Tabla de Contenidos: “…Fundamentals of Sequential System Monitoring and Prognostics Methods -- 3.1 Fundamentals -- 3.1.1 Prognostics and SHM -- 3.1.2 Damage response modelling -- 3.1.3 Interpreting uncertainty for prognostics -- 3.1.4 Prognostic performance metrics -- 3.2 Bayesian tracking methods -- 3.2.1 Linear Bayesian Processor: The Kalman Filter -- 3.2.2 Unscented Transformation and Sigma Points: The Unscented Kalman Filter -- 3.2.3 Sequential Monte Carlo methods: Particle Filters -- 3.2.3.1 Sequential importance sampling -- 3.2.3.2 Resampling -- 3.3 Calculation of EOL and RUL -- 3.3.1 The failure prognosis problem -- 3.3.2 Future state prediction -- 3.4 Summary…”

Tabla de Contenidos: “…6.3.2.1 Data augmentation based on domain knowledge of optical communication -- 6.3.2.1.1 Data augmentation on polarization state -- 6.3.2.1.2 Data augmentation on the frequency offset -- 6.3.2.2 Transfer learning for adaptation of DNNs -- 6.3.2.3 Federated learning for collaborative DNN training over multiple operators -- 6.3.3 Inference mode of DL-based optical monitors -- 6.3.4 Advanced topics for inference modes of DL-based optical monitors -- 6.3.4.1 Cloud-based vs. edge-based implementations -- 6.3.4.1.1 Cloud-based implementation of inference mode -- 6.3.4.1.2 Edge-based implementation of inference mode -- 6.3.4.2 Estimating the model uncertainty in inference mode -- 6.4 Tips for designing DNNs for DL-based optical monitoring -- 6.4.1 Shallow vs. deep network -- 6.4.2 DNN architecture for optical monitoring -- 6.4.2.1 Fully-connected DNNs -- 6.4.2.2 Convolutional neural networks -- 6.4.2.3 DNN architecture for the optical monitoring -- 6.5 Experimental verifications -- 6.5.1 Experimental setup for data collection -- 6.5.2 Neural network architecture for OSNR estimation task -- 6.5.2.1 DNN used in this experiment -- DNN #1 (FC-DNN): -- DNN #2 (CNN-1): -- 6.5.2.2 Results and discussion -- 6.5.3 Detailed experimental evaluation of CNN-based OSNR estimators -- 6.5.3.1 DNN used in this section -- DNN #3 (CNN-2): -- 6.5.3.2 Results and discussion -- 6.5.4 Versatile monitoring using DNN -- 6.5.4.1 DNN architecture used in this experiment -- DNN #4 (CNN-3): -- 6.5.4.2 Results and discussion -- 6.5.5 Data augmentation based on domain knowledge of optical transceivers -- 6.5.5.1 DNN used in this section -- DNN #5 (CNN-4): -- 6.5.5.2 Results and discussion -- 6.5.6 Estimating uncertainty by dropout at inference -- 6.5.6.1 DNN used in this experiment -- DNN #6 (CNN-5): -- 6.5.6.2 Results and discussion…”

Tabla de Contenidos: “…Accelerating into the Region Best Positioned to Bounce Back -- Our Employees Came Through for Us -- Uptick Thanks to New Business Models -- Transparency, Even About Uncertainty -- What's Ahead? -- The Future of the Industry and Global Business -- About the Contributors -- GOGOX -- About GOGOX -- Backdrop -- First Signs of COVID-19 -- Navigating the Great Lockdown -- The Logistics Flywheel -- People Management in the New Normal -- What We Learned from COVID-19 -- Reverse Engineering -- Future Outlook -- About the Contributors -- Hornet -- About Hornet -- Backdrop: Social Networking for the Gay Community -- First Signs: March 2020 -- During the Great Lockdown of 2020-21 -- Navigating the Great Lockdown -- What the Organization Did for Liquidity -- What the Organization Did with People -- What the Organization Did with Investment Plans -- What Happened Across Regional Markets -- Future Outlook -- Learnings from the Great Lockdown -- About the Contributor -- IndiGrid -- About IndiGrid -- Backdrop -- During the Lockdown -- Future Outlook -- Ready for the Future -- About the Contributor -- Julius Baer -- About Julius Baer -- Backdrop: Wealth Management Industry and Julius Baer Before the Great Lockdown -- First Signs: When COVID-19 Hit the Wealth Management Industry and Julius Baer -- During the Great Lockdown -- Future Outlook -- Learnings from the Great Lockdown -- About the Contributors -- RealWear, Inc -- About RealWear -- The Early Days of the Pandemic -- Navigating the Great Lockdown: The Race to Adapt -- Success Story: How Goodyear Fueled Collaboration with the HMT-1 -- Learnings from the Great Lockdown: Going Forward to Work -- About the Contributors -- SAP -- About SAP -- Introduction -- Backdrop: The Pre-COVID-19 Era -- Growth Strategy -- Goals for Sustained Business Success…”

“…In a time of so much uncertainty, understanding the implications of the shifting energy landscape for economic and environmental goals and for energy security is vital. …”

“…It explains how India's financial markets work, discusses the amazing growth of the Indian economy, identifies growth drivers, uncovers areas of uncertainty and risk. It describes how each market works: private equity and IPOs, bonds, stocks, derivatives, commodities, real estate, currency. …”

Tabla de Contenidos: “…Introduction to Renewable Energy Systems / An Overview of Renewable Energy Systems -- Climate Change -- Renewable Energy Trend -- Types of Renewable Energy Systems -- Introduction -- Wind Power -- Solar Energy -- Geothermal Power -- Hydro Power -- Bioenergy -- Ocean Power -- Economic Aspects of Renewable Energy Systems -- Introduction -- Affecting Factors -- Life-Cycle Costs -- Economic Trend of Renewable Energy Systems -- Opportunities and Challenges of Renewable Energy Systems Integration -- Renewable Energy Systems Integration Opportunities -- Renewable Energy Systems Integration Challenges and Barriers -- Alleviating the Challenges and Barriers -- Current Trends and Future Prospects -- The Need for Optimization Tools to Solve Problems Related to Renewable Energy Systems -- Conclusions -- Acknowledgments -- References -- Introduction to Optimization / Introduction -- Formulation of Optimization Problem -- General Models of Optimization Problems -- Convex Optimization -- Basic Concepts and Models of Linear Optimization -- Solution Techniques for Unconstrained Optimization -- Nelder -- Mead Method -- Golden Section Search -- Fibonacci Search -- Hooke and Jeeves' Method -- Gradient Descent Method -- Coordinate Descent Method -- Solution Techniques for Constrained Optimization and Relevant Applications to Renewable Energy Systems -- Genetic Algorithm -- Particle Swarm Optimization -- Simulating Annealing -- Ant Colony Optimization -- Tabu Search -- Firefly Algorithm -- Artificial Bee Colony Algorithm -- Artificial Immune System -- Game Theory -- Simplex Technique Specifically for Mixed Integer Linear Programming Concept -- Optimal Control Technique -- Conclusion and Discussion -- References -- Optimal Procurement of Contingency and Load Following Reserves by Demand Side Resources Under Wind-Power Generation Uncertainty / Introduction -- Mathematical Model -- Overview and Modeling Assumptions -- Objective Function -- Constraints -- Case Studies -- Wind-Power Production Scenario Generation -- Illustrative Example -- Application on a 24-Bus System -- Computational Statistics -- Conclusions -- Appendix A: 24-Bus System Test System Data -- Nomenclature -- Sets and Indices -- Parameters -- Variables -- References -- Optimum Bidding of Renewable Energy System Owners in Electricity Markets / Renewable Energy System Owners in Electricity Markets -- Electricity Market Overview -- Importance of Integrating Renewables into the Electricity Market -- Current Market Rules for Renewable Energy System Owners in North America -- Price-Taker Models -- Multistage Stochastic Programming Approach -- Multistage Stochastic Programming Approach -- Scenario Generation and Reduction Method -- Risk Management -- Bidding Strategy Models for Price-Taker Renewable Energy Owner -- Mitigating the Trading Risk by Purchasing Additional Power from Conventional Energy Owner -- Price-Maker Models -- MPEC Approach -- Why Consider Wind Power Energy Owners as Price-Makers? …”

Tabla de Contenidos: “…The Changing Landscape -- Creating Responsible and Engaged Students -- Universities Can Regain the Public’s Trust -- Towards the Other Side of Complexity: Values and Decisions in a Time of Uncertainty -- Africa’s Destiny and Higher Education Transformation -- The Constant of Change: Remaining Relevant in 21st Century Higher Education -- The Changing Role of Universities in Lithuanian Society -- Modern Challenges for Universities -- Universities in an Era of Post-Corona “New Order” -- Redefining the Role of Universities in a Rapidly Changing Landscape -- From Emergency Remote Teaching to Strategically Embracing Online Learning -- Overcoming Challenges and Boundaries Through the Innovation of University Learning and Teaching Practices -- Is the Pandemic Leading to a Paradigm Shift in Higher Education? …”

Tabla de Contenidos: “…10.2.1 Fear and Resistance10.2.2 Rational Insight and Emotional Acceptance; 10.2.3 Applying the New Behaviors; 10.2.4 Learning and Integration; Chapter 11 Emotions in Change Processes; 11.1 Uncertainty, Worry, and Anxiety; 11.2 Anger and Aggression; 11.3 Sadness and Disappointment; 11.4 Enthusiasm, Joy, and Courage; Chapter 12 Corporate Culture and Politics; 12.1 The Power of Corporate Culture; 12.2 Corporate Culture and Micropolitics; Chapter 13 Conclusions for Kanban Change Leadership; 13.1 Mindfulness; 13.1.1 A New Paradigm for Management and Leadership; 13.2 Communication…”

Tabla de Contenidos: “…11.1 Introduction11.2 Closed-World Reasoning; 11.3 Circumscription; 11.4 Default Logic; 11.5 Autoepistemic Logic; 11.6 Conclusion; 11.7 Bibliographic Notes; 11.8 Exercises; Chapter 12. Vagueness, Uncertainty, and Degrees of Belief; 12.1 Noncategorical Reasoning; 12.2 Objective Probability; 12.3 Subjective Probability; 12.4 Vagueness; 12.5 Bibliographic Notes; 12.6 Exercises; Chapter 13. …”

Tabla de Contenidos: “…2.2 Brief Overview of Cindynics2.2.1 Basic Concepts; 2.2.2 Dysfunctions; 2.2.3 General principles and axioms; 2.2.4 Perspectives; Bibliography; 2.3 Risk Assessment or Exposure Diagnostic; 2.3.1 Foreword; 2.3.2 Threats and Opportunities: How to deal with uncertainty in a changing world?; 2.3.3 How to Manage the Risks Derived From Partners Resources?…”

Tabla de Contenidos: “…Preference -- 101 Phonetic Symbolism -- 102 Picture Superiority Effect -- 103 Priming -- 104 Progressive Disclosure -- 105 Propositional Density -- 106 Prospect-Refuge -- 107 Prototyping -- 108 Proximity -- 109 Readability -- 110 Reciprocity -- 111 Recognition Over Recall -- 112 Red Effects -- 113 Redundancy -- 114 Root Cause -- 115 Rosetta Stone -- 116 Rule of Thirds -- 117 Saint-Venant's Principle -- 118 Satisficing -- 119 Savanna Preference -- 120 Scaling Fallacy -- 121 Scarcity -- 122 Selection Bias -- 123 Self-Similarity -- 124 Serial Position Effects -- 125 Shaping -- 126 Signal-to-Noise Ratio -- 127 Similarity -- 128 Social Trap -- 129 Stickiness -- 130 Storytelling -- 131 Structural Forms -- 132 Sunk Cost Effect -- 133 Supernormal Stimulus -- 134 Symmetry -- 135 Threat Detection -- 136 Top-Down Lighting Bias -- 137 Uncanny Valley -- 138 Uncertainty Principle -- 139 Uniform Connectedness -- 140 Veblen Effect -- 141 Visibility -- 142 Visuospatial Resonance -- 143 von Restorff Effect -- 144 Wabi-Sabi -- 145 Waist-to-Hip Ratio -- 146 Wayfinding -- 147 Weakest Link -- 148 White Effects -- 149 Yellow Effects -- 150 Zeigarnik Effect -- Credits -- Acknowledgments -- About the Authors -- Dedication -- Copyright…”

Tabla de Contenidos: “…Asking and Answering Research Questions -- A Simple Opinion Poll -- Further Intuitions -- Quiz 1.1 -- Careful Thinking About Uncertainty -- The Replicability Crisis and Open Science -- Meta-Analysis -- A Step-by-Step Plan for Estimation -- Quiz 1.2 -- Reporting Your Work -- Take-Home Messages -- End-of-Chapter Exercises -- Answers to Quizzes -- Answers to In-Chapter Exercises -- 2. …”

Tabla de Contenidos: “…-- Is There Significant Uncertainty About The Effectiveness Of The Proposed Treatment? …”

“…Unlock progress through doubt and uncertainty The biggest threat facing modern business is the sheer complexity of an uncertain future. …”

“…It continues to pose major challenges to national policymakers and institutions around the world. Managing public uncertainty and anxiety is vital in coping with financial crises. …”

Tabla de Contenidos: “…3.1.1 Population and Sample3.1.2 Distribution of Values; 3.2 Important Terms; 3.2.1 Mean, Arithmetic Mean, Average (); 3.2.2 Standard Deviation (σ, s); 3.2.3 Variance (Var,V); 3.2.4 Standard Deviation of Mean Values (); 3.2.5 Relative Standard Deviation (RSD) and Coefficient of Variation (CV); 3.2.6 Confidence Interval (CI), Confidence Limits; 3.3 Quality of Results (Accuracy and Precision); 3.3.1 Measurement Deviations; 3.3.2 Random Deviations - Influence on Precision; 3.3.3 Systematic Deviations - Influence on Accuracy; 3.3.4 Gross Errors; 3.3.5 Uncertainty of Measurement Results…”

Tabla de Contenidos: “…Networks for sequence data -- RNNs and LSTMs -- Building a better optimizer -- Gradient descent to ADAM -- Xavier initialization -- Summary -- References -- Chapter 4: Teaching Networks to Generate Digits -- The MNIST database -- Retrieving and loading the MNIST dataset in TensorFlow -- Restricted Boltzmann Machines: generating pixels with statistical mechanics -- Hopfield networks and energy equations for neural networks -- Modeling data with uncertainty with Restricted Boltzmann Machines -- Contrastive divergence: Approximating a gradient -- Stacking Restricted Boltzmann Machines to generate images: the Deep Belief Network -- Creating an RBM using the TensorFlow Keras layers API -- Creating a DBN with the Keras Model API -- Summary -- References -- Chapter 5: Painting Pictures with Neural Networks Using VAEs -- Creating separable encodings of images -- The variational objective -- The reparameterization trick -- Inverse Autoregressive Flow -- Importing CIFAR -- Creating the network from TensorFlow 2 -- Summary -- References -- Chapter 6: Image Generation with GANs -- The taxonomy of generative models -- Generative adversarial networks -- The generator model -- Training GANs -- Non-saturating generator cost -- Maximum likelihood game -- Vanilla GAN -- Improved GANs -- Deep Convolutional GAN -- Vector arithmetic -- Conditional GAN -- Wasserstein GAN -- Progressive GAN -- The overall method -- Progressive growth-smooth fade-in -- Minibatch standard deviation -- Equalized learning rate -- Pixelwise normalization -- TensorFlow Hub implementation -- Challenges -- Training instability -- Mode collapse -- Uninformative loss and evaluation metrics -- Summary -- References -- Chapter 7: Style Transfer with GANs -- Paired style transfer using pix2pix GAN -- The U-Net generator -- The Patch-GAN discriminator -- Loss -- Training pix2pix -- Use cases…”

Tabla de Contenidos: “…Loading the libraries -- Understanding and preparing the data -- Assessing time series models with traditional interpretation methods -- Generating LSTM attributions with integrated gradients -- Computing global and local attributions with SHAP's KernelExplainer -- Identifying influential features with factor prioritization -- Quantifying uncertainty and cost sensitivity with factor fixing -- Mission accomplished -- Summary -- Dataset and image sources -- References -- Section 3: Tuning for Interpretability -- Chapter 10: Feature Selection and Engineering for Interpretability -- Technical requirements -- The mission -- The approach -- The preparations -- Loading the libraries -- Understanding and preparing the data -- Understanding the effect of irrelevant features -- Reviewing filter-based feature selection methods -- Basic filter-based methods -- Correlation filter-based methods -- Ranking filter-based methods -- Comparing filter-based methods -- Exploring embedded feature selection methods -- Discovering wrapper, hybrid, and advanced feature selection methods -- Wrapper methods -- Hybrid methods -- Advanced methods -- Evaluating all feature-selected models -- Considering feature engineering -- Mission accomplished -- Summary -- Dataset sources -- Further reading -- Chapter 11: Bias Mitigation and Causal Inference Methods -- Technical requirements -- The mission -- The approach -- The preparations -- Loading the libraries -- Understanding and preparing the data -- Detecting bias -- Visualizing dataset bias -- Quantifying dataset bias -- Quantifying model bias -- Mitigating bias -- Pre-processing bias mitigation methods -- In-processing bias mitigation methods -- Post-processing bias mitigation methods -- Tying it all together! …”

Tabla de Contenidos: “…Religious Values and Beliefs -- Uncertainty About the Future -- Post-Traumatic Growth and Resilience -- Conclusion -- References -- 7 Collective Resilience and Imagination -- Collective Resilience Among Displaced Populations -- Imagination, Trauma and Migration -- Imagination from a Sociocultural Perspective -- Case Study: Resilience and Imagination Among Victims of Torture in Athens, Greece -- The Case of Jules -- Discussion -- Conclusion -- References -- 8 Collective Aspirations -- Case Study: Collective Aspirations of Refugees in Europe -- Analysis -- The Case of Mr B -- Discussion -- Conclusion -- References -- 9 Working with Shame and Trauma -- Migration and Post-traumatic Shame -- Cultural Manifestations of Shame and Implications for Clinicians -- Case Study One: Research Among Displaced Victims of Torture in Athens, Greece -- Applied Approach to Dealing with Shame: The Case of Sylvain -- The Shame of Dependence -- Implications for Transformation -- The Shame of Social Discrimination -- Implications for Transformation -- The Shame of Being Unemployed -- Implications for Transformation -- Case Study Two: Female Survivors of Sexual Violence in Cape Town, South Africa -- Analysis -- Conclusion -- References -- 10 Working with Cultural Mediators -- Case Study: Cultural Mediation Among Victims of Torture in Athens -- Cultural Mediators as Negotiating Different Interpretations of Trauma -- Translation: Accuracy Versus Interpretation -- A Game of Alliances Between Refugees and Health Professionals -- Working with Health Professionals Perceived as "Culturally Inexperienced" -- Conclusion -- References -- 11 Working with PTSD in the Asylum Procedure -- PTSD Among Refugee Populations -- The Importance of Correctly Identifying Trauma in the Refugee Determination Process -- PTSD and the Question of Legal Causality…”

“…In each section, they will be introduced and given proven tools and frameworks Jeanette has designed to help navigate FUD (fear, uncertainty, and doubt) including, the "Power Pause," the "C.A.R.E. …”