Suchergebnisse

Mathematical Modeling for Business Analytics is written for decision makers at all levels. This book presents the latest tools and techniques available to help in the decision process. The interpretation and explanation of the results are crucial to understanding the strengths and limitations of modeling. This book emphasizes and focuses on the aspects of constructing a useful model formulation, as well as building the skills required for decision analysis. The book also focuses on sensitivity analysis. The author encourages readers to formally think about solving problems by using a thorough process. Many scenarios and illustrative examples are provided to help solve problems. Each chapter is also comprehensively arranged so that readers gain an in-depth understanding of the subject which includes introductions, background information and analysis. Both undergraduate and graduate students taking methods courses in methods and discrete mathematical modeling courses will greatly benefit from using this book. --

Systemic approaches are needed and useful for the study of the very complex issue of cancer. Modeling has a central position in these systemic approaches. Metabolic reprogramming is nowadays acknowledged as an essential hallmark of cancer. Mathematical modeling could contribute to a better understanding of cancer metabolic reprogramming and to identify new potential ways of therapeutic intervention. Herein, I review several alternative approaches to metabolic modeling and their current and future impact in oncology. ; Supported by grants BIO2014-56092-R (MINECO and FEDER), P12-CTS-1507 (Andalusian Government and FEDER) and funds from group BIO-267 (Andalusian Government). The "CIBER de Enfermedades Raras" is an initiative from the ISCIII (Spain). The funders had no role in the study design, data collection and analysis, decision to publish or preparation of the manuscript.

1. Basic Concepts -- 1.1. Modeling -- 1.2. Classification of Processes -- 1.3. Process Parameters and Variables and their Classification -- 1.4. Classification of Process Models -- Capter 2. Optimizing Models -- 2.1. General Considerations -- 2.2. Objective Function — an Example -- 2.3. Designing the Objective Function -- 2.4. Objective Function as a Function of Time -- 2.5. Constrained and Unconstrained Optima -- 2.6. Objective Function — Example Revisited -- 3. Methods of Optimum Search -- 3.1. Problem Definition -- 3.2. Single Variable Search -- 3.3. Two-dimensional Search (Hill-Climbing) -- 4. Design of Experiments -- 4.1. Replication -- 4.2. Blocking of Experiments -- 4.3. Randomization -- 4.4. Factorial Design -- 4.5. Orthogonality -- 4.6. Confounding -- 4.7. Fractional Factorial Design -- 5. Dynamic Covariance Analysis -- 5.1. Dynamic Models -- 5.2. Linear Dynamic Model — Single Variable -- 5.3. End Conditions -- 5.4. Identification of Linear Model -- 5.5. Linear Dynamic Model — Multiple Variables -- 6. Principal Component Analysis -- 6.1. Reducing Number of Variables -- 6.2. Orthogonal Coordinates in Sample Space -- 6.3. Axes with Stationary Property -- 6.4. Zero-one Normalized Variables -- 6.5. Eigenvalues and Eigenvectors -- 6.6. Orthogonality -- 6.7. Mean-square Distances — Distribution of Variance -- 6.8. Numerical Example -- 6.9. Performance Variables -- 7. Regression Analysis -- 7.1. Principle of Least Squares -- 7.2. Linear Regression -- 7.3. Transformation to Linear Form -- 7.4. Choosing the Form of Model -- 7.5. Stepwise Regression -- 7.6. Non-linear Estimation -- References.

Discusses the physical and mathematical analysis of transport phenomena associated with food processing. This title presents various models that describe many of the important physical and biological transformations that occur in food during processing.

The article outlines and discusses the universal mathematical model created by the author and allowing to predict scenarios for post-Soviet secessions and, more broadly, to forecast secession potentials of any complex subnational regional units. The objects of forecasting are de facto states and different kinds of polities with failed statehood, analyzed through the prism of the "parent state – secession – patron state" triangle. The main research method is quantification of secession factors, which enables a researcher to measure the impacts of objective and subjective conditions on the course and results of secessions through the use of specific variables and indicators. As described in mathematical terms, the model has two extremes: "ideal secession" and "ideal anti-secession".

Intro -- Preface -- Contents -- To Know Without Destroying? -- 1 The MADAR Project: Historical Heritage and Math Towards a Common Path -- 2 Potential and Weaknesses of the Porto Torres (Sardinia) Case Study -- 3 Construction Techniques, Features and Historical Phases of the Complex of Central Baths -- 4 To Know Without Destroying -- References -- Representative Volume Elements for the Analysis of Concrete Like Materials by Computational Homogenization -- 1 Introduction -- 2 Generation of the Geometry of the RVE -- 2.1 Spherical Aggregate Particles -- 2.1.1 Taking Process -- 2.1.2 Placing Process -- 2.2 Polyhedral Aggregate Particles -- 3 Micro-to-Macro Computational Homogenization -- 3.1 Periodic Boundary Conditions -- 4 Numerical Results -- 5 Conclusions -- References -- A New Nonlocal Temperature-Dependent Model for Adhesive Contact -- 1 Introduction -- 1.1 Rate-Independent Models -- 1.2 Rate-Dependent Models -- 1.3 Adhesive Contact with Nonlocal Effects -- 2 The Model and the PDE System -- 2.1 The State and Dissipative Variables -- 2.2 The Free Energy -- 2.3 The Dissipation Potential -- 2.4 The Balance Equations and the Constitutive Laws -- 2.5 The PDE System -- 2.6 Outlook to the Analysis -- References -- Chemomechanical Degradation of Monumental Stones: Preliminary Results -- 1 Introduction -- 2 A Mathematical Model of Marble Sulphation -- 2.1 A Simplified Chemical Reaction -- 2.2 The Hydrodynamical Model -- 3 The Variational Approach to Fracture -- 4 A Chemo-Mechanic Model -- 4.1 Mechanical Properties -- 4.2 Diffusivity -- 4.3 Mathematical Model -- 5 A Numerical Example -- References -- Modelling the Effects of Protective Treatments in Porous Materials -- 1 Introduction -- 2 Materials and Methods -- 3 Modelling of Capillary Imbibition -- 3.1 Boundary Conditions -- 4 Numerical Results and Comparison with Experimental Data.