Tabla de Contenidos: “…HTEP Applications; Airbus A380 Jumbo Jet; HTEP Opportunity with Bananas; Tropical Storm Disruption; BP Oil Explosion; Ford Supply Chain; Dell Supply Chain; Chilean Mine Rescue; Conclusion; 11. Product Launch Application; Market Risk; Product Risk; Capital Risk; Intellectual Property Risk; Risk Profile; Expanding the View; Conclusion; Part Three. …”

Tabla de Contenidos: “…; Chapter 12 - How do I Respond to Feelings (Mine and My Client's)?; Part III - Interviewing; Chapter 13 - How do I Interview Young Children about Suspected Sexual Abuse?…”

Tabla de Contenidos: “…-- We Need More Than Technology -- Part I Why Cybersecurity Needs Better Measurements for Risk -- Chapter 1 The One Patch Most Needed in Cybersecurity -- Insurance: A Canary in the Coal Mine -- The Global Attack Surface -- The Cyber Threat Response -- A Proposal for Cybersecurity Risk Management -- Notes -- Chapter 2 A Measurement Primer for Cybersecurity -- The Concept of Measurement -- A Taxonomy of Measurement Scales -- The Object of Measurement -- The Methods of Measurement -- Notes -- Chapter 3 The Rapid Risk Audit: Starting With a Simple Quantitative Risk Model -- The Setup and Terminology -- The Rapid Audit Steps -- Some Initial Sources of Data -- The Expert as the Instrument -- Supporting the Decision: Return on Controls -- Doing "Uncertainty Math" -- Visualizing Risk With a Loss Exceedance Curve -- Where to Go from Here -- Notes -- Chapter 4 The Single Most Important Measurement in Cybersecurity -- The Analysis Placebo: Why We Can't Trust Opinion Alone -- How You Have More Data than You Think -- When Algorithms Beat Experts -- Tools for Improving the Human Component -- Summary and Next Steps -- Notes -- Chapter 5 Risk Matrices, Lie Factors, Misconceptions, and Other Obstacles to Measuring Risk -- Scanning the Landscape: A Survey of Cybersecurity Professionals -- What Color Is Your Risk? …”

Tabla de Contenidos: “…Trust What You Love to Do Leave People More Energized; Let's Recap; Chapter 3: Inquiry: Provoke with Questions, Not Answers; Start with a Growth Mindset; Get Curious; Exercise Divergent Thinking; Choose Optimism; Close the Organizational Inquiry Gap; Narrow Choices; Let's Recap; Chapter 4: Exploration: Go to the Woodshed; Accomplish More through Grit; Put a Stake in the Ground; Allow Time for Focusing; Mine the Organization for Expertise; Reinforce Company Culture by Capturing Internal Voices of Distinction; Deal with Innovation Blockers; Let's Recap…”

Tabla de Contenidos: “…About this book -- STEP -- Worked Problems ; Worked problem 1 ; Worked problem 2 ; Problems-- ‡a P1 An integer equation P2 Partitions of 10 and 20 P3 Mathematical deduction P4 Divisibility P5 The modulus function P6 The regular Reuleaux heptagon P7 Chain of equations P8 Trig. equations P9 Integration by substitution P10 True or false P11 Egyptian fractions P12 Maximising with constraints P13 Binomial expansion P14 Sketching subsets of the plane P15 More sketching subsets of the plane P16 Non-linear simultaneous equations P17 Inequalities P18 Inequalities from cubics P19 Logarithms P20 Cosmological models P21 Melting snowballs P22 Gregory's series P23 Intersection of ellipses P24 Sketching x m ( 1 - x ) n P25 Inequalities by area estimates P26 Simultaneous integral equations P27 Relation between coefficients of quartic for real roots P28 Fermat numbers P29 Telescoping series P30 Integer solutions of cubics P31 The harmonic series P32 Integration by substitution P33 More curve sketching P34 Trig sum P35 Roots o ‡a f a cubic equation P36 Root counting P37 Irrationality of e P38 Discontinuous integrands P39 A difficult integral P40 Estimating the value of an integral P41 Integrating the modulus function P42 Geometry P43 The t substitution P44 A differential-difference equation P45 Lagrange's identity P46 Bernoulli polynomials P47 Vector geometry P48 Solving a quartic P49 Areas and volumes P50 More curve sketching P51 Spherical loaf P52 Snowploughing P53 Tortoise and hare P54 How did the chicken cross the road? P55 Hank's gold mine P56 A chocolate orange P57 Lorry on bend P58 Fielding P59 Equilibrium of rod of non-uniform density P60 Newton's cradle P61 Kinematics of rotating target P62 Particle on wedge P63 Sphere on step P64 Elastic band on cylinder P65 A knock-out tournament P66 Harry the calculating horse P67 PIN guessing P68 Breaking plates P69 Lottery P70 Bodies in the fridge P71 Choosing keys P72 Commuting by train P ‡a 73 Collecting voles P74 Breaking a stick P75 Random quadratics -- Syllabus…”

Tabla de Contenidos: “…; IoT reference model; IoT platforms; IoT verticals; Big data and IoT; Infusion of AI -- data science in IoT; Cross-industry standard process for data mining; AI platforms and IoT platforms; Tools used in this book; TensorFlow; Keras; Datasets; The combined cycle power plant dataset; Wine quality dataset; Air quality data; Summary; Chapter 2: Data Access and Distributed Processing for IoT; TXT format Using TXT files in PythonCSV format; Working with CSV files with the csv module; Working with CSV files with the pandas module; Working with CSV files with the NumPy module; XLSX format; Using OpenPyXl for XLSX files; Using pandas with XLSX files; Working with the JSON format; Using JSON files with the JSON module; JSON files with the pandas module; HDF5 format; Using HDF5 with PyTables; Using HDF5 with pandas; Using HDF5 with h5py; SQL data; The SQLite database engine; The MySQL database engine; NoSQL data; HDFS; Using hdfs3 with HDFS; Using PyArrow's filesystem interface for HDFS; Summary; Chapter 3: Machine Learning for IoTML and IoT; Learning paradigms; Prediction using linear regression; Electrical power output prediction using regression; Logistic regression for classification; Cross-entropy loss function; Classifying wine using logistic regressor; Classification using support vector machines; Maximum margin hyperplane; Kernel trick; Classifying wine using SVM; Naive Bayes; Gaussian Naive Bayes for wine quality; Decision trees; Decision trees in scikit; Decision trees in action; Ensemble learning; Voting classifier; Bagging and pasting; Improving your model -- tips and tricksFeature scaling to resolve uneven data scale; Overfitting; Regularization; Cross-validation; No Free Lunch theorem; Hyperparameter tuning and grid search; Summary; Chapter 4: Deep Learning for IoT; Deep learning 101; Deep learning-why now?…”

Tabla de Contenidos: “…No Longer an Underutilized Business Asset -- Organizational Alignment -- Executive Sponsors -- Existing Clients -- Incremental Revenue -- Business Effectiveness -- Chapter 9 ERG Analytics -- Data‐Driven Insights -- Normative Database Mining -- ERG Leadership Roles Need to Be Highly Desired -- Appoint Your ERG Leaders to Top Grade the Role -- ERGs Are an Underutilized Asset -- Professional Development Across the Career Continuum Is Lacking -- ERGs Are Not Benchmarking Adequately -- Not All Business Units Value ERGs -- Career and Commerce Are Key -- Chapter 10 ERG Metrics‐That‐Matter -- Measuring ERG Impact and Excellence -- Key Measurement Principles -- ERG Metrics‐That‐Matter -- Chapter 11 High Performers and High Potentials -- ERGs and Talent Management -- ERG Ownership -- ERG Membership -- Leadership Development Mechanisms -- ERG Leader Competencies -- High Performance -- Business Credibility -- Strategic Mindset -- Ability to Develop Others -- Building Effective Teams -- Transitioning to an Appointment Process -- Executive Sponsor Buy-In -- Communicating the Reason for Change -- Alignment with Talent Management -- Chapter 12 Strategic Planning -- Using the Google Maps Approach -- First, Determine ERG Current State -- Next, Establish a Desired Future State -- Finalize Your Strategic Plan -- Chapter 13 Next‐Generation ERGs -- The ERG Excellence Manifesto -- About The Author -- Index -- EULA…”

Tabla de Contenidos: “…COVID-19: Classification of Countries for Analysis and Prediction of Global Novel Corona Virus Infections Disease Using Data Mining Techniques / Sachin Kamley, Shailesh Jaloree, RS Thakur, Kapil Saxena -- Sentiment Analysis on Social Media for Emotional Prediction During COVID-19 Pandemic Using Efficient Machine Learning Approach / Kalimuthu Sivanantham -- Primary Healthcare Model for Remote Area Using Self-Organizing Map Network / Sayan Das, Jaya Sil -- Face Mask Detection in Real-Time Video Stream Using Deep Learning / Alok Negi, Krishan Kumar -- A Computational Intelligence Approach for Skin Disease Identification Using Machine/Deep Learning Algorithms / Swathi Jamjala Narayanan, Pranav Raj Jaiswal, Ariyan Chowdhury, Amitha Maria Joseph, Saurabh Ambar -- Asymptotic Patients' Healthcare Monitoring and Identification of Health Ailments in Post COVID-19 Scenario / Pushan KR Dutta, Akshay Vinayak, Simran Kumari -- COVID-19 Detection System Using Cellular Automata-Based Segmentation Techniques / Rupashri Barik, M Nazma, B J Naskar, Sarbajyoti Mallik -- Interesting Patterns From COVID-19 Dataset Using Graph-Based Statistical Analysis for Preventive Measures / C B Abhilash, Kavi Mahesh -- Prospective of Computational Intelligence in Healthcare. …”

Tabla de Contenidos: “…-- Paul's Tree -- From the Top -- My Cuppa Tea -- Yours Forever -- Pit Stops -- Many Hands -- Caffeine Start -- Happy Anniversary -- Welcome -- Studies Paid Off -- Small Thing, Big Smile -- Royal TNT -- Bowled Over -- Dzikuj Ci -- With Love -- Highflyer -- From Fran -- Seasonal Thoughts -- Father-Daughter Inspiration -- Mine's a 99 -- Hugs Online -- Feeling Appreciated -- Caring Bosses -- Sincere Thanks -- At Home -- Kosta's Coffee Mug -- Sent Home -- For Everyone -- Family Business -- Two Sugars? …”

Tabla de Contenidos: “…Receipts from petroleum and minerals; Figure 1.8. Oil and gas versus mining value added; Figure 1.9. Average government take in oil and gas fiscal regimes; Taxes on international trade; Consumption taxes; Figure 1.10. …”

Tabla de Contenidos: “…How Investors May Be Fooled by Earnings, But Not by Cash FlowUnderstanding the Fundamentals of Free Cash Flow; Chapter 8: Using Financial Ratios to Pinpoint Investments; Using Financial Ratios to Find Out What's Really Going on at a Company; Getting Familiar with the Price-to-Earnings Ratio; Putting the P-E into Perspective; Chapter 9: Mining the Proxy Statement for Investment Clues; Getting up to Speed with What the Proxy Statement Is; Expanding Fundamental Analysis Beyond the Numbers; Stepping Through the Proxy; How Much Are We Paying You? …”

Tabla de Contenidos: “…Section HeadingsQuestions Posing as Section Headings; Step Headings; Button Labels; Messages; Error Messages; General Instructions; Yours or Mine?; Start Without Pronouns; Where Pronouns Can Be Helpful; Referring to More Than Two Parties; Words That Work; Layout; A Mantra: It's All about Balance; For Realz; Abbreviations; Choose Your Field Types; Problems with Using "Enhancements" to Answer Field Types; Issues with Dropdowns; What to Use Instead of a Dropdown; Long Lists of Options; Implementing Country Text Box with Auto-suggest; Segmented Controls and Switches…”

Tabla de Contenidos: “…-- LSTM and GRU networks -- LSTM -- GRU -- RNNs from scratch in R -- Classes in R with R6 -- Perceptron as an R6 class -- Logistic regression -- Multi-layer perceptron -- Implementing a RNN -- Implementation as an R6 class -- Implementation without R6 -- RNN without derivatives - the cross-entropy method -- RNN using Keras -- A simple benchmark implementation -- Generating new text from old -- Exercises -- Summary -- Chapter 5: Sentiment Analysis with Word Embeddings -- Warm-up - data exploration -- Working with tidy text -- The more, the merrier - calculating n-grams instead of single words -- Bag of words benchmark -- Preparing the data -- Implementing a benchmark - logistic regression -- Exercises -- Word embeddings -- word2vec -- GloVe -- Sentiment analysis from movie reviews -- Data preprocessing -- From words to vectors -- Sentiment extraction -- The importance of data cleansing -- Vector embeddings and neural networks -- Bi-directional LSTM networks -- Other LSTM architectures -- Exercises -- Mining sentiment from Twitter -- Connecting to the Twitter API -- Building our model -- Exploratory data analysis -- Using a trained model -- Summary -- Other Books You May Enjoy -- Index…”

Tabla de Contenidos: “…Introduction to Android Performance; Performance Matters to Your Users; Ecommerce and Performance; Beyond Ecommerce Sales; Performance Infrastructure Savings; The Ultimate Performance Fail: Outages; Performance as a Rolling Outage; Consumer Reaction to Performance Bugs; Smartphone Battery Life: The Canary in the Coal Mine…”

Tabla de Contenidos: “…The semantic moduleThe process engine; Node instance structures; Components inside jBPM6; Transactions and persistence; Audit/History logs; Real-time dashboards; Data mining and data analysis tools; The KIE APIs; KIE services; The KIE module; The KIE container; The KIE base; The KIE session; External interactions; The Human task component; Human tasks - life cycle; Human tasks - APIs; The User/Group callback; The BPMS ecosystem; BPM and service-oriented architecture; Service orchestration; Enterprise Service Bus; Rule engines; Classic BPM system and rule engine integration…”

Tabla de Contenidos: “…Chapter 10: Leveraging the Prospecting PyramidWalk Like an Egyptian: Managing the Prospecting Pyramid; Powerful Lists Get Powerful Results; Chapter 11: Own Your Database: Why the CRM Is Your Most Important Sales Tool; Own It Like a CEO; A Trash Can or a Gold Mine; Chapter 12: The Law of Familiarity; Prospecting Lubrication; The Five Levers of Familiarity; Chapter 13: Social Selling; Social Selling Is Not a Panacea; The Social Selling Challenge; Social Selling Is Not Selling; Choosing the Right Social Channels; Five Objectives of Social Prospecting; Personal Branding; Building Familiarity…”

Tabla de Contenidos: “…Export capacity investment outlook; Summary; Investment in export mining capacity; Investment in export infrastructure capacity; Regional analysis; Australia; Colombia; South Africa; Mozambique; Russia; Indonesia; Canada; United States; References; Annex; Glossary; Regional and country groupings; Africa; China; Europe and Mediterranean; Latin America; Non-OECD Europe/Eurasia; North Africa; OECD; OECD Americas; OECD Asia Oceania; OECD Europe; Other developing Asia…”

Tabla de Contenidos: “…Fong -- Smart ecology of cities : integrating development impacts on ecosystem services / Marc Morrison, Ravi Srinivasan, Cynnamon Dobbs -- Data driven modeling, control and tools for smart cities / Madhur Behl, Rahul Mangharam -- Bringing named data networks into smart cities / Syed Hassan Ahmed, Safdar Hussain Bouk, Dongkyun Kim, Mahasweta Sarkar -- Human context sensing in smart cities / Juhi Ranjan, Kamin Whitehouse -- Smart cities and the symbiotic relationship between citizen engagement and smart governance / Tori Onker -- Smart economic development / Madhavi Venkatesan -- Managing the cyber security life-cycle of smart cities / Mridul Sankar Barik, Anirban Sengupta, Chandan Mazumdar -- Mobility as a service / Christopher Expâosito-Izquierdo, Airam Expâosito-Mâarquez, Julio Brito-Santana -- Clustering and fuzzy reasoning as data mining methods for the development of retrofit strategies for building stocks / Philipp Geyer, Arno Schlèuter -- A framework to achieve large scale energy savings for building stocks through targeted occupancy interventions / Aslihan Karatas, Allisandra Stoiko, Carol Menassa -- Smart cities sustainability assessment : balancing social, economic, and environmental performance / Ali Komeily, Ravi Srinivasan -- Resilient electric grid for smart cities / Jiankang Wang -- Smart energy and grid : novel approaches for the efficient generation, storage and usage of energy in the smart home and the smart grid link-up / Julian Prass, Johannes Weber, Sebastian Staub, Johannes Bèurner, Ralf Bèohm, Thomas Braun, Moritz Hein, Markus Michl, Michael Beck, Jèorg Franke -- Building cyber-physical systems : a smart building use case / Jupiter Bakakeu, Franziska Schèafer, Jochen Bauer, Markus Michl, Jèorg Franke -- Climate resilience and the design of smart buildings / Saranya Gunasingh, Nora Wang, Doug Alh, Scott Schuetter -- Smart audio sensing based HVAC monitoring / Nirjon Shahriar, Ravi Srinivasan, Tamim Sookoor -- Smart lighting / Jie Lian -- Large-scale air quality monitoring in smart and sustainable cities / Xiaofan Jiang -- The smart city production system / Patrick Hennelly, Roy Meriton, Gary Graham, Jag Srai -- Smart health monitoring using smart systems / Carl Chalmers -- Significance of automated driving in japan / Sadayuki Tsugawa -- Environment-assisted vehicular data in smart city / Wei Chang, Huanyang Zheng, Jie Wu, Chiu C. …”

Tabla de Contenidos: “…Data Source ConnectionsSSIS Transformations; Row Transformations; Rowset Transformations; Split and Join Transformations; Data Quality Transformations; Data-Mining Transformations; Other Transformations; Synchronous and Asynchronous Transformations; Using Expressions in Packages; Expression Usage in SSIS; Expressions Elements; Building Expressions; Using Data Flow Transformations; Opening and Exploring the SSIS Project; Creating the Data Flow Task; Using a Flat File Source; Adding a Connection Manager; Adding a Conditional Split Transformation; Adding a Derived Column Transformation…”

Tabla de Contenidos: “…Oracle content managementOracle search capabilities; Oracle Spatial Option; XML DB; Database Connection Features; Oracle Internet Directory; Oracle Connection Manager; Oracle Application Server; Distributed Database Features; Heterogeneous Services; Data Movement Features; Advanced Queuing and Oracle Streams; Extraction, Transformation, and Loading; Database Performance Features; Data Warehousing and Business Intelligence; Star query optimization; Materialized views; Analytic functions; OLAP Option; Data Mining Option; Business intelligence tools; Database Management Features…”