Tabla de Contenidos: “…Chapter 5: AI Machine Vision System for Wafer Defect Detection -- 5.1: Introduction and Background -- 5.2: Machine Vision-based System Description -- 5.3: Conclusion -- References -- Chapter 6: Failure Detection in Silicon Package -- 6.1: Introduction and Background -- 6.2: Dataset Description -- 6.2.1: Data Collection &amp -- Labelling -- 6.3: Development and Deployment -- 6.4: Transfer Learning and Scalability -- 6.5: Result and Discussion -- 6.6: Conclusion and Outlooks -- References -- Chapter 7: S2ORC-SemiCause: Annotating and Analysing Causality in the Semiconductor Domain -- 7.1: Introduction -- 7.2: Dataset Creation -- 7.2.1: Corpus -- 7.2.2: Annotation Guideline -- 7.2.3: Annotation Methodology -- 7.2.4: Dataset Statistics -- 7.2.5: Causal Cue Phrases -- 7.3: Baseline Performance -- 7.3.1: Train-Test Split -- 7.3.2: Causal Argument Extraction -- 7.3.3: Error Analysis -- 7.4: Conclusions -- References -- Chapter 8: Feasibility of Wafer Exchange for European Edge AI Pilot Lines -- 8.1: Introduction -- 8.2: Technical Details and Comparison -- 8.2.1: Comparison TXRF and VPD-ICPMS Equipment for Surface Analysis -- 8.2.2: VPD-ICPMS Analyses on Bevel -- 8.3: Cross-Contamination Check-Investigation -- 8.3.1: Example for the Comparison of the Institutes -- 8.4: Conclusiion -- References -- Chapter 9: A Framework for Integrating Automated Diagnosis into Simulation -- 9.1: Introduction -- 9.2: Model-based Diagnosis -- 9.3: Simulation and Diagnosis Framework -- 9.3.1: FMU Simulation Tool -- 9.3.2: ASP Diagnose Tool -- 9.4: Experiment -- 9.5: Conclusion -- References -- Chapter 10: Deploying a Convolutional Neural Network on Edge MCU and Neuromorphic Hardware Platforms -- 10.1: Introduction -- 10.2: Related Work -- 10.3: Methods -- 10.3.1: Neural Network Deployment -- 10.3.1.1: Task and Model -- 10.3.1.2: Experimental Setup -- 10.3.1.3: Deployment…”

Tabla de Contenidos: “…Public Companies (1999)5.2.10 Joseph Wells, Principles of Fraud Examination (2005); 5.3 The Statistical Studies; 5.3.1 Earnings Management Studies; 5.4 Conclusion; 6 Impression Management; 6.1 Introduction; 6.1.1 Accounting Narratives; 6.1.2 Graphs; 6.2 Conclusion; 7 Taking the Long View: Accounting Scandals over Time; 7.1 Introduction; 7.1.1 Ancient and Medieval; 7.1.2 Seventeenth and Eighteenth Centuries; 7.1.3 Nineteenth Century; 7.1.4 Twentieth Century: Before Second World War…”

Tabla de Contenidos: “…Exploring the Functional World in a Computer Enriched Environment, Carmen Sessa -- Re-centring the individual in participatory accounts of professional identity, Jeppe Skott -- Enactive metaphorising in the learning of mathematics, Jorge Soto-Andrade -- Number Sense in Elementary School Children from different Social Backgrounds: The uses and Meanings Given to Numbers, Alina Galvão Spinillo -- Uncovering Chinese Pedagogy: Spiral Variation—The Unspoken Principle of Algebra Thinking to Develop Chinese Curriculum and instruction of “Two Basics”, Xuhua Sun -- Digital Pedagogy in Mathematics Learning, Yahya Tabesh -- Activity Theory in French Didactic Research, Fabrice Vandebrouck -- The effect of a video-based intervention on the knowledge-based reasoning of future mathematics teachers, Naďa Vondrová -- Popularization of the of Probability Theory and Statistics in School Through Intellectual Competitions, Ivan Vysotskiy -- Noticing in Pre-Service Teacher Education: Research Lessons as a context for reflection on learners’ Mathematical Reasoning and Sense-Making, Helena Wessels -- Dialogues on Numbers: Script-writing as approximation of practice, Rina Zazkis -- Equity in mathematics education: What did TIMSS and PISA tell us in the last two decades? …”

Tabla de Contenidos: “…Industrial Organic Chemicals; Contents; Preface; Preface to the First Edition; Preface to the Second Edition; Acknowledgments; Bryan Godel Reuben 1934-2012; List of Acronyms and Abbreviations; Introduction: How to Use Industrial Organic Chemicals, Third Edition; I.1 Why This Book Was Written and How It Is Structured; I.2 North American Industry Classification System; I.3 Units and Nomenclature; I.4 General Bibliography; I.4.1 Encyclopedias; I.4.2 Books; I.4.3 Journals; I.4.4 Patents; I.4.5 Statistics and Internet Sources of Information; 1. The Evolution of the Organic Chemicals Industry…”

Tabla de Contenidos: “…4.5.1 Industries Shifting to AI-Enabled Big Data Analytics -- 4.5.2 Industries Shifting to AI-Powered IoT Devices -- 4.5.3 Statistical Data of These Shifts -- 4.6 Conclusion -- References -- 5 IoT's Data Processing Using Spark -- 5.1 Introduction -- 5.2 Introduction to Apache Spark -- 5.2.1 Advantages of Apache Spark -- 5.2.2 Apache Spark's Components -- 5.3 Apache Hadoop MapReduce -- 5.3.1 Limitations of MapReduce -- 5.4 Resilient Distributed Dataset (RDD) -- 5.4.1 Features and Limitations of RDDs -- 5.5 DataFrames -- 5.6 Datasets -- 5.7 Introduction to Spark SQL -- 5.7.1 Spark SQL Architecture…”

Tabla de Contenidos: “…-- Simulated Direct Loan Portfolios with Leverage -- Determinants of Financing Costs -- Chapter 12 Business Development Companies -- What is a BDC? -- BDC Industry Statistics -- Private BDCs -- Publicly Traded BDCs -- BDC Market Indices -- BDCs - A Tale of Two Markets -- BDC Dividend Yield -- BDC Total Return -- Chapter 13 Selecting Direct Lending Managers -- Selection Matters -- Manager Direct Loan Yield -- Credit Losses Across Direct Lenders -- Total Return -- Direct Lending Managers -- Organization…”

Tabla de Contenidos: “…-- Basics of RDD operation -- Summary -- Chapter 3: Big Data Cleaning and Wrangling with Spark Notebooks -- Using Spark Notebooks for quick iteration of ideas -- Sampling/filtering RDDs to pick out relevant data points -- Splitting datasets and creating some new combinations -- Summary -- Chapter 4: Aggregating and Summarizing Data into Useful Reports -- Calculating averages with map and reduce -- Faster average computations with aggregate -- Pivot tabling with key-value paired data points -- Summary -- Chapter 5: Powerful Exploratory Data Analysis with MLlib -- Computing summary statistics with MLlib -- Using Pearson and Spearman correlations to discover correlations -- The Pearson correlation -- The Spearman correlation -- Computing Pearson and Spearman correlations -- Testing our hypotheses on large datasets -- Summary -- Chapter 6: Putting Structure on Your Big Data with SparkSQL -- Manipulating DataFrames with Spark SQL schemas -- Using Spark DSL to build queries -- Summary -- Chapter 7: Transformations and Actions -- Using Spark transformations to defer computations to a later time -- Avoiding transformations -- Using the reduce and reduceByKey methods to calculate the results…”

Tabla de Contenidos: “…-- How to do Clustering in Tableau -- Creating Clusters -- Clustering example in Tableau -- Creating a Tableau group from cluster results -- Constraints on saving Clusters -- Interpreting your results -- How Clustering Works in Tableau -- The clustering algorithm -- Scaling -- Clustering without using k-means -- Hierarchical modeling -- Statistics for Clustering -- Describing Clusters - Summary tab -- Testing your Clustering -- Describing Clusters - Models Tab -- Introduction to R -- Summary -- Chapter 7: Advanced Analytics with Unsupervised Learning -- What are neural networks? …”

Tabla de Contenidos: “…4.1.3 Serial Independence: Ljung-Box and McLeod-Li Tests4.1.5 Normality; 4.1.6 Neural Network Test for Neglected Nonlinearity: Lee-White-Granger Test; 4.1.7 Brock-Deckert-Scheinkman Test for Nonlinear Patterns; 4.1.8 Summary of In-Sample Criteria; 4.1.9 MATLAB Example; 4.2 Out-of-Sample Criteria; 4.2.1 Recursive Methodology; 4.2.2 Root Mean Squared Error Statistic; 4.2.3 Diebold-Mariano Test for Out-of-Sample Errors; 4.2.4 Harvey, Leybourne, and Newbold Size Correction of Diebold-Mariano Test; 4.2.5 Out-of-Sample Comparison with Nested Models…”

Tabla de Contenidos: “…. -- 57 Not everything that counts can be counted. -- 58 Test for statistical generalizability. -- 59 Don't base personas on assumptions. -- 60 Keep your enemies close. -- 61 Learn from bad examples. -- 62 Make expectations work in your favor. -- 63 Uncover consensus and ambiguity. -- Design -- 64 Brainstorm efficiently. -- 65 Build consensus. -- 66 Learn from real-world navigation. -- 67 Build a logical structure. -- 68 Visualize the relationship between pages. -- 69 Don't get gimmicky with navigation. -- 70 Yes, side doors matter. -- 71 Prime before presenting. -- 72 Move from low to high fidelity. -- 73 Don't just illustrate, annotate. -- 74 Interaction design is the brand. -- 75 Bad typography leads to bad UX. -- 76 So you think you can scroll. -- 77 Animate responsibly. -- 78 Make data lovable. -- 79 Dark mode rises. -- 80 Never give total control. -- 81 Personalization is hit or miss. -- 82 A word is worth a thousand pictures. -- 83 Understand the sales funnel. -- 84 Target the right devices. -- 85 Systems are great for corporations. -- 86 Modularity is great for designers. -- 87 Expect the unexpected. -- Validate -- 88 Voice assistants suck. -- 89 Don't ask for unnecessary things. -- 90 Manage errors effectively. -- 91 Accept many inputs. -- 92 Confirm user actions. -- 93 Broken pages shouldn't feel broken. -- 94 Fill the gap imagination can't bridge. -- 95 Metric-based design is silly. -- 96 Most issues can be spotted a mile ahead. -- 97 Don't grade your own homework. -- 98 Get the most bang for your buck. -- 99 Stay involved postlaunch. -- 100 Lower expectations for high satisfaction. -- About the Author -- Acknowledgments -- Index -- Copyright…”

Tabla de Contenidos: “…Corpus documentation; 1.4.7. Statistical analysis of data; 1.4.8. The use of corpora in NLP; 1.5. …”

Tabla de Contenidos: “…An Evaluation of Social Conversations with a Virtual Receptionist -- Characteristics of Nonverbal Behavior -- Gesture Expressivity Modulations in an ECA Application -- Visual Attention and Eye Gaze During Multiparty Conversations with Distractions -- Behavior Representation Languages -- Towards a Common Framework for Multimodal Generation: The Behavior Markup Language -- MPML3D: A Reactive Framework for the Multimodal Presentation Markup Language -- Generation of Nonverbal Behavior with Speech -- Creativity Meets Automation: Combining Nonverbal Action Authoring with Rules and Machine Learning -- Nonverbal Behavior Generator for Embodied Conversational Agents -- [HUGE]: Universal Architecture for Statistically Based HUman GEsturing -- A Story About Gesticulation Expression -- IVAs in Serious Games -- Introducing EVG: An Emotion Evoking Game -- Towards a Reactive Virtual Trainer -- Making It Up as You Go Along – Improvising Stories for Pedagogical Purposes -- Cognition and Emotion I -- A Neurobiologically Inspired Model of Personality in an Intelligent Agent -- Feeling Ambivalent: A Model of Mixed Emotions for Virtual Agents -- Are Computer-Generated Emotions and Moods Plausible to Humans? …”

Tabla de Contenidos: “…10.1 Compound Materials versus Silicon10.2 Substrate Materials for GaN Devices; 10.3 Polarization Properties of III-Nitride Wurtzite; 10.4 AlGaN/GaN Heterojunction; 10.5 Traps in AlGaN/GaN Structure; 10.6 A Simple AlGaN/GaN HEMT; 10.7 GaN Power HEMT Example I; 10.8 GaN Power HEMT Example II; 10.9 Gate Leakage Simulation of GaN HEMT; 10.10 Market Prospect of Compound Semiconductors for Power Applications; Appendix A: Carrier Statistics; Appendix B: Process Simulation Source Code; Appendix C: Trap Dynamics and AC Analysis; Bibliography…”

Tabla de Contenidos: “…Environmental Epidemiology -- Copyright -- Preface -- Contents -- Summary -- ORGANIZATION OF THE REPORT -- Section One: Public Health And Hazardous Wastes: The Context -- Chapter 1: Introduction -- Chapter 2: State and Federal Context for Environmental Epidemiology of Hazardous Wastes -- Chapter 3: Dimensions of the Problem: Exposure Assessment -- Section Two: Hazardous Wastes In Air, Water, Soil, And Food -- Biologic Markers -- Chapter 4: Air Exposures -- Chapter 5: Domestic Water Consumption -- Chapter 6: Soil and Food as Potential Sources of Exposure at Hazardous Waste Sites -- Chapter 7: Biologic Markers in Studies of Hazardous-Waste Sites -- CONCLUSIONS -- Section One Public Health and Hazardous Wastes: The Context -- 1 Introduction -- ENVIRONMENTAL EPIDEMIOLOGY -- Epidemiologic Research -- Causal Inference -- Statistical Significance -- Causation In Epidemiology -- Strength of the Association -- Specificity of the Association -- Consistency of the Association -- Temporality -- Biologic Gradient or Relationship Between Estimated Exposure and Disease -- Effects of the Removal of a Suspected Cause -- Biological Plausibility -- CHALLENGES IN THE STUDY OF HAZARDOUS-WASTE SITES -- Historical Context Of The Study -- Agency For Toxic Substances And Disease Registry -- OVERVIEW OF THIS VOLUME -- References -- 2 State and Federal Context for Environmental Epidemiology of Hazardous Wastes -- FEDERAL LEGISLATION, POLICIES, AND PROGRAMS -- Hazardous-Waste Site Evaluation And Remediation -- Preremedial Process -- Remedial Process -- Development and Screening of Alternatives -- DISTRIBUTION OF EXPOSURE -- Universe Of Potential Exposures -- CHARACTERIZATION OF EXPOSURE -- Preremediation Phase -- Remediation Phase -- Deferral Of Sites And Nfrap Designation -- FEDERAL POLICIES AND ENVIRONMENTAL EPIDEMIOLOGY -- STATE PROGRAMS…”

Tabla de Contenidos: “…11.2 Managing Using Oracle Enterprise Manager11.3 Monitoring the Warehouse; 11.4 Reorganizing the Warehouse; 11.5 Refreshing the Warehouse; 11.6 Gathering Optimizer Statistics; 11.7 Parallel Management Tasks; 11.8 Maintaining Security; 11.9 Monitoring Space Usage; 11.10 Other Management Issues; 11.11 Summary; Chapter 12. …”

Tabla de Contenidos: “…Investigating and Influencing the Optimizer; 8.1 Text-based query plans and statistics; 8.2 Query plans in Management Studio; 8.3 Hinting to the optimizer; 8.4 Stored procedures and the query optimizer; 8.5 Non-stored procedure plans; 8.6 The syscacheobjects system table; Chapter 9. …”

Tabla de Contenidos: “…Networking-Related CommandsClient Utilities; finger; ftp; hostname; irftp; rcp; rsh, rexec; telnet; tftp; Administrative Utilities; arp; atmadm; dhcplocRK; dnscmd; getmacRK; iisreset; ipconfig; ipsecpolRK; nbtstat; net session; net statistics; netsh; netstat; nslookup; pathping; ping; pptpclnt, pptpsrv; qtcpRK; rasdial; raslistRK; rasusersRK; route; rpingsRK; tracert; winschkRK; winsclRK; Administering Users and Groups; addusersRK; cusrmgrRK; delprofRK; globalRK; localRK; net accounts; net group; net localgroup; net user; ntrightsRK; sdcheck; showgrpsRK; showmbrsRK; showprivRK; usrstatRK…”

Tabla de Contenidos: “…Text Documents; 2.1 Computer Typesetting; 2.2 Text Formats; 2.3 Ways of Searching; 2.4 Web Searching; 2.5 Thesauri; 2.6 Statistical Language Processing; 2.7 Document Conversion; 2.8 Summary; Chapter 3. …”

Tabla de Contenidos: “…Radio Propagation and Propagation Path-Loss Models; 3.1 Introduction; 3.2 Free-Space Attenuation; 3.3 Attenuation over Reflecting Surface; 3.4 Effect of Earth's Curvature; 3.5 Radio Wave Propagation; 3.6 Characteristics of a Wireless Channel; 3.7 Signal Fading Statistics; 3.8 Level Crossing Rate and Average Fade Duration; 3.9 Propagation Path-Loss Models; 3.10 Indoor Path-Loss Models; 3.11 Fade Margin…”

Tabla de Contenidos: “…3.2.2 Geometric Multilateration Based on AOA Measurements3.2.3 Geometric Multilateration Based on TDOA Measurements; 3.3 Statistical Multilateration; 3.3.1 Least-Squares Multilateration; 3.3.2 LS Multilateration with Uncertain Reference Node Positions; 3.3.3 Hybrid Location Estimation Systems; 3.4 Location Estimation in Multihop Scenarios; 3.4.1 Centroid Algorithm; 3.4.2 Approximate Point-in-Triangulation Algorithm; 3.4.3 Ad Hoc Positioning System Algorithms; 3.4.4 Dead-Reckoning; 3.5 Performance Assessment of Location Estimation Systems; 3.5.1 Cramer-Rao Bound…”