Physical Sciences and Mathematics Commons^™

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. …

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.

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 …

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.

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 …

Demo-Abstract: A Dtn System For Tracking Miners Using Gae-Lstm And Contact Graph Routing In An Underground Mine, Abhay Goyal, Sanjay Kumar Madria, Samuel Frimpong

Computer Science Faculty Research & Creative Works

Localization and prediction of movement of miners in underground mines have been a constant problem more so during a mine disaster. Due to the unavailability of GPS signals, the pillars are used as a method to locate these miners, and thus, location prediction is also carried out with reference to these pillars. In this work, we demon- strate a Delay-tolerant Network (DTN) system called Miner-Finder that leverages Machine Learning (ML) framework (GAE-LSTM) that works on edge devices (e.g., mobile phones, tablets) to predict the location of miners in an underground mine. The information such as speed, angle, time, nearest pillar …

A Developed Framework For Studying Cyberethical Behaviour In North Central Nigeria, Aderinola Ololade Dunmade, Adeyinka Tella, Uloma Doris Onuoha

Journal of Cybersecurity Education, Research and Practice

ICT advancements have enabled more online activities, resulting in several cyberethical behaviours. Literature documents prevalence of plagiarism, and online fraud, among other misbehaviours. While behaviour has been explained by several theories, as scholarship and research advances, frameworks are modified to include more constructs. The researchers modified Fishbein and Ajzen (2011)'s Reasoned Action Approach to study female postgraduate students' perspectives toward cyberethical behaviour in North Central Nigerian universities.

The study focused on four variables, which were adequately captured by the model: perception, awareness, and attitude.

An adapted questionnaire collected quantitative data. This study used multistage sampling. A sample size of 989 …

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 …

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.

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. …

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 …

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 …

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 …

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 …

Ship Registry And Flag State Obligations For The Plurinational State Of Bolivia: A Case Study For A Landlocked State, Marco Antonio Lucano Uzquiano

World Maritime University Dissertations

No abstract provided.

A Dynamic Online Dashboard For Tracking The Performance Of Division 1 Basketball Athletic Performance, Erica Juliano, Chelsea Thakkar, Christopher B. Taber, Mehul S. Raval, Kaya Tolga, Samah Senbel

School of Computer Science & Engineering Undergraduate Publications

Using Data Analytics is a vital part of sport performance enhancement. We collect data from the Division 1 'Women's basketball athletes and coaches at our university, for use in analysis and prediction. Several data sources are used daily and weekly: WHOOP straps, weekly surveys, polar straps, jump analysis, and training session information. In this paper, we present an online dashboard to visually present the data to the athletes and coaches. R shiny was used to develop the platform, with the data stored on the cloud for instant updates of the dashboard as the data becomes available. The performance of athletes …

Modification Of Chitosan Using Glycidyl Methacrylate-Grafted Cellulose (Gmagcell/ Chi) For Methylene Blue Adsorption, Haya Fathana, Rahmi Rahmi, Muhammad Adlim, Surya Lubis

Karbala International Journal of Modern Science

In this study, a glycidyl methacrylate-grafted cellulose/chitosan (GMA-g-Cell/Chi) film was successfully prepared and characterized. GMA-g-Cell was obtained from the grafting process of cellulose derived from sugarcane bagasse using glycidyl methacrylate (GMA). The cellulose grafting process was obtained using 20% GMA for 4 hours at 60oC. The percentage of grafting (PG) and grafting efficiency (GE) values for these parameters were 516 and 60.28%, respectively. Chitosan was modified with GMA-g-Cell and has higher adsorption capacity and tensile strength than chitosan. The adsorption kinetics tend to follow the pseudo-first-order adsorption kinetics model, with Qe and k1 being 7 mg/g and 0.067 g/mg. minute. …

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

Biological Systems Engineering: Papers and 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, …

Evaluating Methods For Improving Dnn Robustness Against Adversarial Attacks, Laureano Griffin

USF Tampa Graduate Theses and Dissertations

Deep learning has become more widespread as advances in the field continue. As aresult, making sure deep learning is safe has become a priority. A seemingly normal image with intentional pixel changes can cause a well-trained model to misclassify the image with high confidence. Those kinds of images are called adversarial attacks. Adversarial training has been developed to defend against adversarial attacks. This thesis evaluates different adversarial training methods against a variety of adversarial attacks. The key metrics for evaluation are classification accuracy and training time. This thesis also experiments with an improvement on an existing adversarial training method, the …

Leveraging Vr/Ar/Mr/Xr Technologies To Improve Cybersecurity Education, Training, And Operations, Paul Wagner, Dalal Alharthi

Journal of Cybersecurity Education, Research and Practice

The United States faces persistent threats conducting malicious cyber campaigns that threaten critical infrastructure, companies and their intellectual property, and the privacy of its citizens. Additionally, there are millions of unfilled cybersecurity positions, and the cybersecurity skills gap continues to widen. Most companies believe that this problem has not improved and nearly 44% believe it has gotten worse over the past 10 years. Threat actors are continuing to evolve their tactics, techniques, and procedures for conducting attacks on public and private targets. Education institutions and companies must adopt emerging technologies to develop security professionals and to increase cybersecurity awareness holistically. …

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 …

Hydrogen Peroxide-Dependent Oxidation Of Erk2 Within Its D-Recruitment Site Alters Its Substrate Selection, Anthony E. Postiglione, Laquaundra L. Adams, Ese S. Ekhator, Anuoluwapo E. Odelade, Supriya Patwardhan, Meenal Chaudhari, Avery S. Pardue, Anjali Kumari, William A. Lefever, Olivia P. Tornow, Tamer S. Kaoud, Johnathan Neiswinger, Jun Seop Jeong, Derek Parsonage, Kimberly J. Nelson, Dukka Kc, Cristina M. Furdui, Heng Zhu, Andrew J. Wommack, Kevin N. Dalby, Ming Dong, Leslie B. Poole, Jeremiah D. Keyes, Robert H. Newman

Michigan Tech Publications, Part 2

Extracellular signal-regulated kinases 1 and 2 (ERK1/2) are dysregulated in many pervasive diseases. Recently, we discovered that ERK1/2 is oxidized by signal-generated hydrogen peroxide in various cell types. Since the putative sites of oxidation lie within or near ERK1/2’s ligand-binding surfaces, we investigated how oxidation of ERK2 regulates interactions with the model substrates Sub-D and Sub-F. These studies revealed that ERK2 undergoes sulfenylation at C159 on its D-recruitment site surface and that this modification modulates ERK2 activity differentially between substrates. Integrated biochemical, computational, and mutational analyses suggest a plausible mechanism for peroxide-dependent changes in ERK2-substrate interactions. Interestingly, oxidation decreased ERK2’s …

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 …

Dynamic Mechanism Of Science Based Technological Innovation And Industrial Evolution—Take Semiconductor, Digital Computer And Radio Technologies As Examples, Yi Zhang, Qiang Yan

Bulletin of Chinese Academy of Sciences (Chinese Version)

By studying the technological innovation and industrial development process of semiconductor, digital computer and radio, this study analyzes the path, conditions and force of science-based technological innovation and its industrialization, establishes a chain reaction model of large-scale technological innovation and diffusion, and compares it with market-based technological innovation. It is found that the large-scale aggregation of scientific research institutions and industrial laboratories accelerates the speed of technological innovation, and diffuses along two paths of scientific research institutions to enterprises and enterprises to enterprises, forming a chain reaction of large-scale technological innovation. Strategic demand is the basic driving force for the …