Artificial Intelligence and Robotics Commons^™

Modeling And Verification Of Cooperative Vehicle Infrastructure System At Unsignalized Intersection Based On Time Automata, Wei Liu, Qirui Xiao, Xinhai Chen, Chang Rao, Yu Zhang, Bosi Wang

Journal of System Simulation

Abstract: Cooperative vehicle infrastructure system (CVIS) is one of the advanced solutions to enhance intersection vehicle passage safety. Due to the lack of clear specifications and standards regarding the dynamic timing and transition processes of system object state interaction in existing CVIS technologies, ensuring the safety of passage control logic is challenging. This study utilizes formal language to describe the functional logic of CVIS in unsignalized intersections, verifying the safety of system object state interaction and control logic to improve vehicle passage safety at unsignalized intersections. Simulations are conducted for scenarios including single-vehicle non-conflict, dual-vehicle conflict, and multi-vehicle conflict to …

Real-Time Non-Photorealistic Rendering Method For Black And White Comic Style In Games And Animation, Yan Hu, Lizhe Chen, Hanna Xie, Yuyao Ge, Shun Zhou, Xingquan Cai

Journal of System Simulation

Abstract: To address the issues of high resource consumption and lengthy workflow in general nonphotorealistic, this paper proposes a real-time non-photorealistic rendering method for black and white comic style in games and animation. A specialized lighting model is designed to highlight the main environmental light and the grayscale grading of diffuse reflection based on the analysis of the lighting model effect. The pre-processing of the scene is achieved by merging the various components of the lighting model. A screen space three-phase edge detection method is proposed to sequentially perform depth edge detection, normal edge detection, and color edge detection on …

Simulation System For Carrier-Based Aircraft Ammunition Support Scheduling, Zhe Liu, Jiafeng Chen, Junfei Ma, Songhua Ma

Journal of System Simulation

Abstract: For inefficient scheduling of carrier-based aircraft ammunition support on the flight deck of aircraft carriers, a Unity3D-based 3D virtual demonstration method for carrier-based aircraft ammunition scheduling is proposed, and a 3D virtual simulation system for carrier-based aircraft ammunition scheduling on the flight deck of aircraft carriers is constructed. A problem model targeted at carrierbased aircraft ammunition transportation and loading scheduling process as well as processing rules for path determination, sequence constraint, and loading position compensation are established based on the defining system. An optimal solution for the scheduling process is realized by using the improved discrete grey wolf optimizer …

Uav Path Planning Based On Improved Harris Hawk Algorithm And B-Spline Curve, Zhifeng Huang, Yuanhua Liu

Journal of System Simulation

Abstract: Aiming at the global path planning problem of unmanned aerial vehicles (UAVs) in dynamic environments, this paper proposes an improved Harris Hawk optimization algorithm. To address the problem of insufficient search performance in the later stage of the algorithm, an adaptive chaos and core population dynamic partitioning strategy is proposed to improve the searchability of the algorithm in the later stage. The Harris Hawk update formula is modified, and the golden sine strategy is introduced to improve the search efficiency of the algorithm. Then, an adaptive dynamic cloud optimal solution perturbation strategy is integrated to improve the ability of …

Optimal Scheduling Of Vehicle-Network Interaction Based On Interval Stackelberg Game Of Virtual Power Plant, Weiliang Liu, Qianwen Yan, Qiliang Zhang, Shuai Liu, Changliang Liu, Jiayao Kang, Xin Wang

Journal of System Simulation

Abstract: To better exploit the regulation potential of electric vehicles (EVs), resolve the conflicts of interest among the stakeholders in vehicle-to-grid (V2G) interactions, and overcome the uncertainty of distributed energy sources and load, this paper proposes a two-level optimization scheduling model for V2G interactions based on the interval Stackelberg game of a virtual power plant (VPP). The VPP aggregator is considered as the upper level, and the EV users as the lower level. The upper level model uses interval numbers to describe the uncertainty of sources and loads, with the aim of minimizing the operating cost of the VPP aggregator, …

Maglev Ball Control Algorithm Based On Levant Differentiator, Zhenli Zhang, Yongzhuan Wang, Yao Qin, Jie Yang

Journal of System Simulation

Abstract: To solve the problem of unsatisfactory control effect of permanent magnet electromagnetic hybrid suspension system caused by signal mutation and noise interference, the control method ILevant- PID, the combination of an improved Levant differentiator and PID, is proposed. The proposed method combines the strong adaptability of PID control and the robust characteristic of Levant differentiator on input noise to solve the chattering problem of the system output. The simulated anneal-particle swarm optimization is utilized to solve the constraints of the ILevant-PID controller, such as multiple parameters and strong correlation. The simulation results show that compared with the traditional PID …

Real-Time Scheduling Method For Dynamic Flexible Job Shop Scheduling, Quan Jiang, Jingxuan Wei

Journal of System Simulation

Abstract: A multi-objective dynamic flexible job shop scheduling problem model with machine breakdown and random jobs arrival is constructed to address the interference of dynamic events in manufacturing processing on the scheduling scheme, and a real-time scheduling method with multiobjective proximal policy optimization (MPPO) algorithm is proposed. The MPPO algorithm trains two agents, routing agent (RA) and sequencing agent (SA), for real-time scheduling and real-time processing of dynamic events. It employs a linear combination of weight vectors and reward vectors as reward signals and stores the agents' parameters for each weight vector to optimize multiple objectives. The required state information, …

Path Planning For Mobile Robot Based On Angle Search, Yaru Wang, Dexin Yao, Zengli Liu, Yi Peng

Journal of System Simulation

Abstract: The angle search algorithm for angle-controlled robots is proposed to increase the path search speed and optimize the path length. The algorithm effectively finds a path in static surroundings by performing an efficient search in a specific dimensional range based on the position of the robot and the target point. Firstly, search angles are predetermined according to the characteristics of the environment in the grid map. Then, the estimated angle of the robot's surrounding grid is computed. Finally, a new extension point is chosen by comparing the estimated angle to the search angle, demonstrating the usefulness and viability of …

Digital Application Of Equipment System Test And Evaluation Based On Digital Twin And Parallel Experiment Theory, Hongjie Dang, Wenguang Yu, Huahui Yang

Journal of System Simulation

Abstract: With the development of equipment systematization, traditional test with real equipment can not meet the requirements of Test and Evaluation(T&E), especially for complex equipment. As the main digital methods in current, digital twins and parallel experiments can support the digital application in the field of equipment Test and Evaluation. This paper makes a comparative analysis of the two digital technology means, extracts their technical connotation and characteristics, and then integrates them to explore the application mode, application time and application occasions in the field of equipment T&E. Taking the satellite for example, by constructing the digital architecture of equipment …

Interaction Between Virus Transmission Variation And Population Crossover Activity And Diffusion Model, Lei Yu, Xichou Zhu, Huaming Liao, Jiafeng Guo, Xueqi Cheng

Journal of System Simulation

Abstract: In view of the current high incidence of human-to-human infectious viruses, a multi-agent simulation and deduction model was proposed and designed based on the random characteristics of virus transmission variation and the influence of population crossover activity. The external pathogenicity and infectious characteristics of the virus and the external activities and immune characteristics of the human were quantified, and the interdependence and confrontation process between the virus and the human were modeled. The development trends and statistical characteristics of a large number of viruses and humans were deduced through the model. The experimental analysis reveals that the randomness of …

Decision-Making Considering Power Consumption And Preference For New Energy Under Dual-Credit Policy, Fang Li, Tianhao Dong

Journal of System Simulation

Abstract: To explore the production decision-making problem of the electrification transformation in the domestic automobile industry faced by automobile manufacturers, different decision-making models under two production scenarios are constructed for the secondary supply chain composed of manufacturers and retailers under the background of a dual-credit policy. The electric energy consumption of new energy vehicles and consumers' preference for new energy are introduced. The Stackelberg game is applied to obtain the optimal production decision and income analysis of each member in the supply chain under different decision modes in different production scenarios. The results show that the in-depth implementation of the …

Vysion Software, Isaias Hernandez-Dominguez Jr, Chander Luderman Miller

2024 Symposium

Vision loss presents significant challenges in daily life. Existing solutions for blind and visually impaired individuals are often limited in functionality, expensive, or complex to use. Vysion Software addresses this gap by developing a user-friendly, all-in-one AI companion app that provides features including text summarization, real-time audio descriptions, and AI-enhanced navigation. This project details the development plan, initial functionalities, and future vision for Vysion Software.

Identification And Characterization Of Intrinsically Disordered Protein Regions, Guy Wayne Dayhoff Ii

USF Tampa Graduate Theses and Dissertations

This dissertation investigates protein intrinsic disorder and intrinsically disordered protein regions (IDPRs) through the development and application of advanced computational and experimental techniques. Chapter 1 provides an introduction to protein intrinsic disorder, outlining the historical context and fundamental concepts that highlight the importance of intrinsically disordered proteins (IDPs) and IDPRs in various biological processes. Chapter 2 focuses on the rapid prediction and analysis of protein intrinsic disorder. We introduce RIDAO (Rapid Intrinsic Disorder Analysis Online), a high-efficiency web-based tool that integrates multiple disorder predictors. RIDAO significantly outperforms existing predictors in computational efficiency, making it suitable for large-scale proteomic studies. We …

Design Of Long-Distance Entanglement Distribution Protocols For Quantum Networks, Stav Haldar

LSU Doctoral Dissertations

Future quantum technologies such as quantum communication, quantum sensing, and distributed quantum computation, will rely on networks of shared entanglement between spatially separated nodes. Distributing entanglement between these nodes, especially over long distances, currently remains a challenge, due to limitations resulting from the fragility of quantum systems, such as photon losses, non-ideal measurements, and quantum memories with short coherence times. In the absence of full-scale fault-tolerant quantum error correction, which can in principle overcome these limitations, we should understand the extent to which we can circumvent these limitations. In this work, we provide improved protocols and policies for entanglement distribution …

Human Centered Approaches And Taxonomies For Explainable Artificial Intelligence, Helen Sheridan, Emma Murphy, Dympna O'Sullivan

Conference papers

Recent interest within the research community related to explainable artificial intelligence (XAI) has led to a profuse amount of literature on the subject. Those who wish to tackle the domain from an HCI focus may be presented with overwhelming material, most of which does not pertain to human aspects of XAI. Taxonomies can serve to categorize a subject into topic areas and distill content into an overview of the field. This late breaking work intends to help those within the HCI community with a focus on XAI to understand relevant aspects of human centered XAI. We also present a taxonomy …

Evaluating Artificial Intelligence On The Efficacy Of Preference Assessments For Preservice Speech-Language Pathologists, Brenna Griffin, Elizabeth R. Lorah, Christine Holyfield, Nicolette Caldwell, John Nosek

Curriculum and Instruction Faculty Publications and Presentations

Individuals with intellectual and developmental disabilities (IDD) face many barriers to meaningful inclusion, including limited language and communication skills. Professionals, such as speech-language pathologists (SLPs), can provide personalized instruction to promote skill development and inclusion. Providing opportunities for individuals to express preferences and choice, such as the multiple stimulus without replacement preference assessment (MSWO; DeLeon & Iwata 1996), within these programs, further increases skill acquisition and social interaction. However, limitations in professionals’ knowledge and skills in performing assessments can be another barrier to meaningful inclusion for individuals with IDD and traditional training methods can be challenging and time consuming. …

Peatmoss: A Dataset And Initial Analysis Of Pre-Trained Models In Open-Source Software, Wenxin Jiang, Jerin Yasmin, Jason Jones, Nicholas Synovic, Jiashen Kuo, Nathaniel Bielanski, Yuan Tian, George K. Thiruvathukal, James C. Davis

Computer Science: Faculty Publications and Other Works

The development and training of deep learning models have become increasingly costly and complex. Consequently, software engineers are adopting pre-trained models (PTMs) for their downstream applications. The dynamics of the PTM supply chain remain largely unexplored, signaling a clear need for structured datasets that document not only the metadata but also the subsequent applications of these models. Without such data, the MSR community cannot comprehensively understand the impact of PTM adoption and reuse. This paper presents the PeaTMOSS dataset, which comprises metadata for 281,638 PTMs and detailed snapshots for all PTMs with over 50 monthly downloads (14,296 PTMs), along with …

Do Realistic Avatars Make Virtual Reality Better? Examining Human-Like Avatars For Vr Social Interactions, Alan D. Fraser, Isabella Branson, Ross C. Hollett, Craig P. Speelman, Shane L. Rogers

Research outputs 2022 to 2026

No abstract provided.

Empirical Insights Into Ai-Assisted Game Development: A Case Study On The Integration Of Generative Ai Tools In Creative Pipelines, Andrew Begemann, James Hutson

Student Scholarship

This study conducts an empirical exploration of generative Artificial Intelligence (AI) tools across the game development pipeline, from concept art creation to 3D model integration in a game engine. Employing AI generators like Leonardo AI, Scenario AI, Alpha 3D, and Luma AI, the research investigates their application in generating game assets. The process, documented in a diary-like format, ranges from producing concept art using fantasy game prompts to optimizing 3D models in Blender and applying them in Unreal Engine 5. The findings highlight the potential of AI to enhance the conceptualization phase and identify challenges in producing optimized, high-quality 3D …

Analysis Of American Think Tanks' Views On China-Us Chip Competition And Its Enlightenment, Bingcheng He, Guoli Yang

Journal of Scientific Information Research

[Purpose/significance]This paper focuses on the viewpoints of leading American think tanks on chip competition with China, aiming to unravel the logic behind the formulation of U.S. chip policies towards China. It also seeks to explore innovative pathways for the development of China's chip industry and provide strategic recommendations beneficial to Sino-American chip competition. [Method/process]The study selects 20 representative research reports from 9 prominent think tanks and employs a literature analysis approach to dissect the viewpoints, motives, and potential influences found in these reports. [Result/conclusion]The results reveal that most American think tanks adopt a firm stance, perceiving the rise of China's …

React: Recognize Every Action Everywhere All At Once, Naga Venkata Sai Raviteja Chappa, Pha Nguyen, Page Daniel Dobbs, Khoa Luu

Electrical Engineering and Computer Science Faculty Publications and Presentations

In the realm of computer vision, Group Activity Recognition (GAR) plays a vital role, finding applications in sports video analysis, surveillance, and social scene understanding. This paper introduces Recognize Every Action Everywhere All At Once (REACT), a novel architecture designed to model complex contextual relationships within videos. REACT leverages advanced transformer-based models for encoding intricate contextual relationships, enhancing understanding of group dynamics. Integrated Vision-Language Encoding facilitates efficient capture of spatiotemporal interactions and multi-modal information, enabling comprehensive scene understanding. The model’s precise action localization refines joint understanding of text and video data, enabling precise bounding box retrieval and …

Enhancing Adult Learner Success In Higher Education Through Decision Tree Models: A Machine Learning Approach, Emily Barnes, James Hutson, Karriem Perry

Faculty Scholarship

This article explores the use of machine learning, specifically Classification and Regression Trees (CART), to address the unique challenges faced by adult learners in higher education. These learners confront socio-cultural, economic, and institutional hurdles, such as stereotypes, financial constraints, and systemic inefficiencies. The study utilizes decision tree models to evaluate their effectiveness in predicting graduation outcomes, which helps in formulating tailored educational strategies. The research analyzed a comprehensive dataset spanning the academic years 2013–2014 to 2021–2022, evaluating the predictive accuracy of CART models using precision, recall, and F1 score. Findings indicate that attendance, age, and Pell Grant eligibility are key …

Label-Free Surface-Enhanced Raman Spectroscopy Coupled With Machine Learning Algorithms In Pathogenic Microbial Identification: Current Trends, Challenges, And Perspectives, Jia Wei Tang, Quan Yuan, Xin Ru Wen, Muhammad Usman, Alfred Chin Yen Tay, Liang Wang

Research outputs 2022 to 2026

Infectious diseases caused by microbial pathogens remain a primary contributor to global health burdens. Prompt control and effective prevention of these pathogens are critical for public health and medical diagnostics. Conventional microbial detection methods suffer from high complexity, low sensitivity, and poor selectivity. Therefore, developing rapid and reliable methods for microbial pathogen detection has become imperative. Surface-enhanced Raman Spectroscopy (SERS), as an innovative non-invasive diagnostic technique, holds significant promise in pathogenic microorganism detection due to its rapid, reliable, and cost-effective advantages. This review comprehensively outlines the fundamental theories of Raman Spectroscopy (RS) with a focus on label-free SERS strategy, reporting …

Development Of A Rule-Based Monitoring System For Autonomous Heavy Equipment Safety, Amirpooya Shirazi

Department of Construction Engineering and Management: Dissertations, Theses, and Student Research

Roadway construction work zones are constantly exposed to interactions among construction equipment, workers, and vehicles. Furthermore, ensuring safety in these areas is considered a challenging task due to the complexity of the environment. As shown in the rising trend of fatal accidents in roadway work zones, current OSHA regulations in construction safety are insufficient in effectively detecting unsafe situations and mitigating the risks. Furthermore, best practices, such as internal traffic control planning (ITCP), exhibit critical limitations requiring continuous monitoring of active work zones as well as adjustments to the site coordination plans due to the dynamic nature of work zone …

My Ai Companion: An Examination Of The Removal Of Erotic Role Play From Replika Through User Discussion On Reddit, Chelsee M. Allen

Department of Sociology: Dissertations, Theses, and Student Research

The development of artificial intelligence (AI) software has expanded rapidly in recent years, and thus has emerged the importance of exploring human relationships with AI chatbots. Replika, an app which uses AI to mimic human conversation, removed a function called Erotic Role Play (ERP) that allowed for sexual conversation with users’ customizable chatbots in February of 2023. This exploratory qualitative study examines the aftermath of ERP’s removal through an analysis of user interactions on Reddit. Five overarching themes emerged through the analysis of top posts to a Replika-specific subreddit, encompassing topics around mental health, stigma, coping, sex work and gendered …

Cognitive Technologies, Tom Davenport

Asian Management Insights

AI and the revolution of work.

Professor Tom Davenport, the President’s Distinguished Professor of Information Technology and Management at Babson College, speaks about how companies can integrate generative Artificial Intelligence (GenAI) into their operations while ensuring workforce adaptation and skills development.

Deep Learning In Reproducing Kernel Banach Spaces, Mingsong Yan

Mathematics & Statistics Theses & Dissertations

Deep learning has achieved immense success in the past decade. The goal of this dissertation is to understand deep learning through the framework of reproducing kernel Banach spaces (RKBSs), which were originally proposed for promoting sparse solutions. We begin by considering learning problems in a general functional setting, and establishing explicit and data-dependent representer theorems for both minimal norm interpolation (MNI) problems and regularization problems. These theorems provide a crucial foundation for the subsequent results derived for both sparse learning and deep learning. Next, we investigate the essential properties of RKBSs capable of encouraging sparsity in learning solutions. With the …

Mesostructure Reconstruction Of Prepreg Platelet Molded Composite With Artificial Intelligence, Richard Larson

Mechanical & Aerospace Engineering Theses & Dissertations

Prepreg platelet molded composites (PPMC) are long, discontinuous fiber reinforced polymer materials. PPMC are an important subcategory of composite materials as they are processible into geometrically complex structures and can be produced via high-throughput manufacturing processes, however they have higher stiffness and strength as compared to traditional discontinuous fiber reinforced polymers. However, there is inherent randomness in the structure of PPMCs and as such, PPMC parts frequently require per part testing that is cost prohibitive.

Herein, a method using artificial intelligence is proposed as a more cost-effective method of inspecting PPMC parts. Different artificial intelligence (AI) architectures are explored to …

Harnessing Social Media For Disaster Response: Intelligent Identification Of Reliable Rescue Requests During Hurricanes, Wael Khallouli

Engineering Management & Systems Engineering Theses & Dissertations

Hurricanes pose a significant threat to both human lives and infrastructure. Decision-makers face substantial challenges during such events, as they must act quickly to address victims’ needs. Social media platforms provide a valuable source for quick and real-time information. Recent hurricane events have shown that people turn to social media to call for help when official communication channels, such as 911, are overwhelmed. However, extracting actionable information from the massive number of messages posted on social media is challenging. Furthermore, verifying social media messages posted by the public is a critical concern for disaster response practitioners, making them hesitant to …

Unveiling The Dynamics Of Ai Applications: A Review Of Reviews Using Scientometrics And Bertopic Modeling, Raghu Raman, Debidutta Pattnaik, Laurie Hughes, Prema Nedungadi

Research outputs 2022 to 2026

In a world that has rapidly transformed through the advent of artificial intelligence (AI), our systematic review, guided by the PRISMA protocol, investigates a decade of AI research, revealing insights into its evolution and impact. Our study, examining 3,767 articles, has drawn considerable attention, as evidenced by an impressive 63,577 citations, underscoring the scholarly community's profound engagement. Our study reveals a collaborative landscape with 18,189 contributing authors, reflecting a robust network of researchers advancing AI and machine learning applications. Review categories focus on systematic reviews and bibliometric analyses, indicating an increasing emphasis on comprehensive literature synthesis and quantitative analysis. The …