Artificial Intelligence and Robotics Commons^™

Generative Ai-Based Non-Person Character (Npc) For Navigating Virtual Worlds, Ananth Ramaseri-Chandra

Computer Science Posters and Presentations

An innovative approach to virtual world interactions through generative AI-based Non-person Characters (NPCs). These AI-driven NPCs significantly advance over traditional, scripted characters by providing more realistic, adaptive, and dynamic interactions in various virtual environments. The work details the development process of these NPCs, from algorithm design to data integration and iterative refinement, ensuring their seamless integration into game environments. Additionally, the poster explores the wide-ranging applications of these AI NPCs, including enhancing gaming experiences, offering realistic training environments, and facilitating personalized virtual learning experiences. This research marks a substantial leap in virtual interaction, pushing the boundaries of immersion and realism …

Search-Based Fairness Testing: An Overview, Hussaini Mamman, Shuib Basri, Abdullateef Balogun, Abdullahi Abubakar Imam, Ganesh Kumar, Luiz Fernando Capretz

Electrical and Computer Engineering Publications

Artificial Intelligence (AI) has demonstrated remarkable capabilities in domains such as recruitment, finance, healthcare, and the judiciary. However, biases in AI systems raise ethical and societal concerns, emphasizing the need for effective fairness testing methods. This paper reviews current research on fairness testing, particularly its application through search-based testing. Our analysis highlights progress and identifies areas of improvement in addressing AI systems’ biases. Future research should focus on leveraging established search-based testing methodologies for fairness testing.

Electromagnetic Transient Equivalent Modeling Method For Wind Power Clusters Adapted To Expected Faults, Dongsheng Li, Ye Liu, Yankan Song, Chen Shen

Journal of System Simulation

Abstract: Based on an existing equivalent modeling method for individual wind farm, an iterative simulation-based equivalent modeling method for wind power clusters is proposed and a software development for equivalent modeling of wind power clusters is completed by using CloudPSS-XStudio suite. The system integrates expected fault selection, equivalent parameter calculation and result analysis, which provides support for dynamic security assessment of power systems with large-scale wind power clusters. The equivalent method takes the average wind speed of each wind farm and the expected faults as input, and obtains the cluster index of each wind turbine based on the iterative simulation …

Key Technology And Application Of Digital Twin Modeling For Mri, Shanshan Chen, Hongzhi Wang, Tian Xia

Journal of System Simulation

Abstract: With the accelerating digitalization in education, the construction of digital resources and application platforms has caught increasing attention. The framework of MRI equipment digital twin fivedimensional model is constructed to solve the problems in teaching and training for magnetic resonance imaging (MRI). A modeling and simulation method based on the mechanism model is proposed. The multi-dimensional physical data are obtained to perform digital human modeling, and the virtual acquisition and image reconstruction method is proposed to generate images. The digital twin data are adopted for iterative optimization to implement the whole process of the three-dimensional visual operation including preparation …

A Hybrid Empirical Method For Fast Modeling Of Ship Manoeuvring Motion, Peng Wu, Zongmo Yang, Qianfeng Jing, Yulin Li

Journal of System Simulation

Abstract: Simulation testing is an important means to verify the functions of intelligent ships. Ship maneuvering motion modeling and simulation is the key theoretical basis for the intelligent collision avoidance of multiple vessels in complex sea areas. To address the problem that the calculation of the hydrodynamic coefficients required for ship maneuvering modeling is complex and difficult to obtain, a hybrid empirical method is proposed, a combination method of the existing regression methods is established, the comprehensive performance indicators are constructed, the optimal hydrodynamic coefficients groups are selected by simulated maneuvering experiments, and a rapid modeling program code is developed …

Reliability Evaluation Method Of Radar Simulation Model Based On Air Combat Mechanism, Chenguang Wang, Jinpeng Bai, Tingting Li, Lifeng Miao, Kaifeng Wang

Journal of System Simulation

Abstract: In modern air combat simulation, the reliability of radar simulation model is very important. Based on simulation model VV&A theory, a cropped and suitable for engineering applications simulation model reliability evaluation method is proposed. Based on the analysis of radar use mechanism in medium and long range air combat and short range air combat is analyzed,, the requirement of radar model in air combat simulation system, the evaluation index system is established, and the reliability quantification method based on JS dispersion is proposed, which further enriches the base of basic method. The test case is designed, the simulation test …

Learning And Analysis Of Dynamic Models For Grid Discrete Events Based On Log Information, Danlong Zhu, Yunqi Yan, Ying Chen, Jiaqi Zhang, Longxing Jin, Wei Fu

Journal of System Simulation

Abstract: With the increasing scale of power grid, the massive amount of log information generated bydevices in the power grid poses a challenge to the manual analysis of abnormal grid conditions. The log information generated during the operation of the power grid has the typical discrete sequential characteristics. By analyzing the log information of grid alarm messages, a station event transition probability model and an event sequence risk calculation method are proposed to effectively model and analyze the abnormal operation level of primary and secondary systems in substations. The proposed method not only successfully identifies the event sequences corresponding to …

Research On Multi-Aircraft Air Combat Behavior Modeling Based On Hierarchical Intelligent Modeling Methods, Yukun Wang, Ze Wang, Liwei Dong, Ni Li

Journal of System Simulation

Abstract: In response to the problem of the difficulty of decision-making in the game of force under the constraints of high-dimensional state-space in multi-machine air combat confrontation scenarios, a force intelligent agent decision-making generation strategy based on deep reinforcement learning is adopted. The developing situational cognition and reward feedback generation algorithms for force intelligentgame are proposed, a behavior modeling hierarchical framework based on hybrid intelligence modeling method is constructed, which solve the technical difficulty of sparse reward in the reinforcement learning process. It provides an feasible reinforcement learning training method that can solve the large-scale, multi-model, and multi-element air combat …

Dynamic 3d Scene Perception Based On Battlefield Metaverse, Haoyu Wang, Guanghong Gong, Jihong Cai, Bipeng Ye, Zhaofang Zhou, Zheng Mei, Ni Li

Journal of System Simulation

Abstract: Informatization combat needs higher requirements for battlefield situational awareness, and the use of unmanned intelligences to conduct battlefield reconnaissance and perceive target information is particularly important. Facing the needs of complex dynamic environment localization and target recognition, a dynamic 3D scene perception system is proposed and constructed based on battlefield meta-universe target data and operational environment, which uses vision and IMU fusion sensor simulation data as inputs, extracts battlefield target information through instance segmentation and dense optical flow estimation network and uses it as a scene prior, and synchronizes the position estimation of unmanned intelligences in the battlefield with …

Executive Order On The Safe, Secure, And Trustworthy Development And Use Of Artificial Intelligence, Joseph R. Biden

Copyright, Fair Use, Scholarly Communication, etc.

Section 1. Purpose. Artificial intelligence (AI) holds extraordinary potential for both promise and peril. Responsible AI use has the potential to help solve urgent challenges while making our world more prosperous, productive, innovative, and secure. At the same time, irresponsible use could exacerbate societal harms such as fraud, discrimination, bias, and disinformation; displace and disempower workers; stifle competition; and pose risks to national security. Harnessing AI for good and realizing its myriad benefits requires mitigating its substantial risks. This endeavor demands a society-wide effort that includes government, the private sector, academia, and civil society.

My Administration places the highest urgency …

A Precise Attention Tracking System Based On Computer Vision, Jiyuan Liu, Hanwen Qi, Zhicheng Liu, Minrui Fei, Kun Zhang

Journal of System Simulation

Abstract: A precise attention tracking system based on machine vision is designed to address the difficulty in studying students' attention allocation. The system includes an image capture device and an accurate attention tracking algorithm. The image capture device can capture the clearer ocular images. The pupil center localization algorithm replaces VGG16 with lightweight MobileNetv3 and uses twostage feature fusion and center keypoint prediction techniques to improve the speed and accuracy. The algorithm achieves a speed of up to 36 frames/s and 97.42% accuracy. The gaze tracking algorithm compensates for the head movements to achieve the meticulous gaze tracking. An interactive …

Modeling And Analysis On Scattering Characteristics Automatic Driving Radar Bands In Rainy Environment, Mengfan Zou, Xiaoyu He

Journal of System Simulation

Abstract: The operating frequency band of modern communication and radar systems has extended to millimeter wave and terahertz frequency band, and the analysis on propagation characteristics of electromagnetic signals in rainy environment is important. A calculation model through Mie scattering theory is built to simulate the attenuation and the scattering of electromagnetic signals in rainy environments. Different types of raindrop size distribution function are adopted to analyze the propagation attenuation under different rainfall of frequencies spanning from 1 GHz to 1 THz. Experimental results are compared with international telecommunication union (ITU) half-empirical model to verify the validation of the model. …

Integrated Scheduling Simulation Based On Improved Moth Flame Optimizer, Tianrui Zhang, Huiyuan Niu, Wei Xie

Journal of System Simulation

Abstract: Aiming at the rising cost of manufacturing enterprises, a mathematical programming model of integrated scheduling of production and transportation is established, and a double adaptive weights for moth flame optimizer(DAWMFO) is proposed. A double adaptive weight mechanism is proposed. The spiral function is used to update the population, which improves the convergence speed and accuracy of the algorithm. The benchmark function is tested by the improved algorithm. The results show that the improved algorithm can converge quickly and not easily fall into local optimum. Compared with other algorithms, the optimization ability is also improved. Through the simulation experiment on …

Simulation And Research Of Manipulator Motion Strategy Based On Adaptive Dynamic Programming, Ming Li, Qun Xu, Yan Wang, Zhicheng Ji

Journal of System Simulation

Abstract: Aiming at the difficulty of manipulator to realize high-precision motion tracking in complex and harsh environment, a strategy method based on the combination of adaptive dynamic programming (ADP) and sliding mode admittance control is proposed. The unknown environment is modeled as a linear model and based on quasi, a sliding mode admittance controller is derived to resist disturbance interference. An optimal control method that combines ADP with sliding mode admittance controller is proposed, in which the definition of R-matrix in value function is optimized and improved to further improve the tracking accuracy. The neural network based on ADP is …

Design And Simulation Of A Location Privacy Protection Scheme Based On Zero-Knowledge Proof For Military Iot, Mingjie Shi, Chengyu Xie, Chuanfu Zhang

Journal of System Simulation

Abstract: In the military Internet of Things (IoT) combat environment, the location privacy issue becomes a key challenge. An innovative location privacy protection scheme based on zero-knowledge proof is proposed to ensure that in unreliable communication channels, the location information of combat units can be verified without revealing their specific coordinates, so as to achieve the goal of protecting sensitive location information. Based on the idea of cryptography, by using zero-knowledge proof, through algebraic circuit, rank-1 constraint system(R1CS), quadratic arithmetic programs(QAP), and other steps, the position coordinate information proof problem is transformed into a point verification problem on a polynomial …

Time-Varying Rbf Neural Network-Based Controller Design For A Class Of Time-Varying Nonlinear Systems, Jing Li, Taotao Zhang, Kai Jin, Shengzhi Yuan, Zilong Zha

Journal of System Simulation

Abstract: A time-varying RBF neural network with time-varying properties is firstly proposed, and its approximation theorem is obtained. For a class of nonlinear systems with non-parametric time-varying uncertainties, the proposed time-varying RBF neural network is used to approximate the time-varying uncertainties, and the controller is designed by making use of Lyapunov stability theory and adaptive iterative learning control techniques. We obtain the stability theorem of the designed controller. The simulation results verify the effectiveness of the time-varying neural network and the correctness of the controller design scheme.

A Structured Conceptual Model Of Joint Operations From Design Perspective, Rui Wen

Journal of System Simulation

Abstract: With the development of technology, through the complementary interaction among operations, operation effectiveness can non-linearly increase and realize fissional and exponential effect. In order to realize dynamic convergence, it is necessary to carry out the action, information and energy unified design. From the antagonism view, taking into account the factors such as the purpose of the operation, the strength of the operation, the conditions of the operation, and so on, the joint operation is divided into the preorder action/ state, the major operational action, the counter-action, the response action, and the branch action, which is synthesized to major operation, …

Terrain Surface Texture Generation Networks For User Semantics Customization, Yan Gao, Jimeng Li, Jianzhong Xu, Hongyan Quan

Journal of System Simulation

Abstract: Customizing terrain based on user semantics has practical value in the virtual terrain modeling of military simulation applications. This study provides a terrain surface texture generation network (TSTG-Net) that can synthesize realistic terrain based on user input semantics. TSTG-Net is designed as a Pix2pix structure and is based on CGAN. It learns the topology of customized terrain by encoding and parsing user semantics and regards the semantics feature as the constraint of CGAN. In the generator-discriminator structure, user-customized semantics are used as the input, and the real terrain with semantics is employed as the ground truth in network optimization. …

Air Distribution Simulation And Comfort Evaluation Of Large Space Building Based On Rans And Les, Shen Zhang, Ming Cheng, Yifan Wang, Fankai Meng, Ting Li, Han Chen, Zhifeng Ji

Journal of System Simulation

Abstract: Air distribution simulation and thermal comfort evaluation for heating, ventilation and air conditioning (HVAC) design of large space buildings is of great significance for the human thermal comfort improvement and the energy consumption reduction. By combining the steady analysis based on RANS and the transient analysis of large eddy simulation (LES), an air distribution simulation and thermal comfort evaluation process in large space buildings is established. Due to the low calculation consumption, the steady analysis based on RANS is conducted to efficiently evaluate the thermal comfort and the air quality under multiple working conditions. Considering the high computational consumption …

A Fuzzy Group Decision-Making-Based Method For Green Supplier Selection And Order Allocation, Lu Liu, Wenxin Li, Xiao Song, Bingli Sun, Guanghong Gong

Journal of System Simulation

Abstract: With the intensity of market competitiveness, the worsening of the global environment, and the improvement of public concern about environmental protection, the issue of green purchasing has received considerable attention. The vast majority of existing studies on green purchasing have concentrated on supplier selection with green criteria, so as to realize sustainable operations, whereas it is more feasible and economical for businesses to obtain the proper products from adaptable and suitable suppliers at the right times, rates, and volumes, which is referred to as supplier selection and order allocation. To resolve the aforementioned two crucial challenges, we propose a …

An Automatic Code Generation Method For Generic Real-Time Hardware-In-The-Loop Simulation Based On Custom Wizard, Zihan Liu, Lingxiao Hou, Yang Li, Zhiguang Wang, Wulong Zhang

Journal of System Simulation

Abstract: For the capability improvement demands of automation and generalization hardware-in-theloop simulation system, an automatic code generation method for generic real-time hardware-in-the-loop simulation based on custom wizard is proposed. A modular and universal code template-based frame documents and professional resource library are constructed with years of technical accumulation in hardware-in-the-loop simulation. The responsive front-ends and scripts are designed by HTML, CSS and JavaScript and an universal automatic code generation software AutoSimRTX is developed, which effectively supports the construction of hardware-in-the-loop simulation system.

Ai And The Creative Process: Part Three, James Hutson

Faculty Scholarship

Article discussing the effects of artificial intelligence on the creative process in the art world.

Artst: Arabic Text And Speech Transformer, Hawau Olamide Toyin, Amirbek Djanibekov, Ajinkya Kulkarni, Hanan Al Darmaki

Natural Language Processing Faculty Publications

We present ArTST, a pre-trained Arabic text and speech transformer for supporting open-source speech technologies for the Arabic language. The model architecture follows the unified-modal framework, SpeechT5, that was recently released for English, and is focused on Modern Standard Arabic (MSA), with plans to extend the model for dialectal and code-switched Arabic in future editions. We pre-trained the model from scratch on MSA speech and text data, and fine-tuned it for the following tasks: Automatic Speech Recognition (ASR), Text-To-Speech synthesis (TTS), and spoken dialect identification. In our experiments comparing ArTST with SpeechT5, as well as with previously reported results in …

Statistical And Machine Learning Approaches To Describe Factors Affecting Preweaning Mortality Of Piglets, Md Towfiqur Rahman, Tami M. Brown-Brandl, Gary A. Rohrer, Sudhendu R. Sharma, Vamsi Manthena, Yeyin Shi

Department of Agricultural and Biological Systems Engineering: Faculty Publications

High preweaning mortality (PWM) rates for piglets are a significant concern for the worldwide pork industries, causing economic loss and well-being issues. This study focused on identifying the factors affecting PWM, overlays, and predicting PWM using historical production data with statistical and machine learning models. Data were collected from 1,982 litters from the United States Meat Animal Research Center, Nebraska, over the years 2016 to 2021. Sows were housed in a farrowing building with three rooms, each with 20 farrowing crates, and taken care of by well-trained animal caretakers. A generalized linear model was used to analyze the various sow, …

A Psychometric Analysis Of Natural Language Inference Using Transformer Language Models, Antonio Laverghetta Jr.

USF Tampa Graduate Theses and Dissertations

Large language models (LLMs) are poised to transform both academia and industry. But the excitement around these generative AIs has also been met with concern for the true extent of their capabilities. This dissertation helps to address these questions by examining the capabilities of LLMs using the tools of psychometrics. We focus on analyzing the capabilities of LLMs on the task of natural language inference (NLI), a foundational benchmark often used to evaluate new models. We demonstrate that LLMs can reliably predict the psychometric properties of NLI items were those items administered to humans. Through a series of experiments, we …

Text Augmentation For Semantic Frame Induction And Parsing, Saba Anwar, Artem Shelmanov, Nikolay Arefyev, Alexander Panchenko, Chris Biemann

Natural Language Processing Faculty Publications

Semantic frames are formal structures describing situations, actions or events, e.g., Commerce buy, Kidnapping, or Exchange. Each frame provides a set of frame elements or semantic roles corresponding to participants of the situation and lexical units (LUs)—words and phrases that can evoke this particular frame in texts. For example, for the frame Kidnapping, two key roles are Perpetrator and the Victim, and this frame can be evoked with lexical units abduct, kidnap, or snatcher. While formally sound, the scarce availability of semantic frame resources and their limited lexical coverage hinders the wider adoption of frame semantics across languages and domains. …

Yet Another Model For Arabic Dialect Identification, Ajinkya Kulkarni, Hanan Al Darmaki

Natural Language Processing Faculty Publications

In this paper, we describe a spoken Arabic dialect identification (ADI) model for Arabic that consistently outperforms previously published results on two benchmark datasets: ADI-5 and ADI-17. We explore two architectural variations: ResNet and ECAPA-TDNN, coupled with two types of acoustic features: MFCCs and features exratected from the pre-trained self-supervised model UniSpeech-SAT Large, as well as a fusion of all four variants. We find that individually, ECAPA-TDNN network outperforms ResNet, and models with UniSpeech-SAT features outperform models with MFCCs by a large margin. Furthermore, a fusion of all four variants consistently outperforms individual models. Our best models outperform previously reported …

Decentralized Science (Desci): A New Paradigm For Diverse And Sustainable Scientific Development, Feiyue Wang, Wenwen Ding

Bulletin of Chinese Academy of Sciences (Chinese Version)

The rise of artificial intelligence for science (AI4S) has made it particularly important and urgent to ensure the openness, fairness, impartiality, diversity, and sustainability of scientific systems. This is significant to the discourse power and leadership of countries in global innovation and industrial revolution, and also affects the security, stability, and sustainable development of a community with a shared future for mankind. To address these challenges, AI4S needs to adopt new scientific organizational and operational methods. Decentralized science (DeSci) has emerged to vitalize AI4S and provide strong support, effectively addressing issues such as information silos, biases, unfair distribution, and monopolies …

Metaverse Key Requirements And Platforms Survey, Akbobek Abilkaiyrkyzy, Ahmed Elhagry, Fedwa Laamarti, Abdulmotaleb El Saddik

Computer Vision Faculty Publications

The growing interest in the metaverse has led to an abundance of platforms, each with its own unique features and limitations. This paper's objective is two-fold. First, we aim at providing an objective analysis of requirements that need to be fulfilled by metaverse platforms. We survey a broad set of criteria including interoperability, immersiveness, persistence, multimodal and social interaction, scalability, level of openness, configurability, market access, security, and blockchain integration, among others. Second, we review a wide range of existing metaverse platforms, and we critically evaluate their ability to meet the requirements listed. We identify their limitations, which must be …

Lrtransformer: Learn-Region Transformer For Object-Agnostic Point Cloud Segmentation, Dipesh Gyawali

LSU Master's Theses

3D point cloud segmentation segments the 3D point cloud data into different regions/instances depending on their features that have numerous applications in robotics, autonomous driving, digital twinning, augmented reality, etc. The majority of the existing point cloud segmentation methods depend on class labels to identify 3D objects in the surroundings. Our work focuses on segmenting point clouds into different regions/instances in an object-agnostic manner for any number of objects in the environment. Given the point cloud, our method can segment the entire scene into multiple instances without depending on object shape and size. We leverage the power of the self-attention …