Computer Sciences Commons^™

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 …

For People And Planet: Teachers’ Evaluation Of An Educational Mobile Game And Resource Pack, Ma. Mercedes T. Rodrigo, Johanna Marion R. Torres, Janina Carla M. Castro, Abigail Marie T. Favis, Ingrid Yvonne Herras, Francesco U. Amante, Hakeem Jimenez, Juan Carlo F. Mallari, Kevin Arnel C. Mora, Walfrido David A. Diy, Jaclyn Ting Ting M. Lim, Ma. Assunta C. Cuyegkeng

Department of Information Systems & Computer Science Faculty Publications

For People and Planet: An SDG Adventure refers to a freely available Android-based narrative adventure game and teacher resource pack that helps learners see the United Nations Sustainable Development Goals (SDGs) in their day-to-day lives. In this paper, we describe the results of an evaluation of both the game and the resource pack by eight (8) middle school teachers. After playing the game and reading the resource pack, teachers gave their feedback about what they liked best and least about the materials, how they could use these resources for their classes, and how these resources could be improved further. Overall, …

Introducing A Test Framework For Quality Of Service Mechanisms In The Context Of Software-Defined Networking, Josiah Eleazar T. Regencia, William Emmanuel S. Yu

Department of Information Systems & Computer Science Faculty Publications

In traditional non-distributed networking architecture, supporting Quality of Service (QoS) has been challenging due to its centralized nature. Software-Defined Networking (SDN) provides dynamic, flexible and scalable control and management for networks. This study introduces a test framework for testing QoS mechanisms and network topologies inside an SDN environment. Class-Based Queueing QoS mechanisms are tested as an anchor to test the introduced framework. Using a previous study as a benchmark to test the introduced framework, results show that the test framework works accordingly and is capable of producing accurate results. Moreover, results in this study show that the distributed Leaf-enforced QoS …

Activity Based Traffic Indicator System For Monitoring The Covid-19 Pandemic, Justin Junsay, Aaron Joaquin Lebumfacil, Ivan George Tarun, William Emmanuel S. Yu

Department of Information Systems & Computer Science Faculty Publications

This study describes an activity based traffic indicator system to provide information for COVID-19 pandemic management. The activity based traffic indicator system does this by utilizing a social probability model based on the birthday paradox to determine the exposure risk, the probability of meeting someone infected (PoMSI). COVID-19 data, particularly the 7-day moving average of the daily growth rate of cases (7-DMA of DGR) and cumulative confirmed cases of next week covering a period from April to September 2020, were then used to test PoMSI using Pearson correlation to verify whether it can be used as a factor for the …

Mental Health And The Covid-19 Pandemic: Analysis Of Twitter Discourse, Omar El-Gayar, Abdullah Wahbeh, Tareq Nasralah, Ahmed El Noshokaty, Mohammad A. Al-Ramahi

Computer Information Systems Faculty Publications (Archived)

This study analyzed Twitter discourse to understand the association of the COVID-19 pandemic with mental health. The study compared tweets’ volume over time, tweets’ volume per mental health category, emotions, and the top hashtags on mental health before and after November 2019, the month on which the first COVID-19 case was reported. We analyzed a total of 273 million English tweets on mental health collected from 56 million unique users. Results and analysis showed a significant shift in trend for the volume of tweets on mental health over time. There was also a notable increase in the volume of tweets …

Detecting Face Mask Usage Trends In Social Media With Machine Learning, Seth Ockerman

Student Summer Scholars Manuscripts

The use of face masks to prevent disease spread among the general population has become widespread due to the COVID-19 pandemic. The ability to accurately detect and monitor the trends in face mask usage is crucial to understanding and predicting hotspot areas for both current and future pandemics. In this work, we investigate the detection of face masks in social media images using deep learning, specifically convolutional neural networks (CNNs). The use of CNNs for face mask detection has been explored by the research community; however, a common limiting factor has been the lack of a large, diverse image dataset …

Learning From Multi-Class Imbalanced Big Data With Apache Spark, William C. Sleeman Iv

Theses and Dissertations

With data becoming a new form of currency, its analysis has become a top priority in both academia and industry, furthering advancements in high-performance computing and machine learning. However, these large, real-world datasets come with additional complications such as noise and class overlap. Problems are magnified when with multi-class data is presented, especially since many of the popular algorithms were originally designed for binary data. Another challenge arises when the number of examples are not evenly distributed across all classes in a dataset. This often causes classifiers to favor the majority class over the minority classes, leading to undesirable results …

Towards Effective Delivery Of Digital Interventions For Mental And Behavioral Health, Varun Mishra

Dartmouth College Ph.D Dissertations

The pervasiveness of sensor-rich mobile, wearable, and IoT devices has enabled researchers to passively sense various user traits and characteristics, which in turn have the potential to detect and predict different mental and behavioral health outcomes. Upon detecting or anticipating a negative outcome, the same devices can be used to deliver in-the-moment interventions and support to help users. One important factor that determines the effectiveness of digital health interventions is delivering them at the right time: (1) when a person needs support, i.e., at or before the onset of a negative outcome, or a psychological or contextual state that might …

Structural Analysis And Link Prediction Algorithm Comparison For A Local Scientific Collaboration Network, Denys Guriev

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Scientific collaboration between researchers is very common and much influential and ground-breaking research is performed by teams comprised of scientist from different fields and organizations. In this thesis, we analyze and model a small scientific collaboration network limited to two organizations: Wright State University and the Air Force Research Laboratory. Research paper co-authorship is used for establishing the network structure. We analyze several network properties and compare them to past results from analysis of larger and more diverse collaboration networks. We show that the two-organization network we explored exhibits properties similar to those of larger networks. Guided by advances in …

Computational Simulation And Analysis Of Neuroplasticity, Madison E. Yancey

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Homeostatic synaptic plasticity is the process by which neurons alter their activity in response to changes in network activity. Neuroscientists attempting to understand homeostatic synaptic plasticity have developed three different mathematical methods to analyze collections of event recordings from neurons acting as a proxy for neuronal activity. These collections of events are from control data and treatment data, referring to the treatment of neuron cultures with pharmacological agents that augment or inhibit network activity. If the distribution of control events can be functionally mapped to the distribution of treatment events, a better understanding of the biological processes underlying homeostatic synaptic …

Deep Learning For Compressive Sar Imaging With Train-Test Discrepancy, Morgan R. Mccamey

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We consider the problem of compressive synthetic aperture radar (SAR) imaging with the goal of reconstructing SAR imagery in the presence of under sampled phase history. While this problem is typically considered in compressive sensing (CS) literature, we consider a variety of deep learning approaches where a deep neural network (DNN) is trained to form SAR imagery from limited data. At the cost of computationally intensive offline training, on-line test-time DNN-SAR has demonstrated orders of magnitude faster reconstruction than standard CS algorithms. A limitation of the DNN approach is that any change to the operating conditions necessitates a costly retraining …

Content Adaption And Design In Mobile Learning Of Wind Instruments, Neha Priyadarshani

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People in today's world seek things that are simple to use. Learning is one of the most crucial aspects of the ongoing digital transformation. Everything is now accessible with a single click on mobile devices, making access to instructional materials faster, easier, and more comfortable. It takes time and effort to build abilities and become an expert in the fields of learning, training, and teaching; and music learning demands a great deal of both practice and mentoring. Initially, music teachers and band directors must maintain a steady attention and devote a significant amount of time to manually teaching materials. This …

Mathematical Formula Recognition And Automatic Detection And Translation Of Algorithmic Components Into Stochastic Petri Nets In Scientific Documents, Elisavet Elli Kostalia

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A great percentage of documents in scientific and engineering disciplines include mathematical formulas and/or algorithms. Exploring the mathematical formulas in the technical documents, we focused on the mathematical operations associations, their syntactical correctness, and the association of these components into attributed graphs and Stochastic Petri Nets (SPN). We also introduce a formal language to generate mathematical formulas and evaluate their syntactical correctness. The main contribution of this work focuses on the automatic segmentation of mathematical documents for the parsing and analysis of detected algorithmic components. To achieve this, we present a synergy of methods, such as string parsing according to …

Evaluating The Performance Of Using Speaker Diarization For Speech Separation Of In-Person Role-Play Dialogues, Raveendra Medaramitta

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Development of professional communication skills, such as motivational interviewing, often requires experiential learning through expert instructor-guided role-plays between the trainee and a standard patient/actor. Due to the growing demand for such skills in practices, e.g., for health care providers in the management of mental health challenges, chronic conditions, substance misuse disorders, etc., there is an urgent need to improve the efficacy and scalability of such role-play based experiential learning, which are often bottlenecked by the time-consuming performance assessment process. WSU is developing ReadMI (Real-time Assessment of Dialogue in Motivational Interviewing) to address this challenge, a mobile AI solution aiming to …