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Realistic-science, technology, engineering, and mathematics assisted by google classroom as a learning innovation in the new normal era to improve statistical thinking skill 7

Realistic-science, technology, engineering, and mathematics ...

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7th International Conference on mathematics, Science, and Education 2020, ICMSE 2020

作者： Ardiansyah, A.S. Novita, N.A. Zhintya, H. Kurnianto, D. Mathematics Education Study Program Universitas Negeri Semarang Indonesia Applied Statistics and Computation Study Program Universitas Negeri Semarang Indonesia

Based on government policies regarding the implementation of learning from home, it is necessary the learning innovation to continue learning in the new normal era by utilizing existing technological advances. In this digital era, statistics thinking is important because it is needed to be able to interpret and understand and make good decisions from the statistical data obtained. From these problems, one of the innovations that can be done is by implementing Realistic mathematics Education integrated Science, Technology, Engineering, and mathematics assisted by Google Classroom (R-STEM-GC). This paper aims to determine the effect of R-STEM-GC learning on students' statistical thinking skills. This paper uses literature review method research that identifies, assesses, and interprets all findings on a research topic to answer existing research questions. It can concluded that realistic learning was more effective in terms of students' mathematical reasoning and communication than conventional learning;learning with the application of STEM can improve students' problem solving abilities compared to conventional learning;and the use of google classrooms that can improve communication skills. From the results of this analysis, the application of R-STEM-GC learning can be an innovative solution in improving students' statistical thinking skills in new normal era. © Published under licence by IOP Publishing Ltd.

关键词： Students

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Fuzzy-Valued Distance Between Fuzzy Numbers Based on a Generalized Extension Principle 19th

Fuzzy-Valued Distance Between Fuzzy Numbers Based on a Gen...

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19th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2022

作者： Araújo, Juscelino Bedregal, Benjamin Santiago, Regivan Postgraduate Program in Systems and Computation Federal University of Rio Grande do Norte Natal59072-970 Brazil Department of Informatics and Applied Mathematics Federal University of Rio Grande do Norte Natal59072-970 Brazil

ISBN: (纸本)9783031089701

This paper presents a generalization of the extension principle for fuzzy numbers. The minimum is substituted by a general binary aggregation function. It is used to extend the usual metric for real numbers to fuzzy numbers, generating a new family of fuzzy-valued distances between fuzzy numbers. Then, some conditions on these aggregation functions are studied to hold the fuzzy number properties of the generated distances. © 2022, Springer Nature Switzerland AG.

关键词： Fuzzy rules

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An Assessment of the Supremizer and Aggregation Methods of Stabilization for Reduced-Order Models

arXiv

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arXiv 2023年

作者： Davie, Kayla D. Elman, Howard C. Applied Mathematics & Statistics Scientific Computation Program University of Maryland College ParkMD20742 United States Department of Computer Science Institute for Advanced Computer Studies University of Maryland College ParkMD20742 United States

MSC Codes 65N22, 65K10, 65F45We explore the features of two methods of stabilization, aggregation and supremizer methods, for reduced-order modeling of parametrized optimal control problems. In both methods, the reduced basis spaces are augmented to guarantee stability. For the aggregation method, the reduced basis approximation spaces for the state and adjoint variables are augmented in such a way that the spaces are identical. For the supremizer method, the reduced basis approximation space for the state-control product space is augmented with the solutions of a supremizer equation. We implement both of these methods for solving several parametrized control problems and assess their performance. Results indicate that the number of reduced basis vectors needed to approximate the solution space to some tolerance with the supremizer method is much larger, possibly double, that for aggregation. There are also some cases where the supremizer method fails to produce a converged solution. We present results to compare the accuracy, efficiency, and computational costs associated with both methods of stabilization which suggest that stabilization by aggregation is a superior stabilization method for control problems. © 2023, CC BY.

关键词： Stabilization

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Estimation of Parameter Distributions for Reaction-Diffusion Equations with Competition using Aggregate Spatiotemporal Data

arXiv

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arXiv 2023年

作者： Nguyen, Kyle Rutter, Erica M. Flores, Kevin Biomathematics Graduate Program North Carolina State University RaleighNC United States Center for Research in Scientific Computation North Carolina State University RaleighNC United States Department of Applied Mathematics University of California Merced MercedCA United States Department of Mathematics North Carolina State University RaleighNC United States

Reaction diffusion equations have been used to model a wide range of biological phenomenon related to population spread and proliferation from ecology to cancer. It is commonly assumed that individuals in a population have homogeneous diffusion and growth rates, however, this assumption can be inaccurate when the population is intrinsically divided into many distinct subpopulations that compete with each other. In previous work, the task of inferring the degree of phenotypic heterogeneity between subpopulations from total population density has been performed within a framework that combines parameter distribution estimation with reaction-diffusion models. Here, we extend this approach so that it is compatible with reaction-diffusion models that include competition between subpopulations. We use a reaction-diffusion model of Glioblastoma multiforme, an aggressive type of brain cancer, to test our approach on simulated data that are similar to measurements that could be collected in practice. We use Prokhorov metric framework and convert the reaction-diffusion model to a random differential equation model to estimate joint distributions of diffusion and growth rates among heterogeneous subpopulations. We then compare the new random differential equation model performance against other partial differential equation models’ performance. We find that the random differential equation is more capable at predicting the cell density compared to other models while being more time efficient. Finally, we use k-means clustering to predict the number of subpopulations based on the recovered distributions. © 2023, CC BY.

关键词： Parameter estimation

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PERMUTATION INVARIANT REPRESENTATIONS with APPLICATIONS to GRAPH DEEP LEARNING

arXiv

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arXiv 2022年

作者： Balan, Radu Haghani, Naveed Singh, Maneesh Department of Mathematics University of Maryland College ParkMD20742 United States Applied Mathematics and Statistics and Scientific Computation Program University of Maryland College ParkMD20742 United States Verisk Analytics Jersey CityNJ07310 United States

This paper presents primarily two Euclidean embeddings of the quotient space generated by matrices that are identified modulo arbitrary row permutations. The original application is in deep learning on graphs where the learning task is invariant to node relabeling. Two embedding schemes are introduced, one based on sorting and the other based on algebras of multivariate polynomials. While both embeddings exhibit a computational complexity exponential in problem size, the sorting based embedding is globally bi-Lipschitz and admits a low dimensional target space. Additionally, an almost everywhere injective scheme can be implemented with minimal redundancy and low computational cost. In turn, this proves that almost any classifier can be implemented with an arbitrary small loss of performance. Numerical experiments are carried out on two data sets, a chemical compound data set (QM9) and a proteins data set (PROTEINS FULL).MSC Codes 05C62, 20C32, 68R12 © 2022, CC BY.

关键词： Embeddings

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Consensus dynamics and coherence in hierarchical small-world networks

arXiv

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arXiv 2023年

作者： Liao, Yunhua Maama, Mohamed Aziz-Alaoui, M.A. Department of Mathematics Hunan University of Technology and Business Hunan Changsha410205 China Key Laboratory of Hunan Province for Statistical Learning and Intelligent Computation Hunan Changsha410205 China Applied Mathematics and Computational Science Program KAUST Thuwal23955-6900 Saudi Arabia Normandie Univ UNIHAVRE LMAH FR-CNRS-3335 ISCN Le Havre76600 France

The hierarchical small-world network is a real-world network. It models well the benefit transmission web of the pyramid selling in China and many other countries. In this paper, by applying the spectral graph theory, we study three important aspects of the consensus problem in the hierarchical small-world network: convergence speed, communication time-delay robustness, and network coherence. Firstly, we explicitly determine the Laplacian eigenvalues of the hierarchical small-world network by making use of its treelike structure. Secondly, we find that the consensus algorithm on the hierarchical small-world network converges faster than that on some well-studied sparse networks, but is less robust to time delay. The closed-form of the first-order and the second-order network coherence are also derived. Our result shows that the hierarchical small-world network has an optimal structure of noisy consensus dynamics. Therefore, we provide a positive answer to two open questions of Yi et al. Finally, we argue that some network structure characteristics, such as large maximum degree, small average path length, and large vertex and edge connectivity, are responsible for the strong robustness with respect to external perturbations. Copyright © 2023, The Authors. All rights reserved.

关键词： Eigenvalues and eigenfunctions

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Estimation of mask effectiveness perception for small domains using multiple data sources

arXiv

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arXiv 2021年

作者： Sen, Aditi Lahiri, Partha Applied Mathematics & Statistics and Scientific Computation University of Maryland College Park United States The Joint Program in Survey Methodology Department of Mathematics University of Maryland College ParkMD20742 United States

All pandemics are local;so learning about the impacts of pandemics on public health and related societal issues at granular levels is of great interest. COVID-19 is affecting everyone in the globe and mask wearing is one of the few precautions against it. To quantify people's perception of mask effectiveness and to prevent the spread of COVID-19 for small areas, we use Understanding America Study's (UAS) survey data on COVID-19 as our primary data source. Our data analysis shows that direct survey-weighted estimates for small areas could be highly unreliable. In this paper, we develop a synthetic estimation method to estimate proportions of mask effectiveness for small area using a logistic model that combines information from multiple data sources. We select our working model using an extensive data analysis facilitated by a new variable selection criterion for survey data and benchmarking ratios. We propose a jackknife method to estimate variance of our proposed estimator. From our data analysis, it is evident that our proposed synthetic method outperforms direct survey-weighted estimator with respect to commonly used evaluation measures. Copyright © 2021, The Authors. All rights reserved.

关键词： Data handling

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Transcutaneous Vagus Nerve Stimulation: an Alternative Treatment of Chronic Migraine—a Systematic Review

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SN Comprehensive Clinical Medicine 2022年第1期4卷 1-13页

作者： de Carvalho, Ana Cláudia Marques, Aeska Lanary Cristino Ferreira, Lais Leite de Brito, Francisco Xavier Baptista, Abrahão Fontes da Silva, Marcelo Lourenço da Silva, Josie Resende Torres Federal University of Alfenas Alfenas Brazil Biosciences Applied to Health Program Federal University of Alfenas Alfenas Brazil Health and Function Study Nucleus Federal University of Bahia Salvador Bahia Brazil Center for Mathematics Computation and Cognition Federal University of ABC São Paulo Brazil Institute of Motricity Sciences Federal University of Alfenas Alfenas Brazil Federal University of Alfenas LANNED Laboratory of Neuroscience Neuromodulation and Study of Pain Alfenas Brazil

Migraine is a disabling condition that is currently underdiagnosed and undertreated. Transcutaneous vagus nerve stimulation (VNS) is among the most researched non-invasive brain stimulation techniques for migraine control. In this systematic review, we discuss the effects of VNS parameters (waveform, frequency, intensity, cycle, and current) and central and clinical mechanisms in auricular (taVNS) or cervical (tcVNS) transcutaneous VNS in the control of migraine pain. PubMed (National Library of Medicine), Cochrane Library, CAPES Journals (Portal of Journals of the Coordination for the Improvement of Higher Education Personnel), Virtual Health Library (VHL), and Google Scholar were searched by computer from the establishment of within the 10-year period (2011– 2021). Initially, a total of 10,017 articles were identified. After applying the exclusion criteria, 10,007 articles were excluded. The eligibility criteria were analyzed and only ten articles fulfilled the criteria. The most used parameters in this study for VNS were the frequencies of 1 Hz, 25 Hz, and 30 Hz. The 1-Hz stimulation caused a more significant reduction in the number of days with headache. The total stimulation time varies between studies, ranging from 2 to 240 min, and can be repeated for a period or a single session. Studies that used a longer treatment period showed clinical results in reducing pain and analyzed the scores. Moreover, studies have shown reduced intensity or severity of pain after taVNS. The studies performed taVNS or tcVNS, and both methods had positive effects on migraine control, pain reduction, and migraine score. An systematic literature review of transcutaneous vagus nerve stimulation (tVNS) on migraine pain management. The results indicate that auricular or cervical tVNS methods had positive effects on migraine control, pain reduction, and migraine score.

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Realistic-science, technology, engineering, and mathematics assisted by google classroom as a learning innovation in the new normal era to improve statistical thinking skill

引用

Journal of Physics: Conference Series 2021年第4期1918卷

作者： A S Ardiansyah N A Novita H Zhintya D Kurnianto Mathematics Education Study Program Universitas Negeri Semarang Applied Statistics and Computation Study Program Universitas Negeri Semarang

Based on government policies regarding the implementation of learning from home, it is necessary the learning innovation to continue learning in the new normal era by utilizing existing technological advances. In this digital era, statistics thinking is important because it is needed to be able to interpret and understand and make good decisions from the statistical data obtained. From these problems, one of the innovations that can be done is by implementing Realistic mathematics Education integrated Science, Technology, Engineering, and mathematics assisted by Google Classroom (R-STEM-GC). This paper aims to determine the effect of R-STEM-GC learning on students' statistical thinking skills. This paper uses literature review method research that identifies, assesses, and interprets all findings on a research topic to answer existing research questions. It can concluded that realistic learning was more effective in terms of students' mathematical reasoning and communication than conventional learning; learning with the application of STEM can improve students' problem solving abilities compared to conventional learning; and the use of google classrooms that can improve communication skills. From the results of this analysis, the application of R-STEM-GC learning can be an innovative solution in improving students' statistical thinking skills in new normal era.

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Using Cluster Analysis and Dynamic programming for Demand Response applied to Electricity Load in Residential Homes

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Journal of Engineering for Sustainable Buildings and Cities 2020年第1期1卷 011006页

作者： Chanpiwat, Pattanun Gabriel, Steven A. Moglen, Rachel L. Siemann, Michael J. Department of Mechanical Engineering University of Maryland College Park 20742 MD United States Department of Mechanical Engineering and the Applied Mathematics Statistics and Scientific Computation Program University of Maryland College Park 20742 MD United States Department of Industrial Economics and Technology Management Norwegian University of Science and Technology Trondheim NO-7491 Norway Operations Research and Industrial Engineering The University of Texas at Austin Austin 78712 TX United States Resideo Technologies Austin 78702 TX United States

This paper develops means to analyze and cluster residential households into homogeneous groups based on the electricity load. Classifying customers by electricity load profiles is a top priority for retail electric providers (REPs), so they can plan and conduct demand response (DR) effectively. We present a practical method to identify the most DR-profitable customer groups as opposed to tailoring DR programs for each separate household, which may be computationally prohibitive. Electricity load data of 10,000 residential households from 2017 located in Texas was used. The study proposed the clustered load-profile method (CLPM) to classify residential customers based on their electricity load profiles in combination with a dynamic program for DR scheduling to optimize DR profits. The main conclusions are that the proposed approach has an average 2.3% profitability improvement over a business-as-usual heuristic. In addition, the proposed method on average is approximately 70 times faster than running the DR dynamic programming separately for each household. Thus, our method not only is an important application to provide computational business insights for REPs and other power market participants but also enhances resilience for power grid with an advanced DR scheduling tool. Copyright © 2020 by ASME.

关键词： cluster analysis customer classification demand response dynamic programming energy efficiency integrated systems occupant behavior optimization residential household

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