Computer Sciences Commons^™

Deapsecure Computational Training For Cybersecurity Students: Improvements, Mid-Stage Evaluation, And Lessons Learned, Wirawan Purwanto, Yuming He, Jewel Ossom, Qiao Zhang, Liuwan Zhu, Karina Arcaute, Masha Sosonkina, Hongyi Wu

University Administration Publications

DeapSECURE is a non-degree computational training program that provides a solid high-performance computing (HPC) and big-data foundation for cybersecurity students. DeapSECURE consists of six modules covering a broad spectrum of topics such as HPC platforms, big-data analytics, machine learning, privacy-preserving methods, and parallel programming. In the second year of this program, to improve the learning experience, we implemented a number of changes, such as grouping modules into two broad categories, "big-data" and "HPC"; creating a single cybersecurity storyline across the modules; and introducing post-workshop (optional) "hackshops." Two major goals of these changes are, firstly, to effectively engage students to maintain …

Covid-19 And Biocybersecurity's Increasing Role On Defending Forward, Xavier Palmer, Lucas N. Potter, Saltuk Karahan

Electrical & Computer Engineering Faculty Publications

The evolving nature of warfare has been changing with cybersecurity and the use of advanced biotechnology in each aspect of the society is expanding and overlapping with the cyberworld. This intersection, which has been described as “biocybersecurity” (BCS), can become a major front of the 21st-century conflicts. There are three lines of BCS which make it a critical component of overall cybersecurity: (1) cyber operations within the area of BCS have life threatening consequences to a greater extent than other cyber operations, (2) the breach in health-related personal data is a significant tool for fatal attacks, and (3) health-related misinformation …

Ship Deck Segmentation In Engineering Document Using Generative Adversarial Networks, Mohammad Shahab Uddin, Raphael Pamie-George, Daron Wilkins, Andres Sousa Poza, Mustafa Canan, Samuel Kovacic, Jiang Li

Engineering Management & Systems Engineering Faculty Publications

Generative adversarial networks (GANs) have become very popular in recent years. GANs have proved to be successful in different computer vision tasks including image-translation, image super-resolution etc. In this paper, we have used GAN models for ship deck segmentation. We have used 2D scanned raster images of ship decks provided by US Navy Military Sealift Command (MSC) to extract necessary information including ship walls, objects etc. Our segmentation results will be helpful to get vector and 3D image of a ship that can be later used for maintenance of the ship. We applied the trained models to engineering documents provided …

Do Blockchain And Iot Architecture Create Informedness To Support Provenance Tracking In The Product Lifecycle?, Somnath Mazumdar, Thomas Jensen, Raghava Rao Mukkamala, Robert John Kauffman, Jan Damsgaard

Research Collection School Of Computing and Information Systems

Consumers often lack information about the origin and provenance of the products they buy. They may ask: Is a food product truly organic? Or, what is the origin of the gemstone in the ring I purchased? They also may have sustainability concerns about the footprint of a product at the end of its life. Producers and sellers, meanwhile, wish to know how longitudinal tracking of the provenance of products and their components can boost their sales prices and after-market value, and re- veal new business opportunities. We focus on how the product lifecycle (PLC) can be leveraged to track information …

Inference Of Surface Velocities From Oblique Time Lapse Photos And Terrestrial Based Lidar At The Helheim Glacier, Franklyn T. Dunbar Ii

Graduate Student Theses, Dissertations, & Professional Papers

Using time dependent observations derived from terrestrial LiDAR and oblique
time-lapse imagery, we demonstrate that a Bayesian approach to glacial motion es-
timation provides a concise way to incorporate multiple data products into a single
motion estimation procedure effectively producing surface velocity estimates with
an associated uncertainty. This approach brings both improved computational effi-
ciency, and greater scalability across observational time-frames when compared to
existing methods. To gauge efficacy, we apply these methods to a set of observa-
tions from the Helheim Glacier, a critical actor in contemporary mass loss trends
observed in the Greenland Ice Sheet. We find that …

Detection Of Gaussian Attacks In Power Systems Under A Scalable Kalman Consensus Filter Framework, Arnold Fernandes, Rui Bo, Jonathan W. Kimball, Bruce M. Mcmillin

Electrical and Computer Engineering Faculty Research & Creative Works

The dynamic non-linear state-space model of a power-system consisting of synchronous generators, buses, and static loads has been linearized and a linear measurement function has been considered. A distributed dynamic framework for estimating the state vector of the power system has been designed here. This framework employs a type of distributed Kalman filter (DKF) known as a Kalman consensus filter (KCF) which is located at distributed control centers (DCCs) that fuse locally available noise ridden measurements, state vector estimates of neighboring control centers, and a prediction obtained by the linearized model to obtain a filtered state vector estimate. Further, the …

Sample Mislabeling Detection And Correction In Bioinformatics Experimental Data, Soon Jye Kho

Browse all Theses and Dissertations

Sample mislabeling or incorrect annotation has been a long-standing problem in biomedical research and contributes to irreproducible results and invalid conclusions. These problems are especially prevalent in multi-omics studies in which a large set of biological samples are characterized by multiple types of omics platforms at different times or different labs. While multi-omics studies have demonstrated tremendous value in understanding disease biology and improving patient outcomes, the complexity of these studies may increase opportunities for human error. Fortunately, the interrelated nature of the data collected in multi-omics studies can be exploited to facilitate the identification and, in some cases, correction …

Natural User Interface Based American Sign Language Tutoring Program, Bryce J. Allen

Williams Honors College, Honors Research Projects

The COVID-19 pandemic has exposed a substantial shortcoming in the modern American educational system: there is a sufficient need for our educators to be trained in the practices required to provide an educational experience for their students that is as effective as in-person instruction. There exist already systems of online instruction for various academic subjects, such as math and the sciences. In the subject of linguistic studies, educational programs have been developed to evaluate student proficiency in both the written and spoken forms of the language in which they are studying. However, there exist few programs that can effectively provide …

Design Project: Smart Headband, John Michel, Jack Durkin, Noah Lewis

Williams Honors College, Honors Research Projects

Concussion in sports is a prevalent medical issue. It can be difficult for medical professionals to diagnose concussions. With the fast pace nature of many sports, and the damaging effects of concussions, it is important that any concussion risks are assessed immediately. There is a growing trend of wearable technology that collects data such as steps and provides the wearer with in-depth information regarding their performance. The Smart Headband project created a wearable that can record impact data and provide the wearer with a detailed analysis on their risk of sustaining a concussion. The Smart Headband uses accelerometers and gyroscopes …

Football’S Future: An Analytical Interpretation Of The Premier League, Hunter Witeof

Williams Honors College, Honors Research Projects

This project looks to take the statistics of soccer players and run them through an algorithm to determine how well a player is performing. The system that will be designed in the project will look to accomplish 3 main goals: allow the user to enter new statistics, store the data for all 38 game weeks for all 20 teams, and compute a score for each player’s performance for each game as well as the average of all of the player's scores.

A Rebellion Framework With Learning For Goal-Driven Autonomy, Zahiduddin Mohammad

Browse all Theses and Dissertations

Modeling an autonomous agent that decides for itself what actions to take to achieve its goals is a central objective of artificial intelligence. There are various approaches used to build autonomous agents including neural networks, state machines, utility functions, learning agents, and cognitive architectures. In this thesis, we focus on cognitive architectures. Our approach uses specific knowledge of the world, the goals they pursue, and the actions being performed. Most agents do what they are told (i.e., achieve the goals given to them by a human), but a genuinely autonomous agent does more. It can formulate its own goal or …

Partial Facial Re-Imaging Using Generative Adversarial Networks, Derek Desentz

Browse all Theses and Dissertations

Existing facial recognition software relies heavily on using neural networks to extract key facial features to accurately classify known individuals. Some of these key features include the shape, size, and distance between an individual’s eyes, nose, and mouth. When these key features cannot be extracted due to facial coverings, existing applications become inaccurate and unreliable. The accuracy and reliability of these technologies are growing concerns as the facial recognition market continues to grow at an exponential rate. In this thesis, we have developed a web-based application service that is able to take in a partially covered face image and generate …

Clustering Data To Classify Hearthstone Decks, Tim Inzitari

Williams Honors College, Honors Research Projects

The esports game of "Hearthstone" is a collectible card game with a competitive format that has every team submit 4 decks of 30 cards each. Using K-Means clustering an adaptable way to group data for classifying can be made that works well in every update of the game. This system will take in a list of decks and cluster them to easily classify large amounts of information in a timely fashion. This system will be able to be used by the Universities esports department for years to come to aid the preparation of "Hearthstone" matches. This model uses qualities about …

Interactive Virtual Reality Reading Experience, Nathaniel Shetler

Williams Honors College, Honors Research Projects

The project is an interactive virtual reality reading experience. The user is able to read a book or story in VR. When certain achievements are reached, such as finishing a chapter, the user is given the opportunity to transport to the environment that they are reading about. This gives the user a great opportunity to interact and learn hands-on with the material they are reading about. For example, if the user is reading about World War I, they will be given the opportunity to transport to the battlefields/trenches in Europe.

Online Marketplace, Devin Hopkins

Williams Honors College, Honors Research Projects

The goal of this project was to create a website that helped a common person search for items from online marketplaces, such as eBay, Amazon, or Facebook Marketplace. The intention was to ease the burden of needing to search several different websites for the same product. Currently, if a person wants to look for a specific item on multiple different marketplaces, they must go to each marketplace individually and search for it. They must enter their specifications repeatedly and load virtually the same web page multiple times. This project’s goal was to condense that so the user would only have …

Source Code Comment Classification Artificial Intelligence, Cole Sutyak

Williams Honors College, Honors Research Projects

Source code comment classification is an important problem for future machine learning solutions. In particular, supervised machine learning solutions that have largely subjective data labels but are difficult to obtain the labels for. Machine learning problems are problems largely because of a lack of data. In machine learning solutions, it is better to have a large amount of mediocre data than it is to have a small amount of good data. While the mediocre data might not produce the best accuracy, it produces the best results because there is much more to learn from the problem.

In this project, data …

Versatility Of Low-Power Wide-Area Network Applications, Dali Ismail

Wayne State University Dissertations

Low-Power Wide-Area Network (LPWAN) is regarded as the leading communication technology for wide-area Internet-of-Things (IoT) applications. It offers low-power, long-range, and low-cost communication. With different communication requirements for varying IoT applications, many competing LPWAN technologies operating in both licensed (e.g., NB-IoT, LTE-M, and 5G) and unlicensed (e.g., LoRa and SigFox) bands have emerged. LPWANs are designed to support applications with low-power and low data rate operations. They are not well-designed to host applications that involve high mobility, high traffic, or real-time communication (e.g., volcano monitoring and control applications).With the increasing number of mobile devices in many IoT domains (e.g., agricultural …

Methods For Ad Hoc And Conversational Entity Retrieval From Knowledge Graphs, Fedor Nikolaev

Wayne State University Dissertations

The recent years have witnessed the increase in popularity of knowledge graphs in various applications, such as information extraction and retrieval systems, and intelligent assistants. Traditionally, retrieval from knowledge graphs is performed by submitting queries in SPARQL, a rigid query language based on triple patterns and logical operations. In this work, we propose several approaches to ad hoc and conversational entity retrieval that transcend the limitations of this approach by allowing the user to either submit queries using natural language in an ad hoc retrieval setting or have a conversation with an intelligent retrieval system by asking a series of …

Optimizing Sparse Tensor Computations Via Orderings And Multilayered Data-Structures, Trevor Garnett

Summer Community of Scholars Posters (RCEU and HCR Combined Programs)

No abstract provided.

Evaluation Of Traceability Management Tools For Student Software Development, Abi Kunkle

Summer Community of Scholars Posters (RCEU and HCR Combined Programs)

No abstract provided.

The Data Science Corps Wrangle-Analyze- Visualize Program: Building Data Acumen For Undergraduate Students, Nicholas J. Horton, Benjamin Baumer, Andrew Zieffler, Valerie Barr

Statistical and Data Sciences: Faculty Publications

We congratulate Kolaczyk, Wright, and Yajima on their innovative statistics practicum that places “practice” at the center of data science education (Kolaczyk et al., 2021, this issue). Their year-long practicum course focuses on the data science life cycle with engagement with external partners and university consulting projects. We agree that training postgraduates in practice needs to be foregrounded in the curriculum in order for students to develop necessary depth in data science practice.

Four Opportunities For Se Ethics Education, Alicia M. Grubb

Computer Science: Faculty Publications

Many software engineers direct their talents to- wards software systems which do not fall into traditional definitions of safety critical systems, but are integral to society (e.g., social media, expert advisor systems). While codes of ethics can be a useful starting point for ethical discussions, codes are often limited in scope to professional ethics and may not offer answers to individuals weighing competing ethical priorities. In this paper, we present our vision for improving ethics education in software engineering. To do this, we consider current and past curricular recommendations, as well as recent efforts within the broader computer science community. …

Towards A Generic Method For Articulating Design Uncertainty, Mouna Dhaouadi, Kate M. B. Spencer, Megan H. Varnum, Alicia M. Grubb, Michalis Famelis

Computer Science: Faculty Publications

Modelers encounter different kinds of uncertainty in their designs and models of software systems. One such type concerns uncertainty about how to build a model. This is called design-time uncertainty, and existing research has studied how modelers can work in its presence. However, the process by which they come to elicit and express their uncertainties remains unclear. In this paper, we take steps towards addressing this gap by introducing DRUIDE (Design and Requirements Uncertainty Integrated Development Environment), a language and workflow for articulating design time uncertainty. We present and illustrate our proposal on a software design example. Additionally, we conduct …

Secure Network Access Via Ldap, Nicholas Valaitis

Williams Honors College, Honors Research Projects

Networks need the ability to be access by secure accounts and users. The goal of this project is to configure and expand on LDAP configurations with considerations for AAA via TACACS+ and Radius for network equipment. This will provide adequate security for any given network in terms of access and prevent lose of access to devices which happens all to often with locally configured accounts on devices.

Preforming A Vulnerability Assessment On A Secured Network, Mathias Sovine

Williams Honors College, Honors Research Projects

A computer network will be built using 3 routers, 1 switch, and 4 computers. The network will be used to simulate the connections between an at home office and the internet. The network will be divided into 3 sub-networks. The routers will be secured using methods like access control lists, changing default admin passwords, and network encryption. The switch will be secured using methods like switchport security and setting access passwords. Once the network is secured, three penetration testing techniques and three exploits will be performed on the network. The results of the exploits and penetration testing techniques will be …

Understanding The Research And Applications Of Quantum Computing, Joshua Foss

Williams Honors College, Honors Research Projects

In-Depth research of current quantum computing understanding and practices. Presentation of possible new and creative applications of quantum computing.

Cura Personalis: Institutionalizing Compassion During Emergency Remote Teaching, Ma. Monica L. Moreno, Ma. Mercedes T. Rodrigo, Johanna Marion R. Torres, Timothy Jireh Gaspar, Jenilyn L. Agapito

Department of Information Systems & Computer Science Faculty Publications

Faced with the fears and anxieties brought on by the COVID-19 crisis, educational institutions had to devise new compassion-based teaching and learning policies and approaches that recognized and provided for the pandemic’s psychological and emotional toll. This paper describes how the Ateneo de Manila University in the Philippines enacted its core value of cura personalis, care for the entire person, in the context of emergency remote teaching. We describe the circumstances that prompted the greater emphasis on compassion and the adjustments to classroom management, course content, class interactions, and assessment. Finally we describe the tradeoffs or costs of this …

Transactional Distances During Emergency Remote Teaching Experiences, Ma. Monica L. Moreno, Ma. Mercedes T. Rodrigo, Johanna Marion R. Torres, Timothy Jireh Gaspar, Jenilyn L. Agapito

Department of Information Systems & Computer Science Faculty Publications

The Transactional Distance Theory posits that successful remote learning occurs when teachers decrease psychological or transactional gaps. Narrowing the transactional distance can be achieved through a balance of appropriate course structure and dialogue, fostering healthy student autonomy in the process. This paper describes the Emergency Remote Teaching experiences of faculty and students of the Ateneo de Manila University in the Philippines. It examines these experiences in the context of the transactional distance framework. Findings show that a sudden shift to remote learning mandates greater student autonomy, which increases transactional distance. Because of this, efforts by faculty to increase student-teacher dialogue …

Xiphias: Using A Multidimensional Approach Towards Creating Meaningful Gamification-Based Badge Mechanics, Jonathan D.L Casano, Jenilyn L. Agapito, Nicole Ann F. Tolosa

Department of Information Systems & Computer Science Faculty Publications

This paper shows the design and initial testing of three new Xiphias Badges --Presence; Mastery; and Antifragility – based on the merging of the salient features from James Clear’s Behavior Change model (2016); Johann Hari’s Lost Connections model (2018); and Jordan Peterson’s recent interpretation of the Big Five model of Personality Traits (2007). This multidimensional approach is an attempt to cater to the multidimensionality of a user and aims to be a more universal gamification approach that taps into internal motivations. The badge mechanics were tested on 69 undergraduate students using a Low-Fidelity Gamified Tracker. The results of a survey …

Comparison Of English Comprehension Among Students From Different Backgrounds Using A Narrative-Centered Digital Game, May Marie P. Talandron-Felipe, Kent Levi A. Bonifacio, Gladys S. Ayunar, Ma. Mercedes T. Rodrigo

Department of Information Systems & Computer Science Faculty Publications

This paper reports the continuation of the field testing of a narrative-centered digital game for English comprehension called Learning Likha: Rangers to the Rescue (LLRR) with a two-fold goal: first, identify the differences in terms of usage, attitudes towards, and perceptions of the English language between students from southern Philippines and the National Capital Region, and second, to determine how the LLRR in-game performance, post-test comprehension scores, engagement, and motivation of students differ between the groups. The participants who are grade school students from a province in southern Philippines answered questionnaires about their attitude towards and perception of English, played …