Preface |
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xiii | |
Acknowledgements |
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xv | |
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xvii | |
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xxi | |
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xxv | |
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xxvii | |
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1 Similarity Solutions of Spherical Shock Waves in a Self-Gravitating Ideal Gas |
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1 | (22) |
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1 | (2) |
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1.2 Formulation of Problem |
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3 | (2) |
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5 | (3) |
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8 | (5) |
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13 | (2) |
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1.6 Results and Discussion |
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15 | (4) |
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19 | (1) |
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19 | (4) |
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2 Dual Solutions for Finite Element Analysis of Unsteady Hydromagnetic Stagnation Point Flow of Cu - Water Nanofluid Generated by Stretching Sheet |
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23 | (28) |
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24 | (2) |
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2.2 Formulation of the Problem |
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26 | (2) |
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2.3 Similarity Transformation |
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28 | (1) |
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2.4 Local Skin Friction and Local Nusselt Number |
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29 | (1) |
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29 | (3) |
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32 | (1) |
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2.7 Numerical Results and Discussion |
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32 | (14) |
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46 | (1) |
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47 | (4) |
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3 Multiparametric Modeling of Carbon Cycle in Temperate Wetlands for Regional Climate Change Analysis Using Satellite Data |
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51 | (44) |
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52 | (2) |
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3.2 On the Methodology of Emission Analysis |
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54 | (3) |
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3.2.1 Generalized Approach |
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54 | (2) |
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3.2.2 On the Uncertainty Control |
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56 | (1) |
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3.3 Modeling of the Carbon Cycle |
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57 | (15) |
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3.3.1 Key Model Variables and Parameters |
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57 | (4) |
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3.3.2 From Local to Global Methane Cycle Modeling: Variables and Parameters |
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61 | (4) |
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3.3.3 Uncertainty Analysis in the Carbon Models |
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65 | (1) |
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3.3.4 On the Local Models Integration into the Global Models: A Methodology |
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66 | (6) |
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3.4 Satellite Tools and Data for the Carbon Cycle Control |
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72 | (7) |
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3.4.1 Satellite Tools for GHG Monitoring |
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72 | (1) |
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3.4.2 Satellite Tools for Plant Productivity and Carbon Stock Assessment |
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73 | (2) |
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3.4.3 Satellite Tools for Uncertainty Assessment in Crops Productivity |
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75 | (4) |
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3.5 Approach to Emission Assessment and Control |
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79 | (3) |
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3.5.1 Stochastic Tools for Decision Making in Carbon Emissions Control |
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80 | (2) |
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3.6 Results of Multiparametric Modeling of Methane Cycle in Temperate Wetlands in View of Regional Climate Change Using Satellite Data |
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82 | (5) |
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87 | (3) |
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90 | (5) |
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4 An Intelligent Neuro Fuzzy System for Pattern Classification |
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95 | (18) |
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96 | (1) |
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4.2 Artificial Neural Networks Approach |
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97 | (1) |
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97 | (1) |
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4.4 Design of an Intelligent Neuro Fuzzy System |
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97 | (1) |
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4.5 Hybrid Learning Algorithm of Proposed Method |
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98 | (1) |
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98 | (2) |
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100 | (4) |
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4.7.1 Rules' Index Vector |
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101 | (3) |
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104 | (2) |
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4.9 Graphs of Performance Error Vs No. of Iterations |
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106 | (4) |
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110 | (3) |
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5 Fuzzy Inventory Model with Demand, Deterioration and Inflation: A Comparative Study Through NGTFN and CNTFN |
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113 | (26) |
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114 | (1) |
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115 | (3) |
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118 | (1) |
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118 | (3) |
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5.5 Formulation of Fuzzy Mathematical Model |
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121 | (8) |
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129 | (1) |
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130 | (1) |
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5.8 Concluding Remarks and Future Studies |
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130 | (4) |
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134 | (5) |
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6 Summability and Its Application for the Stability of the System |
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139 | (20) |
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139 | (2) |
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141 | (1) |
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142 | (1) |
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6.3.1 Ordinary Summability |
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142 | (1) |
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142 | (1) |
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6.3.3 Absolute Summability |
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143 | (1) |
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6.4 Regularity of a Summability Process |
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143 | (1) |
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6.5 Silverman-Toeplitz Theorem |
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143 | (1) |
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6.6 Application of Absolute Summable Factor for Stability |
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144 | (12) |
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6.6.1 Stability of the Frequency Response of the Moving Average System |
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144 | (3) |
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6.6.2 Stability of the Frequency Response of the Oscillating Impulse System |
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147 | (3) |
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6.6.3 Stability of the Frequency Response of the Exponential System |
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150 | (1) |
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6.6.3.1 Stability of frequency response of the exponential system up to n = 0, 1,2,, 88 |
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151 | (2) |
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6.6.3.2 Stability of frequency response of the exponential system up to n = 0, 1,2, 176 |
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153 | (3) |
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156 | (1) |
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157 | (2) |
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7 Design of Manufacturing, Control, and Automation Systems |
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159 | (20) |
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159 | (2) |
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7.2 Steps in Design of Manufacturing Systems |
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161 | (1) |
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7.3 Types of Manufacturing |
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162 | (1) |
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7.4 Additive Manufacturing (AM) |
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162 | (4) |
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7.4.1 Design of Additive Manufacturing System |
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163 | (1) |
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7.4.2 Subtractive Type Manufacturing |
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163 | (1) |
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7.4.3 Machining Process in Subtractive Manufacturing |
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164 | (1) |
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7.4.4 Cutting Tools for Subtractive Manufacturing |
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165 | (1) |
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166 | (5) |
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7.5.1 Advantages and Disadvantages of Rapid Prototyping |
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166 | (1) |
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7.5.2 Types of Rapid Prototypes |
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167 | (4) |
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171 | (2) |
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7.6.1 Feedback in Control System |
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172 | (1) |
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173 | (2) |
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7.7.1 Application of Automation in Industries |
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174 | (1) |
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7.7.2 Type of Automation System |
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174 | (1) |
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175 | (1) |
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176 | (3) |
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8 SEIR - Application for Crop Through Water and Soil Texture |
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179 | (14) |
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179 | (2) |
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179 | (1) |
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8.1.2 Dynamics of Crop using Fertile Soil |
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180 | (1) |
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8.2 Mathematical Modeling |
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181 | (3) |
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184 | (2) |
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184 | (1) |
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185 | (1) |
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186 | (3) |
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189 | (1) |
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190 | (3) |
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9 Advances in Radial Basis Functions |
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193 | (16) |
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193 | (1) |
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9.2 Requirement of Mesh-free Methods |
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194 | (1) |
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9.3 Radial Basis Function |
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195 | (1) |
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9.4 Properties of Radial Basis Functions |
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195 | (1) |
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9.5 Developments in Radial Basis Functions |
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196 | (1) |
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196 | (2) |
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198 | (2) |
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9.8 Solution of Differential Equation |
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200 | (5) |
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200 | (1) |
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9.8.2 Symmetric Collocation Method |
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201 | (1) |
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9.8.3 RBF-pseudospectral Approach |
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201 | (4) |
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205 | (1) |
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205 | (4) |
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10 Modeling for Time Period of Natural Frequency for Non-Homogeneous Square Plate with Variable Thickness and Temperature Effect |
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209 | (20) |
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209 | (1) |
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210 | (3) |
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213 | (1) |
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10.4 Construction of Problem |
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214 | (2) |
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216 | (2) |
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10.6 Numerical Illustration and Discussions |
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218 | (5) |
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223 | (1) |
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224 | (1) |
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225 | (4) |
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11 A Study on Metric Fixed Point Theorems Satisfying Integral Type Contractions |
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229 | (20) |
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230 | (1) |
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230 | (4) |
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11.3 Fixed Point Theorem Satisfying Weak Integral Type Rational Contractions |
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234 | (9) |
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11.4 (tt, (p)--- Integral Type Weak Contractions and Fixed-Point Theorems |
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243 | (3) |
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246 | (1) |
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246 | (3) |
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12 Objective Function - in Radiometric Studies - Application to AGRS Surveys Associated with Radon |
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249 | (16) |
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Shivvaran Singh Raghuwanshi |
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249 | (1) |
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12.2 Ordinary and Weighted Linear Regression Models |
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250 | (2) |
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12.3 Computations of Compton Factors |
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252 | (4) |
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12.3.1 Study of Variations in Stripping Factors when the Correlation among Radioelements Exists |
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253 | (2) |
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12.3.2 Estimation of Stripping Factors and their Variations with Flying Heights |
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255 | (1) |
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12.4 Objective Function for Study of Random Errors in Stripping Coefficients |
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256 | (2) |
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12.5 Effects of Airborne Bi24 and Error Bias due to It |
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258 | (1) |
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12.6 Ground and Airborne Experiments |
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259 | (1) |
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12.7 Results and Discussion |
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260 | (1) |
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260 | (1) |
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260 | (1) |
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12.7.3 Area of Very High Thorium Concentration |
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261 | (1) |
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12.7.4 Area of High Uranium Concentration |
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261 | (1) |
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261 | (1) |
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262 | (3) |
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13 Modeling Kernel Function in Blackbody Radiation Inversion |
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265 | (12) |
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Shivvaran Singh Raghuwanshi |
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265 | (1) |
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13.2 Nature and Statement of the Problem |
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266 | (3) |
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13.3 Towards a Solution to the Problem |
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269 | (7) |
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13.3.1 Reducing $(x) Function to Gaussians |
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272 | (2) |
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13.3.2 Convolution of Equation (13.4) |
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274 | (2) |
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276 | (1) |
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276 | (1) |
Index |
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277 | (4) |
About the Editors |
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281 | |