Seeking Northlake: Place, technology, and public as enabling constraints for urban transdisciplinary research

Brown, Megan E.; Benson, Odessa Gonzalez; Keel, Roneva; Mahoney, Eleanor; Porter, Jennifer; Thompson, James R.

doi:10.1016/j.cities.2016.10.003

Cited by 3 publications

(2 citation statements)

References 56 publications

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“…With the ever-enriching city lives, open public places, such as pedestrian streets, commercial streets, parks, and squares, have gradually become an important part of people's lives [1]. These open places, without definite space boundary, are likely to cause overcrowding with the inrush of massive pedestrians in a short period, which could arise evacuation problems, leading to the occurrence of stampedes [2,3].…”

Section: Introductionmentioning

confidence: 99%

Pedestrian Flow Prediction in Open Public Places Using Graph Convolutional Network

Liu

et al. 2021

IJGI

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Open public places, such as pedestrian streets, parks, and squares, are vulnerable when the pedestrians thronged into the sidewalks. The crowd count changes dynamically over time with various external factors, such as surroundings, weekends, and peak hours, so it is essential to predict the accurate and timely crowd count. To address this issue, this study introduces graph convolutional network (GCN), a network-based model, to predict the crowd flow in a walking street. Compared with other grid-based methods, the model is capable of directly processing road network graphs. Experiments show the GCN model and its extension STGCN consistently and significantly outperform other five baseline models, namely HA, ARIMA, SVM, CNN and LSTM, in terms of RMSE, MAE and R2. Considering the computation efficiency, the standard GCN model was selected to predict the crowd. The results showed that the model obtains superior performances with higher prediction precision on weekends and peak hours, of which R2 are above 0.9, indicating the GCN model can capture the pedestrian features in the road network effectively, especially during the periods with massive crowds. The results will provide practical references for city managers to alleviate road congestion and help pedestrians make smarter planning and save travel time.

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Section: Introductionmentioning

confidence: 99%

Pedestrian Flow Prediction in Open Public Places Using Graph Convolutional Network

Liu

et al. 2021

IJGI

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“…Accordingly, new concepts and systems need to be shaped or integrated into the educational process that also make the traditional triangle of passive education (content, teacher, and student) invalid (Steiner & Posch, 2006). Therefore, the demand for sustainability has made the teaching scenarios more complicated since a variety of new methods, lenses, and competencies should merge to make teaching schemes more careerrelevant and ensure that they meet the new expectations (Brown et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Analysing Transdisciplinary Education: A Scoping Review

Daneshpour

Kwegyir-Afful

2021

Sci & Educ

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The present study sheds light on transdisciplinary education through the application of a scoping literature review, as a lack of a comprehensive synthesis in this area is evident. Thus, the overview frames and outlines the scattered research that has been fulfilled until now in this field. As a result, within transdisciplinary education, medical and adolescent themes form the main scopes, while within sustainable transdisciplinary education, pedagogical design, socio-efficiency, and philosophy are the major themes. Furthermore, the present study contributes to the understanding of transdisciplinary education by highlighting the avenues for future research. Consequently, the translation of transdisciplinary teaching practices to comparable languages and an increase of transparency in the application and reporting of the transdisciplinary design steps are suggested.

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Problematizing transdisciplinary urbanism research: A reply to “Seeking Northlake”

Rizzo

Galanakis

2017

Cities

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Seeking Northlake: Place, technology, and public as enabling constraints for urban transdisciplinary research

Cited by 3 publications

References 56 publications

Pedestrian Flow Prediction in Open Public Places Using Graph Convolutional Network

Pedestrian Flow Prediction in Open Public Places Using Graph Convolutional Network

Analysing Transdisciplinary Education: A Scoping Review

Problematizing transdisciplinary urbanism research: A reply to “Seeking Northlake”

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