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Many recent documents call for a renewed emphasis on computational estimation in the classroom. However, researchers are only now giving attention to how students learn computational estimation. The research described here focused on how children develop the ability to estimate computations. We begin with a brief description of the theory on which the research was based, describe the research study itself, and finally discuss the study's implications and extensions into the classroom.
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Lampert, Magdalene. "Research into Practice: Arithmetic as Problem Solving." Arithmetic Teacher 36, no. 7 (March 1989): 34–36. http://dx.doi.org/10.5951/at.36.7.0034.
Teachers often feel torn, especially in upper elementary school mathematics classes, between spending time on problem-solving work that will get students to understand mathematics and spending time on developing computational skills. The conflict is especially strong because the computational skills in the curriculum at this level are complex: “long” multiplication and division, relating fractions to decimals and percents, and operations on fractions. The procedures involved in doing these computations involve many steps, and students often have difficulty remembering what to do and in what order.
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DONG, ANDY. "Special Issue: Design computing and cognition." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 19, no. 4 (November 2005): 227–28. http://dx.doi.org/10.1017/s0890060405050158.
The field of research in design computing and cognition focuses on computational theories and systems that enact design. Design computing and cognition produces a unifying framework to model and explain design beyond the description of “design computing and cognition,” as in “design computing” and “design cognition” as two cognate disciplines. Research in design computing and cognition recognizes not only the essential relationship between human cognitive processes as models of computation but also how models of computation inspire conceptual realizations of human cognition in design. The articles in this Special Issue address the concomitant key areas of research in design computing and cognition: computational models of design, computational representations in design, computational design systems, and design cognition. The computationally inspired perspectives, metaphors, models, and theories that the papers deliver create a base for computing and cognition to (re)shape design practice and its role in design science and inquiry.
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Cases Martín, Ignacio, and Alfonso Lacadena García-Gallo. "A Computational Approach to Scribal Practice." Revista Española de Antropología Americana 49, Especial (July 5, 2019): 209–24. http://dx.doi.org/10.5209/reaa.64967.
The study of the construction of social meaning in ancient Maya communities of Mesoamerica poses a variety of methodological problems in historical sociolinguistics due to the reliance on written records by means of a writing system that exhibits variation itself. While variation in writing systems has been previously studied in terms of diachronic shifts and dialectal variation, systematic approaches still remain elusive. This paper explores new avenues for the computational extraction of sociolinguistic features, resulting in the automatic extraction of useful sociolinguistic information from written corpora using Machine Learning algorithms. We show that these features can help illuminating the contribution of pragmatic choices in the selection of graphemes to stylistic practices that are key in the construction of Mayan scribal communities of practice.
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Lee, Irene, Fred Martin, Jill Denner, Bob Coulter, Walter Allan, Jeri Erickson, Joyce Malyn-Smith, and Linda Werner. "Computational thinking for youth in practice." ACM Inroads 2, no. 1 (February 25, 2011): 32–37. http://dx.doi.org/10.1145/1929887.1929902.
Reddy, BL. "Computational Challenges in Statistical Outcome of Teaching Learning Practice: A Scientific Review." Journal of Advanced Research in Dynamical and Control Systems 12, SP7 (July 25, 2020): 2603–6. http://dx.doi.org/10.5373/jardcs/v12sp7/20202395.
L. M. Adleman launched the field of DNA computing with a demonstration in 1994 that strands of DNA could be used to solve the Hamiltonian path problem for a simple graph. He also identified three broad categories of open questions for the field. First, is DNA capable of universal computation? Second, what kinds of algorithms can DNA implement? Third, can the error rates in the manipulations of the DNA be controlled enough to allow for useful computation? In the two years that have followed, theoretical work has shown that DNA is in fact capable of universal computation. Furthermore, algorithms for solving interesting questions, like breaking the Data Encryption Standard, have been described using currently available technology and methods. Finally, a few algorithms have been proposed to handle some of the apparently crippling error rates in a few of the common processes used to manipulate DNA. It is thus unlikely that DNA computation is doomed to be only a passing curiosity. However, much work remains to be done on the containment and correction of errors. It is far from clear if the problems in the error rates can be solved sufficiently to ever allow for general-purpose computation that will challenge the more popular substrates for computation. Unfortunately, biological demonstrations of the theoretical results have been sadly lacking. To date, only the simplest of computations have been carried out in DNA. To make significant progress, the field will require both the assessment of the practicality of the different manipulations of DNA and the implementation of algorithms for realistic problems. Theoreticians, in collaboration with experimentalists, can contribute to this research program by settling on a small set of practical and efficient models for DNA computation.
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Duncan, David R., and Bonnie H. Litwiller. "Ideas." Arithmetic Teacher 33, no. 7 (March 1986): 26–32. http://dx.doi.org/10.5951/at.33.7.0026.
To maintain students' computational skills, practice is needed. Students find practice activities more in teresting if they are provided in new and novel situations. It's a bonus if students discover number patterns as a result of the computations.
Dissertations / Theses on the topic "Computational practice":
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Barbaresi, Mattia. "Computational mechanics: from theory to practice." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/15649/.
In the last fifty years, computational mechanics has gained the attention of a large number of disciplines, ranging from physics and mathematics to biology, involving all the disciplines that deal with complex systems or processes. With ϵ-machines, computational mechanics provides powerful models that can help characterizing these systems. To date, an increasing number of studies concern the use of such methodologies; nevertheless, an attempt to make this approach more accessible in practice is lacking yet. Starting from this point, this thesis aims at investigating a more practical approach to computational mechanics so as to make it suitable for applications in a wide spectrum of domains. ϵ-machines are analyzed more in the robotics scene, trying to understand if they can be exploited in contexts with typically complex dynamics like swarms. Experiments are conducted with random walk behavior and the aggregation task. Statistical complexity is first studied and tested on the logistical map and then exploited, as a more applicative case, in the analysis of electroencephalograms as a classification parameter, resulting in the discrimination between patients (with different sleep disorders) and healthy subjects.
The number of applications that may benefit from the use of such a technique is enormous. Hopefully, this work has broadened the prospect towards a more applicative interest.
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Kelly, David. "Computational mechanics in practice : mathematical adaptions and experimental applications." Thesis, University of Bristol, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.570852.
The definition and quantification of complexity is a source of debate. A promising answer, from Crutch field, Shalizi and co-workers, identifies complexity with the amount of information required to optimally predict the future of a process. Computational mechanics computes this quantity for discrete time series; quantifying the complexity and generating minimal, optimally predictive models. Here we adapt and apply these methods to two very different problems. First, we extend computational mechanics to continuous data which cluster around discrete values. This is applied to the analysis of single molecule experimental data; allowing us to infer hidden Markov models without the necessity of assuming model architecture and allowing for the inference of degenerate states, giving advantages over previous analysis methods. The new analysis methods are demonstrated to perform well on both simulated data, in high noise and sparse data conditions; and experimental data, namely fluorescence resonance energy transfer spectra of Holliday junction conformational dynamics. Secondly, we apply computational mechanics to investigations of the HP model of protein folding. Computational mechanics was used to investigate the properties of the sequence sets folding to the highly designable structures. A hypothesised correlation between structures' designability and the statistical complexity of its sequence set was unsupported. However, methods were developed to succinctly encapsulate the non-local statistical regularities of sequence sets and used to accurately predict the structure of designing and randomly generated sequences. Finally, limitations of the standard algorithm for reconstructing predictive models are addressed. The algorithm can fail due to pair-wise comparisons of conditional distributions. A clustering method, considering all distributions simultaneously has been developed. This also makes clear when the algorithm may be effectively employed. A second issue concerns a class of processes for which computational mechanics cannot infer the correct, optimally predictive models. Adaptions to allow the inference of these processes have been devised.
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Garg, Shilpa [Verfasser], and Tobias [Akademischer Betreuer] Marschall. "Computational haplotyping : theory and practice / Shilpa Garg ; Betreuer: Tobias Marschall." Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2018. http://d-nb.info/116249607X/34.
Joyce, Sam. "Performance driven design systems in practice." Thesis, University of Bath, 2016. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.687303.
This thesis is concerned with the application of computation in the context of professional architectural practice and specifically towards defining complex buildings that are highly integrated with respect to design and engineering performance. The thesis represents applied research undertaken whilst in practice at Foster + Partners. It reviews the current state of the art of computational design techniques to quickly but flexibly model and analyse building options. The application of parametric design tools to active design projects is discussed with respect to real examples as well as methods to then link the geometric definitions to structural engineering analysis, to provide performance data in near real time. The practical interoperability between design software and engineering tools is also examined. The role of performance data in design decision making is analysed by comparing manual work-flows with methods assisted by computation. This extends to optimisation methods which by making use of design automation actively make design decisions to return optimised results. The challenges and drawbacks of using these methods effectively in real deign situations is discussed, especially the limitations of these methods with respect to incomplete problem definitions, and the design exploration resulting in modified performance requirements. To counter these issues a performance driven design work flow is proposed. This is a mixed initiative whereby designer centric understanding and decisions are computer assisted. Flexible meta-design descriptions that encapsulate the variability of the design space under consideration are explored and compared with existing optimisation approaches. Computation is used to produce and visualise the performance data from these large design spaces generated by parametric design descriptions and associated engineering analysis. Novel methods are introduced that define a design and performance space using cluster computing methods to speed up the generation of large numbers of options. The use of data visualisation is applied to design problems, showing how in real situations it can aid design orientation and decision making using the large amount of data produced. Strategies to enable these work-flows are discussed and implemented, focusing on re-appropriating existing web design paradigms using a modular approach concentrating on scalable data creation and information display.
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Harding, John. "Meta-parametric design : developing a computational approach for early stage collaborative practice." Thesis, University of Bath, 2015. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.646138.
Computational design is the study of how programmable computers can be integrated into the process of design. It is not simply the use of pre-compiled computer aided design software that aims to replicate the drawing board, but rather the development of computer algorithms as an integral part of the design process. Programmable machines have begun to challenge traditional modes of thinking in architecture and engineering, placing further emphasis on process ahead of the final result. Just as Darwin and Wallace had to think beyond form and inquire into the development of biological organisms to understand evolution, so computational methods enable us to rethink how we approach the design process itself. The subject is broad and multidisciplinary, with influences from design, computer science, mathematics, biology and engineering. This thesis begins similarly wide in its scope, addressing both the technological aspects of computational design and its application on several case study projects in professional practice. By learning through participant observation in combination with secondary research, it is found that design teams can be most effective at the early stage of projects by engaging with the additional complexity this entails. At this concept stage, computational tools such as parametric models are found to have insufficient flexibility for wide design exploration. In response, an approach called Meta-Parametric Design is proposed, inspired by developments in genetic programming (GP). By moving to a higher level of abstraction as computational designers, a Meta-Parametric approach is able to adapt to changing constraints and requirements whilst maintaining an explicit record of process for collaborative working.
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Tsoukalas, Kyriakos. "On Affective States in Computational Cognitive Practice through Visual and Musical Modalities." Diss., Virginia Tech, 2021. http://hdl.handle.net/10919/104069.
Learners' affective states correlate with learning outcomes. A key aspect of instructional design is the choice of modalities by which learners interact with instructional content. The existing literature focuses on quantifying learning outcomes without quantifying learners' affective states during instructional activities. An investigation of how learners feel during instructional activities will inform the instructional systems design methodology of a method for quantifying the effects of individually available modalities on learners' affect.
The objective of this dissertation is to investigate the relationship between affective states and learning modalities of instructional computing. During an instructional activity, learners' enjoyment, excitement, and motivation are measured before and after a computing activity offered in three distinct modalities. The modalities concentrate on visual and musical computing for the practice of computational thinking. An affective model for the practice of computational thinking through musical expression was developed and validated.
This dissertation begins with a literature review of relevant theories on embodied cognition, learning, and affective states. It continues with designing and fabricating a prototype instructional apparatus and its virtual simulation as a web service, both for the practice of computational thinking through musical expression, and concludes with a study investigating participants' affective states before and after four distinct online computing activities.
This dissertation builds on and contributes to extant literature by validating an affective model for computational thinking practice through self-expression. It also proposes a nomological network for the construct of computational thinking for future exploration of the construct, and develops a method for the assessment of instructional activities based on predefined levels of skill and knowledge. Doctor of Philosophy This dissertation investigates the role of learners' affect during instructional activities of visual and musical computing. More specifically, learners' enjoyment, excitement, and motivation are measured before and after a computing activity offered in four distinct ways. The computing activities are based on a prototype instructional apparatus, which was designed and fabricated for the practice of computational thinking. A study was performed using a virtual simulation accessible via internet browser. The study suggests that maintaining enjoyment during instructional activities is a more direct path to academic motivation than excitement.
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Hudson, Roland. "Strategies for parametric design in architecture : an application of practice led research." Thesis, University of Bath, 2010. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.524059.
A new specialist design role is emerging in the construction industry. The primary task related to this role is focused on the control, development and sharing of geometric information with members of the design team in order to develop a design solution. Individuals engaged in this role can be described as a parametric designers. Parametric design involves the exploration of multiple solutions to architectural design problems using parametric models. In the past these models have been defined by computer programs, nowcommercially available parametric software provides a simpler means of creating these models. It is anticipated that the emergence of parametric designers will spread and a deeper understanding of the role is required. This thesis is aimed at establishing a detailed understanding of the tasks related to this new specialism and to develop a set of considerations that should be made when undertaking these tasks. The position of the parametric designer in architectural practice presents new opportunities in the design process this thesis also aims to capture these. Developments in this field of design are driven by practice. It is proposed that a generalised understanding of applied parametric design is primarily developed through the study of practical experience. Two bodies of work inform this study. First, a detailed analytical review of published work that focuses on the application of parametric technology and originatesfrompractice. This material concentrates on the documentation of case studies from a limited number of practices. Second, a series of case studies involving the author as participant and observer in the context of contemporary practice. This primary research of applied use of parametric tools is documented in detail and generalised findings are extracted. Analysis of the literature from practice and generalisations based on case studies is contrasted with a review of relevant design theory. Based on this, a series of strategies for the parametric designer are identified and discussed.
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Van, der Beek Nick. "From practice to theory : computational studies on fluorescence detection and laser therapy in dermatology." Thesis, University of Wales Trinity Saint David, 2017. http://repository.uwtsd.ac.uk/819/.
Computational studies on light‐tissue interactions in medical treatment and diagnosis have offered deeper insights in the processes underlying laser treatments and fluorescence measurements. I apply this approach in the study of fluorescence detection and of laser therapy. First, I investigate three methods of fluorescence detection and the reported contrast between healthy skin and malignant tissue. I varied the concentration of haemoglobin in the target, the concentration of melanin in the epidermis, the scattering of light in the skin, the depth at which the target is located in the skin, the width of the target, the thickness of the target, the concentration of photosensitizer in the target, and the concentration of photosensitizer in the skin. My findings confirm previous clinical studies in that the auto‐fluorescence corrected fluorescence detection method generally shows a higher contrast than the other methods. The results support earlier clinical studies and are in accordance with expert experience. Second, I study laser therapy for psoriasis. In a series of simulations, I analyse three types of pulsed dye laser systems and one IPL system. The investigated biological effects are heat shock proteins, hyperthermic tissue damage and vasoconstriction of the microvasculature. The changes in the skin concern blood volume, blood oxygenation and scattering in the epidermis. The calculations show that there are some notable differences in the effect changes in the composition of psoriatic tissue has on the efficacy of laser and IPL therapy. Still, Inter‐device variance was more prominent than intra‐geometry variance. My study adds to the understanding of fluorescence detection of keratinocyte skin cancers, as well as that of laser therapy for psoriasis. Additionally, it offers potential avenues for increasing the efficacy and efficiency of these therapies.
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Selby, Cynthia Collins. "How can the teaching of programming be used to enhance computational thinking skills?" Thesis, University of Southampton, 2014. https://eprints.soton.ac.uk/366256/.
The use of the term computational thinking, introduced in 2006 by Jeanette Wing, is having repercussions in the field of education. The term brings into sharp focus the concept of thinking about problems in a way that can lead to solutions that may be implemented in a computing device. Implementation of these solutions may involve the use of programming languages. This study explores ways in which programming can be employed as a tool to teach computational thinking and problem solving. Data is collected from teachers, academics, and professionals, purposively selected because of their knowledge of the topics of problem solving, computational thinking, or the teaching of programming. This data is analysed following a grounded theory approach. A Computational Thinking Taxonomy is developed. The relationships between cognitive processes, the pedagogy of programming, and the perceived levels of difficulty of computational thinking skills are illustrated by a model. Specifically, a definition for computational thinking is presented. The skills identified are mapped to Bloom’s Taxonomy: Cognitive Domain. This mapping concentrates computational skills at the application, analysis, synthesis, and evaluation levels. Analysis of the data indicates that the less difficult computational thinking skills for beginner programmers are generalisation, evaluation, and algorithm design. Abstraction of functionality is less difficult than abstraction of data, but both are perceived as difficult. The most difficult computational thinking skill is reported as decomposition. This ordering of difficulty for learners is a reversal of the cognitive complexity predicted by Bloom’s model. The plausibility of this inconsistency is explored. The taxonomy, model, and the other results of this study may be used by educators to focus learning onto the computational thinking skills acquired by the learners, while using programming as a tool. They may also be employed in the design of curriculum subjects, such as ICT, computing, or computer science.
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Bridge, Catherine. "Computational case-based redesign for people with ability impairment rethinking, reuse and redesign learning for home modification practice /." Connect to full text, 2005. http://hdl.handle.net/2123/707.
Thesis (Ph. D.)--University of Sydney, 2006. Title from title screen (viewed 30 May 2008). Submitted in fulfilment of the requirements for the degree of Doctor of Philosophy to the School of Architecture, Design Science and Planning, Faculty of Architecture. Degree awarded 2006; thesis submitted 2005. Includes bibliographical references. Also available in print form.
Ambos-Spies, Klaus, Benedikt Löwe, and Wolfgang Merkle, eds. Mathematical Theory and Computational Practice. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03073-4.
Reusch, Bernd, and Karl-Heinz Temme, eds. Computational Intelligence in Theory and Practice. Heidelberg: Physica-Verlag HD, 2001. http://dx.doi.org/10.1007/978-3-7908-1831-4.
Thu, Bui Lam, and Alam Sameer, eds. Multi-objective optimization in computational intelligence: Theory and practice. Hershey: Information Science Reference, 2008.
Favorskaya, Margarita N., Ilia S. Nikitin, and Natalia S. Severina, eds. Advances in Theory and Practice of Computational Mechanics. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8926-0.
Jain, Lakhmi C., Margarita N. Favorskaya, Ilia S. Nikitin, and Dmitry L. Reviznikov, eds. Advances in Theory and Practice of Computational Mechanics. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2600-8.
Book chapters on the topic "Computational practice":
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Forrest, A. R. "Computational Geometry in Practice." In Fundamental Algorithms for Computer Graphics, 707–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-84574-1_30.
Briganti, Giovanni. "Augmented Medicine: Changing Clinical Practice with Artificial Intelligence." In Computational Biology, 333–39. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69951-2_14.
Teixeira, Andreia Sofia, Francisco C. Santos, and Alexandre P. Francisco. "Spanning Edge Betweenness in Practice." In Studies in Computational Intelligence, 3–10. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30569-1_1.
Kitzler, Thomas M., and Nathan W. Levin. "Clinical Practice Guidelines in Nephrology." In Studies in Computational Intelligence, 1587–628. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-27558-6_18.
Moody, Rebecca, and Lasse Gerrits. "Values in Computational Models Revalued." In Policy Practice and Digital Science, 205–19. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-12784-2_10.
Kadijevich, Djordje M. "Cultivating Computational Thinking Through Data Practice." In IFIP Advances in Information and Communication Technology, 24–33. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23513-0_3.
Xie, Haiyan, Kelun Wang, and Xiaoju Huang. "Reform and Practice of Computational Intelligence." In Communications in Computer and Information Science, 243–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-27503-6_33.
Matijevics, István. "Wireless Sensors Networks – Theory and Practice." In Studies in Computational Intelligence, 405–17. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03737-5_29.
Conference papers on the topic "Computational practice":
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Blackwell, A. "Computational thinking and creative practice." In 2012 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC 2012). IEEE, 2012. http://dx.doi.org/10.1109/vlhcc.2012.6344467.
Yonezawa, Akinori, Tadashi Watanabe, Mitsuo Yokokawa, Mitsuhisa Sato, and Kimihiko Hirao. "Advanced Institute for Computational Science (AICS)." In State of the Practice Reports. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2063348.2063366.
Asif, Ali D., Hamza Malik, Chandra Orrill, Ramprasad Balasubramanian, and Shakhnoza Kayumova. "Computational Thinking: Teachers’ Practice of Abstraction." In 18th International Conference of the Learning Sciences (ICLS) 2024. International Society of the Learning Sciences, 2024. http://dx.doi.org/10.22318/icls2024.877800.
Zhang, Wei, and Zhong-cheng Fan. "Research and Practice on Computer Hardware Curriculums Practical Teaching." In 2nd International Conference on Teaching and Computational Science. Paris, France: Atlantis Press, 2014. http://dx.doi.org/10.2991/ictcs-14.2014.62.
Prabhu, Prakash, Yun Zhang, Soumyadeep Ghosh, David I. August, Jialu Huang, Stephen Beard, Hanjun Kim, et al. "A survey of the practice of computational science." In State of the Practice Reports. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2063348.2063374.
"Practice of computational intelligence techniques in engineering." In 2008 6th IEEE International Conference on Industrial Informatics. IEEE, 2008. http://dx.doi.org/10.1109/indin.2008.4618142.
Nguyen, John, and Brady Peters. "Computational Fluid Dynamics in Building Design Practice." In ACADIA 2020: Distributed Proximities. ACADIA, 2020. http://dx.doi.org/10.52842/conf.acadia.2020.1.574.
Loukanova, Roussanka. "Teaching Formal Methods for Computational Linguistics at Uppsala University." In Teaching Formal Methods: Practice and Experience. BCS Learning & Development, 2006. http://dx.doi.org/10.14236/ewic/tfm2006.11.
Albrant, Evgeniy Olegovich. "Techniques of fast solving computational problems in computer science." In IX International Research-to-practice conference. TSNS Interaktiv Plus, 2016. http://dx.doi.org/10.21661/r-114007.
Zhang, Hu, and Jia-heng Zheng. "An exploration on computational linguistics in teaching practice." In the 1st ACM Summit on Computing Education in China. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1517632.1517641.
Heymsfield, Ernie, and Jeb Tingle. State of the practice in pavement structural design/analysis codes relevant to airfield pavement design. Engineer Research and Development Center (U.S.), May 2021. http://dx.doi.org/10.21079/11681/40542.
An airfield pavement structure is designed to support aircraft live loads for a specified pavement design life. Computer codes are available to assist the engineer in designing an airfield pavement structure. Pavement structural design is generally a function of five criteria: the pavement structural configuration, materials, the applied loading, ambient conditions, and how pavement failure is defined. The two typical types of pavement structures, rigid and flexible, provide load support in fundamentally different ways and develop different stress distributions at the pavement – base interface. Airfield pavement structural design is unique due to the large concentrated dynamic loads that a pavement structure endures to support aircraft movements. Aircraft live loads that accompany aircraft movements are characterized in terms of the load magnitude, load area (tire-pavement contact surface), aircraft speed, movement frequency, landing gear configuration, and wheel coverage. The typical methods used for pavement structural design can be categorized into three approaches: empirical methods, analytical (closed-form) solutions, and numerical (finite element analysis) approaches. This article examines computational approaches used for airfield pavement structural design to summarize the state-of-the-practice and to identify opportunities for future advancements. United States and non-U.S. airfield pavement structural codes are reviewed in this article considering their computational methodology and intrinsic qualities.
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Liberman, Babe, and Viki Young. Equity in the Driver’s Seat: A Practice-Driven, Equity-Centered Approach for Setting R&D Agendas in Education. Digital Promise, July 2020. http://dx.doi.org/10.51388/20.500.12265/100.
Education research is too often based on gaps in published research or the niche interests of researchers, rather than the priority challenges faced by schools and districts. As a result, the education studies that researchers design and publish are often not applicable to schools’ most pressing needs. To spur future research to address the specific equity goals of schools and districts, Digital Promise set out to define and test a collaborative process for developing practice-driven, equity-centered R&D agendas. Our process centered on convening a range of education stakeholders to listen to and prioritize the equity-related challenges that on-the-ground staff are facing, while considering prominent gaps in existing research and solutions. We selected two challenge topics around which to pilot this approach and create sample agendas (adolescent literacy and computational thinking).
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Brindley, Kyle, Prabhu Khalsa, Thomas Roberts, Sergio Cordova, Matthew Fister, and Scott Ouellette. Engineering Computational Practices. Office of Scientific and Technical Information (OSTI), April 2023. http://dx.doi.org/10.2172/1970254.
de Kemp, E. A., H. A. J. Russell, B. Brodaric, D. B. Snyder, M. J. Hillier, M. St-Onge, C. Harrison, et al. Initiating transformative geoscience practice at the Geological Survey of Canada: Canada in 3D. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/331097.
Application of 3D technologies to the wide range of Geosciences knowledge domains is well underway. These have been operationalized in workflows of the hydrocarbon sector for a half-century, and now in mining for over two decades. In Geosciences, algorithms, structured workflows and data integration strategies can support compelling Earth models, however challenges remain to meet the standards of geological plausibility required for most geoscientific studies. There is also missing links in the institutional information infrastructure supporting operational multi-scale 3D data and model development. Canada in 3D (C3D) is a vision and road map for transforming the Geological Survey of Canada's (GSC) work practice by leveraging emerging 3D technologies. Primarily the transformation from 2D geological mapping, to a well-structured 3D modelling practice that is both data-driven and knowledge-driven. It is tempting to imagine that advanced 3D computational methods, coupled with Artificial Intelligence and Big Data tools will automate the bulk of this process. To effectively apply these methods there is a need, however, for data to be in a well-organized, classified, georeferenced (3D) format embedded with key information, such as spatial-temporal relations, and earth process knowledge. Another key challenge for C3D is the relative infancy of 3D geoscience technologies for geological inference and 3D modelling using sparse and heterogeneous regional geoscience information, while preserving the insights and expertise of geoscientists maintaining scientific integrity of digital products. In most geological surveys, there remains considerable educational and operational challenges to achieve this balance of digital automation and expert knowledge. Emerging from the last two decades of research are more efficient workflows, transitioning from cumbersome, explicit (manual) to reproducible implicit semi-automated methods. They are characterized by integrated and iterative, forward and reverse geophysical modelling, coupled with stratigraphic and structural approaches. The full impact of research and development with these 3D tools, geophysical-geological integration and simulation approaches is perhaps unpredictable, but the expectation is that they will produce predictive, instructive models of Canada's geology that will be used to educate, prioritize and influence sustainable policy for stewarding our natural resources. On the horizon are 3D geological modelling methods spanning the gulf between local and frontier or green-fields, as well as deep crustal characterization. These are key components of mineral systems understanding, integrated and coupled hydrological modelling and energy transition applications, e.g. carbon sequestration, in-situ hydrogen mining, and geothermal exploration. Presented are some case study examples at a range of scales from our efforts in C3D.
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de Kemp, E. A., H. A. J. Russell, B. Brodaric, D. B. Snyder, M. J. Hillier, M. St-Onge, C. Harrison, et al. Initiating transformative geoscience practice at the Geological Survey of Canada: Canada in 3D. Natural Resources Canada/CMSS/Information Management, 2023. http://dx.doi.org/10.4095/331871.
Application of 3D technologies to the wide range of Geosciences knowledge domains is well underway. These have been operationalized in workflows of the hydrocarbon sector for a half-century, and now in mining for over two decades. In Geosciences, algorithms, structured workflows and data integration strategies can support compelling Earth models, however challenges remain to meet the standards of geological plausibility required for most geoscientific studies. There is also missing links in the institutional information infrastructure supporting operational multi-scale 3D data and model development. Canada in 3D (C3D) is a vision and road map for transforming the Geological Survey of Canada's (GSC) work practice by leveraging emerging 3D technologies. Primarily the transformation from 2D geological mapping, to a well-structured 3D modelling practice that is both data-driven and knowledge-driven. It is tempting to imagine that advanced 3D computational methods, coupled with Artificial Intelligence and Big Data tools will automate the bulk of this process. To effectively apply these methods there is a need, however, for data to be in a well-organized, classified, georeferenced (3D) format embedded with key information, such as spatial-temporal relations, and earth process knowledge. Another key challenge for C3D is the relative infancy of 3D geoscience technologies for geological inference and 3D modelling using sparse and heterogeneous regional geoscience information, while preserving the insights and expertise of geoscientists maintaining scientific integrity of digital products. In most geological surveys, there remains considerable educational and operational challenges to achieve this balance of digital automation and expert knowledge. Emerging from the last two decades of research are more efficient workflows, transitioning from cumbersome, explicit (manual) to reproducible implicit semi-automated methods. They are characterized by integrated and iterative, forward and reverse geophysical modelling, coupled with stratigraphic and structural approaches. The full impact of research and development with these 3D tools, geophysical-geological integration and simulation approaches is perhaps unpredictable, but the expectation is that they will produce predictive, instructive models of Canada's geology that will be used to educate, prioritize and influence sustainable policy for stewarding our natural resources. On the horizon are 3D geological modelling methods spanning the gulf between local and frontier or green-fields, as well as deep crustal characterization. These are key components of mineral systems understanding, integrated and coupled hydrological modelling and energy transition applications, e.g. carbon sequestration, in-situ hydrogen mining, and geothermal exploration. Presented are some case study examples at a range of scales from our efforts in C3D.
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Striuk, Andrii M., and Serhiy O. Semerikov. The Dawn of Software Engineering Education. [б. в.], February 2020. http://dx.doi.org/10.31812/123456789/3671.
Designing a mobile-oriented environment for professional and practical training requires determining the stable (fundamental) and mobile (technological) components of its content and determining the appropriate model for specialist training. In order to determine the ratio of fundamental and technological in the content of software engineers’ training, a retrospective analysis of the first model of training software engineers developed in the early 1970s was carried out and its compliance with the current state of software engineering development as a field of knowledge and a new the standard of higher education in Ukraine, specialty 121 “Software Engineering”. It is determined that the consistency and scalability inherent in the historically first training program are largely consistent with the ideas of evolutionary software design. An analysis of its content also provided an opportunity to identify the links between the training for software engineers and training for computer science, computer engineering, cybersecurity, information systems and technologies. It has been established that the fundamental core of software engineers’ training should ensure that students achieve such leading learning outcomes: to know and put into practice the fundamental concepts, paradigms and basic principles of the functioning of language, instrumental and computational tools for software engineering; know and apply the appropriate mathematical concepts, domain methods, system and object-oriented analysis and mathematical modeling for software development; put into practice the software tools for domain analysis, design, testing, visualization, measurement and documentation of software. It is shown that the formation of the relevant competencies of future software engineers must be carried out in the training of all disciplines of professional and practical training.
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Vines, John, Kelly Kirk, Eric Mark, Carrie Spear, and Joel Martin. A Practical Application of the Computational Science Environment (CSE). Fort Belvoir, VA: Defense Technical Information Center, December 2011. http://dx.doi.org/10.21236/ada553972.
Ballard, Grey. Reducing Computation and Communication in Scientific Computing: Connecting Theory to Practice. Office of Scientific and Technical Information (OSTI), June 2016. http://dx.doi.org/10.2172/1618256.
Mills, Kelly, Merijke Coenraad, Pati Ruiz, Quinn Burke, and Josh Weisgrau. Computational Thinking for an Inclusive World: A Resource for Educators to Learn and Lead. Digital Promise, December 2021. http://dx.doi.org/10.51388/20.500.12265/138.
Technology is becoming more integral across professional fields and within our daily lives, especially since the onset of the pandemic. As such, opportunities to learn computational thinking are important to all students—not only the ones who will eventually study computer science or enter the information technology industry. However, large inequalities continue to exist in access to equipment and learning opportunities needed to build computational thinking skills for students that experience marginalization. We call all educators to integrate computational thinking into disciplinary learning across PreK-12 education, while centering inclusivity, to equip students with the skills they need to participate in our increasingly technological world and promote justice for students and society at large. This report issues two calls to action for educators to design inclusive computing learning opportunities for students: (1) integrate computational thinking into disciplinary learning, and (2) build capacity for computational thinking with shared leadership and professional learning. Inspired by the frameworks, strategies, and examples of inclusive computational thinking integration, readers can take away practical implications to reach learners in their contexts.
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Gamba, Mirko, and Venkat Raman. A Joint Experimental/Computational Study of Non-Idealities in Practical Rotating Detonation Engines. Office of Scientific and Technical Information (OSTI), September 2019. http://dx.doi.org/10.2172/1601159.
