Physical Sciences and Mathematics Commons^™

Advancing Endovascular Neurosurgery Training With Extended Reality: Opportunities And Obstacles For The Next Decade, Shray Patel, Michael Covell, Saarang Patel, Sandeep Kandregula, Sai Krishna Palepu, Avi Gajjar, Oleg Shekhtman, Georgios Sioutas, Ali Dhanaliwala, Terence Gade, Jan-Karl Burkhardt, Visish Srinivasan

SKMC Student Presentations and Publications

Background: Extended reality (XR) includes augmented reality (AR), virtual reality (VR), and mixed reality (MR). Endovascular neurosurgery is uniquely positioned to benefit from XR due to the complexity of cerebrovascular imaging. Given the different XR modalities available, as well as unclear clinical utility and technical capabilities, we clarify opportunities and obstacles for XR in training vascular neurosurgeons. Methods: A systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was conducted. Studies were critically appraised using ROBINS-I. Results: 19 studies were identified. 13 studies used VR, while 3 studies used MR, and 3 studies used AR. …

Module: Ai And Value-Neutrality, Jonathan Auyer Ph.D., Department Of Philosophy

Artificial Intelligence, 2024-25

Artificial Intelligence is on the tips of everyone’s tongues these days – What exactly is it? What will can it be used for? What will it be used for in the future? What problems will it create or solve or exacerbate? This learning module aims to look at a specific facet of AI — the issue of value-neutrality — by having students look inward at capabilities necessary for human flourishing and then ask whether AI can cultivate (or inhibit) those capabilities. This will lead to a discussion of what values underlie AI and what this says about whether or not …

Creating A Business In 50 Minutes With Ai, Mark A. Rider Vanarsdale Chair In Entrepreneurship, School Of Business

Artificial Intelligence, 2024-25

This lesson plan explores using artificial intelligence (AI) to enhance the process of business idea generation and validation. Over a dynamic 50-minute workshop, students will engage with AI tools, particularly Microsoft's Copilot, to develop viable business concepts aligned with their personal interests and market needs.

The session begins with the Ikigai exercise, guiding students to identify their passions, strengths, and potential economic opportunities. Following this, students will use AI to engage in divergent thinking, generating a wide range of business ideas and refining them through iterative prompts until they find promising concepts.

In the validation phase, students will employ AI …

Chatgpt Can Write My Class Assignments, Right?: A Guided Classroom Activity For Teaching The Strengths And Weaknesses Of Generative-Ai Tools, Dr. Peter J. Kalenda Assistant Professor, Elementary Science & Math, School Of Education

Artificial Intelligence, 2024-25

This module is designed to support your undergraduate or graduate students with developing an understanding of:

• How to use generative-AI tools, like ChatGPT,
• The strengths and weaknesses of generative-AI tools for completing different tasks,
• How to design and revise a classroom presentation that is aligned with course topics and objectives by using generative-AI tools as a resource, and
• How to engage in prompt engineering and prompt revision for generative-AI tools.

Your students are being tasked with creating an engaging presentation they will deliver to their peers that aligns with the topics and learning objectives of your course. However, they will …

Ai And Academic Integrity, Max Sparkman Research Instruction Librarian, Milne Library, Brandon West Head Of Research & Instruction, Milne Library

Artificial Intelligence, 2024-25

This short module introduces students to important concepts regarding the use of AI and academic integrity. Concepts covered include a brief overview of generative AI, whether or not their use is considered plagiarism, how to use generative AI tools responsibly, and potential use cases. The module ends with a quiz where students can apply concepts from the module to three scenarios.

Psychology And The Digital Everywhere: Artificial Intelligence, Cassie Van Stolk Assistant Professor Of Psychology, Department Of Psychology

Artificial Intelligence, 2024-25

This module within the PSYC 390: Psychology and the Digital Everywhere course investigates the the implications of AI on human experiences using a biopsychosocial lens. Topics covered include an exploration of AI as a tool versus as an autonomous mind, ethical considerations of AI usage, and the promises and pitfalls of AI as a tool within the field of psychology. This module aligns with the "Contemporary Global Challenges, Creativity and Innovation" Participation in a Global Society outcome within the Geneseo GLOBE Curriculum.

Using Ai In Higher Ed: Is It Cheating?, David Levy Associate Professor & Chair Of Philosophy

Artificial Intelligence, 2024-25

Students generate a course-based or college-wide policy regarding the use of Generative AI, based on assigned readings, discussion, practice using the tools on writing assignments.

As Soon As [A]I Speak[S], Lytton Smith Professor Of Poetry, Department Of English

Artificial Intelligence, 2024-25

This guide facilitates the delivery of a two-workshop sequence allowing students to understand how an Artificial Intelligence (AI) Large Language Model (LLM) composes poetry, and to use that knowledge to compose their own poem for optional display in both electronic and physical form. Students may participate in either/both workshops, and in each will engage in reflective work to understand how AI impacts them and vice versa. This guide and curriculum aligns with the "Contemporary Global Challenges, Creativity and Innovation" Participation in a Global Society outcome within the Geneseo GLOBE Curriculum.

The Basic Dualism In The World: Object-Oriented Ontology And Systems Theory, Martin Zwick

Systems Science Faculty Publications and Presentations

Graham Harman writes that the “basic dualism in the world lies…between things in their intimate reality and things as confronted by other things.” However, dualism implies irreconcilable difference; what Harman points to is better expressed as a dyad, where the two components imply one another and interact. This article shows that systems theory has long asserted the fundamental character of Harman’s dyad, expressing it as the union of internal structure and external function, which correspond exactly to what Levi Bryant, characterizing Harman’s views, refers to as the intra-ontic and the inter-ontic, respectively. After interpreting Harman’s dyad in terms of the …

Understanding Protein Deep Learning Models Through Explainability, Zahra Fazel

Electronic Thesis and Dissertation Repository

This thesis investigates the application of Explainable Artificial Intelligence (XAI) techniques to deep learning models in the field of protein analysis, specifically targeting protein language models and protein interaction site prediction models. Despite the increasing adoption of these sophisticated deep learning models in bioinformatics, their intrinsic complexity often results in a black-box nature, obscuring the understanding of their decision-making processes.

This research represents a thorough effort to integrate explanation methods within this context. We analyze the resulting interpretations using biological-specific statistical tests to enhance the transparency and interpretability of the models. This work evaluates the efficacy of current XAI methods …

Molecular Docking, Pharmacological Profiling, And Molecular Dynamics Simulation Of Potential Antihyperuricemic Agent From Secondary Metabolites Of Dillenia Philippinensis Rolfe (Dilleniaceae), Louie Rince C. Suyo, John P. Paulin, Nicole Clarence Louise L. Gapaz, Markus Brent S. Arevalo, Vince Tyrell P. Yongco, Librado A. Santiago

Karbala International Journal of Modern Science

Crystal accumulation in the joints due to increased serum uric acid (sUA) may lead to an inflammatory condition called gout. Increased sUA is caused by the excessive reabsorption of the urate anion transporter-1 (URAT-1). Therefore, URAT-1 inhibition will promote uric acid excretion and reduce the risk of having gout. Dillenia philippinensis Rolfe, often known as katmon, is an endemic plant in the Philippines with bioactive compounds associated with several therapeutic benefits. The present study represents the first scientific inquiry into the antihyperuricemic potential of compounds isolated from D. philippinensis. This study aimed to assess the interaction of URAT-1 with …

Research And Practice Of Digital Institute And Its System Framework, Jianjun Yu, Yue Wang, Kongmin Wang, Zhuomin Shi

Bulletin of Chinese Academy of Sciences (Chinese Version)

In the era of the digital economy, digital scientific research and digital government are both crucial components, serving as application scenarios enabled by new information technologies. Currently, the new generation of information technologies, especially artificial intelligence and big data, is instrumental in modernizing governance at scientific research institutions within Chinese Academy of Sciences (CAS). They notably drive paradigm shifts in scientific activities and accelerate the digital transformation of these institutions. The digital system formed by the digital transformation of management processes in scientific activities at research institutes is defined as the digital institute. This study analyzes the impact of digital …

Developing Green Design, Leading Green And Low-Carbon Society, Yongxiang Lu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Green design refers to a design principle and method that comprehensively considers energy and resource conservation, emission reduction, and environmental impact during the product manufacturing and operation process in the product design stage. It strives to reduce greenhouse gas emissions throughout the entire product lifecycle. In the era of information networks, green design is supported by big data, AI network collaborative design, network detection and monitoring, etc. It involves selecting energy-saving processes, green and low-carbon materials, and optimizing product geometry design and surface treatment to achieve efficient resource utilization and minimize waste. For example, selecting environmentally friendly materials through networked …

Challenges And Recommendations For Building Open Source Innovation Ecosystem For Large-Models In China, Xin Wen, Chao Zhang, Rui Guo, Kaihua Chen, Ze Feng, Qigang Zhu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Addressing the current technological development issues that constrain the development of China’s large-scale model industry is needed to promote the continuous prosperity and development of the industry and enhance its international competitiveness. The study analyzes the significance of the open-source innovation ecosystem for the development of large-scale models in China. Based on reviewing the international experience of constructing the open-source innovation ecosystem, it further dissects the problems and challenges faced by the construction of the open-source innovation ecosystem for large-scale models in China and puts forward targeted suggestions. The study finds that the open-source innovation ecosystem for large-scale models in …

Research And Implications Of The Us Clean Energy Strategy, Lanchun Li, Qing Liu, Wei Chen, Yun Tang, Jun Chen

Bulletin of Chinese Academy of Sciences (Chinese Version)

As the world enters a new period of carbon neutrality, the US government is actively building a clean energy innovation ecosystem through both internal and external measures. Systematically tracking and in-depth analysis of the intent, structure, approach, and other characteristics of the new phase of the US clean energy strategy is of practical significance to Chinese energy revolution. The US focuses on the strategic objectives of science and technology innovation, energy security, and infrastructure, and has constructed an innovation ecology characterized by technology lists, planning blueprints, full-chain research, and innovative subjects from the perspective of whole-government coordination, cross-institutional decision-making, deep …

Technology Governance And Governance Technology: From Perspective Of Regulatory Research On Blockchain Digital Assets, Yikai Wu, Guoan Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

The Outline of the 14th Five-Year Plan takes blockchain as one of the key industries of the digital economy, and a number of ministries and commissions have also made clear deployments to accelerate the innovative application of blockchain, promote the digital transformation of the industry, and promote the high-quality development of the economy and society in the policy documents related to the informatization of the industry. The regulation and governance of blockchain digital assets cannot be separated from the understanding and analysis of blockchain technology itself, and observing the development mechanism of blockchain digital assets from the scientific and technological …

Challenges And Practices Of Deep Learning Model Reengineering: A Case Study On Computer Vision, Wenxin Jiang, Vishnu Banna, Naveen Vivek, Abhinav Goel, Nicholas Synovic, George K. Thiruvathukal, James C. Davis

Computer Science: Faculty Publications and Other Works

Many engineering organizations are reimplementing and extending deep neural networks from the research community. We describe this process as deep learning model reengineering. Deep learning model reengineering — reusing, replicating, adapting, and enhancing state-of-the-art deep learning approaches — is challenging for reasons including under-documented reference models, changing requirements, and the cost of implementation and testing.

Predictive Filtering-Based Image Inpainting, Xiaoguang Li

Theses and Dissertations

Image inpainting is an important challenge in the computer vision field. The primary goal of image inpainting is to fill in the missing parts of an image. This technique has many real-life uses including fixing old photographs and restoring ancient artworks, e.g., the degraded Dunhuang frescoes. Moreover, image inpainting is also helpful in image editing. It has the capability to eliminate unwanted objects from images while maintaining a natural and realistic appearance, e.g., removing watermarks and subtitles. Disregarding the fact that image inpainting expects the restored result to be identical to the original clean one, existing deep generative inpainting methods …

Transforming Computer Science Pedagogy: An Exploration Of Self-Recorded Videos (Srv) As A Teaching And Evaluation Tool, Hussam Ghunaim

Computer Science Faculty Publications

This study aims to introduce Self-Recorded Videos (SRV) as a novel method to help improve students’ performance in coding assignments in computer science courses. To our best knowledge, this is the first time the SRV method is applied in the context of computer science classes. The study was conducted with a sample size of 41 students who were registered in the online CSCI 331 Operating Systems course at Fort Hays State University. These students were given specific instructions to create Self-Recorded Videos SRVs for every coding assignment they were tasked with. This approach was designed to encourage students to engage …

Object Classification, Detection And Tracking In Challenging Underwater Environment, Md Modasshir

Theses and Dissertations

The main contributions of this thesis is the applicability and architectural designs of deep learning algorithms in underwater imagery. In recent times, deep learning techniques for object classification and detection have achieved exceptional levels of accuracy that surpass human capabilities. However, the effectiveness of these techniques in underwater environments has not been thoroughly researched. This thesis delves into various research areas related to underwater environments, such as object classification, detection, semantic segmentation, pose regression, and semi-supervised retraining of detection models.

The first part of the thesis studies image classification and detection. Image classification is a fundamental process that involves assigning …

Interventional Radiology's Exploration Into Artificial Intelligence, Raymond Nguyen

Master's Projects and Capstones

Background: Artificial intelligence (AI) has become more prominent in our daily lives in recent years. This includes various aspects of healthcare. Interventional radiology (IR) is one of these specialties that has taken strides in understanding how AI can be leveraged for patient care. This literature review aims to understand what areas will be most impacted by AI in IR and how it will influence both the patient and interventional radiologist.

Methods: Twenty-six publications from 2019-2024 were selected from PubMed and Scopus. Publications were sourced through a combination of keywords, subject headings (MeSH terms), and citation searching.

Results: This literature review …

Automated Data-Flow Optimization For Digital Signal Processors, Madushan Thilina Abeysinghe

Theses and Dissertations

Digital signal processors (DSP), which are characterized by statically-scheduled Very-Long Instruction Word architectures and software-defined scratchpad memory, are currently the go-to processor type for low-power embedded vision systems, as exemplified by the DSP processors integrated into systems-on-chips from NVIDIA, Samsung, Qualcomm, Apple, and Texas Instruments. DSPs achieve performance by statically scheduling workloads, both in terms of data movement and instructions. We developed a method for scheduling buffer transactions across a data flow graph using data-driven performance models, yielding a 25% average reduction in execution time and a reduction of up to 85% DRAM utilization for randomly-generated data flow graphs. We …

Human-Human Vs Human-Ai Therapy: An Empirical Study, Mohammad Amin Kuhail, Nazik Alturki, Justin Thomas, Amal K. Alkhalifa, Amal Alshardan

All Works

In many nations, demand for mental health services currently outstrips supply, especially in the area of talk-based psychological interventions. Within this context, chatbots (software applications designed to simulate conversations with human users) are increasingly explored as potential adjuncts to traditional mental healthcare service delivery with a view to improving accessibility and reducing waiting times. However, the effectiveness and acceptability of such chatbots remains under-researched. This study evaluates mental health professionals’ perceptions of Pi, a relational Artificial Intelligence (AI) chatbot, in the early stages of the psychotherapeutic process (problem exploration). We asked 63 therapists to assess therapy transcripts between a human …

Scene Text Detection And Recognition Via Discriminative Representation, Liang Zhao

Theses and Dissertations

Scene texts refer to arbitrary text presented in an image captured by a camera in the real world. The tasks of scene text detection and recognition from complex images play a crucial role in computer vision, with potential applications in scene understanding, information retrieval, robotics, autonomous driving, etc. Despite the notable progress made by existing deep-learning methods, achieving accurate text detection and recognition remains challenging for robust real-world applications. The challenges in scene text detection and recognition stem from: 1) diverse text shapes, fonts, colors, styles, layouts, etc.; 2) countless combinations of characters with unfixed attributes for complete detection, coupled …

On Parallelization Of Graph Algorithms, Performance Modelling And Autonomous 3d Printable Object Synthesis, Shams-Ul-Haq Syed

Theses and Dissertations

The degree of hardware level parallelism offered by today’s GPU architecture makes it ideal for problem domains with massive inherent parallelism potential, fields such as computer vision, image processing, graph theory and graph computations. We have identified three problem areas for purpose of this research dissertation, under the umbrella of performance improvement by harnessing the power of GPUs for novel applications. The first area is concerned with k-vertex connectivity in graph theory, the second area deals performance evaluation using extended roofline models for GPU parallel applications and finally the third problem area is related to synthesis 3D printable objects from …

Approximation Algorithms For High Multiplicity Strip Packing, Thief Orienteering, And K-Median, Andrew Bloch-Hansen

Electronic Thesis and Dissertation Repository

This thesis investigates three research objectives on three different problems: (1) algorithm design for problems in which the input can be grouped into a small number of classes, demonstrated on the high multiplicity strip packing problem; (2) algorithm design for problems with multiple interdependent sub-problems, demonstrated on the thief orienteering problem; and (3) algorithm design using neural networks with few layers, demonstrated on the k-median problem.

(1) The two-dimensional strip packing problem consists of packing in a rectangular strip of width $1$ and minimum height a set of $n$ rectangles, where each rectangle has width $0 < w \leq 1$ and height $0 < h \leq h_{max}$. We consider the high-multiplicity version of the problem in which there are only $K$ different types of rectangles. For the case when $K = 3$, we give an algorithm that produces solutions requiring at most height $\frac{3}{2}h_{max} + \epsilon$ plus the height of an optimal solution, where $\epsilon$ is any positive constant. For the case when $K = 4$, we give an algorithm yielding solutions of height at most $\frac{7}{3}h_{max} + \epsilon$ plus the height of an optimal solution. For the case when $K > 3$, we give an …

Groundwater Modeling Of The Ogallala Aquifer: Use Of Machine Learning For Model Parameterization And Sustainability Assessment, Tewodros Aboret Tilahun

Dissertations and Doctoral Documents from University of Nebraska-Lincoln, 2023–

Addressing groundwater depletion problems in heterogeneous aquifer systems is a challenge. The heterogeneous Ogallala Aquifer, a critical source of groundwater in the central United States, has undergone decades of decline in water levels due to pumping. This project aims to build a robust groundwater model to evaluate optimal scenarios for sustainable use of the groundwater resource within a section of the Ogallala aquifer located in the Middle Republican Natural Resources District (MRNRD). This study follows a comprehensive approach involving parameterization, construction, and optimization. The model is parametrized using hydraulic conductivity and recharge values obtained from a random forest-based machine learning …

Open-Source Forensics Tools Are Great Tools For Critical Used Machines, Erik Herrera

Electronic Theses and Dissertations

Open-Source software exists on everything from operating systems to daily productivity applications. In digital forensics, a very popular tool that is used to learn on and expand is Autopsy. Autopsy is known in the digital world due to its potential and wide usage. It is in many built packages of software inside the open-source world of applications. It is built into premade operating systems that are involved in Digital Forensics and Penetration Testing. Prebuilt OS includes Kali Linux and Computer Aided Investigative Environment (CAINE).

In the application to defend Open-Source software being just as good as closed-source software, I will …

Ethical Challenges And Solutions Of Generative Ai: An Interdisciplinary Perspective, Inseiw@Gmail.Com, Al-Kfairy, Mousa (Zayed University; College Of Technological Innovation, Zayed University, Abu Dhabi P.O. Box 144534, United Arab Emirates;, Inseiw@Gmail.Com, Omar.Alfandi@Zu.Ac.Ae, ;, Omar.Alfandi@Zu.Ac.Ae

All Works

This paper conducts a systematic review and interdisciplinary analysis of the ethical challenges of generative AI technologies (N = 37), highlighting significant concerns such as privacy, data protection, copyright infringement, misinformation, biases, and societal inequalities. The ability of generative AI to produce convincing deepfakes and synthetic media, which threaten the foundations of truth, trust, and democratic values, exacerbates these problems. The paper combines perspectives from various disciplines, including education, media, and healthcare, underscoring the need for AI systems that promote equity and do not perpetuate social inequalities. It advocates for a proactive approach to the ethical development of AI, emphasizing …

Ai-Based Methods For Detecting And Classifying Age-Related Macular Degeneration: A Comprehensive Review, Niveen Nasr El-Den, Mohamed Elsharkawy, Ibrahim Saleh, Mohammed Ghazal, Ashraf Khalil, Mohammad Z. Haq, Ashraf Sewelam, Hani Mahdi, Ayman El-Baz

All Works

This paper explores the advancements and achievements of artificial intelligence (AI) in computer vision (CV), particularly in the context of diagnosing and grading age-related macular degeneration (AMD), one of the most common leading causes of blindness and low vision that impact millions of patients globally. Integrating AI in biomedical engineering and healthcare has significantly enhanced the understanding and development of the CV application to mimic human problem-solving abilities. By leveraging AI-based models, ophthalmologists can improve the accuracy and speed of disease diagnosis, enabling early treatment and mitigating the severity of the conditions. This paper presents a comprehensive analysis of many …