Computer Sciences Commons^™

Board 326: K-12 Teachers And Data Science: Learning Interdiscplinary Science Through Research Experiences, Katherine G. Herbert-Berger, Thomas J. Marlowe, Vaibhav Anu, Stefan A. Robila

School of Computing Faculty Scholarship and Creative Works

Data science is now pervasive across STEM, and early exposure and education in its basics will be important for the future workforce, academic programs, and scholarly research in engineering, technology, and the formal and natural sciences, and in fact, across the full spectrum of disciplines. When combined with an emphasis on soft skills and an interdisciplinary focus, such educational experiences have deeper and more meaningful effects. Our Montclair State University NSF Research Experience for Teachers (RET) grant (NSF Award Number: #2206885, IRB Number: 22-23-3003) exposed teachers to a program integrating solar weather, data science, computer science and artificial intelligence, and …

A Robust Data-Driven Framework For Artificial Intelligent Systems, Quoc H. Nguyen

USF Tampa Graduate Theses and Dissertations

Artificial Intelligence (AI) systems have demonstrated remarkable performance across various domains. However, their robustness remains a critical concern, particularly in terms of data and model reliability. This dissertation aims to address the challenges associated with building robust AI systems by focusing on two key aspects: data robustness and model robustness. Data robustness poses significant challenges, including data shift, concept shifting, limited and imbalanced datasets, and interoperability issues in IoT systems for data collection. Existing methods fall short in handling dynamic business objectives and evolving data landscapes effectively. To bridge these gaps, we propose an IoT framework that ensures interoperability, seamless …

Creative Insights Into Motion: Enhancing Human Activity Understanding With 3d Data Visualization And Annotation, Isaac Browen, Hector M. Camarillo-Abad, Franceli L. Cibrian, Trudi Di Qi

Engineering Faculty Articles and Research

This paper presents a novel 3D system for human motion analysis - Motion Data Visualization and Annotation (MoViAn). Designed to provide a comprehensive visual representation of 3D human motion data, MoViAn incorporates detailed visualization of gaze direction, hand movements, and object interactions, alongside an interactive interface for efficient data annotation. A user study involving eight participants indicates that MoViAn enables users to thoroughly explore and annotate human motion data, with System Usability Scale (SUS) results demonstrating a satisfactory usability level. The contribution of this paper lies in the development of an interactive and usable data analytics tool aimed at deepening …

Modified (N + 1) D Laplacian For Smooth Pressure Reconstruction Based On Time-Resolved Velocimetry (1): Analysis And Numerics, Junrong Zhang, Nazmus Sakib, Zhao Pan

Electrical and Computer Engineering Student Research

We analyze a smooth pressure solver based on the ‘modified Poisson equation’: ∇²p + ξ² ∂²p/∂t² = f(u(t)), where p is the pressure field, u(t) is the velocity field measured by time-resolved image velocimetry, and ξ² is a tunable parameter to control the solver’s diffusive behaviour in time. This modified Poisson equation aims at obtaining smooth pressure fields from potentially noisy image velocimetry measurements, and is a part of the current four-dimensional (4D) pressure solver (implemented in, for example, DaVis 10.2) by LaVision. This work focuses on investigating three aspects …

Anonymized Identity Recognition And Classification Using Privacy Preserving Facial Encoding, Manas Sanjay Pakalapati

USF Tampa Graduate Theses and Dissertations

The need for sharing large-scale datasets to train deep neural network models, particularly in healthcare, raises significant data security and privacy concerns. To address these issues, methods such as data encryption or encoding are utilized. These techniques can encrypt the data and make it unreadable to humans, while still retaining its usefulness for training models.

In this study, we investigate various image encoding techniques designed to protect privacy by making images unrecognizable while still retaining their usefulness for model training. Our investigation utilized publicly available facial databases and focused on evaluating the trade-offs inherent in image encoding techniques, with a …

A Simple Mobile Plausibly Deniable System Using Image Steganography And Secure Hardware, Lichen Xia, Jinghui Liao, Niusen Chen, Bo Chen, Weisong Shi

Michigan Tech Publications

Traditional encryption methods cannot defend against coercive attacks in which the adversary captures both the user and the possessed computing device, and forces the user to disclose the decryption keys. Plausibly deniable encryption (PDE) has been designed to defend against this strong coercive attacker. At its core, PDE allows the victim to plausibly deny the very existence of hidden sensitive data and the corresponding decryption keys upon being coerced. Designing an efficient PDE system for a mobile platform, however, is challenging due to various design constraints bound to the mobile systems. Leveraging image steganography and the built-in hardware security feature …

An Empirical Study On Detecting And Explaining Global Structural Change In Evolving Graph Using Martingale, Tarun Teja Kairamkonda

Theses and Dissertations

There is a growing interest in practical applications involving networks of interacting entities such as sensor networks, social networks, urban traffic networks, and power grids, all of which can be represented using evolving graphs. Changes in these evolving graphs can signify shifts in the behavior of interacting entities or alterations in the patterns of their interactions. Identifying and detecting these changes is crucial for addressing potential challenges or opportunities in various domains. In this study, we propose an approach for detecting structure change in evolving graphs based on the martingale change detection framework on multiple graph features extracted over time. …

Making Proteomics Accessible: Rokaixplorer For Interactive Analysis Of Phospho-Proteomic Data, Serhan Yılmaz, Filipa Blasco Tavares Pereira Lopes, Daniela Schlatzer, Marzieh Ayati, Mark R. Chance, Mehmet Koyutürk

Computer Science Faculty Publications

We present RokaiXplorer, an intuitive web tool designed to address the scarcity of user-friendly solutions for proteomics and phospho-proteomics data analysis and visualization. RokaiXplorer streamlines data processing, analysis, and visualization through an interactive online interface, making it accessible to researchers without specialized training in proteomics or data science. With its comprehensive suite of modules, RokaiXplorer facilitates phospho-proteomic analysis at the level of phosphosites, proteins, kinases, biological processes, and pathways. The tool offers functionalities such as data normalization, statistical testing, activity inference, pathway enrichment, subgroup analysis, automated report generation, and multiple visualizations, including volcano plots, bar plots, heat maps, and network …

Integration Of Machine Learning In Structural Health Monitoring For Damage Identification And Response Prediction In Bridges, Naga Lakshmi Chittitalli Ravuri

Theses and Dissertations

Machine learning-based structural health monitoring (ML-SHM) plays a pivotal role in enhancing structural resilience. By recognizing potential hazards, implementing resistance measures, facilitating swift recovery, and continuously monitoring structural health, ML-SHM ensures proactive maintenance and minimizes recovery delays post-events. Leveraging machine learning algorithms and sensor data, ML-SHM enables early detection of anomalies, prediction of failures, and adaptive responses, enhancing the structure's ability to withstand and recover from adverse conditions. This integrated approach not only improves the structure's performance and adaptability but also contributes to overall safety and longevity. This thesis presents a comprehensive exploration of structural health monitoring (SHM) techniques for …

Accelerated Particle Swarm Optimization Algorithm For Efficient Cluster Head Selection In Wsn, Imtiaz Ahmad, Tariq Hussain, Babar Shah, Altaf Hussain, Iqtidar Ali, Farman Ali

All Works

Numerous wireless networks have emerged that can be used for short communication ranges where the infrastructure-based networks may fail because of their installation and cost. One of them is a sensor network with embedded sensors working as the primary nodes, termed Wireless Sensor Networks (WSNs), in which numerous sensors are connected to at least one Base Station (BS). These sensors gather information from the environment and transmit it to a BS or gathering location. WSNs have several challenges, including throughput, energy usage, and network lifetime concerns. Different strategies have been applied to get over these restrictions. Clustering may, therefore, be …

Digital Technologies Empower Innovative Development Governance Of The Yellow River Basin, Tara Qian Sun, Yingying Jia, Gaozuo Sun, Xixi Zhao, Rongping Mu

Bulletin of Chinese Academy of Sciences (Chinese Version)

The application of digital technologies is the core driving force for innovating traditional development and realizing a leap in productivity. The innovative development governance of the Yellow River Basin is a complex social system, involving economic, social, and ecological aspects. Its key driving force is the profound influence of digital technologies. Focused on how digital technologies empower the innovative development governance of the Yellow River Basin, the development process, problems, and challenges are analyzed at different stages, from the digital Yellow River to the digital twin Yellow River. It is found that the governance of the Yellow River Basin still …

Study On Data Mining Of Hydrogen Energy Policy In China Based On Natural Language Processing Technology, Dongling Huang, Yuan Liu, Xiaoshuai Yuan, Guozhong Jin, Yuanhang Cai, Li Liu, Heng Cao, Wanjun Li, Rui Cai

Bulletin of Chinese Academy of Sciences (Chinese Version)

Report to the 20th National Congress of the CPC emphasized the importance of “working actively and prudently towards the goals of reaching peak carbon emissions and carbon neutrality”, as well as “speeding up the planning and development of a system for new energy sources”. As a green and low-carbon secondary energy source, hydrogen energy has multiple applications in promoting the large-scale and efficient use of renewable energy as well as energy substitution in the field of transportation. It can also accelerate decarbonization in industry, and as such, is an indispensable part of building a new energy system, reaching peak carbon …

Do You Say Please Or Thank You To Chatgpt? The Subtle Influence Of Prompt Engineering On Digital Civility, Essraa Nawar

Library Articles and Research

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In the dynamic and rapidly evolving landscape of artificial intelligence, tools like ChatGPT have become integral to our daily digital interactions. These advanced AI systems assist us with a myriad of tasks, from generating text and answering complex questions to providing creative solutions. However, as we engage more frequently with these non-human entities, an intriguing question arises: Are we inadvertently becoming ruder in our digital communications, or are we consciously maintaining our ingrained habits of politeness?"

Large-Scale Research Infrastructure Empowers High-Quality Development Of Private Enterprises: Current Situation, Challenges, And Policy Recommendations, Lingling Zhang, Fuqiang Wang, Mingze Zhang, Zexia Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

Private enterprises have become an important source of innovation in China’s economic development. Large-scale research infrastructure, as a crucial strategic support and innovation element for breaking through key technologies, provides a platform for the innovative development of private enterprises. At present, some large-scale research infrastructures in China, such as the China Spallation Neutron Source and the Shanghai Synchrotron Radiation Facility, have begun actively exploring mechanisms to serve private enterprises. These efforts have helped a number of private companies overcome critical technological bottlenecks and achieve original innovations. Nevertheless, in the current process of opening up large-scale research infrastructures to private enterprises …

Context-Driven: Logic And Pathway Of Industrial Intelligence To Accelerate Development Of New Quality Productive Forces, Ximing Yin, Yaxin Su, Tailun Chen, Jin Chen, Jiang Yu

Bulletin of Chinese Academy of Sciences (Chinese Version)

The development of new productive forces hinges on industrial intelligence, which is driven by the deep integration of technological innovation and industrial innovation, and the accelerated construction of a modern industrial system. Industrial intelligence refers to the process of transforming traditional industrial development models and cultivating new pillar industries through the empowerment of intelligent technologies and data elements. It serves as a pivotal engine for promoting new industrialization and developing new productive forces. However, existing research has largely overlooked the critical theoretical and practical issues of how to leverage China’s ultra-large market and its vast contextual advantages to improve the …

Integration Of Digital And Real Economies To Shape New Advantages In Development: New Form Of Human-Cyber-Physical Ternary Fusion, Jiaofeng Pan, Jing Wu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Facing the accelerating of scientific and technological revolution and industrial transformation, expediting the deep integration of digital economy and real economy is a crucial pathway to enhance industrial competitiveness and address social development challenges. The integration of digital and real economies, with the linkage of human-cyber-physical ternary fusion, brings about an increase in production factors and a reduction in uncertainty. This integration permeates through the whole process and channels of the real economy, including R&D innovation, manufacturing, collaborative integration, and supply services, triggering systemic transformations in the real economy. Looking to the future, the deep connection of technology, data, and …

Building Engineering Ecology For Industrial Change In Digital Age, Zhengzhong Xu, Jian Chan

Bulletin of Chinese Academy of Sciences (Chinese Version)

In the digital civilization era, scientific and technological innovation has emerged as a crucial pathway to unleash new quality productive forces and spearhead the ascendancy of great powers. It has become a vital pillar for major nations to engage in international competition and reshape the global order. Furthermore, it acts as a key instrument to smooth out economic cycles and overcome the limitations imposed by these cycles. The rise model, marked by advanced scientific and technological innovation and a commitment to scientific self-sufficiency and enhancement, significantly boosts the viability and acceptance of China’s approach to international governance. At the same …

A Pathway For Digital Economy To Enable The Development Of Low-Carbon Transition Under “Technology-Organization-Environment” Framework, Wendong Wei, Yang Sun, Bei Liu, Hui Wang, Yong Geng

Bulletin of Chinese Academy of Sciences (Chinese Version)

The booming development of the digital economy has provided robust technical, management, and institutional means for the in-depth promotion of low-carbon transition. However, at present, there are still problems, such as the limited level of digital technological innovation, the insufficient supply of digital talents, and the urgent need for a sound digital governance system, which constrains the empowering effect of the digital economy on the development of China’s low-carbon transition. Based on the Technology-Organization-Environment (TOE) framework, this study discusses the technology iteration, management transform, and system optimization of the influence of digital economy on the development of low carbon transformation. …

Comparative Analysis And Insights Into R&D Mode Of Top Artificial Intelligence Companies In China And The Us, Xiyi Yang, Jia Jia, Xiaoyu Zhou, Shouyang Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Artificial intelligence (AI) is currently one of the most prominent fields in the technology industry, with China and the US being two global centers for AI research and development. However, the two countries differ in their development levels of the AI industry. In particular, the emergence of ChatGPT in 2022 has sparked extensive discussions regarding the capabilities and competitiveness of Chinese AI companies. This study analyzes over 120 000 AI invention patents approved in the past five years in both China and the US. Firstly, it constructs a multidimensional index based on AI patent features to identify the top 10 …

Fspde: A Full Stack Plausibly Deniable Encryption System For Mobile Devices, Jinghui Liao, Niusen Chen, Lichen Xia, Bo Chen, Weisong Shi

Michigan Tech Publications

In today’s digital landscape, the ubiquity of mobile devices underscores the urgent need for stringent security protocols in both data transmission and storage. Plausibly deniable encryption (PDE) stands out as a pivotal solution, particularly in jurisdictions marked by rigorous regulations or increased vulnerabilities of personal data. However, the existing PDE systems for mobile platforms have evident limitations. These include vulnerabilities to multi-snapshot attacks over RAM and flash memory, an undue dependence on non-secure operating systems, traceable PDE entry point, and a conspicuous PDE application prone to reverse engineering. To address these limitations, we have introduced FSPDE, the first Full-Stack mobile …

Reinforcement Learning For Robotic Tasks: Analyzing And Understanding The Learning Process Using Explainable Artificial Intelligence Methods, Brian J. Campana

Theses and Dissertations

As deep reinforcement learning (RL) models gain traction across more industries, there is a growing need for reliable agent-explanation techniques to understand these models. Researchers have developed explainable artificial intelligence (XAI) methods to help understand these 'black boxes'. While these models have been tested on many supervised learning tasks, there is a lack of examination of how these well these methods can explain hard reinforcement learning problems like robotic control. The sequential nature of learning RL policies and testing episodes create fundamentally different policies over time compared to more traditional supervised learning models. In this thesis, two important questions are …

Ct-To-Mri Synthesis For High-Dose-Rate Brachytherapy Treatment Planning, Rachel Nicole Gordon

Master's Theses

High-dose-rate (HDR) brachytherapy is a radiation treatment modality that places radioactive sources directly in cancerous regions. Radiation treatment planning for HDR prostate brachytherapy utilizes both CT and MRI to visualize the path of the radioactive source and the prostate gland, respectively. In this work, we propose GAN-CM, a method for conditional CT-to-MRI translation that is based on Generative Adversarial Networks (GANs). The proposed method uses the typical generator-discriminator design of GANs with a modified generator that incorporates semantic masks obtained from the domain image. The use of semantic masks allows GAN-CM to better capture the anatomical details and tissue characteristics …

Specification, Enforcement, And Measurement Of Integrity Policies, Kevin Dennis

USF Tampa Graduate Theses and Dissertations

The first step to improving an organization's security posture is to define the organization's security goals. At a technical level, these goals are expressed as security policies. Security policies are predicates over programs, that return true or false if the program adheres to the policy. Defining these policies correctly is thus essential to ensuring the overarching security goals are met, but it is often quite difficult to translate human-oriented goals into their technical policy counterparts. In addition, these policies must be specified so that they are enforceable while minimizing false positives and false negatives. Integrity policies, which specify how data …

Development Of Cyber Security Platform For Experiential Learning, Abhishek Vaish, Ravindra Kumar, Samo Bobek, Simona Sternad

Journal of Cybersecurity Education, Research and Practice

The cyber security education market has grown-up exponentially, with a CAGR of 13.9 % as reported by Data Intelo. The report published by the World Economic Fo- rum 2023 indicates a shortfall of 2.27 million cyber security experts in 2021 across different roles and hence manifest that Skill-based cyber security education is the need of the hour. Cybersecurity as a field has evolved as a multi-discipline, multi-stakeholder and multi-role discipline. Therefore, the need to address formal education with an outcome-based philosophy is imperative to address for a wider audience with varied past training in their formal education. With the Internet …

Liability For Use Of Artificial Intelligence In Medicine, Nicholson W. Price Ii, Sara Gerke, I. Glenn Cohen

Book Chapters

While artificial intelligence (AI) has substantial potential to improve medical practice, errors will certainly occur, sometimes resulting in injury. Who will be liable? Questions of liability for AI-related injury raise not only immediate concerns for potentially liable parties but also broader systemic questions about how AI will be developed and adopted. The landscape of liability is complex, involving healthcare providers and institutions and the developers of AI systems. In this chapter, we consider these three principal loci of liability. At the outset, we note a few issues that shape our analysis.

Scaling Expertise: A Note On Homophily In Online Discourse And Content Moderation, Dylan Weber

New England Journal of Public Policy

It is now empirically clear that the structure of online discourse tends toward homophily; users strongly prefer to interact with content and other users that are similar to them. I review the evidence for the ubiquity of homophily in discourse and highlight some of its worst effects including narrowed information landscape for users and increased spread of misinformation. I then discuss the current state of moderation frameworks at large social media platforms and how they are ill-equipped to deal with structural trends in discourse such as homophily. Finally, I sketch a moderation framework based on a principal of “scaling expertise” …

Mixed Uncertainty Analysis On Pumping By Peristaltic Hearts Using Dempster-Shafer Theory, Yanyan He, Nicholas A. Battista, Lindsay D. Waldrop

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

In this paper, we introduce the numerical strategy for mixed uncertainty propagation based on probability and Dempster–Shafer theories, and apply it to the computational model of peristalsis in a heart-pumping system. Specifically, the stochastic uncertainty in the system is represented with random variables while epistemic uncertainty is represented using non-probabilistic uncertain variables with belief functions. The mixed uncertainty is propagated through the system, resulting in the uncertainty in the chosen quantities of interest (QoI, such as flow volume, cost of transport and work). With the introduced numerical method, the uncertainty in the statistics of QoIs will be represented using belief …

Henna Chatbot Capstone Review, Kobe Norcross

University Honors Theses

This thesis reviews the development of the Henna Chatbot, an AI-powered DEI consultant designed to provide personalized feedback to organizations. Sponsored by DEI consultant Arsh Haque, the project aims to address gaps in current DEI software, which often lacks team-specific feedback. The Henna Chatbot leverages GPT-3.5 Turbo to create an affordable SaaS platform where organizations can train Henna with their DEI values, and Henna will help organizations stay aligned with those values. The project spanned twenty weeks and was completed by a team of eight computer science students at Portland State University. The development process followed Agile methodologies, emphasizing effective …

Trust, Transparency, And Transport: The Impact Of Privacy Protection On The Acceptance Of Last-Mile Drone Delivery, Jurgen Heinz Famula

Electronic Theses and Dissertations

A common set of problems commercial delivery companies face is finding ways to increase the efficiency and reliability of the “last mile” of a package’s journey, all while reducing operating costs. This need for efficiency has driven many companies to explore using unmanned aerial vehicles (UAVs), or drones, to get packages to their final destination. Although UAVs have great potential to help increase efficiency in commercial package delivery, this comes at a potential cost to the privacy of people who intersect the flight paths of these unmanned vehicles. This thesis explores the effect of a mobile phone application for commercial …

Bridging Design And Perception: Novel Tools And Technologies For Creating Effective Human-Robot Interactions, Benjamin Dossett

Electronic Theses and Dissertations

This thesis explores human perception of robots through the use of novel tools and technologies. First, the impact of Augmented Reality (AR) data presentation on human perception of robots is investigated. A study conducted with the AR human-robot teaming system found that robot performance significantly influenced participants’ perceptions, overshadowing the impact of matching or mismatching robot confidence feedback. Second, the DU Want to Build-A-Bot platform is presented, which enables participatory robot design and opens the door for novel research of how robot design affects human perception. The Build-A-Bot platform enables the collection of diverse robot designs, facilitating machine learning analysis …