics techniques or creating new forensics techniques on consumer grade hardware. We'll be testing how viable each individual piece of hardware is as …

Exploring Complementary Strengths Of Invariant And Equivariant Representations For Few-Shot Learning, Mamshad Nayeem Rizve, Salman Khan, Fahad Shahbaz Khan, Mubarak Shah

Computer Vision Faculty Publications

In many real-world problems, collecting a large number of labeled samples is infeasible. Few-shot learning (FSL) is the dominant approach to address this issue, where the objective is to quickly adapt to novel categories in presence of a limited number of samples. FSL tasks have been predominantly solved by leveraging the ideas from gradient-based meta-learning and metric learning approaches. However, recent works have demonstrated the significance of powerful feature representations with a simple embedding network that can outperform existing sophisticated FSL algorithms. In this work, we build on this insight and propose a novel training mechanism that simultaneously enforces equivariance …

A Deep Reinforcement Learning-Based Dynamic Computational Offloading Method For Cloud Robotics, Manoj Penmetcha, Byung-Cheol Min

Purdue University Libraries Open Access Publishing Fund

Robots come with a variety of computing capabilities, and running computationally-intense applications on robots is sometimes challenging on account of limited onboard computing, storage, and power capabilities. Meanwhile, cloud computing provides on-demand computing capabilities, and thus combining robots with cloud computing can overcome the resource constraints robots face. The key to effectively offloading tasks is an application solution that does not underutilize the robot's own computational capabilities and makes decisions based on crucial cost parameters such as latency and CPU availability. In this paper, we formulate the application offloading problem as a Markovian decision process and propose a deep reinforcement …

Mpi4py Implementation Of Greedy Algorithm For The Shortest Path Problem, Arianna Martin, Jeremy Evert, Charles Sleeper

Student Research

No abstract provided.

Microfluidic-Based Bacterial Molecular Computing On A Chip, Daniel P. Martins, Michael Taynnan Barros, Benjamin O'Sullivan, Ian Seymour, Alan O'Riordan, Lee Coffey, Joseph Sweeney, Sasitharan Balasubramaniam,

School of Computing: Faculty Publications

Biocomputing systems based on engineered bacteria can lead to novel tools for environmental monitoring and detection of metabolic diseases. In this paper, we propose a Bacterial Molecular Computing on a Chip (BMCoC) using microfluidic and electrochemical sensing technologies. The computing can be flexibly integrated into the chip, but we focus on engineered bacterial AND Boolean logic gate and ON-OFF switch sensors that produces secondary signals to change the pH and dissolved oxygen concentrations. We present a prototype with experimental results that shows the electrochemical sensors can detect small pH and dissolved oxygen concentration changes created by the engineered bacterial populations’ …

Non-Hazardous Industrial Solid Waste Tracking System, Justin Tank

Masters Theses & Doctoral Dissertations

The Olmsted Non-Hazardous Industrial Solid Waste Tracking System allows waste generators of certain materials to electronically have their waste assessments evaluated, approved, and tracked through a simple online process. The current process of manually requesting evaluations, prepopulating tracking forms, and filling them out on triplicate carbonless forms is out of sync with other processes in the department. Complying with audit requirements requires pulling physical copies and providing them physically to fulfill information requests.

Waste generators in Minnesota are required to track their waste disposals for certain types of industrial waste streams. This ensures waste is accounted for at the point …

Automated Evolution Of Feature Logging Statement Levels Using Git Histories And Degree Of Interest, Yiming Tang, Allan Spektor, Raffi Khatchadourian, Mehdi Bagherzadeh

Publications and Research

Logging—used for system events and security breaches to more informational yet essential aspects of software features—is pervasive. Given the high transactionality of today’s software, logging effectiveness can be reduced by information overload. Log levels help alleviate this problem by correlating a priority to logs that can be later filtered. As software evolves, however, levels of logs documenting surrounding feature implementations may also require modification as features once deemed important may have decreased in urgency and vice-versa. We present an automated approach that assists developers in evolving levels of such (feature) logs. The approach, based on mining Git histories and manipulating …

The Origin & Evolution Of The Chinese Language, Charity Bullis, Yan Xie

Liberty University Research Week

Undergraduate

Textual or Investigative

Sql Injection & Web Application Security: A Python-Based Network Traffic Detection Model, Nyki Anderson

Cybersecurity Undergraduate Research Showcase

The Internet of Things (IoT) presents a great many challenges in cybersecurity as the world grows more and more digitally dependent. Personally identifiable information (PII) (i,e., names, addresses, emails, credit card numbers) is stored in databases across websites the world over. The greatest threat to privacy, according to the Open Worldwide Application Security Project (OWASP) is SQL injection attacks (SQLIA) [1]. In these sorts of attacks, hackers use malicious statements entered into forms, search bars, and other browser input mediums to trick the web application server into divulging database assets. A proposed technique against such exploitation is convolution neural network …

Mesoscopic Traffic Simulation Model And Calibration Considering Stretching-Segment Design, Zhaocheng He, Xuanhua Lin, Peilin Nie, Ronghui Zhang

Journal of System Simulation

Abstract: In order to make the simulation model fit the characteristics of urban traffic, both high accuracy and high performance, a lightweight mesoscopic traffic simulation system and the process of calibration are established. The speed-density model and vertical queue model are equivalent to the vehicle movement processes, the simulation accuracy and calibration efficiency are improved by the stretching-segment design at urban intersections of vertical queuing model, and the real individual vehicle information is used as the calibration data source. The application of the model in Xuancheng urban road network shows that, compared with the vertical queuing model, it can …

Modeling And Simulation Of Electric Vehicle Industry Development Based On System Dynamics, Yueqiang Fu, Tiantian Xia

Journal of System Simulation

Abstract: New energy electric vehicle are the main trend of automobile industry upgrading. It plays an important role in ensuring the energy security and improving the ecological environment. It is of theoretical and practical significance to carry out research on the development of new energy electric vehicles. The affecting factors are systematically analyzed, the causal relationship model and stock flow model are established, and the dynamic equation of the model are determined and the parameter assignments are made. The model is verified and the system simulation and analysis are performed. The development trend and main influencing factors of …

Unified Multi-Objective Genetic Algorithm For Energy Efficient Job Shop Scheduling, Hongjong Wei, Shaobo Li, Huageng Quan, Dacheng Liu, Shu Rao, Chuanjiang Li, Jianjun Hu

Faculty Publications

In recent years, people have paid more and more attention to traditional manufacturing’s environmental impact, especially in terms of energy consumption and related emissions of carbon dioxide. Except for adopting new equipment, production scheduling could play an important role in reducing the total energy consumption of a manufacturing plant. Machine tools waste a considerable amount of energy because of their underutilization. Consequently, energy saving can be achieved by switching machines to standby or off when they lay idle for a comparatively long period. Herein, we first introduce the objectives of minimizing non-processing energy consumption, total weighted tardiness and earliness, and …

Small Fault Detection Based On Cumulative Sum Of Neighbor Statistic, Xiaoping Guo, Jiajun Gao, Jianbin Guo, Li Yuan

Journal of System Simulation

Abstract: Aiming at the small faults and the common data non-linear problems of industrial process, a fault detection method based oncumulative sum of neighbor statistic (CUSUM-NS) is proposed. Mutual information principal component analysis (MIPCA) is used to reduce the dimension of training data, and the principal components based on mutual information are extracted to construct a new sample space. For the new sample space after dimensionality reduction, the nonlinear features of the process data can be fully extracted through the distance square sum statistics of k nearest neighbors. Cumulative summation(CUSUM) method is used to accumulate the sum of squares of …

Visual Simulation Platform For Visible Light Reconnaissance Load Of Unmanned Aerial Vehicle, Yuzhou Chen, Li Yuan, Qinglin Wang, Zhang Qing, Jinyuan Zhang

Journal of System Simulation

Abstract: In view of the simulation and evaluation requirement of the visual system parameters on the performance of video imaging during the operation and reconnaissance of unmanned aerial vehicle, a visual simulation platform for the reconnaissance load is designed and constructed. The collected video is processed according to the visual system parameters and the flight parameters, and the support for the evaluation and the index design of the unmanned aerial vehicle reconnaissance load system is provided, and the guidance is provided for the flight parameters and the flight track setting when the unmanned aerial vehicle reconnaissance and operation …

Research On Some Questions Of Simulation Body Of Knowledge, Xiaogang Qiu, Duan Hong, Xie Xu, Bin Chen

Journal of System Simulation

Abstract: Simulation body of knowledge (BOK) is the knowledge required to conduct Modeling and Simulation (M&S) activities, which is a logic system consisting of concepts, propositions, and inferences that are tightly related to each other. The simulation BOK organizes the M&S knowledge in a hierarchical way, reflects the composition and structure of the knowledge in the M&S domain. The establishment of the simulation BOK is crucial to advance the M&S research and education. The requirements for establishing the simulation BOK are summarized, three basic features of the simulation knowledge, practical, systematical, and epochal are discussed, the challenges of establishing the …