检索结果-内蒙古大学图书馆

Building Ramps and Pathways to Data science in K-12, Minority-Serving Institutions, and Two-Year Colleges

Scatterplot 2024年第1期1卷

作者： Rachel Saidi Helen Burn Ben Baumer Jason Black Debzani Deb Zarek Drozda a Math Statistics and Data Science Department Montgomery College – Rockville Campus Rockville MD USA b Mathematics Department Highline College Des Moines Washington Des Moines WA USA c Statistical and Data Sciences Department Smith College Northampton MA USA d School of Business and Interdisciplinary Center for Creativity and Innovation (ICCI) Florida A&M University Tallahassee FL USA e Computer Science Department Center for Applied Data Science (CADS) Winston-Salem State University Winston-Salem NC USA f Data Science 4 Everyone (DS4E) Program University of Chicago Chicago IL USA

Global demand for data scientists and analysts is on a trajectory of sustained growth, underscoring the need to expand enrollment of students in data science and data analytics courses and programs. This article explores diverse pathways to data science for various groups, including high school students, those in two-year colleges, and students in small colleges and minority-serving institutions. This article identifies opportunities and challenges associated with pursuing data science for students in these sectors, including factors such as building partnerships and awareness of the field and difficulties in establishing articulation agreements between institutions. The authors, representing various organizations participating in a panel discussion at the 2023 Data science Leadership Summit of the Academic Data science Alliance (ADSA), share insights into efforts to develop nontraditional pathways, serving as a resource for schools, colleges, and organizations contemplating creation of data science programs. The panelists’ combined experience spans work with a broad range of organizations including ADSA, American mathematics Association of Two-Year Colleges, American Statistical Association, Data science for Everyone, the Department of Education, HBCU Data science Consortium, Mathematical Association of America, National Academies of science, Engineering, and Medicine, HBCU Data science Consortium, National science Foundation, and StatPREP.

关键词： Data science pathways access K-12 minority-serving institution two-year college

来源：评论

学校读者我要写书评

暂无评论

Multigoal-oriented error estimation and mesh adaptivity for fluid-structure interaction

arXiv

引用

arXiv 2021年

作者： Ahuja, K. Endtmayer, B. Steinbach, M.C. Wick, Thomas Discipline of Computer Science and Engineering Indian Institute of Technology Indore India Leibniz Universität Hannover Institut für Angewandte Mathematik Welfengarten 1 Hannover30167 Germany Leibniz Universität Hannover Germany Université Paris-Saclay ENS Paris-Saclay LMT - Laboratoire de Mécanique et Technologie Gif-sur-Yvette91190 France Johannes Kepler University Linz Doctoral Program on Computational Mathematics Altenbergerstr. 69 LinzA-4040 Austria Austrian Academy of Sciences Johann Radon Institute for Computational and Applied Mathematics Altenbergerstr. 69 LinzA-4040 Austria

In this work, we consider multigoal-oriented error estimation for stationary fluid-structure interaction. The problem is formulated within a variational-monolithic setting using arbitrary Lagrangian-Eulerian coordinates. Employing the dual-weighted residual method for goal-oriented a posteriori error estimation, adjoint sensitivities are required. For multigoal-oriented error estimation, a combined functional is formulated such that several quantities of interest are controlled simultaneously. As localization technique for mesh refinement we employ a partition-of-unity. Our algorithmic developments are substantiated with several numerical tests such as an elastic lid-driven cavity with two goal functionals, an elastic bar in a chamber with two goal functionals, and the FSI-1 benchmark with three goal *** Codes 65N30, 65N50, 74F10 © 2021, CC BY-NC-ND.

关键词： Fluid structure interaction

来源：评论

学校读者我要写书评

暂无评论

Implementation of Fuzzy-based Model for Prediction of Prostate Cancer

引用

Journal of Physics: Conference Series 2021年第1期1751卷

作者： Rusliyawati Kurnia Muludi Admi Syarif Agus Wantoro Doctoral Program of Mathematics and Science Faculty Lampung University Jl. Sumantri Brojonegoro No 1 Bandar Lampung Indonesia. Faculty of Engineering and Computer Science Universitas Teknokrat Indonesia J. ZA. Pagaralam No. 9-11 Bandar Lampung Indonesia. Department of Computer Science Faculty of Mathematics and Science University of Lampung Jl. Sumantri Brojonegoro No 1 Bandar Lampung Indonesia

Cancer is one of the leading causes of death worldwide. One type of cancer that causes death in the male population is prostate cancer. This disease occurs only in men because in women they do not have a prostate appearance. The aim of this study was to compare the accuracy of the model with the predictions of prostate cancer specialists. Prediction is made based on prostate specific antigen data, age, and patient prostate volume. The independent variables in this study were prostate specific antigen, age, and prostate volume. The dependent variable is the risk of prostate cancer using a fuzzy model. The novelty of this study is that the model has a low, moderate, high, and very high prostate cancer risk level output. In the previous article only PCR values were produced. The results show that the proposed fuzzy model provides a PCR value that is within the PCR interval predicted by a specialist doctor can be used properly to help diagnose and analyze the possibility of prostate cancer and is one of the considerations for doctors to decide whether or not a biopsy is needed for these patients.

关键词：

来源：评论

学校读者我要写书评

暂无评论

International Workshop on Applications of Probability and Statistics to Biology,July 11-13,2019--In Honor of Professor Minping Qian’s 80th Birthday

引用

Quantitative Biology 2020年第2期8卷 177-186页

作者： Minghua Deng Jianfeng Feng Hong Qian Lin Wan Fengzhu Sun Center for Quantitative Biology Peking UniversityBeijing 100871China LMAM Center for Statistical ScienceSchool of Mathematical SciencesPeking UniversityBeijing 100871China Institute of Science and Technology for Brain-inspired Intelligence Fudan UniversityShanghai 200433China School of Mathematical Sciences Fudan UniversityShanghai 200433China Centre for Computational Systems Biology Fudan UniversityShanghai 200433China Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence at Fudan University Ministry of EducationShanghai 200433China Department of Computer Science University of WarwickCoventryCV47ALUnited Kingdom Department of Applied Mathematics University of WashingtonSeattleWA 98195USA NCMIS Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China Quantitative and Computational Biology Program University of Southern CaliforniaLos AngelesCA 90089USA

The International Workshop on Applications of Probability and Statistics to Biology(APSB)was successfully held in Shanghai,China,July 11-13,*** workshop was hosted by the Institute of science and Technology for Brain-inspired Intelligence(ISTBI)at Fudan University,and in honor of the 80th birthday of *** Qian of Peking *** of the twenty eight speakers were former students or close collaborators of ***;and there were over eighty participants from all over China and United States.

关键词： Probability speakers ping

来源：评论

学校读者我要写书评

暂无评论

Develop learning methods imr (integrated material realistic) alternative mathematics learning during a pandemic

引用

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

作者： I.M. Rusmana Zainuri Wardono A.L Nulhakim Doctoral Program Universitas Negeri Semarang Indonesia Department of Mathematic Education Faculty of Mathematics and Natural Science Universitas Indraprasta PGRI Jakarta Indonesia Department of Mathematic Education Faculty of Mathematics and Natural Science Universitas Negeri Semarang Indonesia Department of Informatics Engineering Faculty of Engineering and Computer Science Universitas Indraprasta PGRI Jakarta Indonesia

The learning methods used by teachers in schools in Serang City are very ineffective, especially during the pandemic. This is because not integrated content of material in one subject with other subjects. Never mind between subjects, sometimes the material is not well integrated. The purpose of this study is to provide an alternative learning method during a pandemic, namely a method that integrates material with the realities of life which is abbreviated as IMR (Integrated Realistic Material). The method in this research is Research and Development (RnD) with the ADDIE model. In making this learning method according to the stages from the ADDIE study. The results of this study are in the form of learning methods that are integrated with the realities of life during the pandemic.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Interpretable bias mitigation for textual data: Reducing gender bias in patient notes while maintaining classification performance

arXiv

引用

arXiv 2021年

作者： Minot, Joshua R. Cheney, Nicholas Maier, Marc Elbers, Danne C. Danforth, Christopher M. Dodds, Peter Sheridan Computational Story Lab University of Vermont BurlingtonVT05401 United States Vermont Complex Systems Center University of Vermont BurlingtonVT05401 United States Department of Computer Science University of Vermont BurlingtonVT05401 United States Neurobotics Lab University of Vermont BurlingtonVT05401 United States MassMutual Data Science AmherstMA01002 United States VA Cooperative Studies Program VA Boston Healthcare System BostonMA02130 United States Department of Mathematics and Statistics University of Vermont BurlingtonVT05401 United States

Medical systems in general, and patient treatment decisions and outcomes in particular, are affected by bias based on gender and other demographic elements. As language models are increasingly applied to medicine, there is a growing interest in building algorithmic fairness into processes impacting patient care. Much of the work addressing this question has focused on biases encoded in language models—statistical estimates of the relationships between concepts derived from distant reading of corpora. Building on this work, we investigate how word choices made by healthcare practitioners and language models interact with regards to bias. We identify and remove gendered language from two clinical-note datasets and describe a new debiasing procedure using BERT-based gender classifiers. We show minimal degradation in health condition classification tasks for low- to medium-levels of bias removal via data augmentation. Finally, we compare the bias semantically encoded in the language models with the bias empirically observed in health records. This work outlines an interpretable approach for using data augmentation to identify and reduce the potential for bias in natural language processing pipelines. Copyright © 2021, The Authors. All rights reserved.

关键词： Natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

Identification of Sumatera Butterfly species by using deep learning with data augmentation

引用

AIP Conference Proceedings 2024年第1期2970卷

作者： Rico Andrian Admi Syarif Favorisen Rosyking Lumbanraja Emantis Rosa Doctoral Program of Mathematics and Natural Sciences Lampung University Jl. Prof. Dr. Sumantri Brojonegoro No. 1 Bandar Lampung 35145 Indonesia Department of Computer Science Lampung University Jl. Prof. Dr. Sumantri Brojonegoro No. 1 Bandar Lampung 35145 Indonesia Department of Biology Lampung University Jl. Prof. Dr. Sumantri Brojonegoro No. 1 Bandar Lampung 35145 Indonesia

Butterflies are members of the Lepidoptera order. The complexity of the Sumatera Butterfly’s patterns and hues makes it difficult to identify with the naked eye. Gita Persada Butterfly Park is always crowded with people who want to see and learn about the different species of Sumatera butterfly. The Sumatera Butterfly, which humans can see with the naked eye, is quite difficult to identify without the assistance of certain technologies due to its diverse patterns and colors and the fact that there are nearly several species. AlexNet is one of the deep learning architectures that can detect images of the Sumatera Butterfly, functioning similarly to the human brain in object recognition. Deep learning employs artificial neural networks for learning. The first stage of this research consisted of collecting the Sumatera Butterfly dataset and identifying the butterfly species with AlexNet. The second step is identifying Sumatera butterfly species using AlexNet with additional data augmentation, flip data augmentation, and rotate data augmentation. The comparison between pre- and post-augmentation performance will reveal the difference. AlexNet’s accuracy without boost is 98.12 percent. After adding data augmentation to AlexNet architecture, the accuracy ratio is 99.06 percent, while AlexNet’s highest accuracy is 99.37 percent with flip augmentation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

In silico analysis of tetrahydroxycurcumin compound in tumeric (Curcuma longa) as inhibitor of SARS-CoV-2 virus replication

引用

AIP Conference Proceedings 2023年第1期2748卷

作者： Mohamad Amin Nanda Hilda Khikmawati Suryadi Suryadi Rifcha Fachrunnisa Ihya Fakhrurizal Amin Dina Maulina Ahya Zhilalikbar Amin Nik Ahmad Nizam Nik Malek Restu Fitriani Department of Biology Faculty of Mathematics and Natural Sciences Universitas Negeri Malang Jl. Semarang No.5 Malang 65145 Indonesia Special Education Department Faculty of Education Universitas Negeri Malang Jl. Semarang No.5 Malang 65145 Indonesia Faculty of Medicine Universitas Indonesia Jakarta Indonesia Biology Education Study Program Faculty of Teacher Training and Education Universitas Lampung Lampung Indonesia Department of Biosciences Faculty of Science Universiti Teknologi Malaysia Johor Malaysia Study Program of Informatics Engineering Faculty of Computer Sciencies Universitas Brawijaya Malang Indonesia Biotechnology Program Faculty of Mathematics and Natural Sciences Universitas Negeri Malang Jl. Semarang No.5 Malang 65145 Indonesia

There are many uses of natural ingredients to find out their potential in overcoming Coronavirus Disease 2019. One of the plants that is often used to treat various diseases, including SARS-Cov2 infection is turmeric. Turmeric contains Tetrahydroxycurcumin compounds. The aim of this research was to study the potential of Tetrahydroxycurcumin in preventing infection with the SARS-CoV-2 virus. The results showed that Tetrahydroxicurcumin has the potential to inhibit Tyrosine protein kinase ABL1, which is a protein that plays a role in the preparation of the cytoskeleton during viral infection. The binding affinity of Tetrahydroxycurcumin for this protein is -8.4 kcal/mol.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Topological Data Analysis of Black Hole Images

arXiv

引用

arXiv 2022年

作者： Christian, Pierre Chan, Chi-Kwan Hsu, Anthony Özel, Feryal Psaltis, Dimitrios Natarajan, Iniyan Physics Department Fairfield University 1073 N Benson Rd FairfieldCT06824 United States Department of Astronomy University of Arizona 933 North Cherry Avenue TucsonAZ85721 United States Data Science Institute University of Arizona 1230 N. Cherry Ave. TucsonAZ85721 United States Program in Applied Mathematics University of Arizona 617 N. Santa Rita TucsonAZ85721 United States Department of Computer Science University of Arizona 1040 4th St TucsonAZ85721 United States Wits Centre for Astrophysics University of the Witwatersrand 1 Jan Smuts Avenue Braamfontein Johannesburg2050 South Africa South African Radio Astronomy Observatory Observatory Cape Town7925 South Africa

Features such as photon rings, jets, or hot spots can leave particular topological signatures in a black hole image. As such, topological data analysis can be used to characterize images resulting from high resolution observations (synthetic or real) of black holes in the electromagnetic sector. We demonstrate that persistent homology allows for this characterization to be made automatically by counting the number of connected components and one-dimensional holes. Further, persistent homology also allows for the distance between connected components or diameter of holes to be extracted from the image. In order to apply persistent homology on synthetic black hole images, we also introduce metronization, a new algorithm to prepare black hole images into a form that is suitable for topological analysis. Copyright © 2022, The Authors. All rights reserved.

关键词： Black holes

来源：评论

学校读者我要写书评

暂无评论

Emergent Dimer-Model Topological Order and Quasiparticle Excitations in Liquid Crystals: Combinatorial Vortex Lattices

引用

Physical Review X 2025年第2期15卷 021084-021084页

作者： Cuiling Meng Jin-Sheng Wu Žiga Kos Jörn Dunkel Cristiano Nisoli Ivan I. Smalyukh Department of Physics and Chemical Physics Program University of Colorado Boulder Colorado 80309 USA International Institute for Sustainability with Knotted Chiral Meta Matter (WPI-SKCM) Hiroshima University Higashihiroshima Hiroshima Japan Department of Mathematics Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Faculty of Mathematics and Physics University of Ljubljana Ljubljana Slovenia Department of Condensed Matter Physics Jožef Stefan Institute Ljubljana Slovenia Theoretical Division Physics of Condensed Matter and Complex Systems and Center For Nonlinear Studies Los Alamos National Laboratory Los Alamos New Mexico 87545 USA Department of Electrical Computer and Energy Engineering Materials Science and Engineering Program University of Colorado Boulder Colorado 80309 USA Renewable and Sustainable Energy Institute National Renewable Energy Laboratory University of Colorado Boulder Colorado 80309 USA

Liquid crystals have proven to provide a versatile experimental and theoretical platform for studying topological objects such as vortices, skyrmions, and hopfions. In parallel, in hard condensed matter physics, the concept of topological phases and topological order has been introduced in the context of spin liquids to investigate emergent phenomena like quantum Hall effects and high-temperature superconductivity. Here, we bridge these two seemingly disparate perspectives on topology in physics. Combining experiments and simulations, we show how topological defects in liquid crystals can be used as versatile building blocks to create complex, highly degenerate topological phases, which we refer to as “combinatorial vortex lattices” (CVLs). CVLs exhibit extensive residual entropy and support locally stable quasiparticle excitations in the form of charge-conserving topological monopoles, which can act as mobile information carriers and be linked via Dirac strings. CVLs can be rewritten and reconfigured on demand, endowed with various symmetries, and modified through laser-induced topological surgery—an essential capability for information storage and retrieval. We demonstrate experimentally the realization, stability, and precise optical manipulation of CVLs, thus opening new avenues for understanding and technologically exploiting higher-hierarchy topology in liquid crystals and other ordered media.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：