level building
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2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Steven Pattinson ◽  
James Cunningham ◽  
David Preece ◽  
Mark A. P. Davies

PurposeThis paper identifies exigent factors that enable and constrain trust building in a science-based innovation ecosystem.Design/methodology/approachSet in the Northeast England, this study adopts a processual sensemaking approach to thematically analyse interviews with a diverse range of participants in six science-based SMEs.FindingsThe findings provide a unique exposition of trust building in an innovation ecosystem across geographic and platform relationships. In doing so, the findings highlight factors outside of contractual agreements that enable or constrain trust building in an innovation ecosystem.Research limitations/implicationsLimitations centred on subjectivity in the use of thematic analysis, sample bias and size. Sampling limitations were mitigated through the research design and analysis.Practical implicationsThe findings provide unique insights into understanding the exigent factors that enable or constrain trust building in a science-based innovation ecosystem.Originality/valueThe study identifies five exigent factors that constrain or enable trust building in science-based SMEs' innovation ecosystem at a micro-level – building network relationships, degree of novelty, protection of innovations, propensity for adding value, propensity for risk.


2022 ◽  
Vol 51 ◽  
pp. 101475
Author(s):  
Yan Feng ◽  
Dorine C. Duives ◽  
Serge P. Hoogendoorn

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 207
Author(s):  
Qi Chen ◽  
Yuanyi Zhang ◽  
Xinyuan Li ◽  
Pengjie Tao

Deep learning techniques such as convolutional neural networks have largely improved the performance of building segmentation from remote sensing images. However, the images for building segmentation are often in the form of traditional orthophotos, where the relief displacement would cause non-negligible misalignment between the roof outline and the footprint of a building; such misalignment poses considerable challenges for extracting accurate building footprints, especially for high-rise buildings. Aiming at alleviating this problem, a new workflow is proposed for generating rectified building footprints from traditional orthophotos. We first use the facade labels, which are prepared efficiently at low cost, along with the roof labels to train a semantic segmentation network. Then, the well-trained network, which employs the state-of-the-art version of EfficientNet as backbone, extracts the roof segments and the facade segments of buildings from the input image. Finally, after clustering the classified pixels into instance-level building objects and tracing out the roof outlines, an energy function is proposed to drive the roof outline to maximally align with the building footprint; thus, the rectified footprints can be generated. The experiments on the aerial orthophotos covering a high-density residential area in Shanghai demonstrate that the proposed workflow can generate obviously more accurate building footprints than the baseline methods, especially for high-rise buildings.


2021 ◽  
Vol 10 (9) ◽  
pp. 328
Author(s):  
Sophie Pierszalowski ◽  
Jana Bouwma-Gearhart ◽  
Lindsay Marlow

While the benefits of undergraduate research experiences for students from underrepresented racial/ethnic groups have been well explored, more research is needed to better understand how students of color access these experiences. We summarize a non-structured review of literature that highlights barriers to success that students of color face in relation to STEM programming at the postsecondary level. Building from this, we report on a structured review of barriers to accessing undergraduate research. We discuss implications of the relative lack of research on access to undergraduate research for students of color at postsecondary institutions. We consider how barriers for the success and persistence of students of color in postsecondary STEM, overall, may manifest as barriers to accessing the undergraduate research experiences argued to help reduce these barriers. With the hope of guiding future relevant action, we put forth recommendations for researchers and practitioners.


2021 ◽  
Vol 1 ◽  
pp. 2287-2296
Author(s):  
Yuemin Hou ◽  
Linhong Ji

AbstractThis paper discusses the formation of structures by taking the process of gene transcription and translation as the template. The hypothesis of this paper is that the gene transcription and translation process can describe the formation of structures both in engineering design and in biology. The paper first presents design examples including integrated circuit (IC) chambers, flapping wings of bird robots, and typical mechanisms and formulate the formation patterns of the design process as four steps: information interpretation, selection of building blocks, the connection of building blocks, and formation of structures. The key step of the formation process is to assemble building blocks for structures both in engineering and in biology. Building blocks in biology are amino acids while they are structures in design. The autonomous degree of the formation process depends on the level of building blocks. The reuse degree of the building blocks depends on the level of building blocks too. In biology, structures of proteins are self-organized, so one way towards design automation is to use lower-level building blocks.


2021 ◽  
Vol 1 ◽  
pp. 1587-1596
Author(s):  
Lore Veelaert ◽  
Ingrid Moons ◽  
Els Du Bois

AbstractMaterials can be considered from a technical and experiential perspective. However, the latter perspective is more complex to study systematically. Four intertwined experiential levels describe the overall materials experience: sensorial, interpretive, affective, and performative level. Building upon the need in experiential material characterization for comparable physical material representations to enable within-material-class comparisons and the inclusion of extensive user aspects, this paper sums up the reasoning process regarding the understanding and design of an experimental set-up and its parameters of a specific case. The case objective is to formulate guidelines for the designer/researcher to set up experiential material characterization experiments with (i) plastic demonstrator forms and (ii) by consumers. Following elements are discussed: Assessors, Stimuli, Interaction Modalities, Dependent variables, Method, and Practical considerations. Next, future experiments can be carried out in order to generate holistic plastic material data on a larger scale, that can be collected in an experiential database and used by designers throughout the design process.


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