Tabla de Contenidos: “…Modifying the getOrAddCustodian() function -- Improving the ingestDirectory() function -- A closer look at the formatTimestamp() function -- Converting the writeOutput() function -- Simplifying the writeCSV() function -- Condensing the writeHTML() function -- Running our new and improved script -- Challenge -- Summary -- Chapter 6: Extracting Artifacts from Binary Files -- UserAssist -- Understanding the ROT-13 substitution cipher - rot13.py -- Evaluating code with timeit -- Working with the Registry module -- Introducing the Struct module -- Creating spreadsheets with the xlsxwriter module -- Adding data to a spreadsheet -- Building a table -- Creating charts with Python -- The UserAssist framework -- Developing our UserAssist logic processor - userassist.py -- Evaluating the main() function -- Defining the createDictionary() function -- Extracting data with the parseValues() function -- Processing strings with the getName() function -- Writing Excel spreadsheets - xlsx_writer.py -- Controlling output with the excelWriter() function -- Summarizing data with the dashboardWriter() function -- Writing artifacts in the userassistWriter() function -- Defining the fileTime() function -- Processing integers with the sortByCount() function -- Processing DateTime objects with the sortByDate() function -- Writing generic spreadsheets - csv_writer.py -- Understanding the csvWriter() function -- Running the UserAssist framework -- Additional challenges -- Summary -- Chapter 7: Fuzzy Hashing -- Background on hashing -- Hashing files in Python -- Deep dive into rolling hashes -- Implementing rolling hashes - hashing_example.py -- Limitations of rolling hashes -- Exploring fuzzy hashing - fuzzy_hasher.py -- Starting with the main function -- Working with files in the fileController() function -- Working with directories in the directoryController() function…”

Tabla de Contenidos: “…Generating variations on image data -- Sampling data in different ways -- Accessing Data in Structured Flat-File Form -- Reading from a text file -- Reading CSV delimited format -- Reading Excel and other Microsoft Office files -- Sending Data in Unstructured File Form -- Managing Data from Relational Databases -- Interacting with Data from NoSQL Databases -- Accessing Data from the Web -- Chapter 7 Conditioning Your Data -- Juggling between NumPy and pandas -- Knowing when to use NumPy -- Knowing when to use pandas -- Validating Your Data -- Figuring out what's in your data -- Removing duplicates -- Creating a data map and data plan -- Manipulating Categorical Variables -- Creating categorical variables -- Renaming levels -- Combining levels -- Dealing with Dates in Your Data -- Formatting date and time values -- Using the right time transformation -- Dealing with Missing Data -- Finding the missing data -- Encoding missingness -- Imputing missing data -- Slicing and Dicing: Filtering and Selecting Data -- Slicing rows -- Slicing columns -- Dicing -- Concatenating and Transforming -- Adding new cases and variables -- Removing data -- Sorting and shuffling -- Aggregating Data at Any Level -- Chapter 8 Shaping Data -- Working with HTML Pages -- Parsing XML and HTML -- Using XPath for data extraction -- Working with Raw Text -- Dealing with Unicode -- Stemming and removing stop words -- Introducing regular expressions -- Using the Bag of Words Model and Beyond -- Understanding the bag of words model -- Working with n-grams -- Implementing TF-IDF transformations -- Working with Graph Data -- Understanding the adjacency matrix -- Using NetworkX basics -- Chapter 9 Putting What You Know in Action -- Contextualizing Problems and Data -- Evaluating a data science problem -- Researching solutions -- Formulating a hypothesis -- Preparing your data…”

Tabla de Contenidos: “…7.6.1 QS, Biofilm Growth, and MIC -- 7.6.2 Bioinformatics Analysis -- 7.7 Adhesion-Induced Emergent Properties in Biofilm -- 7.8 Methods to Inhibit Quorum Sensing -- 7.9 Conclusion -- Acknowledgments -- References -- Chapter 8 Data-Driven 2D Material Discovery Using Biofilm Data and Information Discovery System (Biofilm-DIDS) -- 8.1 Introduction -- 8.1.1 Microbial Community, Biofilm, and Material-Biofilm Interaction -- 8.1.2 Complex System Design: SDLC and Agile Methodology Meets Big Data -- 8.1.3 Big Data Mining and Knowledge Discovery -- 8.2 Interface between the Living and the Non-Living: a System Thinking Approach -- 8.2.1 System Understanding of Biointerface -- 8.2.2 Big Data in Biointerfaces -- 8.3 Biofilm-DIDS Overview -- 8.4 Using Biofilm-DIDS to Extract Biocorrosion Gene of Interest from the Literature and Material Dimension Prediction -- 8.4.1 Expert Informed Relevant Dataset Extraction from User Free Text Question -- 8.4.2 Downstream Analysis for Material Dimension Prediction -- 8.5 Conclusions -- Acknowledgments -- References -- Chapter 9 Machine Learning-Guided Optical and Raman Spectroscopy Characterization of 2D Materials -- 9.1 Introduction -- 9.2 Established Surface Characterization Techniques -- 9.3 ML-Guided Optical Detection of 2D Materials -- 9.4 ML-Guided Raman Spectroscopy Detection of 2D Materials -- 9.5 Common Challenges to ML in Raman Spectroscopy -- 9.6 Future Prospects -- 9.7 Summary -- References -- Chapter 10 Atomistic Experiments for Discovery of 2D Coatings: Biological Applications -- 10.1 Introduction -- 10.2 Molecular Dynamics (Algorithms and Methods) -- 10.2.1 Empirical Forcefields -- 10.2.2 Periodic Boundary Conditions -- 10.2.3 Binding Energy -- 10.2.4 Free Energy -- 10.2.5 Umbrella Sampling -- 10.2.6 Coarse-Grained Modeling -- 10.3 Employment of MD on Functional 2D Materials…”

Tabla de Contenidos: “…Building a gRPC client -- A command-line tool to consume the service -- Parsing arguments in CLIs -- Maintaining good line of sight by extracting case bodies -- Installing tools from the Go source code -- Rate limiting with service middleware -- Middleware in Go kit -- Manually testing the rate limiter -- Graceful rate limiting -- Summary -- Chapter 11: Deploying Go Applications Using Docker -- Using Docker locally -- Installing Docker tools -- Dockerfile -- Building Go binaries for different architectures -- Building a Docker image -- Running a Docker image locally -- Inspecting Docker processes -- Stopping a Docker instance -- Deploying Docker images -- Deploying to Docker Hub -- Deploying to Digital Ocean -- Creating a droplet -- Accessing the droplet's console -- Pulling Docker images -- Running Docker images in the cloud -- Accessing Docker images in the cloud -- Summary -- Appendix: Good Practices for a Stable Go Environment -- Installing Go -- Configuring Go -- Getting GOPATH right -- Go tools -- Cleaning up, building, and running tests on save -- Integrated developer environments -- Sublime Text 3 -- Visual Studio Code -- Summary -- Index…”

Tabla de Contenidos: “…-- XML Resources -- Oracle and XML -- Storing XML Data -- Storing XML as a CLOB -- Inspecting the XML Document -- XPath -- The extract( ) member function -- The extractValue( ) member function -- The existsNode( ) member function -- Moving data to relational tables -- Storing XML as a Set of Objects -- Registering your schema -- Assigning the schema to a column -- Inserting data -- XMLType validity functions -- Updating document content -- Generating XML Documents -- XMLElement( ) -- XMLAgg( ) -- XMLForest( ) -- Putting It All Together -- Summary -- Regular Expressions -- Elementary Regular Expression Syntax -- Matching a Single Character -- Matching Any of a Set of Characters -- Matching Repeating Sequences -- Defining Alternate Possibilities -- Subexpressions -- Anchoring an Expression…”

Tabla de Contenidos: “…-- Stakeholders -- Ethical, legal, and regulatory requirements -- Managing and executing a penetration test -- Using the cyber kill chain -- Standards in penetration testing -- Report writing -- Summary -- Chapter 2: Programming Principles in PowerShell -- Basic concepts of PowerShell and pipelines in PowerShell -- JSON in PowerShell -- Retrieving JSON data from web APIs -- Parsing JSON data -- JSON manipulation for payloads -- Interacting with JSON from files -- Web scraping and data extraction -- XML in PowerShell -- Reading and parsing XML files -- Extracting information from XML nodes -- Modifying XML data -- Crafting XML payloads -- XML injection testing -- COM, WMI, and .NET in PowerShell -- Using WMI for system information gathering -- Querying WMI for network information -- Interacting with COM objects -- Using .NET for cryptographic operations -- Using .NET for network operations -- Analyzing .NET assemblies for vulnerabilities -- Summary -- Part 2: Identification and Exploitation -- Chapter 3: Network Services and DNS -- Network services -- TCP/IP network services -- The IP addresses -- The TCP/UDP port numbers -- The OSI stack -- DNS and types of DNS queries -- DNS overview -- Types of DNS queries -- DNS and PowerShell -- Summary -- Chapter 4: Network Enumeration and Port Scanning -- Network enumeration using PowerShell -- TCP port scanning using PowerShell -- Single port scanning with Test-NetConnection -- Multiple port scanning with Test-NetConnection -- Enumerating open ports with Test-NetConnection -- Single port scanning with .NET -- Multiple port scanning with .NET…”

“…The EM Imaging through Synthetic Aperture Radar (SAR) technique is used for data extraction. The second section presents a few smart tag detection techniques for existing chipless RFID systems. …”

“…Text processing and pattern matching simplified About This Book Master the fastest and most elegant big data munging language Implement text processing and pattern matching using the advanced features of AWK and GAWK Implement debugging and inter-process communication using GAWK Who This Book Is For This book is for developers or analysts who are inclined to learn how to do text processing and data extraction in a Unix-like environment. Basic understanding of Linux operating system and shell scripting will help you to get the most out of the book. …”

“…Chapter 4 focuses on wavelets and convolutional-neural filters for feature extraction and entropy-based anomaly detection, and Chapter 5 deals with a number of metrics such as cross correlation ratios and the Hausdorff distance for variational analysis of the state of snow. …”

Tabla de Contenidos: “…Fire Prevention in Ventilating Systems -- Fire Dampers in Ductwork -- Pressurisation of Escape Routes -- Smoke Extraction, Ventilation and Control -- Portable Fire Extinguishers -- Carbon Monoxide Detectors -- Part Fourteen-Security Installations -- Physical Security -- Intruder Alarms -- Micro-Switch and Magnetic Reed -- Radio Sensor, Pressure Mat and Taut Wiring -- Acoustic, Vibration and Inertia Detectors -- Ultrasonic and Microwave Detectors -- Active Infra-Red Detector -- Passive Infra-Red Detector -- Lightning Protection Systems -- Surge Protection -- Part Fifteen-Accommodation for Building Services -- Underground Utilities -- Ducts for Engineering Services -- Notching and Holing Joists -- Floor and Skirting Ducts -- Medium and Large Vertical Ducts -- Medium and Large Horizontal Ducts -- Subways or Walkways -- Penetration of Fire Structure by Pipes -- Raised Access Floors -- Suspended and False Ceilings -- Flue Pipe Location -- Part Sixteen-Alternative and Renewable Energy -- Energy Production -- Alternative Energy -- Renewable Energy -- Anaerobic Digestion -- Biogas -- Wind Power -- Wind Power and Fuel Cells -- Water Power -- Geothermal Power -- Micro-Combined Heat and Power -- Solar Power -- Photovoltaic Systems -- Biomass or Biofuel -- Underground Coal Gasification -- Carbon Capture and Storage -- Hydraulic Fracturing -- Anaerobic Waste Processing -- Part Seventeen-Appendices -- Appendix 1 - Glossary of Common Abbreviations -- Appendix 2 - Abbreviations for Pipework -- Appendix 3 - Abbreviations for Pipework Components -- Appendix 4 - Abbreviations Used for Drainage Systems -- Appendix 5 - Abbreviations Used for Sanitation Systems -- Appendix 6 - Graphical Symbols for Pipework -- Appendix 7 - Identification of Pipework -- Appendix 8 - Graphical Symbols for Electrical Installation Work -- Appendix 9 - Metric Units…”

Tabla de Contenidos: “…10.3 Issues, Challenges and Problem Statement -- 10.3.1 Time and Memory Constraints -- 10.3.2 Class Imbalance -- 10.3.3 Concept Drift -- 10.4 Cybersecurity and IoT -- 10.5 Conclusion -- Chapter 11 A Study on Image Detection and Extraction to Estimate Distracted Drivers Using CNN and IoT -- 11.1 Introduction -- 11.2 Motivations -- 11.3 Literature Survey or Related Work -- 11.4 Existing System -- 11.5 Methodology and Objectives -- 11.5.1 Device Initialisation Module -- 11.5.2 Drowsiness Detection Module -- 11.5.3 Alert Module -- 11.6 Proposed System -- 11.7 Face Detection Using OpenCV -- 11.8 Search Strategy -- 11.9 Conclusion -- 11.10 Future Enhancement -- Chapter 12 Social Engineering: Cyberattacks, Countermeasures, and Conclusions -- 12.1 Introduction -- 12.2 Case Study on Social Engg Attack-IBMReport [25] -- 12.2.1 The Cost of Average Social Engineering-Related Breach -- 12.3 Methodology and Detection -- 12.3.1 Social Engineering Toolkit for SMS Spoofing -- 12.3.2 SMS Spam Message Detection with Term Frequency-Inverse Document Frequency (TF-IDF) and Random Forest Algorithm -- 12.4 Results -- 12.5 Conclusion -- 12.6 Acknowledgment -- Index…”

Tabla de Contenidos: “…Advanced Queuing and Streams; 1.7.5. Extraction, Transformation, Loading; 1.7.6. Availability; 1.8. …”

Tabla de Contenidos: “…Ensemble synthetic data generation -- Diversity regularization -- Incorporating external knowledge -- Progressive training -- Procedural content generation with game engines -- Diversity issues in the synthetic data realm -- Balancing diversity and realism -- Privacy and confidentiality concerns -- Validation and evaluation challenges -- Summary -- Chapter 16: Photorealism in Computer Vision -- Synthetic data photorealism for computer vision -- Feature extraction -- Domain gap -- Robustness -- Benchmarking performance -- Photorealism approaches -- Physically Based Rendering (PBR) -- Neural style transfer -- Photorealism evaluation metrics -- Structural Similarity Index Measure (SSIM) -- Learned Perceptual Image Patch Similarity (LPIPS) -- Expert evaluation -- Challenges and limitations of photorealistic synthetic data -- Creating hyper-realistic scenes -- Resources versus photorealism trade-off -- Summary -- Chapter 17: Conclusion -- Real data and its problems -- Synthetic data as a solution -- Real-world case studies -- Challenges and limitations -- Future perspectives -- Summary -- Index -- Other Books You May Enjoy…”

Tabla de Contenidos: “…-- The Apriori algorithm - a practical example -- Evaluation metrics -- In summary -- Applications of UL -- Market segmentation -- Anomaly detection -- Feature extraction -- Summary -- Interpreting and Evaluating Machine Learning Models -- How do I know whether this model will be accurate? …”

Tabla de Contenidos: “…Higher Brain Centers for Intelligent Motor Control in Insects -- Introduction -- Learning and Memory in the Central Complex for Approaching Objects -- Experimental Evidence -- The Central Complex Model -- Intelligent Motor Control beyond the Current Model -- An Integrator for the Orientation in Gradients -- Motor Learning -- A Representation of Body Size in the Brain -- Termination of Inappropriate Behavior -- Conclusion -- References -- An Insect-Inspired, Decentralized Memory for Robot Navigation -- Introduction -- The Model -- Results -- Discussion -- References -- Models of Visually Guided Routes in Ants: Embodiment Simplifies Route Acquisition -- Introduction -- Background -- Overview of Our Approach -- Detailed Methods -- Results -- Summary -- References -- Intelligent Visual Systems -- Robust Object Tracking for Resource-Limited Hardware Systems -- Introduction -- Overview of Tracking System -- Dominant Color-Spatial Based Object Representation -- Dominant Color Mode Extraction -- Spatial Layout of the Dominant Color -- Similarity Measure for Matching -- Cross Bin-Ratio Based Color Similarity Measure -- Spatial Similarity Measure -- Swarm Intelligence Based Searching Method -- Annealed Particle Swarm Optimization -- Integral Image of Model Parameters -- Experimental Results -- Different Object Representations -- Different Similarity Measure -- Different Searching Methods -- Conclusion -- References -- Adaptive Rank Transform for Stereo Matching -- Introduction -- Adaptive Rank Transform -- The Motivation Behind Adaptive Rank Transform -- Adaptive Rank Window -- New Transform Rules -- Comparison between Adaptive and Original Rank Transform -- Obtaining the Match Window from Multiple Rank Windows -- Experiments -- Conclusion -- References -- Real Time Vision Based Multi-person Tracking for Mobile Robotics and Intelligent Vehicles -- Introduction…”

Tabla de Contenidos: “…Security and exits -- 5.1 Security in Content Manager overview -- 5.2 RACF logon exit implementation -- 5.2.1 Activating RACF exit -- 5.2.2 APF authorizing Content Manager load library -- 5.2.3 Using security managers other than RACF -- 5.2.4 Users not validated by the security exit -- 5.2.5 Importing user definitions from RACF -- 5.2.6 Specifying ACLs and privilege sets for imported users -- 5.2.7 Sample SQLs to extract information from Content Manager -- 5.2.8 Extract user list and information from Content Manager…”

Tabla de Contenidos: “…Structure and analysis of biominerals -- 1 On the transition temperature to calcite and cell lengths for various biogenic aragonite -- 2 TEM study of the radular teeth of the chiton Acanthopleura japonica -- 3 Experimental cremation of bone - crystallite size and lattice parameter evolution -- 4 Effect of carbonic anhydrase immobilized on eggshell membranes on calcium carbonate crystallization in vitro -- 5 Proteomic Analysis of Venomous Fang Matrix Proteins of Protobothrops flavoviridis (Habu) Snake -- 6 Characterization of goldfish scales by vibrational spectroscopic analyses -- 7 Relationship between Bone Morphology and Bone Quality in Female Femurs: Implication for Additive Risk of Alternative Forced Molting -- 8 Spectroscopic investigation of shell pigments from the family Neritidae (Mollusca: Gastropoda) -- 9 3D visualization of calcified and non-calcified molluscan tissues using computed tomography -- Part II Molecular and cellular regulation of biomineralization -- 10 Calcium Ion and Mineral Pathways in Biomineralization: a Perspective -- 11 Identification of barnacle shell proteins by transcriptome and proteomic approaches -- 12 The optical characteristics of cultured Akoya pearl are influenced by both donor and recipient oysters -- 13 Influence of B vitamins on proliferation and differentiation of osteoblastic bovine cell cultures; an in vitro study -- 14 Rice plant biomineralization: Electron microscopic study on plant opals and exploration of organic matrices involved in biosilica formation -- 15 DMP1 binds specifically to type I collagen and regulates mineral nucleation and growth -- 16 Exploration of genes associated with sponge silicon biomineralization in the whole genome sequence of the hexactinellid Euplectella curvistellata -- Part III Genome-based analysis of biomineralization -- 17 The origin and early evolution of SCPP genes and tissue mineralization in vertebrates -- Part IV Evolution in biomineralization -- 18 Immunolocalization of enamel matrix protein-like proteins in the tooth enameloid of actinopterygian bony fish -- 19 Geographical and seasonal variations of the shell microstructures in the bivalve Scapharca broughtonii -- Part V Biomineralization in medical and dental sciences -- 20 Enhancement of bone tissue repair by octacalcium phosphate crystallizing into hydroxyapatite in situ -- 21 The relationship between the structure and calcification of dentin and the role of melatonin -- 22 Fabrication of hydroxyapatite nanofibers with high aspect ratio vialow-temperature wet precipitation methods under acidic conditions -- 23 Physico-chemical characterisation of the processes involved in enamel remineralisation by CPP-ACP -- 24 Molecular Interactions of Peptide Encapsulated Calcium Phosphate Delivery Vehicle at Enamel Surfaces -- 25 Preparation of random and aligned polycaprolactone fiber as template for classical calcium oxalate through electrocrystallization -- Part VI Bio-inspired materials science and engineering -- 26 Dysprosium biomineralization by acidophilic fungus Penidiella sp. strain T9 and its application for metal recovery -- 27 Various shapes of gold nanoparticles synthesized by glycolipids extracted from Lactobacillus casei -- 28 Octacalcium phosphate overgrowth on b-tricalcium phosphate substrate in metastable calcium phosphate solution -- Part VII Biominerals for environmental and paleoenvironmental sciences -- 29 Coral-based approaches to paleoclimate studies, future ocean environment assessment, and disaster research -- 30 An elemental fractionation mechanism common to biogenic calcium carbonate -- 31 Biomineralization of metallic tellurium by bacteria isolated from deep marine sediment in Niigata Bay Japan -- 32 Calcium oxalate crystals in plant communities of the southeast of the Pampean Plain, Argentina -- 33 Iron and calcium biomineralizations in the Pampean coastal plains, Argentina: their role in the environmental reconstruction of the Holocene -- Part VIII Mollusk shell formation -- 34 Skeletal organic matrices in molluscs: origin, evolution, diagenesis -- 35 Functional Analysis on Shelk2 of Pacific Oyster -- 36 Mollusk shells: Does the nacro-prismatic “model” exist? …”

Tabla de Contenidos: “…Detecting eyes -- Afterthought -- Fun with eyes -- Positioning the sunglasses -- Detecting ears -- Detecting a mouth -- It's time for a moustache -- Detecting pupils -- Deconstructing the code -- Summary -- Chapter 5: Extracting Features from an Image -- Why do we care about keypoints? …”

Tabla de Contenidos: “…About the Editors vii -- Sivaramakrishnan Rajaraman and Sameer Antani Editorial on Special Issue "Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases" Reprinted from: Diagnostics 2022, 12, 2615, doi:10.3390/diagnostics12112615 1 -- Noemi Gozzi, Edoardo Giacomello, Martina Sollini, Margarita Kirienko, Angela Ammirabile, Pierluca Lanzi, Daniele Loiacono, et al. Image Embeddings Extracted from CNNs Outperform Other Transfer Learning Approaches in Classification of Chest Radiographs Reprinted from: Diagnostics 2022, 12, 2084, doi:10.3390/diagnostics12092084 9 -- Abdulaziz Fahad AlOthman, Abdul Rahaman Wahab Sait and Thamer Abdullah Alhussain Detecting Coronary Artery Disease from Computed Tomography Images Using a Deep Learning Technique Reprinted from: Diagnostics 2022, 12, 2073, doi:10.3390/diagnostics12092073 29 -- Guan-Hua Huang, Qi-Jia Fu, Ming-Zhang Gu, Nan-Han Lu, Kuo-Ying Liu and Tai-Been Chen Deep Transfer Learning for the Multilabel Classification of Chest X-ray Images Reprinted from: Diagnostics 2022, 12, 1457, doi:10.3390/diagnostics12061457 49 -- Sivaramakrishnan Rajaraman, Peng Guo, Zhiyun Xue and Sameer K. …”

Tabla de Contenidos: “…Indexing and Slicing; 5.2.2.2. S licing (S[i:j]) extracts contiguous sections of a sequence; 5.2.3. …”