“…Bergson, however, believes that scientific time is derived by abstraction, even in the sense of extraction, from a more fundamental time. The plurality of times envisaged by the theory of Relativity does not, for him, contradict the philosophical intuition of the existence of a single time. …”

“…With deep insights into everyday work practices of Indian and European contractors and manual labourers, the book establishes a bridge across the globe, between two poor regions as sites of extraction and industrial transformation, resulting from global migration and capital flows. …”

“…Global value production and transnational value practices that rely on exploitation and extraction have left us with toxic commons and a damaged planet. …”

Tabla de Contenidos: “…Motivation -- 3. Feature extraction and classification using CNN -- 3.1. Cognitive computing -- 3.1.1. …”

Tabla de Contenidos: “…Evolution of Domestic Extraction -- 2.5. The specialization of Spain’s agricultural production -- 2.6. …”

Tabla de Contenidos: “…3.4 Transformation to Spatial Representations3.5 Generation of Tree Representation; 3.6 Search and Problem Solving; 3.7 Logical Inference; 3.8 Production Systems; 3.9 Inference Using Frames; 3.10 Constraint Representation and Relaxation; 3.11 Summary; Keywords; Exercises; Chapter 4. Pattern Feature Extraction; 4.1 Detecting an Edge; 4.2 Detection of a Boundary Line; 4.3 Extracting a Region; 4.4 Texture Analysis; 4.5 Detection of Movement; 4.6 Representing a Boundary Line; 4.7 Representing a Region; 4.8 Representation of a Solid; 4.9 Interpretation of Line Drawings; Summary; Keywords…”

Tabla de Contenidos: “…; What's Next?; Chapter 4. Extracting the Model; Where We Were; The Basic Plan; The Refactoring; What's Next?…”

Tabla de Contenidos: “…. -- Using a different classifier builder -- See also -- Extracting named entities -- How to do it... -- How it works... -- There's more... -- Binary named entity extraction -- See also -- Extracting proper noun chunks -- How to do it... -- How it works... -- There's more... -- See also -- Extracting location chunks -- How to do it... -- How it works... -- There's more... -- See also -- Training a named entity chunker -- How to do it... -- How it works... -- There's more... -- See also -- Training a chunker with NLTK-Trainer -- How to do it... -- How it works... -- There's more... -- Saving a pickled chunker -- Training a named entity chunker -- Training on a custom corpus -- Training on parse trees -- Analyzing a chunker against a chunked corpus -- Analyzing a chunked corpus -- See also -- 6. …”

Tabla de Contenidos: “…. -- There's more... -- See also -- Extracting distinctive regions using MSER -- How to do it... -- How it works... -- See also -- Extracting foreground objects with the GrabCut algorithm -- How to do it... -- How it works... -- See also -- Chapter 6: Filtering the Images -- Filtering images using low-pass filters -- How to do it... -- How it works... -- See also -- Downsampling an image -- How to do it... -- How it works... -- There's more... -- Interpolating pixel values -- See also -- Filtering images using a median filter -- How to do it... -- How it works... -- Applying directional filters to detect edges -- How to do it... -- How it works... -- There's more... -- Gradient operators -- Gaussian derivatives -- See also -- Computing the Laplacian of an image -- How to do it... -- How it works... -- There's more... -- Enhancing the contrast of an image using the Laplacian -- Difference of Gaussians -- See also -- Chapter 7: Extracting Lines, Contours, and Components -- Detecting image contours with the Canny operator -- How to do it... -- How it works... -- See also -- Detecting lines in images with the Hough transform -- Getting ready -- How to do it... -- How it works... -- There's more... -- Detecting circles -- See also -- Fitting a line to a set of points -- How to do it... -- How it works... -- There's more... -- Extracting the components' contours -- How to do it... -- How it works... -- There's more... -- Computing components' shape descriptors -- How to do it..…”

Tabla de Contenidos: “…Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Dedication -- Acknowledgement -- Table of Contents -- Preface -- List of Figures -- List of Tables -- List of Contributors -- Chapter 1: Benchmarking Neuromorphic Computing for Inference -- 1.1: Introduction -- 1.2: State of the art in Benchmarking -- 1.2.1: Machine Learning -- 1.2.2: Hardware -- 1.3: Guidelines -- 1.3.1: Fair and Unfair Benchmarking -- 1.3.2: Combined KPIs and Approaches for Benchmarking -- 1.3.3: Outlook : Use-case Based Benchmarking -- 1.4: Conclusion -- References -- Chapter 2: Benchmarking the Epiphany Processor as a Reference Neuromorphic Architecture -- 2.1: Introduction and Background -- 2.2: Comparison with a Few Well-Known Digital Neuromorphic Platforms -- 2.3: Major Challenges in Neuromorphic Architectures -- 2.3.1: Memory Allocation -- 2.3.2: Efficient Communication -- 2.3.3: Mapping SNN onto Hardware -- 2.3.4: On-chip Learning -- 2.3.5: Idle Power Consumption -- 2.4: Measurements from Epiphany -- 2.5: Conclusion -- References -- Chapter 3: Temporal Delta Layer: Exploiting Temporal Sparsity in Deep Neural Networks for Time-Series Data -- 3.1: Introduction -- 3.2: Related Works -- 3.3: Methodology -- 3.3.1: Delta Inference -- 3.3.2: Sparsity Induction Using Activation Quantization -- 3.3.2.1: Fixed Point Quantization -- 3.3.2.2: Learned Step-Size Quantization -- 3.3.3: Sparsity Penalty -- 3.4: Experiments and Results -- 3.4.1: Baseline -- 3.4.2: Experiments -- 3.4.3: Result Analysis -- 3.5: Conclusion -- References -- Chapter 4: An End-to-End AI-based Automated Process for Semiconductor Device Parameter Extraction -- 4.1: Introduction -- 4.2: Semantic Segmentation -- 4.2.1: Proof of Concept and Architecture Overview -- 4.2.2: Implementation Details and Result Overview -- 4.3: Parameter Extraction -- 4.4: Conclusion -- 4.5: Future Work -- References…”

Tabla de Contenidos: “…Understanding coordinate conversion -- Understanding reprojection -- Understanding coordinate format conversion -- Calculating the area of a polygon -- Using ChatGPT to measure a polygon perimeter -- Summary -- Questions -- Further reading -- Chapter 6: Creating and Editing GIS Data -- Technical requirements -- Editing shapefiles -- Accessing the shapefile -- Changing a shapefile -- Adding fields -- Merging shapefiles -- Splitting shapefiles -- Performing selections -- Aggregating geometry -- Extracting geometry -- Connecting polygon faces to the nearest line point -- Creating images for visualization -- Dot density calculations -- Choropleth maps -- Using spreadsheets -- Creating heat maps -- Using GPS data -- Turning addresses into points with geocoding -- Performing GIS analysis faster with multiprocessing -- Summary -- Questions -- Further reading -- Chapter 7: Python and Remote Sensing -- Technical requirements -- Examining raster data properties -- Swapping image bands -- Creating image histograms -- Performing a histogram stretch -- Clipping images -- Classifying images -- Extracting features from images -- Understanding change detection -- Extracting image footprints using ChatGPT -- Summary -- Questions -- Further reading -- Chapter 8: Python and Elevation Data -- Technical requirements -- Accessing ASCII Grid files -- Reading grids -- Writing grids -- Creating a shaded relief -- Creating elevation contours -- Working with LiDAR data -- Creating a grid from the LiDAR data -- Using PIL to visualize LiDAR data -- Creating a triangulated irregular network -- Colorizing LiDAR with aerial images -- Classifying LiDAR -- Working with bathymetry -- Summary -- Questions -- Further reading -- Part 3: Practical Geospatial Processing Techniques -- Chapter 9: Advanced Geospatial Modeling -- Technical requirements…”

Tabla de Contenidos: “…Adding swimlanes and completing the process diagram -- Defining data models -- Building the Task UI -- Integration with external services -- Working with users -- Working together with robots -- Packaging and deployment -- Escalation and exception handling -- Administration and troubleshooting -- Summary -- Further reading -- Chapter 8: Automating Decisions to Speed Up Your Processes -- Business problem -- Modeling - decision models and task models -- The decision model -- The data model -- The task model -- Composition of models -- Writing simple and complex decision logic -- Business rules -- Decision tables -- Defining the logic -- Rule vocabulary -- Governing changes in decision logic -- Collaboration -- Changes and commits -- Branches and merges -- Connection with Git -- Testing decisions -- Packaging and deploying decisions -- Single-click deployment -- Automation services -- Packaging and advanced deployment options -- Combining decisions with AI prediction -- Summary -- Chapter 9: Manage Documents with Content Management -- Problem statement -- Designing your content repositories -- Security -- Business data -- Applications -- Creating a content desktop -- Document entry template -- Role-based redaction -- Teamspaces -- Searching and accessing content from applications -- Extensions -- Retention policy -- Summary -- Further reading -- Chapter 10: Extract Meanings with Document Processing -- Technical requirements -- Example - a bill of lading document -- Setting expectations for AI document processing systems -- Problem statement - automating inventory management systems -- Content classification and extraction with AI -- Document types and samples -- Training the classification model -- Training the extraction model -- Building a document processing application -- Customized document types and data formats -- Create document type…”

Tabla de Contenidos: “…. -- 3.1 PRETREATMENT AND ANALYSIS METHODS OF HEAVY METALS -- 3.1.1 Pretreatment Procedures and Equipment -- 3.1.1.1 Crushing -- 3.1.1.2 Digestion and Analysis of Total Amount of Heavy Metals -- 3.1.2 Analysis of Heavy Metals -- 3.1.3 Analysis of Mercury -- 3.1.4 European Communities Bureau of Reference (BCR) Morphological Analysis of Construction and Demolition Waste -- 3.1.4.1 Acid Extractable Fraction -- 3.1.4.2 Reducible Fraction -- 3.1.4.3 Oxidisable Fraction -- 3.1.4.4 Residual Fraction -- 3.1.5 Analysis of Heavy Metals Leaching Toxicity in Waste -- 3.1.6 X-Ray Powder Diffraction and X-Ray Photoelectron Spectroscopy Analysis -- 3.2 ANALYSIS OF ORGANIC POLLUTANTS AND CYANIDES -- 3.2.1 Sample Preparation and Storage -- 3.2.2 Extraction Procedures of Organic Pollutants -- 3.2.2.1 Soxhlet Extraction -- 3.2.2.2 Ultrasonic Extraction -- 3.2.3 Cleanup Methods of Organic Pollutants -- 3.2.4 Qualitative and Quantitative Analysis Using GC-MS -- 3.2.5 Effects of Pollutants, Procedures, and Types of Waste on Recovery Rate -- 3.2.6 Comparison of Organic Pollutants Leaching Systems in Waste -- Four - Pollution Characteristics of Industrial Construction and Demolition Waste -- 4.1 MERCURY AND ITS DISTRIBUTION IN CONSTRUCTION AND DEMOLITION WASTE -- 4.1.1 Distribution Characteristics of Mercury -- 4.1.2 Single Factor Evaluation of Mercury Pollution -- 4.2 CHARACTERIZATION OF CU/ZN/PB/CR/CD/NI IN INDUSTRIAL C&amp -- D WASTE -- 4.2.1 Total Concentrations of Heavy Metals in C&amp -- D Waste -- 4.2.2 X-Ray Fluorescence Analysis of Heavy Metals in C&amp -- D Waste -- 4.2.3 X-Ray Diffraction Analysis of Heavy Metals in C&amp -- D Waste -- 4.2.4 Chemical Speciation of Heavy Metals in C&amp -- D Waste…”

Tabla de Contenidos: “…2.2.13 Leave-One-Out Encoding -- 2.2.14 James-Stein Encoding -- 2.2.15 M-Estimator Encoding -- 2.2.16 Using HephAIstos to Encode Categorical Data -- 2.3 Time-Related Features Engineering -- 2.3.1 Date-Related Features -- 2.3.2 Lag Variables -- 2.3.3 Rolling Window Feature -- 2.3.4 Expending Window Feature -- 2.3.5 Understanding Time Series Data in Context -- 2.4 Handling Missing Values in Machine Learning -- 2.4.1 Row or Column Removal -- 2.4.2 Statistical Imputation: Mean, Median, and Mode -- 2.4.3 Linear Interpolation -- 2.4.4 Multivariate Imputation by Chained Equation Imputation -- 2.4.5 KNN Imputation -- 2.5 Feature Extraction and Selection -- 2.5.1 Feature Extraction -- 2.5.1.1 Principal Component Analysis -- 2.5.1.2 Independent Component Analysis -- 2.5.1.3 Linear Discriminant Analysis -- 2.5.1.4 Locally Linear Embedding -- 2.5.1.5 The t-Distributed Stochastic Neighbor Embedding Technique -- 2.5.1.6 More Manifold Learning Techniques -- 2.5.1.7 Feature Extraction with HephAIstos -- 2.5.2 Feature Selection -- 2.5.2.1 Filter Methods -- 2.5.2.2 Wrapper Methods -- 2.5.2.3 Embedded Methods -- 2.5.2.4 Feature Importance Using Graphics Processing Units (GPUs) -- 2.5.2.5 Feature Selection Using HephAIstos -- Further Reading -- Chapter 3 Machine Learning Algorithms -- 3.1 Linear Regression -- 3.1.1 The Math -- 3.1.2 Gradient Descent to Optimize the Cost Function -- 3.1.3 Implementation of Linear Regression -- 3.1.3.1 Univariate Linear Regression -- 3.1.3.2 Multiple Linear Regression: Predicting Water Temperature -- 3.2 Logistic Regression -- 3.2.1 Binary Logistic Regression -- 3.2.1.1 Cost Function -- 3.2.1.2 Gradient Descent -- 3.2.2 Multinomial Logistic Regression -- 3.2.3 Multinomial Logistic Regression Applied to Fashion MNIST -- 3.2.3.1 Logistic Regression with scikit-learn -- 3.2.3.2 Logistic Regression with Keras on TensorFlow…”

Tabla de Contenidos: “…Cover -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1 Text Extraction from Images Using Tesseract -- 1.1 Introduction -- 1.1.1 Areas -- 1.1.2 Why Text Extraction? …”

Tabla de Contenidos: “…3.3.2.3 Error Estimation to Prevent Overflow and Underflow -- 3.3.2.4 Twice-Try Structures for Block Discrimination -- 3.3.2.5 Improved Embedding and Extracting Processes -- 3.3.2.6 Simulation Results -- 3.3.3 HISTOGRAM SHIFT TECHNIQUE IN INTEGER DISCRETE COSINE TRANSFORM DOMAIN -- 3.3.3.1 Histogram Modification Technique for Lossless Information Hiding -- 3.3.3.2 Yang et al.'…”

Tabla de Contenidos: “…Slide, Slider, Grid, and Card -- Term and Details -- Body -- Map -- Table -- Trip -- Quote -- Weather and Forecast -- Banner -- Level -- Search result -- User Login -- Summary -- Chapter 5: Styling the Header and the Footer -- Regions and blocks -- Passing PHP variables by reference -- Retrieving the currently active theme -- Rendering an array for (very) simple markup -- Twig's autoescape feature -- How to override a template -- Defining theme regions -- Custom page.html.twig -- Overriding custom templates -- Including templates -- Finding templates -- Template suggestions -- Providing a new suggestion -- Blocks -- Styling menus -- Template preprocess -- Xdebug -- Summary -- Chapter 6: Styling the Content -- Entity, fields, bundles, and display modes -- Bundles -- Display modes -- Media and image styles -- Image styles -- Taxonomy terms -- How to structure content -- Using fields -- Using paragraphs -- Defining a new field formatter -- Plugins -- Customizing the WYSIWYG editor -- Text formats -- Alternative ways to manage content -- Summary -- Chapter 7: Styling Forms -- Understanding forms -- Render elements -- Theme wrappers -- Process, pre-, and post-render -- Altering existing forms -- Styling forms -- Styling generic forms -- Styling specific form -- Summary -- Chapter 8: Styling Views -- View templates -- Using a row plugin -- Using fields -- Exposed filters -- Pagers -- Summary -- Chapter 9: Styling Blocks -- Technical requirements -- Editorial blocks -- Adding a new block suggestion -- Injecting the block content into the template -- Extracting field values from the entity -- Extracting field values using a preprocess function -- Extracting field values using a bundle class -- Programmatic blocks -- Titles and breadcrumbs -- Title -- Breadcrumb -- Summary -- Chapter 10: Styling the Maintenance, Taxonomy, Search Results, and 403/404 Pages…”

Tabla de Contenidos: “…B.1.1 Step A: identify body fluids -- B.1.2 Step B: choose one body fluid -- B.1.3 Step C: identify metabolite chemical formula -- B.1.4 Step E: calculate the molecular size of the metabolite -- B.1.5 Design membrane system to separate metabolite -- B.1.6 Conductivity measurement of different compartments -- B.1.7 Calculate metabolite concentration -- B.1.8 Comments about the method -- B.2 Second method: surface modified interdigitated electrodes -- C Extracting Δεα from impedance measurements -- C.1 Equivalent circuit model -- C.2 Fitting the experimental data -- C.3 Extracting Δεα -- C.4 Example of fitting PC-3 cells experiments to extract Δε0 -- Complete Table Cell Surface Charge -- Bibliography…”

Tabla de Contenidos: “…An Overview of Our Research -- Transfer of Radiocesium to Rice in Contaminated Paddy Fields -- Cesium Translocation in Rice -- Absorption of radioceasium in soybean -- An observational study of pigs exposed to radiation -- A Composting System to Decompose Radiocesium Contaminated Baled Grass Silage -- Weathered Biotite: A Key Material of Radioactive Contamination in Fukushima -- Radiocesium accumulation in koshiabura (Eleutherococcus sciadophylloides) and other wild vegetables and in Fukushima Prefecture -- The Transition of Radiocesium in Peach Trees After the Fukushima Nuclear Accident -- Application of the Artificial Annual Environmental Cycle and Dormancy-induced Suppression of Cesium Uptake in Poplar -- Radiocesium Contamination in Forests and the Current Situation of Growing Oak Trees for Mushroom Logs -- Radiocesium Dynamics in Wild Mushrooms During the First Five Years After the Fukushima Accident -- The Spatial Distribution of Radiocesium Over a Four-year Period in a Forest Ecosystem in North Fukushima After the Nuclear Power Station Accident -- Parallel Measurement of Ambient and Individual External Radiation in Iitate Village, Fukushima -- Mobility of Fallout Radiocesium Depending on the Land Use in Kasumigaura Basin -- Challenges of Agricultural Land Remediation and Renewal of Agriculture in Iitate Village by a Collaboration Between Researchers and a Non-profit Organization -- Radiocesium Contamination on a University Campus and in Forests in Kashiwa City, Chiba Prefecture, a Suburb of Metropolitan Tokyo -- The State of Fisheries and Marine Species in Fukushima: Six Years After the 2011 Disaster -- Visualization of Ion Transport in Plants -- 90Sr analysis using inductively coupled plasma mass spectrometry with split-flow injection and online solid-phase extraction for multiple concentration and separation steps…”

Tabla de Contenidos: “…Putting big data at the heart of the decision-making process / Ian Thomas -- ch. 11. Extracting useful information from multivariate temporal data / Artur Dubrawski -- ch. 12. …”