Tabla de Contenidos: “…Analyzing Activity Logs with Lead -- 15. Forecasting with Linear Regression -- 16. Rolling Sums to Forecast Reaching Minimums -- Part III. …”

Tabla de Contenidos: “…Part I: Foundations -- 1: Introduction -- 2: Cryptography Fundamentals -- 3: Mathematical Background and Its Applicability -- 4: Large Integer Arithmetic -- 5: Floating Point Arithmetic -- 6: New Features in C++20 -- 7: Secure Coding Guidelines -- 8: Cryptography Libraries in C/C++20 -- Part II: Pro Cryptography -- 9: Elliptic Curve Cryptography -- 10: Lattice-based Cryptography -- 11: earchable Encryption -- 12: Homomorphic Encryption -- 13: (Ring) Learning with Errors Cryptography -- 14: Chaos-based Cryptography -- 15: Big Data Cryptography16:Cloud Computing Cryptography -- Part III: Pro Cryptanalysis -- 17: Getting Started with Cryptanalysis -- 18: Cryptanalysis Attacks and Techniques -- 19: Linear and Differential Cryptanalysis -- 20: Integral Cryptanalysis -- 21: Brute Force and Buffer Overflow Attacks -- 22: Text Characterization -- 23: Implementation and Practical Approach of Cryptanalysis Methods…”

Tabla de Contenidos: “…Mechanics -- Chapter 1: Units and Measurement -- Chapter 2: Vectors -- Chapter 3: Motion Along a Straight Line -- Chapter 4: Motion in Two and Three Dimensions -- Chapter 5: Newton's Laws of Motion -- Chapter 6: Applications of Newton's Laws -- Chapter 7: Work and Kinetic Energy -- Chapter 8: Potential Energy and Conservation of Energy -- Chapter 9: Linear Momentum and Collisions -- Chapter 10: Fixed-Axis Rotation -- Chapter 11: Angular Momentum -- Chapter 12: Static Equilibrium and Elasticity -- Chapter 13: Gravitation -- Chapter 14: Fluid Mechanics -- Unit 2. …”

Tabla de Contenidos: “…The path to electron-positron collisions -- AdA at Orsay -- Bruno Touschek and Statistical Mechanics -- Role of Bruno Touschek in the Realization of the Particle-Antiparticle Colliders -- Adone, Asymptotic Freedom and QCD -- The Standard Theory and Theoretical Physics in Roma -- Detectors and Experiments at the Laboratory for Electro-strong Physics: a personal view -- From the hadronic string to quantum gravity and back -- QCD and Supercomputers -- Bruno Touschek and the physics at Frascati at the time of AdA and ADONE -- Accelerators at LNF: From AdA to EuPRAXIA -- Accelerator Physics at IJCLab-ORSAY -- Technical challenges for future accelerators -- The making of AdA: Bruno Touschek’s journey from Widerøe’s betatron to storage rings -- The Making of ADONE -- Spontaneous symmetry breaking in particle physics -- String Theory -- Multi-Messenger Astronomy -- High Energy Physics and the European Strategy -- Circular Colliders in China -- Linear Colliders -- Remembering Bruno Touschek…”

Tabla de Contenidos: “…Change and continuity in a central London street / Ilaria Pulini ; Towards a phenomenology of the concrete megastructure : space and perception at the Brunswick Centre, London / Clare Melhuish ; Isolation : a walk through a London estate / Dave Yates ; The making of a suburb / David Jeevendrampillai ; The linear village : experience of continuous cruising on the London waterways / Titika Malkogeorgou Part II. …”

Tabla de Contenidos: “…Claroscuro de la guerra: Baltimore - Sudán - Angola - China - Ginebra - Suecia; Mapa II. Claroscuro de la ciencia y la fe: Colombia - Rumania - Nepal - Tíbet; Mapa III. …”

Tabla de Contenidos: “…Per l'Ebre / Josep Pla -- La Seso / Francesca Aliern -- Cançó de l'Ebre ; L'encanyissada / Joan Cid Mulet -- Convivència d'aigües, el meu paisatge ; El jo que no sóc a mi s'adreça ; Era el riu i el corrent que feien sonar els còdols ; Es dupliquen els arbres, ja grocs ; Fotografia esgroguissada de Borrell: un viatge en llaüt al far de Buda vell / Zoraida Burgos -- El riu ; Paisatge ; Mare Nostrum / Jesús Masip -- Com un riu ; Els amants / Manuel Pérez-Bonfill -- Cos de l'estiu ; Tot aquí em pren, i és per bellesa de no dir ; Riu / Albert Roig -- De lírica fluvial ; parlo d'un riu mític i remorós / Gerard Vergés -- L'home del pontó / Josep Igual -- Terres de l'Ebre / Sebastià Juan Arbó -- Agnès dels Ginegalls / Manuel Ollé -- El somni d'un somni / Emili Rosales…”

Tabla de Contenidos: “…Per l'Ebre / Josep Pla -- La Seso / Francesca Aliern -- Cançó de l'Ebre ; L'encanyissada / Joan Cid Mulet -- Convivència d'aigües, el meu paisatge ; El jo que no sóc a mi s'adreça ; Era el riu i el corrent que feien sonar els còdols ; Es dupliquen els arbres, ja grocs ; Fotografia esgroguissada de Borrell: un viatge en llaüt al far de Buda vell / Zoraida Burgos -- El riu ; Paisatge ; Mare Nostrum / Jesús Masip -- Com un riu ; Els amants / Manuel Pérez-Bonfill -- Cos de l'estiu ; Tot aquí em pren, i és per bellesa de no dir ; Riu / Albert Roig -- De lírica fluvial ; parlo d'un riu mític i remorós / Gerard Vergés -- L'home del pontó / Josep Igual -- Terres de l'Ebre / Sebastià Juan Arbó -- Agnès dels Ginegalls / Manuel Ollé -- El somni d'un somni / Emili Rosales…”

Tabla de Contenidos: “…About the Author xiii Preface xv 1 Forecasting a Monthly Time Series 1 1.1 Introduction 1 1.2 Forecasting Using LV(p) Models 1 1.2.1 Basic or Regular LV(p) Models 1 1.2.2 Special LV(p) Models 6 1.3 Forecasting Using the LVARMA(p,q,r) Model 8 1.3.1 Special Notes on the ARMA Model 9 1.3.2 Application of Special LVAR Models 10 1.4 Forecasting Using TGARCH(a,b,c) Models 12 1.4.1 Application of ARCH(a), GARCH(b), and TARCH(c) Models 14 1.4.2 Application of TGARCH(a,b,0) Models 14 1.4.3 Application of TGARCH(a,b,c) Models 20 1.4.4 Other Alternative Models 20 1.5 Instrumental Variables Models 20 1.5.1 Application of the GMM Estimation Method 21 1.5.2 Application of the TSLS Estimation Method 36 1.6 Special Notes and Comments on Residual Analysis 42 1.6.1 Specific Residual Analysis 43 1.6.2 Additional Special Notes and Comments 61 1.6.3 Serial Correlation Tests 65 1.7 Statistical Results Using Alternative Options 67 1.7.1 Application of an Alternative Coefficient Covariance Matrix 67 1.7.2 Application of Selected Combinations of Options 70 1.7.3 Final Notes and Conclusions 71 2 Forecasting with Time Predictors 73 2.1 Introduction 73 2.2 Application of LV(p) Models of HS on MONTH by YEAR 73 2.2.1 Special LV(12) Models of HS on MONTH by YEAR 73 2.2.2 Application of the Omitted Variables Test - Likelihood Ratio 75 2.2.3 Heterogeneous Model of HS on HS(−12) and Month by YEAR 79 2.3 Forecast Models of HS on MONTH by YEAR 79 2.3.1 Application of LV(1) Models of HS on MONTH by YEAR 79 2.3.2 Application of Basic LV(p) Models of HS on MONTH by YEAR 82 2.3.3 Application of AR(q) Models of HS on MONTH by YEAR 86 2.3.4 Application of ARMA(q,r) Models of HS on MONTH by YEAR 89 2.3.5 Application of LVAR(p,q) Models of HS on MONTH by YEAR 89 2.3.6 Application of LVAR(p,q) Models of HS on YEAR by MONTH 92 2.4 Heterogeneous Classical Growth Models 95 2.4.1 Forecasting Based on LV(p) Het_CGMs of HS 95 2.4.2 Forecasting Based on AR(q) Het_CGMs 99 2.4.3 Forecasting Based on LVAR(p,q) Het_CGMs 101 2.5 Forecast Models of G in Currency.wf1 103 2.5.1 LVAR(p,q) Additive Models of G by @Month with @Trend 104 2.5.2 LV(1) Heterogeneous Models of G by @Month 111 2.6 Forecast Models of G on G(−1) and Polynomial Time Variables 116 2.6.1 Heterogeneous Model of G on G(−1) and Polynomial T by @Month 116 2.6.2 Forecast Model of G on G(−1) with Heterogeneous Polynomial Trend 138 2.7 Forecast Models of CURR in Currency.wf1 140 2.7.1 Developing Scatter Graphs with Regressions 141 2.7.2 Additive Forecast Models of CURR with a Time Predictor 143 2.7.3 Interaction Forecast Models of CURR 159 2.7.4 Forecast Models Based on Subsamples 169 3 Continuous Forecast Models 185 3.1 Introduction 185 3.2 Forecasting of FSPCOM 185 3.2.1 Simple Continuous Models of FSPCOM 185 3.2.2 LVAR(P,Q) Models of Y = FSPCOM with Polynomial Trend 190 3.2.3 Translog Models with Time Predictor 195 3.3 Forecasting Based on Subsamples 207 3.3.1 Lag Variable Models With Lower and Upper Bounds 209 3.4 Special LV(12) Models of HS with Upper and Lower Bounds 222 3.4.1 Special LVARMA(12,q,r) Model of LNYul Without Time Predictor 223 3.4.2 Special LVARMA(12,q,r) of LNYul With Time Predictor 223 4 Forecasting Based on (Xt,Yt) 229 4.1 Introduction 229 4.2 Forecast Models Based on (Xt,Yt) 229 4.3 Data Analysis Based on a Monthly Time Series 230 4.4 Forecast Models without a Time Predictor 230 4.4.1 Two-Way Interaction Models 230 4.4.2 Cobb-Douglass Model and Alternatives 235 4.5 Translog Quadratic Model 236 4.5.1 Forecasting Using a Subsample 240 4.5.2 Forecast Model with Trend 243 4.6 Forecasting of FSXDP 247 4.6.1 Forecasting of Y2 Based on a Subsample 247 4.6.2 Extension of the Model (4.25) with Time Variables 252 4.7 Translog Linear Models 256 4.7.1 Basic Translog Linear Model 256 4.7.2 Tanslog Linear Model with Trend 256 4.7.3 Heterogeneous Tanslog Linear Model 260 4.8 Application of VAR Models 262 4.8.1 Unstructured VAR Models Based on (X1t,Y1t) 262 4.8.2 The Simplest VAR Models with Alternative Trends 264 4.8.3 Complete Heterogeneous VAR Models by @Month 270 4.8.4 Bayesian VAR Models 271 4.8.5 VEC Models 271 4.9 Forecast Models Based on (Y1t,Y2t) 275 4.9.1 Forecast Models Based on Figures 4.42a and b 275 4.9.2 Reciprocal Causal Effects Models 279 4.9.3 Models with the Time Independent Variables 280 4.10 Special Notes and Comments 287 5 Forecasting Based On (X1t,X2t,Yt) 289 5.1 Introduction 289 5.2 Translog Linear Models Based on (X1,X2,Y1) 289 5.2.1 Basic Translog Linear Model 289 5.2.2 Tanslog Linear Model with Trend 292 5.2.3 Tanslog Linear Model with Heterogeneous Trends 292 5.3 Translog Linear Models Based on (X1,X2,Y2) 293 5.3.1 Translog Linear Models Using the Subsample {@Year>1990} 296 5.3.2 Translog Linear Models Using the Subsample {@Year>1975} 298 5.3.3 Translog Linear Models Using the Whole Sample 298 5.4 Forecast Models Using Original (X1,X2,Y) 300 5.4.1 Model Based on Figure 5.6a 300 5.4.2 Model Based on Figure 5.6b 301 5.4.3 Model Based on Figure 5.6c 307 5.5 Alternative Forecast Models Using Original (X1,X2,Y) 310 5.5.1 Three-Way Interaction Based on Figure 5.14a 311 5.5.2 Three-Way Interaction Based on Figure 5.14b and c 311 5.6 Forecasting Models with Trends Using Original (X1,X2,Y) 311 5.7 Application of VAR Models Based on (X1t,X2t,Y1t) 316 5.7.1 Unrestricted VAR Models 316 5.7.2 The Simplest Two-Way Interaction VAR Model 317 5.7.3 The Simplest Three-Way Interaction VAR Model 318 5.8 Applications of the Object "System" 320 5.8.1 The MLV(1,1,1) Models of (Y1,Y2,Y3) on (Y1(−1),Y2(−1),Y3(−1)) 320 5.8.2 Circular Effects MLV(1,1,1) Models 328 5.9 Models Presenting Causal Relationships Y1,Y2, and Y3 335 5.9.1 Triangular Effects Models 335 5.9.2 Circular Effects Models 340 5.9.3 Reciprocal Effects Models 341 5.10 Extended Models 344 5.10.1 Extension to the Models with Additional Exogenous Variables 344 5.10.2 Extension to the Models with Alternative Trends 347 5.10.3 Extension to LVARMA(p,q,r) 352 5.10.4 Extension to Heterogeneous Regressions by Months 356 5.11 Special Notes and Comments 369 6 Forecasting Quarterly Time Series 371 6.1 Introduction 371 6.2 Alternative LVARMA(p,q,r) Of a Single Time Series 371 6.2.1 LV(P) Forecast Model of GCDANt 371 6.2.2 LVARMA(p,q.r) Forecast Models of GCDN 372 6.2.3 Forecast Models of GCDAN with Time Variables 374 6.2.4 Special Notes on Uncommon Models 381 6.3 Complete Heterogeneous LV(2) Models of GCDAN By @Quarter 383 6.3.1 Using the Simplest Equation Specification 383 6.3.2 Using a Complete Equation Specification 387 6.4 LV(2) Models of GCDAN with Exogenous Variables 387 6.4.1 LV(2) Models with an Exogenous Variable 387 6.4.2 LV(2) Models with Two Exogenous Variables 390 6.5 Alternative Forecast Models Based on (Y1,Y2) 393 6.5.1 LV(2) Basic Interaction Models 393 6.5.2 LV(2) Models of (Y1,Y2) with an Exogenous Variable and @Trend 394 6.5.3 LV(2) Models of (Y1,Y2) with two Exogenous Variables and Trend 400 6.5.4 LV(2) Models of (Y1,Y2) with Three Exogenous Variables and Trend 409 6.6 Triangular Effects Models Based on (X1,X2,Y1) 413 6.6.1 Partial Two-Way Interaction LV(p) TE_Models 413 6.6.2 A Complete Two-Way Interaction LV(p) TE_Models 414 6.6.3 Three-Way Interaction LV(p) TE_ Models 415 6.7 Bivariate Triangular Effects Models Based on (X1,X2,Y1,Y2) 417 6.7.1 Partial Two-Way Interaction Models 417 6.7.2 Three-Way Interaction TE_Models 418 6.8 Models with Exogenous Variables and Alternative Trends 422 6.8.1 Models Based on (X1,X2,Y1) 422 6.8.2 Models Based on (X1,X2,Y1,Y2) with Trend 424 6.9 Special LV(4) Models with Exogenous Variables 427 6.10 Models with Exogenous Variables by @Quarter 433 6.10.1 Alternative Models Based on the Whole Sample 433 6.10.2 Forecasting Based on each Quarter's Level 435 7 Forecasting Based on Time Series by States 447 7.1 Introduction 447 7.2 Models Based on a Bivariate (Y1_1,Y1_2) 447 7.2.1 Alternative LV(p) Models Based on Figure 7.1a 448 7.2.2 Alternative LV(p) Models Based on Figure 7.1b 451 7.2.3 Alternative LV(p) Models Based on Figure 7.1c 454 7.3 Advanced LP(p) Models of (Y1_1,Y1_2) 455 7.3.1 Two-Way Interaction LV(p) Models 455 7.3.2 Three-Way Interaction LV(p) Models 456 7.3.3 Alternative Additive Models 456 7.4 Advanced LP(p) Models of (Y1_1,Y1_2,Y1_3) 457 7.4.1 Triangular Effects Model of (Y1_1,Y1_2,Y1_3) 457 7.4.2 Full-Lag Variables Triangular Effects Model 462 7.4.3 Translog-Linear Triangular Effects Model 466 7.5 Full-Lag Variables Circular Effects Model 466 7.5.1 Two-Way Interaction…”

Tabla de Contenidos: “…Preface -- -- Part One Basics of Process Dynamics -- -- 1 Mathematical Representations of Linear Processes -- 1.1 Introduction to Process Control and Identification -- 1.2 Properties of Linear Processes -- 1.3 Laplace Transform -- 1.4 Transfer Function and State-Space Systems -- Problems -- -- 2 Simulations -- 2.1 Simulating Processes Composed of Differential Equations -- 2.2 Simulating Processes Including Time Delay -- 2.3 Simulating Closed-Loop Control Systems -- 2.4 Useful Numerical Analysis Methods -- Problems -- -- 3 Dynamic Behavior of Linear Processes -- 3.1 Low-Order Plus Time-Delay Processes -- 3.2 Process Reaction Curve Method -- 3.3 Poles and Zeroes -- 3.4 Block Diagram -- 3.5 Frequency Responses -- Problems -- -- Part Two Process Control -- -- 4 Proportional-Integral-Derivative Control -- 4.1 Structure of Proportional-Integral-Derivative Controllers and Implementation in Computers/Microprocessors -- 4.2 Roles of Three Parts of Proportional-Integral-Derivative Controllers -- 4.3 Integral Windup -- 4.4 Commercial Proportional-Integral-Derivative Controllers -- Problems -- -- 5 Proportional-Integral-Derivative Controller Tuning -- 5.1 Trial-and-Error Tuning -- 5.2 Simple Process Identification Methods -- 5.3 Ziegler-Nichols Tuning Rule -- 5.4 Internal Model Control Tuning Rule -- 5.5 Integral of the Time-Weighted Absolute Value of the Error Tunning Rule for a First-Order Plus Time-Delay Model (ITAE-1) -- 5.6 Integral of the Time-Weighted Absolute Value of the Error Tunning Rule for a Second-Order Plus Time-Delay Model (ITAE-2) -- 5.7 Optimal Gain Margin Tuning Rule for an Unstable Second-Order Plus Time-Delay Model (OGM-unstable) -- 5.8 Model Reduction Method for Proportional-Integral-Derivative Controller Tuning -- 5.9 Consideration of Modeling Errors -- 5.10 Concluding Remarks -- Problems -- -- 6 Dynamic Behavior of Closed-Loop Control Systems -- 6.1 Closed-Loop Transfer Function and Characteristic Equation -- 6.2 Bode Stability Criterion -- 6.3 Nyquist Stability Criterion…”

Tabla de Contenidos: “…2.3.4 Grating-Coupled Configuration2.3.4.1 Incident Plane Wave; 2.3.4.2 Reflected and Transmitted Field Phasors; 2.3.4.3 Linear Reflectances and Transmittances; 2.3.4.4 Rigorous Coupled-Wave Approach; 2.3.4.5 Stable RCWA Algorithm; 2.3.4.6 Excitation of an SPP Wave; 2.3.4.7 Illustrative Results; 2.3.5 Waveguide-Coupled Configuration; 2.4 Nonlinear Dielectric Materials; General Theory of Surface-Wave Propagation; 3.1 Introduction; 3.2 Bianisotropic Materials; 3.2.1 Maxwell Postulates; 3.2.2 Linear Constitutive Relations; 3.2.3 Periodic Nonhomogeneity; 3.2.4 Homogeneous Bianisotropic Materials…”

“…Este trabajo de fin de grado (TFG) presenta una propuesta didáctica utilizando la gamificación como metodología para generar motivación en el aula de inglés en educación primaria…”
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“…La fuerza es una de las capacidades condicionales que desempeña un importante papel en el mundo del entrenamiento deportivo, bien sea como elemento principal del rendimiento o como base para generar la tensión necesaria para crear cualquier movimiento. …”

“…Hay personas que nunca hallan descanso, aun dándose cuenta de que generar preocupaciones sin tregua les produce una sensación desagradable de disgusto y malestar. …”

“…Esta obra tiene como objetivo contribuir a generar espacios de reflexión ante la realidad de la existencia y la convivencia en la sociedad actual con el ciberespacio. …”
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“…Por último aprenderemos a generar código automáticamente a partir de diagramas de clases y viceversa. …”

“…Proporciona un marco secuencial para generar un diagnóstico diferencial, utilizando un enfoque de seis pasos, que ayudará a los médicos a desarrollar sus habilidades para la toma de decisiones clínicas y garantizar que se tomen en cuenta las múltiples causas de los trastornos mentales, así como sus interrelaciones…”