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Systemic Risks Analysis In International Crude Oil Market: Evidence And Countermeasures, Han Zhang, Yuejun Zhang Jan 2026

Systemic Risks Analysis In International Crude Oil Market: Evidence And Countermeasures, Han Zhang, Yuejun Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Crude oil, often referred to as the “lifeblood” of the modern economy, plays a pivotal role in global economic stability and energy security. However, with the recurrence of crises in recent years, such as the the Russia-Ukraine conflict, escalating tensions in the Middle East, and intensifying trade frictions, the international crude oil market has been facing complex systemic risks, which are accelerated by persistent geopolitical conflicts, fragile supply-demand structures, and the intertwining of macroeconomic and financial uncertainties and so on. For China, with crude oil import dependence remaining above 70% for a prolonged period, economic and social development faces the …

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Satellite-Derived Bathymetry In Island Coastal Zones: Technology, Shilin Tang, Yuye Huang, Yongming Liu, Jianping Yin, Deke Chen, Ronggang Huang, Shuang Li Jan 2026

Satellite-Derived Bathymetry In Island Coastal Zones: Technology, Shilin Tang, Yuye Huang, Yongming Liu, Jianping Yin, Deke Chen, Ronggang Huang, Shuang Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

Shallow bathymetry data constitute the core foundational information underpinning the ecological, resource, and strategic values of island and coastal zones. Satellite-derived bathymetry has evolved into a key technical means for large-scale acquisition of shallow bathymetry information. Focusing on satellite-based lidar bathymetry, optical imaging bathymetry, and synthetic aperture radar (SAR) bathymetry, this study systematically summarizes the core principles, applicable scenarios, technical strengths, and inherent limitations of each technology. It is shown that satellite-derived bathymetry has undergone an evolutionary shift from theoretical construction to practical application, and from single-method, single-data-source approaches to multi-technology, multi-source data fusion frameworks. In the future, to meet …

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Identifying And Overcoming Some Operational Limitations Of Reconfigurable Intelligent Surfaces In 5g And Beyond Wireless Networks, Souvik Deb Jan 2026

Identifying And Overcoming Some Operational Limitations Of Reconfigurable Intelligent Surfaces In 5g And Beyond Wireless Networks, Souvik Deb

Doctoral Theses

Reconfigurable intelligent surfaces (RIS) can dynamically reshape the propagation environment to enhance signal strength, spectral efficiency and reliability in 5th generation (5G) cellular as well as device to device (D2D) communications. However, to reap such benefits, a range of practical and operational challenges need to be addressed for effectively utilizing RIS in realistic urban environments. This includes maintaining line of sight (LoS) between the RIS and the communicating devices for reliable signal reflection in millimeter wave (mmWave) communication, reducing high channel estimation overhead for communication using multipath rich channels and preventing violation of strict latency constraints due to high complexity …

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Gatos – Xi. Excess Dust Heating In The Narrow-Line Regions Of Nearby Agn Revealed With Jwst/Miri, Houda Haidar, David J. Rosario, Ismael García-Bernete, Almudena Alonso-Herrero, Anelise Audibert, Steph Campbell, Chris M. Harrison, Tiago Costa, Laura Hermosa Muñoz, Françoise Combes, Dimitra Rigopoulou, Claudio Ricci, Cristina Ramos Almeida, Enrica Bellocchi, Peter Boorman, Andrew Bunker, Richard Davies, Daniel Delaney, Tanio Díaz Santos, Federico Esposito, Enrique Lopez Rodriguez, Et. Al. Jan 2026

Gatos – Xi. Excess Dust Heating In The Narrow-Line Regions Of Nearby Agn Revealed With Jwst/Miri, Houda Haidar, David J. Rosario, Ismael García-Bernete, Almudena Alonso-Herrero, Anelise Audibert, Steph Campbell, Chris M. Harrison, Tiago Costa, Laura Hermosa Muñoz, Françoise Combes, Dimitra Rigopoulou, Claudio Ricci, Cristina Ramos Almeida, Enrica Bellocchi, Peter Boorman, Andrew Bunker, Richard Davies, Daniel Delaney, Tanio Díaz Santos, Federico Esposito, Enrique Lopez Rodriguez, Et. Al.

Faculty Publications

We present James Webb Space Telescope/Mid-Infrared Instrument imaging of eight nearby active galactic nuclei (AGN) from the GATOS (Galactic Activity, Torus, and Outflow Survey) survey to investigate the physical conditions of extended dust in their narrow-line regions (NLRs). In four galaxies (ESO 428–G14, NGC 4388, NGC 3081, and NGC 5728), we detect spatially resolved dust structures extending ∼100–200 pc along the NLR. In these systems, we find a strong link between the morphology of the dust, the radio ejecta, and the coronal [Si VI] emission, implying that dust carries imprints of the processes shaping the NLR. Using spatially resolved …

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Table Of Contents Jan 2026

Table Of Contents

Journal of the South Carolina Academy of Science

No abstract provided.

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Evaluating Corruption Defenses On Learning Adversarial Robustness, Roland Yang, Akhil Kanthamneni Jan 2026

Evaluating Corruption Defenses On Learning Adversarial Robustness, Roland Yang, Akhil Kanthamneni

Journal of the South Carolina Academy of Science

No abstract provided.

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A Hybrid Cooling System Utilizing Active Air And Phase Change Material Polyethylene Glycol In A Lithium-Ion Battery Pack, Arieleus Taine Jan 2026

A Hybrid Cooling System Utilizing Active Air And Phase Change Material Polyethylene Glycol In A Lithium-Ion Battery Pack, Arieleus Taine

Journal of the South Carolina Academy of Science

Batteries have become one of the most important components of electronic devices. However, a large issue lies in overheating batteries, which decreases their performance and lifespan. Although cooling systems have been researched to combat this, the combination of phase change material polyethylene glycol (PEG) and fans has not been observed. The purpose of this study was to determine if a hybrid system consisting of PEG and air cooling would decrease temperatures compared to individual cooling systems such as just air cooling. It was hypothesized that the hybrid cooling system would have lower overall temperatures as compared to individual active and …

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The Comparative Effect Of Four Reflective Coatings On The Thermal Performance Of Residential Roofing In Climate Zone 8b, Henry Holton Jan 2026

The Comparative Effect Of Four Reflective Coatings On The Thermal Performance Of Residential Roofing In Climate Zone 8b, Henry Holton

Journal of the South Carolina Academy of Science

No abstract provided.

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Ultrasonic Extraction-Based Analysis Of Persistent Organic Pollutants In Blubber From False Killer Whales, Michael O. Eze, Eva Borras, Mitchell M. Mccartney, Don R. Bergfelt, Kristi L. West, Sarah E. Hooper, Cristina E. Davis Jan 2026

Ultrasonic Extraction-Based Analysis Of Persistent Organic Pollutants In Blubber From False Killer Whales, Michael O. Eze, Eva Borras, Mitchell M. Mccartney, Don R. Bergfelt, Kristi L. West, Sarah E. Hooper, Cristina E. Davis

Chemistry Faculty Research & Creative Works

In view of the toxic effects of persistent organic pollutants (POPs), fast and effective assessment of their concentrations in marine mammals is important for understanding individual and population-level health impacts. This study developed an ultrasonic-based method that is less time-consuming, uses minimal solvent, and thus is more sustainable than the gold standard Soxhlet method for accurate analysis of organochlorine pesticides (OCs), polychlorinated biphenyls (PCBs), and benzene hexachlorides (BHC) in false killer whale blubber. This method was developed by comparing concentrations of POPs obtained using the traditional Soxhlet and novel ultrasonic extraction methods using blubber from false killer whales (n = …

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Nonresonance For Problems Involving (P, Q)-Laplacian Equations With Nonlinear Perturbations, E. Lopera, Nsoki Mavinga, D. Sánchez Jan 2026

Nonresonance For Problems Involving (P, Q)-Laplacian Equations With Nonlinear Perturbations, E. Lopera, Nsoki Mavinga, D. Sánchez

Mathematics & Statistics Faculty Works

We are concerned with the existence of solutions of (p, q)-Laplacian problems that include nonlinear perturbation terms in both the differential equations and the boundary. Using variational methods and critical point theory, we prove the existence of weak solutions for the nonlinear problem when the nonlinearities involved remain asymptotically below the infimum of the set of eigenvalues of the (p, q)-Laplacian problem with weights and a spectral parameter present in both the differential equation and the boundary. Additionally, we establish an existence result for the nonlinear problem when the nonlinearities involved remain asymptotically below …

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Natural Protective Mechanisms Of Cucumis Callosus Leaves In Escherichia Species-Induced Urinary Tract Infection: An Integrated In Silico And In Vivo Study, Meenal Sahu, Tripti Paliwal, Radhika Joshi, Arya Kuhu Vishwapriya, Namita Misra, Smita Jain, Gautam Singhvi, Gulshan Kumar, Devesh U. Kapoor, Dipjyoti Chakraborty, Swapnil Sharma Jan 2026

Natural Protective Mechanisms Of Cucumis Callosus Leaves In Escherichia Species-Induced Urinary Tract Infection: An Integrated In Silico And In Vivo Study, Meenal Sahu, Tripti Paliwal, Radhika Joshi, Arya Kuhu Vishwapriya, Namita Misra, Smita Jain, Gautam Singhvi, Gulshan Kumar, Devesh U. Kapoor, Dipjyoti Chakraborty, Swapnil Sharma

Michigan Tech Publications

Leaves of Cucumis callosus, traditionally employed in Ayurvedic medicine for the treatment of urinary disorders, were investigated in depth for their therapeutic potential against bacterially induced urinary tract infection (UTI) for the first time. The present work is the first to explore the antibacterial activity of C. callosus leaf fractions with an integrative in silico, in vitro, and in vivo approach. Through bioassay-guided fractionation, the chloroform fraction (F1) was identified as the most active, exhibiting potent activity against Uropathogenic Escherichia spp. species. Liquid chromatography–mass spectrometry (LC-MS) analysis of F1 revealed the presence of bioactive compounds, including stigmasterol, 1,2,3,4-tetrahydroisoquinoline, lactose, hydroxy(mesityl)acetic …

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Estimation Of Net Premium For Flight Delay Insurance Using The Aggregate Loss Model: A Case Study Of Indonesia Otas, Azka Nurul Husna, Yulial Hikmah, Ira Rosianal Hikmah Jan 2026

Estimation Of Net Premium For Flight Delay Insurance Using The Aggregate Loss Model: A Case Study Of Indonesia Otas, Azka Nurul Husna, Yulial Hikmah, Ira Rosianal Hikmah

Jurnal Vokasi Indonesia

Air transportation, as one of the most chosen transportation modes, is frequently susceptible to delays. Flight Delay Insurance offers a vital solution to mitigate the financial losses associated with this risk. Premium pricing is a key factor influencing the decision to purchase this insurance, particularly on Online Travel Agent (OTA) platforms where product offerings are often highly comparable. The aggregate loss method is employed herein to ascertain the net premium (or pure premium) price. The loss severity component (X) is modeled using an empirical distribution, while the loss frequency component (N) is modeled using a Negative Binomial distribution with parameters …

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3d Object Tracking Registration Based On Improved Rbot Method, Jiarui Zhou, Haihua Cui, Pengcheng Li, Shihao Gu, Huipu Hao, Xifu Zhao, Anan Zhao, Tao Jiang Jan 2026

3d Object Tracking Registration Based On Improved Rbot Method, Jiarui Zhou, Haihua Cui, Pengcheng Li, Shihao Gu, Huipu Hao, Xifu Zhao, Anan Zhao, Tao Jiang

Journal of System Simulation

Abstract: To address the limitations of region-based object tracking (RBOT) in handling isotropic objects and scenarios with similar foreground-background colors, an improved method integrating edge features is proposed. The approach employs edge detection to extract object contours and designs a region segmentation strategy incorporated into an energy function framework to optimize internal line and edge consistency, thereby enhancing adaptability in dynamic environments and improving pose estimation accuracy. Validation through augmented reality assembly experiments on an aero-engine demonstrates that the proposed method effectively reduces rotational and translational errors, achieving initialization deviations of less than 1.5° and 0.5%, respectively. For static …

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3d Reconstruction For Stadium Cad Drawings Based On Graphic Element Arrangement Pattern Analysis, Shang Ma, Mengyu Zhang, Lan Zhang, Gang Yang Jan 2026

3d Reconstruction For Stadium Cad Drawings Based On Graphic Element Arrangement Pattern Analysis, Shang Ma, Mengyu Zhang, Lan Zhang, Gang Yang

Journal of System Simulation

Abstract: To address the issue of the time-consuming and labor-intensive manual conversion of two-dimensional CAD design drawings of buildings into three-dimensional models, and leveraging the characteristic that stadiums contain a large number of repetitively and regularly arranged objects, this study proposes a similar graphical element detection algorithm. This algorithm detects similarities between graphical elements by constructing their bounding boxes and calculating the L2-Norm distance, identifying all graphical elements of the same type within the CAD drawing. Furthermore, a transformation sequence detection algorithm is proposed. Based on the geometric transformation relationships between graphical elements, a geometric transformation space is defined. By …

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Visual Relocalization Method Combining Region Classification And Local Feature Enhancement, Yining Wang, Yanli Liu, Guanyu Xing Jan 2026

Visual Relocalization Method Combining Region Classification And Local Feature Enhancement, Yining Wang, Yanli Liu, Guanyu Xing

Journal of System Simulation

Abstract: Visual relocalization tasks have important application value in fields such as digital twin and augmented reality. The current mainstream methods still face challenges such as mismatch between coordinate regression scale and receptive field and insufficient attention to local information. A visual relocalization method that combines region classification and local feature enhancement is proposed. The coordinate regression problem in large space is transformed into a multi-region classification problem and a coordinate regression problem inside a small scene, which significantly reduces the uncertainty of coordinate regression and makes the network globally have a large receptive field. A conditioning layer using deep …

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Diffusion Model For Human Motion Generation With Fine-Grained Text And Spatial Control Signals, Binze Jiang, Wenfeng Song, Xia Hou, Shuai Li Jan 2026

Diffusion Model For Human Motion Generation With Fine-Grained Text And Spatial Control Signals, Binze Jiang, Wenfeng Song, Xia Hou, Shuai Li

Journal of System Simulation

Abstract: To improve the accuracy, controllability, and realism of text-driven human motion generation, a novel method is proposed that integrates fine-grained textual semantics with spatial control signals. Within the diffusion model framework, both global text tokens and body-part-level local tokens are introduced. These are encoded using CLIP to obtain corresponding features, which are then fed into the motion diffusion model to enable fine control over different body parts. Spatial guidance is used to dynamically adjust joint positions during the diffusion denoising process, ensuring that the generated motion adheres to spatial constraints. Realism guidance is incorporated to enhance the naturalness and …

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Virtual Reality Rehabilitation Training System Based On Multimodal Brain-Computer Interface, Jing Qu, Kaining Fang, Shantong Zhu, Lingguo Bu Jan 2026

Virtual Reality Rehabilitation Training System Based On Multimodal Brain-Computer Interface, Jing Qu, Kaining Fang, Shantong Zhu, Lingguo Bu

Journal of System Simulation

Abstract: The aging population has led to an increasing demand for rehabilitation for cognitive and motor functions. In response to the lack of interest in traditional rehabilitation and the absence of objective physiological assessment in existing virtual reality (VR) rehabilitation systems, a VR rehabilitation training system based on multimodal brain computer interface is developed by integrating VR interaction, near-infrared brain functional imaging, and motion capture technology. An immersive cognitive-motor integrated training environment was constructed to guide users in completing upper limb tasks. By recruiting subjects and synchronously collecting brain network data and Kinect upper limb motion parameters, multimodal assessment …

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Defect Detection Method Based On Hierarchical Microscopic Feature Modeling And Simulation, Jing Zou, Xu Tan, Junji Mao, Haidong Gao, Jianrong Tan Jan 2026

Defect Detection Method Based On Hierarchical Microscopic Feature Modeling And Simulation, Jing Zou, Xu Tan, Junji Mao, Haidong Gao, Jianrong Tan

Journal of System Simulation

Abstract: To address the challenge of detecting small and low-contrast defects in complex microscopic images, a defect method technology based on hierarchical microscopic feature modeling and simulation is proposed. The method is built on the RT-DETR (real-time detection transformer)framework to construct the HM-RTDETR (hierarchical microscopic RT-DETR) model. It maintains the global feature modeling ability of the Transformer and introduces a Dense O2O-Mosaic, a high-density one-to-one Mosaic augmentation strategy, to increase supervision density for small samples. A depthwise separable convolution (DWConv) module is used to enhance local detail extraction in microscopic textures, and a learnable PatchExpand module is applied …

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Material Reconstruction From Single Image Combining Neural Networks With Singular Value Decomposition, Zhiqiang Li, Xukun Shen, Yong Hu, Xueyang Zhou, Yifan Chen Jan 2026

Material Reconstruction From Single Image Combining Neural Networks With Singular Value Decomposition, Zhiqiang Li, Xukun Shen, Yong Hu, Xueyang Zhou, Yifan Chen

Journal of System Simulation

Abstract: The tabulated BRDFs (bidirectional reflectance distribution function) can realistically reproduce the surface appearance of objects. However, due to their high-dimensional characteristics and the fact that a single planar image contains limited reflectance information and small differences, methods for estimating tabulated BRDFs typically require complex equipment or the capture of multiple images. To address this issue, a method is proposed for reconstructing material properties from a single image by combining neural networks with singular value decomposition. The singular value decomposition is introduced to compress the material into a lower-dimensional space. The task of solving the tabulated BRDFs is simplified to …

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Full-Body Co-Speech Gesture Generation Based On Spatial-Temporal Enhanced Generation Model, Shuozhe Zhang, Wenfeng Song, Xia Hou, Shuai Li Jan 2026

Full-Body Co-Speech Gesture Generation Based On Spatial-Temporal Enhanced Generation Model, Shuozhe Zhang, Wenfeng Song, Xia Hou, Shuai Li

Journal of System Simulation

Abstract: Full-body co-speech gesture generation significantly enhances the interactivity of virtual digital humans, requiring generated gestures to not only align accurately with speech but also demonstrate realistic full-body dynamics. To address limitations of existing methods—Transformer-based approaches often overlook temporal features of action sequences, while diffusion model-based ones inadequately capture spatial correlations between body parts, a full-body action generation method integrating diffusion models, Mamba, and attention mechanisms is proposed. We introduce the spatial self-attention-temporal state space model (STMamba Layer) as the core of denoising network to extract
inter-part spatial features and intra-part temporal features, thus enhancing action quality and diversity. …

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Vrbt: Vr Badminton Training With Multitask Injury Alerts Based On Lightweight 3d Skeletal Reconstruction, Yuning Zhu, Meng Yang, Tianyue Chen, Weiliang Meng Jan 2026

Vrbt: Vr Badminton Training With Multitask Injury Alerts Based On Lightweight 3d Skeletal Reconstruction, Yuning Zhu, Meng Yang, Tianyue Chen, Weiliang Meng

Journal of System Simulation

Abstract: To overcome the limitations of traditional badminton training, a VR training method that integrates multiple models for collaborative simulation is proposed. A "perception-decision- interaction" framework is developed within Unity, featuring diverse training modules powered by a physics engine for realistic trajectory simulation. The system employs a lightweight MHFormer for 3D pose estimation and a novel multi-task model (enhanced injury prediction system, EIPS) that combines random forest and XGBoost to jointly assess injury risk. This approach offers a solution for balancing real-time performance with accuracy in skeleton reconstruction and enables personalized training through dynamic risk assessment.

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Addressing The Void Of Ai Policies In Education For Students With Specific Learning Disabilities, Mikyung Shin, Fatmana Deniz, Latesha Watson, Cynthia Dieterich, Kathy B. Ewoldt, Friggita Johnson, Jennifer E. Kong, Sung Hee Lee, April Whitehurst Jan 2026

Addressing The Void Of Ai Policies In Education For Students With Specific Learning Disabilities, Mikyung Shin, Fatmana Deniz, Latesha Watson, Cynthia Dieterich, Kathy B. Ewoldt, Friggita Johnson, Jennifer E. Kong, Sung Hee Lee, April Whitehurst

Education Faculty Articles and Research

The purpose of this study was to identify the current state of artificial intelligence (AI) policies in U.S. education and propose actionable recommendations through large language model–based topic modeling and Delphi surveys. Out of 12 policy documents released between 2015 and 2025, only two documents (National Center for Learning Disabilities, 2024; W.A. v. Clarksville/Montgomery County School System, 2024) specifically addressed learning disabilities. Policy documents addressing topics such as AI-driven risk assessment, data protection, legal risk management, and ethical guidelines covering other disabilities and general AI in education policy were provided as baselines that could be discussed and validated through …

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Inverse Kinematics 3d Human Modeling Simulation Based On Multi-View Vision, Guoyu Fang, Yanze Li, Kai Chen, Xiaodong Zhao, Zizhuo Hu, Mingshi Yang, Wanqing Wu, Zichen Wang, Wenkai Guo Jan 2026

Inverse Kinematics 3d Human Modeling Simulation Based On Multi-View Vision, Guoyu Fang, Yanze Li, Kai Chen, Xiaodong Zhao, Zizhuo Hu, Mingshi Yang, Wanqing Wu, Zichen Wang, Wenkai Guo

Journal of System Simulation

Abstract: In autonomous driving simulation and industrial virtual reality simulation, there is a high demand for accuracy and robustness in 3D human body modeling. However, current joint-based human modeling approaches suffer from issues such as continuous modeling jitter, local distortion, and poor adaptability to occlusion, which degrade model quality and limit the development of practical applications such as intelligent driving and digital factories. To address these challenges, this paper proposes a multi-view vision-based inverse kinematics 3D human modeling method using a vector quantized variational autoencoder(IK-VQ-VAE). By integrating joint training with an automatic variational gradient descent approach, the proposed method achieves …

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Pdr-Stgcn: An Enhanced Stgcn With Multi-Scale Periodic Fusion And A Dynamic Relational Graph For Traffic Forecasting, Jie Hu, Bingbing Tang, Langsha Zhu, Yiting Li, Jianjun Hu, Guanci Yang Jan 2026

Pdr-Stgcn: An Enhanced Stgcn With Multi-Scale Periodic Fusion And A Dynamic Relational Graph For Traffic Forecasting, Jie Hu, Bingbing Tang, Langsha Zhu, Yiting Li, Jianjun Hu, Guanci Yang

Faculty Publications

Accurate traffic flow prediction is a core component of intelligent transportation systems, supporting proactive traffic management, resource optimization, and sustainable urban mobility. However, urban traffic networks exhibit heterogeneous multi-scale periodic patterns and time-varying spatial interactions among road segments, which are not sufficiently captured by many existing spatio-temporal forecasting models. To address this limitation, this paper proposes PDR-STGCN (Periodicity-Aware Dynamic Relational Spatio-Temporal Graph Convolutional Network), an enhanced STGCN framework that jointly models multi-scale periodicity and dynamically evolving spatial dependencies for traffic flow prediction. Specifically, a periodicity-aware embedding module is designed to capture heterogeneous temporal cycles (e.g., daily and weekly patterns) and …

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Military Metaverse: Conceptual Connotation, Construction And Application Framework, Key Issues, Dayong Liu, Zhiming Dong, Jiancheng Gao Jan 2026

Military Metaverse: Conceptual Connotation, Construction And Application Framework, Key Issues, Dayong Liu, Zhiming Dong, Jiancheng Gao

Journal of System Simulation

Abstract: Based on the analysis of the concept of the metaverse, the military metaverse concept model is established and compared with virtual-real fusion systems such as the digital twin battlefield, analyzing its core characteristics and construction significance. To accelerate the construction of the military metaverse, an overall logical architecture for the construction and application of the military metaverse is designed, the concept of military metaverse primitives is proposed, and the technical architecture is designed. The main application directions of the military metaverse are analyzed, and the construction stage division and overall thinking are provided. The key issues in construction and …

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Virtual-Real Fusion Simulation Technology And Application Research For Industrial Control Systems Cybersecurity Of Process Manufacturing, Xinwei Wang, Jinjiang Wang, Zheng Wang, Laibin Zhang Jan 2026

Virtual-Real Fusion Simulation Technology And Application Research For Industrial Control Systems Cybersecurity Of Process Manufacturing, Xinwei Wang, Jinjiang Wang, Zheng Wang, Laibin Zhang

Journal of System Simulation

Abstract: Aiming at the problem that the industrial control system in the process manufacturing industry lacks an effective attack and defense drill platform when facing network attacks, it is difficult to truly simulate the attack situation, verify the protective measures, and accurately evaluate the impact of attacks on the physical system, an industrial control cybersecurity simulation technology based on virtual-real fusion is proposed to build an efficient attack and defense drill range. The industrial control cybersecurity simulation architecture based on virtual-real fusion is designed, and the consistency analysis of virtual-real fusion data is carried out. At the same time, …

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Spatio-Temporal Swin Transformer-Based Flow-Solid Coupling Interaction Sequence Image Prediction Network, Changjun Zou, Zhiyu Ge, Chenxi Zhong Jan 2026

Spatio-Temporal Swin Transformer-Based Flow-Solid Coupling Interaction Sequence Image Prediction Network, Changjun Zou, Zhiyu Ge, Chenxi Zhong

Journal of System Simulation

Abstract: To address limitations in modeling long-term dependencies and multi-scale features in fluidstructure interaction scenarios, a spatiotemporal deep learning model (SwinLSTM) integrating ConvLSTM and Swin Transformer is proposed. The model employs a gated spatiotemporal attention mechanism that dynamically embeds Swin Transformer's window-based multi-head self-attention into ConvLSTM's output gate, enabling adaptive temporal-spatial feature coupling, and designs a multi-level ConvLSTM framework to hierarchically capture complex spatiotemporal correlations. Experiments on a self-built fluid-interaction dataset show that our method achieves the highest PSNR and leading SSIM scores, with superior performance in preserving vortex details and boundary consistency. This work provides an efficient solution …

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Pl-Mamba: A 3d Point Cloud Semantic Segmentation Network Based On Bimodal Fusion, He Zhu, Feng Zhou, Mengxiao Zhu, Ju Dai Jan 2026

Pl-Mamba: A 3d Point Cloud Semantic Segmentation Network Based On Bimodal Fusion, He Zhu, Feng Zhou, Mengxiao Zhu, Ju Dai

Journal of System Simulation

Abstract: To enhance the semantic discrimination capability in point cloud semantic segmentation, a 3D point cloud semantic segmentation network named PL-Mamba is proposed, which is centered on the fusion of point cloud (P) and language (L) dual modalities. This method takes PointMamba as the backbone network, leveraging its excellent long-sequence modeling and global perception capabilities. It introduces a language prompt mechanism and uses a pretrained language model BERT to encode the context of category labels, obtaining semantically rich text features. The text information serves as a language guided token and is deeply integrated with point cloud features through cross modal …

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Dehpr: A Diffusion-Based End-To-End Hand Pose Reconstruction Network, Guoqiong Liao, Longjie Huang, Qingxin Li, Jiajun Zhang, Kefan Chen Jan 2026

Dehpr: A Diffusion-Based End-To-End Hand Pose Reconstruction Network, Guoqiong Liao, Longjie Huang, Qingxin Li, Jiajun Zhang, Kefan Chen

Journal of System Simulation

Abstract: Traditional methods such as convolutional neural networks (CNNs) and Transformers suffer from strong dependence on large-scale annotated data and limited generalization capability when dealing with hand pose reconstruction in complex scenarios. To address these issues, a diffusion-based end-to-end hand pose reconstruction network (DEHPR) is proposed. This method employs a diffusion model to directly generate and refine 3D predictions, thereby reducing spatial uncertainties inherent in 2D-to-3D modeling paradigms. By incorporating an end-to-end framework that reprojects multiple 3D candidate predictions to select optimal joint positions, the approach ultimately produces accurate hand pose estimations. Comprehensive evaluations conducted on HO3D V2, DexYCB, …

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Cross-Domain Crowd Counting Model Based On Frequency Domain Enhancement, De Zhang, Zishan Liang, Ningning Liu Jan 2026

Cross-Domain Crowd Counting Model Based On Frequency Domain Enhancement, De Zhang, Zishan Liang, Ningning Liu

Journal of System Simulation

Abstract: Crowd counting takes video surveillance data as input and can be applied to the construction of city digital twin platforms, virtual city modeling and smart city management, etc. However, when there are data domain differences between the application scenario and training scenario, counting performance often significantly decreases. A cross-domain crowd counting model based on frequency domain enhancement is proposed. To alleviate the distribution differences between domains, a frequency domain feature enhancement module and a domain invariant frequency domain adapter module are constructed: the former uses discrete cosine transform to extract key statistical features to enhance spatial representation ability, while …

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