Tabla de Contenidos: “…4.2.2 Likelihood Equations for Poisson Loglinear Model -- 4.2.3 The Key Role of the Mean-Variance Relation -- 4.2.4 Large-Sample Normal Distribution of Model Parameter Estimators -- 4.2.5 Delta Method Yields Covariance Matrix for Fitted Values -- 4.2.6 Model Misspecification: Robustness of GLMs with Correct Mean -- 4.3 Likelihood-Ratio/Wald/Score Methods of Inference for GLM Parameters -- 4.3.1 Likelihood-Ratio Tests -- 4.3.2 Wald Tests -- 4.3.3 Score Tests -- 4.3.4 Illustrating the Likelihood-Ratio, Wald, and Score Tests -- 4.3.5 Constructing Confidence Intervals by Inverting Tests -- 4.3.6 Profile Likelihood Confidence Intervals -- 4.4 Deviance of a GLM, Model Comparison, and Model Checking -- 4.4.1 Deviance Compares Chosen Model with Saturated Model -- 4.4.2 The Deviance for Poisson GLMs and Normal GLMs -- 4.4.3 Likelihood-Ratio Model Comparison Uses Deviance Difference -- 4.4.4 Score Tests and Pearson Statistics for Model Comparison -- 4.4.5 Residuals and Fitted Values Asymptotically Uncorrelated -- 4.4.6 Pearson, Deviance, and Standardized Residuals for GLMs -- 4.5 Fitting Generalized Linear Models -- 4.5.1 Newton-Raphson Method -- 4.5.2 Fisher Scoring Method -- 4.5.3 Newton-Raphson and Fisher Scoring for a Binomial Parameter -- 4.5.4 ML as Iteratively Reweighted Least Squares -- 4.5.5 Simplifications for Canonical Link Functions -- 4.6 Selecting Explanatory Variables for a GLM -- 4.6.1 Stepwise Procedures: Forward Selection and Backward Elimination -- 4.6.2 Model Selection: The Bias-Variance Tradeoff -- 4.6.3 AIC: Minimizing Distance of the Fit from the Truth -- 4.6.4 Summarizing Predictive Power: R-Squared and Other Measures -- 4.6.5 Effects of Collinearity -- 4.7 Example: Building a GLM -- 4.7.1 Backward Elimination with House Selling Price Data -- 4.7.2 Gamma GLM Has Standard Deviation Proportional to Mean…”

Tabla de Contenidos: “…-- Economic Activity -- Wants: The Basis of All Economic Activities -- Circular Flow of Economic Activity -- Real Flows -- Money Flows -- Production -- Definition -- Consumers' Goods and Producers' Goods -- Utility -- Goods -- Free Goods and Economic Goods -- Consumption Goods and Capital Goods -- Value -- Wealth -- Classes -- Wealth and Welfare -- Consumption -- Human Wants -- Formation -- Categories -- Characteristics -- Standard of Living -- Factors Affecting the Standard of Living -- The Standard of Living in India -- Engel'S Law of Family Expenditure -- Scales of Preferences -- Savings and Investment -- Summary -- Notes -- Key Words -- Discussion Questions -- Suggested Readings -- Chapter 2: National Income -- Definitions -- Marshall's Production-Based Definition -- Pigou's Income-Based Definition -- Fisher's Consumption-Based Definition -- Concepts in National-Income Analysis -- Gross National Product -- Net National Product -- National Income At Factor Cost -- Personal Income -- Personal Disposable Income -- Per Capita Income -- Measurement of National Income -- The Product Method -- The Income-Received Method -- The Consumption-Savings Method -- A Comparison of the Three Methods -- The Sectoral Composition of National Income -- Estimates of the National Income of India -- Post-Independence Background -- Special Features of the 1980-81 Series -- RBI's Role in National Income Accounting -- Advance Estimates and Quick Estimates of National Income -- Difficulties in the Measurement of National Income -- National Income Data and the Changing Profile of the Indian Economy -- Characteristics of the Indian Economy -- The National Statistical Commission…”

Tabla de Contenidos: “…Realizing the Benefits of a Trusting and Psychologically Safe Workplace -- Identifying the Factors that Drive and Undermine Psychological Safety -- Factors that undermine trust and psychological safety -- Factors that cultivate trust and psychological safety -- Creating Psychological Safety -- Increasing Inclusion Safety -- Increasing Learner Safety -- Increasing Contributor Safety -- Increasing Challenger Safety -- Measuring Psychological Safety -- Recognizing Best Practice Companies -- Pixar: "Fail Early and Often" -- Eileen Fisher: "Leadership is About Listening" -- Barry-Wehmiller: "What We Do Matters" -- X Development LLC: "Shoot for the Moon" -- Chapter 12 Coaching and Giving Feedback -- Acknowledging the Impact of Not Providing Coaching and Feedback -- Understanding the Difference between Coaching and Feedback -- Customizing Your Coaching Approach using Situational Leadership -- Telling -- Selling -- Participating -- Delegating -- Avoiding Common Feedback Pitfalls -- Being unprepared -- Failing to establish trust -- Ignoring cultural context -- Treating everyone the same way -- Avoiding reciprocal feedback -- Giving Great Feedback -- Before the conversation -- During the conversation -- After the conversation -- Chapter 13 Communicating Inclusively -- Recognizing the Benefits of Inclusive Communication -- Understanding the Impact of Non-Inclusive Language -- Working With Human Resources to Promote Inclusive Language -- Practicing Inclusive Communication -- Chapter 14 Dealing with Conflict -- Addressing the Reasons We Avoid Conflict -- Normalizing Conflict as a Tool for Higher Performance -- Identifying the Topics We Tend to Avoid -- Seeing the Benefits of Engaging in Uncomfortable Conversations -- Interpreting Two Models for Managing Conflict -- Thomas-Kilman conflict modes -- Intercultural Conflict Styles…”

Tabla de Contenidos: “…Singer -- Focus (1945) / Arthur Miller -- Passage from home (1946) / Isaac Rosenfeld -- Wasteland (1946) / Jo Sinclair -- East River (1946) / Sholem Asch -- The Amboy dukes (1947) / Irving Shulman -- My glorious brothers (1948) / Howard Fast -- The naked and the dead (1948) / Norman Mailer -- The break-up of our camp and other stories (1949) / Paul Goodman -- A stone for Danny Fisher (1952) / Harold Robbins -- The adventures of Augie March (1953) / Saul Bellow -- Blessed is the land (1954) / Louis Zara -- Marjorie Morningstar (1955) / Herman Wouk -- Compulsion (1956) / Meyer Levin -- Remember me to God (1957) / Myron S. …”
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Tabla de Contenidos: “…. -- There's more... -- The Fisher-Behrens problem -- How to do it... -- How it works... -- There's more... -- Paired t-test -- How to do it... -- How it works... -- There's more... -- Calculating ANOVA sum of squares and F tests -- How to do it... -- Two-way ANOVA -- How to do it... -- How it works... -- There's more... -- Type I, Type II, and Type III sum of squares -- Type I -- Type II -- Type III -- Getting ready -- How to do it... -- How it works... -- Random effects -- Getting ready -- How to do it... -- How it works... -- There's more... -- Repeated measures -- Getting ready -- How to do it... -- How it works... -- There's more... -- Multivariate t-test -- Getting ready... -- How to do it... -- How it works... -- There's more... -- MANOVA -- Getting ready -- How to do it... -- How it works... -- There's more... -- Chapter 3: Linear Regression -- Introduction -- Computing ordinary least squares estimates -- How to do it... -- How it works... -- Reporting results with the sjPlot package -- Getting ready -- How to do it... -- How it works... -- There's more... -- Finding correlation between the features -- Getting ready... -- How to do it... -- Testing hypothesis -- Getting ready -- How to do it... -- How it works... -- Testing homoscedasticity -- Getting ready -- How to do it... -- How it works... -- Implementing sandwich estimators -- Getting ready -- How to do it... -- How it works... -- Variable selection -- Getting ready -- How to do it... -- How it works... -- Ridge regression -- Getting ready -- How to do it... -- How it works…”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright -- Contents -- List of Figures -- List of Table -- Preface -- Acknowledgments -- Acronyms -- Chapter 1 Introduction -- 1.1 State of a Dynamic System -- 1.2 State Estimation -- 1.3 Construals of Computing -- 1.4 Statistical Modeling -- 1.5 Vision for the Book -- Chapter 2 Observability -- 2.1 Introduction -- 2.2 State‐Space Model -- 2.3 The Concept of Observability -- 2.4 Observability of Linear Time‐Invariant Systems -- 2.4.1 Continuous‐Time LTI Systems -- 2.4.2 Discrete‐Time LTI Systems -- 2.4.3 Discretization of LTI Systems -- 2.5 Observability of Linear Time‐Varying Systems -- 2.5.1 Continuous‐Time LTV Systems -- 2.5.2 Discrete‐Time LTV Systems -- 2.5.3 Discretization of LTV Systems -- 2.6 Observability of Nonlinear Systems -- 2.6.1 Continuous‐Time Nonlinear Systems -- 2.6.2 Discrete‐Time Nonlinear Systems -- 2.6.3 Discretization of Nonlinear Systems -- 2.7 Observability of Stochastic Systems -- 2.8 Degree of Observability -- 2.9 Invertibility -- 2.10 Concluding Remarks -- Chapter 3 Observers -- 3.1 Introduction -- 3.2 Luenberger Observer -- 3.3 Extended Luenberger‐Type Observer -- 3.4 Sliding‐Mode Observer -- 3.5 Unknown‐Input Observer -- 3.6 Concluding Remarks -- Chapter 4 Bayesian Paradigm and Optimal Nonlinear Filtering -- 4.1 Introduction -- 4.2 Bayes' Rule -- 4.3 Optimal Nonlinear Filtering -- 4.4 Fisher Information -- 4.5 Posterior Cramér-Rao Lower Bound -- 4.6 Concluding Remarks -- Chapter 5 Kalman Filter -- 5.1 Introduction -- 5.2 Kalman Filter -- 5.3 Kalman Smoother -- 5.4 Information Filter -- 5.5 Extended Kalman Filter -- 5.6 Extended Information Filter -- 5.7 Divided‐Difference Filter -- 5.8 Unscented Kalman Filter -- 5.9 Cubature Kalman Filter -- 5.10 Generalized PID Filter -- 5.11 Gaussian‐Sum Filter -- 5.12 Applications -- 5.12.1 Information Fusion -- 5.12.2 Augmented Reality…”

Tabla de Contenidos: “…Conté: Buildings featured: Toto Seminar House, Tsuna-Gun, Hyogo, Japan, 1994-97 / Tadao Ando - Daylight Museum, Gamo-Gun, Shiga, Japan, 1997-98 / Tadao Ando - Our Lady of the Ark of the Covenant, Paris, France, 1996-97 / Architecture Studio - Paper House, Lake Yamanashi, Japan, 1994-95 / Shigeru Ban - Wall-less house, Karuizawa, Nagano, Japan, 1997 / Shigeru Ban - Jean Moulin student residence, Le Creusot, France, 1993 / BDM - Mobius House, 'T Gooi, The Netherlands, 1993-97 - Quay buildings, Kop van Zuid, Rotterdam, The Netherlands, 1991-96 / Bolles+Wilson - New Luxor Theater, Rotterdam, The Netherlands, 1998-2000 / Bolles+Wilson - Church of Saint John the Baptist, Mogno, Ticino, Switzerland, 1986/92-98 / Mario Botta - Powerhouse::UK, London, England, 1997-98 / Branson Coates - Temple Kol Ami, Scottsdale, Arizona, United States, 1992-94 / Will Bruder - Mad River boat trips, Jackson, Wyoming, United States, 1995-97 / Will Bruder - Oriente Station, Lisbon, Portugal, 1993-98 / Santiago Calatrava - Joseph Menswear, London, England, 1997 / David Chipperfield - Sunshine Coast University Club, Sippy Downs, Queensland, Australia, 1996 / Clare Design - UFA Cinema Center, Dresden, Germany, 1996-98 / Coop Himmelblau - House extension, Santa Monica, California, United States, 1996-98 / Steven Ehrlich - P.S.1 (The Institute for Contemporary Art) Long Island City, New York, New York, United States, 1995-97 / Frederick Fisher - Hong Kong International Airport, Hong Kong, China, 1995-98 / Norman Foster - Reichstag, Berlin, Germany, 1993-99 / Norman Foster - The Eden Project, St. …”

Tabla de Contenidos: “…Intro -- Contents -- 1 Introduction -- 1.1 Organization -- 2 The Bayes Paradigm, Estimation and Information Measures -- 2.1 Bayes Posterior Distribution -- 2.1.1 Minimum Risk Estimation -- 2.1.2 Information Measures -- 2.2 Mathematical Preliminaries -- 2.2.1 Probability Spaces, Random Variables, Distributions, Densities, and Expectation -- 2.2.2 Transformations of Variables -- 2.2.3 The Multivariate Normal Distribution -- 2.2.4 Characteristic Function -- 2.3 Minimum Risk Hypothesis Testing on Discrete Spaces -- 2.3.1 Minimum Probability of Error via Maximum A Posteriori Hypothesis Testing -- 2.3.2 Neyman-Pearson and the Optimality of the Likelihood Ratio Test -- 2.4 Minimum Mean-Squared Error Risk Estimation in Vector Spaces -- 2.4.1 Normed Linear and Hilbert Spaces -- 2.4.2 Least-Squares Estimation -- 2.4.3 Conditional Mean Estimation and Gaussian Processes -- 2.5 The Fisher Information of Estimators -- 2.6 Maximum-Likelihood and its consistency -- 2.6.1 Consistency via Uniform Convergence of Empirical Log-likelihood -- 2.6.2 Asymptotic Normality and &amp -- #8730 -- n Convergence Rate of the MLE -- 2.7 Complete-Incomplete Data Problems and the EM Algorithm -- 2.8 Hypothesis Testing and Model Complexity -- 2.8.1 Model-Order Estimation and the d/2 log Sample-Size Complexity -- 2.8.2 The Gaussian Case is Special -- 2.8.3 Model Complexity and the Gaussian Case -- 2.9 Building Probability Models via the Principle of Maximum Entropy -- 2.9.1 Principle of Maximum Entropy -- 2.9.2 Maximum Entropy Models -- 2.9.3 Conditional Distributions are Maximum Entropy -- 3 Probabilistic Directed Acyclic Graphs and Their Entropies -- 3.1 Directed Acyclic Graphs (DAGs) -- 3.2 Probabilities on Directed Acyclic Graphs (PDAGs) -- 3.3 Finite State Markov Chains -- 3.4 Multi-type Branching Processes -- 3.4.1 The Branching Matrix -- 3.4.2 The Moment-Generating Function…”

Tabla de Contenidos: “…2.1 Pre-Existing Conditions of Fragility - Indivisibility of Rights -- 2.2 Impacts On the Right to Food, in Light of Its Legal Elements -- 2.2.1 Food Accessibility -- 2.2.2 Food Adequacy -- 2.2.3 Food Availability -- 2.3 Differential Impacts On Specific Population Groups -- 2.3.1 Women and Lgbtq Persons -- 2.3.2 Agricultural Workers in the Industrial Sector -- 2.3.3 Peasant and Fisher Communities -- 2.3.4 Indigenous Peoples -- 3 A Survey of Responses and Recommendations -- 3.1 The Responses By Affected Communities, Social Movements, and Civil Society Organizations -- 3.2 Responses By National Decision Makers -- 3.3 Some Responses By the Corporate Sector -- 3.4 Responses of International Human Rights Institutions -- 4 The Strengths and Promises of the Rural Movements' Proposal -- 5 Conclusion -- References -- 13 Covid-19 and the Human Rights to Water and Sanitation -- 1 Evolution of the Rights to Water and Sanitation Over the Past Decade -- 2 Impacts of Covid-19 On Water and Sanitation Services -- 2.1 Availability of Services -- 2.2 Affordability and Other Economic Impacts On Consumers and Operators -- 2.3 Covid-19 and the Governance and Regulation of Services -- 3 Human Rights Implications of Measures Adopted for Water and Sanitation Services During the Pandemic -- 3.1 Affordability and Flexible Payment Options -- 3.2 Physical Accessibility -- 3.3 Access to Information, Participation, and Accountability -- 4 Towards Sustainability of the Rights to Water and Sanitation -- Notes -- References -- 14 Land Rights in Crisis -- 1 Human Rights and Land: a Rights-Based Approach -- 2 'shock Strategy' and Land Rights in a Crisis -- 3 Government Oversight and Enforcement Mechanisms under Strain Due to the Pandemic -- 4 Government Failures to Protect Land Are Exacerbating Inequality and Poverty…”

Tabla de Contenidos: “…-- The Fed's Use of M1 Versus M2 in Practice -- QUANTITY THEORY OF MONEY -- Velocity of Money and the Equation of Exchange -- From the Equation of Exchange to the Quantity Theory of Money -- The Classical Dichotomy -- Quantity Theory and the Price Level -- Quantity Theory and Inflation -- APPLICATION: Testing the Quantity Theory of Money -- HYPERINFLATION -- POLICY AND PRACTICE: The Zimbabwean Hyperinflation -- INFLATION AND INTEREST RATES -- APPLICATION: Testing the Fisher Effect -- THE COST OF INFLATION -- Costs of Anticipated Inflation…”

Tabla de Contenidos: “…-- Review Questions and Exercises -- Endnotes -- Further Readings -- Chapter 10: Theories of Interest and Investment Decisions -- Introduction -- Capital as a Factor of Production -- Some Early Thoughts on Interest Theory -- Theories of Interest -- Bohm-Bawerk's Theory of Interest -- Fisher's Theory of Interest: The Time Preference Theory -- Criticism -- The Classical Theory of Interest -- Keynes' Criticism of Classical Theory -- The Loanable Fund Theory of Interest -- Classical vs Neo-Classical Theory of Interest -- Criticism -- Interest and Investment Decisions…”

Tabla de Contenidos: “…-- Introduction -- Comparing two means (rating scales and task times) -- Within-subjects comparison (paired t-test) -- Confidence interval around the difference -- Practical significance -- Comparing task times -- Normality assumption of the paired t-test -- Between-subjects comparison (two-sample t-test) -- Confidence interval around the difference -- Assumptions of the t-tests -- Normality -- Equality of variances -- Don't worry too much about violating assumptions (except representativeness) -- Comparing completion rates, conversion rates, and A/B testing -- Between-subjects -- Chi-square test of independence -- Small sample sizes -- Two-proportion test -- Fisher exact test -- Yates correction -- N−1 Chi-square test -- N−1 Two-proportion test -- Confidence interval for the difference between proportions -- Within-subjects -- McNemar exact test -- Concordant pairs -- Discordant pairs -- Alternate approaches -- Chi-square statistic…”

Tabla de Contenidos: “…9.3.2 Case-study: Size-and-shape analysis and mutation -- 9.4 Edge-based shape coordinates -- 9.5 Investigating allometry -- 10 Shape and size-and-shape distributions -- 10.1 The uniform distribution -- 10.2 Complex Bingham distribution -- 10.2.1 The density -- 10.2.2 Relation to the complex normal distribution -- 10.2.3 Relation to real Bingham distribution -- 10.2.4 The normalizing constant -- 10.2.5 Properties -- 10.2.6 Inference -- 10.2.7 Approximations and computation -- 10.2.8 Relationship with the Fisher-von Mises distribution -- 10.2.9 Simulation -- 10.3 Complex Watson distribution -- 10.3.1 The density -- 10.3.2 Inference -- 10.3.3 Large concentrations -- 10.4 Complex angular central Gaussian distribution -- 10.5 Complex Bingham quartic distribution -- 10.6 A rotationally symmetric shape family -- 10.7 Other distributions -- 10.8 Bayesian inference -- 10.9 Size-and-shape distributions -- 10.9.1 Rotationally symmetric size-and-shape family -- 10.9.2 Central complex Gaussian distribution -- 10.10 Size-and-shape versus shape -- 11 Offset normal shape distributions -- 11.1 Introduction -- 11.1.1 Equal mean case in two dimensions -- 11.1.2 The isotropic case in two dimensions -- 11.1.3 The triangle case -- 11.1.4 Approximations: Large and small variations -- 11.1.5 Exact moments -- 11.1.6 Isotropy -- 11.2 Offset normal shape distributions with general covariances -- 11.2.1 The complex normal case -- 11.2.2 General covariances: Small variations -- 11.3 Inference for offset normal distributions -- 11.3.1 General MLE -- 11.3.2 Isotropic case -- 11.3.3 Exact isotropic MLE in R -- 11.3.4 EM algorithm and extensions -- 11.4 Practical inference -- 11.5 Offset normal size-and-shape distributions -- 11.5.1 The isotropic case -- 11.5.2 Inference using the offset normal size-and-shape model -- 11.6 Distributions for higher dimensions -- 11.6.1 Introduction…”

Tabla de Contenidos: “…2.6.1 Use of Texture and Context -- 2.6.2 Using Ancillary Multisource Data -- 2.7 Epilogue -- References -- Chapter 3 Dimensionality Reduction: Feature Extraction and Selection -- 3.1 Feature Extraction -- 3.1.1 Principal Component Analysis -- 3.1.2 Minimum/Maximum Autocorrelation Factors -- 3.1.3 Maximum Noise Fraction (MNF) Transformation -- 3.1.4 Independent Component Analysis -- 3.1.5 Projection Pursuit -- 3.2 Feature Selection -- 3.2.1 Greedy Search Methods -- 3.2.2 Simulated Annealing -- 3.2.3 Separability Indices -- 3.2.4 Filter-Based Methods -- 3.2.4.1 Correlation-Based Feature Selection -- 3.2.4.2 Information Gain -- 3.2.4.3 Gini Impurity Index -- 3.2.4.4 Minimum Redundancy-Maximum Relevance -- 3.2.4.5 Chi-Square Test -- 3.2.4.6 Relief-F -- 3.2.4.7 Symmetric Uncertainty -- 3.2.4.8 Fisher's Test -- 3.2.4.9 OneR -- 3.2.5 Wrappers -- 3.2.5.1 Genetic Algorithm -- 3.2.5.2 Particle Swarm Optimization -- 3.2.5.3 Feature Selection with SVMs -- 3.2.6 Embedded Methods -- 3.2.6.1 K-Nearest Neighbor-Based Feature Selection -- 3.2.6.2 Feature Selection with Ensemble Learners -- 3.2.6.3 Hilbert-Schmidt Independence Criterion with Lasso -- 3.3 Concluding Remarks -- References -- Chapter 4 Multisource Image Fusion and Classification -- 4.1 Image Fusion -- 4.1.1 Image Fusion Methods -- 4.1.1.1 PCA-Based Image Fusion -- 4.1.1.2 IHS-Based Image Fusion -- 4.1.1.3 Brovey Transform -- 4.1.1.4 Gram-Schmidt Transform -- 4.1.1.5 Wavelet Transform -- 4.1.1.6 Deep Learning for Image Fusion -- 4.1.2 Assessment of Fused Image Quality -- 4.1.3 Performance Evaluation of Fusion Methods -- 4.2 Multisource Classification Using the Stacked-Vector Method -- 4.3 The Extension of Bayesian Classification Theory -- 4.3.1 An Overview -- 4.3.1.1 Feature Extraction -- 4.3.1.2 Probability or Evidence Generation -- 4.3.1.3 Multisource Consensus…”

Tabla de Contenidos: “…Método de Bonferroni (Fisher) -- 4. Método basado en la amplitud máxima -- 5. …”

“…Territorial Use Rights in Fisheries in Chile: El Quisco and Puerto Oscuro by Gloria Gallardo Fernandés is an important contribution to our understanding of the multifaceted challenges underlying sustainable solutions to ecological fisheries, the book describes how, in Chile, indiscriminate harvest of the edible shellfish Concholepas concholepas (false abalone or Loco), has been threatening not only the living of small-scale artisan fishers but also the ecosystem. In an attempt to strengthen the fishers' livelihoods and at the same time recuperate the fish, the Chilean government introduced the regulatory measure: Management and Exploitation Areas for Benthic Resources (MEABRs), locally known as Management Areas (MAs) and internationally as Territorial Use Rights in Fisheries (TURFs)…”

“…Territorial Use Rights in Fisheries in Chile: El Quisco and Puerto Oscuro by Gloria Gallardo Fernandés is an important contribution to our understanding of the multifaceted challenges underlying sustainable solutions to ecological fisheries, the book describes how, in Chile, indiscriminate harvest of the edible shellfish Concholepas concholepas (false abalone or Loco), has been threatening not only the living of small-scale artisan fishers but also the ecosystem. In an attempt to strengthen the fishers' livelihoods and at the same time recuperate the fish, the Chilean government introduced the regulatory measure: Management and Exploitation Areas for Benthic Resources (MEABRs), locally known as Management Areas (MAs) and internationally as Territorial Use Rights in Fisheries (TURFs)…”

Tabla de Contenidos: “…West, Marina Ratova, Leanne Fisher, Soheyla Ostovarpour and Joanna Verran Feature Article: Structural Formation and Photocatalytic Activity of Magnetron Sputtered Titania and Doped-Titania Coatings Reprinted from: Molecules 2014, 19(10), 16327-16348 http://www.mdpi.com/1420-3049/19/10/16327 -- Pierre Pichat Review: Are TiO2 Nanotubes Worth Using in Photocatalytic Purification of Air and Water? …”

Tabla de Contenidos: “…-- 7.8.4 Constrained LS Estimation -- 7.9 Robust Estimation -- Chapter 8 Cramér-Rao Bound -- 8.1 Cramér-Rao Bound and Fisher Information Matrix -- 8.1.1 CRB for Scalar Problem (P=1) -- 8.1.2 CRB and Local Curvature of Log-Likelihood -- 8.1.3 CRB for Multiple Parameters (p≥1) -- 8.2 Interpretation of CRB and Remarks -- 8.2.1 Variance of Each Parameter -- 8.2.2 Compactness of the Estimates -- 8.2.3 FIM for Known Parameters -- 8.2.4 Approximation of the Inverse of FIM -- 8.2.5 Estimation Decoupled From FIM -- 8.2.6 CRB and Nuisance Parameters -- 8.2.7 CRB for Non-Gaussian rv and Gaussian Bound -- 8.3 CRB and Variable Transformations -- 8.4 FIM for Gaussian Parametric Model xN(μ(θ),C(θ)) -- 8.4.1 FIM for x=s(θ)+w with wN(0,Cw) -- 8.4.2 FIM for Continuous-Time Signals in Additive White Gaussian Noise -- 8.4.3 FIM for Circular Complex Model -- Appendix A: Proof of CRB -- Appendix B: FIM for GaussianModel -- Appendix C: Some Derivatives for MLE and CRB Computations…”

Tabla de Contenidos: “…7.3.3 Methodology Flow Chart -- 7.3.4 Data Pre-Processing -- 7.3.5 Models Deployed -- 7.3.6 Training and Testing -- 7.4 Analysis -- 7.4.1 Datasets -- 7.4.2 Feature Extraction -- 7.4.3 Splitting of Data into Samples -- 7.4.4 Algorithms Used -- 7.4.4.1 Multinomial Logistic Regression -- 7.4.4.2 K-Nearest Neighbors -- 7.4.4.3 Decision Tree -- 7.4.4.4 Support Vector Machine (SVM) -- 7.4.4.5 Random Forest -- 7.5 Results and Discussion -- 7.5.1 Importance of Classification Reports -- 7.5.2 Importance of Confusion Matrices -- 7.5.3 Decision Tree -- 7.5.4 Random Forest -- 7.5.5 K-Nearest Neighbors -- 7.5.6 Logistic Regression -- 7.5.7 Support Vector Machine -- 7.5.8 Comparison of the Algorithms -- 7.5.8.1 Accuracies -- 7.5.8.2 Precision and Recall -- 7.6 Conclusions -- 7.7 Scope of Future Work -- References -- Chapter 8 Smart Vision-Based Sensing and Monitoring of Power Plants for a Clean Environment -- 8.1 Introduction -- 8.1.1 Color Image Processing -- 8.1.2 Motivation -- 8.1.3 Objectives -- 8.2 Literature Review -- 8.2.1 Gas Turbine Power Plants -- 8.2.2 Artificial Intelligent Methods -- 8.3 Materials and Methods -- 8.3.1 Feature Extraction -- 8.3.2 Classification -- 8.4 Results and Discussion -- 8.4.1 Fisher's Linear Discriminant Function (FLDA) and Curvelet -- 8.5 Conclusion -- 8.5.1 Future Scope of Work -- References -- Chapter 9 Implementation of FEM and Machine Learning Algorithms in the Design and Manufacturing of Laminated Composite Plate -- Abbreviations -- 9.1 Introduction -- 9.2 Numerical Experimentation Program -- 9.3 Discussion of the Results -- 9.4 Conclusion -- Acknowledgements -- References -- Part II: Integration of Digital Technologies to Operations -- Chapter 10 Edge Computing-Based Conditional Monitoring -- 10.1 Introduction -- 10.1.1 Problem Statement -- 10.2 Literature Review -- 10.3 Edge Computing -- 10.4 Methodology…”