Volatile Data Mining: A Proof Of Concept For Performance Evaluation Of The Built Environment Using Drones

2017 ◽  
Keyword(s):  
Data Mining ◽  
Performance Evaluation ◽  
Built Environment ◽  
Proof Of Concept

scholarly journals Preparation and Performance Evaluation of Duotone 3D-Printed Polyetheretherketone as Oral Prosthetic Materials: A Proof-of-Concept Study

Polymers ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 1949
Author(s):  
Ling Ding ◽  
Wei Lu ◽  
Jiaqi Zhang ◽  
Chuncheng Yang ◽  
Guofeng Wu
Keyword(s):  
Titanium Dioxide ◽  
Performance Evaluation ◽  
Mechanical Performance ◽  
Mechanical Tests ◽  
Flexural Properties ◽  
Proof Of Concept ◽  
Tooth Color ◽  
Dental Application ◽  
3D Printed ◽  
And Performance

Literature has reported the successful use of 3D printed polyetheretherketone (PEEK) to fabricate human body implants and oral prostheses. However, the current 3D printed PEEK (brown color) cannot mimic the vivid color of oral tissues and thus cannot meet the esthetical need for dental application. Therefore, titanium dioxide (TiO2) and ferric oxide (Fe2O3) were incorporated into PEEK to prepare a series of tooth-color and gingival-color PEEK composites in this study. Through color measurements and mechanical tests, the color value and mechanical performance of the 3D printed PEEK composites were evaluated. In addition, duotone PEEK specimens were printed by a double nozzle with an interface between tooth-color and gingival-color parts. The mechanical performance of duotone PEEK with two different interfaces (horizontal and vertical) was investigated. With the addition of TiO2 and Fe2O3, the colors of 3D printed PEEK composites become closer to that of dental shade guides. 3D printed PEEK composites generally demonstrated superior tensile and flexural properties and hence have great potential in the dental application. In addition, duotone 3D printed PEEK with a horizontal interfacial orientation presented better mechanical performance than that with a vertical one.

scholarly journals Life-cycle Asset Management in Residential Developments Building on Transport System Critical Attributes via a Data-mining Algorithm

Buildings ◽  
2018 ◽  
Vol 9 (1) ◽  
pp. 1 ◽  
Author(s):  
Umair Hasan ◽  
Andrew Whyte ◽  
Hamad Al Jassmi
Keyword(s):  
Data Mining ◽  
Life Cycle ◽  
Built Environment ◽  
Transport System ◽  
Asset Management ◽  
Public Transport ◽  
Categorical Variables ◽  
Data Mining Algorithm ◽  
Large Set ◽  
Mining Algorithm

Public transport can discourage individual car usage as a life-cycle asset management strategy towards carbon neutrality. An effective public transport system contributes greatly to the wider goal of a sustainable built environment, provided the critical transit system attributes are measured and addressed to (continue to) improve commuter uptake of public systems by residents living and working in local communities. Travel data from intra-city travellers can advise discrete policy recommendations based on a residential area or development’s public transport demand. Commuter segments related to travelling frequency, satisfaction from service level, and its value for money are evaluated to extract econometric models/association rules. A data mining algorithm with minimum confidence, support, interest, syntactic constraints and meaningfulness measure as inputs is designed to exploit a large set of 31 variables collected for 1,520 respondents, generating 72 models. This methodology presents an alternative to multivariate analyses to find correlations in bigger databases of categorical variables. Results here augment literature by highlighting traveller perceptions related to frequency of buses, journey time, and capacity, as a net positive effect of frequent buses operating on rapid transit routes. Policymakers can address public transport uptake through service frequency variation during peak-hours with resultant reduced car dependence apt to reduce induced life-cycle environmental burdens of buildings by altering residents’ mode choices, and a potential design change of buildings towards a public transit-based, compact, and shared space urban built environment.

Image Features from Morphological Scale-Spaces

2011 ◽  
pp. 32-79
Author(s):  
Sébastien Lefèvre
Keyword(s):  
Data Mining ◽  
Performance Evaluation ◽  
Video Processing ◽  
State Of The Art ◽  
Image Features ◽  
Video Data ◽  
Multimedia Data ◽  
Multimedia Data Mining ◽  
Shot Detection ◽  
Scale Spaces

Video processing and segmentation are important stages for multimedia data mining, especially with the advance and diversity of video data available. The aim of this chapter is to introduce researchers, especially new ones, to the “video representation, processing, and segmentation techniques”. This includes an easy and smooth introduction, followed by principles of video structure and representation, and then a state-of-the-art of the segmentation techniques focusing on the shot-detection. Performance evaluation and common issues are also discussed before concluding the chapter.

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