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Book ; Online: Generative Structural Design Integrating BIM and Diffusion Model

He, Zhili / Wang, Yu-Hsing / Zhang, Jian

2023

Abstract: Intelligent structural design using AI can effectively reduce time overhead and increase efficiency. It has potential to become the new design paradigm in the future to assist and even replace engineers, and so it has become a research hotspot in the ... ...

Abstract	Intelligent structural design using AI can effectively reduce time overhead and increase efficiency. It has potential to become the new design paradigm in the future to assist and even replace engineers, and so it has become a research hotspot in the academic community. However, current methods have some limitations to be addressed, whether in terms of application scope, visual quality of generated results, or evaluation metrics of results. This study proposes a comprehensive solution. Firstly, we introduce building information modeling (BIM) into intelligent structural design and establishes a structural design pipeline integrating BIM and generative AI, which is a powerful supplement to the previous frameworks that only considered CAD drawings. In order to improve the perceptual quality and details of generations, this study makes 3 contributions. Firstly, in terms of generation framework, inspired by the process of human drawing, a novel 2-stage generation framework is proposed to replace the traditional end-to-end framework to reduce the generation difficulty for AI models. Secondly, in terms of generative AI tools adopted, diffusion models (DMs) are introduced to replace widely used generative adversarial network (GAN)-based models, and a novel physics-based conditional diffusion model (PCDM) is proposed to consider different design prerequisites. Thirdly, in terms of neural networks, an attention block (AB) consisting of a self-attention block (SAB) and a parallel cross-attention block (PCAB) is designed to facilitate cross-domain data fusion. The quantitative and qualitative results demonstrate the powerful generation and representation capabilities of PCDM. Necessary ablation studies are conducted to examine the validity of the methods. This study also shows that DMs have the potential to replace GANs and become the new benchmark for generative problems in civil engineering. Comment: 38 pages, 9 figures. Preprint submitted to Elsevier
Keywords	Computer Science - Machine Learning ; Computer Science - Computer Vision and Pattern Recognition
Subject code	006
Publishing date	2023-11-07
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Infrastructure Crack Segmentation

He, Zhili / Chen, Wang / Zhang, Jian / Wang, Yu-Hsing

Boundary Guidance Method and Benchmark Dataset

2023

Abstract: Cracks provide an essential indicator of infrastructure performance degradation, and achieving high-precision pixel-level crack segmentation is an issue of concern. Unlike the common research paradigms that adopt novel artificial intelligence (AI) ... ...

Abstract	Cracks provide an essential indicator of infrastructure performance degradation, and achieving high-precision pixel-level crack segmentation is an issue of concern. Unlike the common research paradigms that adopt novel artificial intelligence (AI) methods directly, this paper examines the inherent characteristics of cracks so as to introduce boundary features into crack identification and then builds a boundary guidance crack segmentation model (BGCrack) with targeted structures and modules, including a high frequency module, global information modeling module, joint optimization module, etc. Extensive experimental results verify the feasibility of the proposed designs and the effectiveness of the edge information in improving segmentation results. In addition, considering that notable open-source datasets mainly consist of asphalt pavement cracks because of ease of access, there is no standard and widely recognized dataset yet for steel structures, one of the primary structural forms in civil infrastructure. This paper provides a steel crack dataset that establishes a unified and fair benchmark for the identification of steel cracks. Comment: 17 pages, 10 figures
Keywords	Computer Science - Computer Vision and Pattern Recognition
Subject code	006
Publishing date	2023-06-15
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: An Experimental Microstructural Characterization of High-quality, Load-preserved Fabric 1-D Consolidated Kaolinite Samples

Chow Jun Kang / Li Zhaofeng / Wang Yu-Hsing

E3S Web of Conferences, Vol 92, p

2019 Volume 01006

Abstract: This paper describes a microstructural characterizations of high-quality, load-preserved fabric 1-D consolidated kaolinite samples, which covers from the beginning stage of clay sample preparation to the final stage of the microstructural analyses. To ... ...

Abstract	This paper describes a microstructural characterizations of high-quality, load-preserved fabric 1-D consolidated kaolinite samples, which covers from the beginning stage of clay sample preparation to the final stage of the microstructural analyses. To achieve this goal, a tailor-made oedometer is produced using the 3-D printing technique. First, a uniform kaolinite sample is prepared from a slurry state and then positioned into the 3-D printed oedometer for 1-D consolidation tests. Then, together with the applied loadings, the whole oedometer containing the consolidated kaolinite sample is submerged into the liquid nitrogen. This aims for preparing the dry sample by freeze drying, and at the same time, preserving the fabric associations for the subsequent microstructural characterizations. Afterwards, the sample is cut in half while frozen. An observation plane along the centre with the morphological information preserved is used for the scanning electron microscopy (SEM) analyses, and the remaining section is undergone the mercury intrusion porosimetry to obtain complementary information on the pore-size distribution. By ensuring the position and orientation of the SEM images taken, the number of SEM images, as well as the amount of particles and voids identified are maximized to enhance the statistical representation of the analysed results. In each sample, at least 3000 particles are identified, and the voids are segmented using proper binary images, of which their irregular shapes are further described using an equivalent ellipse. Fabric tensors are used to quantify the directional behaviour of the voids and particles. In addition, the shape evolution of the pores is examined to further understand the associated deformation mechanism. These comprehensive analyses provides quantitative evidences that the loading response of clay under 1-D consolidation is mainly governed by the inter-aggregate pores.
Keywords	Environmental sciences ; GE1-350
Subject code	669
Language	English
Publishing date	2019-01-01T00:00:00Z
Publisher	EDP Sciences
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: DV-Det

Su, Zhaoyu / Tan, Pin Siang / Wang, Yu-Hsing

Efficient 3D Point Cloud Object Detection with Dynamic Voxelization

2021

Abstract: In this work, we propose a novel two-stage framework for the efficient 3D point cloud object detection. Instead of transforming point clouds into 2D bird eye view projections, we parse the raw point cloud data directly in the 3D space yet achieve ... ...

Abstract	In this work, we propose a novel two-stage framework for the efficient 3D point cloud object detection. Instead of transforming point clouds into 2D bird eye view projections, we parse the raw point cloud data directly in the 3D space yet achieve impressive efficiency and accuracy. To achieve this goal, we propose dynamic voxelization, a method that voxellizes points at local scale on-the-fly. By doing so, we preserve the point cloud geometry with 3D voxels, and therefore waive the dependence on expensive MLPs to learn from point coordinates. On the other hand, we inherently still follow the same processing pattern as point-wise methods (e.g., PointNet) and no longer suffer from the quantization issue like conventional convolutions. For further speed optimization, we propose the grid-based downsampling and voxelization method, and provide different CUDA implementations to accommodate to the discrepant requirements during training and inference phases. We highlight our efficiency on KITTI 3D object detection dataset with 75 FPS and on Waymo Open dataset with 25 FPS inference speed with satisfactory accuracy.
Keywords	Computer Science - Computer Vision and Pattern Recognition
Subject code	006
Publishing date	2021-07-27
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Deep learning-enhanced extraction of drainage networks from digital elevation models

Mao, Xin / Chow, Jun Kang / Su, Zhaoyu / Wang, Yu-Hsing / Li, Jiaye / Wu, Tao / Li, Tiejian

Environmental modelling & software. 2021 Oct., v. 144

2021

Abstract: Drainage network extraction is essential for different research and applications. However, traditional methods have low efficiency, low accuracy for flat regions, and difficulties in detecting channel heads. Although deep learning techniques have been ... ...

Abstract	Drainage network extraction is essential for different research and applications. However, traditional methods have low efficiency, low accuracy for flat regions, and difficulties in detecting channel heads. Although deep learning techniques have been used to solve these problems, different challenges remain unsolved. Therefore, we introduced distributed representations of aspect features to facilitate the deep learning model calculating the flow direction; adopted a semantic segmentation model, U-Net, to improve the accuracy and efficiency in predicting flow directions and in pixel classifications; and used postprocessing to delineate the flowlines. Our proposed framework achieved state-of-the-art results compared with the traditional methods and the published deep-learning-based methods. Further, case study results demonstrated that our framework can extract drainage networks with high accuracy for rivers of different widths flowing through terrains of different characteristics. This framework, requiring no parameters provided by users, can also produce waterbody polygons and allow cyclic graphs in the drainage network.
Keywords	case studies ; computer software ; drainage ; surface water
Language	English
Dates of publication	2021-10
Publishing place	Elsevier Ltd
Document type	Article
ISSN	1364-8152
DOI	10.1016/j.envsoft.2021.105135
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Understanding the dynamic properties of trees using the motions constructed from multi-beam flash light detection and ranging measurements.

Chau, Wai Yi / Loong, Cheng Ning / Wang, Yu-Hsing / Chiu, Siu-Wai / Tan, Tun Jian / Wu, Jimmy / Leung, Mei Ling / Tan, Pin Siang / Ooi, Ghee Leng

Journal of the Royal Society, Interface

2022 Volume 19, Issue 193, Page(s) 20220319

Abstract: Measuring the three-dimensional motion of trees at every position remains challenging as it requires dynamic measurement technology with sufficient spatial and temporal resolution. Consequently, this study explores the use of a novel multi-beam flash ... ...

Abstract	Measuring the three-dimensional motion of trees at every position remains challenging as it requires dynamic measurement technology with sufficient spatial and temporal resolution. Consequently, this study explores the use of a novel multi-beam flash light detection and ranging (LiDAR) sensor to tackle such a sensing barrier. A framework is proposed to record tree vibrations, to construct the motions of tree skeletons from the point-cloud frames recorded by the LiDAR sensor and to derive the dynamic properties of trees. The feasibility of the framework is justified through measurement on a
MeSH term(s)	Motion ; Trees/physiology ; Vibration
Language	English
Publishing date	2022-08-03
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2156283-0
ISSN	1742-5662 ; 1742-5689
ISSN (online)	1742-5662
ISSN	1742-5689
DOI	10.1098/rsif.2022.0319
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: DV-ConvNet

Su, Zhaoyu / Tan, Pin Siang / Chow, Junkang / Wu, Jimmy / Cheong, Yehur / Wang, Yu-Hsing

Fully Convolutional Deep Learning on Point Clouds with Dynamic Voxelization and 3D Group Convolution

2020

Abstract: 3D point cloud interpretation is a challenging task due to the randomness and sparsity of the component points. Many of the recently proposed methods like PointNet and PointCNN have been focusing on learning shape descriptions from point coordinates as ... ...

Abstract	3D point cloud interpretation is a challenging task due to the randomness and sparsity of the component points. Many of the recently proposed methods like PointNet and PointCNN have been focusing on learning shape descriptions from point coordinates as point-wise input features, which usually involves complicated network architectures. In this work, we draw attention back to the standard 3D convolutions towards an efficient 3D point cloud interpretation. Instead of converting the entire point cloud into voxel representations like the other volumetric methods, we voxelize the sub-portions of the point cloud only at necessary locations within each convolution layer on-the-fly, using our dynamic voxelization operation with self-adaptive voxelization resolution. In addition, we incorporate 3D group convolution into our dense convolution kernel implementation to further exploit the rotation invariant features of point cloud. Benefiting from its simple fully-convolutional architecture, our network is able to run and converge at a considerably fast speed, while yields on-par or even better performance compared with the state-of-the-art methods on several benchmark datasets.
Keywords	Computer Science - Computer Vision and Pattern Recognition
Subject code	006
Publishing date	2020-09-07
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Domain randomization-enhanced deep learning models for bird detection.

Mao, Xin / Chow, Jun Kang / Tan, Pin Siang / Liu, Kuan-Fu / Wu, Jimmy / Su, Zhaoyu / Cheong, Ye Hur / Ooi, Ghee Leng / Pang, Chun Chiu / Wang, Yu-Hsing

Scientific reports

2021 Volume 11, Issue 1, Page(s) 639

Abstract: Automatic bird detection in ornithological analyses is limited by the accuracy of existing models, due to the lack of training data and the difficulties in extracting the fine-grained features required to distinguish bird species. Here we apply the ... ...

Abstract	Automatic bird detection in ornithological analyses is limited by the accuracy of existing models, due to the lack of training data and the difficulties in extracting the fine-grained features required to distinguish bird species. Here we apply the domain randomization strategy to enhance the accuracy of the deep learning models in bird detection. Trained with virtual birds of sufficient variations in different environments, the model tends to focus on the fine-grained features of birds and achieves higher accuracies. Based on the 100 terabytes of 2-month continuous monitoring data of egrets, our results cover the findings using conventional manual observations, e.g., vertical stratification of egrets according to body size, and also open up opportunities of long-term bird surveys requiring intensive monitoring that is impractical using conventional methods, e.g., the weather influences on egrets, and the relationship of the migration schedules between the great egrets and little egrets.
MeSH term(s)	Animal Migration/physiology ; Animals ; Birds/physiology ; Deep Learning ; Environment ; Random Allocation ; Weather
Language	English
Publishing date	2021-01-12
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-020-80101-x
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: Is Discriminator a Good Feature Extractor?

Mao, Xin / Su, Zhaoyu / Tan, Pin Siang / Chow, Jun Kang / Wang, Yu-Hsing

2019

Abstract: The discriminator from generative adversarial nets (GAN) has been used by researchers as a feature extractor in transfer learning and appeared worked well. However, there are also studies that believe this is the wrong research direction because ... ...

Abstract	The discriminator from generative adversarial nets (GAN) has been used by researchers as a feature extractor in transfer learning and appeared worked well. However, there are also studies that believe this is the wrong research direction because intuitively the task of the discriminator focuses on separating the real samples from the generated ones, making features extracted in this way useless for most of the downstream tasks. To avoid this dilemma, we first conducted a thorough theoretical analysis of the relationship between the discriminator task and the features extracted. We found that the connection between the task of the discriminator and the feature is not as strong as was thought, for that the main factor restricting the feature learned by the discriminator is not the task, but is the need to prevent the entire GAN model from mode collapse during the training. From this perspective and combined with further analyses, we found that to avoid mode collapse, the features extracted by the discriminator are not guided to be different for the real samples, but divergence without noise is indeed allowed and occupies a large proportion of the feature space. This makes the features more robust and helps answer the question as to why the discriminator can succeed as a feature extractor in related research. Consequently, to expose the essence of the discriminator extractor as different from other extractors, we analyze the counterpart of the discriminator extractor, the classifier extractor that assigns the target samples to different categories. We found the performance of the discriminator extractor may be inferior to the classifier based extractor when the source classification task is similar to the target task, which is the common case, but the ability to avoid noise prevents the discriminator from being replaced by the classifier. Comment: 12 pages, 3 figures, two tables
Keywords	Computer Science - Machine Learning ; Statistics - Machine Learning
Subject code	004
Publishing date	2019-12-02
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: The Effects of the pH-influenced Structure on the Dielectric Properties of Kaolinite–Water Mixtures

Dong, Xiaobo / Wang, Yu-Hsing

Soil Science Society of America journal. 2008 Nov., v. 72, no. 6

2008

Abstract: The properties of clay–water mixtures are reflected in their wide-frequency dielectric responses that result from different polarization mechanisms. This feature is useful in various soil science applications but has not been systematically investigated. ...

Abstract	The properties of clay–water mixtures are reflected in their wide-frequency dielectric responses that result from different polarization mechanisms. This feature is useful in various soil science applications but has not been systematically investigated. The objective of this study was to characterize the broadband dielectric spectrum of kaolinite sediments with different charge properties and structures using a slim-form open-ended coaxial probe. The sediment structure in this study was manipulated by changing the pore-fluid pH. When the pH was below the isoelectrical point of the edge surface, IEP, the edge-to-face flocculation structure was formed in voluminous sediments with an average porosity of 0.87 (Group A samples). A higher dielectric constant due to bulk water polarization (an average of 65.47) was measured because of the higher water content. As the pH was increased to greater than the IEP, a dense sediment with face-to-face aggregation was produced in the Group B samples, and a lower dielectric constant (an average of 60.11) was obtained. In bound water polarization, a higher relaxation strength (∼2.7 times higher on average) and a longer relaxation time (∼1.5 times longer on average) were observed in the Group B samples compared with those of the Group A samples. Similar trends can also be found in the results of spatial polarization. These findings can be attributed to more negatively charged surfaces and denser packing. Fluid conductivity dominated the global conductivity of the sediment in the Group A samples so that the β value, i.e., the ratio between the conductivity of the sediment and the fluid, was <1. The β value was >1 in the Group B samples owing to an overcompensation of surface conduction.
Keywords	dielectric properties ; mixtures ; kaolinite ; water ; sediments ; pH ; electrical charges
Language	English
Dates of publication	2008-11
Size	p. 1532-1541.
Publishing place	Soil Science Society
Document type	Article
Note	epub
ZDB-ID	2239747-4
ISSN	1435-0661 ; 0361-5995
ISSN (online)	1435-0661
ISSN	0361-5995
DOI	10.2136/sssaj2007.0238
Database	NAL-Catalogue (AGRICOLA)

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