Search Results - "algorithms"

Radar for Fully Autonomous Driving. by Markel, Matt

Table of Contents: “…4.2.1 Waveform Orthogonality via TDM -- 4.2.2 Waveform Orthogonality via DDM -- 4.2.3 Waveform Orthogonality via FDM -- 4.3 Angle Finding in Automotive MIMO Radar -- 4.3.1 High Resolution Angle Finding with ULA -- 4.3.2 High Resolution Angle Finding with SLA -- 4.4 High Resolution Imaging Radar for Autonomous Driving -- 4.4.1 Cascade of Multiple Radar Transceivers -- 4.4.2 Examples of Cascaded Imaging Radars -- 4.4.3 Design Challenges of Imaging Radar -- 4.5 Challenges in Automotive MIMO Radar -- 4.5.1 Angle Finding in the Presence of Multipath Reflections -- 4.5.2 Waveform Orthogonality in Automotive MIMO Radar -- 4.5.3 Efficient, High Resolution Angle Finding Algorithms Are Needed -- References -- Chapter 5 Synthetic Aperture Radar for Automotive Applications -- 5.1 Introduction -- 5.1.1 Historical Background -- 5.1.2 Comparison to Traditional Radar Systems -- 5.1.3 SAR and Point Cloud Imaging Performance -- 5.1.4 Applications for Automotive Use -- 5.2 Mathematical Foundation -- 5.2.1 Key Assumptions -- 5.2.2 Signal Model -- 5.2.3 Slow Time -- 5.3 Building an Automotive SAR -- 5.3.1 Measuring Ego-Motion -- 5.3.2 SAR Image Formation -- 5.3.3 Coexistence with Point Cloud Pipeline -- 5.3.4 Elevation Information -- 5.4 Future Directions -- 5.4.1 Forward-Facing SAR -- 5.4.2 SAR for Moving Objects -- 5.4.3 Gapped SAR -- 5.5 Conclusion -- References -- Chapter 6 Radar Transceiver Technologies -- 6.1 Background and Introduction to Automotive Radar -- 6.2 Block Diagram Overview of an FMCW Radar Transceiver -- 6.3 Challenges with Deeply Scaled CMOS -- 6.4 Active Devices in CMOS -- 6.5 Passives in CMOS -- 6.6 Circuit Architectures Suitable for Advanced CMOS -- 6.6.1 The Transmit Power Amplifier -- 6.6.2 The TX Phase Shifter -- 6.7 The LO/FMCW Chirp Generator -- 6.8 The Receiver Signal Chain -- 6.8.1 RX Frontend -- 6.8.2 Radar RX Baseband -- 6.9 Summary.…”
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Electromagnetic nondestructive evaluation (XII)

Table of Contents: “…Elastic Properties of Thermally Aged Fe-Cu Model Alloys Measured by EMAR Method -- Nondestructive Evaluation of Ferromagnetic Structural Materials Using FG Sensor -- Inverse Problem and Imaging -- Standoff Detection and Imaging of Suspicious and Concealed Objects with Electromagnetic Waves in the Centimetre and Millimetre Range -- Pulsed Terahertz Imaging for Nondestructive Evaluation -- On the Imaging of Two-Dimensional Thin Inclusions by a MUSIC-Type Algorithm from Boundary Measurements -- Chance-Constrained Programming: A Tool for Solving Linear Eddy Current Inverse Problem -- A Multiple Frequency Strategy for Reconstruction of Stress Corrosion Crack from ECT Signals -- Estimation Theory Metrics in Electromagnetic NDE -- Three Dimensional Shape Recovery of Fatigue Crack Using Eddy Current Testing Signals -- Application of Electromagnetic Nondestructive Techniques -- Development of Strong Magnetizer and Robust Sensor Mount System to Increase Performance in Detecting Defects on Pipeline -- Electromagnetic Evaluation of Honeycomb Composite Materials -- An Electromagnetic Method for Evaluation of Fatigue and for Detection of Damage at Bjork-Shiley Convexo-Concave Prosthetic Heart Valves -- Electromagnetic Evaluation of Soil Condition -- Investigation of Cu-Pc Thin Films on ITO Substrate by Using a Near-Field Microwave Microprobe -- Noncontact Characterization of Electric Carriers Density at Heterojunction Interfaces -- Electromagnetic Field Interaction with Aqueous Glucose Solution in Dielectric Resonator -- Quantitative Evaluation of Corrosion Shape on Back Surface of SUS Samples by EMAT -- Inspection of 3D Flaws Using EMAT -- Nondestructive Evaluation of Beryllium to Copper Joining for ITER by Using an Electromagnetic Acoustic Transducer (EMAT) -- Subject Index -- Author Index.…”
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Automated/mechanized drilling and countersinking of airframes by Bullen, George N.

Table of Contents: “…4.3.5 Vision System4.3.6 Inspection; 4.3.7 Integration Level II; 4.4 Controller; 4.4.1 Human Machine Interface; 4.4.2 Volumetric Compensation Algorithm; 4.4.3 Integration Level III; 4.5 Calibration; 4.6 Sustainability; 4.7 Summary; References; Chapter 5 Considerations Before Replacing Hand Drilling with Mechanization or Automation; 5.1 Introduction; 5.2 Before the Decision to Automate; 5.2.1 Feasibility Analysis; 5.2.1.1 Access; 5.2.1.2 Flooring; 5.2.1.3 Tooling Integration; 5.2.1.4 Factory Infrastructure; 5.2.1.5 Current Operations; 5.2.1.6 Environment; 5.2.1.7 Labor; 5.2.1.8 Risk Assessment.…”
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Power system dynamics by Guruprasada, Rau V.

Table of Contents: “…18.1 Concept of Lyapunov Stability, Asymptotic Stability and Instability -- 18.2 Lyapunov's Asymptotic Stability Theorem -- References -- Chapter 19 Methods of Construction of Lyapunov Functions -- 19.1 Sylvester's Criteria for Definiteness and Semi-Definiteness -- 19.2 Construction of Lyapunov Functions for a Power System -- References -- Chapter 20 Generation of Lyapunov Functions -- 20.1 Energy Metric Algorithm for Generation of Lyapunov Functions -- 20.2 Application to Power System -- 20.3 Evaluation of Region of Asymptotic Stability -- 20.4 Application of Lyapunov Method to Linear System -- References -- Chapter 21 Exercise Problems -- 21.1 Problems with Solutions -- 21.2 Unsolved Problems -- References.…”
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Advanced battery management technologies for electric vehicles by Xiong, Rui, Shen, Weixiang

Table of Contents: “…2.7.2 Case One -- OFFPIM Application2.7.3 Case Two -- ONPIM Application; 2.7.4 Discussions; 2.8 Model Uncertainties; 2.8.1 Battery Aging; 2.8.2 Battery Type; 2.8.3 Battery Temperature; 2.9 Other Battery Models; 2.10 Summary; References; Chapter 3 Battery State of Charge and State of Energy Estimation; 3.1 Background; 3.2 Classification; 3.2.1 Look-Up-Table-Based Method; 3.2.2 Ampere-Hour Integral Method; 3.2.3 Data-Driven Estimation Methods; 3.2.4 Model-Based Estimation Methods; 3.3 Model-Based SOC Estimation Method with Constant Model Parameters; 3.3.1 Discrete-Time Realization Algorithm…”
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Principles of GNSS, inertial, and multisensor integrated navigation systems by Groves, Paul D. (Paul David)

Table of Contents: “…Kalman Filter Algorithm -- 3.2.3. System Model -- 3.2.4. Measurement Model -- 3.2.5. …”
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Aerospace Sensors. by Nebylov, Alexander

Table of Contents: “…Principles and examples of sensor integration -- 9.1 Sensor systems -- 9.1.1 The sensor system concept -- 9.1.2 Joint processing of readings from identical sensors -- 9.1.3 Joint processing of readings from cognate sensors with different measurement ranges -- 9.1.4 Joint processing of diverse sensors readings -- 9.1.5 Linear and nonlinear sensor integration algorithms -- 9.2 Fundamentals of integrated measuring system synthesis -- 9.2.1 Synthesis problem statement -- 9.2.2 Classes of dynamic system realization -- 9.2.3 Measurement accuracy indices -- 9.2.4 Excitation properties -- 9.2.5 Objective functions for robust system optimisation -- 9.2.6 Methods of dynamic system accuracy index analysis under excitation with given numerical characteristics of derivatives -- 9.2.6.1 Estimation of error variance -- 9.2.6.2 Example of error variance analysis -- 9.2.6.3 Use of equivalent harmonic excitation -- 9.2.6.4 Estimation of error maximal value -- 9.2.7 System optimization under maximum accuracy criteria -- 9.2.8 Procedures for the dimensional reduction of a measuring system -- 9.2.8.1 Determination of an optimal set of sensors -- 9.2.8.2 Analysis of the advantages of invariant system construction -- 9.2.8.3 Advantages of the zeroing of several system parameters -- 9.2.9 Realization and simulation of integration algorithms -- 9.3 Examples of two-component integrated navigation systems -- 9.3.1 Noninvariant robust integrated speed meter -- 9.3.2 Integrated radio-inertial measurement -- 9.3.3 Airborne gravimeter integration -- 9.3.4 The orbital verticant -- References…”
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Multi-dimensional Imaging. by Javidi, Bahram

Table of Contents: “…About the Editors xv -- List of Contributors xvii -- Preface xxi -- Acknowledgments xxiii -- Part I MULTI-DIMENSIONAL DIGITAL HOLOGRAPHIC TECHNIQUES -- 1 Parallel Phase-Shifting Digital Holography 3 / Yasuhiro Awatsuji -- 1.1 Chapter Overview 3 -- 1.2 Introduction 3 -- 1.3 Digital Holography and Phase-Shifting Digital Holography 4 -- 1.4 Parallel Phase-Shifting Digital Holography 6 -- 1.5 Experimental Demonstration of Parallel Phase-Shifting Digital Holography 8 -- 1.6 High-Speed Parallel Phase-Shifting Digital Holography System 12 -- 1.7 Single-Shot Femtosecond-Pulsed Parallel Phase-Shifting Digital Holography System 14 -- 1.8 Portable Parallel Phase-Shifting Digital Holography System 17 -- 1.9 Functional Extension of Parallel Phase-Shifting Digital Holography 17 -- 1.10 Prospects and Conclusion 20 -- 2 Imaging and Display of Human Size Scenes by Long Wavelength Digital Holography 25 / Massimiliano Locatelli, Eugenio Pugliese, Melania Paturzo, Vittorio Bianco, Andrea Finizio, Anna Pelagotti, Pasquale Poggi, Lisa Miccio, Riccardo Meucci and Pietro Ferraro -- 2.1 Introduction 25 -- 2.2 Digital Holography Principles 25 -- 2.3 Infrared Digital Holography 33 -- 2.4 Latest Achievements in IRDH 34 -- 2.5 Conclusion 46 -- 3 Digital Hologram Processing in On-Axis Holography 51 / Corinne Fournier, Lo<U+0082>Sic Denis, Mozhdeh Seifi and Thierry Fournel -- 3.1 Introduction 51 -- 3.2 Model of Hologram Image Formation 52 -- 3.3 DH Reconstruction Based on Back Propagation 56 -- 3.4 Hologram Reconstruction Formulated as an Inverse Problem 57 -- 3.5 Estimation of Accuracy 64 -- 3.6 Fast Processing Algorithms 65 -- 3.7 Conclusion 69 -- 4 Multi-dimensional Imaging by Compressive Digital Holography 75 / Yair Rivenson, Adrian Stern, Joseph Rosen, and Bahram Javidi -- 4.1 Introduction 75 -- 4.2 Compressive Sensing Preliminaries 76 -- 4.3 Conditions for Accurate Reconstruction of Compressive Digital Holographic Sensing 79 -- 4.4 Applications of Compressive Digital Holographic Sensing 84.…”
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Official Google Cloud Certified Professional Data Engineer study guide by Sullivan, Dan, 1962-

Table of Contents: “…Row Key Access 13 -- Unstructured Data 15 -- Google's Storage Decision Tree 16 -- Schema Design Considerations 16 -- Relational Database Design 17 -- NoSQL Database Design 20 -- Exam Essentials 23 -- Review Questions 24 -- Chapter 2 Building and Operationalizing Storage Systems 29 -- Cloud SQL 30 -- Configuring Cloud SQL 31 -- Improving Read Performance with Read Replicas 33 -- Importing and Exporting Data 33 -- Cloud Spanner 34 -- Configuring Cloud Spanner 34 -- Replication in Cloud Spanner 35 -- Database Design Considerations 36 -- Importing and Exporting Data 36 -- Cloud Bigtable 37 -- Configuring Bigtable 37 -- Database Design Considerations 38 -- Importing and Exporting 39 -- Cloud Firestore 39 -- Cloud Firestore Data Model 40 -- Indexing and Querying 41 -- Importing and Exporting 42 -- BigQuery 42 -- BigQuery Datasets 43 -- Loading and Exporting Data 44 -- Clustering, Partitioning, and Sharding Tables 45 -- Streaming Inserts 46 -- Monitoring and Logging in BigQuery 46 -- BigQuery Cost Considerations 47 -- Tips for Optimizing BigQuery 47 -- Cloud Memorystore 48 -- Cloud Storage 50 -- Organizing Objects in a Namespace 50 -- Storage Tiers 51 -- Cloud Storage Use Cases 52 -- Data Retention and Lifecycle Management 52 -- Unmanaged Databases 53 -- Exam Essentials 54 -- Review Questions 56 -- Chapter 3 Designing Data Pipelines 61 -- Overview of Data Pipelines 62 -- Data Pipeline Stages 63 -- Types of Data Pipelines 66 -- GCP Pipeline Components 73 -- Cloud Pub/Sub 74 -- Cloud Dataflow 76 -- Cloud Dataproc 79 -- Cloud Composer 82 -- Migrating Hadoop and Spark to GCP 82 -- Exam Essentials 83 -- Review Questions 86 -- Chapter 4 Designing a Data Processing Solution 89 -- Designing Infrastructure 90 -- Choosing Infrastructure 90 -- Availability, Reliability, and Scalability of Infrastructure 93 -- Hybrid Cloud and Edge Computing 96 -- Designing for Distributed Processing 98 -- Distributed Processing: Messaging 98 -- Distributed Processing: Services 101 -- Migrating a Data Warehouse 102 -- Assessing the Current State of a Data Warehouse 102 -- Designing the Future State of a Data Warehouse 103 -- Migrating Data, Jobs, and Access Controls 104 -- Validating the Data Warehouse 105 -- Exam Essentials 105 -- Review Questions 107 -- Chapter 5 Building and Operationalizing Processing Infrastructure 111 -- Provisioning and Adjusting Processing Resources 112 -- Provisioning and Adjusting Compute Engine 113 -- Provisioning and Adjusting Kubernetes Engine 118 -- Provisioning and Adjusting Cloud Bigtable 124 -- Provisioning and Adjusting Cloud Dataproc 127 -- Configuring Managed Serverless Processing Services 129 -- Monitoring Processing Resources 130 -- Stackdriver Monitoring 130 -- Stackdriver Logging 130 -- Stackdriver Trace 131 -- Exam Essentials 132 -- Review Questions 134 -- Chapter 6 Designing for Security and Compliance 139 -- Identity and Access Management with Cloud IAM 140 -- Predefined Roles 141 -- Custom Roles 143 -- Using Roles with Service Accounts 145 -- Access Control with Policies 146 -- Using IAM with Storage and Processing Services 148 -- Cloud Storage and IAM 148 -- Cloud Bigtable and IAM 149 -- BigQuery and IAM 149 -- Cloud Dataflow and IAM 150 -- Data Security 151 -- Encryption 151 -- Key Management 153 -- Ensuring Privacy with the Data Loss Prevention API 154 -- Detecting Sensitive Data 154 -- Running Data Loss Prevention Jobs 155 -- Inspection Best Practices 156 -- Legal Compliance 156 -- Health Insurance Portability and Accountability Act (HIPAA) 156 -- Children's Online Privacy Protection Act 157 -- FedRAMP 158 -- General Data Protection Regulation 158 -- Exam Essentials 158 -- Review Questions 161 -- Chapter 7 Designing Databases for Reliability, Scalability, and Availability 165 -- Designing Cloud Bigtable Databases for Scalability and Reliability 166 -- Data Modeling with Cloud Bigtable 166 -- Designing Row-keys 168 -- Designing for Time Series 170 -- Use Replication for Availability and Scalability 171 -- Designing Cloud Spanner Databases for Scalability and Reliability 172 -- Relational Database Features 173 -- Interleaved Tables 174 -- Primary Keys and Hotspots 174 -- Database Splits 175 -- Secondary Indexes 176 -- Query Best Practices 177 -- Designing BigQuery Databases for Data Warehousing 179 -- Schema Design for Data Warehousing 179 -- Clustered and Partitioned Tables 181 -- Querying Data in BigQuery 182 -- External Data Access 183 -- BigQuery ML 185 -- Exam Essentials 185 -- Review Questions 188 -- Chapter 8 Understanding Data Operations for Flexibility and Portability 191 -- Cataloging and Discovery with Data Catalog 192 -- Searching in Data Catalog 193 -- Tagging in Data Catalog 194 -- Data Preprocessing with Dataprep 195 -- Cleansing Data 196 -- Discovering Data 196 -- Enriching Data 197 -- Importing and Exporting Data 197 -- Structuring and Validating Data 198 -- Visualizing with Data Studio 198 -- Connecting to Data Sources 198 -- Visualizing Data 200 -- Sharing Data 200 -- Exploring Data with Cloud Datalab 200 -- Jupyter Notebooks 201 -- Managing Cloud Datalab Instances 201 -- Adding Libraries to Cloud Datalab Instances 202 -- Orchestrating Workflows with Cloud Composer 202 -- Airflow Environments 203 -- Creating DAGs 203 -- Airflow Logs 204 -- Exam Essentials 204 -- Review Questions 206 -- Chapter 9 Deploying Machine Learning Pipelines 209 -- Structure of ML Pipelines 210 -- Data Ingestion 211 -- Data Preparation 212 -- Data Segregation 215 -- Model Training 217 -- Model Evaluation 218 -- Model Deployment 220 -- Model Monitoring 221 -- GCP Options for Deploying Machine Learning Pipeline 221 -- Cloud AutoML 221 -- BigQuery ML 223 -- Kubeflow 223 -- Spark Machine Learning 224 -- Exam Essentials 225 -- Review Questions 227 -- Chapter 10 Choosing Training and Serving Infrastructure 231 -- Hardware Accelerators 232 -- Graphics Processing Units 232 -- Tensor Processing Units 233 -- Choosing Between CPUs, GPUs, and TPUs 233 -- Distributed and Single Machine Infrastructure 234 -- Single Machine Model Training 234 -- Distributed Model Training 235 -- Serving Models 236 -- Edge Computing with GCP 237 -- Edge Computing Overview 237 -- Edge Computing Components and Processes 239 -- Edge TPU 240 -- Cloud IoT 240 -- Exam Essentials 241 -- Review Questions 244 -- Chapter 11 Measuring, Monitoring, and Troubleshooting Machine Learning Models 247 -- Three Types of Machine Learning Algorithms 248 -- Supervised Learning 248 -- Unsupervised Learning 253 -- Anomaly Detection 254 -- Reinforcement Learning 254 -- Deep Learning 255 -- Engineering Machine Learning Models 257 -- Model Training and Evaluation 257 -- Operationalizing ML Models 262 -- Common Sources of Error in Machine Learning Models 263 -- Data Quality 264 -- Unbalanced Training Sets 264 -- Types of Bias 264 -- Exam Essentials 265 -- Review Questions 267 -- Chapter 12 Leveraging Prebuilt Models as a Service 269 -- Sight 270 -- Vision AI 270 -- Video AI 272 -- Conversation 274 -- Dialogflow 274 -- Cloud Text-to-Speech API 275 -- Cloud Speech-to-Text API 275 -- Language 276 -- Translation 276 -- Natural Language 277 -- Structured Data 278 -- Recommendations AI API 278 -- Cloud Inference API 280 -- Exam Essentials 280 -- Review Questions 282 -- Appendix Answers to Review Questions 285 -- Chapter 1: Selecting Appropriate Storage Technologies 286 -- Chapter 2: Building and Operationalizing Storage Systems 288 -- Chapter 3: Designing Data Pipelines 290 -- Chapter 4: Designing a Data Processing Solution 291 -- Chapter 5: Building and Operationalizing Processing Infrastructure 293 -- Chapter 6: Designing for Security and Compliance 295 -- Chapter 7: Designing Databases for Reliability, Scalability, and Availability 296 -- Chapter 8: Understanding Data Operations for Flexibility and Portability 298 -- Chapter 9: Deploying Machine Learning Pipelines 299 -- Chapter 10: Choosing Training and Serving Infrastructure 301 -- Chapter 11: Measuring, Monitoring, and Troubleshooting Machine Learning Models 303 -- Chapter 12: Leveraging Prebuilt Models as a Service 304 -- Index 307.…”
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Nano-Biomedical Engineering 2009 : Proceedings of the Tohoku University Global Centre of Excellence Programme Global Nano-Biomedical Engineering Education and Research Network Cent...

Table of Contents: “…Pulse diagnosis machine and autogenic training / Tomoyuki Yambe. Detection algorithm of fatal arrhythmias for implantable cardioverter defibrillators using joint probability / Makoto Yoshizawa [and others]. …”
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Lippincott's primary care orthopaedics

Table of Contents: “…Approach to the Knee: Management Algorithm / Jess H. Lonner -- 15. Chondromalacia Patella: Anterior Knee Pain in the Young Patient / Eric B. …”
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Every planar map is four colorable by Appel, Kenneth I., 1932-2013, Haken, Wolfgang

Table of Contents: “…(X) The main algorithm -- (y) An upper bound for the time demand, polynomial in N -- (z) Possible improvements -- Supplement to Part I -- Lemmas on T -dischargings, stated S-2 -- proofs S-3 -- Lemma (I) S-6 -- Table l S-7 -- Proof of Lemma (I), continued S-12 -- Proof of Lemma (S+) S-14 -- Proof of the qTS(V5)-Lemma Introduction S-15 -- Cases (So (B = 0,1 S-18 -- Case (So (B = 2 S-19 -- Case (So (B = 3 S-20 -- Case (So (B = 4 S-31 -- Case (So (B = 5 S-38 -- Proof of the L-Lemma S-44 -- Tables of 3- ..., 7-digit arrangements S-45 -- Proof of the qn(V1)-Lemma Case (Sn (B = 0 S-47 -- Case (Sn (B = 1 S-57 -- Case (Sn (B e"2 S-65 -- Lemmas on L- and T -dischargings stated S-66 -- Table, L2 S-68 -- Proofs S-72 -- Proof of qTL(Vk)-Lemma, k = 8, ..., 11 S-79 -- Proof of qTL(V8)-LemmaCase W e"6 S-79 -- Case W = 5 S-83 -- Case W = 4 S-93 -- Case W = 3 S-105 -- Case W = 0 S-115 -- Proof of the qTL(V9)-Lemma Case W e"6 S-121 -- Case W = 5 S-127 -- Case W = 4 S-142 -- Case W = 3 S-160 -- Case W = 0 S-167 -- Proof of the qTL(V10)-Lemma S-170 -- Case 5,L, T2 S-172 -- Case 5,L, ., L,5 S-173 -- Case (Sp (B e"8 S-174 -- Case v = 7 S-175 -- Case v = 6 or 5 S-177 -- Proof of the qTL(V11)-Lemma S-195 -- Proof of the S-Lemma S-197 -- Supplement to Part II -- ((Sa (B) The immersion reducibility of the configurations of U S-198 -- ((Sb (B) The reducers S-202 -- ((Sd (B) The n-decreased extensions S-218 -- ((Se (B) n- and m-values and major vertices of the configurations of U S-250 -- ((Sf (B)List of configurations in U-U' S-251 -- Corresponding Class Check Lists -- (a), (b) C-1 -- I1-1 ..., 15-35 C-1 -- C-23 -- (1a) ..., (1l) C-32 -- (2a) ..., (2fg) C-37 -- (3a) ..., (3cb) C-88 -- (4a) ..., (4g) C-125 -- CTS#04 ..., CTS#33 C-133 -- (5a) ..., (5s) C-139 -- (6a) ..., (7h) C-146 -- (8a) ..., (8c) C-152 -- (8d) ..., (8x) C-153 -- (9a) ..., (10v) C-165 -- (11a) ..., (11h) C-177 -- (12a) ..., (12g) C-179.…”
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Mobile phones : technology, networks, and user issues

Table of Contents: “…Seamless Sensor Fusion -- 4.1. Particle Filter Algorithm -- 4.2. Motion Model -- 4.3. Measurement Model -- 4.4. …”
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High Accuracy Computing Methods : Fluid Flows and Wave Phenomena by Sengupta, Tapan

Table of Contents: “…Parallel and cluster computing -- 1.3.2. Algorithmic issues of HPC -- 1.4.Computational Fluid Mechanics -- 1.5. …”
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Binary decision diagrams and extensions for system reliability analysis by Xing, Liudong

Table of Contents: “…4.6.1 Prime Implicants Based Method -- 4.6.2 BDD Based Method -- 4.7 Disjoint Failures -- 4.8 Dependent Failures -- 4.8.1 Common-Cause Failures (CCFs) -- 4.8.2 Functional Dependent Failures -- 5 Phased-Mission Systems -- 5.1 System Description -- 5.2 Rules of Phase Algebra -- 5.3 BDD-Based Method for PMS Analysis -- 5.3.1 Input Variable Ordering -- 5.3.2 Single-Phase BDD Generation -- 5.3.3 PMS BDD Generation -- 5.3.4 PMS BDD Evaluation -- 5.4 Mission Performance Analysis -- 6 Multi-State Systems -- 6.1 Assumptions -- 6.2 An Illustrative Example -- 6.3 MSS Representation -- 6.3.1 MSS Representation Using MFT -- 6.3.2 MSS Representation Using MRBD -- 6.3.3 Equivalency of MRBD and MFT Representations -- 6.4 Multi-State BDD (MBDD) -- 6.4.1 Step 1 -- State Variable Encoding -- 6.4.2 Step 2 -- Generating MBDD from MFT -- 6.4.3 Step 3 -- MBDD Evaluation -- 6.4.4 Example Illustration -- 6.5 Logarithmically-Encoded BDD (LBDD) -- 6.5.1 Step 1 -- Variable Encoding -- 6.5.2 Step 2 -- Generating LBDD from MFT -- 6.5.3 Step 3 -- LBDD Evaluation -- 6.5.4 Example Illustration -- 6.6 Multi-State Multi-Valued Decision Diagrams (MMDD) -- 6.6.1 Step 1 -- Variable Encoding -- 6.6.2 Step 2 -- Generating MMDD from MFT -- 6.6.3 Step 3 -- MMDD Evaluation -- 6.6.4 Example Illustration -- 6.7 Performance Evaluation and Benchmarks -- 6.7.1 Example Analyses -- 6.7.2 Benchmark Studies -- 6.7.3 Performance Comparison and Discussions -- 6.7.3.1 Comparing Model Size -- 6.7.3.2 Comparing Runtime Complexity of Model Construction -- 6.7.3.3 Comparing Runtime Complexity of Model Evaluation -- 6.8 Summary -- 7 Fault Tolerant Systems and Coverage Models -- 7.1 Basic Types -- 7.2 Imperfect Coverage Model -- 7.3 Applications to Binary-State Systems -- 7.3.1 BDD Expansion Method -- 7.3.2 Simple and Efficient Algorithm -- 7.4 Applications to Multi-State Systems.…”
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Mastering Active Directory by Francis, Dishan

Table of Contents: “…-- Active Directory Certificate Service components -- The certification authority -- Certificate Enrollment Web Service -- Certificate Enrollment Policy Web Service -- Certification Authority Web Enrollment -- Network Device Enrollment Service -- Online Responder -- The types of CA -- Planning PKI -- Internal or public CAs -- Identifying the object types -- Cryptographic provider -- The cryptography key length -- Hash algorithms -- The certificate validity period -- The CA hierarchy -- High availability -- Deciding certificate templates -- The CA boundary -- PKI deployment models -- The single-tier model -- The two-tier model -- Three-tier models -- Setting up PKI -- Setting up a stand-alone root CA -- DSConfigDN -- CDP locations -- AIA locations -- CA time limits -- CRL time limits -- The new CRL -- Publishing the root CA data into the Active Directory -- Setting up the issuing CA.…”
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The Johns Hopkins guide to digital media

Table of Contents: “…Algorithm / Bethany Nowviskie -- Alternate reality gaming / Nicole Labitzke -- Analog versus digital / Jake Buckley -- Animated poetry / Philippe Bootz -- Animation/kineticism / Brian Kim Stefans -- Archive / Katherine Harris -- Artificial intelligence / David Elson -- Artificial life / Simon Penny -- Augmented reality / Jay David Bolter -- Authoring systems / Judy Malloy -- Avatars / Bjarke Liboriussen -- Biopoetry / Eduardo Kac -- Blogs / Ruth Page -- Book to e-text / Kirstyn Leuner -- Cave / John Cayley -- Cell phone novel / Larissa Hjorth -- Characteristics of digital media / David Golumbia -- Chatterbots / Ragnhild Tronstad -- Cheats / Julian Kücklich -- Code / Mark C. …”

Mechanical and Electronics Engineering : proceedings of the International Conference on ICMEE 2009, Chennai, India, 24-26 July 2009

Table of Contents: “…Prakasam and Madheswaran Muthusamy -- Rapid prototyping substitute material preparation and applications in casting process / Changming Zhang and Hui Zhang -- A novel fast motion estimation method based on clonal particle swarm optimization / Ranganadham D, Pavankumar Gorpuni and Ganapati Panda -- Two level encryption -- a new algorithm for information security / Subhashis Maitra -- Physical modeling of high rib and thin web aerocraft frame part with different cross-section during isotherm condition / Hui Zhang -- Semi-automatic manufacturing feature recognition for feature interaction problem in process planning / Deepali Tatkar and Venkatesh Kamat -- Multi-resolution segmentation of retinal vessels using optimal thresholding method / M.C. …”
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Sound waves : propagation, frequencies, and effects

Table of Contents: “…CASE STUDIES -- 6. GENETIC ALGORITHM -- 7. RESULTS AND DISCUSSION -- 7.1. Results -- 7.1.1. …”
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Pediatric evidence : the practice-changing studies

Table of Contents: “…Clinical Prediction Algorithm for Septic Arthritis -- 56. Oral versus Intravenous Therapy for Urinary Tract Infections -- 57. …”
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