Introduction to Scientific Programming and Simulation Using R

Jones, Owen; Maillardet, Robert; Robinson, Andrew

doi:10.1201/9781420068740

Cited by 43 publications

(17 citation statements)

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“…Each AE vector contained 1024 values, corresponding to a PDF curve over the sampling intervals. Using the trapezoidal rule (Jones et al ., ), we approximated the area under the curve ( A n ) in each AE n vector. For a more detailed description of the trapezoidal, please refer to the Supporting Information.…”

Section: Methodsmentioning

confidence: 99%

Scanning electron microscopy image representativeness: morphological data on nanoparticles

Odziomek

Ushizima

Oberbek

et al. 2016

Journal of Microscopy

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A sample of a nanomaterial contains a distribution of nanoparticles of various shapes and/or sizes. A scanning electron microscopy image of such a sample often captures only a fragment of the morphological variety present in the sample. In order to quantitatively analyse the sample using scanning electron microscope digital images, and, in particular, to derive numerical representations of the sample morphology, image content has to be assessed. In this work, we present a framework for extracting morphological information contained in scanning electron microscopy images using computer vision algorithms, and for converting them into numerical particle descriptors. We explore the concept of image representativeness and provide a set of protocols for selecting optimal scanning electron microscopy images as well as determining the smallest representative image set for each of the morphological features. We demonstrate the practical aspects of our methodology by investigating tricalcium phosphate, Ca (PO ) , and calcium hydroxyphosphate, Ca (PO ) (OH), both naturally occurring minerals with a wide range of biomedical applications.

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Section: Methodsmentioning

confidence: 99%

Scanning electron microscopy image representativeness: morphological data on nanoparticles

Odziomek

Ushizima

Oberbek

et al. 2016

Journal of Microscopy

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“…and stemming or merging words equivalent in meaning. For that purpose we used the tm package (Feinerer 2015). Second, an appropriate number of topics needed to be selected for the LDA analysis.…”

Section: Technological Diversitymentioning

confidence: 99%

Multi-disciplinarity breeds diversity: the influence of innovation project characteristics on diversity creation in nanotechnology

et al. 2017

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Nanotechnology is an emerging and promising field of research. Creating sufficient technological diversity among its alternatives is important for the long-term success of nanotechnologies, as well as for other emerging technologies. Diversity prevents early lock-in, facilitates recombinant innovation, increases resilience, and allows market growth. Creation of new technological alternatives usually takes place in innovation projects in which public and private partners often collaborate. Currently, there is little empirical evidence about which characteristics of innovation projects influence diversity. In this paper we study the influence of characteristics of EU-funded nanotechnology projects on the creation of technological diversity. In addition to actor diversity and the network of the project, we also include novel variables that have a plausible influence on diversity creation: the degree of multi-disciplinarity of the project and the size of the joint knowledge base of project partners. We apply topic modelling (Latent Dirichlet allocation) as a novel method to categorize technological alternatives. Using an ordinal logistic regression model, our results show that the largest contribution to diversity comes from the multidisciplinary nature of a project. The joint knowledge base of project partners and the geographical distance between them were positively associated with technological diversity creation. In contrast, the number and diversity of actors and the degree of clustering showed a negative association with technological diversity creation. These results extend current micro-level explanations of how the diversity of an emerging technology is created. The contribution of this study could also be helpful for policy makers to influence the level of diversity in a technological field, and hence to contribute to survival of emerging technologies.

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“…More specific psychometric software packages, such as flexMIRT (Cai, ), are able to simulate data as well. Additionally, Rick Wicklin () has an entire book devoted to simulations in SAS; another text is devoted to R (Jones, Maillardet, & Robinson, ). Furthermore, resources have been written for specific approaches such as factor analysis (Tucker, Koopman, & Linn, ) and structural equation modeling (Bandalos, ; Muthén & Muthén, ), among others.…”

Section: Illustration Of Simulation Implementationmentioning

confidence: 99%

Conducting Simulation Studies in Psychometrics

Feinberg

Rubright

2016

Educational Measurement

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Simulation studies are fundamental to psychometric discourse and play a crucial role in operational and academic research. Yet, resources for psychometricians interested in conducting simulations are scarce. This Instructional Topics in Educational Measurement Series (ITEMS) module is meant to address this deficiency by providing a comprehensive introduction to the topic of simulation that can be easily understood by measurement specialists at all levels of training and experience. Specifically, this module describes the vocabulary used in simulations, reviews their applications in recent literature, and recommends specific guidelines for designing simulation studies and presenting results. Additionally, an example (including computer code in R) is given to demonstrate how common aspects of simulation studies can be implemented in practice and to provide a template to help users build their own simulation.

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Introduction to Scientific Programming and Simulation Using R

Cited by 43 publications

References 0 publications

Scanning electron microscopy image representativeness: morphological data on nanoparticles

Scanning electron microscopy image representativeness: morphological data on nanoparticles

Multi-disciplinarity breeds diversity: the influence of innovation project characteristics on diversity creation in nanotechnology

Conducting Simulation Studies in Psychometrics

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