Spectrum-preserving sparsification for visualization of big graphs

Imre, Martin; Tao, Jun; Wang, Yongyu; Zhao, Zhiqiang; Feng, Zhuo; Wang, Chaoli

doi:10.1016/j.cag.2020.02.004

Cited by 14 publications

(8 citation statements)

References 29 publications

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“…Many factors can destroy this balance, so that the pleural fluid increases, that is, pleural effusion. PE is a common medical problem, and its pathogenesis includes (Imre et al 2020 ; Liu et al 2020 ; Metintas et al 2010 ; Ye et al 2020 ): The increase of pleural capillary hydrostatic pressure is caused by cardiac insufficiency, increased blood volume and venous obstruction. Low protein synthesis or excessive loss of protein results in hypoproteinemia, which leads to the decrease of colloidal osmotic pressure.…”

Section: Introductionmentioning

confidence: 99%

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RETRACTED ARTICLE: AI driven feature extraction model for chest cavity spectrum signal visualization

Niu

2021

Int J Speech Technol

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Lung cancer is the most fatal cancer in the world. Early detection, diagnosis and treatment of lung cancer is an important means to improve the survival rate of lung cancer patients. The early signs of lung cancer are small pulmonary nodules, so early detection and timely treatment of pulmonary nodules are of great significance to save the lives of lung cancer patients. With the progress of medical CT technology, a large number of image data obtained by medical CT examination are increasing, which can provide more organ and tissue information, but also bring a great burden to doctors. Therefore, the detection technology of thoracic spectrum signal is a key point. The chest cavity is a non adjustable resonator with a fixed volume and space, which is located in the chest ribs and below the vocal cords. According to the principle of resonance in physical theory, the resonance characteristics are mainly related to the size of the cavity surrounded by a certain hardness of the outer wall. Therefore, some researchers believe that the volume of the chest cavity is related to the resonance of the chest cavity. Although in recent years, some teams have combined deep learning and machine learning to improve signal feature extraction, which makes signal feature extraction easier and more efficient, most of them are still based on IQ data for signal modulation recognition. Therefore, this paper studies the visual feature extraction model based on artificial intelligence and thoracic echo spectrum, and the experimental results show the effectiveness of this method compared with the latest approaches.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: AI driven feature extraction model for chest cavity spectrum signal visualization

Niu

2021

Int J Speech Technol

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“…The authors report significant improvements both in power consumption and other design metrics to support low power quality rendering. Finally, a paper by Martin et al [10] proposes a method to simplify big graphs using spectral graph theory, in a way suitable for efficient drawing of large graphs at varying levels of detail. Their approach outperforms state-of-theart graph simplification methods while working with any graph drawing algorithm.…”

Section: Technical Sectionmentioning

confidence: 99%

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Jorge¹

2020

Computers & Graphics

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“…GraphVisual supports the D3-force-directed layout [7] which is an implementation and adaptation of Dwyer's [12] algorithm, fast multipole multilevel method (FM 3 ) [14], ForceAtlas2 [20] which focuses on network spatialization, OpenOrd [22] which is designed for large graphs, and Yifan Hu's algorithm [18] which combines a multilevel approach, together with Barnes and Hut octree force calculation [2] and an adaptive cooling scheme for the general force model for efficient high-quality graph drawing. Among non-force-directed layouts, GraphVisual supports a spectral layout which uses the spectrum of the graph to assign node positions [19], a circular layout which simply aligns nodes along a circle, and a random layout which assigns node positions randomly. In addition, GraphVisual supports two special layouts, geographical layout and bipartite layout, for drawing graphs with geographical information and bipartite graphs, respectively.…”

Section: Introductionmentioning

confidence: 99%

GraphVisual: Design and Evaluation of a Web-Based Visualization Tool for Teaching and Learning Graph Visualization

Imre

Chang

Wang

et al.

2020 ASEE Virtual Annual Conference Content Access Proceedings

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is a fourth-yeard PhD candidate at the University of Notre Dame working with Dr. Chaoli Wang on High Performance Computing and Scientific Visualization. His main research focus is summarization and reconstruction of big data using GPU-acceleration and deep learning techniques. He has applied his research in isosurface selection for volume visualization and analysis, graph visualization, and is currently using deep learning techniques for analysis of unsteady flow simulations. He has completed a research internship at Argonne National Laboratory in summer 2018. He received his BSc (2014) and MSc (2016) in Software Engineering at the Vienna University of Technology. During his Master's program, he conducted research at the VRVis Research Center in Vienna and continued acquiring experience during a research internship at the University of California, Irvine. Miss Wenqing Chang, Xi'an Jiaotong UniversityWenqing Chang is currently a senior student in Information Engineering from Xi'an Jiaotong University. In 2018, she joined NUS Summer Workshop, developing a 2D webpage game using WebGL and rendering 3D animation using OpenGL. From the fall of 2018 to present, she is a lab researcher in wireless communication, built ambient backscatter enabled secondary communication model and right now is involved in deep learning for joint source-channel coding.

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Spectrum-preserving sparsification for visualization of big graphs

Cited by 14 publications

References 29 publications

RETRACTED ARTICLE: AI driven feature extraction model for chest cavity spectrum signal visualization

RETRACTED ARTICLE: AI driven feature extraction model for chest cavity spectrum signal visualization

Editorial Note

GraphVisual: Design and Evaluation of a Web-Based Visualization Tool for Teaching and Learning Graph Visualization

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