Artificial Intelligence and Robotics Commons^™

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.

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, …

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 …

Teacher Candidates’ Conceptions And Practices Of Computational Thinking For Equity, Heather F. Clark, Symone A. Gyles, Imelda Nava-Landeros

Journal of Computer Science Integration

This study documents novice science and math teachers’ developing pedagogical approaches to integrating computational thinking (CT) and data into their courses to support educational equity and social justice. The 10 novice teacher candidates (TCs) studied were part of an urban teacher residency program that empowered them with an asset-based pedagogy we describe as “CT for Equity.” Drawing on coursework and interviews as data, we asked three questions: What are teachers’ conceptions of CT? What are their CT instructional practices? And how did their students respond to those practices? To explore conceptions of CT, we used Kafai et al.’s (2020) articulation …

Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian

I-GUIDE Forum

Given multi-model ensemble climate projections, the goal is to accurately and reliably predict future sea-level rise while lowering the uncertainty. This problem is important because sea-level rise affects millions of people in coastal communities and beyond due to climate change's impacts on polar ice sheets and the ocean. This problem is challenging due to spatial variability and unknowns such as possible tipping points (e.g., collapse of Greenland or West Antarctic ice-shelf), climate feedback loops (e.g., clouds, permafrost thawing), future policy decisions, and human actions. Most existing climate modeling approaches use the same set of weights globally, during either regression or …

Machine Learning Prediction Of Hea Properties, Nicholas J. Beaver, Nathaniel Melisso, Travis Murphy

College of Engineering Summer Undergraduate Research Program

High-entropy alloys (HEA) are a very new development in the field of metallurgical materials. They are made up of multiple principle atoms unlike traditional alloys, which contributes to their high configurational entropy. The microstructure and properties of HEAs are are not well predicted with the models developed for more common engineering alloys, and there is not enough data available on HEAs to fully represent the complex behavior of these alloys. To that end, we explore how the use of machine learning models can be used to model the complex, high dimensional behavior in the HEA composition space. Based on our …

Online Aircraft System Identification Using A Novel Parameter Informed Reinforcement Learning Method, Nathan Schaff

Doctoral Dissertations and Master's Theses

This thesis presents the development and analysis of a novel method for training reinforcement learning neural networks for online aircraft system identification of multiple similar linear systems, such as all fixed wing aircraft. This approach, termed Parameter Informed Reinforcement Learning (PIRL), dictates that reinforcement learning neural networks should be trained using input and output trajectory/history data as is convention; however, the PIRL method also includes any known and relevant aircraft parameters, such as airspeed, altitude, center of gravity location and/or others. Through this, the PIRL Agent is better suited to identify novel/test-set aircraft.

First, the PIRL method is applied to …

Spoken Language Processing And Modeling For Aviation Communications, Aaron Van De Brook

Doctoral Dissertations and Master's Theses

With recent advances in machine learning and deep learning technologies and the creation of larger aviation-specific corpora, applying natural language processing technologies, especially those based on transformer neural networks, to aviation communications is becoming increasingly feasible. Previous work has focused on machine learning applications to natural language processing, such as N-grams and word lattices. This thesis experiments with a process for pretraining transformer-based language models on aviation English corpora and compare the effectiveness and performance of language models transfer learned from pretrained checkpoints and those trained from their base weight initializations (trained from scratch). The results suggest that transformer language …

Deep-Learning-Based Classification Of Digitally Modulated Signals, John A. Snoap

Electrical & Computer Engineering Theses & Dissertations

This dissertation presents several novel deep-learning (DL)-based approaches for classifying digitally modulated signals, one method of which involves the use of capsule networks (CAPs) together with cyclic cumulant (CC) features of the signals. These were blindly estimated using cyclostationary signal processing (CSP) and were then input into the CAP for training and classification. The classification performance and the generalization abilities of the proposed approach were tested using two distinct datasets that contained the same types of digitally modulated signals but had distinct generation parameters. The results showed that the classification of digitally modulated signals using CAPs and CCs proposed in …

Faster, Cheaper, And Better Cfd: A Case For Machine Learning To Augment Reynolds-Averaged Navier-Stokes, John Peter Romano Ii

Mechanical & Aerospace Engineering Theses & Dissertations

In recent years, the field of machine learning (ML) has made significant advances, particularly through applying deep learning (DL) algorithms and artificial intelligence (AI). The literature shows several ways that ML may enhance the power of computational fluid dynamics (CFD) to improve its solution accuracy, reduce the needed computational resources and reduce overall simulation cost. ML techniques have also expanded the understanding of underlying flow physics and improved data capture from experimental fluid dynamics.

This dissertation presents an in-depth literature review and discusses ways the field of fluid dynamics has leveraged ML modeling to date. The author selects and describes …

Objectfusion: Multi-Modal 3d Object Detection With Object-Centric Fusion, Q. Cai, Y. Pan, T. Yao, Chong-Wah Ngo, T. Mei

Research Collection School Of Computing and Information Systems

Recent progress on multi-modal 3D object detection has featured BEV (Bird-Eye-View) based fusion, which effectively unifies both LiDAR point clouds and camera images in a shared BEV space. Nevertheless, it is not trivial to perform camera-to-BEV transformation due to the inherently ambiguous depth estimation of each pixel, resulting in spatial misalignment between these two multi-modal features. Moreover, such transformation also inevitably leads to projection distortion of camera image features in BEV space. In this paper, we propose a novel Object-centric Fusion (ObjectFusion) paradigm, which completely gets rid of camera-to-BEV transformation during fusion to align object-centric features across different modalities for …

Balanced Blended Space: Proposing A Universal Theoretical Framework For Combinative Reality, David Smith, Frederick Bianchi

Publications and Research

In today's fragmented societies, a unified framework for communication and collaboration across different realities is crucial. We introduce Balanced Blended Space (BBS) as a framework for describing combinative reality, encompassing virtual, physical, and conceptual realms, all intrinsically connected. Interactions within these environments shape our perceptual space. This paper outlines key axiomatic assumptions, criteria for a universal framework, and fundamental terminology. We identify deep symmetries enabling the BBS framework, including Cognitive and Computational Symmetry, Physical and Virtual Symmetry, Mediation Pathway Symmetry, Space-Time Symmetry, and Sensory Symmetry. We propose tests to determine its viability, emphasizing virtual intelligence as a collaborative partner. We …

3d Garment Collision Simulation Based On Human Skeletal Features, Yuanyuan Chen, Yongjian Huai, Xiaoying Nie, Ke Lang

Journal of System Simulation

Abstract: In order to enhance the realism of garment and human body collision in real-time fabric simulation, an automated human body fitting collision method based on the bounding box and mesh method is proposed. According to the human skeletal structure and garment type, the skeletal information involved in collision simulation is effectively optimized, so as to better obtain the feature points of the human body and semantically segment them. According to the characteristics of skinning animation, simple capsule colliders and mesh colliders are generated to fit the geometric shape of the human body, and the dynamic following of colliders is …

Research On Support Effectiveness Evaluation Method Of Equipment Systems Based On Pert And Abms, Shanzhi Ma, Hongliang Wang, Hua He, Weicheng Lun

Journal of System Simulation

Abstract: The support of an equipment system directly affects its combat effectiveness, and the support effectiveness evaluation of equipment systems has the characteristics of large scope, multiple levels, complete elements, and long process. According to the systematic combat requirements of aircraft equipment, the difficulties in evaluating the support effectiveness of aircraft equipment systems are analyzed. The PERT-based modeling method of airfield support is proposed, and the PERT-based process model of equipment system support activity is established according to the modeling requirements and sequential characteristics of aircraft equipment support tasks. The operational model framework of combinable equipment systems based on ABMS …

Simulation Research On Multi-Antenna Coupled Radiation Of Launch Vehicle In Tower, Fen Zhang, Tao Yu, Yong Han, Longwei He

Journal of System Simulation

Abstract: The signal radiation of the launch vehicle wireless system test in the closed tower of the launching site is very complex. In order to further study the antenna radiation characteristics, especially the multi-antenna coupled radiation in the whole vehicle state, a multi antenna model with tower-vehicle body is established in this paper based on UG modeling technology and Altair Hyper Works 2017 electromagnetic compatibility simulation platform. It involves the method of moments-physical optics (MOM-PO) hybrid algorithm and delineates different calculation areas for different scale divisions, so as to solve quickly and accurately electromagnetic parameters of multi-antenna coupled radiation. The …

Research On Flight Route Planning For Specific Multi-Missions, Lin Zhong, Ming'an Tong, Sheng Li

Journal of System Simulation

Abstract: In order to complete specific aviation missions, a flight route planning model for specific multi-missions is presented. The grid method is used to build a battlefield environment model. Accordingto the complex and real battlefield environment and operational requirements, five target route planning models including distance, fuel consumption, mission completion, ground-to-air threat, and air-to-air threat are proposed. On the basis of specific mission demands, several requirements for missions are analyzed, and the index of mission completion is presented. According to the problem's characteristics, the two-stage solution algorithm for route planning is proposed. In the first stage, the multi-mission sequence is …

Cloud-Edge Collaborative Service Architecture For Lvc Training System, Peng Yong, Miao Zhang, Yue Hu

Journal of System Simulation

Abstract: LVC training, an important means of military training, has received great attention from military and M&S experts. As the virtual and physical elements become more abundant and deeply integrated, LVC training systems become increasingly complex. Aiming at physical-virtual connection, information interaction, simulation computation, run-time control, etc., this paper designs a cloud-edge collaborative service architecture for LVC training systems (CESA-LVC) by reference to cyber-physical systems and cloud-edge computing architectures. CESA-LVC standardizes the structures of LVC training systems from several aspects of intelligent real-time interconnection, joint simulation computation, training auxiliary service, training cognitive decision, and dynamic configuration optimization. It provides a …

Rgb-D Saliency Object Detection Based On Cross-Refinement And Circular Attention, Qingqing Dong, Hao Wu, Wenhua Qian, Fengling Kong

Journal of System Simulation

Abstract: In order to solve the problems that the boundary of the saliency object detection area is vague, and the detection area is incomplete or inaccurate, an RGB-D saliency object detection method based on cross-refinement and circular attention is proposed. A cross-refinement module is designed at the stage of extracting features using encoders, which is used to supplement feature information of each other and improve the feature quality before fusion. It also suppresses the negative impact of poor-quality depth maps and addresses the issue that the edges of the saliency object are blurred. For the features after fusion, the circular …

Data Generation Model-Based Synthetic Sample Imputation Method, Yulin He, Jiaqi Chen, Hepeng Xu, Zhexue Huang, Jianfei Yin

Journal of System Simulation

Abstract: In order to solve the problem of inconsistent probability distribution between synthetic samples by imputation and real samples, a data generation model-based synthetic sample imputation (DGM-SSI) method is proposed. The data generation model of real samples is constructed based on the Gaussian mixture model, and the number of corresponding components of the Gaussian mixture model is determined by the multi-model fusion strategy. The synthetic samples required for model imputation are generated by using the data obtained from the real samples. Specifically, the components of the data generation model and their weights are used to control the generation of synthetic …

Research On Hierarchical Motion Planning Method For Uav Substation Inspection, Songming Jiao, Yunfeng Shou, Jianpeng Bai, Zhu Wang

Journal of System Simulation

Abstract: In order to improve the efficiency and quality of unmanned aerial vehicle (UAV) substation inspection, a hierarchical motion planning method for UAV inspection based on front-end path search and back-end trajectory generation is proposed. At the front end, an improved A* algorithm is proposed to increase the planning speed and reduce the path turnings by constraining the direction of node expansion and modifying the heuristic function. At the back end, a minimum-snap trajectory optimization combined with the waypoint filtering method is proposed to generate a smooth trajectory that is beneficial for UAV inspection and tracking. The simulation results show …

Aircraft Assignment Method For Optimal Utilization Of Maintenance Intervals, Runxia Guo, Yifu Wang

Journal of System Simulation

Abstract: The aircraft assignment problem is studied from a maintenance assurance perspective. In order to ensure its continuous airworthiness, civil aircraft are required to perform maintenance tasks, i. e., scheduled inspections, at specified intervals. The scheduled inspection interval is usually controlled by the number of flight cycles (FC), flight hours (FH), or flight days (FD), whichever comes first. In order to make balanced use of the inspection interval, an aircraft assignment model for a given fleet size is developed to optimize the maintenance interval utilization, and it is solved by a reinforcement learning algorithm to minimize the variance of the …

Fall Detection Method Of Digital Sequence Based On Fusion Strategy, Riming Sun, Hu Guo, Li Zou, Jiaqi Mao, Shengfa Wang

Journal of System Simulation

Abstract: Falls have become the primary cause of disability due to injury for the elderly. Timely and accurate warning of fall events is an important link to rescue work. In order to improve the accuracy of fall detection, a fall detection method based on a fusion strategy is proposed, which considers both the integrity of high-dimensional digital sequences and the specificity of different dimensions. The input digital sequences obtained from the wrist portable sensor are processed by window segmentation according to the saliency of resultant acceleration, so as to ensure the timing of the data and improve the identifiability of …

Virtual Navigation Path Planning Based On Octree Potential Field For Endonasal Endoscope, Wenjing Li, Yanlin Luo, Yuhui Wang, Li Zhu

Journal of System Simulation

Abstract: Virtual navigation can intuitively display the internal structure of human tissue from multiple viewpoints. The navigation path planning algorithm is the key to achieving excellent navigation effects. The traditional centerline extraction algorithm can ensure a wide field of view during navigation, but the time efficiency is not high enough on the complex nasal-skull base volume model. To solve the problem, a rapid navigation path planning algorithm based on the octree potential field is proposed. The space outside the obstacles is modeled by an octree, and the octree potential field is constructed by calculating the potential of all the octree …

Training Simulation Scenario Generation Based On Particle Swarm Optimization, Jianxing Gong, Zimu Wang, Qilong Yang

Journal of System Simulation

Abstract: The training effect in the training simulation scenario is not ideal. Therefore, in order to obtain the training simulation scenario with a better training effect, the training simulation scenario is optimized, and a training simulation scenario generation method based on the PSO algorithm is proposed. A fitness function is constructed based on the improved situation assessment method of the power field model, and the ability weight parameters are determined by combining the improved AHP with computer simulation software; by instantiating particles with the attributes of the combat platform, the particle swarm optimization algorithm is improved to solve the optimization …

Survey On Intelligent Wargaming: Tactical & Campaign Wargame And Strategic Game From Game-Theoretic Perspective, Junren Luo, Wanpeng Zhang, Fengtao Xiang, Chaoyuan Jiang, Jing Chen

Journal of System Simulation

Abstract: Wargaming is a pre-practice activity to study national security and competition, military conflict and war, crisis management, and other major strategic issues. An intelligent wargaming system needs the ability of artificial intelligence technology. This paper briefly summarizes the research progress of intelligent game, the evolution of wargaming, intelligent wargaming, and strategic gaming methods. From the perspective of game theory, it analyzes the game problem model for intelligent wargaming and sorts out the application mode of intelligent wargaming and the organization mode of a strategic game. An intelligent wargaming service-oriented architecture based on cloud native is proposed. Pre-training method for …

Deceptive Path Planning In Fog Of War, Dejun Chen, Zihao Fang, Yunxiu Zeng, Kai Xu

Journal of System Simulation

Abstract: Computer generated forces (CGFs) are virtual combat force objects created by computers and critical elements in the field of military simulation. Deceptive path planning is a basic method of deceptive behavior, which is important for improving the intelligence and competitiveness of CGFs. However, the current combination of deceptive behavior and military simulation is insufficient, and classical path planning methods cannot effectively take advantage of the partial observability of the battlefield and achieve better deceptive effects. To solve these problems, we propose four new deceptive path planning methods by re-defining a single circular fog road network based on road networks …

Formation Obstacle Avoidance Algorithm Based On Joint Virtual Sub-Target And Boundary Force, Man Wang, Dapeng Li, Lianghui Ding, Tianlin Zhu

Journal of System Simulation

Abstract: In view of the formation control of leader-follower swarm and obstacle avoidance in artificial potential field method in unmanned aerial vehicle (UAV) swarm formation system under complex environmental conditions, an obstacle avoidance algorithm for UAV swarm formation based on joint virtual sub-target and boundary force (JVBF) is proposed. The leader-follower method based on a virtual sub-target is used, and the modified force function is optimized to realize the formation control of the UAV swarm, so as to help the follower UAV to recover the formation quickly; the artificial potential field method based on boundary force is used for local …

Research On Artificial Population Generation And Application Based On Genetic Algorithm, Hongli Zhang, Jingshuang Deng

Journal of System Simulation

Abstract: High-precision micro-population data are one of the key basic data for simulation systems such as disease spread, traffic travel, and emergency events. In reality, computer-generated artificial populations are often used for simulation. Due to computational efficiency and standardization of generation steps, the iterative proportional fitting method is currently used for artificial population synthesis. However, it has strict requirements on basic data and faces zero-unit and data representational deviation problems, and it fails to guarantee the fitting at the individual and family levels at the same time. In order to overcome this deficiency, an improved genetic algorithm using a simulated …

Research On Intelligent Statistical Analysis Of Wargaming Data Based On Nl2sql, Laixiang Yin, Zhiqiang Li, Qiongying Fu

Journal of System Simulation

Abstract: In the face of massive wargaming data, the traditional interface query method can no longer meet the commander's requirements, i. e., fast, comprehensive, and accurate data querying. Through indepth analysis of the characteristics of wargaming data and the defects of the mainstream natural language to struct query language (NL2SQL) model, a set of solutions for the intelligent statistical query of wargaming data is presented. Due to the lack of datasets, a wargaming dataset construction scheme based on human-machine assistance and dynamic iteration is provided. In order to solve the timesensitive problem of wargaming querying, time expression recognition and standardization …