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 Zhang, Zhengyou.
 Berlin, Heidelberg : Springer Berlin Heidelberg, 1992.
 Description
 Book — 1 online resource (xi, 300 pages)
 Summary

 1. Introduction. 1.1 Brief Overview of Motion Analysis. 1.2 Statement of the "Motion from Stereo" Problem. 1.3 Organization of The Book.
 2. Uncertainty Manipulation and Parameter Estimation. 2.1 Probability Theory and Geometric Probability. 2.2 Parameter Estimation. 2.2.1 Standard Kalman filter. 2.2.2 Extended Kalman filter. 2.2.3 Discussion. 2.2.4 Iterated ExtendKalman Filter. 2.2.5 Robustness and Confidence Procedure. 2.3 Summary. 2.4 Appendix: LeastSquares Techniques.
 3. Reconstruction of 3D Line Segments. 3.1 Why 3D Line Segments. 3.2 Stereo Calibration. 3.2.1 Camera Calibration. 3.2.2 Epipolar Constraint. 3.3 Algorithm of the Trinocular Stereovision. 3.4 Reconstruction of 3D Segments. 3.5 Summary.
 4. Representations of Geometric Objects. 4.1 Rigid Motion. 4.1.1 Definition. 4.1.2 Representations. 4.2 3D Line Segments. 4.2.1 Previous Representations and Deficiencies. 4.2.2 A New Representation. 4.3 Summary. 4.4 Appendix: Visualizing Uncertainty.
 5. A Comparative Study of 3D Motion Estimation. 5.1 Problem Statement. 5.1.1 Line Segment Representations. 5.1.2 3D Line Segment Transformation. 5.2 Extended Kalman Filter Approaches. 5.2.1 Linearization of the Equations. 5.2.2 Derivation of Rotation Matrix. 5.3 Minimization Techniques. 5.4 Analytical Solution. 5.4.1 Determining the Rotation. 5.4.2 Determining the Translation. 5.5 Kim and Aggarwal's method. 5.5.1 Determining the Rotation. 5.5.2 Determining the Translation. 5.6 Experimental Results. 5.6.1 Results with Synthetic Data. 5.6.2 Results with Real Data. 5.7 Summary. 5.8 Appendix: Motion putation Using the New Line Segment Representation.
 6. Matching and Rigidity Constraints. 6.1 Matching as a Search. 6.2 Rigidity Constraint. 6.3 Completeness of the Rigidity Constraints. 6.4 Error Measurements inn the Constraints. 6.4.1 Norm Constraint. 6.4.2 DotProduct Constraint. 6.4.3 TripleProduct Constraint. 6.5 Other Formalisms Rigidity Constraints. 6.6 Summary.
 7. HypothesizeandVerify Method for Two 3D View Motion Analysis. 7.1 General Presentation. 7.1.1 Search in the Transformation Space. 7.1.2 HypothesizeandVerify Method. 7.2 Generating Hypotheses. 7.2.1 Definition and Primary Algorithm. 7.2.2 Control Strates in Hypothesis Generation. 7.2.3 Additional Constraints. 7.2.4 Algorithm of Hypothesis Generation. 7.3 Verifying Hypothesis. 7.3.1 Estimating the Initial Rigid Motion. 7.3.2 Propagating Hyphoteses. 7.3.3 Choosing the Best Hypothesis. 7.3.4 Algorithm of Hypothesis Verification. 7.4 Matching Noisy Segments. 7.4.1 Version 1. 7.4.2 Version 2. 7.4.3 Version 3. 7.5 Experimental Results. 7.5.1 Indoor Scenes with a Large Common Part. 7.5.2 Indoor Scenes with a Small Common Part. 7.5.3 Rock Scenes. 7.6 Summary. 7.7 Appendix: Transforming a 3D Line Segment.
 8. Further Considerations on Reducing Complexity. 8.1 Sorting Data Features. 8.2 "GoodEnough" Problem. 1.3 Organization of The Book.
 2. Uncertainty Manipulation and Parameter Estimation. 2.1 Probability Theory and Geometric Probability. 2.2 Parameter Estimation. 2.2.1 Standard Kalman filter. 2.2.2 Extended Kalman filter. 2.2.3 Discussion. 2.2.4 Iterated ExtendKalman Filter. 2.2.5 Robustness and Confidence Procedure. 2.3 Summary. 2.4 Appendix: LeastSquares Techniques.
 3. Reconstruction of 3D Line Segments. 3.1 Why 3D Line Segments. 3.2 Stereo Calibration. 3.2.1 Camera Calibration. 3.2.2 Epipolar Constraint. 3.3 Algorithm of the Trinocular Stereovision. 3.4 Reconstruction of 3D Segments. 3.5 Summary.
 4. Representations of Geometric Objects. 4.1 Rigid Motion. 4.1.1 Definition. 4.1.2 Representations. 4.2 3D Line Segments. 4.2.1 Previous Representations and Deficiencies. 4.2.2 A New Representation. 4.3 Summary. 4.4 Appendix: Visualizing Uncertainty.
 5. A Comparative Study of 3D Motion Estimation. 5.1 Problem Statement. 5.1.1 Line Segment Representations. 5.1.2 3D Line Segment Transformation. 5.2 Extended Kalman Filter Approaches. 5.2.1 Linearization of the Equations. 5.2.2 Derivation of Rotation Matrix. 5.3 Minimization Techniques. 5.4 Analytical Solution. 5.4.1 Determining the Rotation. 5.4.2 Determining the Translation. 5.5 Kim and Aggarwal's method. 5.5.1 Determining the Rotation. 5.5.2 Determining the Translation. 5.6 Experimental Results. 5.6.1 Results with Synthetic Data. 5.6.2 Results with Real Data. 5.7 Summary. 5.8 Appendix: Motion putation Using the New Line Segment Representation.
 6. Matching and Rigidity Constraints. 6.1 Matching as a Search. 6.2 Rigidity Constraint. 6.3 Completeness of the Rigidity Constraints. 6.4 Error Measurements inn the Constraints. 6.4.1 Norm Constraint. 6.4.2 DotProduct Constraint. 6.4.3 TripleProduct Constraint. 6.5 Other Formalisms Rigidity Constraints. 6.6 Summary.
 7. HypothesizeandVerify Method for Two 3D View Motion Analysis. 7.1 General Presentation. 7.1.1 Search in the Transformation Space. 7.1.2 HypothesizeandVerify Method. 7.2 Generating Hypotheses. 7.2.1 Definition and Primary Algorithm. 7.2.2 Control Strates in Hypothesis Generation. 7.2.3 Additional Constraints. 7.2.4 Algorithm of Hypothesis Generation. 7.3 Verifying Hypothesis. 7.3.1 Estimating the Initial Rigid Motion. 7.3.2 Propagating Hyphoteses. 7.3.3 Choosing the Best Hypothesis. 7.3.4 Algorithm of Hypothesis Verification. 7.4 Matching Noisy Segments. 7.4.1 Version 1. 7.4.2 Version 2. 7.4.3 Version 3. 7.5 Experimental Results. 7.5.1 Indoor Scenes with a Large Common Part. 7.5.2 Indoor Scenes with a Small Common Part. 7.5.3 Rock Scenes. 7.6 Summary. 7.7 Appendix: Transforming a 3D Line Segment.
 8. Further Considerations on Reducing Complexity. 8.1 Sorting Data Features. 8.2 "GoodEnough" Method. 8.3 Speeding Up the Hypothesis Generation Process Through Grouping. 8.4 Finding Clusters Based on Proximity. 8.5 Finding Planes. 8.6 Experimental Results. 8.6.1 Grouping Results. 8.6.2 Motion Results. 8.7 Conclusion.
 9. Multiple Object Motions. 9.1 Multiple Object Motions. 9.2 Influence of Egomotion on Observed Object Motion. 9.3 Experimental Results. 9.3.1 Real Scene with Synthetic Moving Objects. 9.3.2 Real Scene with a Real Moving Object. 9.4 Summary.
 10. Object Recognition and Localization. 10.1 ModelBased Object Recognition. 10.2 Adapting the MotionDetermination Algorithm. 10.3 Experimental Result. 10.4 Summary.
 11. Calibrating a Mobile Robot and Visual Navigation. 11.1 The INRIA Mobile Robot. 11.2 Calibration Problem. 11.3 Navigation Problem. 11.4 Experimental Results. 11.5 Integrating Motion Information from Odometry. 11.6 Summary.
 12. Fusing Multiple 3D Frames. 12.1 System Description. 12.2 Fusing Segments from Multiple Views. 12.2.1 Fusing General Primitives. 12.2.2 Fusing Line Segments. 12.2.3 Example. 12.2.4 Summary of the Fusion Algorithm. 12.3 Experimental Results. 12.3.1 Example
 1: Integration of Two Views. 12.3.2 Example
 2: Integration of a Long Sequence. 12.4 Summary.
 13. Solving the Motion Tracking Problem: A Framework. 13.1 Previous Work. 13.2 Position of the Problem and Primary Ideas. 13.3 Solving the Motion Tracking Problem: A Framework. 13.3.1 Outline of the Framework. 13.3.2 A Pedagogical Example. 13.4 Splitting or Merging. 13.5 Handling Abrupt Changes of Motion. 13.6 Discussion. 13.7 Summary.
 14. Modeling and Estimating Motion Kinematics. 14.1 The Classical Kinematic Model. 14.2 ClosedForm Solutions for Some Special Motions. 14.2.1 Motion with Constant Angular and Translational Velocities. 14.2.2 Motion with Constant Angular Velocity and Constant Translational Acceleration. 14.2.3 Motion with Constant Angular Velocity and General Translational Velocity. 14.2.4 Discussions. 14.3 Relation with TwoView Motion Analysis. 14.4 Formulation for the EKF Approach. 14.4.1 State Transition Equation. 14.4.2 Measurement Equations. 14.5 Linearized Kinematic Model. 14.5.1 Linear Approximation. 14.5.2 State Transition Equation. 14.5.3 Measurement Equations. 14.5.4 Discussions. 14.6 Summary.
 15. Implementation Details and Experimental Results. 15.1 Matching Segments. 15.1.1 Prediction of a Token. 15.1.2 Matching Criterion. 15.1.3 Reducing the Complexity by Bucketing Techniques. 15.2 Support of Existence. 15.3 Algorithm of the Token Tracking Process. 15.4 Grouping Tokens into Objects. 15.5 Experimental Results. 15.5.1 Synthetic Data. 15.5.2 Real Data with Controlled Motion. 15.5.3 Real Data with Uncontrolled Motion. 15.6 Summary.
 16. Conclusions and Perspectives. 16.1 Summary. 16.2 Perspectives. Appendix: Vector Manipulation and Differentiation. A.1 Manipulation of Vectors. A.2 Differentiation of Vectors. References.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
2. Acta polytechnica Scandinavica. Physics including nucleonics series [1958  1975]
 Helsinki Finnish Academy of Technical Sciences
 Description
 Book — 110 no. illustrations 26 cm
 Online
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QC1 .A362 NO.1436 19611965  Available 
QC1 .A362 NO.3749 19661967  Available 
QC1 .A362 NO.5062 1968  Available 
QC1 .A362 NO.6385 19691971  Available 
QC1 .A362 NO.86110 19721975  Available 
3. AIP Scitation [electronic resource]. [1996 ]
 Melville, NY : American Institute of Physics, 1996
 Database topics
 Chemistry and Chemical Engineering; Physics and Astronomy
 Summary

Provides fulltext access to journals published and distributed by the American Institute of Physics, American Physical Society, American Society of Civil Engineers, American Society of Mechanical Engineers International, International Society for Optical Engineering, and other science and engineering societies. Covers physics, astronomy, electronics, engineering, materials science, mathematics and associated disciplines.
4. American Institute of Physics handbook [1957]
 American Institute of Physics.
 New York, McGrawHill, 1957.
 Description
 Book — 1 v. (various pagings) illus., diagrs., tables. 24 cm.
 Online
Earth Sciences Library (Branner), SAL3 (offcampus storage)
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530.8 .A512  Available 
QC61 .A5 1957  Available 
QC61 .A5 1957  Available 
 Burman, I͡A.
 Moskva : Uaĭli, 1995.
 Description
 Book — xii, 658 p. ; 25 cm.
 Online
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T10 .B87 1995  Available 
 Pipes, Louis A. (Louis Albert), 19101971
 3d ed.  New York, McGrawHill [1970]
 Description
 Book — xxii, 1015 p. illus. 23 cm.
 Online
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QA401 .P5 1970  Available 
7. Applied parallel computing [1995 ]
 PARA.
 Berlin ; New York : SpringerVerlag, c1995
 Description
 Journal/Periodical — v. : ill. ; 24 cm.
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QA76.58 .P35 2ND 1995  Available 
QA76.58 .P35 3RD 1996  Available 
QA76.58 .P35 4TH 1998  Available 
 PARA '95 (1995 : Lyngby, Denmark)
 Berlin ; New York : Springer, 1996.
 Description
 Book — 1 online resource (562 pages) : illustrations
 Summary

 A high performance matrix multiplication algorithm for MPPs. Iterative moment method for electromagnetic transients in grounding systems on CRAY T3D. Analysis of crystalline solids by means of a parallel FEM method. Parallelization strategies for Tree Nbody codes. Numerical solution of stochastic differential equations on transputer network. Development of a stencil compiler for onedimensional convolution operators on the CM5. Automatic parallelization of the AVL FIRE benchmark for a distributedmemory system. 2D cellular automata and short range molecular dynamics programs for simulations on networked workstations and parallel computers. Pablobased performance monitoring tool for PVM applications. Linear algebra computation on parallel machines. A neural classifier for radar images. ScaLAPACK: A portable linear algebra library for distributed memory computers  Design issues and performance. A proposal for a set of parallel basic linear algebra subprograms. Parallel implementation of a Lagrangian stochastic particle model of turbulent dispersion in fluids. Reduction of a regular matrix pair (A, B) to block Hessenbergtriangular form. Parallelization of algorithms for neural networks. Paradigms for the parallelization of Branch&Bound algorithms. Threedimensional version of the Danish Eulerian Model. A proposal for a Fortran 90 interface for LAPACK. ScaLAPACK tutorial. Highly parallel concentrated heterogeneous computing. Adaptive polynomial preconditioning for the conjugate gradient algorithm. The IBM parallel engineering and scientific subroutine library. Some preliminary experiences with sparse BLAS in parallel iterative solvers. Load balancing in a Network Flow Optimization code. Userlevel VSM optimization and its application. Benchmarking the cache memory effect. Efficient Jacobi algorithms on multicomputers. Front tracking: A parallelized approach for internal boundaries and interfaces. Program generation techniques for the development and maintenance of numerical weather forecast Grid models. High performance computational chemistry: NWChem and fully distributed parallel applications. Parallel abinitio molecular dynamics. Dynamic domain decomposition and load balancing for parallel simulations of longchained molecules. Concurrency in feature analysis. A parallel iterative solver for almost blockdiagonal linear systems. Distributed general matrix multiply and add for a 2D mesh processor network. Distributed and parallel computing of shortrange molecular dynamics. Lattice field theory in a parallel environment. Parallel time independent quantum calculations of atom diatom reactivity. Parallel oil reservoir simulation. Formal specification of multicomputers. Multimillion particle molecular dynamics on MPPs. Wave propagation in urban microcells: a massively parallel approach using the TLM method. The NAG Numerical PVM Library. Cellular automata modeling of snow transport by wind. Parallel algorithm for mapping of parallel programs into pyramidal multiprocessor. Dataparallel molecular dynamics with neighborlists. Visualizing astrophysical 3D MHD turbulence. A parallel sparse QRfactorization algorithm. Decomposing linear programs for parallel solution. A parallel computation of the NavierStokes equation for the simulation of free surface flows with the volume of fluid method. Improving the performance of parallel triangularization of a sparse matrix using a reconfigurable multicomputer. Comparison of two imagespace subdivision algorithms for Direct Volume Rendering on distributedmemory multicomputers. Communication harnesses for transputer systems with tree structure and cube structure. A thorough investigation of the projector quantum Monte Carlo method using MPP technologies. Distributed simulation of a set of elastic macro objects. Parallelization of ab initio molecular dynamics method. Parallel computations with large atmospheric models.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Camejo, Silvia Arroyo.
 Milano : SpringerVerlag Italia, 2008.
 Description
 Book
10. Cardinalities of Fuzzy Sets [2003]
 Wygralak, Maciej.
 Berlin, Heidelberg : Springer Berlin Heidelberg, 2003.
 Description
 Book — 1 online resource (xiv, 196 pages) Digital: text file; PDF.
 Summary

 1. Triangular Operations and Negations (Allegro). 1
 .1. Triangular Norms and Conorms. 1
 .2. Negations. 1
 .3. Associated Triangular Operations. 1
 .4. Archimedean Triangular Operations. 1
 .5. Induced Negations and Complementary Triangular Operations. 1
 .6. Implications Induced by Triangular Norms.
 2. Fuzzy Sets (Andante spianato). 2
 .1. The Concept of a Fuzzy Set. 2
 .2. Operations on Fuzzy Sets. 2
 .3. Generalized Operations. 2
 .4. Other Elements of the Language of Fuzzy Sets. 2
 .5. Towards Cardinalities of Fuzzy Sets.
 3. Scalar Cardinalities of Fuzzy Sets (Scherzo). 3
 .1. An Axiomatic Viewpoint. 3
 .2. Cardinality Patterns. 3
 .3. Valuation Property and Subadditivity. 3
 .4. Cartesian Product Rule and Complementarity. 3
 .5. On the Fulfilment of a Group of the Properties. 3.5
 .1. VAL and CART. 3.5
 .2. CART and COMP. 3.5
 .3. VAL and COMP. 3.5
 .4. VAL, CART and COMP.
 4. Generalized Cardinals with Triangular Norms (Rondeau a la polonaise). 4
 .1. Generalized FGCounts. 4.1
 .1. The Corresponding Equipotency Relation. 4.1
 .2. Inequalities. 4.1
 .3. Arithmetical Operations. 4.1.3
 .1. Addition. 4.1.3
 .2. Subtraction. 4.1.3
 .3. Multiplication. 4.1.3
 .4. Division. 4.1.3
 .5. Exponentiation. 4.1
 .4. Some Derivative Concepts of Cardinality. 4
 .2. Generalized FLCounts. 4.2
 .1. Equipotencies and Inequalities. 4.2
 .2. Addition and Other Arithmetical Operations. 4
 .3. Generalized FECounts. 4.3
 .1. The Height of a Generalized FECount. 4.3
 .2. Singular Fuzzy Sets. 4.3
 .3. Equipotencies, Inequalities and Arithmetical Questions. List of Symbols.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Lehto, Jukka.
 Weinheim : WileyVCH, 2010.
 Description
 Book — 1 online resource (xix, 402 p.) : ill.
 Summary

 Preface. Acknowledgments. 1 Radionuclides and their Radiometric Measurement. 1.1 Radionuclides. 1.2 Modes of Radioactive Decay. 1.3 Detection and Measurement of Radiation. 2 Special Features of the Chemistry of Radionuclides and their Separation. 2.1 Small Quantities. 2.2 Adsorption. 2.3 Use of Carriers. 2.4 Utilization of Radiation in the Determination of Radionuclides. 2.5 Consideration of Elapsed Time. 2.6 Changes in the System Caused by Radiation and Decay. 2.7 The Need for Radiochemical Separations. 3 Factors Affecting Chemical Forms of Radionuclides in Aqueous Solutions. 3.1 Solution pH. 3.2 Redox Potential. 3.3 Dissolved Gases. 3.4 Ligands Forming Complexes with Metals. 3.5 Humic Substances. 3.6 Colloidal Particles. 3.7 Source and Generation of Radionuclides. 3.8 Appendix: Reagents Used to Adjust Oxidation States of Radionuclides. 4 Separation Methods. 4.1 Precipitation. 4.2 Solubility Product. 4.3 Ion Exchange. 4.4 Solvent Extraction. 4.5 Extraction Chromatography. 5 Yield Determinations and Counting Source Preparation. 5.1 The Determination of Chemical Yield in Radiochemical Analyses. 5.2 Preparation of Sources for Activity Counting. 5.3 Essentials in Chemical Yield Determination and in Counting Source Preparation. 6 Radiochemistry of the Alkali Metals. 6.1 Most Important Radionuclides of the Alkali Metals. 6.2 Chemical Properties of the Alkali Metals. 6.3 Separation Needs of Alkali Metal Radionuclides. 6.4 Potassium 40K. 6.5 Cesium 134Cs, 135Cs, and 137Cs. 6.6 Essentials in the Radiochemistry of the Alkali Metals. 7 Radiochemistry of the Alkaline Earth Metals. 7.1 Most Important Radionuclides of the Alkaline Earth Metals. 7.2 Chemical Properties of the Alkaline Earth Metals. 7.3 Beryllium 7Be and 10Be. 7.4 Calcium 41Ca and 45Ca. 7.5 Strontium 89Sr and 90Sr. 7.6 Radium 226Ra and 228Ra. 7.7 Essentials in the Radiochemistry of the Alkaline Earth Metals. 8 Radiochemistry of the 3dTransition Metals. 8.1 The Most Important Radionuclides of the 3dTransition Metals. 8.2 Chemical Properties of the 3dTransition Metals. 8.3 Iron 55Fe. 8.4 Nickel 59Ni and 63Ni. 8.5 Essentials in 3d Transition Metals Radiochemistry. 9 Radiochemistry of the 4dTransition Metals. 9.1 Important Radionuclides of the 4dTransition Metals. 9.2 Chemistry of the 4dTransition Metals. 9.3 Technetium 99Tc. 9.4 Zirconium 93Zr. 9.5 Molybdenum 93Mo. 9.6 Niobium 94Nb. 9.7 Essentials in the Radiochemistry of 4d Transition Metals. 10 Radiochemistry of the Lanthanides. 10.1 Important Lanthanide Radionuclides. 10.2 Chemical Properties of the Lanthanides. 10.3 Separation of Lanthanides from Actinides. 10.4 Lanthanides as Actinide Analogs. 10.5 147Pm and 151Sm. 10.6 Essentials of Lanthanide Radiochemistry. 11 Radiochemistry of the Halogens. 11.1 Important Halogen Radionuclides. 11.2 Physical and Chemical Properties of the Halogens. 11.3 Chlorine 36Cl. 11.4 Iodine 129I. 11.5 Essentials of Halogen Radiochemistry. 12 Radiochemistry of the Noble Gases. 12.1 Important Radionuclides of the Noble Gases. 12.2 Physical and Chemical Characteristics of the Noble Gases. 12.3 Measurement of Xe Isotopes in Air. 12.4 Determination of 85Kr in Air. 12.5 Radon and its Determination. 12.6 Essentials of Noble Gas Radiochemistry. 13 Radiochemistry of Tritium and Radiocarbon. 13.1 Tritium 3H. 13.2 Radiocarbon 14C. 13.3 Essentials of Tritium and Radiocarbon Radiochemistry. 14 Radiochemistry of Lead, Polonium, Tin, and Selenium. 14.1 Polonium 210Po. 14.2 Lead 210Pb. 14.3 Tin 126Sn. 14.4 Selenium 79Se. 14.5 Essentials of Polonium, Lead, Tin, and Selenium Radiochemistry. 15 Radiochemistry of the Actinides. 15.1 Important Actinide Isotopes. 15.2 Generation and Origin of the Actinides. 15.3 Electronic Structures of the Actinides. 15.4 Oxidation States of the Actinides. 15.5 Ionic Radii of the Actinides. 15.6 Major Chemical Forms of the Actinides. 15.7 Disproportionation. 15.8 Hydrolysis and Polymerization of the Actinides. 15.9 Complex Formation of the Actinides. 15.10 Oxides of the Actinides. 15.11 Actinium. 15.12 Thorium. 15.13 Protactinium. 15.14 Uranium. 15.15 Neptunium. 15.16 Plutonium. 15.17 Americium and Curium. 16 Speciation Analysis. 16.1 Considerations Relevant to Speciation. 16.2 Significance of Speciation. 16.3 Categorization of Speciation Analyzes. 16.4 Fractionation Techniques for Environmental Samples. 16.5 Analysis of Radionuclide and Isotope Compositions. 16.6 Spectroscopic Speciation Methods. 16.7 Wet Chemical Methods. 16.8 Sequential Extractions. 16.9 Computational Speciation Methods. 16.10 Characterization of Radioactive Particles. 17 Measurement of Radionuclides by Mass Spectrometry. 17.1 Introduction. 17.2 Inductively Coupled Plasma Mass Spectrometry (ICPMS). 17.3 Accelerator Mass Spectrometry (AMS). 17.4 Thermal Ionization Mass Spectrometry (TIMS). 17.5 Resonance Ionization Mass Spectrometry (RIMS). 17.6 Essentials of the Measurement of Radionuclides by Mass Spectrometry. 18 Sampling and Sample Pretreatment for the Determination of Radionuclides. 18.1 Introduction. 18.2 Air Sampling and Pretreatment. 18.3 Sampling Gaseous Components. 18.4 Atmospheric Deposition Sampling. 18.5 Water Sampling. 18.6 Sediment Sampling and Pretreatment. 18.7 Soil Sampling and Pretreatment. 18.8 Essentials in Sampling and Sample Pretreatment for Radionuclides. 19 Chemical Changes Induced by Radioactive Decay. 19.1 Autoradiolysis. 19.2 Transmutation and Subsequent Chemical Changes. 19.3 Recoil Hot Atom Chemistry. Index.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Online

 dx.doi.org Wiley Online Library
 Google Books (Full view)
 Cham : Springer, 2015.
 Description
 Book — 1 online resource Digital: text file; PDF.
 Summary

 Design and Modeling of Anti Wind Up PID Controllers. A Hybrid Global Optimization Algorithm: Particle Swarm Optimization in Association with a Genetic Algorithm. Towards Robust Performance Guarantees for Models Learned from HighDimensional Data. ExpertBased Method of Integrated Waste Management Systems for Developing Fuzzy Cognitive Map. Leukocyte Detection through an Evolutionary Method. PWARX model identification based on clustering approach. Supplier quality evaluation using a fuzzy multi criteria decision making approach. Concept Trees: Building Dynamic Concepts from SemiStructured Data using NatureInspired Methods. Swarm Intelligence Techniques and Their Adaptive Nature with Applications. Signal Based Fault Detection and Diagnosis for rotating electrical machines: Issues and Solutions. Modelling Of Intrusion Detection System Using Artificial Intelligence Evaluation Of Performance Measures. Enhanced Power System Security Assessment through Intelligent Decision Trees. Classification of Normal and Epileptic Seizure EEG Signals based on Empirical Mode Decomposition. A Rough Set Based Total Quality Management Approach in Higher Education. Iterative Dual Rational Krylov and Iterative SVDDual Rational Krylov Model Reduction for Switched Linear Systems. Household Electrical Consumption Modeling through Fuzzy Logic Approach. Modeling, Identification and Control of irrigation station with sprinkling: Takagi Sugeno approach. Review and Improvement of Several Optimal Intelligent Pitch Controllers and Estimator of WECS via Artificial Intelligent Approaches. Secondary and Tertiary Structure Prediction of Proteins: A Bioinformatic Approach. Approximation of Optimized Fuzzy Logic Controller for Shunt Active Power Filter.Soft Computing Techniques For Optimal Capacitor Placement. Advanced Metaheuristicsbased Approach for Fuzzy Control Systems Tuning. Robust Estimation Design for Unknown Inputs Fuzzy Bilinear Models: Application to Faults Diagnosis. Unit Commitment Optimization Using GradientGenetic algorithm and Fuzzy logic approaches. Impact of Hardware/Software Partitioning and MicroBlaze FPGA Configurations on the Embedded Systems Performances. A Neural Approach to Cursive Handwritten Character Recognition using Features Extracted from Binarization Technique. System Identification Technique and Neural Networks for Material Lifetime Assessment Application. Measuring Software Reliability: A Trend using Machine Learning Techniques. Hybrid Metaheuristic Approach for Scheduling of Aperiodic OS Tasks.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Enns, Richard H.
 New York, NY : Springer New York, 2001.
 Description
 Book — 1 online resource (xiv, 778 pages)
 Summary

Computer algebra systems allow students to work on mathematical models more efficiently than in the case of pencil and paper. The use of such systems also leads to fewer errors and enables students to work on complex and computationally intensive models. Aimed at undergraduates in their second or third year, this book is filled with examples from a wide variety of disciplines, including biology, economics, medicine, engineering, game theory, physics, and chemistry. The text includes a large number of Maple(R) recipes.
(source: Nielsen Book Data)
 Steinhauser, M. O. (Martin Oliver), author.
 Berlin : Walter de Gruyter GmbH & Co. KG, 2013.
 Description
 Book — 1 online resource (xix, 508 pages) : illustrations
 Summary

 Preface
 1. Introduction to Computer Simulation 1.1 Historical Background 1.2 Theory, Modeling and Simulation in Physics 1.3 Reductionism in Physics 1.4 Basics of Ordinary and Partial Differential Equations in Physics 1.5 Numerical Solution of Differential Equations: MeshBased vs. Particle Methods 1.6 The Role of Algorithms in Scientific Computing 1.7 Remarks on Software Design 1.8 Summary
 2. Fundamentals of Statistical Physics 2.1 Introduction 2.2 Elementary Statistics 2.3 Introduction to Classical Statistical Mechanics 2.4 Introduction to Thermodynamics 2.5 Summary
 3. Inter and Intramolecular ShortRange Potentials 3.1 Introduction 3.2 Quantum Mechanical Basis of Intermolecular Interactions 3.2.1 Perturbation Theory 3.3 Classical Theories of Intermolecular Interactions 3.4 Potential Functions 3.5 Molecular Systems 3.6 Summary
 4. Molecular Dynamics Simulation 4.1 Introduction 4.2 Basic Ideas of MD 4.3 Algorithms for Calculating Trajectories 4.4 Link between MD and Quantum Mechanics 4.5 Basic MD Algorithm: Implementation Details 4.6 Boundary Conditions 4.7 The Cutoff Radius for ShortRange Potentials 4.8 Neighbor Lists: The LinkedCell Algorithm 4.9 The Method of Ghost Particles 4.10 Implementation Details of the Ghost Particle Method 4.11 Making Measurements 4.12 Ensembles and Thermostats 4.13 Case Study: Impact of Two Different Bodies 4.14 Case Study: RayleighTaylor Instability 4.15 Case Study: LiquidSolid Phase Transition of Argon
 5. Advanced MD Simulation 5.1 Introduction 5.2 Parallelization 5.3 More Complex Potentials and Molecules 5.4 Many Body Potentials 5.5 Coarse Grained MD for Mesoscopic Systems
 6. Outlook on Monte Carlo Simulations 6.1 Introduction 6.2 The Metropolis MonteCarlo Method 6.2.1 Calculation of Volumina and Surfaces 6.2.2 Percolation Theory 6.3 Basic MC Algorithm: Implementation Details 6.3.1 Case Study: The 2D Ising Magnet 6.3.2 Trial Moves and Pivot Moves 6.3.3 Case Study: Combined MD and MC for Equilibrating a Gaussian Chain 6.3.4 Case Study: MC of Hard Disks 6.3.5 Case Study: MC of Hard Disk Dumbbells in 2D 6.3.6 Case Study: Equation of State for the LennardJones Fluid 6.4 Rosenbluth and Rosenbluth Method 6.5 Bond Fluctuation Model 6.6 Monte Carlo Simulations in Different Ensembles 6.7 Random Numbers Are Hard to Find
 7. Applications from Soft Matter and Shock Wave Physics 7.1 Biomembranes 7.2 Scaling Properties of Polymers 7.3 Polymer Melts 7.4 Polymer Networks as a Model for the Cytoskeleton of Cells 7.5 Shock Wave Impact in Brittle Solids
 8. Concluding Remarks A Appendix A.1 Quantum Statistics of Ideal Gases A.2 MaxwellBoltzmann, BoseEinstein and FermiDirac Statistics A.3 Stirling's Formula A.4 Useful Integrals in Statistical Physics A.3 Useful Conventions for Implementing Simulation Programs A.4 Quicksort and Heapsort Algorithms A.4 Selected Solutions to Exercises Abbreviations Bibliography Index.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Online
 Steinhauser, M. O. (Martin Oliver), author.
 Berlin : Walter de Gruyter GmbH & Co. KG, 2013.
 Description
 Book — 1 online resource (xix, 508 pages) : illustrations
 Summary

 Preface
 1. Introduction to Computer Simulation 1.1 Historical Background 1.2 Theory, Modeling and Simulation in Physics 1.3 Reductionism in Physics 1.4 Basics of Ordinary and Partial Differential Equations in Physics 1.5 Numerical Solution of Differential Equations: MeshBased vs. Particle Methods 1.6 The Role of Algorithms in Scientific Computing 1.7 Remarks on Software Design 1.8 Summary
 2. Fundamentals of Statistical Physics 2.1 Introduction 2.2 Elementary Statistics 2.3 Introduction to Classical Statistical Mechanics 2.4 Introduction to Thermodynamics 2.5 Summary
 3. Inter and Intramolecular ShortRange Potentials 3.1 Introduction 3.2 Quantum Mechanical Basis of Intermolecular Interactions 3.2.1 Perturbation Theory 3.3 Classical Theories of Intermolecular Interactions 3.4 Potential Functions 3.5 Molecular Systems 3.6 Summary
 4. Molecular Dynamics Simulation 4.1 Introduction 4.2 Basic Ideas of MD 4.3 Algorithms for Calculating Trajectories 4.4 Link between MD and Quantum Mechanics 4.5 Basic MD Algorithm: Implementation Details 4.6 Boundary Conditions 4.7 The Cutoff Radius for ShortRange Potentials 4.8 Neighbor Lists: The LinkedCell Algorithm 4.9 The Method of Ghost Particles 4.10 Implementation Details of the Ghost Particle Method 4.11 Making Measurements 4.12 Ensembles and Thermostats 4.13 Case Study: Impact of Two Different Bodies 4.14 Case Study: RayleighTaylor Instability 4.15 Case Study: LiquidSolid Phase Transition of Argon
 5. Advanced MD Simulation 5.1 Introduction 5.2 Parallelization 5.3 More Complex Potentials and Molecules 5.4 Many Body Potentials 5.5 Coarse Grained MD for Mesoscopic Systems
 6. Outlook on Monte Carlo Simulations 6.1 Introduction 6.2 The Metropolis MonteCarlo Method 6.2.1 Calculation of Volumina and Surfaces 6.2.2 Percolation Theory 6.3 Basic MC Algorithm: Implementation Details 6.3.1 Case Study: The 2D Ising Magnet 6.3.2 Trial Moves and Pivot Moves 6.3.3 Case Study: Combined MD and MC for Equilibrating a Gaussian Chain 6.3.4 Case Study: MC of Hard Disks 6.3.5 Case Study: MC of Hard Disk Dumbbells in 2D 6.3.6 Case Study: Equation of State for the LennardJones Fluid 6.4 Rosenbluth and Rosenbluth Method 6.5 Bond Fluctuation Model 6.6 Monte Carlo Simulations in Different Ensembles 6.7 Random Numbers Are Hard to Find
 7. Applications from Soft Matter and Shock Wave Physics 7.1 Biomembranes 7.2 Scaling Properties of Polymers 7.3 Polymer Melts 7.4 Polymer Networks as a Model for the Cytoskeleton of Cells 7.5 Shock Wave Impact in Brittle Solids
 8. Concluding Remarks A Appendix A.1 Quantum Statistics of Ideal Gases A.2 MaxwellBoltzmann, BoseEinstein and FermiDirac Statistics A.3 Stirling's Formula A.4 Useful Integrals in Statistical Physics A.3 Useful Conventions for Implementing Simulation Programs A.4 Quicksort and Heapsort Algorithms A.4 Selected Solutions to Exercises Abbreviations Bibliography Index.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Steinhauser, M. O. (Martin Oliver)
 Berlin : Walter de Gruyter, [2012]
 Description
 Book — 1 online resource (xix, 508 pages) : illustrations.
 Summary

 Preface
 1. Introduction to Computer Simulation 1.1 Historical Background 1.2 Theory, Modeling and Simulation in Physics 1.3 Reductionism in Physics 1.4 Basics of Ordinary and Partial Differential Equations in Physics 1.5 Numerical Solution of Differential Equations: MeshBased vs. Particle Methods 1.6 The Role of Algorithms in Scientific Computing 1.7 Remarks on Software Design 1.8 Summary
 2. Fundamentals of Statistical Physics 2.1 Introduction 2.2 Elementary Statistics 2.3 Introduction to Classical Statistical Mechanics 2.4 Introduction to Thermodynamics 2.5 Summary
 3. Inter and Intramolecular ShortRange Potentials 3.1 Introduction 3.2 Quantum Mechanical Basis of Intermolecular Interactions 3.2.1 Perturbation Theory 3.3 Classical Theories of Intermolecular Interactions 3.4 Potential Functions 3.5 Molecular Systems 3.6 Summary
 4. Molecular Dynamics Simulation 4.1 Introduction 4.2 Basic Ideas of MD 4.3 Algorithms for Calculating Trajectories 4.4 Link between MD and Quantum Mechanics 4.5 Basic MD Algorithm: Implementation Details 4.6 Boundary Conditions 4.7 The Cutoff Radius for ShortRange Potentials 4.8 Neighbor Lists: The LinkedCell Algorithm 4.9 The Method of Ghost Particles 4.10 Implementation Details of the Ghost Particle Method 4.11 Making Measurements 4.12 Ensembles and Thermostats 4.13 Case Study: Impact of Two Different Bodies 4.14 Case Study: RayleighTaylor Instability 4.15 Case Study: LiquidSolid Phase Transition of Argon
 5. Advanced MD Simulation 5.1 Introduction 5.2 Parallelization 5.3 More Complex Potentials and Molecules 5.4 Many Body Potentials 5.5 Coarse Grained MD for Mesoscopic Systems
 6. Outlook on Monte Carlo Simulations 6.1 Introduction 6.2 The Metropolis MonteCarlo Method 6.2.1 Calculation of Volumina and Surfaces 6.2.2 Percolation Theory 6.3 Basic MC Algorithm: Implementation Details 6.3.1 Case Study: The 2D Ising Magnet 6.3.2 Trial Moves and Pivot Moves 6.3.3 Case Study: Combined MD and MC for Equilibrating a Gaussian Chain 6.3.4 Case Study: MC of Hard Disks 6.3.5 Case Study: MC of Hard Disk Dumbbells in 2D 6.3.6 Case Study: Equation of State for the LennardJones Fluid 6.4 Rosenbluth and Rosenbluth Method 6.5 Bond Fluctuation Model 6.6 Monte Carlo Simulations in Different Ensembles 6.7 Random Numbers Are Hard to Find
 7. Applications from Soft Matter and Shock Wave Physics 7.1 Biomembranes 7.2 Scaling Properties of Polymers 7.3 Polymer Melts 7.4 Polymer Networks as a Model for the Cytoskeleton of Cells 7.5 Shock Wave Impact in Brittle Solids
 8. Concluding Remarks A Appendix A.1 Quantum Statistics of Ideal Gases A.2 MaxwellBoltzmann, BoseEinstein and FermiDirac Statistics A.3 Stirling's Formula A.4 Useful Integrals in Statistical Physics A.3 Useful Conventions for Implementing Simulation Programs A.4 Quicksort and Heapsort Algorithms A.4 Selected Solutions to Exercises Abbreviations Bibliography Index.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
17. COMSOL for engineers [2014]
 Tabatabaian, Mehrzad.
 Dulles, VA : Mercury Learning and Information, ©2014.
 Description
 Book — 1 online resource
 Summary

 Cover page; Half title; LICENSE, DISCLAIMER OF LIABILITY, AND LIMITED WARRANTY; Title Page; Copyright; Dedication; CONTENTS; Preface;
 Chapter 1: Introduction;
 Chapter 2: Finite Element MethodA Summary; Overview; FEM Formulation; Matrix Approach; Example 2.1: Analysis of a 2D Truss; General Procedure for Global Matrix Assembly; Example 2.2: Global Matrix for Triangular Elements; Weighted Residual Approach; Galerkin Method; Shape Functions; Convergence and Stability; Example2.3: Heat Transfer in a Slender Steel Bar; Exercise Problems; References;
 Chapter 3: COMSOLA Modeling Tool for Engineers.
 OverviewCOMSOL Interface; COMSOL Modules; COMSOL Model Library and Tutorials; General Guidelines for Building a Model;
 Chapter 4: COMSOL Models for Physical Systems; Overview; Section 4.1: Static and Dynamic Analysis of Structures; Example 4.1: Stress Analysis for a Thin Plate Under Stationary Loads; Example 4.2: Dynamic Analysis for a Thin Plate: Eigenvalues and Modal Shapes; Example 4.3: Parametric Study for a Bracket Assembly: 3D Stress Analysis; Example 4.4: Buckling of a Column with Triangular Crosssection: Linearized Buckling Analysis.
 Example 4
 .5: Static and Dynamic Analysis for a 2D Bridgesupport TrussExample 4
 .6: Static and Dynamic Analysis for a 3D Truss Tower; Section 4
 .2: Dynamic Analysis and Models of Internal Flows: Laminar and Turbulent; Example 4
 .7: Axisymmetric Flow in a Nozzle: Simplified Waterjet; Example 4
 .8: Swirl Flow Around a Rotating Disk: Laminar Flow; Example 4
 .9: Swirl Flow Around a Rotating Disk: Turbulent Flow; Example 4
 .10: Flow in a Ushape Pipe with Square Crosssectional Area: Laminar Flow; Example 4
 .11: Doubledriven Cavity Flow: Moving Boundary Conditions.
 Example 4
 .12: Water Hammer Model: Transient Flow AnalysisExample 4
 .13: Static Fluid Mixer Model; Section 4
 .3: Modeling of Steady and Unsteady Heat Transfer in Media; Example 4
 .14: Heat Transfer in a Multilayer Sphere; Example 4
 .15: Heat Transfer in a Hexagonal Fin; Example 4
 .16: Transient Heat Transfer Through a Nonprismatic Fin with Convective Cooling; Example 4
 .17: Heat Conduction Through a Multilayer Wall with Contact Resistance; Section 4
 .4: Modeling of Electrical Circuits; Example 4
 .18: Modeling an RC Electrical Circuit; Example 4
 .19: Modeling an RLC Electrical Circuit.
 Section 4
 .5: Modeling Complex and Multiphysics ProblemsExample 4
 .20: Stress Analysis for an Orthotropic Thin Plate; Example 4
 .21: Thermal Stress Analysis and Transient Response of a Bracket; Example 4
 .22: Static Fluid Mixer with Flexible Baffles; Example 4
 .23: Double Pendulum: Multibody Dynamics; Example 4
 .24: Multiphysics Model for Thermoelectric Modules; Example 4
 .25: Acoustic Pressure Wave Propagation in an Automotive Muffler; Exercise Problems; References; Suggested Further Readings; Trademark References; Index.
18. COMSOL for engineers [2014]
 Tabatabaian, Mehrzad.
 Dulles, VA : Mercury Learning and Information, ©2014.
 Description
 Book — 1 online resource
 Summary

 1: Introduction.
 2: Finite Element Method (FEM)A Summary.
 3: COMSOL  A Modeling Tool For Engineers.
 4: Modeling SinglePhysics Problems.
 5: Modeling MultiPhysics Problems.
 6: Modeling Energy Systems With COMSOL.
 7: Advanced Features Of COMSOL.
 Appendices.
 Index.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Online
19. COMSOL5 for engineers [2016]
 Tabatabaian, Mehrzad, author.
 Dulles, Virginia : Mercury Learning and Information, [2016]
 Description
 Book — 1 online resource
 Summary

 1: Introduction
 2: Finite Element Method (FEM)A Summary
 3: COMSOL  A Modeling Tool For Engineers
 4: Modeling SinglePhysics Problems
 5: Modeling MultiPhysics Problems
 6: Modeling Energy Systems With COMSOL
 7: Advanced Features of COMSOL
 Appendices
 Index.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
20. COMSOL5 for engineers [2016]
 Tabatabaian, Mehrzad, author.
 Dulles, Virginia : Mercury Learning and Information, [2016]
 Description
 Book — 1 online resource
 Summary

 1: Introduction
 2: Finite Element Method (FEM)A Summary
 3: COMSOL  A Modeling Tool For Engineers
 4: Modeling SinglePhysics Problems
 5: Modeling MultiPhysics Problems
 6: Modeling Energy Systems With COMSOL
 7: Advanced Features of COMSOL
 Appendices
 Index.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Online