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Launching A 3d Printing Program For Students: Recommendations And Best Practices For Libraries, Wilhelmina Randtke, Lee Bareford 2023 Georgia Southern University Libraries

Launching A 3d Printing Program For Students: Recommendations And Best Practices For Libraries, Wilhelmina Randtke, Lee Bareford

Georgia Library Quarterly

The Georgia Southern University Libraries launched a 3D printing program for students in July 2022. Prior to launch, library employees at two of Georgia Southern University’s campuses investigated options for implementing safe, affordable, and sustainable 3D printing in existing academic libraries without retrofitting costly ventilation systems into existing facilities. This article describes the reasons why the Georgia Southern University Libraries thought that a 3D printing program could fulfill a service need for students across university colleges and departments and outlines some of the challenges, best practices, and unique innovations that the library’s employees experienced throughout the program launch process. The …


Molecular Dynamics Of High Temperature Hydrogen Attack, Mike Travis Bodden Connor 2022 Mississippi State University

Molecular Dynamics Of High Temperature Hydrogen Attack, Mike Travis Bodden Connor

Theses and Dissertations

High temperature hydrogen attack (HTHA) is a damage mechanism that only affects carbon steel and low alloy material. Most of the data regarding HTHA are experimental-driven. Even though this approach has been successful, there are still much more things that the oil and gas industry does not understand about HTHA. The regions that were considered safe (below the Nelson curves) have experienced catastrophic failure. Our research consists of performing Molecular Dynamics (MD) and the Nudge Elastic Band (NEB) calculation of HTHA to better understand the atomistic behavior of this damage mechanism.


Light Field Salient Object Detection: A Review And Benchmark, Keren Fu, Yao Jiang, Ge-Peng Ji, Tao Zhou, Qijun Zhao, Deng-Ping Fan 2022 College of Computer Science, Sichuan University, and National Key Laboratory of Fundamental Science on Synthetic Vision, Sichuan University, Chengdu 610065, China

Light Field Salient Object Detection: A Review And Benchmark, Keren Fu, Yao Jiang, Ge-Peng Ji, Tao Zhou, Qijun Zhao, Deng-Ping Fan

Computational Visual Media

Salient object detection (SOD) is a long-standing research topic in computer vision with increasing interest in the past decade. Since light fields record comprehensive information of natural scenes that benefit SOD in a number of ways, using light field inputs to improve saliency detection over conventional RGB inputs is an emerging trend. This paper provides the first comprehensive review and a benchmark for light field SOD, which has long been lacking in the saliency community. Firstly, we introduce light fields, including theory and data forms, and then review existing studies on light field SOD, covering ten traditional models, seven deep …


Recent Advances In Glinty Appearance Rendering, Junqiu Zhu, Sizhe Zhao, Yanning Xu, Xiangxu Meng, Lu Wang, Ling-Qi Yan 2022 Shandong University, Jinan, China

Recent Advances In Glinty Appearance Rendering, Junqiu Zhu, Sizhe Zhao, Yanning Xu, Xiangxu Meng, Lu Wang, Ling-Qi Yan

Computational Visual Media

The interaction between light and materials is key to physically-based realistic rendering. However, it is also complex to analyze, especially when the materials contain a large number of details and thus exhibit "glinty" visual effects. Recent methods of producing glinty appearance are expected to be important in next-generation computer graphics. We provide here a comprehensive survey on recent glinty appearance rendering. We start with a definition of glinty appearance based on microfacet theory, and then summarize research works in terms of representation and practical rendering. We have implemented typical methods using our unified platform and compare them in terms of …


Automatic Location And Semantic Labeling Of Landmarks On 3d Human Body Models, Shan Luo, Qitong Zhang, Jieqing Feng 2022 State Key Lab of CAD&CG, Zhejiang University, Hangzhou 310058, China

Automatic Location And Semantic Labeling Of Landmarks On 3d Human Body Models, Shan Luo, Qitong Zhang, Jieqing Feng

Computational Visual Media

Landmarks on human body models are of great significance for applications such as digital anthropometry and clothing design. The diversity of pose and shape of human body models and the semantic gap make landmarking a challenging problem. Inthis paper, a learning-based method is proposed to locate landmarks on human body models by analyzing the relationship between geometric descriptors and semantic labels of landmarks. A shape alignmentalgorithm is proposed to align human body models to break symmetric ambiguity. A symmetry-awaredescriptor is proposed based on the structure of the human body models, which is robust to both pose and shape variations in …


Constructing Self-Supporting Surfaces With Planar Quadrilateral Elements, Long Ma, Sidan Yao, Jianmin Zheng, Yang Liu, Yuanfeng Zhou, Shi-Qing Xin, Ying He 2022 School of Software, Shandong University, Jinan 250101, China;School of Computer Science and Engineering, Nanyang Technological University, Singapore 639798, Singapore

Constructing Self-Supporting Surfaces With Planar Quadrilateral Elements, Long Ma, Sidan Yao, Jianmin Zheng, Yang Liu, Yuanfeng Zhou, Shi-Qing Xin, Ying He

Computational Visual Media

We present a simple yet effective method for constructing 3D self-supporting surfaces with planar quadrilateral (PQ) elements. Starting with a triangular discretization of a self-supporting surface, we firstcompute the principal curvatures and directions of each triangular face using a new discrete differential geometryapproach, yielding more accurate results than existing methods. Then, we smooth the principal direction field to reduce the number of singularities. Next, we partition all faces into two groups in terms of principalcurvature difference. For each face with small curvature difference, we compute a stretch matrix that turns the principal directions into a pair of conjugate directions. For …


Blnet: Bidirectional Learning Network For Point Clouds, Wenkai Han, Hai Wu, Chenglu Wen, Cheng Wang, Xin Li 2022 School of Informatics, Xiamen University, 422 Siming South Road, Xiamen 361005, China

Blnet: Bidirectional Learning Network For Point Clouds, Wenkai Han, Hai Wu, Chenglu Wen, Cheng Wang, Xin Li

Computational Visual Media

The key challenge in processing point clouds lies in the inherent lack of ordering and irregularity of the 3D points. By relying on per-point multi-layer perceptions (MLPs), most existing point-based approaches only address the first issue yet ignore the second one. Directly convolving kernels with irregular points will result in loss of shape information. This paper introduces a novel point-based bidirectional learning network (BLNet) to analyze irregular 3D points. BLNet optimizes the learning of 3D points through two iterative operations: feature-guided point shifting and feature learning from shifted points, so as to minimise intra-class variances, leading to a more regular …


Joint Self-Supervised And Reference-Guided Learning For Depth Inpainting, Heng Wu, Kui Fu, Yifan Zhao, Haokun Song, Jia Li 2022 State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering,Beihang University, Beijing 100191, China

Joint Self-Supervised And Reference-Guided Learning For Depth Inpainting, Heng Wu, Kui Fu, Yifan Zhao, Haokun Song, Jia Li

Computational Visual Media

Depth information can benefit various computer vision tasks on both images and videos. However, depth maps may suffer from invalid values in many pixels, and also large holes. To improve such data, we propose a joint self-supervised and reference-guided learning approach for depth inpainting. For the self-supervised learning strategy, we introduce an improved spatial convolutional sparse coding module in which total variation regularization is employed to enhance the structural information while preserving edge information. This module alternately learns a convolutional dictionary and sparse coding from a corrupted depth map. Then, both the learned convolutional dictionary and sparse coding are convolved …


Image-Guided Color Mapping For Categorical Data Visualization, Qian Zheng, Min Lu, Sicong Wu, Ruizhen Hu, Joel Lanir, Hui Huang 2022 Suzhou University of Science and Technology, Suzhou 215009, China

Image-Guided Color Mapping For Categorical Data Visualization, Qian Zheng, Min Lu, Sicong Wu, Ruizhen Hu, Joel Lanir, Hui Huang

Computational Visual Media

Appropriate color mapping for categorical data visualization can significantly facilitate the discovery of underlying data patterns and effectively bring out visual aesthetics. Some systems suggest pre-defined palettes for this task. However, a predefined color mapping is not always optimal, failing to consider users’ needs for customization. Given an input cate-gorical data visualization and a reference image, we present an effective method to automatically generate a coloring that resembles the reference while allowing classes to be easily distinguished. We extract a color palette with high perceptual distance between the colors by sampling dominant and discriminable colors from the image’s color space. …


Self-Supervised Coarse-To-Fine Monocular Depth Estimation Using A Lightweight Attention Module, Yuanzhen Li, Fei Luo, Chunxia Xiao 2022 School of Computer Science, Wuhan University, Wuhan 430072, China

Self-Supervised Coarse-To-Fine Monocular Depth Estimation Using A Lightweight Attention Module, Yuanzhen Li, Fei Luo, Chunxia Xiao

Computational Visual Media

Self-supervised monocular depth estimation has been widely investigated and applied in previous works. However, existing methods suffer from texture-copy, depth drift, and incomplete structure. It is difficult for normal CNN networks to completely understand the relationship between the object and its surrounding environment. Moreover, it is hard to design the depth smoothness loss to balance depth smoothness and sharpness. To address these issues, we propose a coarse-to-fine method with a normalized convolutional block attention module (NCBAM). In the coarse estimation stage, we incorporate the NCBAM into depth and pose networks to overcome the texture-copy and depth drift problems. Then, we …


High Fidelity Virtual Try-On Network Via Semantic Adaptation And Distributed Componentization, Chenghu Du, Feng Yu, Minghua Jiang, Ailing Hua, Yaxin Zhao, Xiong Wei, Tao Peng, Xinrong Hu 2022 School of Computer Science and Artificial Intelligence, Wuhan Textile University, Wuhan 430200, China

High Fidelity Virtual Try-On Network Via Semantic Adaptation And Distributed Componentization, Chenghu Du, Feng Yu, Minghua Jiang, Ailing Hua, Yaxin Zhao, Xiong Wei, Tao Peng, Xinrong Hu

Computational Visual Media

Image-based virtual try-on systems have significant commercial value in online garment shopping. However, prior methods fail to appropriately handle details, so are defective in maintaining the original appearance of organizational items including arms, the neck, and in-shop garments. We propose a novel high fidelity virtual try-on network to generate realistic results. Specifically, a distributed pipeline is used for simultaneous generation of organizational items. First, the in-shop garment is warped using thin plate splines (TPS) to give a coarse shape reference, and then a corresponding target semantic map is generated, which can adaptively respond to the distribution of different items triggered …


Parametric Modeling Of Biomimetic Sharkskin For Wire Edm For Drag Reduction And Hydrophobicity, Joel Maxwell 2022 University of Nebraska-Lincoln

Parametric Modeling Of Biomimetic Sharkskin For Wire Edm For Drag Reduction And Hydrophobicity, Joel Maxwell

Mechanical (and Materials) Engineering -- Dissertations, Theses, and Student Research

This research sets out to demonstrate the viability of parametric modeling for biomimetic sharkskin in the effort to reduce drag and create a self-cleaning surface. Multiple designs were created to be machined by Wire EDM on stainless steel and titanium and were comparatively tested. Limitations of current manufacturing processes to economically produce naturally occurring structures such as sharkskin, emphasize the need to be able to calculate the most accurate design for a given manufacturing process. By designing a simplified but parametrically consistent model compared to an accurately depicted 3D model of sharkskin, the textured samples produced can be further tested …


Multiple Heat Exchanger Cooling System For Automotive Applications – Design, Mathematical Modeling, And Experimental Observations, Zaker Syed 2022 Clemson University

Multiple Heat Exchanger Cooling System For Automotive Applications – Design, Mathematical Modeling, And Experimental Observations, Zaker Syed

All Dissertations

The design of the automotive cooling systems has slowly evolved from engine-driven mechanical to computer-controlled electro-mechanical components. With the addition of computer-controlled variable speed actuators, cooling system architectures have been updated to maximize performance and efficiency. By switching from one large radiator to multiple smaller radiators with individual flow control valves, the heat rejection requirements may be precisely adjusted. The combination of computer regulated thermal management system should reduce power consumption while satisfying temperature control objectives. This research focuses on developing and analyzing a multi-radiator system architecture for implementation in ground transportation applications. The premise is to use a single …


Image Based Processing For Weld Defect Detection, Shems-Eddine Belhout 2022 University of Tennessee Knoxville

Image Based Processing For Weld Defect Detection, Shems-Eddine Belhout

Masters Theses

There is a growing need for automation in the welding industry due to a growing shortage in skilled welders. TIG [Tungsten Inert Gas] welding, a method of welding that uses an electrode shielded by gas and is fed externally by a wire, is incredibly advantageous for its precise heat control. TIG welding is considered the standard for nuclear application which requires highly precise welds to be performed. Robotic welding can address this issue, and one major problem that occurs during welding is welding defects. Typical weld defect detection requires a highly knowledgeable welder or destructive and nondestructive evaluation. Destructive evaluation …


Using Strategic Options Development And Analysis (Soda) To Understand The Simulation Accessibility Problem, Andrew J. Collins, Ying Thaviphoke, Antuela A. Tako 2022 Old Dominion University

Using Strategic Options Development And Analysis (Soda) To Understand The Simulation Accessibility Problem, Andrew J. Collins, Ying Thaviphoke, Antuela A. Tako

Engineering Management & Systems Engineering Faculty Publications

Simulation modelling is applied to a wide range of problems, including defense and healthcare. However, there is a concern within the simulation community that there is a limited use and implementation of simulation studies in practice. This suggests that despite its benefits, simulation may not be reaching its potential in making a real-world impact. The main reason for this could be that simulation tools are not widely accessible in industry. In this paper, we investigate the issues that affect simulation modelling accessibility through a workshop with simulation practitioners. We use Strategic Options Development and Analysis (SODA), a problem-structuring approach that …


Pvt V2: Improved Baselines With Pyramid Vision Transformer, Wenhai Wang, Enze Xie, Xiang Li, Deng-Ping Fan, Kaitao Song, Ding Liang, Tong Lu, Ping Luo, Ling Shao 2022 Shanghai AI Laboratory, Shanghai 200232, China;Department of Computer Science and Technology, NanjingUniversity, Nanjing 210023, China

Pvt V2: Improved Baselines With Pyramid Vision Transformer, Wenhai Wang, Enze Xie, Xiang Li, Deng-Ping Fan, Kaitao Song, Ding Liang, Tong Lu, Ping Luo, Ling Shao

Computational Visual Media

Transformers have recently lead to encouraging progress in computer vision. In this work, we present new baselines by improving the original Pyramid Vision Transformer (PVT v1) by adding three designs: (i) a linear complexity attention layer, (ii) an overlapping patch embedding, and (iii) a convolutional feed-forward network. With these modifications, PVT v2 reduces the computational complexity of PVT v1 to linearity and provides significant improvements on fundamental vision tasks such as classification, detection, and segmentation. In particular, PVT v2 achieves comparable or better performance than recent work such as the Swin transformer. We hope this work will facilitate state-of-the-art transformer …


Attention Mechanisms In Computer Vision: A Survey, Meng-Hao Guo, Tian-Xing Xu, Jiang-Jiang Liu, Zheng-Ning Liu, Peng-Tao Jiang, Tai-Jiang Mu, Song-Hai Zhang, Ralph R. Martin, Ming-Ming Cheng, Shi-Min Hu 2022 BNRist, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China

Attention Mechanisms In Computer Vision: A Survey, Meng-Hao Guo, Tian-Xing Xu, Jiang-Jiang Liu, Zheng-Ning Liu, Peng-Tao Jiang, Tai-Jiang Mu, Song-Hai Zhang, Ralph R. Martin, Ming-Ming Cheng, Shi-Min Hu

Computational Visual Media

Humans can naturally and effectively find salient regions in complex scenes. Motivated by thisobservation, attention mechanisms were introduced into computer vision with the aim of imitating this aspect of the human visual system. Such an attention mechanism can be regarded as a dynamic weight adjustment process based on features of the input image. Attention mechanisms have achieved great success in many visual tasks, including image classification, object detection, semantic segmentation, video understanding, image generation, 3D vision, multi-modal tasks, and self-supervised learning. In this survey, we provide a comprehensive review of various attention mechanisms in computer vision and categorize them according …


High-Quality Indoor Scene 3d Reconstruction With Rgb-D Cameras: A Brief Review, Jianwei Li, Wei Gao, Yihong Wu, Yangdong Liu, Yanfei Shen 2022 School of Sports Engineering, Beijing Sports University, Beijing 100084, China

High-Quality Indoor Scene 3d Reconstruction With Rgb-D Cameras: A Brief Review, Jianwei Li, Wei Gao, Yihong Wu, Yangdong Liu, Yanfei Shen

Computational Visual Media

High-quality 3D reconstruction is an important topic in computer graphics and computer vision with many applications, such as robotics and augmented reality. The advent of consumer RGB-D cameras has made a profound advance in indoor scenereconstruction. For the past few years, researchers have spent significant effort to develop algorithms to capture 3D models with RGB-D cameras. As depth images produced by consumer RGB-D cameras are noisy and incomplete when surfaces are shiny, bright, transparent, or far from the camera, obtaining high- quality 3D scene models is still a challenge for existing systems. We here review high-quality 3D indoor scene reconstruction …


Robust And Efficient Edge-Based Visual Odometry, Feihu Yan, Zhaoxin Li, Zhong Zhou 2022 State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing 100191, China

Robust And Efficient Edge-Based Visual Odometry, Feihu Yan, Zhaoxin Li, Zhong Zhou

Computational Visual Media

Visual odometry, which aims to estimate relative camera motion between sequential video frames, has been widely used in the fields of augmented reality, virtual reality, and autonomous driving. However, it is still quite challenging for state-of-the-art approaches to handle low-texture scenes. In this paper, we propose a robust and efficient visual odometry algorithm that directly utilizes edge pixels to track camera pose. In contrast to direct methods, we choose reprojection error to construct the optimization energy, which can effectively cope with illumination changes. The distance transform map built upon edge detection for each frame is used to improve tracking efficiency. …


Message From The Best Paper Award Committee, Ming C. Lin, Xin Tong, Wenping Wang 2022 University of Maryland at College Park, USA

Message From The Best Paper Award Committee, Ming C. Lin, Xin Tong, Wenping Wang

Computational Visual Media

No abstract provided.


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