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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 2023 National Key Laboratory of Modeling and Simulation for Complex Systems, Beijing Simulation Center, Beijing 100854, China

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.


Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian 2023 University of Minnesota - Twin Cities

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 …


Robust Bidirectional Poly-Matching, Ween Jiann LEE, Maksim TKACHENKO, Hady Wirawan LAUW 2023 Singapore Management University

Robust Bidirectional Poly-Matching, Ween Jiann Lee, Maksim Tkachenko, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

A fundamental problem in many scenarios is to match entities across two data sources. It is frequently presumed in prior work that entities to be matched are of comparable granularity. In this work, we address one-to-many or poly-matching in the scenario where entities have varying granularity. A distinctive feature of our problem is its bidirectional nature, where the 'one' or the 'many' could come from either source arbitrarily. Moreover, to deal with diverse entity representations that give rise to noisy similarity values, we incorporate novel notions of receptivity and reclusivity into a robust matching objective. As the optimal solution to …


Designing A Human-Centered Intelligent System To Monitor & Explain Abnormal Patterns Of Older Adults, Min Hun LEE, Daniel P. Siewiorek, Alexandre Bernardino 2023 Singapore Management University

Designing A Human-Centered Intelligent System To Monitor & Explain Abnormal Patterns Of Older Adults, Min Hun Lee, Daniel P. Siewiorek, Alexandre Bernardino

Research Collection School Of Computing and Information Systems

Older adult care technologies are increasingly explored to support the independent living of older adults by monitoring their abnormal activities and informing caregivers to provide intervention if necessary. However, the adoption of these technologies remains challenging due to several factors (e.g. lack of usability). In this work, we present a human-centered, intelligent system for older adult care. Our proposed designs of the system were created based on the findings from a focus group session with caregivers. This system monitors the abnormal activities of an older adult using wireless motion sensors and machine learning models. In addition, unlike previous work that …


Deconstructing The Software Factory: A Practical Application Of Interorganizational Network Analysis, Zachary O. Ryan, Mark Reith, Clay Koschnick 2023 Air Force Institute of Technology

Deconstructing The Software Factory: A Practical Application Of Interorganizational Network Analysis, Zachary O. Ryan, Mark Reith, Clay Koschnick

Faculty Publications

Over the past 5 years, the number of DoD software organizations that employ nontraditional organizational structures has increased. These organizations, commonly referred to as software factories, often employ the network-based organizational structures found within high-technology industries. This article details ways in which network analysis techniques can be used to create a big picture view of these nontraditional organizations. Drawing on methodologies employed by network researchers, the authors develop and present an interorganizational analysis process that highlights a program's social and economic structures. Following the case history approach, they demonstrate the applicability of this approach by analyzing an emergent DoD software …


Icl-D3ie: In-Context Learning With Diverse Demonstrations Updating For Document Information Extraction, Jiabang HE, Lei WANG, Yi HU, Ning LIU, Hui LIU, Xing XU, Heng Tao SHEN 2023 University of Electronic Science and Technology of China

Icl-D3ie: In-Context Learning With Diverse Demonstrations Updating For Document Information Extraction, Jiabang He, Lei Wang, Yi Hu, Ning Liu, Hui Liu, Xing Xu, Heng Tao Shen

Research Collection School Of Computing and Information Systems

arge language models (LLMs), such as GPT-3 and ChatGPT, have demonstrated remarkable results in various natural language processing (NLP) tasks with in-context learning, which involves inference based on a few demonstration examples. Despite their successes in NLP tasks, no investigation has been conducted to assess the ability of LLMs to perform document information extraction (DIE) using in-context learning. Applying LLMs to DIE poses two challenges: the modality and task gap. To this end, we propose a simple but effective in-context learning framework called ICL-D3IE, which enables LLMs to perform DIE with different types of demonstration examples. Specifically, we extract the …


Underwater Image Translation Via Multi-Scale Generative Adversarial Network, Dongmei YANG, Tianzi ZHANG, Boquan LI, Menghao LI, Weijing CHEN, Xiaoqing LI, Xingmei WANG 2023 Singapore Management University

Underwater Image Translation Via Multi-Scale Generative Adversarial Network, Dongmei Yang, Tianzi Zhang, Boquan Li, Menghao Li, Weijing Chen, Xiaoqing Li, Xingmei Wang

Research Collection School Of Computing and Information Systems

The role that underwater image translation plays assists in generating rare images for marine applications. However, such translation tasks are still challenging due to data lacking, insufficient feature extraction ability, and the loss of content details. To address these issues, we propose a novel multi-scale image translation model based on style-independent discriminators and attention modules (SID-AM-MSITM), which learns the mapping relationship between two unpaired images for translation. We introduce Convolution Block Attention Modules (CBAM) to the generators and discriminators of SID-AM-MSITM to improve its feature extraction ability. Moreover, we construct style-independent discriminators that enable the discriminant results of SID-AM-MSITM to …


Hallucination Detection: Robustly Discerning Reliable Answers In Large Language Models, Yuyuan CHEN, Qiang FU, Yichen YUAN, Zhihao WEN, Ge FAN, Dayiheng LIU, Dongmei ZHANG, Zhixu LI, Yanghua XIAO 2023 Singapore Management University

Hallucination Detection: Robustly Discerning Reliable Answers In Large Language Models, Yuyuan Chen, Qiang Fu, Yichen Yuan, Zhihao Wen, Ge Fan, Dayiheng Liu, Dongmei Zhang, Zhixu Li, Yanghua Xiao

Research Collection School Of Computing and Information Systems

Large language models (LLMs) have gained widespread adoption in various natural language processing tasks, including question answering and dialogue systems. However, a major drawback of LLMs is the issue of hallucination, where they generate unfaithful or inconsistent content that deviates from the input source, leading to severe consequences. In this paper, we propose a robust discriminator named RelD to effectively detect hallucination in LLMs' generated answers. RelD is trained on the constructed RelQA, a bilingual question-answering dialogue dataset along with answers generated by LLMs and a comprehensive set of metrics. Our experimental results demonstrate that the proposed RelD successfully detects …


Hrgcn: Heterogeneous Graph-Level Anomaly Detection With Hierarchical Relation-Augmented Graph Neural Networks, Jiaxi LI, Guansong PANG, Ling CHEN, Mohammad-Reza NAMAZI-RAD 2023 Singapore Management University

Hrgcn: Heterogeneous Graph-Level Anomaly Detection With Hierarchical Relation-Augmented Graph Neural Networks, Jiaxi Li, Guansong Pang, Ling Chen, Mohammad-Reza Namazi-Rad

Research Collection School Of Computing and Information Systems

This work considers the problem of heterogeneous graph-level anomaly detection. Heterogeneous graphs are commonly used to represent behaviours between different types of entities in complex industrial systems for capturing as much information about the system operations as possible. Detecting anomalous heterogeneous graphs from a large set of system behaviour graphs is crucial for many real-world applications like online web/mobile service and cloud access control. To address the problem, we propose HRGCN, an unsupervised deep heterogeneous graph neural network, to model complex heterogeneous relations between different entities in the system for effectively identifying these anomalous behaviour graphs. HRGCN trains a hierarchical …


Utilizing Graph Thickness Heuristics On The Earth-Moon Problem, Robert C. Weaver 2023 York College of Pennsylvania

Utilizing Graph Thickness Heuristics On The Earth-Moon Problem, Robert C. Weaver

Rose-Hulman Undergraduate Mathematics Journal

This paper utilizes heuristic algorithms for determining graph thickness in order to attempt to find a 10-chromatic thickness-2 graph. Doing so would eliminate 9 colors as a potential solution to the Earth-moon Problem. An empirical analysis of the algorithms made by the author are provided. Additionally, the paper lists various graphs that may or nearly have a thickness of 2, which may be solutions if one can find two planar subgraphs that partition all of the graph’s edges.


Training Simulation Scenario Generation Based On Particle Swarm Optimization, Jianxing Gong, Zimu Wang, Qilong Yang 2023 College of Intelligence Science, National University of Defense Technology, Changsha 410073, China

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 …


Deceptive Path Planning In Fog Of War, Dejun Chen, Zihao Fang, Yunxiu Zeng, Kai Xu 2023 College of Systems Engineering, National University of Defense Technology, Changsha 410073, China

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 …


3d Garment Collision Simulation Based On Human Skeletal Features, Yuanyuan Chen, Yongjian Huai, Xiaoying Nie, Ke Lang 2023 School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China

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 …


Method For Extracting Data During Flight Phase Of Ski Jumping Based On Monocular Video, Ziyi Shen, Meng Yang, Chao Yang, Weidi Tang, Xie Wu, Yu Liu, Bin Sheng 2023 School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China

Method For Extracting Data During Flight Phase Of Ski Jumping Based On Monocular Video, Ziyi Shen, Meng Yang, Chao Yang, Weidi Tang, Xie Wu, Yu Liu, Bin Sheng

Journal of System Simulation

Abstract: To solve the problem of the high difficulty factor of ski jumping and the difficulty of extracting data of this sport due to the danger of invasive devices such as wearable sensors and high price, a method for extracting data during the flight phase of ski jumping based on monocular video is proposed. The distortion and background clutter of the monocular video are preprocessed. The distortion of the captured images is corrected by calibrating camera parameters, and the background is removed by the inter-frame difference method. The human pose recognition library, namely OpenPose is used to initially identify the …


Research On Support Effectiveness Evaluation Method Of Equipment Systems Based On Pert And Abms, Shanzhi Ma, Hongliang Wang, Hua He, Weicheng Lun 2023 AVIC Chengdu Aircraft Design & Research Institute, Chengdu 610091, China

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 2023 PLA 63723 Troops, Xinzhou 036300, China

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 …


Survey On Intelligent Wargaming: Tactical & Campaign Wargame And Strategic Game From Game-Theoretic Perspective, Junren Luo, Wanpeng Zhang, Fengtao Xiang, Chaoyuan Jiang, Jing Chen 2023 College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China

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 …


Research On Flight Route Planning For Specific Multi-Missions, Lin Zhong, Ming'an Tong, Sheng Li 2023 College of Electronic Information, Xijing University, Xi'an 710123, China

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 …


Research On Artificial Population Generation And Application Based On Genetic Algorithm, Hongli Zhang, Jingshuang Deng 2023 School of Management Science and Engineering, Southwestern University of Finance and Economics, Chengdu 611130, China

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 …


Cloud-Edge Collaborative Service Architecture For Lvc Training System, Peng Yong, Miao Zhang, Yue Hu 2023 College of Systems Engineering, National University of Defense Technology, Changsha 410073, China

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 …


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