Journal articles: 'Computational practice'

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Sowder, Judith. "Research into Practice: Developing Understanding of Computational Estimation." Arithmetic Teacher 36, no. 5 (January 1989): 25–27. http://dx.doi.org/10.5951/at.36.5.0025.

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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.

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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.

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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.

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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.

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Khatibi, Rahman. "Some Issues in Computational Hydraulics Practice." Journal of Hydraulic Engineering 127, no. 6 (June 2001): 438–42. http://dx.doi.org/10.1061/(asce)0733-9429(2001)127:6(438).

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Bruel, Jean-Michel, Benoit Combemale, Ileana Ober, and Hélène Raynal. "MDE in Practice for Computational Science." Procedia Computer Science 51 (2015): 660–69. http://dx.doi.org/10.1016/j.procs.2015.05.182.

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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.

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Maley, Carlo C. "DNA Computation: Theory, Practice, and Prospects." Evolutionary Computation 6, no. 3 (September 1998): 201–29. http://dx.doi.org/10.1162/evco.1998.6.3.201.

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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.

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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.

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Downes, Stephen. "Modeling scientific practice: Paul Thagard's computational approach." New Ideas in Psychology 11, no. 2 (July 1993): 229–43. http://dx.doi.org/10.1016/0732-118x(93)90036-d.

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Demchuk, Eugene, Patricia Ruiz, Jewell D. Wilson, Franco Scinicariello, Hana R. Pohl, Mike Fay, Moiz M. Mumtaz, Hugh Hansen, and Christopher T. De Rosa. "Computational Toxicology Methods in Public Health Practice." Toxicology Mechanisms and Methods 18, no. 2-3 (January 2008): 119–35. http://dx.doi.org/10.1080/15376510701857148.

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Yuan, Zheng, and Jacob Fish. "Toward realization of computational homogenization in practice." International Journal for Numerical Methods in Engineering 73, no. 3 (2007): 361–80. http://dx.doi.org/10.1002/nme.2074.

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Hastings, William R. "Sharing Teaching Ideas: Practical Practice." Mathematics Teacher 82, no. 9 (December 1989): 702–4. http://dx.doi.org/10.5951/mt.82.9.0702.

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Unimaginative and repetitive drills of elementary number facts can be boring to both students and teachers. Yet computational facility is very important and must be developed and strengthened. The following exercise helps students practice computational skills, discover patterns, and check their own answers.

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Cheatle, Amy, and Steven Jackson. "(Re)collecting Craft: Reviving Materials, Techniques, and Pedagogies of Craft for Computational Makers." Proceedings of the ACM on Human-Computer Interaction 7, CSCW2 (September 28, 2023): 1–23. http://dx.doi.org/10.1145/3610041.

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This paper examines craft's foundational relations to materials, techniques, and collaborative modes of teaching and learning, and these can be called upon to strengthen and extend computational craft as practiced in fields like CSCW and HCI. Drawing from literature in HCI, craft studies and Science and Technology Studies (STS), we explore craft's modern formation at the dawn of the Industrial Revolution across three formative sites: Scandinavian Slöyd, British Arts and Crafts, and Japanese Mingei. From this review we identify three key (and still evolving) features: craft's accountabilities to natural materials and local ecologies; craft's holistic ways of making with 'head, heart, and hand'; and craft's distinctly collaborative and embodied styles of teaching and learning. We then show how these lessons can be applied to contemporary practices and pedagogies of computational making. We argue that doing so can help to rebalance computation's ecological ties and relations, recenter its practice on a sensorially rich and 'whole-self' concept of making, and support more collaborative modes of teaching and learning that are inclusive, relational, and heterogeneous.

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Atherton, Timothy J. "Resource Letter CP-3: Computational physics." American Journal of Physics 91, no. 1 (January 2023): 7–27. http://dx.doi.org/10.1119/5.0106476.

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This Resource Letter provides information and guidance for those looking to incorporate computation into their courses or to refine their own computational practice. We begin with general resources, including policy documents and supportive organizations. We then survey efforts to integrate computation across the curriculum as well as provide information for instructors looking to teach a computational physics course specifically. An overview of education research into computation in physics, including materials from beyond Physics Education Research, is then provided, followed by suggestions for tools, languages, and environments. We conclude with some emerging topics for which only preliminary resources exist but represent important topics for future innovation.

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José Raimundo, Anderson, and Claudinea Angélica dos Santos. "COMPUTATIONAL THINKING." Journal of Interdisciplinary Debates 4, no. 01 (March 31, 2023): 47–69. http://dx.doi.org/10.51249/jid.v4i01.1253.

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Technology is present in the world so that its use becomes intuitive. The purpose of the study originated from the perception of people, especially young people who use technology practically all the time, but many of them do not use it to develop. In this case, the need to implement computing teaching in schools increases. The introduction of computing concepts from the early years of basic education gains a lot of importance. Computational thinking instructs people how to think about solving problems through concepts in the field of informatics. The unplugged activity presents great computing concepts, even without the need to use electronic devices, being an effective alternative in teaching. The method used is based on bibliographical reading on the subject and use of resources such as data show, cardboard, markers, cardboard, paper, glue, bond sheets and notebook. The general objective is to present the computer language and its importance by experiencing it in practice through the suggested games. As specific objectives, instigate students to learn by playing, increase interest in subjects such as mathematics, physical education, science, art and the Portuguese language, practice the programming language in known games in an interactive and unplugged way. As expected results are to contribute to computational thinking to become present and worked in schools in order to reframe the school teaching and learning process.

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Park, Buhm Soon. "Between Accuracy and Manageability: Computational Imperatives in Quantum Chemistry." Historical Studies in the Natural Sciences 39, no. 1 (2009): 32–62. http://dx.doi.org/10.1525/hsns.2009.39.1.32.

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This article explores the place of computation in the history of quantum theory by examining the development of several approximation methods to solve the Schröödinger equation without using empirical information, as these were worked out in the years from 1927 to 1933. These ab initio methods, as they became known, produced the results that helped validate the use of quantum mechanics in many-body atomic and molecular systems, but carrying out the computations became increasingly laborious and difficult as better agreement between theory and experiment was pursued and more complex systems were tackled. I argue that computational work in the early years of quantum chemistry shows an emerging practice of theory that required human labor, technological improvement (computers), and mathematical ingenuity.

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Denning, Peter J., and Matti Tedre. "Computational thinking for professionals." Communications of the ACM 64, no. 12 (December 2021): 30–33. http://dx.doi.org/10.1145/3491268.

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Thomas, Dave. "Computational Diversity, Practice and a Passion for Applications." Journal of Object Technology 2, no. 3 (2003): 7. http://dx.doi.org/10.5381/jot.2003.2.3.c1.

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Katherine Hayles, N. "Revealing and Transforming: How literature revalues computational practice." Performance Research 11, no. 4 (December 2006): 5–16. http://dx.doi.org/10.1080/13528160701363192.

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de Vries, Alex H., Piet Th van Duijnen, Rob W. J. Zijlstra, and Marcel Swart. "Thole's interacting polarizability model in computational chemistry practice." Journal of Electron Spectroscopy and Related Phenomena 86, no. 1-3 (August 1997): 49–55. http://dx.doi.org/10.1016/s0368-2048(97)00048-0.

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Critchley, Frank, and Paul Marriott. "Computational Information Geometry in Statistics: Theory and Practice." Entropy 16, no. 5 (May 2, 2014): 2454–71. http://dx.doi.org/10.3390/e16052454.

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B Odden, Tor Ole, and Anders Malthe-Sørenssen. "Using computational essays to scaffold professional physics practice." European Journal of Physics 42, no. 1 (November 12, 2020): 015701. http://dx.doi.org/10.1088/1361-6404/abb8b7.

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Needleman, A. "Computational Mechanics." Applied Mechanics Reviews 38, no. 10 (October 1, 1985): 1282–83. http://dx.doi.org/10.1115/1.3143692.

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Computational methods play a key role in solid mechanics, as a way of modelling fundamental aspects of mechanical behavior, as a vehicle for transferring this improved modelling capability into new engineering tools, and as a means of utilizing these tools in engineering practice. Modern computational methods enable realistic models of mechanical systems to be formulated without regard as to whether or not analytical solutions are feasible. Increased computational capability is also an incentive for developing more accurate theories, since it becomes possible to use such theories to solve complex engineering problems.

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Haas, Alison, Scott E. Grapin, Daniel Wendel, Lorena Llosa, and Okhee Lee. "How Fifth-Grade English Learners Engage in Systems Thinking Using Computational Models." Systems 8, no. 4 (November 22, 2020): 47. http://dx.doi.org/10.3390/systems8040047.

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The purpose of this study was to investigate how computational modeling promotes systems thinking for English Learners (ELs) in fifth-grade science instruction. Individual student interviews were conducted with nine ELs about computational models of landfill bottle systems they had developed as part of a physical science unit. We found evidence of student engagement in four systems thinking practices. Students used data produced by their models to investigate the landfill bottle system as a whole (Practice 1). Students identified agents and their relationships in the system (Practice 2). Students thought in levels, shuttling between the agent and aggregate levels (Practice 3). However, while students could think in levels to develop their models, they struggled to engage in this practice when presented with novel scenarios (e.g., open vs. closed system). Finally, students communicated information about the system using multiple modalities and less-than-perfect English (Practice 4). Overall, these findings suggest that integrating computational modeling into standards-aligned science instruction can provide a rich context for fostering systems thinking among linguistically diverse elementary students.

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Sun, Jiameng, Binrui Zhu, Jing Qin, Jiankun Hu, and Jixin Ma. "Confidentiality-Preserving Publicly Verifiable Computation Schemes for Polynomial Evaluation and Matrix-Vector Multiplication." Security and Communication Networks 2018 (June 21, 2018): 1–15. http://dx.doi.org/10.1155/2018/5275132.

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With the development of cloud services, outsourcing computation tasks to a commercial cloud server has drawn attention of various communities, especially in the Big Data era. Public verifiability offers a flexible functionality in real circumstance where the cloud service provider (CSP) may be untrusted or some malicious users may slander the CSP on purpose. However, sometimes the computational result is sensitive and is supposed to remain undisclosed in the public verification phase, while existing works on publicly verifiable computation (PVC) fail to achieve this requirement. In this paper, we highlight the property of result confidentiality in publicly verifiable computation and present confidentiality-preserving public verifiable computation (CP-PVC) schemes for multivariate polynomial evaluation and matrix-vector multiplication, respectively. The proposed schemes work efficiently under the amortized model and, compared with previous PVC schemes for these computations, achieve confidentiality of computational results, while maintaining the property of public verifiability. The proposed schemes proved to be secure, efficient, and result-confidential. In addition, we provide the algorithms and experimental simulation to show the performance of the proposed schemes, which indicates that our proposal is also acceptable in practice.

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Thomas, Will R., Benjamin Galewsky, Sandeep Puthanveetil Satheesan, Gregory Jansen, Richard Marciano, Shannon Bradley, Jong Lee, Luigi Marini, and Kenton McHenry. "Petabytes in Practice: Working with Collections as Data at Scale." Data and Information Management 3, no. 1 (March 19, 2019): 18–25. http://dx.doi.org/10.2478/dim-2019-0004.

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AbstractThe emerging transdiscipline of Computational Archival Science (CAS) links frameworks such as Brown Dog and repository software such as Digital Repository At Scale To Invite Computation (DRAS-TIC) to yield an understanding of working with digital collections at scale for cultural data. The DRAS-TIC and Brown Dog projects here serve as the basis for an expandable distributed storage/service architecture with on-demand, horizontally scalable integrated digital preservation and analysis services.

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Bovermann, Till, and Dave Griffiths. "Computation as Material in Live Coding." Computer Music Journal 38, no. 1 (March 2014): 40–53. http://dx.doi.org/10.1162/comj_a_00228.

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What does computation sound like, and how can computational processing be integrated into live-coding practice along with code? This article gives insights into three years of artistic research and performance practice with Betablocker, an imaginary central processing unit architecture, specifically designed and implemented for live-coding purposes. It covers the themes of algorithmic composition, sound generation, genetic programming, and autonomous coding in the light of self-manipulating code and artistic research practice.

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Lambert, Rachel, Kara Imm, and Dina A. Williams. "Number Strings: Daily Computational Fluency." Teaching Children Mathematics 24, no. 1 (September 2017): 48–55. http://dx.doi.org/10.5951/teacchilmath.24.1.0048.

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Chen, Kian Wee, Patrick Janssen, Dorit Aviv, Yazid Ninsalam, and Forrest Meggers. "A framework for considering the use of computational design technologies in the built environment design process." Journal of Information Technology in Construction 27 (November 22, 2022): 1010–27. http://dx.doi.org/10.36680/j.itcon.2022.049.

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This research proposes a Computation in Design (C-in-D) framework for design practices to consider the adoption of computational technologies in their design process. Examples of computational design technologies include but are not limited to computational algorithms, the Internet of Things (IoT), reality capture and digital fabrications. We develop the framework by categorizing design projects based on their physical scales, defining the work stages in a design project, and decomposing the design process into tasks and data flows. The computational design technologies can then be assessed by mapping its usage onto these data flows. The framework provides a basic structure for practices to customize and systematically assess the impacts of using computational design technologies in their design process. We demonstrate the C-in-D framework in three case studies, a sculpture design, an interior retrofit, and a form-based code development. The demonstration shows that web-based interactive parametric modeling and reality capture technologies can improve collaboration between the artist and modeler in the sculpture design project. IoT and optimization algorithms can improve the daylighting performance of the interior retrofit, and the use of Geographic Information System and reality capture technology can improve site analysis and visioning of the form-based code development process. The framework is a valuable tool for facilitating the adoption of new design technologies in practice.

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Heath, Anna, Natalia Kunst, Christopher Jackson, Mark Strong, Fernando Alarid-Escudero, Jeremy D. Goldhaber-Fiebert, Gianluca Baio, Nicolas A. Menzies, and Hawre Jalal. "Calculating the Expected Value of Sample Information in Practice: Considerations from 3 Case Studies." Medical Decision Making 40, no. 3 (April 2020): 314–26. http://dx.doi.org/10.1177/0272989x20912402.

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Background. Investing efficiently in future research to improve policy decisions is an important goal. Expected value of sample information (EVSI) can be used to select the specific design and sample size of a proposed study by assessing the benefit of a range of different studies. Estimating EVSI with the standard nested Monte Carlo algorithm has a notoriously high computational burden, especially when using a complex decision model or when optimizing over study sample sizes and designs. Recently, several more efficient EVSI approximation methods have been developed. However, these approximation methods have not been compared, and therefore their comparative performance across different examples has not been explored. Methods. We compared 4 EVSI methods using 3 previously published health economic models. The examples were chosen to represent a range of real-world contexts, including situations with multiple study outcomes, missing data, and data from an observational rather than a randomized study. The computational speed and accuracy of each method were compared. Results. In each example, the approximation methods took minutes or hours to achieve reasonably accurate EVSI estimates, whereas the traditional Monte Carlo method took weeks. Specific methods are particularly suited to problems where we wish to compare multiple proposed sample sizes, when the proposed sample size is large, or when the health economic model is computationally expensive. Conclusions. As all the evaluated methods gave estimates similar to those given by traditional Monte Carlo, we suggest that EVSI can now be efficiently computed with confidence in realistic examples. No systematically superior EVSI computation method exists as the properties of the different methods depend on the underlying health economic model, data generation process, and user expertise.

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Smeulders, Bart, Laurens Cherchye, and Bram De Rock. "Nonparametric Analysis of Random Utility Models: Computational Tools for Statistical Testing." Econometrica 89, no. 1 (2021): 437–55. http://dx.doi.org/10.3982/ecta17605.

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Kitamura and Stoye (2018) recently proposed a nonparametric statistical test for random utility models of consumer behavior. The test is formulated in terms of linear inequality constraints and a quadratic objective function. While the nonparametric test is conceptually appealing, its practical implementation is computationally challenging. In this paper, we develop a column generation approach to operationalize the test. These novel computational tools generate considerable computational gains in practice, which substantially increases the empirical usefulness of Kitamura and Stoye's statistical test.

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Zhan, Tao, Zhi Gang Liao, and Li Gao. "Research of from Theory to Practice about Computational Thinking." Advanced Materials Research 1044-1045 (October 2014): 1266–69. http://dx.doi.org/10.4028/www.scientific.net/amr.1044-1045.1266.

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Computer Thinking is the core content of Computer Basic knowledge. With the full implementation of quality education in order to cultivate the innovative spirit and practical ability, computer thinking knowledge and skills are necessary for current college students. Aimed at the, the paper puts forward Visualization teaching methods and use typical cases in teaching experience of College Computer Foundation, which will help students have access to professional knowledge and skills about computer science.

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Crum, Justin, Cyrus Cheng, David A. Ham, Lawrence Mitchell, Robert C. Kirby, Joshua A. Levine, and Andrew Gillette. "Bringing Trimmed Serendipity Methods to Computational Practice in Firedrake." ACM Transactions on Mathematical Software 48, no. 1 (March 31, 2022): 1–19. http://dx.doi.org/10.1145/3490485.

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We present an implementation of the trimmed serendipity finite element family, using the open-source finite element package Firedrake. The new elements can be used seamlessly within the software suite for problems requiring H 1 , H (curl), or H (div)-conforming elements on meshes of squares or cubes. To test how well trimmed serendipity elements perform in comparison to traditional tensor product elements, we perform a sequence of numerical experiments including the primal Poisson, mixed Poisson, and Maxwell cavity eigenvalue problems. Overall, we find that the trimmed serendipity elements converge, as expected, at the same rate as the respective tensor product elements, while being able to offer significant savings in the time or memory required to solve certain problems.

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Spencer, Matt. "Image and Practice: Visualization in Computational Fluid Dynamics Research." Interdisciplinary Science Reviews 37, no. 1 (March 2012): 86–100. http://dx.doi.org/10.1179/0308018812z.0000000006.

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Cui, Juan, and Jiang Shu. "Circulating microRNA trafficking and regulation: computational principles and practice." Briefings in Bioinformatics 21, no. 4 (August 28, 2019): 1313–26. http://dx.doi.org/10.1093/bib/bbz079.

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Abstract Rapid advances in genomics discovery tools and a growing realization of microRNA’s implication in intercellular communication have led to a proliferation of studies of circulating microRNA sorting and regulation across cells and different species. Although sometimes, reaching controversial scientific discoveries and conclusions, these studies have yielded new insights in the functional roles of circulating microRNA and a plethora of analytical methods and tools. Here, we consider this body of work in light of key computational principles underpinning discovery of circulating microRNAs in terms of their sorting and targeting, with the goal of providing practical guidance for applications that is focused on the design and analysis of circulating microRNAs and their context-dependent regulation. We survey a broad range of informatics methods and tools that are available to the researcher, discuss their key features, applications and various unsolved problems and close this review with prospects and broader implication of this field.

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Liu, Xin-Qiao, Xin-Yu Ji, Xing Weng, and Yi-Fan Zhang. "Artificial intelligence ecosystem for computational psychiatry: Ideas to practice." World Journal of Meta-Analysis 11, no. 4 (April 18, 2023): 79–91. http://dx.doi.org/10.13105/wjma.v11.i4.79.

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Russell, Susan Jo. "Principles and Standards: Developing Computational Fluency with Whole Numbers." Teaching Children Mathematics 7, no. 3 (November 2000): 154–58. http://dx.doi.org/10.5951/tcm.7.3.0154.

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Principles and Standards for School Mathematics (NCTM 2000) emphasizes the goal of computational fluency for all students. It articulates expectations regarding fluency with basic number combinations and the importance of computational facility grounded in understanding (see a summary of key messages regarding computation in Principles and Standards in the sidebar on page 156). Building on the Curriculum and Evaluation Standards for School Mathematics (NCTM 1989) and benefiting from a decade of research and practice, Principles and Standards articulates the need for students to develop procedural competence within a school mathematics program that emphasizes mathematical reasoning and problem solving. In fact, learning about whole-number computation is a key context for learning to reason about the baseten number system and the operations of addition, subtraction, multiplication, and division.

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Sun, Jiameng, Binrui Zhu, Jing Qin, Jiankun Hu, and Qianhong Wu. "Confidentiality-Preserving Publicly Verifiable Computation." International Journal of Foundations of Computer Science 28, no. 06 (September 2017): 799–818. http://dx.doi.org/10.1142/s0129054117400196.

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Cloud computing enables users to outsource complicated computational tasks to a commercial computing server and relieves the users from establishing and maintaining expensive local computation systems. In this scenario, the minimum security requirement is that the result returned by the server must be correct. Publicly verifiable computation (PVC) has been proposed to address this issue by allowing the computational result to be publicly verifiable. Observing that computational tasks are usually private business in practice, we propose a confidentiality-preserving security tool referred to as confidentiality-preserving publicly verifiable computation (CP-PVC), to efficiently address the scenario where a client would like to outsource a computational task to a cloud server but does not possess the input value locally. The CP-PVC allows the client to delegate the outsourcing computational task to anyone authorized and keeps the computational result confidential to anyone except the client, while not sacrificing the property of public verifiability. We propose a CP-PVC construction based on any one-key secure attribute-based encryption (ABE). Our construction is general as known ABE schemes are all one-key secure. Analysis shows that our CP-PVC scheme achieves computational result privacy without any significant extra cost and is almost as efficient as the up-to-date PVC schemes. These features render our CP-PVC as a practical and widely applicable tool to secure cloud computing.

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Boren, Braxton B. "Computational acoustic musicology." Digital Scholarship in the Humanities 34, no. 4 (December 24, 2018): 707–15. http://dx.doi.org/10.1093/llc/fqy073.

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Abstract While the challenge of historical reconstruction of past musical performances is not a fully solved problem, not all the elements are equally unknown, or of equal magnitude. Despite some uncertainty about the interpretation of individual performers on specific dates, scholarship can still inform other factors of greater perceptual importance, leading to a good approximation of historical performances. In addition to performance style and period instruments, computer simulations make it possible to also account for the acoustics of the period performance space. In addition, the most accurate reconstruction should simulate the room’s acoustics in real time for the performers, thus retaining the feedback mechanisms of room response on performance practice.

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Guidara, Marissa. "Rethinking Computational Thinking for Public Libraries' Youth Programs: Challenges and Recommendations." Pennsylvania Libraries: Research & Practice 6, no. 2 (November 26, 2018): 75–85. http://dx.doi.org/10.5195/palrap.2018.188.

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Computational thinking has become a popular and important concept in education throughout the nation. Public libraries, with their technology services and their role as an informal learning space, have been tagged as an ideal place for computational thinking learning for children. However, the literature and research surrounding computational thinking is often vague and even misleading, presenting differing visions of what computational thinking is, what it should look like in practice, and how it might be evaluated for effectiveness. As a result, youth services librarians face many challenges in their attempts to understand, design, and evaluate computational thinking programs for their libraries. This paper explores the issues inherent in current computational thinking research and discusses the challenges they represent in designing and facilitating youth computational thinking programs in public libraries, as well as presents recommendations for best practices.

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Cortés, J. C., J. V. Romero, M. D. Roselló, Francisco-J. Santonja, and Rafael-J. Villanueva. "Solving Continuous Models with Dependent Uncertainty: A Computational Approach." Abstract and Applied Analysis 2013 (2013): 1–10. http://dx.doi.org/10.1155/2013/983839.

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This paper presents a computational study on a quasi-Galerkin projection-based method to deal with a class of systems of random ordinary differential equations (r.o.d.e.’s) which is assumed to depend on a finite number of random variables (r.v.’s). This class of systems of r.o.d.e.’s appears in different areas, particularly in epidemiology modelling. In contrast with the other available Galerkin-based techniques, such as the generalized Polynomial Chaos, the proposed method expands the solution directly in terms of the random inputs rather than auxiliary r.v.’s. Theoretically, Galerkin projection-based methods take advantage of orthogonality with the aim of simplifying the involved computations when solving r.o.d.e.’s, which means to compute both the solution and its main statistical functions such as the expectation and the standard deviation. This approach requires the previous determination of an orthonormal basis which, in practice, could become computationally burden and, as a consequence, could ruin the method. Motivated by this fact, we present a technique to deal with r.o.d.e.’s that avoids constructing an orthogonal basis and keeps computationally competitive even assuming statistical dependence among the random input parameters. Through a wide range of examples, including a classical epidemiologic model, we show the ability of the method to solve r.o.d.e.’s.

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Simone, Pernice, Follia Laura, Balbo Gianfranco, Milanesi Luciano, Sartini Giulia, Totis Niccoló, Lió Pietro, Merelli Ivan, Cordero Francesca, and Beccuti Marco. "Integrating Petri Nets and Flux Balance Methods in Computational Biology Models: a Methodological and Computational Practice." Fundamenta Informaticae 171, no. 1-4 (October 23, 2019): 367–92. http://dx.doi.org/10.3233/fi-2020-1888.

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FRAGIADAKIS, MICHALIS, and MANOLIS PAPADRAKAKIS. "MODELING, ANALYSIS AND RELIABILITY OF SEISMICALLY EXCITED STRUCTURES: COMPUTATIONAL ISSUES." International Journal of Computational Methods 05, no. 04 (December 2008): 483–511. http://dx.doi.org/10.1142/s0219876208001674.

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A critical review of the current state of the art of the computing practices adopted by the earthquake engineering community is presented. Advanced computational tools are necessary for estimating the demand on seismically excited structures. Such computational methodologies can provide valuable information on a number of engineering parameters which have been proven essential for earthquake the engineering practice. The discussion extends from the finite element modeling of earthquake-resistant structures and the analysis procedures currently used to future developments considering the calculation of uncertainty and methodologies which rely on sophisticated computational methods. The objective is to provide a common ground of collaboration between the earthquake engineering and computational mechanics communities in an effort to mitigate future earthquake losses.

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Rodríguez-Cerdeira, Carmen, José Luís González-Cespón, and Roberto Arenas. "Current Status of Computational Intelligence Applications in Dermatological Clinical Practice." Open Dermatology Journal 14, no. 1 (April 21, 2020): 6–13. http://dx.doi.org/10.2174/1874372202014010006.

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Background: The yeast infections are increasingly frequent and the correct diagnosis consists of the identification of the yeast fungus, which in our case we are going to refer to the different species of Candida. The prescription of a broad-spectrum antifungal without taking into account the etiological agent, leads to an increase in the resistance to these treatments. Objective: The objective of this work is to differentiate Candida albicans from other Candida species (Candida spp.) By means of digital images obtained from the optical microscope. Material and Methods: It has reviewed about 100 photographs from patients in our consultations. In this study we will use the microscopic images of the Candida variety to be processed later with the Octave programming language and its image processing package (image-2.8.0). Results and Discussion: This system is able to differentiate Candida albicans from the other varieties of Candida such as C. parapsilosis, C. krusei, and C. kefyr with accuracy. The candida identifier application, which was designed and programmed in Octave, allows identification of candida species by locating certain geometric descriptors, such as the centroid and the surfaces of circular objects within the images. The program was highly effective for the diagnosis of Candida spp. So, we got a sensitivity and specificity above 90% with the images used. Conclusion: The results that we obtain from the Candida spp. identifier system that opens the way to be able to work with images obtained from the optical microscope.

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Jordanous, Anna. "Four PPPPerspectives on computational creativity in theory and in practice." Connection Science 28, no. 2 (March 9, 2016): 194–216. http://dx.doi.org/10.1080/09540091.2016.1151860.

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Dias, W. P. S. "Philosophical grounding and computational formalization for practice based engineering knowledge." Knowledge-Based Systems 20, no. 4 (May 2007): 382–87. http://dx.doi.org/10.1016/j.knosys.2006.06.002.

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Ahn, Woo-Young, and Jerome R. Busemeyer. "Challenges and promises for translating computational tools into clinical practice." Current Opinion in Behavioral Sciences 11 (October 2016): 1–7. http://dx.doi.org/10.1016/j.cobeha.2016.02.001.

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Chakraborty, Supratik, Kuldeep S. Meel, and Moshe Y. Vardi. "On the Hardness of Probabilistic Inference Relaxations." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 7785–92. http://dx.doi.org/10.1609/aaai.v33i01.33017785.

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A promising approach to probabilistic inference that has attracted recent attention exploits its reduction to a set of model counting queries. Since probabilistic inference and model counting are #P-hard, various relaxations are used in practice, with the hope that these relaxations allow efficient computation while also providing rigorous approximation guarantees. In this paper, we show that contrary to common belief, several relaxations used for model counting and its applications (including probablistic inference) do not really lead to computational efficiency in a complexity theoretic sense. Our arguments proceed by showing the corresponding relaxed notions of counting to be computationally hard. We argue that approximate counting with multiplicative tolerance and probabilistic guarantees of correctness is the only class of relaxations that provably simplifies the problem, given access to an NP-oracle. Finally, we show that for applications that compare probability estimates with a threshold, a new notion of relaxation with gaps between low and high thresholds can be used. This new relaxation allows efficient decision making in practice, given access to an NP-oracle, while also bounding the approximation error.

Journal articles on the topic 'Computational practice'

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