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[null,"1.","Record Nr.",null,"UNINA9910144405103321"]
[null,null,"Titolo",null,"Ultrasound in chemistry : analytical applications / / edited by Jose-Luis Capelo-Martinez"]
[null,null,"Pubbl/distr/stampa",null,"Weinheim, [Germany] : , : Wiley-VCH Verlag GmbH & Co. KGaA, , 2009"]
[{"$nulls":4},"©2009"]
[null,null,"ISBN",null,"1-282-01064-6"]
[{"$nulls":4},"9786612010644"]
[{"$nulls":4},"3-527-62350-7"]
[{"$nulls":4},"3-527-62351-5"]
[null,null,"Descrizione fisica",null,"1 online resource (173 p.)"]
[null,null,"Disciplina",null,"543.5"]
[null,null,"Soggetti",null,"Ultrasonic waves"]
[{"$nulls":4},"Acoustic spectroscopy"]
[{"$nulls":4},"Chemistry, Analytic"]
[{"$nulls":4},"Sonochemistry"]
[{"$nulls":4},"Electronic books."]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references at the end of each chapters and index."]
[null,null,"Nota di contenuto",null,"Ultrasound in Chemistry; Contents; Preface; List of Contributors; 1 The Power of Ultrasound; 1.1 Introduction; 1.2 Cavitation; 1.2.1 Parameters Affecting Ultrasonic Cavitation; 1.2.1.1 Frequency; 1.2.1.2 Intensity; 1.2.1.3 Solvent; 1.2.1.4 Temperature; 1.2.1.5 External Pressure and Bubbled Gas; 1.2.1.6 Direct and Indirect Ultrasonic Application; 1.3 Common Ultrasonic Devices Used in Analytical Chemistry; 1.3.1 Ultrasonic Bath; 1.3.1.1 Types of Ultrasonic Baths; 1.3.1.2 How to Locate the Most Efcient Place Inside an Ultrasonic Bath; 1.3.1.3 Temperature Control"]
[{"$nulls":4},"1.3.1.4 Shape and Material of Reaction Container1.3.2 The Ultrasonic Probe; 1.3.2.1 Parts of an Ultrasonic Probe; 1.3.2.2 Types of Ultrasonic Probes; 1.3.2.3 Dead Zones; 1.3.2.4 How to Choose the Correct Ultrasonic Probe; 1.3.2.5 Temperature Control; 1.3.2.6 Shape and Material of Reaction Container; 1.4 Current Ultrasonic Devices for New Analytical Applications; References; 2 Ultrasonic Energy as a Tool for Sample Treatment for the Analysis of Elements and Elemental Speciation; 2.1 Introduction; 2.2 Parameters Inuencing Element "]
[{"$nulls":4},"Ultrasonic Solid-Liquid Extraction; 2.2.1 Extracting Reagent"]
[{"$nulls":4},"2.2.1.1 Extracting Reagents for Total Element Extraction2.2.1.2 Extracting Reagents for Elemental Speciation; 2.2.1.3 Extracting Reagents for Sequential Extraction Schemes; 2.2.2 Matrix Properties; 2.2.2.1 Type of Matrix; 2.2.2.2 Mass of Matrix; 2.2.2.3 Sample Size; 2.2.3 Ultrasonic Device; 2.2.3.1 Type of Ultrasonic Device; 2.2.3.2 Time of Ultrasonication; 2.2.3.3 Ultrasonic Amplitude; 2.2.3.4 Ultrasonic Frequency; 2.2.3.5 Temperature of Sonication; 2.3 US-SLE from Soils and Sediments; 2.4 US-SLE from Sewage Sludge; 2.5 US-SLE Extraction from Plants; 2.6 Extraction from Soft Tissues"]
[{"$nulls":4},"2.7 Total Element Determination2.7.1 US-SLE and US-SS for F-AAS; 2.7.2 US-SLE and US-SS for ET-AAS; 2.7.3 US-SLE and US-SS for CV and HG Employed with AAS or AFS; 2.8 Elemental Fractionation and Elemental Speciation; 2.8.1 What is Speciation?; 2.8.2 Shortening Sequential Fractionation Schemes; 2.8.3 Speciation for Soils and Sediments; 2.8.4 Speciation from Plants; 2.8.5 Speciation from Soft Tissues; 2.8.6 Speciation from Other Types of Samples; 2.9 On-Line Applications; 2.9.1 Open and Closed Systems; 2.9.2 UB; 2.9.3 UP; 2.10 Current Trends; 2.10.1 Accelerating Liquid-Liquid Extractions"]
[{"$nulls":4},"2.10.2 Chemical Vapor Formation2.11 Conclusion; References; 3 Ultrasonic Assisted Extraction for the Analysis of Organic Compounds by Chromatographic Techniques; 3.1 Introduction; 3.2 Overview of Classic and Modern Extraction Procedures for Organics; 3.3 Ultrasonic Assisted Extraction (UAE); 3.3.1 Basic Principles; 3.3.2 Parameters Inuencing Ultrasonic Assisted Extraction; 3.3.2.1 Amount of Sample; 3.3.2.2 Sample Particle Size; 3.3.2.3 Extraction Solvent; 3.3.2.4 pH of Extracting Solution; 3.3.2.5 Solvent Volume; 3.3.2.6 Sonic Power; 3.3.2.7 Frequency; 3.3.2.8 Extraction Time"]
[{"$nulls":4},"3.3.2.9 Extraction Temperature"]
[null,null,null,"Sommario/riassunto","This comprehensive reference and handbook covers all aspects of ultrasound for analytical applications. Besides classical extraction techniques, it also provides an overview of ultrasound applications and devotes two chapters to proteomics and polymer technology.From the contents:* Common ultrasonic devices * Elemental speciation* On-line applications* Accelerated extraction of semivolatile and volatile organics * Extracting reagent* The ultrasonic bath vs. the ultrasonic probe* Liquid-liquid extraction* Liquid-solid extraction* Solid-liquid extraction<b"]
[null,"2.","Record Nr.",null,"UNINA9910484512803321"]
[null,null,"Titolo",null,"Intelligent Data Engineering and Automated Learning -- IDEAL 2013 : 14th International Conference, IDEAL 2013, Hefei, China, October 20-23, 2013, Proceedings / / edited by Hujun Yin, Ke Tang, Yang Gao, Frank Klawonn, Minho Lee, Bin Li, Thomas Weise, Xin Yao"]
[null,null,"Pubbl/distr/stampa",null,"Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013"]
[null,null,"ISBN",null,"3-642-41278-5"]
[null,null,"Edizione",null,"[1st ed. 2013.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XVIII, 639 p. 215 illus.)"]
[null,null,"Collana",null,"Information Systems and Applications, incl. Internet/Web, and HCI, , 2946-1642 ; ; 8206"]
[null,null,"Disciplina",null,"006.312"]
[null,null,"Soggetti",null,"Data mining"]
[{"$nulls":4},"Pattern recognition systems"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Algorithms"]
[{"$nulls":4},"Information storage and retrieval systems"]
[{"$nulls":4},"Computer science"]
[{"$nulls":4},"Data Mining and Knowledge Discovery"]
[{"$nulls":4},"Automated Pattern Recognition"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Information Storage and Retrieval"]
[{"$nulls":4},"Theory of Computation"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Bibliographic Level Mode of Issuance: Monograph"]
[null,null,"Nota di contenuto",null,"A Pruning Algorithm for Extreme Learning Machine -- Measuring Stability and Discrimination Power of Metrics in Information Retrieval Evaluation -- System for Monitoring and Optimization of Micro- and Nano-Machining Processes Using Intelligent Voice and Visual Communication -- Racing for Unbalanced Methods Selection -- Super-Resolution from One Single Low-Resolution Image Based on R-KSVD and Example-Based Algorithm -- Bilateral Multi-issue Parallel Negotiation Model Based on Reinforcement Learning -- Learning to Detect the Subway Station Arrival for Mobile Users -- Vision Based Multi-pedestrian Tracking Using Adaptive Detection and Clustering -- Drilling Cost Prediction Based on Self-adaptive Differential Evolution and Support Vector Regression -- Web Service Evaluation Method Based "]
[{"$nulls":4},"on Time-aware Collaborative Filtering -- An Improved PBIL Algorithm for Path Planning Problem of Mobile Robots -- An Initialized ACO for the VRPTW -- Deadline-Aware Event Scheduling for Complex Event Processing Systems -- A Discrete Hybrid Bees Algorithm for Service Aggregation Optimal Selection in Cloud Manufacturing -- Continuous Motion Recognition Using Multiple Time Constant Recurrent Neural Network with a Deep Network Model -- An Extended Version of the LVA-Index -- Anomaly Monitoring Framework Based on Intelligent Data Analysis -- Customer Unification in E-Commerce -- Network Management Based on Domain Partition for Mobile Agents -- Multi-objective Quantum Cultural Algorithm and Its Application in the Wireless Sensor Networks’ Energy-Efficient Coverage Optimization -- Image Super Resolution via Visual Prior Based Digital Image Characteristics -- Deep Learning on Natural Viewing Behaviors to Differentiate Children with Fetal Alcohol Spectrum Disorder -- Prevailing Trends Detection of Public Opinions Based on Tianya Forum -- Fast and Accurate Sentiment Classification Using an Enhanced Naïve Bayes Model -- A Scale-Free Based Memetic Algorithm for Resource-Constrained Project Scheduling Problems -- ADirection based Multi-Objective Agent Genetic Algorithm -- A Study of Representations for Resource Constrained Project Scheduling Problems Using Fitness Distance Correlation -- Adapt a Text-Oriented Chunker for Oral Data: How Much Manual Effort Is Necessary? -- SVD Based Graph Regularized Matrix Factorization -- Clustering, Noise Reduction and Visualization Using Features Extracted from the Self-Organizing Map -- Efficient Service Deployment by Image-Aware VM Allocation Strategy -- Forecasting Financial Time Series Using a Hybrid Self-Organising Neural Model -- A Novel Diversity Maintenance Scheme for Evolutionary Multi-objective Optimization -- Adaptive Differential Evolution Fuzzy Clustering Algorithm with Spatial Information and Kernel Metric for Remote Sensing Imagery -- Dynamic EM in Neologism Evolution -- Estimation of the Regularisation Parameter in Huber-MRF for Image Resolution Enhancement -- Sparse Prototype Representation by Core Sets -- Reconstruction of Wind Speed Based on Synoptic Pressure Values and Support Vector Regression -- Direct Solar Radiation Prediction Based on Soft-Computing Algorithms Including Novel Predictive Atmospheric Variables -- A Novel Coral Reefs Optimization Algorithm for Multi-objective Problems -- Fuzzy Clustering with Grouping Genetic Algorithms -- Graph-Based Substructure Pattern Mining Using CUDA Dynamic Parallelism -- Scaling Up Covariance Matrix Adaptation Evolution Strategy Using Cooperative Coevolution -- Gradient Boosting-Based Negative Correlation Learning -- Metamodel Assisted Mixed-Integer Evolution Strategies Based on Kendall Rank Correlation Coefficient -- Semi-supervised Ranking via List-Wise Approach -- Gaussian Process for Transfer Learning through Minimum Encoding -- Kernel Based Manifold Learning for Complex Industry Fault Detection -- An Estimation of Distribution Algorithm for the 3D Bin Packing Problem with Various Bin Sizes -- Accelerating BIRCH for Clustering Large Scale Streaming Data Using CUDA Dynamic Parallelism -- Swarm Intelligence in Big Data Analytics -- Multidimensional Dynamic Trust Measurement Model with Incentive Mechanism for Internetware -- Global Path Planning of Wheeled Robots Using a Multi-Objective Memetic Algorithm -- Quantifying Flow Field Distances Based on a Compact Streamline Representation -- MCGA: A Multiobjective Cellular Genetic Algorithm Based on a 3D Grid -- Multi-Objective Particle Swarm Optimization Algorithm Based on Population Decomposition -- An Effective Ant Colony Approach for Scheduling Parallel Batch-Processing Machines -- Understanding Instance "]
[{"$nulls":4},"Complexity in the Linear Ordering Problem -- Multi-Objective Evolutionary Algorithm Based on Decomposition for Air Traffic Flow Network Rerouting Problem -- Temporal Dependence in Legal Documents -- Learning-Guided Exploration in Airfoil Optimization -- A Trigram Language Model to Predict Part of Speech Tags Using Neural Network -- Handling Different Levels of Granularity within Naive Bayes Classifiers -- Genetic Algorithm on GPU Performance Optimization Issues -- Mutual Information for Performance Assessment of Multi Objective Optimisers: Preliminary Results -- Velocity Divergence of CCPSO in Large Scale Global Optimization -- Machine Learning Enhanced Multi-Objective Evolutionary Algorithm Based on Decomposition -- High against Low Quantile Comparison for Biomarker and Classifier Evaluation -- Learning a Label-Noise Robust Logistic Regression: Analysis and Experiments -- Hybrid Bacterial Foraging Algorithm for Data Clustering -- Swarm Intelligence with Clustering for Solving SAT -- Multilevel Bee Swarm Optimization for Large Satisfiability Problem Instances -- Voting-XCSc: A Consensus Clustering Method via Learning Classifier System -- Distance Weighted Cosine Similarity Measure for Text Classification -- A Survey on Benchmarks for Big Data and Some More Considerations -- Spectral Clustering Algorithm Based on Local Sparse Representation."]
[null,null,null,"Sommario/riassunto","This book constitutes the refereed proceedings of the 14th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2013, held in Hefei, China, in October 2013. The 76 revised full papers presented were carefully reviewed and selected from more than 130 submissions. These papers provided a valuable collection of latest research outcomes in data engineering and automated learning, from methodologies, frameworks and techniques to applications. In addition to various topics such as evolutionary algorithms, neural networks, probabilistic modelling, swarm intelligent, multi-objective optimisation, and practical applications in regression, classification, clustering, biological data  processing, text processing, video analysis, including a number of special sessions on emerging topics such as adaptation and learning multi-agent systems, big data, swarm intelligence and data mining, and combining learning and optimisation in intelligent data engineering."]