LEADER 05063nam 2200625 450 001 9910464763103321 005 20200520144314.0 010 $a1-68015-600-4 010 $a0-7844-7860-0 035 $a(CKB)3710000000185856 035 $a(EBL)3115679 035 $a(SSID)ssj0001472120 035 $a(PQKBManifestationID)11783398 035 $a(PQKBTitleCode)TC0001472120 035 $a(PQKBWorkID)11435168 035 $a(PQKB)10635171 035 $a(MiAaPQ)EBC3115679 035 $a(Au-PeEL)EBL3115679 035 $a(CaPaEBR)ebr10898806 035 $a(OCoLC)922966144 035 $a(EXLCZ)993710000000185856 100 $a20140807h20142014 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt$crdacontent 182 $cc$crdamedia 183 $acr$2rdacarrier 200 00$aShale energy engineering 2014 $etechnical challenges, environmental issues, and public policy : proceedings of the 2014 Shale Energy Engineering Conference, July 21-23, 2014, Pittsburgh, Pennsylvania /$fsponsored by The Energy Division of the American Society of Civil Engineers ; edited by Christopher L. Meechan [and four others] 210 1$aReston, Virginia :$cAmerican Society of Civil Engineers,$d2014. 210 4$d©2014 215 $a1 online resource (747 p.) 300 $aDescription based upon print version of record. 311 $a0-7844-1365-7 320 $aIncludes bibliographical references. 327 $a""Cover""; ""Contents""; ""Water Resources Management in Shale Oil and Gas Development""; ""Water Resources and Groundwater Issues in Shale Development""; ""Modeling of Land Movement due to Groundwater Pumping from an Aquifer System with Stress-Dependent Storage""; ""Baseline Water Quality Monitoring Prior to Hydraulic Fracturing to Promote Scientifically-Based Transparency""; ""Feasibility of Using Brackish Groundwater Desalination Concentrate as Hydraulic Fracturing Fluid in the Eagle Ford Shale""; ""Produced Water Management and Treatment Technologies"" 327 $a""Evolution of Best Management Practices and Water Treatment in High-Volume Hydraulic Fracturing Operations""""Recycling of Produced and Flowback Water in Oil and Gas Drilling Operations through Hydraulic Fracturing in Texas""; ""Review of Flowback and Produced Water Management, Treatment, and Beneficial Use for Major Shale Gas Development Basins""; ""Characterization of Waste Waters from Hydraulic Fracturing""; ""Electrodialysis Treatment of Flow-Back Water for Environmental Protection in Shale Gas Development""; ""Conversion of Marcellus Production Wastewater into Salable Products"" 327 $a""Environmental Issues in Produced Water Disposal""""Regulation of TDS and Chloride from Oil and Gas Wastewater in Pennsylvania""; ""Management of Produced Water in Pennsylvania: 2010a???2012""; ""Evaluating Leachability of Residual Solids from Hydraulic Fracturing in the Marcellus Shale""; ""Geological and Geotechnical Aspects of Shale Oil and Gas Well Development""; ""Geotechnical Aspects of Shale Oil and Gas""; ""The Role of Shallow Surface Investigations in Appalachian Shale Energy Development""; ""Geomechanical Characterization of Shale Formations for Sustainable Production"" 327 $a""Comminution of Solids Due to Kinetic Energy of High Shear Strain Rate: Implications for Shock and Shale Fracturing""""Guided Ultrasonic Waves for the Nondestructive Evaluation Imaging of Pipes""; ""Mechanical Behaviors of an Anisotropic Shale Rock""; ""Shale Fracturing for Energy Recovery: Current Issues and Review of Available Analytical and Computational Models""; ""Particle Stacking Model to Simulate Sedimentary Rock Microcracks""; ""Geomechanics and Numerical Simulation of Hydraulic Fracturing""; ""Fracture Mechanics Evaluation of Parameters Associated with Horizontal Hydrofracturing"" 327 $a""Numerical Simulation of Simultaneous Growth of Multiple Interacting Hydraulic Fractures from Horizontal Wells""""Subcritical Crack Propagation Enhanced by Chemical Injection""; ""Numerical Analysis on Deformation Behavior of Expandable Casing and Contact Evaluation of Its Threaded Connection""; ""Hydro-Mechanical Coupled Model of Hydraulic Fractures Using the eXtended Finite Element Method""; ""Modeling Flow Regime in Shale Using Isogeometric Analysis""; ""Characterizing and Validating Seismic Impact""; ""Towards a Real-Time Forecast of Induced Seismicity for Enhanced Geothermal Systems"" 327 $a""Predicting the Seismic Hazard Due to Deep Injection Well-Induced Seismicity"" 606 $aShale oils$vCongresses 606 $aShale gas industry$vCongresses 608 $aElectronic books. 615 0$aShale oils 615 0$aShale gas industry 676 $a665.4 702 $aMeechan$b Christopher L. 712 02$aEnergy Division of the American Society of Civil Engineers, 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910464763103321 996 $aShale energy engineering 2014$91940773 997 $aUNINA LEADER 03567nam 2200673 a 450 001 9910778186603321 005 20230207230429.0 010 $a0-674-04310-3 024 7 $a10.4159/9780674043107 035 $a(CKB)1000000000786854 035 $a(StDuBDS)AH23050876 035 $a(SSID)ssj0000158191 035 $a(PQKBManifestationID)11155950 035 $a(PQKBTitleCode)TC0000158191 035 $a(PQKBWorkID)10145951 035 $a(PQKB)10699074 035 $a(DE-B1597)574305 035 $a(DE-B1597)9780674043107 035 $a(MiAaPQ)EBC3300359 035 $a(OCoLC)1262307809 035 $a(EXLCZ)991000000000786854 100 $a20050815d2003 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aFreedom is, freedom ain't$b[electronic resource] $ejazz and the making of the sixties /$fScott Saul 210 $aCambridge, Mass. ;$aLondon $cHarvard University Press$d2003 215 $a1 online resource (xiv, 394 p. ) $cill., ports 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a0-674-01853-2 320 $aIncludes bibliographical references and index. 327 $tFrontmatter -- $tCONTENTS -- $tList of Illustrations -- $tPreface -- $tIntroduction: Hard Bop and the Impulse to Freedom -- $tPART ONE. A New Intellectual Vernacular -- $t1 Birth of the Cool: The Early Career of the Hipster -- $t2 Radicalism by Another Name: The White Negro Meets the Black Negro -- $tPART TWO. Redefining Youth Culture -- $t3 Riot on a Summer?s Day: White Youth and the Rise of the Jazz Festival -- $t4 The Riot in Reverse: The Newport Rebels, Langston Hughes, and the Mockery of Freedom -- $tPART THREE. The Sound of Struggle -- $t5 Outrageous Freedom: Charles Mingus and the Invention of the Jazz Workshop -- $t6 ?This Freedom?s Slave Cries?: Listening to the Jazz Workshop -- $tPART FOUR. Freedom?s Saint -- $t7 The Serious Side of Hard Bop: John Coltrane?s Early Dramas of Deliverance -- $t8 Loving A Love Supreme: Coltrane, Malcolm, and the Revolution of the Psyche -- $tPART FIVE. In and Out of the Whirlwind -- $t9 ?Love, Like Jazz, Is a Four Letter Word?: Jazz and the Counterculture -- $t10 The Road to ?Soul Power?: The Many Ends of Hard Bop -- $tNotes -- $tAcknowledgments -- $tIndex 330 $aThis text tells the story of the long decade between the mid-fifties and the late sixties - a time when jazz became both newly militant and newly seductive, its example powerfully shaping the social dramas of the Civil Rights movement, the Black Power movement and the counterculture. 606 $aJazz$y1961-1970$xHistory and criticism 606 $aJazz$y1951-1960$xHistory and criticism 606 $aJazz$xSocial aspects$zUnited States 606 $aMusic$2eflch 606 $aMusic$2HILCC 606 $aMusic, Dance, Drama & Film$2HILCC 606 $aMusic History & Criticism, Popular - Jazz, Rock, etc$2HILCC 608 $aElectronic books.$2lcsh 615 0$aJazz$xHistory and criticism. 615 0$aJazz$xHistory and criticism. 615 0$aJazz$xSocial aspects 615 7$aMusic. 615 7$aMusic 615 7$aMusic, Dance, Drama & Film 615 7$aMusic History & Criticism, Popular - Jazz, Rock, etc. 676 $a781.65097309046 700 $aSaul$b Scott$01462651 801 0$bStDuBDS 801 1$bStDuBDS 801 2$bUkPrAHLS 906 $aBOOK 912 $a9910778186603321 996 $aFreedom is, freedom ain't$93671715 997 $aUNINA LEADER 12521nam 22006855 450 001 9910746971103321 005 20230928041936.0 010 $a3-031-40688-5 024 7 $a10.1007/978-3-031-40688-1 035 $a(MiAaPQ)EBC30757759 035 $a(Au-PeEL)EBL30757759 035 $a(OCoLC)1401058336 035 $a(DE-He213)978-3-031-40688-1 035 $a(PPN)272736899 035 $a(CKB)28328636600041 035 $a(EXLCZ)9928328636600041 100 $a20230928d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aInnovations in Machine and Deep Learning $eCase Studies and Applications /$fedited by Gilberto Rivera, Alejandro Rosete, Bernabé Dorronsoro, Nelson Rangel-Valdez 205 $a1st ed. 2023. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2023. 215 $a1 online resource (506 pages) 225 1 $aStudies in Big Data,$x2197-6511 ;$v134 311 08$aPrint version: Rivera, Gilberto Innovations in Machine and Deep Learning Cham : Springer International Publishing AG,c2023 9783031406874 327 $aIntro -- Preface -- Contents -- Analytics-Oriented Applications -- Recursive Multi-step Time-Series Forecasting for Residual-Feedback Artificial Neural Networks: A Survey -- 1 Introduction -- 2 Residual-Feedback ANNs: A Systematic Review -- 2.1 Systematic Review Planning and Execution -- 2.2 Overview of the Systematic Review Findings -- 3 The Existing Recursive Multi-step Forecast Strategy Solution -- 4 Limitation -- 5 Conclusions and Future Works -- References -- Feature Selection: Traditional and Wrapping Techniques with Tabu Search -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Description -- 3.2 Entropy-Based Feature Selection -- 3.3 Feature Selection Using Principal Component Analysis -- 3.4 Correlation-Based Feature Selection -- 4 Tabu Search -- 4.1 Initial Solution -- 4.2 Neighborhood -- 4.3 Objective Function -- 4.4 Memory Structures -- 5 Results -- 6 Discussion -- 7 Conclusions and Future Work -- References -- Pattern Classification with Holographic Neural Networks: A New Tool for Feature Selection -- 1 Introduction -- 2 Holographic Neural Networks -- 2.1 Basic Theory -- 2.2 Learning and Prediction Methods -- 2.3 red Explainability and Optimization of Holographic Models -- 3 Feature Selection with Holographic Neural Neworks -- 3.1 Previous Works -- 3.2 Pythagorean Membership Grades -- 4 Pattern Classification -- 4.1 Iris Dataset -- 4.2 red NIPS Feature Selection Challenge -- 5 red Conclusions and Future Works -- References -- Reusability Analysis of K-Nearest Neighbors Variants for Classification Models -- 1 Introduction -- 2 The K-Nearest Neighbors Algorithm -- 3 The Parameter K -- 4 Closeness Metrics -- 5 Analysis of KNN Variants -- 5.1 Heuristics for Class Assignment -- 5.2 Reduction of Dataset Records -- 5.3 Estimation of Dataset Variables -- 5.4 Discussion -- 6 Conclusions -- References. 327 $aSpeech Emotion Recognition Using Deep CNNs Trained on Log-Frequency Spectrograms -- 1 Introduction -- 2 Literature Survey -- 2.1 Motivation -- 2.2 Contributions -- 3 Proposed Methodology -- 3.1 Data Augmentation -- 3.2 Extraction of Log-Frequency Spectrograms -- 3.3 Motivation Behind Using Spectrograms -- 3.4 Log-Frequency Spectrogram Extraction -- 3.5 Understanding What a Spectrogram Conveys -- 4 The Deep Convolutional Neural Network -- 4.1 Architecture -- 4.2 Training -- 5 Observations -- 5.1 Dataset Used -- 5.2 Performance Metrics Used -- 5.3 Results Obtained -- 5.4 Comparison Study -- 6 Conclusion -- References -- Text Classifier of Sensationalist Headlines in Spanish Using BERT-Based Models -- 1 Introduction -- 2 Background -- 2.1 Sensationalism -- 2.2 BERT-Based Models -- 3 Related Work -- 4 Dataset and Methods -- 4.1 Data Gathering and Data Labeling -- 4.2 Data Analysis -- 4.3 Model Generation and Fine-Tuning -- 5 Results -- 6 Conclusion -- References -- Arabic Question-Answering System Based on Deep Learning Models -- 1 Introduction -- 2 Natural Language Processing (NLP) -- 2.1 Difficulties in NLP -- 2.2 Natural Language Processing Phases -- 3 Question Answer System -- 3.1 Usage Deep Learning Models in Questions Answering System -- 3.2 Different Questions Based on Bloom's Taxonomy -- 3.3 Question-Answering System Based on Types -- 3.4 Wh-Type Questions (What, Which, When, Who) -- 4 List-Based Questions -- 5 Yes/No Questions -- 6 Causal Questions [Why or How] -- 7 Hypothetical Questions -- 8 Complex Questions -- 8.1 Question Answering System Issues -- 9 Arabic Language Overview -- 9.1 Arabic Language Challenges -- 10 Related Work -- 11 Proposed Methodology -- 11.1 Recurrent Neural Networks (RNNs) -- 11.2 Long Short-Term Memory (LSTM) -- 11.3 Gated Recurrent Unit (GRU) -- 12 Prepare the Dataset -- 12.1 Collecting Data -- 13 Data Preprocessing. 327 $a14 Results and Discussion -- 15 Conclusion and Future Work -- References -- Healthcare-Oriented Applications -- Machine and Deep Learning Algorithms for ADHD Detection: A Review -- 1 Introduction -- 2 Research Methodology -- 3 Related Work -- 3.1 Machine Learning Approaches -- 3.2 Deep Learning Approaches -- 4 Approaches for ADHD Detection Using AI Algorithms -- 4.1 Machine Learning-Based Approaches -- 4.2 Deep Learning-Based Approaches -- 5 Datasets for ADHD Detection -- 5.1 Hyperaktiv -- 5.2 Working Memory and Reward in Children with and Without ADHD -- 5.3 Working Memory and Reward in Adults -- 5.4 Eeg Data for ADHD -- 6 Machine Learning and Deep Learning Classifiers for ADHD Detection -- 7 Trends and Challenges -- 7.1 New Types of Sensors or Biosensors -- 7.2 Multi-Modal Detection and/or Diagnosis of ADHD -- 7.3 The Use of Biomarkers as Variables for Diagnosis -- 7.4 Interpretability -- 7.5 Building of Standardized and Accurate Public Datasets -- 7.6 Different Classification Techniques -- 8 Conclusion -- References -- Mosquito on Human Skin Classification Using Deep Learning -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Dataset Description -- 3.2 Deep Convolutional Neural Networks and Transfer Learning -- 3.3 Hyperparameter Tuning -- 3.4 Proposed Workflow -- 4 Experiments and Results -- 5 Conclusion and Future Work -- References -- Analysis and Interpretation of Deep Convolutional Features Using Self-organizing Maps -- 1 Introduction -- 2 Materials -- 2.1 Convolutional Neural Networks -- 2.2 Self-organizing Maps -- 3 Proposed Method -- 3.1 Stage A: Training of CNN -- 3.2 Stage B: Extraction of Features -- 3.3 Stage C: SOM Training -- 3.4 Stage D: Analysis and Interpretation -- 4 Application Example -- 4.1 Experimental Setup -- 4.2 Result Analysis -- 5 Conclusions -- References. 327 $aA Hybrid Deep Learning-Based Approach for Human Activity Recognition Using Wearable Sensors -- 1 Introduction -- 2 Literature Analysis -- 3 OPPORTUNITY Dataset -- 4 MHEALTH Dataset -- 5 HARTH Dataset -- 6 Materials and Methods -- 6.1 Some Preliminaries -- 6.2 Basic Architecture of CNN -- 7 Long-Short Term Memory (LSTM) -- 7.1 Working Principle of LSTM -- 8 Proposed Model Architecture -- 9 Dataset Description -- 9.1 MHEALTH Dataset -- 9.2 OPPORTUNITY Dataset -- 9.3 HARTH Dataset -- 10 Experimental Results -- 10.1 Evaluation Metrics Used -- 10.2 Results Analysis on MHEALTH Dataset -- 10.3 Results Analysis on OPPORTUNITY Dataset -- 10.4 Results Analysis on HARTH Dataset -- 10.5 Result Summary and Comparison -- 11 Conclusion and Future Works -- References -- Predirol: Predicting Cholesterol Saturation Levels Using Big Data, Logistic Regression, and Dissipative Particle Dynamics Simulation -- 1 Introduction -- 2 Related Works -- 2.1 Models for the Simulation of Fluids -- 2.2 Data Mining Application for Prevention of Cardiovascular Diseases -- 2.3 Comparative Analysis -- 3 PREDIROL Architecture -- 3.1 Big Data Model -- 3.2 Cholesterol Saturation Level Prediction Module -- 3.3 Cholesterol Levels Simulation Module with Dissipative Particle Dynamics -- 4 Case Study: Prediction of Cholesterol Levels of a Hospital Patients -- 5 Conclusions and Future Work -- References -- Convolutional Neural Network-Based Cancer Detection Using Histopathologic Images -- 1 Introduction -- 2 Image Processing Techniques -- 2.1 Statistical-Based Algorithms -- 2.2 Learning-Based Algorithms -- 2.3 Hyper-Parameters of CNN -- 2.4 Evaluation Metrics -- 2.5 Implementation -- 3 Stage 3: CNN Algorithm Training -- 3.1 Model Training Phase -- 3.2 Model Optimization Phase -- 4 Conclusion -- References. 327 $aArtificial Neural Network-Based Model to Characterize the Reverberation Time of a Neonatal Incubator -- 1 Introduction -- 2 Materials and Methods -- 2.1 Artificial Neural Networks Using the Levenberg-Marquardt Algorithm -- 3 Results -- 3.1 Data Analysis -- 3.2 Artificial Neural Network-Based Model Training -- 4 Conclusions -- References -- A Comparative Study of Machine Learning Methods to Predict COVID-19 -- 1 Introduction -- 2 Related Works -- 3 Background -- 3.1 Covid-19 -- 3.2 Machine Learning -- 4 Materials and Methods -- 4.1 Dataset Pre-processing -- 4.2 Machine Learning Models -- 5 Results and Discussions -- 6 Conclusions -- References -- Sustainability-Oriented Applications -- Multi-product Inventory Supply and Distribution Model with Non-linear CO2 Emission Model to Improve Economic and Environmental Aspects of Freight Transportation -- 1 Introduction -- 2 Literature Review and Contributions -- 3 Development of the Integrated Routing Model -- 3.1 Inventory Planning with Non-deterministic Demand and Multiple Products -- 3.2 Non-linear Emission for Heterogeneous Fleet -- 3.3 Association of Variables -- 4 Assessment of the Model -- 4.1 Numerical Data and Solving Method -- 4.2 Analysis of Results -- 5 Future Work -- 6 Statement -- References -- Convolutional Neural Networks for Planting System Detection of Olive Groves -- 1 Background -- 1.1 Evolution of Production Techniques in Olive Groves -- 1.2 Current Situation of Modern Olive Cultivation Systems -- 1.3 Application of Remote Sensing Techniques for Image Analysis -- 1.4 Scope of the Present Chapter -- 2 Materials and Experimental Methods -- 2.1 Area of Study and Image Acquisition -- 2.2 Methodology -- 3 Results and Discussion -- 4 Conclusions and Future Lines -- References -- A Conceptual Model for Analysis of Plant Diseases Through EfficientNet: Towards Precision Farming -- 1 Introduction. 327 $a2 Related Study. 330 $aIn recent years, significant progress has been made in achieving artificial intelligence (AI) with an impact on students, managers, scientists, health personnel, technical roles, investors, teachers, and leaders. This book presents numerous successful applications of AI in various contexts. The innovative implications covered fall under the general field of machine learning (ML), including deep learning, decision-making, forecasting, pattern recognition, information retrieval, and interpretable AI. Decision-makers and entrepreneurs will find numerous successful applications in health care, sustainability, risk management, human activity recognition, logistics, and Industry 4.0. This book is an essential resource for anyone interested in challenges, opportunities, and the latest developments and real-world applications of ML. Whether you are a student, researcher, practitioner, or simply curious about AI, this book provides valuable insights and inspiration for your work and learning. 410 0$aStudies in Big Data,$x2197-6511 ;$v134 606 $aEngineering$xData processing 606 $aComputational intelligence 606 $aBig data 606 $aData Engineering 606 $aComputational Intelligence 606 $aBig Data 615 0$aEngineering$xData processing. 615 0$aComputational intelligence. 615 0$aBig data. 615 14$aData Engineering. 615 24$aComputational Intelligence. 615 24$aBig Data. 676 $a620.00285 700 $aRivera$b Gilberto$01429198 701 $aRosete$b Alejandro$01429200 701 $aDorronsoro$b Bernabé$0845968 701 $aRangel-Valdez$b Nelson$01431206 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910746971103321 996 $aInnovations in Machine and Deep Learning$93573321 997 $aUNINA