Algebra Calculator的問題,透過圖書和論文來找解法和答案更準確安心。 我們找到下列特價商品、必買資訊和推薦清單

Algebra Calculator的問題,我們搜遍了碩博士論文和台灣出版的書籍,推薦Gilbert, Robert P.,Hsiao, George C.,Ronkese, Robert J.寫的 Maple(tm) Supplement for Differential Equations 和Moyer, Robert E.的 Conquering GRE Math, Fourth Edition都 可以從中找到所需的評價。

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國立臺灣師範大學 數學系 林俊吉、鍾佑民所指導 胡全燊的 數學形態學導出多參數持續同調之層狀結構 (2021),提出Algebra Calculator關鍵因素是什麼,來自於。

而第二篇論文國立臺灣師範大學 數學系數學教學碩士在職專班 謝豐瑞所指導 蘇曉洳的 圖形計算機應用於二維數據分析教學實驗 (2021),提出因為有 圖形計算機、探究式教學、核心素養、二維數據分析的重點而找出了 Algebra Calculator的解答。

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Maple(tm) Supplement for Differential Equations

為了解決Algebra Calculator的問題,作者Gilbert, Robert P.,Hsiao, George C.,Ronkese, Robert J. 這樣論述:

This book illustrates how MAPLE can be used to supplement a standard, elementary text in ordinary and partial differential equation. MAPLE is used with several purposes in mind. The authors are firm believers in the teaching of mathematics as an experimental science where the student does numerou

s calculations and then synthesizes these experiments into a general theory.Projects based on the concept of writing generic programs test a student’s understanding of the theoretical material of the course. A student who can solve a general problem certainly can solve a specialized problem. The aut

hors show MAPLE has a built-in program for doing these problems. While it is important for the student to learn MAPLEŚ in built programs, using these alone removes the student from the conceptual nature of differential equations.The goal of the book is to teach the students enough about the computer

algebra system MAPLE so that it can be used in an investigative way. The investigative materials which are present in the book are done in desk calculator mode DCM, that is the calculations are in the order command line followed by output line. Frequently, this approach eventually leads to a progra

m or procedure in MAPLE designated by proc and completed by end proc. This book was developed through ten years of instruction in the differential equations course. Table of Contents1. Introduction to the Maple DEtools 2. First-order Differential Equations 3. Numerical Methods for First Order Equati

ons 4. The Theory of Second Order Differential Equations with Con-5. Applications of Second Order Linear Equations 6. Two-Point Boundary Value Problems, Catalytic Reactors and7. Eigenvalue Problems 8. Power Series Methods for Solving Differential Equations 9. Nonlinear Autonomous Systems 10. Integra

l Transforms BiographiesRobert P. Gilbert holds a Ph.D. in mathematics from Carnegie Mellon University. He and Jerry Hile originated the method of generalized hyperanalytic function theory. Dr. Gilbert was professor at Indiana University, Bloomington and later became the Unidel Foundation Chair of M

athematics at the University of Delaware. He has published over 300 articles in professional journals and conference proceedings. He is the Founding Editor of two mathematics journals Complex Variables and Applicable Analysis. He is a three-time Awardee of the Humboldt-Preis, and. received a British

Research Council award to do research at Oxford University. He is also the recipient of a Doctor Honoris Causa from the I. Vekua Institute of Applied Mathematics at Tbilisi State University. George C. Hsiao holds a doctorate degree in Mathematics from Carnegie Mellon University. Dr. Hsiao is the Ca

rl J. Rees Professor of Mathematics Emeritus at the University of Delaware from which he retired after 43 years on the faculty of the Department of Mathematical Sciences. Dr. Hsiao was also the recipient of the Francis Alison Faculty Award, the University of Delaware’s most prestigious faculty honor

, which was bestowed on him in recognition of his scholarship, professional achievement and dedication. His primary research interests are integral equations and partial differential equations with their applications in mathematical physics and continuum mechanics. He is the author or co-author of m

ore than 200 publications in books and journals. Dr. Hsiao is world-renowned for his expertise in Boundary Element Method and has given invited lectures all over the world.Robert J. Ronkese holds a PhD in applied mathematics from the University of Delaware. He is a professor of mathematics at the US

Merchant Marine Academy on Long Island. As an undergraduate, he was an exchange student at the Swiss Federal Institute of Technology (ETH) in Zurich. He has held visiting positions at the US Military Academy at West Point and at the University of Central Florida in Orlando.

數學形態學導出多參數持續同調之層狀結構

為了解決Algebra Calculator的問題,作者胡全燊 這樣論述:

Topological Data Analysis (TDA), a fast-growing research topic in applied topology, uses techniques in algebraic topology to capture features from data. Its importance has been discovered in many areas, such as medical image processing, molecular biology, machine learning, and pattern recognition.

Persistent homology (PH) is vital in topological data analysis that detects local changes in filtered topological spaces. It measures the robustness and significance of homological objects in spaces' deformation, such as connected components, loops, or higher dimensional voids. In Morse theory, filt

ered spaces for persistent homology usually rely on a single parameter, such as the sublevel set filtration of height functions. Recently, as a generalization of persistent homology, computational topologists began to be interested in multi-parameter persistent homology. Multi-parameter persistent h

omology (or multi-parameter persistence) is an algebraic structure established on a multi-parametrized network of topological spaces and has more fruitful geometric information than persistent homology. So far, finding methods to extract features in multi-parameter persistence is still an open and

concentrating topic in TDA. Also, examples of multi-parameter filtration are still rare and limited. The three principal contributions of this dissertation are as follows. First, we combined persistent homology features (persistence statistics and persistence curves) and machine learning models for

analyzing medical images. We found that adding topological information into machine learning models can improve recognition accuracy and stability. Second, unlike traditional construction for multi-parameter filtrations in Euclidean spaces, we propose a framework for constructing multi-parameter fi

ltrations from digital images through mathematical morphology and discrete geometry. Multi-parameter persistence derived from mathematical morphology is more efficient for computing and contains intuitive geometric attributes of objects, such as the sizes or robustness of local objects in digital im

ages. We involve these features to remove the salt and pepper noise in digital images as an application. Compared with current denoise algorithms, the proposed approach has a more stable accuracy and keeps the topological structures of original data. The third part of this dissertation focuses on us

ing sheaf theory to analyze the lifespans of objects in multi-parameter persistence. The multi-parameter persistence has a natural sheaf structure by equipping the Alexandrov topology on the based partially ordered set. This sheaf structure uncovers the gluing properties of local image regions in th

e multi-parameter filtration. We referred to these properties as a fingerprint of the filtration and applied them for the character recognition task. Finally, we propose using sheaf operators to define ultrametric norms on local spaces in multi-parameter persistence. Like persistence barcodes, this

metric provides finer geometric and topological quantities.

Conquering GRE Math, Fourth Edition

為了解決Algebra Calculator的問題,作者Moyer, Robert E. 這樣論述:

Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, oraccess to any online entitlements included with the product.A comprehensive tool to help boost your score on the GRE math section If you're one of the more than half a milli

on people who take the GRE every year and want to boost your math score, than this is the ideal study resource for you McGraw-Hill Education's Conquering GRE Math, Fourth Edition is unique in that the problems increase in difficulty as you progress through the book. This will help you develop proble

m-solving skills as you prepare for the exam. Exercises show how each math concept is tested on the GRE. Full-length GRE math sections provide practice with questions just like those on the real test.The author is a math teacher who specializes in helping students enhance their GRE related math skil

ls.Score raising features include: - 3 full-length GRE tests provide practice with questions just like those on the real test- Updated information on how and when to use your calculator on the exam- Complete review of GRE math topics including: number properties, arithmetic, algebra, geometry, and w

ord problems- Strategies for answering every GRE math question type: quantitative comparison, multiple choice, numeric entry, and data analysis- Intensive drills and practice exercises, and more Robert E. Moyer, Ph.D., was formerly associate professor of Mathematics at Southwest Minnesota State Un

iversity in Marshall, MN. He is the co-author of four bestselling Schaum’s Outlines in mathematics, and he has also written math questions for the GED and the ASVAB.

圖形計算機應用於二維數據分析教學實驗

為了解決Algebra Calculator的問題,作者蘇曉洳 這樣論述:

本研究旨在透過以108課綱各項核心素養為導向、二維數據分析單元為主題的圖形計算機探索式教學活動來探究教材發展與教學歷程,並透過研究工具的分析了解活動之於學生在學習成效、素養能力表現的影響為何。因此本研究共提出以下三個研究問題:(1)計算機探索式教學為主的二維數據分析課堂之教材設計發展歷程為何?;(2)計算機探索式教學為主的二維數據分析課堂之特徵為何?與傳統講述式教學有何差異?;(3)圖形計算機探究式教學活動對高一學生之學習成效影響為何?又對於哪種成就學生影響最甚?本研究採用準實驗研究法(Quasi-Experimental Research)之不等組前後測設計,以原有班級為單位,從研究者任教

的班級中立意抽樣兩個在能力上無顯著差異的班級作為實驗組與控制組,進行為期約莫兩週的教學實驗。其中實驗組施以圖形計算機探索式教學,而控制組則進行傳統教師講述式教學。在教學實驗結束後兩組學生皆接受二維數據分析單元成就測驗,而實驗組則額外進行計算機探索式教學活動評估問卷作答,此外研究者亦收集了學生學習單及上課錄影內容等質性資料,最後針對上述各項資料進行量化分析與質性分析,藉以了解學生的學習成效與表現。研究結果包含本研究所發展之二維數據分析單元的圖形計算機探索式教學活動教材內容、課堂中教與學的歷程結果及學生的學習成效,其中學習成效指的是成就測驗表現與教學活動評估問卷結果。透過結果分析本研究得到以下幾項

重要結論:1. 計算機探索式教學活動能有效幫助各成就水準學生提升成就測驗的表現。2. 計算機探索式教學活動能增強學生的學習動機與興趣,有效提升其課堂學習表現。3. 透過圖形計算機將概念視覺化,能有效幫助學生進行探索並理解數學概念4. 計算機探索式教學活動能有效幫助學生培養核心素養與技能。5. 在考試中開放使用計算機能有效減輕學生的計算負荷並提高得分率,進而增強學生在考試時的參與度與自信心。6. 學生會因對工具操作不熟悉或難易度影響學習效果,且越高成就學生越容易受到影響。