Tabla de Contenidos: “…Modelo de tres componentes atencionales; 2.1. Red de alerta; 2.2. Red de orientación; 2.3. Red ejecutiva; 3. …”

Tabla de Contenidos: “…Instrucciones de seguridad y alerta de las instalaciones -- 10. Cumplimentación de documentación y formularios normalizados de la puesta en servicio de instalaciones…”

Tabla de Contenidos: “…Monitozacion de sistemas Windows: 1 Arranque de un servidor Windows ; 2 El proceso de apagado ; 3 Monitorización del rendimiento ; 4 Gestión de logs, alertas y seguridad -- Unidad 9. El proceso de instalacion en Linux: 1 Tareas de preinstalación ; 2 Tipos de instalaciones ; 3 Resolución de problemas durante la instalación ; 4 Documentación de la instalación y las incidencias ; 5 Proceso de arranque y servicios -- Unidad 10. …”

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: “…Backing up and restoring packages -- Making use of aptitude -- Installing Snap packages -- Summary -- Chapter 6: Controlling and Monitoring Processes -- Showing running processes with the ps command -- Managing jobs -- Killing misbehaving processes -- Utilizing htop -- Managing system processes -- Monitoring memory usage -- Scheduling tasks with Cron -- Understanding load average -- Summary -- Chapter 7: Managing Your Ubuntu Server Network -- Planning your IP address scheme -- Serving IP addresses with isc-dhcp-server -- Setting up name resolution (DNS) with bind -- Creating a secondary DNS server -- Setting up an Internet gateway -- Keeping your system clock in sync with NTP -- Summary -- Chapter 8: Accessing and Sharing Files -- File server considerations -- Sharing files with Windows users using Samba -- Setting up NFS shares -- Transferring files with rsync -- Transferring files with SCP -- Mounting remote filesystems with SSHFS -- Summary -- Chapter 9: Managing Databases -- Preparations for setting up a database server -- Installing MariaDB -- Taking a look at MariaDB configuration -- Understanding how MariaDB differs in Ubuntu 16.04 -- Managing databases -- Setting up a slave DB server -- Summary -- Chapter 10: Serving Web Content -- Installing and configuring Apache -- Installing additional Apache modules -- Securing Apache with SSL -- Setting up high availability with keepalived -- Installing and configuring ownCloud -- Summary -- Chapter 11 : Virtualizing Hosts and Applications -- Setting up a virtual machine server -- Creating virtual machines -- Bridging the virtual machine network -- Creating, running, and managing Docker containers -- Summary -- Chapter 12 : Securing Your Server -- Lowering your attack surface -- Securing OpenSSH -- Installing and configuring Fail2ban -- MariaDB best practices -- Setting up a firewall…”

Tabla de Contenidos: “…Multiple Choice Questions -- Open Questions -- Notes -- References -- Chapter 6: Profit-Driven Model Evaluation and Implementation -- Introduction -- Profit-Driven Evaluation of Classification Models -- Average Misclassification Cost -- Cutoff Point Tuning -- ROC Curve-Based Measures -- Profit-Driven Evaluation with Observation-Dependent Costs -- Profit-Driven Evaluation of Regression Models -- Loss Functions and Error-Based Evaluation Measures -- REC Curve and Surface -- Conclusion -- Review Questions -- Multiple Choice Questions -- Open Questions -- Notes -- References -- Chapter 7: Economic Impact -- Introduction -- Economic Value of Big Data and Analytics -- Total Cost of Ownership (TCO) -- Return on Investment (ROI) -- Profit-Driven Business Analytics -- Key Economic Considerations -- In-Sourcing versus Outsourcing -- On Premise versus the Cloud -- Open-Source versus Commercial Software -- Improving the ROI of Big Data and Analytics -- New Sources of Data -- Data Quality -- Management Support -- Organizational Aspects -- Cross-Fertilization -- Conclusion -- Review Questions -- Multiple Choice Questions -- Open Questions -- Notes -- References -- About the Authors -- Index -- EULA…”

Tabla de Contenidos: “…-- Target feature -- Sensitive features -- Analyzing the comments text -- Topic modeling -- Named entity recognition -- POS tagging -- Preparing the model -- Building the vocabulary -- Embedding index and embedding matrix -- Checking vocabulary coverage -- Iteratively improving vocabulary coverage -- Transforming to lowercase -- Removing contractions -- Removing punctuation and special characters -- Building a baseline model -- Transformer-based solution -- Summary -- References -- Chapter 8: Analyzing Acoustic Signals to Predict the Next Simulated Earthquake -- Introducing the LANL Earthquake Prediction competition -- Formats for signal data -- Exploring our competition data -- Solution approach -- Feature engineering -- Trend feature and classic STA/LTA -- FFT-derived features -- Features derived from aggregate functions -- Features derived using the Hilbert transform and Hann window -- Features based on moving averages -- Building a baseline model -- Summary -- References -- Chapter 9: Can You Find Out Which Movie Is a Deepfake? …”

Tabla de Contenidos: “…Bayesian Priors and Working with Probability Distributions -- C-3PO's Asteroid Field Doubts -- Determining C-3PO's Beliefs -- Accounting for Han's Badassery -- Creating Suspense with a Posterior -- Wrapping Up -- Exercises -- Part III: Parameter Estimation -- 10. Introduction to Averaging and Parameter Estimation -- Estimating Snowfall -- Means for Measurement vs. …”

Tabla de Contenidos: “…-- Syntactic Analysis -- Semantic Analysis -- NLP AIOps Use Cases -- Sentiment Analysis -- Language Translation -- Text Extraction -- Topic Classification -- Deep Learning -- Summary -- Chapter 6: AIOps Use Case: Deduplication -- Environment Setup -- Software Installation -- Launch Application -- Performance Analysis of Models -- Mean Square Error/Root Mean Square Error -- Mean Absolute Error -- Mean Absolute Percentage Error -- Root Mean Squared Log Error -- Coefficient of Determination-R2 Score -- Deduplication -- Summary -- Chapter 7: AIOps Use Case: Automated Baselining -- Automated Baselining Overview -- Regression -- Linear Regression -- Time-Series Models -- Time-Series Data -- Stationary Time Series -- Lag Variable -- ACF and PACF -- ARIMA -- Model Development -- Differencing (d) -- Autoregression or AR (p) -- Moving Average or MA (q) -- SARIMA -- Implementation of ARIMA and SARIMA -- Automated Baselining in APM and SecOps -- Challenges with Dynamic Thresholding -- Summary -- Chapter 8: AIOps Use Case: Anomaly Detection -- Anomaly Detection Overview -- K-Means Algorithms -- Correlation and Association…”

Tabla de Contenidos: “…Side step: conservative, spanwise load on an elliptic wing -- Conservative and non-conservative blade loads -- Experimental and numerical results for a model wind turbine rotor -- Determination of the conservative tip load -- The tip vortex trajectory -- The role of conservative forces -- Evaluation -- From disc theory to BEM models: the tip correction -- Introduction -- Development of the tip correction -- In BEM methods -- In actuator disc, actuator line and lifting line methods -- The distribution of the axial velocity -- The radial distribution -- The azimuthal distribution: averaged or at blade position -- The azimuthal distribution: decambering of aerofoils -- The radial distribution of blade -- The aspect ratio as a measure for tip effects -- Conservative tip load and the tip vortex trajectory -- Evaluation -- Epilogue -- Vector expressions in cylindrical coordinates -- Balance of angular momentum -- The blade load expressed as pressure distribution -- The potential flow model -- Components of the model -- Convergence scheme -- Verification, sensitivity and accuracy -- Bibliography -- Index…”

Tabla de Contenidos: “…4.1.2 Available bandwidth4.1.3 Commercially available technologies; 4.1.4 Lasercom challenges; 4.1.4.1 Transmit channel; 4.1.4.2 Optical channel; 4.1.4.3 Receive channel; 4.2 Lasercom Link Budgets; 4.3 Laser Beam Propagation Through the Atmosphere; 4.3.1 Atmospheric attenuation; 4.3.2 Atmospheric radiance; 4.3.3 Atmospheric turbulence; 4.3.4 Turbulence mitigation approaches; 4.3.4.1 Aperture averaging effects on downlink beam; 4.3.4.2 Multibeaming for uplink; 4.3.4.3 Adaptive optics technique for downlink; 4.3.4.4 Coding of downlink and downlink transmitter…”

Tabla de Contenidos:

Tabla de Contenidos: “…-- Appendix A Selected Distributions -- Distribution Name: Triangular -- Distribution Name: Binary -- Distribution Name: Normal -- Distribution Name: Lognormal -- Distribution Name: Beta -- Distribution Name: Power Law -- Appendix B Guest Contributors -- Decision Analysis to Support Ransomware Cybersecurity Risk Management -- Bayesian Networks: One Solution for Specific Challenges in Building ML Systems in Cybersecurity -- The Flaw of Averages in Cyber Security -- Botnets -- Password Hacking -- How Catastrophe Modeling Can Be Applied to Cyber Risk -- Notes -- Index -- EULA…”

Tabla de Contenidos: “…Power Pivot and Data Models -- DAX -- Summary -- Chapter 6: Must-Know Legacy Excel Functions -- Math and statistical functions -- SUM -- SUMIFS -- COUNT -- COUNTIFS -- MIN -- MAX -- AVERAGE -- Logical functions -- IF -- IFS -- IFERROR -- SWITCH -- OR -- AND -- Text manipulation functions -- LEFT -- MID -- RIGHT -- SEARCH -- SUBSTITUTE -- TEXT -- LEN -- Date manipulation functions -- TODAY -- DATE -- YEAR -- MONTH -- DAY -- EDATE -- EOMONTH -- WEEKNUM -- Lookup and reference functions -- VLOOKUP -- HLOOKUP -- INDEX -- MATCH -- OFFSET -- INDIRECT -- CHOOSE -- Summary -- Chapter 7: Dynamic Array Functions and Lambda Functions -- Dynamic array functions -- UNIQUE -- FILTER -- SEQUENCE -- SORT -- SORTBY -- Lambda functions -- LAMBDA -- BYCOL -- BYROW -- MAKEARRAY -- MAP -- REDUCE -- SCAN -- Summary -- Part 3 - Getting the Visualization Right -- Chapter 8: Getting Comfortable with the 19 Excel Charts -- Column chart -- Bar chart -- Line chart -- Area chart -- Pie chart -- Doughnut chart -- XY (scatter) chart -- Bubble chart -- Stock chart -- Surface chart -- Radar chart -- Treemap chart -- Sunburst chart -- Histogram chart -- Box and whisker chart -- Waterfall chart -- Funnel chart -- Filled map chart -- Combo chart -- Summary -- Chapter 9: Non-Chart Visuals -- Conditional formatting -- Highlight Cells Rules -- Top/Bottom Rules -- Data bars -- Color scales -- Icon sets -- Custom formula conditional formatting -- Shapes -- SmartArt -- Sparkline -- Images -- Symbols -- Summary -- Chapter 10: Setting Up the Dashboard's Data Model -- Adventure Works Cycle Limited -- HR schema -- Sales schema -- Purchasing schema -- Production schema -- Person schema -- Building business-relevant dashboards -- Data transformation in Power Query -- Summary -- Chapter 11: Perfecting the Dashboard -- Building the HR manpower dashboard -- Inserting PivotTables…”

Tabla de Contenidos: “…Chapter 3: Big Data Processing with MapReduce -- The MapReduce framework -- Dataset -- Record reader -- Map -- Combiner -- Partitioner -- Shuffle and sort -- Reduce -- Output format -- MapReduce job types -- Single mapper job -- Single mapper reducer job -- Multiple mappers reducer job -- SingleMapperCombinerReducer job -- Scenario -- MapReduce patterns -- Aggregation patterns -- Average temperature by city -- Record count -- Min/max/count -- Average/median/standard deviation -- Filtering patterns -- Join patterns -- Inner join -- Left anti join -- Left outer join -- Right outer join -- Full outer join -- Left semi join -- Cross join -- Summary -- Chapter 4: Scientific Computing and Big Data Analysis with Python and Hadoop -- Installation -- Installing standard Python -- Installing Anaconda -- Using Conda -- Data analysis -- Summary -- Chapter 5: Statistical Big Data Computing with R and Hadoop -- Introduction -- Install R on workstations and connect to the data in Hadoop -- Install R on a shared server and connect to Hadoop -- Utilize Revolution R Open -- Execute R inside of MapReduce using RMR2 -- Summary and outlook for pure open source options -- Methods of integrating R and Hadoop -- RHADOOP - install R on workstations and connect to data in Hadoop -- RHIPE - execute R inside Hadoop MapReduce -- R and Hadoop Streaming -- RHIVE - install R on workstations and connect to data in Hadoop -- ORCH - Oracle connector for Hadoop -- Data analytics -- Summary -- Chapter 6: Batch Analytics with Apache Spark -- SparkSQL and DataFrames -- DataFrame APIs and the SQL API -- Pivots -- Filters -- User-defined functions -- Schema - structure of data -- Implicit schema -- Explicit schema -- Encoders -- Loading datasets -- Saving datasets -- Aggregations -- Aggregate functions -- count -- first -- last -- approx_count_distinct -- min -- max -- avg -- sum…”

Tabla de Contenidos: “…Selecting algorithms based on function -- Using Spark to generate real-time big data analytics -- Chapter 4 Math, Probability, and Statistical Modeling -- Exploring Probability and Inferential Statistics -- Probability distributions -- Conditional probability with Naïve Bayes -- Quantifying Correlation -- Calculating correlation with Pearson's r -- Ranking variable-pairs using Spearman's rank correlation -- Reducing Data Dimensionality with Linear Algebra -- Decomposing data to reduce dimensionality -- Reducing dimensionality with factor analysis -- Decreasing dimensionality and removing outliers with PCA -- Modeling Decisions with Multiple Criteria Decision-Making -- Turning to traditional MCDM -- Focusing on fuzzy MCDM -- Introducing Regression Methods -- Linear regression -- Logistic regression -- Ordinary least squares (OLS) regression methods -- Detecting Outliers -- Analyzing extreme values -- Detecting outliers with univariate analysis -- Detecting outliers with multivariate analysis -- Introducing Time Series Analysis -- Identifying patterns in time series -- Modeling univariate time series data -- Chapter 5 Grouping Your Way into Accurate Predictions -- Starting with Clustering Basics -- Getting to know clustering algorithms -- Examining clustering similarity metrics -- Identifying Clusters in Your Data -- Clustering with the k-means algorithm -- Estimating clusters with kernel density estimation (KDE) -- Clustering with hierarchical algorithms -- Dabbling in the DBScan neighborhood -- Categorizing Data with Decision Tree and Random Forest Algorithms -- Drawing a Line between Clustering and Classification -- Introducing instance-based learning classifiers -- Getting to know classification algorithms -- Making Sense of Data with Nearest Neighbor Analysis -- Classifying Data with Average Nearest Neighbor Algorithms…”

Tabla de Contenidos: “…Latvia reports fewer health professionals than the OECD average -- 1.8.2. The regional repartition of the health workforce is very imbalanced -- 1.8.3. …”

Tabla de Contenidos: “…Average real net investment return by type of domestic insurer in 2014 (direct insurers) -- Figure 13. …”

Tabla de Contenidos: “…Consumer market scoreboard: Czech Republic versus EU average -- Figure 1.21. Barriers to entrepreneurship, 2013 -- Box 1.4. …”

Tabla de Contenidos: “…-- The Basic Indicator Calculations -- Comparing Indicators -- Moving Average Types -- Oscillators and Trading Signals -- Indicator Myths -- Indicator "Types" -- Conclusion…”