The second edition of Reverse Engineering of Algebraic Inequalities is a comprehensively updated new edition demonstrating the exploration of new physical realities and creation of new knowledge in various unrelated domains of human activity through reverse engineering of algebraic inequalities.
The second edition of Reverse Engineering of Algebraic Inequalities is a comprehensively updated new edition demonstrating the exploration of new physical realities and creation of new knowledge in various unrelated domains of human activity through reverse engineering of algebraic inequalities.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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Autorenporträt
Michael T. Todinov is a professor of mechanical engineering at Oxford Brookes University, UK, where he teaches reliability engineering, engineering mathematics, and advanced stress analysis. He holds a PhD in mechanical engineering and a higher doctorate, equivalent to a DSc, in mathematical modeling. Prof. Todinov has pioneered innovative research in several areas, including reverse engineering of algebraic inequalities, domain-independent methods for reliability improvement, analysis and optimization of repairable flow networks, reliability analysis based on the cost of failure, and fracture statistics controlled by defects. Michael Todinov is a recipient of a prestigious award from the Institution of Mechanical Engineers (UK) for his work in risk reduction in mechanical engineering.
Inhaltsangabe
1. Fundamental Approaches in Modelling Real Systems and Processes by Using Algebraic Inequalities: The Principle of Consistency for Algebraic Inequalities 2. Basic Algebraic Inequalities Used in Reverse Engineering and Their Properties 3. Obtaining New Physical Properties by Reverse Engineering of Algebraic Inequalities 4. Light-Weight Designs and Improving the Load-Bearing Capacity of Structures by Reverse Engineering of Algebraic Inequalities 5. Reliability-Related Reverse Engineering of Algebraic Inequalities 6. Enhancing the Reliability of Series-Parallel Systems with Multiple Redundancies by Reverse Engineering of Algebraic Inequalities 7. Reverse Engineering of Algebraic Inequalities to Disprove System Reliability Predictions Based on Average Component Reliabilities 8. Reverse Engineering of the Inequality of Additive Ratios 9. Optimal Selection and Expected Time of Unsatisfied Demand by Reverse Engineering of Algebraic Inequalities 10. Enhancing Systems and Process Performance by Reverse Engineering of Algebraic Inequalities Based on Sub-Additive and Super-Additive Functions 11. Enhancing Decision-Making by Reverse Engineering of Algebraic Inequalities 12. Generating New Knowledge by Reverse Engineering of Algebraic Inequalities in Terms of Potential Energy
1. Fundamental Approaches in Modelling Real Systems and Processes by Using Algebraic Inequalities: The Principle of Consistency for Algebraic Inequalities 2. Basic Algebraic Inequalities Used in Reverse Engineering and Their Properties 3. Obtaining New Physical Properties by Reverse Engineering of Algebraic Inequalities 4. Light-Weight Designs and Improving the Load-Bearing Capacity of Structures by Reverse Engineering of Algebraic Inequalities 5. Reliability-Related Reverse Engineering of Algebraic Inequalities 6. Enhancing the Reliability of Series-Parallel Systems with Multiple Redundancies by Reverse Engineering of Algebraic Inequalities 7. Reverse Engineering of Algebraic Inequalities to Disprove System Reliability Predictions Based on Average Component Reliabilities 8. Reverse Engineering of the Inequality of Additive Ratios 9. Optimal Selection and Expected Time of Unsatisfied Demand by Reverse Engineering of Algebraic Inequalities 10. Enhancing Systems and Process Performance by Reverse Engineering of Algebraic Inequalities Based on Sub-Additive and Super-Additive Functions 11. Enhancing Decision-Making by Reverse Engineering of Algebraic Inequalities 12. Generating New Knowledge by Reverse Engineering of Algebraic Inequalities in Terms of Potential Energy
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