Tabla de Contenidos: “…2.3 How Data Is Organized on a Hard Disk Drive2.4 Hard Disk Drive Performance and Reliability; 2.5 Hard Disk Drive Design for Mobile and Static Consumer Electronics Applications; 2.6 The Cost of Manufacturing a Hard Disk Drive; 2.7 Disk Drive External Interfaces; 2.8 Hard Disk Drive Technology Development; 2.9 Chapter Summary; CHAPTER 3: Fundamentals of Optical Storage; 3.1 Optical Disc Technologies; 3.2 Basic Operation of an Optical Disc Drive; 3.3 How Data Is Organized on an Optical Disc; 3.4 Optical Disc Form Factors; 3.5 Optical Product Reliability; 3.6 Holographic Recording…”

“…When choosing the technology options to develop a wireless sensor network (WSN), it is vital that their performance levels can be assessed for the type of application intended. …”

Tabla de Contenidos: “…4.8 Conditional returns and correlations4.9 Hedge fund behavior in extreme market situations; 4.10 Benefits of hedge funds in a traditional portfolio; 4.11 Quantitative portfolio optimization for hedge funds revisited; 4.12 Summary of empirical properties; 4.13 Appendix: Data providers for past hedge fund performance; 5 The Drivers of Hedge Fund Returns; 5.1 Alpha versus beta; 5.2 The enigma of hedge fund returns; 5.3 Hedge fund returns: how much is alpha?…”

Tabla de Contenidos: “…Programming Streaming FPGA Applications Using Block Diagrams in Simulink; 8.1 Designing High-Performance Datapaths Using Stream-Based Operators; 8.2 An Image-Processing Design Driver…”

Tabla de Contenidos: “…4.4.2 Photoconductors in Silicon: Dynamic Performance4.5 Photon Detection in Silicon pn Junctions; 4.5.1 Defining the Depletion Layer at a pn Junction; 4.5.2 Electron-hole Collection in the Depletion Layer; 4.5.3 Electron-hole Collection in the Substrate; 4.5.4 Electron-hole Collection Close to the Surface; 4.5.5 Backside-illuminated Pin Photodiode; 4.5.6 Electron-hole Collection in Two Stacked pn Junctions; 4.6 Detection Limit; 4.6.1 Noise in the Optical Signal; 4.6.2 Photon Detector Noise; 4.6.3 Photon Detector Readout; 4.7 Photon Detectors with Gain; 4.7.1 The Phototransistor…”

Tabla de Contenidos: “…SYNCHRONOUS MOTOR DRIVES; 7. PERFORMANCE OF BRUSHLESS MOTORS; 8.RELUCTANCE AND HYSTERESIS MOTORS…”

Tabla de Contenidos: “…4.3 SMP Architectures with a Moderate Number of Processors (<= 8)4.4 Multiprocessors with Many Processors (More than 16); 4.5 SMP, CC-NUMA, COMA: a Summary; 4.6 Performance Improvement Provided by SMP; 4.7 Advantages and Disadvantages of SMP Architecture; 4.8 Endnotes; Chapter 5. …”

Tabla de Contenidos: “…Storage Management; 3.1 Disk fundamentals; 3.2 Data operations; 3.3 SAME; 3.4 Oracle Managed Files; 3.5 Storage options for RAC; 3.6 Automatic storage management (ASM); 3.7 Migration to ASM; 3.8 ASM performance monitoring using EM; 3.9 ASM implementations; 3.10 ASM instance crash; 3.11 ASM disk administration; 3.12 Client connection to an ASM instance; 3.13 Conclusion…”

Tabla de Contenidos: “…5.5 Memory as a Limiting Factor to Parallelism5.6 Summary; 5.7 Exercises; 6 Performance Considerations; 6.1 Warps and Thread Execution; 6.2 Global Memory Bandwidth; 6.3 Dynamic Partitioning of Execution Resources; 6.4 Instruction Mix and Thread Granularity; 6.5 Summary; 6.6 Exercises; References; 7 Floating-Point Considerations; 7.1 Floating-Point Format; Normalized Representation of M; Excess Encoding of E; 7.2 Representable Numbers; 7.3 Special Bit Patterns and Precision in Ieee Format; 7.4 Arithmetic Accuracy and Rounding; 7.5 Algorithm Considerations; 7.6 Numerical Stability; 7.7 Summary…”

Tabla de Contenidos: “…Photonic Sensing; Contents; Preface; Contributors; 1 Surface Plasmons for Biodetection; 1.1 Introduction; 1.2 Principles of SPR Biosensors; 1.2.1 Surface Plasmons; 1.2.2 Excitation of Surface Plasmons; 1.2.3 Sensors Based on Surface Plasmons; 1.2.4 SPR Affinity Biosensors; 1.2.5 Performance Characteristics of SPR Biosensors; 1.3 Optical Platforms for SPR Sensors; 1.3.1 Prism-Based SPR Sensors; 1.3.2 SPR Sensors Based on Grating Couplers; 1.3.3 SPR Sensors Based on Optical Waveguides; 1.3.4 Commercial SPR Sensors; 1.4 Functionalization Methods for SPR Biosensors; 1.4.1 Functional Layers…”

Tabla de Contenidos: “…Optimizing Your Media Server Hardware for Better Performance; Display Resolution; Display Refresh Rates; Prep Step #3. …”

“…The structural materials used in airframe and propulsion systems influence the cost, performance and safety of aircraft, and an understanding of the wide range of materials used and the issues surrounding them is essential for the student of aerospace engineering.Introduction to aerospace materials reviews the main structural and engine materials used in aircraft, helicopters and spacecraft in terms of their production, properties, performance and applications.The first three chapters of the book introduce the reader to the range of aerospace materials, focusing on recent developments…”

“…In the last few years, Android has progressed with the debut of better fonts, new User Interface and Experience (UI/UX) APIs, tablet considerations, multi-touch capabilities, multi-tasking, faster performance, improved battery management techniques, and now Google TV Android Apps for the Android game app developer repertoire. …”

Tabla de Contenidos: “…Default ValuesUndoing and Redoing; Undo Groups; Limiting the Undo Stack; Disabling Undo Tracking; Adding Undo to Shapes; Summary; Chapter 6 Refining Result Sets; Building the Test Application; Creating the Org Chart Data; Reading and Outputting the Data; Filtering; Expressions for a Single Value; Expressions for a Collection; Comparison Predicates; Compound Predicates; Subqueries; Aggregating; Sorting; Returning Unsorted Data; Sorting Data on One Criterion; Sorting on Multiple Criteria; Summary; Chapter 7 Tuning Performance and Memory Usage; Building the Application for Testing…”

“…"Unleash innovation potential with creative, serious playBuilding a Better Business Using the LEGO(r) SERIOUS PLAY(r) Method delivers a creative approach to enhancing innovation and improving business performance, with the focus on unleashing play. Written by the two original Master Trainers for LEGO SERIOUS PLAY (LSP), the book outlines how LSP can develop teams, people, relationships and business. …”

Tabla de Contenidos: “…1.2.3 Cost-Effective Resource Sharing1.2.4 Support for Common Services; Identifying Common Communication Patterns; Reliability; 1.2.5 Manageability; 1.3 Network Architecture; 1.3.1 Layering and Protocols; Encapsulation; Multiplexing and Demultiplexing; The 7-Layer Model; 1.3.2 Internet Architecture; 1.4 Implementing network software; 1.4.1 Application Programming Interface (Sockets); 1.4.2 Example Application; Client; Server; 1.5 Performance; 1.5.1 Bandwidth and Latency; 1.5.2 Delay X Bandwidth Product; 1.5.3 High-Speed Networks; 1.5.4 Application Performance Needs; 1.6 Summary…”

Tabla de Contenidos: “…3.3.3 Relative Intensity Noise and Laser Phase Noise3.3.4 Modal Noise; 3.3.5 Quantum Shot Noise; 3.3.6 Dark Current Noise; 3.3.7 Thermal Noise; 3.3.8 Spontaneous Emission Noise; 3.3.9 Noise Beat Components; 3.3.10 Crosstalk Components; 3.4 Channel Impairments; 3.4.1 Fiber Attenuation; 3.4.2 Insertion Losses; 3.4.3 Chromatic Dispersion; 3.4.4 Polarization Mode Dispersion; 3.4.5 Fiber Nonlinearities; 3.5 Transmission System Performance Assessment and System Design; 3.5.1 Quantum Limit for Photodetection; 3.5.2 Shot Noise and Thermal Noise Limit…”

Tabla de Contenidos: “…-- Summary -- Chapter 8: Regular Expression Pitfalls, Optimization, and Performance Improvements -- Common pitfalls and ways to avoid them while writing regular expressions -- Do not forget to escape regex metacharacters outside a character class -- Avoid escaping every non-word character -- Avoid unnecessary capturing groups to reduce memory consumption -- However, don't forget to use the required group around alternation -- Use predefined character classes instead of longer versions -- Use the limiting quantifier instead of repeating a character or pattern multiple times -- Do not use an unescaped hyphen in the middle of a character class -- The mistake of calling matcher.goup() without a prior call to matcher.find(), matcher.matches(), or matcher.lookingAt() -- Do not use regular expressions to parse XML / HTML data -- How to test and benchmark your regular expression performance -- Catastrophic or exponential backtracking -- How to avoid catastrophic backtracking -- Optimization and performance enhancement tips -- Use a compiled form of regular expressions -- Use a negated character class instead of the greedy and slow .* or .+ -- Avoid unnecessary grouping…”

Tabla de Contenidos: “…Data download and exploration -- Preparing the data for our models -- The binary classification model -- The regression model -- Improving the binary classification model -- The unreasonable effectiveness of data -- Summary -- Chapter 5: Image Classification Using Convolutional Neural Networks -- CNNs -- Convolutional layers -- Pooling layers -- Dropout -- Flatten layers, dense layers, and softmax -- Image classification using the MXNet library -- Base model (no convolutional layers) -- LeNet -- Classification using the fashion MNIST dataset -- References/further reading -- Summary -- Chapter 6: Tuning and Optimizing Models -- Evaluation metrics and evaluating performance -- Types of evaluation metric -- Evaluating performance -- Data preparation -- Different data distributions -- Data partition between training, test, and validation sets -- Standardization -- Data leakage -- Data augmentation -- Using data augmentation to increase the training data -- Test time augmentation -- Using data augmentation in deep learning libraries -- Tuning hyperparameters -- Grid search -- Random search -- Use case-using LIME for interpretability -- Model interpretability with LIME -- Summary -- Chapter 7: Natural Language Processing Using Deep Learning -- Document classification -- The Reuters dataset -- Traditional text classification -- Deep learning text classification -- Word vectors -- Comparing traditional text classification and deep learning -- Advanced deep learning text classification -- 1D convolutional neural network model -- Recurrent neural network model -- Long short term memory model -- Gated Recurrent Units model -- Bidirectional LSTM model -- Stacked bidirectional model -- Bidirectional with 1D convolutional neural network model -- Comparing the deep learning NLP architectures -- Summary -- Chapter 8: Deep Learning Models Using TensorFlow in R.…”

Tabla de Contenidos: “…Into the Unthought Known -- Finding Culture in Talk -- Unthought Knowns -- Ethnographic Action Research -- Quantitative Analysis -- Results -- How These SDLs Make Up the Reference System -- Patterns in Practice -- Adaptations -- The I3 Reference System -- FINANCIAL PERFORMANCE FIRST -- How Does It Show Up? (Practices and Adaptations) -- When Overlearned ... -- Where Does This SDL Come From? …”