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11th IEEE International Conference on Teaching, Assessment and Learning for Engineering, TALE 2022

作者： Wan, Han Luo, Hongzhen Zhong, Zihao Yang, Jianlei Beihang University School of Computer Science and Engineering State Key Laboratory of Virtual Reality Technology and Systems Beijing China

ISBN: (纸本)9781665491174

Due to the COVID-19 pandemic, traditional teaching has been migrated online. Different from traditional face-to-face teaching, when students learn online, the online learning platform will generate various data. And these data make it possible for us to analyze students' final academic performance. In this paper, we use structural equation modeling (SEM) to analyze the relationship between students' learning factors. It is found that students' lab scores (LS), exercise scores (LS) and participation in the discussion (PID) have a direct impact on their final programming scores (FPS). This paper also finds that students' assignment submissions have an indirect influence on their final programming scores (FPS) but have a direct effect on lab scores (LS). In addition, students' participation in the discussion (PID) has an indirect influence on assignment submissions (AS) and lab scores (LS). The research in this paper can provide instructional designers with references for instructional design. © 2022 IEEE.

关键词： Students

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Radiographic Reports Generation via Retrieval Enhanced Cross-modal Fusion

Radiographic Reports Generation via Retrieval Enhanced Cross...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Hou, Xia Luo, Yifan Song, Wenfeng Guo, Yuting You, Wenzhe Li, Shuai Beijing Information Science and Technology University School of Computer Science Beijing China Beihang University The State Key Laboratory of Virtual Reality Technology and Systems Beijing China Stomatology Center of China-Japan Friendship Hospital Beijing China

ISBN: (纸本)9798350386226

Accurate radiographic reports are crucial for effective clinical decision-making and patient safety, as they directly influence diagnosis and treatment plans. Existing models for radiographic report generation often struggle with integrating medical image and textual report features and addressing data imbalances. To overcome these limitations, we propose an enhanced cross-modal aligned retrieval-driven network (EARnet). Our model incorporates two key innovations: Enhanced Cross-modal Alignment (ECA) module and Case-based Retrieval Augmenter (CRA) module. ECA ensures the effective integration of medical visual and textual data by aligning these modalities. CRA helps mitigate data imbalance by improving the representation of medical information and ensuring a more balanced and comprehensive coverage of both normal and abnormal cases. This dual-module approach significantly improves the coherence and accuracy of the generated medical reports. Evaluation results demonstrate that our EARnet model substantially outperforms existing methods in terms of report quality and accuracy across multiple metrics. Our codes and models are available at https://***/lyf616/EARnet. © 2024 IEEE.

关键词： Patient treatment

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High-temperature oxidation behaviour of minor Hf-dopedβ-NiAI single crystals in dry and humid atmospheres

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Rare Metals 2023年第8期42卷 2767-2773页

作者： Kai Yan Jian He Hong-Bo Guo School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191China School of Energy and Power Engineering Beihang UniversityBeijing 100191China School of Materials Science and Engineering Beihang UniversityBeijing 100191China

Oxidation behaviour of undopedβ-NiAl andβ-NiAl-0.05Hf single crystals were investigated at 1100℃in 20 vol%O_(2)+Ar and 15 vol%H2O+Ar,*** contrary to the well-known beneficial effect of Hf additions on the oxidation behaviour of polycrystallineβ-NiAl,severe-scale spallation is observed forβ-NiAl-0.05Hf single-crystal alloy,especially in dry *** is proposed that the presence of the grain boundaries in the polycrystalline substrate enables proper content of Hf segregating at the grain boundaries of the oxide scale and at the scale-substrate interface,which promotes the conditions required for reactive element *** the reactive element effect of Hf does not work,its strong affinity with oxygen will accelerate the process of high-temperature ***,the absence of the grain boundaries as fast diffusion paths partially compromises the adverse influence of water vapour on cyclic oxidation resistance ofβ-NiAl single crystal,resulting in considerable suppression of the oxidation rate and less loss of protection compared with that in dry *** addition,interfacial cavities are observed in dry and humid atmospheres,which may eventually result in the spallation of the oxide scale.

关键词： Oxidation Reactive element Water vapour β-NiAl Grain boundary

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A Comprehensive Review of Redirected Walking Techniques:Taxonomy,Methods,and Future Directions

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Journal of Computer Science & technology 2022年第3期37卷 561-583页

作者： Yi-Jun Li Frank Steinicke Miao Wang State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Department of Informatics Universität HamburgHamburg 20146Germany Peng Cheng Laboratory Shenzhen 518055China

virtual reality(VR)allows users to explore and experience a computer-simulated virtual environment so that VR users can be immersed in a totally artificial virtual world and interact with arbitrary virtual ***,the limited physical tracking space usually restricts the exploration of large virtual spaces,and VR users have to use special locomotion techniques to move from one location to *** these techniques,redirected walking(RDW)is one of the most natural locomotion techniques to solve the problem based on near-natural walking *** core idea of the RDW technique is to imperceptibly guide users on virtual paths,which might vary from the paths they physically walk in the real *** a similar way,some RDW algorithms imperceptibly change the structure and layout of the virtual environment such that the virtual environment fits into the tracking *** this survey,we first present a taxonomy of existing RDW *** on this taxonomy,we compare and analyze both contributions and shortcomings of the existing methods in detail,and find view manipulation methods offer satisfactory visual effect but the experience can be interrupted when users reach the physical boundaries,while virtual environment manipulation methods can provide users with consistent movement but have limited application ***,we discuss possible future research directions,indicating combining artificial intelligence with this area will be effective and intriguing.

关键词： virtual reality locomotion redirected walking

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Generative Cooperative Network for Person Image Generation 6

Generative Cooperative Network for Person Image Generation

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6th IEEE International Conference on Universal Village, UV 2022

作者： Liu, Yang Wang, Shuai Wu, Yubin Sheng, Hao Xiong, Zhang Beihang University State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beijing China

ISBN: (纸本)9781665474771

Person image generation is to synthesize realistic pedestrian images that follow the same distribution as the given dataset. Previous attempts can be generally categorized into two classes: some methods use human pose information as guidance and others try to generate person images from scratch. The former is to transfer the pose of a source image to a reference pose. The generated person image have the same identity as the source image. The latter takes a random noise from latent space as input, and the real person images are only used as references for the discriminator. While pose-guided person image generation is widely studied, generating-from-scratch methods are also worth exploring because they can synthesize person image with new identity, which is a useful manner of data augmentation. These two types of generating methods have their different advantages and disadvantages, and sometimes they are complementary. In this work, the authors design a Generative Cooperative Network (GCN) to jointly train two types of GANs. The two GANs serve different purposes, and can learn from each other during the cooperative learning procedure. The proposed approach is verified on public datasets, and the results show that our GCN improves the performance of the baseline methods. Comparisons with state-of-the-art methods also prove the effectiveness of the proposed method. © 2022 IEEE.

关键词： Computer vision

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Dense object detection for remote sensing images based on multi-scale partitioning and super-resolution optimization 24

Dense object detection for remote sensing images based on mu...

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3rd International Conference on Signal Processing, Computer Networks and Communications, SPCNC 2024

作者： Li, Lu Zhu, Xia Ni, Shaofeng Gao, Fan State Grid Location based Service Co. Ltd. Beijing China State Grid Information & Telecommunication Group Co. Ltd. Beijing China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China

ISBN: (纸本)9798400710834

Detecting dense objects in remote sensing image is a critical yet challenging task due to variations in target scale, image resolution, and complex backgrounds. Traditional detection methods often struggle with these dense regions, particularly for small or overlapping objects. To overcome these limitations, this study introduces an innovative approach that combines multi-scale partitioning with super-resolution optimization to improve the detection of densely packed objects. By applying K-Means clustering to identify regions of interest (ROI) and using a local super-resolution network to enhance these areas, we improve the clarity and detectability of small-scale objects. Additionally, we implement a global-local feature extraction architecture, where global features are captured using Transformer-based attention, while local features focus on fine-grained object details. Non-Maximum Suppression (NMS) is employed to fuse multi-scale features and eliminate redundant detections. Experimental results on the DOTA and HRSC2016 datasets demonstrate the effectiveness of our approach, achieving superior performance over state-of-the-art methods in detecting small and densely packed targets. This method shows significant promise for remote sensing applications requiring high-precision target detection. © 2024 Copyright held by the owner/author(s).

关键词： Proximity sensors

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Language Embedded 3D Gaussians for Open-Vocabulary Scene Understanding

Language Embedded 3D Gaussians for Open-Vocabulary Scene Und...

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Jin-Chuan Shi Miao Wang Hao-Bin Duan Shao-Hua Guan State Key Laboratory of Virtual Reality Technology and Systems SCSE Beihang University Zhongguancun Laboratory

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

Open-vocabulary querying in 3D space is challenging but essential for scene understanding tasks such as ob-ject localization and segmentation. Language-embedded scene representations have made progress by incorporating language features into 3D spaces. However, their effi-cacy heavily depends on neural networks that are resource-intensive in training and rendering. Although recent 3D Gaussians offer efficient and high-quality novel view syn-thesis, directly embedding language features in them leads to prohibitive memory usage and decreased performance. In this work, we introduce Language Embedded 3D Gaus-sians, a novel scene representation for open-vocabulary query tasks. Instead of embedding high-dimensional raw semantic features on 3D Gaussians, we propose a dedicated quantization scheme that drastically alleviates the mem-ory requirement, and a novel embedding procedure that achieves smoother yet high accuracy query, countering the multi-view feature inconsistencies and the high-frequency inductive bias in point-based representations. Our compre-hensive experiments show that our representation achieves the best visual quality and language querying accuracy across current language-embedded representations, while maintaining real-time rendering frame rates on a single desktop GPU. Project page: https://***/LEGaussians/.

关键词： Training Visualization Three-dimensional displays Accuracy Uncertainty TV Vector quantization

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SL-SFGR: Segmentation Learning Coupling Spatial-Frequency Structure Information Enhancement for Guiding Registration

SL-SFGR: Segmentation Learning Coupling Spatial-Frequency St...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Gao, Fan He, Yuanbo Li, Shuai Hao, Aimin Wang, Meiyun Cao, Desen Beihang University State Key Laboratory of Virtual Reality Technology and Systems Beijing China Henan Academy of Innovations in Medical Science Zhengzhou China Chinese Pla General Hospital Department of Biomedical Engineering Beijing China

ISBN: (纸本)9798350386226

The core of medical image registration lies in the alignment of corresponding structures. Hence, the effective construction of structure information in images is crucial for guiding registration. Some methods directly introduce explicit structure priors for assisting registration training, but obtaining high-precision structure priors is intrinsically challenging. As a segmentation model for obtaining structure priors, its capability is built upon the effective construction of structure information, thus its model learning can also be used to guide registration. However, existing registration-segmentation joint methods mostly only use segmentation results at the output level to constrain registration, neglecting the guidance of segmentation learning at the feature level for registration. Moreover, most existing methods only extract features in the image spatial domain for registration, overlooking the structure information in the frequency domain that is more easily captured to guide registration. To this end, this paper proposes an innovative registration method, namely Segmentation Learning Coupling Spatial-Frequency Structure Information Enhancement for Guiding Registration (SL-SFGR). Specifically, first, a semi-supervised segmentation learning network is constructed based on the registration deformation field to introduce structure features suitable for guiding registration. Second, an adaptive feature enhancement module is built in the spatial-frequency dual domain to further strengthen the inherent structure features. Finally, Dynamic Weight Average (DWA) is utilized for joint optimization of the model. The effectiveness of the proposed method has been verified on different brain MRI datasets. The related code is available at: https://***/goghfan/SL-SFGR/. © 2024 IEEE.

关键词： Frequency domain analysis

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LogicST: A Logical Self-Training Framework for Document-Level Relation Extraction with Incomplete Annotations

LogicST: A Logical Self-Training Framework for Document-Leve...

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Fan, Shengda Wang, Yanting Mo, Shasha Niu, Jianwei School of Cyber Science and Technology Beihang University Beijing100191 China Zhongguancun Laboratory Beijing100191 China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China

ISBN: (纸本)9798891761643

Document-level relation extraction (DocRE) aims to identify relationships between entities within a document. Due to the vast number of entity pairs, fully annotating all fact triplets is challenging, resulting in datasets with numerous false negative samples. Recently, self-training-based methods have been introduced to address this issue. However, these methods are purely black-box and sub-symbolic, making them difficult to interpret and prone to overlooking symbolic interdependencies between relations. To remedy this deficiency, our insight is that symbolic knowledge, such as logical rules, can be used as diagnostic tools to identify conflicts between pseudo-labels. By resolving these conflicts through logical diagnoses, we can correct erroneous pseudo-labels, thus enhancing the training of neural models. To achieve this, we propose LogicST, a neural-logic self-training framework that iteratively resolves conflicts and constructs the minimal diagnostic set for updating models. Extensive experiments demonstrate that LogicST significantly improves performance and outperforms previous state-of-the-art methods. For instance, LogicST achieves an increase of 7.94% in F1 score compared to CAST (Tan et al., 2023a) on the DocRED benchmark (Yao et al., 2019). Additionally, LogicST is more time-efficient than its self-training counterparts, requiring only 10% of the training time of CAST. Code is available at https://***/XingYing-stack/LogicST. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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Exploring the Overall Stiffness Distribution Law of Weakly Rigid Composite Fairings 7th

Exploring the Overall Stiffness Distribution Law of Weakly R...

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7th China Aeronautical Science and technology Conference, CASTC 2024

作者： Yin, Rongying Kong, Chuifeng Dong, Yushuang Ma, Jichuan Gao, Hanjun Harbin Hafei Aviation Industry Co Ltd Harbin150060 China School of Mechanical Engineering and Automation State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing100191 China School of Technology Forestry University Beijing100083 China

ISBN: (纸本)9789819797677

To elucidate the stresses and deformations occurring during the assembly of the powerhouse fairing, finite element analysis (ABAQUS) was employed to emulate the assembly process. A numerical simulation model was constructed for the assembly process of the weakly rigid composite fairing by digitizing its geometry, material properties, and the forces exerted during assembly. Initially, the geometric data and material parameters of the fairing were meticulously collected and analyzed, considering its weakly rigid composite material properties. Subsequently, the finite element analysis method was utilized to partition the fairing’s geometry into minute regions, thereby establishing a numerical simulation model of the fairing assembly process. During the simulation, various forces acting on the fairing during assembly, such as the binding force of the assembly fixture and mechanical loads, were taken into account. The stress and deformation distributions during the fairing assembly process were derived through numerical simulation of the model. The findings indicate that the overall stiffness distribution law of the weakly rigid composite fairing can be summarized as follows: larger fixed boundaries, smaller applied forces, more rigid materials, and more intricate geometries enhance the overall stiffness of the fairing. © Chinese Society of Aeronautics and Astronautics 2025.

关键词： ABAQUS

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