Computer Sciences Commons^™

Enhancing Pedestrian-Autonomous Vehicle Safety In Low Visibility Scenarios: A Comprehensive Simulation Method, Zizheng Yan, Yang Liu, Hong Yang

Modeling, Simulation and Visualization Student Capstone Conference

Self-driving cars raise safety concerns, particularly regarding pedestrian interactions. Current research lacks a systematic understanding of these interactions in diverse scenarios. Autonomous Vehicle (AV) performance can vary due to perception accuracy, algorithm reliability, and environmental dynamics. This study examines AV-pedestrian safety issues, focusing on low visibility conditions, using a co-simulation framework combining virtual reality and an autonomous driving simulator. 40 experiments were conducted, extracting surrogate safety measures (SSMs) from AV and pedestrian trajectories. The results indicate that low visibility can impair AV performance, increasing conflict risks for pedestrians. AV algorithms may require further enhancements and validations for consistent safety performance …

U-Net Based Multiclass Semantic Segmentation For Natural Disaster Based Satellite Imagery, Nishat Ara Nipa

Modeling, Simulation and Visualization Student Capstone Conference

Satellite image analysis of natural disasters is critical for effective emergency response, relief planning, and disaster prevention. Semantic segmentation is believed to be on of the best techniques to capture pixelwise information in computer vision. In this work we will be using a U-Net architecture to do a three class semantic segmentation for the Xview2 dataset to capture the level of damage caused by different natural disaster which is beyond the visual scope of human eyes.

Assessing Frustration Towards Venezuelan Migrants In Columbia: Path Analysis On Newspaper Coded Data, Brian Llinás, Guljannat Huseynli, Erika Frydenlund, Katherine Palacia, Jose Padilla

Modeling, Simulation and Visualization Student Capstone Conference

This study analyzes the impact of Venezuelan migrants on local frustration levels in Colombia. The study found a relationship between the influx of Venezuelan migrants and the level of frustration among locals towards migrants, infrastructure, government, and geopolitics. Additionally, we identified that frustration types have an impact on other frustrations. The study used articles from a national newspaper in Colombia from 2015 to 2020. News articles were coded during a previous study qualitatively and categorized into frustration types. The code frequencies were then used as variables in this study. We used path modeling to statistically study the relationship between dependent …

Lidar Buoy Detection For Autonomous Marine Vessel Using Pointnet Classification, Christopher Adolphi, Dorothy Dorie Parry, Yaohang Li, Masha Sosonkina, Ahmet Saglam, Yiannis E. Papelis

Modeling, Simulation and Visualization Student Capstone Conference

Maritime autonomy, specifically the use of autonomous and semi-autonomous maritime vessels, is a key enabling technology supporting a set of diverse and critical research areas, including coastal and environmental resilience, assessment of waterway health, ecosystem/asset monitoring and maritime port security. Critical to the safe, efficient and reliable operation of an autonomous maritime vessel is its ability to perceive on-the-fly the external environment through onboard sensors. In this paper, buoy detection for LiDAR images is explored by using several tools and techniques: machine learning methods, Unity Game Engine (herein referred to as Unity) simulation, and traditional image processing. The Unity Game …

From Policy Promotion To Research Output: Brief Analysis Of Technical Challenges Of Hospital-Led Artificial Intelligence Research, Yu Zhuang, Cheng Zhou

Bulletin of Chinese Academy of Sciences (Chinese Version)

In recent years, artificial intelligence has become a key direction of medical and health-related research and a hot spot of international competition. In order to investigate the current situation and challenges in hospital-led artificial intelligence researched, this study selects 14 national pilot hospitals to promote the high-quality development of public hospitals as samples, adopts a combination of quantitative and qualitative methods, analyzes the research articles related to artificial intelligence published by the sample hospitals in recent years, and analyzes the technical challenges in the hospital-led artificial intelligence research. The results show that although the number of hospital-led artificial intelligence research …

Analysis The Role Of The Internet Of Things And Industry 4.0 In Healthcare Supply Chain Using Neutrosophic Sets, Ahmed M. Abdelmouty, Ahmed Abdel-Monem, Samah Ibrahim Abdel Aal, Mahmoud M. Ismail

Neutrosophic Systems with Applications

In today's global economy, the Healthcare supply chain (HCSC) must be aware of a market that is both complicated and ever-changing. The HCSC in Industry 4.0 aims to give patients the medicine they need as quickly and cheaply as possible. The HCSC can improve operations by automating routine tasks and reducing human error by using new technologies like the "Internet of Things" (IoT); so, there is a need to analyze the role of IoT and Industry 4.0 in the Healthcare Supply Chain. This paper aims to analyze the role of IoT and Industry 4.0 in HCSC. Also, this paper proposes …

Novel Paradigm For Ai-Driven Scientific Research: From Ai4s To Intelligent Science, Feiyue Wang, Qinghai Miao

Bulletin of Chinese Academy of Sciences (Chinese Version)

No abstract provided.

Investigating The Comprehension Of Gpt's Interpretation Of Word Meanings, Longge Yuan

Research & Creative Achievement Day

ChatGPT is a large-scale language model developed by OpenAI. Its purpose is to start a conversation with people and provide them with information ranging from simple facts to more complex topics. Trained on a large amount of text data, ChatGPT has shown us that it can understand human language and respond in a meaningful way. In this paper, we show a way to judge whether ChatGPT can accurately understand the various meanings of words and use them based on the answers output by ChatGPT. The five dimensions, each scored up to 5 points, are word explanation, etymology, synonyms and antonyms, …

Ecomves: Enhancing Comves Using Data Piggybacking For Resource Discovery At The Network Edge, Sanzida Hoque

Theses

Over the past few years, Augmented Reality (AR) and Virtual Reality (VR) have emerged as highly popular technologies that demand rapid and efficient processing of data with low latency and high bandwidth, in order to enable seamless real-time interaction between users and the virtual environment. This presents challenges for network infrastructure design, which can be addressed through edge computing. However, edge computing also presents challenges, such as selecting the appropriate edge server for computing tasks in dynamic networks with rapidly changing resource availability. Named Data Networking (NDN) is a potential future Internet architecture that could provide a balanced distribution of …

Nviz: Unraveling Neural Networks Through Visualization, Kevin Hoffman

Mathematics, Computer Science & Statistics Presentations

The growing utility of artificial intelligence (AI) is attributed to the development of neural networks. These networks are a class of models that make predictions based on previously observed data. While the inferential power of neural networks is great, the ability to explain their results is difficult because the underlying model is automatically generated. The AI community commonly refers to neural networks as black boxes because the patterns they learn from the data are not easily understood. This project aims to improve the visibility of patterns that neural networks identify in data. Through an interactive web application, NVIZ affords the …

R Text Analysis For Adam Smith Cie Selected Works, Charlotte Grahame

Mathematics, Computer Science & Statistics Presentations

Text mining and text analysis is a way of understanding text documents using r coding that is more frequently used for numbered data. It helps with understanding portions of the text and drawing conclusions from there. This research looks specifically at the Adam Smith required documents that are used in the CIE course designated for freshmen. It looks at sentiments of the documents, including word sentiment, sentence sentiment, page and overall document sentiment as well. It provides visuals of word clouds to portray word frequency, tf-idf (which is explained in the presentation) and bigram analysis.

Cie Text Analysis: Narrative Of The Life Of Frederick Douglass, The Declaration Of Independence, And The Declaration Of Sentiments, Arianna Knipe

Mathematics, Computer Science & Statistics Presentations

Our STAT-451 class has worked with analyzing the words from CIE texts and assigning them to a sentiment or feeling and comparing them with one another using RStudio. This project analyzes texts from three sources: The Narrative of the Life of Frederick Douglass, The Declaration of Independence and the Declaration of Sentiments.

Loss Scaling And Step Size In Deep Learning Optimizatio, Nora Alosily

Dissertations

Deep learning training consumes ever-increasing time and resources, and that is
due to the complexity of the model, the number of updates taken to reach good
results, and both the amount and dimensionality of the data. In this dissertation,
we will focus on making the process of training more efficient by focusing on the
step size to reduce the number of computations for parameters in each update.
We achieved our objective in two new ways: we use loss scaling as a proxy for
the learning rate, and we use learnable layer-wise optimizers. Although our work
is perhaps not the first …

Rethinking" Risk" In Algorithmic Systems Through A Computational Narrative Analysis Of Casenotes In Child-Welfare, Devansh Saxena, Erina Seh-Young Moon, Aryan Chaurasia, Yixin Guan, Shion Guha

Health Services and Informatics Research

No abstract provided.

Counterventions: A Reparative Reflection On Interventionist Hci, Rua Mae Williams, Louanne E. Boyd, Juan E. Gilbert

Engineering Faculty Articles and Research

Research in HCI applied to clinical interventions relies on normative assumptions about which bodies and minds are healthy, valuable, and desirable. To disrupt this normalizing drive in HCI, we define a “counterventional approach” to intervention technology design informed by critical scholarship and community perspectives. This approach is meant to unsettle normative assumptions of intervention as urgent, necessary, and curative. We begin with a historical overview of intervention in HCI and its critics. Then, through reparative readings of past HCI projects in autism intervention, we illustrate the emergent principles of a counterventional approach and how it may manifest research outcomes that …

Building Credibility, Trust, And Safety On Video-Sharing Platforms, Shuo Niu, Zhicong Lu, Amy X. Zhang, Jie Cai, Carla F. Griggio, Hendrick Heuer

Computer Science

Video-sharing platforms (VSPs) such as YouTube, TikTok, and Twitch attract millions of users and have become influential information sources, especially among the young generation. Video creators and live streamers make videos to engage viewers and form online communities. VSP celebrities obtain monetary benefits through monetization programs and affiliated markets. However, there is a growing concern that user-generated videos are becoming a vehicle for spreading misinformation and controversial content. Creators may make inappropriate content for attention and financial benefits. Some other creators also face harassment and attack. This workshop seeks to bring together a group of HCI scholars to brainstorm technical …

Volume 14, Ireland Seagle, Dalton C. Whitby, Cassandra Poole, Rachel Cannon, Heidi Parker-Combes, Devon G. Shifflett, Antonio Harvey

Incite: The Journal of Undergraduate Scholarship

Table of Contents:

• Introduction: Dr. Amorette Barber
• From the Editor: Dr. Larissa "Kat" Tracy
• From the Designers: Rachel English, Rachel Hanson
• Hungry Like the Wolf: The Wolf as Metaphor in Paramount Network’s Yellowstone: Ireland Seagle
• “Floating Cities”: Illustrating the Commercial and Conservation Conflict of Alaskan Cruise Ship Tourism: Dalton C. Whitby
• What Can You Do When Your Genes are the Enemy? Current Applications of Gene Manipulation and the Associated Ethical Considerations: Cassandra Poole
• La doble cara: un tema romántico en las obras de Larra y Hawthorne: Rachel Cannon
• Resolving a Conflict: How to …

Interpretable Learning In Multivariate Big Data Analysis For Network Monitoring, José Camacho, Rasmus Bro, David Kotz

Dartmouth Scholarship

There is an increasing interest in the development of new data-driven models useful to assess the performance of communication networks. For many applications, like network monitoring and troubleshooting, a data model is of little use if it cannot be interpreted by a human operator. In this paper, we present an extension of the Multivariate Big Data Analysis (MBDA) methodology, a recently proposed interpretable data analysis tool. In this extension, we propose a solution to the automatic derivation of features, a cornerstone step for the application of MBDA when the amount of data is massive. The resulting network monitoring approach allows …

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Computer Organization And Assembly Language Embedded Firmware Overhaul, Elaine Yun Ru Chan

Honors Theses

The WMU Computer Organization and Assembly Language class has encountered some difficulties in the past several years regarding the procurement of required hardware and software for the curriculum. This has led to a number of challenges for students, including:

• Difficulty in obtaining the necessary hardware and software

• Inability to complete assignments and projects due to hardware or software failures

• Frustration and anxiety caused by the challenges of the course

To address these challenges, a new choice of embedded firmware was researched and developed. This firmware allows for more reliable flashing of the MSP430 Microcontroller and remains reliable on modern operating …

The Mceliece Cryptosystem As A Solution To The Post-Quantum Cryptographic Problem, Isaac Hanna

Liberty University Research Week

Undergraduate

Theoretical Proposal

From Point Estimates To Predictive Distributions In Machine Learning Models - A Statistical Importance Sampling Framework, Giuseppina Carannante

Theses and Dissertations

In this thesis, we leverage powerful statistical frameworks for optimal sequential estimation and tracking in non-linear and non-Gaussian dynamical models, which enjoy proven (asymptotic) optimality properties. Initially, we build upon our previous work, which employed first-order Taylor series approximation to propagate the first two predictive moments, to derive Bayesian encoder-decoder networks. This work introduced the notion of dense, pixel-level uncertainty map that is crucial in fields, such as autonomous vehicles and medical segmentation. We then extended the Bayesian framework to an ensembling scheme based on ensemble Kalman Filtering (EnKF). While EnKF represents the predictive distribution with an ensemble of draws, …

Haptic Systems: Trends And Lessons Learned For Haptics In Spacesuits, Mohammad Amin Kuhail, Jose Berengueres, Fatma Taher, Mariam Alkuwaiti, Sana Z. Khan

All Works

Haptic technology uses forces, vibrations, and movements to simulate a sense of touch. In the context of spacesuits, proposals to use haptic systems are scant despite evidence of their efficacy in other domains. Existing review studies have sought to summarize existing haptic system applications. Despite their contributions to the body of knowledge, existing studies have not assessed the applicability of existing haptic systems in spacesuit design to meet contemporary challenges. This study asks, “What can we learn from existing haptic technologies to create spacesuits?”. As such, we examine academic and commercial haptic systems to address this issue and draw insights …

Designing An Equity-Centered Framework And Crosswalk For Integrated Elementary Computer Science Curriculum And Instruction, Carla Strickland, Andrea Ramírez-Salgado, Lauren Weisberg, Latoya Chandler, Jeanne Di Domenico, Elizabeth M. Lehman, Maya Israel

Journal of Computer Science Integration

As computer science (CS) education becomes more prevalent in K-12 instruction, it is critical for educators, researchers, and curriculum developers to identify culturally responsive and pedagogically inclusive approaches that can increase participation, access, and feelings of belonging for students from historically marginalized communities. In response, we developed an equity-centered curricular framework and illustrative crosswalk that synchronizes three distinct pedagogical approaches: culturally responsive pedagogy (CRP), Universal Design for Learning (UDL), and project-based learning (PBL). We describe the framework’s theoretical underpinnings and explain how this framework informed the development of an integrated elementary science+CS curricular unit and provide examples of its implementation. …

Essays On Cybersecurity And Information Privacy, Moez Hamedani Farokhnia

USF Tampa Graduate Theses and Dissertations

This dissertation research focuses on two key aspects of cybersecurity research. Security safeguard allocation, and AI-powered tools for anomaly detection. The first dissertation essay (Chapter 1) proposes a novel framework for the allocation of security countermeasures in the presence of uncertainty using robust optimization technique. The second dissertation essay (Chapter 2) studies the impact of algorithmic bias on the practice of insider threat detection in Electronic Health Record Systems and proposes a mitigations strategy. The final dissertation essay (Chapter 3) investigates how the biases of anomaly detection algorithms, and the characteristics of ensemble methods relate to the ensembles’ accuracy and …

Assessing The Impact Of A Csforall Research-Practice Partnership Using The Prosper Framework: A Case Study Of The Chicago Alliance For Equity In Computer Science (Cafécs), Erin Henrick, Steven Mcgee, Ronald I. Greenberg, Dale Reed, Don Yanek, Lucia Dettori, Haley Williamson

Computer Science: Faculty Publications and Other Works

The Chicago Alliance for Equity in Computer Science (CAFÉCS) Research Practice Partnership (RPP) has been working for more than a decade towards their mission to engage in research and development that enables Chicago Public Schools (CPS) to ensure that all students in Chicago participate in engaging, relevant, and rigorous computing experiences, increase opportunities for all students to pursue computing pathways and prepare all students for the future of work. The partnership engaged in an iterative design process to develop a framework for understanding the areas of RPP impact on a district. This paper applies the PROSPER framework to the CAFÉCS …

Role Of Ai In Threat Detection And Zero-Day Attacks, Kelly Morgan

Cybersecurity Undergraduate Research Showcase

Cybercrime and attack methods have been steadily increasing since the 2019 pandemic. In the years following 2019, the number of victims and attacks per hour rapidly increased as businesses and organizations transitioned to digital environments for business continuity amidst lockdowns. In most scenarios cybercriminals continued to use conventional attack methods and known vulnerabilities that would cause minimal damage to an organization with a robust cyber security posture. However, zero-day exploits have skyrocketed across all industries with an increasingly growing technological landscape encompassing internet of things (IoT), cloud hosting, and more advanced mobile technologies. Reports by Mandiant Threat Intelligence (2022) concluded …

Cybersecurity Workforce Development In Nigeria: Transforming The Cybercrime Gangs Into Cybersecurity Specialists, Olohi Favor Anteyi

Cybersecurity Undergraduate Research Showcase

This paper addresses the issue of cybercrime in Nigeria and the possibility of creating a cybersecurity workforce development program for cyber criminals to develop their skills for the cybersecurity profession, which may facilitate Nigeria’s economic development.

Patient-Handling Tasks And Posture Classification With Machine Learning, Haniah Kring, Annie Ngoc Tran, Elsa Brillinger, Aine Snoap, Noah Bradford

22nd Annual Celebration of Undergraduate Research and Creative Activity (2023)

A 2016 survey indicated that 39% of registered nursing respondents had reported musculoskeletal injuries after two years of regularly performing patient-handling tasks. Optical marker systems (considered the gold standard) can be used in laboratory settings to explore mechanisms of injury during patient-handling tasks, but deploying inertial measuring units (IMUs) in biomechanics allows data collection in both laboratory and clinical environments. IMU-based capture systems are also preferable to optical marker systems because they avoid marker occlusion during more complicated patient-handling tasks. The aims of our study are (1) to identify machine learning models that can accurately predict patient-handling tasks performed and …

Unveiling The Dark Web And The Impact Of Revil's Cyberattacks, Tanya Sasnouskaya

Cybersecurity Undergraduate Research Showcase

The United States Navy originally created the Dark Web for intelligence purposes, but it was later promoted by Western countries as a tool for safeguarding privacy and anonymity. Currently, the Dark Web serves as a platform for deliberate information leaks by nations that want to keep certain information out of the mainstream media. This paper provides an overview of the dark web and the browser used to access it. It covers the layers of the internet and highlights REvil ransomware and some of its technical details. By understanding these risks, users can take appropriate preventive measures to protect themselves from …

Experimental Study: Deep Learning-Based Fall Monitoring Among Older Adults With Skin-Wearable Electronics, Yongkuk Lee, Suresh Pokharel, Asra Al Muslim, Dukka Kc, Kyoung Hag Lee, Woon Hong Yeo

Michigan Tech Publications, Part 1

Older adults are more vulnerable to falling due to normal changes due to aging, and their falls are a serious medical risk with high healthcare and societal costs. However, there is a lack of automatic fall detection systems for older adults. This paper reports (1) a wireless, flexible, skin-wearable electronic device for both accurate motion sensing and user comfort, and (2) a deep learning-based classification algorithm for reliable fall detection of older adults. The cost-effective skin-wearable motion monitoring device is designed and fabricated using thin copper films. It includes a six-axis motion sensor and is directly laminated on the skin …