LEADER 03941nam 22006135 450 001 9910983482303321 005 20241112115737.0 010 $a9783662699737 010 $a3662699737 024 7 $a10.1007/978-3-662-69973-7 035 $a(CKB)36549430000041 035 $a(MiAaPQ)EBC31778860 035 $a(Au-PeEL)EBL31778860 035 $a(DE-He213)978-3-662-69973-7 035 $a(EXLCZ)9936549430000041 100 $a20241112d2025 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aEngineering Mechanics 3: Dynamics /$fby Christian Mittelstedt 205 $a1st ed. 2025. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2025. 215 $a1 online resource (239 pages) 311 08$a9783662699720 311 08$a3662699729 327 $aKinematics of the point mass -- Kinetics of the point mass -- Theorem of work and theorem of energy for the point mass -- Kinematics and kinetics of systems of point masses -- Motions of rigid bodies -- Impact processes -- Vibrations -- Principles of dynamics -- Relative motions. 330 $aThis book follows the classical division of engineering mechanics as it is taught at technical colleges and universities and is dedicated to dynamics, i.e. the consideration of movements of bodies under forces. The aim of this book is to provide students with a clear introduction to dynamics and to enable them to formulate and solve engineering problems independently. The book provides a number of examples for this purpose. This book is aimed at students at technical colleges and universities of mechanical engineering, civil engineering, mechanics and all other degree programmes in which dynamics plays a role. Content Kinematics of the point mass ? Kinetics of the point mass ? Theorem of work and theorem of energy for the point mass ? Kinematics and kinetics of systems of point masses ? Motions of rigid bodies ? Impact processes ? Vibrations ? Principles of dynamics ? Relative motions The author Univ.-Prof. Dr.-Ing. habil. Christian Mittelstedt studied civil engineering at the University of Wuppertal, where he graduated in 1999. He was awarded his doctorate in 2005 at the University of Siegen with a dissertation on stress concentration problems in composite laminates. From 2006 he worked in the German aerospace industry as a research engineer and from 2011 as a technical leader and expert in the field of structural analysis. He habilitated in 2012 with a thesis on the stability of thin-walled composite panels in lightweight engineering and is the author and co-author of more than 200 scientific papers that have been published in international journals, conference proceedings and officially recognised calculation manuals. He is the author of numerous textbooks. Since August 2016, he is the head of the institute for Lightweight Engineering and Structural Mechanics department at the Faculty of Mechanical Engineering at the Technical University of Darmstadt, Germany. 606 $aMechanics, Applied 606 $aMechanics 606 $aContinuum mechanics 606 $aStatics 606 $aEngineering Mechanics 606 $aClassical Mechanics 606 $aContinuum Mechanics 606 $aMechanical Statics and Structures 615 0$aMechanics, Applied. 615 0$aMechanics. 615 0$aContinuum mechanics. 615 0$aStatics. 615 14$aEngineering Mechanics. 615 24$aClassical Mechanics. 615 24$aContinuum Mechanics. 615 24$aMechanical Statics and Structures. 676 $a620.1 700 $aMittelstedt$b Christian$0971547 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910983482303321 996 $aEngineering Mechanics 3: Dynamics$94316906 997 $aUNINA LEADER 03075nam 22004933 450 001 9910984669403321 005 20230918084512.0 010 $a9789815136982 010 $a9815136984 035 $a(CKB)28153922900041 035 $a(MiAaPQ)EBC30745091 035 $a(Au-PeEL)EBL30745091 035 $a(Exl-AI)30745091 035 $a(OCoLC)1399170449 035 $a(EXLCZ)9928153922900041 100 $a20230918d2023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aNumerical Machine Learning 205 $a1st ed. 210 1$aSharjah :$cBentham Science Publishers,$d2023. 210 4$dİ2023. 215 $a1 online resource (225 pages) 311 08$a9789815136999 311 08$a9815136992 327 $aCover -- Title -- Copyright -- End User License Agreement -- Content -- Preface -- Introduction to Machine Learning -- Linear Regression -- Regularization -- Logistic Regression -- Decision Tree -- Gradient Boosting -- Support Vector Machine -- K-means Clustering -- Subject Index $7Generated by AI. 330 $aNumerical Machine Learning is a simple textbook on machine learning that bridges the gap between mathematics theory and practice. The book uses numerical examples with small datasets and simple Python codes to provide a complete walkthrough of the underlying mathematical steps of seven commonly used machine learning algorithms and techniques, including linear regression, regularization, logistic regression, decision trees, gradient boosting, Support Vector Machine, and K-means Clustering. Through a step-by-step exploration of concrete numerical examples, the students (primarily undergraduate and graduate students studying machine learning) can develop a well-rounded understanding of these algorithms, gain an in-depth knowledge of how the mathematics relates to the implementation and performance of the algorithms, and be better equipped to apply them to practical problems. Key features - Provides a concise introduction to numerical concepts in machine learning in simple terms - Explains the 7 basic mathematical techniques used in machine learning problems, with over 60 illustrations and tables - Focuses on numerical examples while using small datasets for easy learning - Includes simple Python codes - Includes bibliographic references for advanced reading The text is essential for college and university-level students who are required to understand the fundamentals of machine learning in their courses. 606 $aMachine learning$7Generated by AI 606 $aNumerical analysis$7Generated by AI 615 0$aMachine learning 615 0$aNumerical analysis 700 $aWang$b Zhiyuan$0654347 701 $aIrfan$b Sayed Ameenuddin$01793401 701 $aTeoh$b Christopher$01793402 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910984669403321 996 $aNumerical Machine Learning$94333097 997 $aUNINA LEADER 03005oam 2200301z- 450 001 9911006966103321 005 20180925092634.0 010 $a1-56080-350-9 010 $a1-5231-1611-0 035 $a(CKB)4100000006674032 035 $a(EXLCZ)994100000006674032 100 $a20190311c2017uuuu -u- - 101 0 $aeng 200 10$aHigh-resolution seismic exploration /$fQing-Zhong Li ; Wei Liu, managing editor ; Jeff Mestayer and Timothy Baker, volume editors ; Hua-Wei Zhou, translation team leader 210 $cSEG (Society of Exploration Geophysicists) 311 $a1-56080-349-5 327 $aIntroduction -- Basic concepts of resolution and signal-to-noise ratio -- Subsurface attenuation of high-frequency signals and the empirical Vp-Q relation -- Recording range of seismometers for high-frequency signals -- The characteristics of high-frequency noise and methods to reduce it in field acquisition -- Static corrections and normal moveout -- The importance of proper deconvolution -- Dip-moveout correction, migration and trace interpolation -- Ways to improve signal-to-noise ratio -- Interpretation of high-resolution seismic profiles -- Challenges and improvements in impedance -- Additional seismic invrsion methods -- Processing principles and reference flow for high-resolution seismic data -- Future perspectives -- Progress and prospects of high-resolution sesimic exploration in the new century -- Summary cards. 330 $aCapitalizing on knowledge learned over decades and combining underlying theory with practical cases, this book presents a systematic analysis of the issues involved in high-resolution seismic exploration. Translated from the original Chinese edition published in 1993 by Petroleum Industry Press and now updated to reflect contemporary developments, the book is adept at clarifying the objectives and approaches toward better precision in seismic prospecting. It provides innovative views on fundamental concepts including: perspective resolution and perspective S/N; the empirical relationship between compressional velocity (Vp) and absorption coefficient (Q); constructing basin absorption models; understanding sand layer tracking; improving dynamic and static corrections of near-surface effects as well as deconvolution; achieving maximum effective bandwidth of seismic data; and regressive seismic impedance inversion. It is an excellent reference for those involved in seismic prospecting research, data processing, and geologic interpretation, and it is recommended for geoscientists and engineers as well as professors and graduate students.--$cSource other than Library of Congress. 606 $aSeismic prospecting 606 $aSeismic prospecting$2fast$3(OCoLC)fst01111259 615 0$aSeismic prospecting. 615 7$aSeismic prospecting. 676 $a622/.1592 700 $aLi$b Qing-Zhong$01823595 906 $aBOOK 912 $a9911006966103321 996 $aHigh-resolution seismic exploration$94390335 997 $aUNINA