“…The JMP 11 Design of Experiments Guide covers classic DOE designs (for example, full factorial, response surface, and mixture designs). …”

Tabla de Contenidos: “…ANÁLISIS MATEMÁTICO -- PÁGINA LEGAL -- CONTENIDO -- INTRODUCCIÓN -- UNIDAD I: TEMAS BÁSICOS -- ORIENTACIONES PARA EL ESTUDIO DE LA UNIDAD I -- PROPÓSITOS DE LA UNIDAD I -- ESQUEMA DE LA UNIDAD I: TEMAS BÁSICOS -- 1.1 INTERVALO -- 1.1.1 EXTREMOS DE UN INTERVALO -- 1.1.2 CLASIFICACIÓN DE LOS INTERVALOS -- 1.1.3 OBSERVACIONES GENERALES SOBRE DE LOS INTERVALOS -- 1.2 CONJUGADO DE UN BINOMIO -- 1.3 CONVERSIONES ENTRE GRADOS Y RADIANES -- 1.4 FUNCIONES TRIGONOMÉTRICAS -- 1.4.1 ILUSTRACIÓN -- 1.4.2 DEFINICIONES DE LAS FUNCIONES TRIGONOMÉTRICAS -- 1.5 IDENTIDADES TRIGONOMÉTRICAS -- 1.6 PRODUCTOS NOTABLES -- 1.7 FACTORIAL DE UN NÚMERO -- 1.8 RACIONALIZACIÓN DE RADICALES -- 1.8.1 RACIONALIZACIÓN EN EL DENOMINADOR -- 1.8.2 RACIONALIZACIÓN DEL NUMERADOR -- 1.9 FACTORIZACIÓN -- 1.9.1 CONCEPTO DE FACTORIZACIÓN -- 1.9.2 FACTORIZACIÓN POR FACTOR COMÚN -- 1.9.3 FACTORIZACIÓN POR AGRUPACIÓN O ASOCIACIÓN -- 1.9.4 DIFERENCIA DE DOS CUADRADOS PERFECTOS -- 1.9.5 TRINOMIO CUADRADO PERFECTO -- 1.9.6 TRINOMIO DE LA FORMA X2 + BX + C -- 1.9.7 TRINOMIO DE LA FORMA AX2 + BX + C -- 1.9.8 SUMA DE CUBOS -- 1.9.9 DIFERENCIA DE CUBOS -- 1.10 CONCEPTO DE SUMATORIA -- 1.10.1 . …”

Tabla de Contenidos: “…Airflow in practice -- 11 Best practices -- 11.1 Writing clean DAGs -- 11.1.1 Use style conventions -- 11.1.2 Manage credentials centrally -- 11.1.3 Specify configuration details consistently -- 11.1.4 Avoid doing any computation in your DAG definition -- 11.1.5 Use factories to generate common patterns -- 11.1.6 Group related tasks using task groups -- 11.1.7 Create new DAGs for big changes -- 11.2 Designing reproducible tasks -- 11.2.1 Always require tasks to be idempotent -- 11.2.2 Task results should be deterministic -- 11.2.3 Design tasks using functional paradigms -- 11.3 Handling data efficiently -- 11.3.1 Limit the amount of data being processed -- 11.3.2 Incremental loading/processing -- 11.3.3 Cache intermediate data -- 11.3.4 Don't store data on local file systems -- 11.3.5 Offload work to external/source systems -- 11.4 Managing your resources -- 11.4.1 Managing concurrency using pools -- 11.4.2 Detecting long-running tasks using SLAs and alerts -- Summary -- 12 Operating Airflow in production -- 12.1 Airflow architectures -- 12.1.1 Which executor is right for me? …”

Tabla de Contenidos: “…5.3.3.2 Case Study 1: Free Spoken Digit (FSD) Recognition -- 5.3.3.3 Case Study 2: Handwritten Digit (MNIST) Recognition -- 5.3.3.4 Case Study 3: American Sign Language (ASL) Recognition -- 5.3.3.5 Implementation and Benchmark -- 5.4 Conclusion -- References -- Chapter 6 Clock Synchronization for Wide‐area Applications1 -- 6.1 Introduction -- 6.2 System Model and Problem Formulation -- 6.2.1 Natural Timestamping for Wireless IoT Devices -- 6.2.2 Clock Synchronization for Wearable IoT Devices -- 6.3 Natural Timestamps in Powerline Electromagnetic Radiation -- 6.3.1 Electrical Network Frequency Fluctuations and Powerline Electromagnetic Radiation -- 6.3.2 Electromagnetic Radiation‐based Natural Timestamping -- 6.3.2.1 Hardware -- 6.3.2.2 ENF Extraction -- 6.3.2.3 Natural Timestamp and Decoding -- 6.3.3 Implementation and Benchmark -- 6.3.3.1 Timestamping Parameter Settings -- 6.3.3.2 Z1 Implementation and Benchmark -- 6.3.4 Evaluation in Office and Residential Environments -- 6.3.4.1 Deployment and Settings -- 6.3.4.2 Evaluation Results -- 6.3.5 Evaluation in a Factory Environment -- 6.3.6 Applications -- 6.3.6.1 Time Recovery -- 6.3.6.2 Run‐time Clock Verification -- 6.3.6.3 Secure Clock Synchronization -- 6.4 Wearables Clock Synchronization Using Skin Electric Potentials -- 6.4.1 Motivation -- 6.4.2 Measurement Study -- 6.4.2.1 Measurement Setup -- 6.4.2.2 iSEP Sensing under Various Settings -- 6.4.3 TouchSync System Design -- 6.4.3.1 TouchSync Workflow -- 6.4.3.2 iSEP Signal Processing -- 6.4.3.3 NTP Assisted with Dirac Combs -- 6.4.4 TouchSync with Internal Periodic Signal -- 6.4.4.1 Extended Design -- 6.4.4.2 Numeric Experiments -- 6.4.4.3 Impact of Clock Skews -- 6.4.5 Implementation -- 6.4.6 Evaluation -- 6.4.6.1 Signal Strength and Wearing Position -- 6.4.6.2 Impact of High‐Power Appliances on TouchSync…”

Tabla de Contenidos: “…8.4.1 Resampling Procedure -- 8.5 Numeric Data: ANOVA -- 8.6 Components of Variance -- 8.6.1 From ANOVA to Regression -- 8.7 Factorial Design -- 8.7.1 Stratification and Blocking -- 8.7.2 Blocking -- 8.8 The Problem of Multiple Inference -- 8.9 Continuous Testing -- 8.9.1 Medicine -- 8.9.2 Business -- 8.10 Bandit Algorithms -- 8.10.1 Web Testing -- 8.11 Appendix: ANOVA, the Factor Diagram, and the F‐Statistic -- 8.11.1 Decomposition: The Factor Diagram -- 8.11.2 Constructing the ANOVA Table -- 8.11.3 Inference Using the ANOVA Table -- 8.11.4 The F‐Distribution -- 8.11.5 Different Sized Groups -- 8.11.5.1 Resampling Method -- 8.11.5.2 Formula Method -- 8.11.6 Caveats and Assumptions -- 8.12 More than One Factor or Variable-From ANOVA to Statistical Models -- 8.13 Python: Contingency Tables and Chi‐square Test -- 8.13.1 Example: Marriage Therapy -- 8.13.2 Example: Imanishi‐Kari Data -- 8.14 Python: ANOVA -- 8.14.1 Visual Comparison of Groups -- 8.14.2 ANOVA Using Resampling Test -- 8.14.3 ANOVA Using the F‐Statistic -- Exercises -- Chapter 9 Correlation -- 9.1 Example: Delta Wire -- 9.2 Example: Cotton Dust and Lung Disease -- 9.3 The Vector Product Sum Test -- 9.3.1 Example: Baseball Payroll -- 9.3.1.1 Resampling Procedure -- 9.4 Correlation Coefficient -- 9.4.1 Inference for the Correlation Coefficient-Resampling -- 9.4.1.1 Hypothesis Test-Resampling -- 9.4.1.2 Example: Baseball Again -- 9.4.1.3 Inference for the Correlation Coefficient: Formulas -- 9.5 Correlation is not Causation -- 9.5.1 A Lurking External Cause -- 9.5.2 Coincidence -- 9.6 Other Forms of Association -- 9.7 Python: Correlation -- 9.7.1 Vector Operations -- 9.7.2 Resampling Test for Vector Product Sums -- 9.7.3 Calculating Correlation Coefficient -- 9.7.4 Calculate Correlation with numpy, pandas -- 9.7.5 Hypothesis Tests for Correlation -- 9.7.6 Using the t Statistic…”

Tabla de Contenidos: “…3.3.6 Methods for Preparing Cash Flow Statements -- 3.4 Funds Flow Statements -- 3.4.1 Sources of Working Capital -- Business Insight 3.2: Currency Fluctuations Hit Operating Cash Flows -- 3.4.2 Funds from Operations -- 3.4.3 Uses of Working Capital -- 3.5 Funds Flow Statements Versus Cash Flow Statements -- 3.6 The Importance of Cash Flow Statements -- Business Snapshot 3.2: Saving Subhiksha -- Key Terms -- Summary -- Classroom Exercises -- Solved Problems -- Unsolved Problems -- Case Application -- Chapter 4: Cost Concepts for Managers -- 4.1 Introduction -- 4.2 Elements of Manufacturing Costs -- 4.2.1 Direct Cost -- 4.2.2 Indirect Cost -- Business Insight 4.1: Innovations in Product Processes -- 4.3 Types of Costing Systems -- 4.3.1 Job-order Costing System -- 4 .3.2 Process Costing System -- Business Insight 4.2: Dual Costing Systems -- 4.3.3 Job-order Costing System Versus Process Costing System -- 4.4 Standard Costing -- 4.5 Variance Analysis -- 4.5.1 Material Variance -- Business Snapshot 4.1: Reducing Packaging Cost -- 4.5.2 Labour Variance -- 4.5.3 Factory Overhead Variance -- 4.6 Approaches to Costing -- 4.7 Activity-based Costing -- 4.8 Budgeting -- 4.8.1 The Importance of Budgeting -- 4.8.2 Types of Budgets -- 4.8.2.1 Sales budget -- 4.8.2.2 Production budget -- Business Snapshot 4.2: GM's Cost Reduction Drive -- 4.8.2.3 Direct materials budget -- 4.8.2.4 Direct labour budget -- 4.8.2.5 Manufacturing overhead budget -- 4.8.2.6 Manufacturing cost budget -- 4.8.2.7 Selling and administrative expense budget -- 4.8.2.8 Cash budget -- 4.8.2.9 Budgeted income statement -- 4.8.2.10 Master budget -- Business Insight 4.3: Static and Flexible Budgets -- Key Terms -- Summary -- Classroom Exercises -- Case Application 1 -- Case Application 2 -- Chapter 5: Cost-Volume-Profit Analysis -- 5.1 Introduction -- 5.2 Understanding CVP Analysis…”

Tabla de Contenidos: “…8.3 Simplified Scripts for Frequently Used Analyses -- 8.4 Example: Difference of Biases -- 8.5 Sampling from the Prior Distribution in JAGS -- 8.6 Probability Distributions Available in JAGS -- 8.6.1 Defining new likelihood functions -- 8.7 Faster Sampling with Parallel Processing in RunJAGS -- 8.8 Tips for Expanding JAGS Models -- 8.9 Exercises -- Chapter 9: Hierarchical Models -- 9.1 A Single Coin from a Single Mint -- 9.1.1 Posterior via grid approximation -- 9.2 Multiple Coins from a Single Mint -- 9.2.1 Posterior via grid approximation -- 9.2.2 A realistic model with MCMC -- 9.2.3 Doing it with JAGS -- 9.2.4 Example: Therapeutic touch -- 9.3 Shrinkage in Hierarchical Models -- 9.4 Speeding up JAGS -- 9.5 Extending the Hierarchy: Subjects Within Categories -- 9.5.1 Example: Baseball batting abilities by position -- 9.6 Exercises -- Chapter 10: Model Comparison and Hierarchical Modeling -- 10.1 General Formula and the Bayes Factor -- 10.2 Example: Two Factories of Coins -- 10.2.1 Solution by formal analysis -- 10.2.2 Solution by grid approximation -- 10.3 Solution by MCMC -- 10.3.1 Nonhierarchical MCMC computation of each model'smarginal likelihood -- 10.3.1.1 Implementation with JAGS -- 10.3.2 Hierarchical MCMC computation of relative model probability -- 10.3.2.1 Using pseudo-priors to reduce autocorrelation -- 10.3.3 Models with different "noise" distributions in JAGS -- 10.4 Prediction: Model Averaging -- 10.5 Model Complexity Naturally Accounted for -- 10.5.1 Caveats regarding nested model comparison -- 10.6 Extreme Sensitivity to Prior Distribution -- 10.6.1 Priors of different models should be equally informed -- 10.7 Exercises -- Chapter 11: Null Hypothesis Significance Testing -- 11.1 Paved with Good Intentions -- 11.1.1 Definition of p value -- 11.1.2 With intention to fix N -- 11.1.3 With intention to fix z.…”

Tabla de Contenidos: “…5.5.3 Zeichencodierungen bei der Ein- und Ausgabe -- 5.5.4 Speichern und Laden von Daten und Objekten -- 5.5.5 Dateiverarbeitung mit dem NIO -- 5.5.6 Neue Hilfsmethoden in der Klasse Files in JDK 11 -- 5.6 Fehlerbehandlung -- 5.6.1 Einstieg in die Fehlerbehandlung -- 5.6.2 Checked Exceptions und Unchecked Exceptions -- 5.6.3 Besonderheiten beim Exception Handling -- 5.6.4 Exception Handling und Ressourcenfreigabe -- 5.6.5 Assertions -- 5.7 Weitere Neuerungen in JDK 9, 10 und 11 -- 5.7.1 Erweiterung der @Deprecated-Annotation in JDK 9 -- 5.7.2 Syntaxerweiterung var in JDK 10 und 11 -- 5.7.3 Versionsverarbeitung mit JDK 9 und 10 -- 5.8 Weiterführende Literatur -- II Bausteine stabiler Java-Applikationen -- 6 Das Collections-Framework -- 6.1 Datenstrukturen und Containerklassen -- 6.1.1 Wahl einer geeigneten Datenstruktur -- 6.1.2 Arrays -- 6.1.3 Das Interface Collection -- 6.1.4 Das Interface Iterator -- 6.1.5 Listen und das Interface List -- 6.1.6 Mengen und das Interface Set -- 6.1.7 Grundlagen von hashbasierten Containern -- 6.1.8 Grundlagen automatisch sortierender Container -- 6.1.9 Die Methoden equals(), hashCode() und compareTo() im Zusammenspiel -- 6.1.10 Schlüssel-Wert-Abbildungen und das Interface Map -- 6.1.11 Erweiterungen am Beispiel der Klasse HashMap -- 6.1.12 Erweiterungen im Interface Map in JDK 8 -- 6.1.13 Collection-Factory-Methoden in JDK 9 -- 6.1.14 Unveränderliche Kopien von Collections mit Java 10 -- 6.1.15 Entscheidungshilfe zur Wahl von Datenstrukturen -- 6.2 Suchen und Sortieren -- 6.2.1 Suchen -- 6.2.2 Sortieren von Arrays und Listen -- 6.2.3 Sortieren mit Komparatoren -- 6.2.4 Erweiterungen im Interface Comparator mit JDK 8 -- 6.3 Utility-Klassen und Hilfsmethoden -- 6.3.1 Nützliche Hilfsmethoden -- 6.3.2 Dekorierer synchronized und unmodifiable -- 6.3.3 Vordefinierte Algorithmen in der Klasse Collections…”

Tabla de Contenidos: “…-- 6.8 One Root to Rule Them All -- 6.8.1 String toString() -- 6.8.2 Size_t toHash() -- 6.8.3 Bool opEquals(Object rhs) -- 6.8.4 Int opCmp(Object rhs) -- 6.8.5 Static Object factory(string className) -- 6.9 Interfaces -- 6.9.1 The Non-Virtual Interface (NVI) Idiom -- 6.9.2 Protected Primitives -- 6.9.3 Selective Implementation -- 6.10 Abstract Classes -- 6.11 Nested Classes -- 6.11.1 Classes Nested in Functions -- 6.11.2 Static Nested Classes -- 6.11.3 Anonymous Classes -- 6.12 Multiple Inheritance -- 6.13 Multiple Subtyping -- 6.13.1 Overriding Methods in Multiple Subtyping Scenarios -- 6.14 Parameterized Classes and Interfaces -- 6.14.1 Heterogeneous Translation, Again -- 6.15 Summary -- 7 Other User-Defined Types -- 7.1 Structs -- 7.1.1 Copy Semantics…”

Tabla de Contenidos: “…4.5.1 Transcriptomic Profiling (Bulk and Single-Cell RNA-Seq) -- 4.5.2 Genetic Mutation and Variation Identification -- 4.5.3 De Novo Genome Assembly -- 4.5.4 Protein-DNA Interaction Analysis (ChIP-Seq) -- 4.5.5 Epigenomics and DNA Methylation Study (Methyl-Seq) -- 4.5.6 Metagenomics -- References -- 5 Early-Stage Next-Generation Sequencing (NGS) Data Analysis: Common Steps -- 5.1 Basecalling, FASTQ File Format, and Base Quality Score -- 5.2 NGS Data Quality Control and Preprocessing -- 5.3 Read Mapping -- 5.3.1 Mapping Approaches and Algorithms -- 5.3.2 Selection of Mapping Algorithms and Reference Genome Sequences -- 5.3.3 SAM/BAM as the Standard Mapping File Format -- 5.3.4 Mapping File Examination and Operation -- 5.4 Tertiary Analysis -- References -- 6 Computing Needs for Next-Generation Sequencing (NGS) Data Management and Analysis -- 6.1 NGS Data Storage, Transfer, and Sharing -- 6.2 Computing Power Required for NGS Data Analysis -- 6.3 Cloud Computing -- 6.4 Software Needs for NGS Data Analysis -- 6.4.1 Parallel Computing -- 6.5 Bioinformatics Skills Required for NGS Data Analysis -- References -- Part III Application-Specific NGS Data Analysis -- 7 Transcriptomics By Bulk RNA-Seq -- 7.1 Principle of RNA-Seq -- 7.2 Experimental Design -- 7.2.1 Factorial Design -- 7.2.2 Replication and Randomization -- 7.2.3 Sample Preparation and Sequencing Library Preparation -- 7.2.4 Sequencing Strategy -- 7.3 RNA-Seq Data Analysis -- 7.3.1 Read Mapping -- 7.3.2 Quantification of Reads -- 7.3.3 Normalization -- 7.3.4 Batch Effect Removal -- 7.3.5 Identification of Differentially Expressed Genes -- 7.3.6 Multiple Testing Correction -- 7.3.7 Gene Clustering -- 7.3.8 Functional Analysis of Identified Genes -- 7.3.9 Differential Splicing Analysis -- 7.4 Visualization of RNA-Seq Data -- 7.5 RNA-Seq as a Discovery Tool -- References…”

Tabla de Contenidos: “…5.9 Modulus Function -- Exercise -- Chapter 6: Quadratic Functions and Theory of Quadratic Equations -- 6.1 Quadratic Functions -- 6.1.1 Quadratic Modeling -- 6.2 Evaluating the Solutions of the Quadratic Equation ax2 + bx + c = 0 -- 6.3 Nature of the Roots of Quadratic Equation -- 6.4 Sum and Product of the Roots -- 6.5 Relations Between the Roots -- 6.6 Condition for the Existence of a Common Root -- 6.7 To form the Equation Whose Roots are r1 and r2 -- 6.8 Graph of the Function f(x) = ax2 + bx + c -- a ≠ 0 -- 6.9 Sign of the Expression f(x) = ax2 + bx + c -- 6.10 Maximum/Minimum Values of a Quadratic Function -- 6.11 Solution of Quadratic Inequalities -- 6.12 Additional Problems -- Exercise -- Chapter 7: Permutation and Combination -- 7.1 Fundamental Counting Principle -- 7.2 Factorial -- 7.3 Permutation -- 7.3.1 Permutation of n Different Things -- 7.3.2 Permutation of n Things not all Different (Taken all Together) -- 7.4 Restricted Permutation -- 7.5 Circular Permutations -- 7.6 Combination -- 7.6.1 To Find the Number of Ways of Selecting r Things Out of n Things -- 7.6.2 Complementary Combination -- 7.6.3 Different Formulas on Combination -- 7.7 Restricted Combinations -- 7.8 Division into Groups -- 7.9 Mixed Problems on Permutation and Combination -- Exercise -- Chapter 8: Mathematical Induction and Binomial Theorem -- 8.1 Principle of Mathematical Induction -- 8.2 Binomial Theorem for a Positive Integral Index -- 8.3 Properties of the Binomial Coefficients -- 8.4 General Term in Binomial Expansion -- 8.5 Middle Term in the Binomial Expansion -- 8.6 Greatest Term in the Binomial Expansion -- 8.7 Binomial Theorem for Any Index -- 8.7.1 Binomial Theorem for a Rational Index -- Exercise -- Chapter 9: Sequence and Series-Its Application to Business -- 9.1 General Idea and Different Types of Sequences -- 9.2 Different Types of Sequence…”

Tabla de Contenidos: “…10.4.3 CPL Instruction -- 10.5 Solved Examples -- Summary -- Points to Remember -- Review Questions -- Evaluate Yourself -- Search for Answers -- Think and Solve -- Chapter 11 : Programming Examples-II -- Chapter Objectives -- 11.1 Introduction -- 11.2 Count 1s in a Byte -- 11.3 Unpack a BCD Number -- 11.4 Pack BCD Digits -- 11.5 Pack Array of Unpacked BCD Digits -- 11.6 Find Largest and Smallest Integers of an Array -- 11.7 Bubble Sorting -- 11.8 Find the Sum of Factorials -- 11.9 Sort Out Numbers Divisible by 4 -- Summary -- Points to Remember -- Review Questions -- Evaluate Yourself -- Search for Answers -- Think and Solve -- Chapter 12 : Advanced Instructions -- Chapter Objectives -- 12.1 Introduction -- 12.2 MOVC Instruction -- 12.3 MOVX Instruction -- 12.4 XCH Instruction -- 12.5 XCHD Instruction -- 12.6 MUL Instruction -- 12.7 DIV Instruction -- 12.8 DA A Instruction -- 12.9 JMP Instruction -- 12.10 SWAP Instruction -- 12.11 JBC Instruction -- 12.12 RETI Instruction -- 12.13 Solved Examples -- Summary -- Points to Remember -- Review Questions -- Evaluate Yourself -- Search for Answers -- Think and Solve -- Chapter 13 : Programming Examples-III -- Chapter Objectives -- 13.1 Compare with External Array -- 13.2 Find Sum of a Series -- 13.3 Reverse an Array -- 13.4 HEX to BCD Conversion -- 13.5 Update Clock Display -- 13.6 Display Shift for Right Entry -- 13.7 Count Number of Words -- 13.8 Generate Prime Numbers -- Summary -- Points to Remember -- Review Questions -- Evaluate Yourself -- Search for Answers -- Think and Solve -- Chapter 14 : External Interrupts -- Chapter Objectives -- 14.1 Introduction -- 14.1.1 What is an Interrupt? …”

Tabla de Contenidos: “…Conté volum 7: Banca dell’Occhio (Emilio Ambasz), p. 54; Saint Edward’s University (Alejandro Aravena), p. 64; Lusatian lakeland landmark (Architektur & landschaft), p. 70; The Yas hotel (Asymtote), p. 76; Sano clinic therapy square (Atelier-Den / Inahara Archi-lab), p. 82; UPENN weave bridge (Cecil Balmond), p. 88; Kielder observatory (Charles Barclay), p. 92; Marcus prize pavilion (Barkow leibinger architects), p. 98; Nordwesthaus (Baumschlager Eberle), p. 102; The Mountaing (BIG), p. 108; Former Arsenale La Maddalena ( Stefano Boeri), p. 116; Three Box House / Hanil Cement Information Center and Guesthouse ( Byoung-soo Cho), p. 122; Liège-Guillemins TGV Station ( Santiago Calatrava), p. 132; The Chronicles of Time (Giacomo Costa), p. 140; Underground (Rand Elliott), p. 146; Bubbletecture H (Shuhei Endo), p. 152; Bahnhof Pionen (Albert France-Lanord), p. 158; Eden Bio ( Edouard François), p. 164; Roof House (Terunobu Fujimori), p. 170; House H ( Sou Fujimoto), p. 176; Towards Paradise ( Gustafson Porter +Gustafson Guthrie Nichol), p. 182; Burnham Pavilion, JS Bach / Zaha Hadid Architects Music Hall (Zaha Hadid), p. 190; Munch Area (Herreros Arquitectos), p. 198; VitraHaus (Herzog &De Meuron), p. 202; Artfarm (HHF), p. 210; HEART: Hearning Museum of Contemporary Art, Knut Hamsun Center (Steven Holl), p. 216; Guangzhou TV and Sightseeing Tower (Information Based Architecture), p. 228; Princess Elisabeth Antarctica (International Polar Foundation), p. 232; Island House (Iroje KHM Architects), p. 244; Green houses (Junya Ishigami), p. 244; ZA-Koenji Public Theater (Toyo Ito), p. 250; The High Line (James Corner Field Operations/Diller Scofidio + Renfro), p. 256; Juvet Landscape Hotel (Jensen & Skodvin Architects), p. 262; Diaphanous Space (Kalhöfer-Korschildgen), p. 268; Church of the Holy Cross, Fiberline Factory ( KHR), p. 274; Top of Tyrol Mountain Platform (LAAC), p. 284; Hotel Aire en Bardenas (Emiliano López Mónica Rivera), p. 290; Blobwall and Toy Furniture (Greg Lynn Form), p. 296; Villa Chardonne (Made in Sàrl), p. 302; Delegation of the Ismaili Imamat (Fumihiko Maki), p. 308; 41 Cooper Square (Morphosis), p. 314; Gateway Art Tower (Eric Own Moss), p. 320; Walls in the Landscape (Susanne Nobis), p. 324; The Beacon of Amsterdam, The Ladies of the Lake (NOX), p. 330; Naoshima Public Baths (Shinro Ohtake), p. 338; Prada Transformer, CCTV Television Station and Headquarters (OMA*AMO/Rem Koolhaas), p. 344; La Olmeda Roman Villa (Paredes Pedrosa Arquitectos), p. 358; EWHA Womans University (Dominique Perrault), p. 364; Emilio and Annavianca Vedova Foundation (Renzo Piano), p. 372; Flowing Gardens (Plasma Studio), p. 378; Villa Navarra (Rudy Ricciotti), p. 384; Alexandra Heritage Center, Mapungubwe Interpretation Center (Peter Rich), p. 390; RDF181 (Rotor), p. 400; Miyajima Office (Hiroshi Sambuichi), p. 406; Serpentine Pavilion, Rolex Learning Center (Sanaa/Kazuyo Sejima + Ryue Nishizawa), p. 412; Termas Geométricas Hot Springs Complex, Villarrica National Park (Germán del Sol), p. 426; Burj Khalifa (Skidmore, Owings & Merrill), p. 432; Frog Queen (Splitterwerk), p. 438; Izu Photo Museum ( Hiroshi Sugimoto), p. 444; Kiltro House (Supersudaka), p. 450; Tenchi House ( Masaharu Takasaki), p. 456; Swarovski Ginza, Waterfall (Yoshioka Tokujin), p. 462; Production Facilities for Les Ballets C de la B and LOD (de Vylder Vinck Taillieu), p. 470.…”

“…Vingerhoets, Executive Director, ICCOCocoa is a valuable commodity, and the cocoa trade involves many different parties from growers and exporters through dealers and factories to those trading futures and options and the banks they deal with. …”

“…It examines the case studies of two large factories, Carl Zeiss Jena (East Germany) and Rába…”

“…Industrial management topics related to Smart Factories, Operations Research, and Value Chain are also discussed"--…”

“…Técnicas descriptivas multivariantes: análisis factorial exploratorio y análisis de cluster o conglomerados. 4. …”
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“…En segundo lugar, identificar, a partir de la realización de un análisis factorial, las dimensiones más relevantes que integran la variable calidad de servicio en este tipo de establecimientos…”
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“…Its four-frame model examines organizations as factories, families, jungles, and theaters or temples:The Structural Frame: how to organize and structure groups and teams to get resultsThe Human Resource Frame: how to tailor organizations to satisfy human needs, improve human resource management, and build positive interpersonal and group dynamicsThe Political Frame: how to cope with power and conflict, build coalitions, hone political skills, and dea…”