Visual analysis method for cultural heritage site risk assessment

Qian, Kun; Sun, Jianghua; Chen, Hui; Zhang, J.

doi:10.1007/s12650-015-0325-7

Cited by 8 publications

(4 citation statements)

References 12 publications

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“…For this task, mainly cultural heritage applications are of interest such as analyzing the risk, cultural heritage sites are facing because of environmental or other influences. Qian et al [QSCZ16] propose a visual analysis technique for the assessment of the risk of deterioration, which is focusing on matching the major needs of the domain with the objectives of deterioration. They encode the risks of detoriation in spatial views, integrating techniques of visual analytics for analyzing the risk level.…”

Section: Visual Computing In Materials Sciencementioning

confidence: 99%

“…Results of individual segmentation‐pipeline runs are selected by brushing in the corresponding scatter plot and linked to 2D slice views and 3D renderings of aggregated segmentation masks and statistical contour renderings. Qian et al [QSCZ16] use linking and brushing to support conservators and site managers in the deterioration risk assessment of cultural heritage. Their approach allows brushing of exogenous factors such as humidity, light, or wind, as well as endogenous factors which cause deterioration.…”

Section: Visual Computing In Materials Sciencementioning

confidence: 99%

“…This way, only fibers within the filter range are visible for the evaluation. Qian et al [QSCZ16] implemented filtering as drop‐down menues for constraining areas of interest, endogenous risk factors, and exogenous factors. This filtering techniques can be combined to for refinements, which demonstrates another option using filters.…”

Section: Visual Computing In Materials Sciencementioning

confidence: 99%

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STAR: Visual Computing in Materials Science

Heinzl

Stappen

2017

Computer Graphics Forum

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Visual computing has become highly attractive for boosting research endeavors in the materials science domain. Using visual computing, a multitude of different phenomena may now be studied, at various scales, dimensions, or using different modalities. This was simply impossible before. Visual computing techniques provide novel insights in order to understand complex material systems of interest, which is demonstrated by strongly rising number of new approaches, publishing new techniques for materials analysis and simulation. Outlining the proximity of materials science and visual computing, this state of the art report focuses on the intersection of both domains in order to guide research endeavors in this field. We provide a systematic survey on the close interrelations of both fields as well as how they profit from each other. Analyzing the existing body of literature, we review the domain of visual computing supported materials science, starting with the definition of materials science as well as material systems for which visual computing is frequently used. Major tasks for visual computing, visual analysis and visualization in materials sciences are identified, as well as simulation and testing techniques, which are providing the data for the respective analyses. We reviewed the input data characteristics and the direct and derived outputs, the visualization techniques and visual metaphors used, as well as the interactions and analysis workflows employed. All our findings are finally integrated in a cumulative matrix, giving insights about the different interrelations of both domains. We conclude our report with the identification of open high level and low level challenges for future research.

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Section: Visual Computing In Materials Sciencementioning

confidence: 99%

Section: Visual Computing In Materials Sciencementioning

confidence: 99%

Section: Visual Computing In Materials Sciencementioning

confidence: 99%

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STAR: Visual Computing in Materials Science

Heinzl

Stappen

2017

Computer Graphics Forum

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“…Scientific and suitable protection is essential to cultural relics for their longterm preservation [13]. Many experts and researchers have put their efforts into the study of protecting the cultural heritages [8,14]. Large amount of data, including information about the relics themselves, the degradations and corresponding impact factors etc., needs to be captured, collected, archived, stored, and analysed [15].…”

Section: Introductionmentioning

confidence: 99%

Energy balanced routing protocol based on improved particle swarm optimisation and ant colony algorithm for museum environmental monitoring of cultural relics

2023

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The environmental monitoring of cultural relics based on wireless sensor networks in museums demands for the transmission and processing of massive data, which in turn leads to problems, such as heavy network traffic, high time delay, and unbalanced node energy consumption. To solve these problems, an energy balanced routing protocol which can minimise the network energy consumption is proposed. The improved swarm intelligence optimisation algorithm which combined particle swarm optimisation with ant colony optimisation is adopted to construct an environmental monitoring system for cultural relics preservation. Simulation results show that the decrease of the path length for data transmission under the proposed algorithm is 2.5% higher than that of other classical algorithms, indicating that the proposed algorithm can effectively reduce the length of network path and improve the transmission performance of network system. In view of optimisation rounds and simulation time, the energy consumption of the network system under our algorithm is 57.5% less compared with other classical algorithms, and the average residual energy variance is 57.1% less. The cultural relics environmental monitoring system based on the proposed routing protocol has better network load balancing performance.

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