3 Search Results for "Yang, Xiang"

Document
DOI: 10.4230/OASIcs.Fog-IoT.2020.11
Realizing Video Analytic Service in the Fog-Based Infrastructure-Less Environments

Authors: Qiushi Zheng, Jiong Jin, Tiehua Zhang, Longxiang Gao, and Yong Xiang

Published in: OASIcs, Volume 80, 2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020)

Abstract
Deep learning has unleashed the great potential in many fields and now is the most significant facilitator for video analytics owing to its capability to providing more intelligent services in a complex scenario. Meanwhile, the emergence of fog computing has brought unprecedented opportunities to provision intelligence services in infrastructure-less environments like remote national parks and rural farms. However, most of the deep learning algorithms are computationally intensive and impossible to be executed in such environments due to the needed supports from the cloud. In this paper, we develop a video analytic framework, which is tailored particularly for the fog devices to realize video analytic service in a rapid manner. Also, the convolution neural networks are used as the core processing unit in the framework to facilitate the image analysing process.
Cite as

Qiushi Zheng, Jiong Jin, Tiehua Zhang, Longxiang Gao, and Yong Xiang. Realizing Video Analytic Service in the Fog-Based Infrastructure-Less Environments. In 2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020). Open Access Series in Informatics (OASIcs), Volume 80, pp. 11:1-11:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{zheng_et_al:OASIcs.Fog-IoT.2020.11,
  author =	{Zheng, Qiushi and Jin, Jiong and Zhang, Tiehua and Gao, Longxiang and Xiang, Yong},
  title =	{{Realizing Video Analytic Service in the Fog-Based Infrastructure-Less Environments}},
  booktitle =	{2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020)},
  pages =	{11:1--11:9},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-144-3},
  ISSN =	{2190-6807},
  year =	{2020},
  volume =	{80},
  editor =	{Cervin, Anton and Yang, Yang},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Fog-IoT.2020.11},
  URN =		{urn:nbn:de:0030-drops-120050},
  doi =		{10.4230/OASIcs.Fog-IoT.2020.11},
  annote =	{Keywords: Fog Computing, Convolution Neural Network, Infrastructure-less Environment}
}
Document
DOI: 10.4230/OASIcs.VLUDS.2011.1
Virtual Reality supported Visualization and Evaluation of Noise Levels in Manufacturing Environments

Authors: Xiang Yang, Bernd Hamann, and Jan C. Aurich

Published in: OASIcs, Volume 27, Visualization of Large and Unstructured Data Sets: Applications in Geospatial Planning, Modeling and Engineering - Proceedings of IRTG 1131 Workshop 2011

Abstract
Virtual Reality (VR) provides users advanced visualization and interaction technology for designing, analyzing and exploring complex data. To address the issue of noise in manufacturing environments, we developed a VR-supported method allowing users to explore noise behavior. This method consists of an implementation of acoustic simulation and visualization for both desktop and Cave Automatic Virtual Environment (CAVE) based VR systems. It enables user-oriented, interactive analysis of simulated data, where there capability to immerse oneself in the data is especially valuable. In a real-world factory, the acoustic measurements obtained essential input data for simulation settings and validation data for simulation results. Furthermore, some political and legal aspects are addressed to enhance the evaluation of results and the visualization. By using the implemented software tool, users are able to understand and investigate the noise issue in manufacturing straightforwardly.
Cite as

Xiang Yang, Bernd Hamann, and Jan C. Aurich. Virtual Reality supported Visualization and Evaluation of Noise Levels in Manufacturing Environments. In Visualization of Large and Unstructured Data Sets: Applications in Geospatial Planning, Modeling and Engineering - Proceedings of IRTG 1131 Workshop 2011. Open Access Series in Informatics (OASIcs), Volume 27, pp. 1-12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)

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@InProceedings{yang_et_al:OASIcs.VLUDS.2011.1,
  author =	{Yang, Xiang and Hamann, Bernd and Aurich, Jan C.},
  title =	{{Virtual Reality supported Visualization and Evaluation of Noise Levels in Manufacturing Environments}},
  booktitle =	{Visualization of Large and Unstructured Data Sets: Applications in Geospatial Planning, Modeling and Engineering - Proceedings of IRTG 1131 Workshop 2011},
  pages =	{1--12},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-46-0},
  ISSN =	{2190-6807},
  year =	{2012},
  volume =	{27},
  editor =	{Garth, Christoph and Middel, Ariane and Hagen, Hans},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.VLUDS.2011.1},
  URN =		{urn:nbn:de:0030-drops-37370},
  doi =		{10.4230/OASIcs.VLUDS.2011.1},
  annote =	{Keywords: virtual reality, acoustic simulation, visualization, manufacturing}
}
Document
DOI: 10.4230/OASIcs.VLUDS.2010.111
Visualization in Human-Centered Virtual Factories

Authors: Xiang Yang, Eduard Deines, and Jan C. Aurich

Published in: OASIcs, Volume 19, Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering (IRTG 1131 Workshop) (2011)

Abstract
In a manufacturing system (MS), a wide range of human activities are applied in production processes. The human factor plays a core role and should be incorporated into the design, planning and decision making processes. In this work we describe different definitions, developments and existing concepts of a Virtual Factory (VF) and discuss VFs from the human oriented point of view. Furthermore, we analyze the potential need and use of visualization methods in VF study and propose a human-centered VF concept. Following this concept we introduce an example implementation and describe how our model facilitates the decision making and design process in MS. In addition, we show an example of a noise analysis of working environment, which is based on our virtual factory model.
Cite as

Xiang Yang, Eduard Deines, and Jan C. Aurich. Visualization in Human-Centered Virtual Factories. In Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering (IRTG 1131 Workshop). Open Access Series in Informatics (OASIcs), Volume 19, pp. 111-119, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2011)

Copy BibTex To Clipboard

@InProceedings{yang_et_al:OASIcs.VLUDS.2010.111,
  author =	{Yang, Xiang and Deines, Eduard and Aurich, Jan C.},
  title =	{{Visualization in Human-Centered Virtual Factories}},
  booktitle =	{Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering (IRTG 1131 Workshop)},
  pages =	{111--119},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-29-3},
  ISSN =	{2190-6807},
  year =	{2011},
  volume =	{19},
  editor =	{Middel, Ariane and Scheler, Inga and Hagen, Hans},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.VLUDS.2010.111},
  URN =		{urn:nbn:de:0030-drops-31031},
  doi =		{10.4230/OASIcs.VLUDS.2010.111},
  annote =	{Keywords: Visualization, Virtual Reality, Virtual Factory, Sound Simulation}
}
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