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Video-based skill acquisition assessment in laparoscopic surgery using deep learning

Global Surgical Education - Journal of the Association for Surgical Education 2024年第1期3卷 1-6页

作者： Yanik, Erim Ainam, Jean Paul Fu, Yaoyu Schwaitzberg, Steven Cavuoto, Lora De, Suvranu College of Engineering Florida A&M University and The Florida State University Tallahassee USA Center for Modeling Simulation and Imaging for Medicine (CeMSIM) Rensselaer Polytechnic Institute Troy USA Department of Industrial and Systems Engineering University at Buffalo Buffalo USA School of Medicine and Biomedical Sciences University at Buffalo Buffalo USA

Surgical skill acquisition is based on the repetitive execution of a surgical task. Each trainee starts with a different skill level and has a unique pace in attaining the necessary motor skills. Current training curriculums, however, lack adaptability to individual learning abilities. They are also time- and resource-intensive for trainees and expert surgeons. The purpose of this study is to provide an individualized and automated assessment of the surgical skills from the surgical learning curves of the subjects using deep learning and video data feeds. The proposed framework consists of two steps. First, given that surgical training is predominantly on surgical simulators, our pipeline was tested on the videos of a laparoscopic suturing simulation under the context of the Fundamentals of Laparoscopic Surgery (FLS). Twenty-three subjects performed FLS suturing with the intracorporeal knot-tying task over two weeks for more than 1600 trials. A self-supervised contrastive model extracted spatiotemporal features from raw videos of suturing trials. Second, a 1D residual neural network was used to utilize these features to classify surgical procedure outcomes and directly predict performance scores. Our findings showed that videos of surgical skill training could sufficiently be used to classify the Pass and Fail outcomes of the procedure with an Accuracy of 0.878 ± 0.002. Furthermore, our network can predict the performance scores of the trainees with a Spearman Correlation Coefficient of 0.746 ± 0.002. This approach offers an objective, automated strategy for efficient surgical skill acquisition prediction. We show that deep learning techniques and video alone can be used to predict surgical skill training task outcomes accurately and reliably. From here, we seek to enable customization of the training program.

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Enhancing realism in LiDAR scene generation with CSPA-DFN and linear cross-attention via Diffusion Transformer model

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Neural Networks 2025年 189卷 107503页

作者： Ye, Shaoxun Di, Xiaoguang Liao, Ming Li, Ximing Control and Simulation Center Harbin Institute of Technology Harbin150080 China National Key Laboratory of Modeling and Simulation for Complex Systems Harbin150080 China

Point cloud diffusion models have found extensive applications in autonomous driving and robotics. However, there is still a big gap between their generated LiDAR scene samples and real-world data in terms of visual quality. This discrepancy primarily arises from the loss of detailed information during the decoding process from latent space and the lack of guidance from global 3D structural information in the point cloud generation process, leading to distortions and artifacts in LiDAR scene samples. In this paper, we propose a novel LiDAR Diffusion Transformer Model that integrates Channel-Spatial Parallel Attention and Dilation Fusion Network (CSPA-DFN) with a linear cross-attention post-processing module to refine the generated LiDAR scene samples. Specifically, CSPA-DFN is designed to simultaneously emphasize detailed features across different channels and spatial locations in parallel, leveraging multi-scale dilated convolutions and channel grouping to preserve and enhance these detailed features. In order to provide global 3D structural information and balance performance and efficiency, we design a post-processing module that fuses voxelized features and range images using a linear ReLU cross-attention mechanism. Our approach is evaluated on the unconditional generation task using the KITTI-360 and nuScenes datasets, achieving the state-of-the-art results in LiDAR scene's generation quality. Furthermore, by incorporating semantic labels and camera views into the latent space, in addition to enhancing the model's semantic understanding capability for LiDAR scenes, our method also demonstrates additional performance improvements compared to previous works in terms of LiDAR scene's visual quality. The code implementation has been released on https://***/HITysx/LiDAR-Scene-Generation. © 2025 Elsevier Ltd

关键词： Photointerpretation

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An Auto-Parallel Method for Deep Learning Models Based on Genetic Algorithm 29

An Auto-Parallel Method for Deep Learning Models Based on Ge...

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29th IEEE International Conference on Parallel and Distributed systems, ICPADS 2023

作者： Zeng, Yan Huang, Chengchuang Ni, Yijie Zhou, Chunbao Zhang, Jilin Wang, Jue Zhou, Mingyao Xue, Meiting Zhang, Yunquan Hangzhou Dianzi University School of Computer Science and Technology Hangzhou310018 China Ministry of Education Key Laboratory for Modeling and Simulation of Complex Systems Hangzhou310018 China Data Security Governance Zhejiang Engineering Research Center Hangzhou310018 China Hangzhou Dianzi University School of ITMO Joint Institute Hangzhou310018 China Institute of Computer Network Information Center of the Chinese Academy of Sciences Beijing100086 China HuaWei China Institute of Computing Technology of the Chinese Academy of Sciences State Key Laboratory of Computer Architecture Beijing100086 China

ISBN: (纸本)9798350330717

As the size of datasets and neural network models increases, automatic parallelization methods for models have become a research hotspot in recent years. The existing auto-parallel methods based on machine learning or graph algorithms still have issues with search efficiency and applicability. This paper proposes an automatic parallel method based on a dual-population genetic algorithm, TGA, which transforms model partitioning and placement into an integer linear programming problem and constructs a cost model to evaluate the solution. The solution space is built using the neural network's dataflow graph and device cluster's topology, and the dual-population genetic algorithm is used to search for the optimal model parallel strategy. Experiments with various models show that the proposed method can improve single-step execution time by up to 42% compared to the Baechi method and up to 37.7% compared to the Hierarchical method. © 2023 IEEE.

关键词： Auto-Parallel Distributed machine learning Genetic algorithm Integer linear programming Model parallelism

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Coupling Weap and Leap Models Using Interaction modeling

Coupling Weap and Leap Models Using Interaction Modeling

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2020 Spring simulation Conference, SpringSim 2020

作者： Fard, Mostafa D. Sarjoughian, Hessam S. Arizona State University Arizona Center for Integrative Modeling Simulation School of Computing Informatics and Decision Systems Engineering TempeAZ United States

ISBN: (纸本)9781565553705

It is useful to model the interactions between the water and energy models separately. A coupled water and energy model using an interaction model lends itself to developing flexible, yet rigorous predictive simulation studies. A WEAP-LEAP interaction model is developed based on the Knowledge Interchange Broker modeling approach. A RESTful simulation framework is developed for coupling the Componentized-WEAP and Componentized-LEAP systems. Every interaction model is defined to have a set of modules where each module has its input and output ports with data transformation schemes. The input and output ports of the Componentized-WEAP and Componentized-LEAP models are coupled with those of the interaction model. A cyclic, synchronous execution protocol is defined for concurrent, bidirectional data transformations. The computational efficiency of this loosely coupled water-energy framework is acceptable compared with the tightly WEAP-LEAP system. This proposed framework shows understanding the water-energy system nexus is advantageous using interaction modeling. © 2020 SCS.

关键词： Computational efficiency

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Composability Verification of Complex systems Using Colored Petri Nets

Composability Verification of Complex Systems Using Colored ...

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simulation Winter Conference

作者： Imran Mahmood Syed Hassan Askari Hessam S. Sarjoughian Center for Research in Modeling & Simulation School of Electrical Engineering and Computer Science National University of Sciences and Technology Islamabad Pakistan Arizona Center for Integrative Modeling & Simulation School of Computing Information and Decision Systems Engineering Arizona State University Tempe Arizona USA

ISBN: (纸本)9781665433129

The discipline of component-based modeling and simulation offers promising gains including reductions in development cost, time, and system complexity. This paradigm promotes the use and reuse of modular components for adequate development of complex simulations. Achieving effective and meaningful model reuse through the composition of components still remains a daunting challenge. “Composability”, an integral part of this challenge, is the capability to select and assemble model components in various combinations to satisfy specific user requirements. In this paper, we propose the use of Colored Petri Nets for component-oriented model development, model composition, and the verification of composed models using state-space analysis technique. We present a case study of an elevator model as a proof of concept. Our case study explains the proposed process of developing and composing CPN-based model components and verifying the composed model using state-space analysis.

关键词： Analytical models Costs Petri nets Elevators Complexity theory Complex systems

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Mechanical performance of recycled PVC window frames: An experimental and numerical investigation

Hybrid Advances

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Hybrid Advances 2025年 9卷

作者： Ait Khouya, Oumaima Sebbar, EL Hassan Elfarissi, Latifa Laaroussi, Najma University Hassan II of Casablanca Laboratory of modeling and Simulation of Intelligent Industrial Systems ENSET Mohammedia Morocco Technical Center of Plastic and Rubber Casablanca Morocco Institute for Research in Solar Energy and New Energies-IRESEN Morocco University Mohammed V in Rabat Material Energy and Acoustics Team (MEAT) EST Salé Morocco

PVC window frames are commonly used in the construction industry due to their durability, low cost, and ease of maintenance. However, with growing environmental concerns and the shift towards a circular economy, replacing virgin PVC with recycled materials in such applications has become a critical area of research. The recycling process as well as the source of waste, highly impact the quality of the recycled materials which limits its use in high-quality products. This study investigates the mechanical characterization of window profiles made from recycled PVC, focusing on their ability to withstand structural loads. Given that window frames are exposed to wind forces and building loads, ensuring their mechanical resistance is essential. The bending and tensile behavior of recycled PVC specimens were tested experimentally and numerically to assess the structural performance of the material under different loading conditions. A comparison between the results of numerical finite element simulations and those of experiments has been carried out to validate the findings. The results show that recycled PVC offers adequate mechanical and thermal performance for use in the manufacture of window profiles. © 2025

关键词： Circular economy Plastic recycling PVC PVC profile Window frame

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Chances and Challenges of ChatGPT and Similar Models for Education in M&S

Chances and Challenges of ChatGPT and Similar Models for Edu...

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2023 Winter simulation Conference, WSC 2023

作者： Tolk, Andreas Barry, Philip Loper, Margaret L. Rabadi, Ghaith Scherer, William T. Yilmaz, Levent The Mitre Corporation Modeling and Analysis Innovation Center 1001 Research Park Blvd #200 CharlottesvilleVA22911 United States L3Harris Corporation Mission Analysis Group 2235 Monroe Street HerndonVA20171 United States Georgia Tech Research Institute Georgia Institute of Technology AtlantaGA30308 United States University of Central Florida School of Modeling Simulation and Training 3100 Technology Pkwy OrlandoFL32826 United States University of Virgina Department of Systems and Information Engineering CharlottesvilleVA22904 United States Auburn University Samuel Ginn College of Engineering Computer Science and Software Engineering AuburnAL36849 United States

ISBN: (纸本)9798350369663

This position paper summarizes the inputs of a group of experts from academia and industry presenting their view on chances and challenges of using ChatGPT within modeling and simulation education. The experts also address the need to evaluate continuous education as well as education of faculty members to address scholastic challenges and opportunities while meeting the expectation of industry. Generally, the use of ChatGPT is encouraged, but it needs to be embedded into an updated curriculum with more emphasis on validity constraints, systems thinking, and ethics. © 2023 IEEE.

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Chances and Challenges of Chatgpt and Similar Models for Education in M&S 23

Chances and Challenges of Chatgpt and Similar Models for Edu...

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Proceedings of the Winter simulation Conference

作者： Andreas Tolk Philip Barry Margaret L. Loper Ghaith Rabadi William T. Scherer Levent Yilmaz The MITRE Corporation Modeling and Analysis Innovation Center Charlottesville USA L3Harris Corporation Mission Analysis Group Herndon USA Georgia Tech Research Institute Georgia Institute of Technology Atlanta USA University of Central Florida School of Modeling Simulation and Training Orlando USA University of Virgina Department of Systems and Information Engineering Charlottesville USA Auburn University Samuel Ginn College of Engineering Computer Science and Software Engineering Auburn USA

ISBN: (纸本)9798350369663

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Multiscale failure analysis of a 3D woven composite containing manufacturing induced voids and disbonds

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Composites Part A: Applied Science and Manufacturing 2022年第0期156卷 106844-106844页

作者： Pineda, Evan J. Bednarcyk, Brett A. Ricks, Trenton M. Farrokh, Babak Jackson, Wade Multiscale and Multiphysics Modeling Branch NASA Glenn Research Center ClevelandOH44135 United States Mechanical Systems Analysis and Simulation Branch NASA Goddard Space Flight Center GreenbeltMD20771 United States Damage Tolerance and Reliability Branch NASA Langley Research Center HamptonVA23681 United States

Multiscale failure simulations of a three-dimensional woven composite repeating unit cell considering six scales, spanning the woven composite mesoscale to the sub-microscale voids, have been performed. The multiscale recursive micromechanics approach, which enables recursive integration of general micromechanics theories over an arbitrary number of length scales, has been employed within the NASA Multiscale Analysis Tool. The multiscale model uses both the generalized method of cells and Mori-Tanaka micromechanics theories and considers failure in the constituent materials using a simple damage model. Baseline results, from a model of a composite containing distributed voids, are compared to uniaxial experimental data for an AS4 carbon fiber/ RTM6 epoxy matrix orthogonal three-dimensional woven composite with good agreement in terms of global stiffness and global failure stress. The multiscale model is then used to examine the nonlinear response of the material to other loading conditions. Case studies, motivated by X-ray computed tomography data, are presented on the effects of manufacturing induced voids and cracks. © 2022

关键词： Computerized tomography

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A Restful Persistent Devs-Based Interaction Model For The Componentized Weap and Leap Restful Frameworks

A Restful Persistent Devs-Based Interaction Model For The Co...

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simulation Winter Conference

作者： Mostafa D. Fard Hessam S. Sarjoughian Arizona Center for Integrative Modeling & Simulation School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ USA

ISBN: (纸本)9781665433129

modeling the interactions between separate models contributes to building flexible hybrid simulation frameworks. In earlier work, an Algorithmic Interaction Model was proposed and developed to integrate the componentized WEAP and LEAP RESTful frameworks for modeling and simulating water and energy systems. However, this approach does not separate modeling and simulation protocol from each other. It also does not support flexible, structured model hierarchies. To overcome these limitations, the parallel DEVS formalism is used to develop an Interaction Model for use with the DEVS-Suite simulator. The resulting DEVS Interaction Model (DEVS-IM) is supported with a RESTful framework and MongoDB for storing the interaction models for the coupled water and energy models. The DEVS-IM, grounded in system theory and component-based modeling, offers strong support for the model reusability, flexibility, and maintainability traits essential for developing realistic simulations of coupled energy and water systems.

关键词： Visualization Protocols Computational modeling Heuristic algorithms Buildings Computational efficiency Dynamical systems

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