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Biblioteca

MARC Lista (tabellare)
Applied Data Science and Smart Systems
Applied Data Science and Smart Systems
Autore Singh Jaiteg
Edizione [1st ed.]
Pubbl/distr/stampa Milton : , : Taylor & Francis Group, , 2024
Descrizione fisica 1 online resource (632 pages)
Altri autori (Persone) GoyalS. B
Kumar KaushalRajesh
KumarNaveen
Singh SehraSukhjit
ISBN 1-003-47105-6
1-04-001723-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910870872903321
Singh Jaiteg  
Milton : , : Taylor & Francis Group, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Big Data Analytics [[electronic resource] ] : 4th International Conference, BDA 2015, Hyderabad, India, December 15-18, 2015, Proceedings / / edited by Naveen Kumar, Vasudha Bhatnagar
Big Data Analytics [[electronic resource] ] : 4th International Conference, BDA 2015, Hyderabad, India, December 15-18, 2015, Proceedings / / edited by Naveen Kumar, Vasudha Bhatnagar
Edizione [1st ed. 2015.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015
Descrizione fisica 1 online resource (XII, 267 p. 104 illus. in color.)
Disciplina 006.312
Collana Information Systems and Applications, incl. Internet/Web, and HCI
Soggetto topico Data mining
Health informatics
Database management
Information storage and retrieval
Algorithms
Data Mining and Knowledge Discovery
Health Informatics
Database Management
Information Storage and Retrieval
Algorithm Analysis and Problem Complexity
ISBN 3-319-27057-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents -- Big Data: Security and Privacy -- Privacy Protection or Data Value: Can We Have Both? -- 1 Introduction -- 2 Big Data -- 3 Privacy -- 3.1 Individuals Own Data About Themselves -- 3.2 Corporations Own Data Collected -- 3.3 Shared Ownership of Data -- 3.4 Summary -- Ownership -- 4 Privacy Principles -- 5 A Call for a New Approach -- 5.1 User and Corporate Obligations -- 5.2 System Obligations -- 5.3 Data Acquisition Process -- 5.4 Managing Private Queries -- 6 Summary -- References -- Open Source Social Media Analytics for Intelligence and Security Informatics Applications -- 1 Introduction -- 1.1 Online Social Media -- 1.2 Intelligence and Security Informatics -- 2 Technical and Computational Challenges -- 3 Machine Learning and Data Mining Techniques -- 4 Case Studies -- 4.1 Identification of Extremist Content, Users and Communities -- 4.2 Event Forecasting for Civil Unrest Related Events -- 5 Characterization and Classification of Related Work -- 6 ISI Leading Conferences and Journals -- 7 Conclusions -- References -- Big Data in Commerce -- Information Exploration in E-Commerce Databases -- 1 Introduction -- 2 Search Interface in E-Commerce -- 3 Obstacles in Exploratory Search -- 3.1 Limited Feedback in the Query Panel -- 3.2 Low Adaptivity of the Result Panel -- 3.3 Information Loss from Hidden Attributes -- 4 Extensions to Facilitate Exploratory Search -- 4.1 Exploratory Search in Query Panel -- 4.2 Exploratory Search in Result Panel -- 5 Evaluation -- 6 Conclusion -- References -- A Framework to Harvest Page Views of Web for Banner Advertising -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Existing Framework -- 3.2 Proposed Framework -- 4 Design Issues -- 5 Summary and Conclusions -- References -- Utility-Based Control Flow Discovery from Business Process Event Logs.
1 Research Motivation and Aim -- 2 Related Work and Research Contributions -- 3 Research Framework and Solution Approach -- 4 Experimental Analysis and Results -- 4.1 Experimental Dataset -- 4.2 Experimental Results -- 4.3 Airport Dataset Results -- 4.4 BPI 2014 Dataset Results -- 5 Conclusion -- References -- An Efficient Algorithm for Mining High-Utility Itemsets with Discount Notion -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 Preliminary -- 3.2 UP-Hist Tree and UP-Hist Algorithm -- 3.3 Utility-List Data Structure and FHM Algorithm -- 3.4 Three-Phase Algorithm for Mining High-Utility Itemsets with Discount Strategies -- 4 Integration of Discount Notion in State-of-the-art Algorithms -- 4.1 UP-Hist Discount Algorithm -- 4.2 FHM Discount Algorithm -- 5 Mining High-Utility Itemsets -- 6 Experiments and Results -- 7 Conclusion and Future Work -- References -- Big Data: Models and Algorithms -- Design of Algorithms for Big Data Analytics -- 1 Introduction -- 2 Building FCA Lattice -- 2.1 Inefficient Map-Reduce Based Design -- 2.2 Efficient Map-Reduce Based Design -- 3 High Velocity Datasets -- 4 Conclusions -- References -- Mobility Big Data Analysis and Visualization (Invited Talk) -- 1 Introduction -- 2 Public Transportation Data Analysis -- 2.1 Framework for Analyzing Smart Card Data -- 2.2 Visual Fusion Analysis Environment -- 3 Vehicle Recorder Data Analysis -- 3.1 Relationships Between Drivers' Behaviors and Their Past Driving Histories -- 3.2 Visual Exploration of Caution Spots -- 4 Conclusions -- References -- Finding Periodic Patterns in Big Data -- 1 Introduction -- 2 Periodic Pattern Mining in Time Series -- 2.1 The Basic Model of Periodic Patterns -- 2.2 The Limitations of Basic Model -- 2.3 Research Efforts to Address the Limitations -- 3 Periodic Pattern Mining in Transactional Databases.
3.1 The Basic Model of Periodic-Frequent Patterns -- 3.2 The Performance Issues of the Periodic-Frequent Pattern Model -- 3.3 Research Efforts to Address the Performance Issues -- 4 Experimental Results -- 4.1 Experimental Setup -- 4.2 Generation of Periodic-Frequent Patterns -- 4.3 Interesting Patterns Discovered in Accidents Database -- 4.4 Interesting Patterns Discovered in Shop-4 Database -- 5 Conclusions -- References -- VDMR-DBSCAN: Varied Density MapReduce DBSCAN -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 3.1 Partitioning Phase -- 3.2 Map Phase -- 3.3 Reduce Phase -- 3.4 Merge Phase -- 3.5 Relabeling of Data Points -- 4 Results and Discussions -- 4.1 Experimental Settings -- 4.2 Experimental Results -- 4.3 Clustering Results on Zahn_compound Dataset (DS1) -- 4.4 Clustering Results on Spiral Dataset (DS2) -- 4.5 Large Synthetic Dataset (DS3) -- 5 Conclusions and Future Work -- References -- Concept Discovery from Un-Constrained Distributed Context -- Abstract -- 1 Introduction -- 2 Definitions and Properties in FCA -- 3 Related Work -- 4 Methodology -- 4.1 Data Format and Input -- 4.2 Data Aggregation -- 4.3 Concept Finding Approach -- 4.4 Additional Important Insights -- 5 Implementation Using Spark -- 6 Evaluation and Results -- 7 Discussion -- 7.1 Scalability with Respect to Context -- 7.2 Comparison with Distributed Frequent Item-Set Mining -- 7.3 Concept Explosion -- 7.4 Mining Links Between Concepts -- 8 Conclusion -- Acknowledgments -- References -- Khanan: Performance Comparisonand Programming -Miner Algorithm in Column-Oriented and Relational Database Query Languages -- 1 Research Motivation and Aim -- 2 Related Work and Novel Contributions -- 2.1 Implementation of Mining Algorithms in Row-Oriented Databases -- 2.2 Implementation of Mining Algorithms in Column-Oriented Databases.
2.3 Performance Comparison of Mining Algorithms in Column-Oriented and Graph Databases -- 3 -Miner Algorithm -- 4 Implementation of -Miner Algorithm in SQL on Row-Oriented Database (MySQL) -- 5 Implementation of -Miner Algorithm on NoSQL Column-Oriented Database Cassandra -- 6 Experimental Dataset -- 7 Benchmarking and Performance Comparison -- 8 Conclusion -- References -- A New Proposed Feature Subset Selection Algorithm Based on Maximization of Gain Ratio -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Theoretical Background -- 4 Algorithm and Analysis -- 5 Empirical Study -- 5.1 Datasets -- 5.2 Experimental Results and Comparisons -- 5.3 Dimension Wise Comparison of Feature Selection Algorithms -- 5.4 Domain Wise Comparison of Feature Selection Algorithms -- 6 Conclusion -- References -- Big Data in Medicine -- Genomics 3.0: Big-Data in Precision Medicine -- 1 Introduction -- 2 Genomics 3.0 -- 3 Dimensions of Big-data -- 4 Genomic Big-data -- 4.1 Patient Data -- 4.2 Background Databases -- 5 Exploratory Data Analysis -- 6 Big-data to Information -- 7 Information to Knowledge -- 8 Integrative Systems Biology -- 9 Patient Stratification -- 10 Characteristics and Life of Genomic Big-data -- 11 Mark-up Languages to Represent Biological Data -- 12 The Big-data Genomics Platform iOMICS -- 13 Live Genome Research Case -- 14 Live Genomics and Precision Medicine Case -- References -- CuraEx - Clinical Expert System Using Big-Data for Precision Medicine -- 1 Introduction -- 2 CuraEx Overview -- 3 Patient Specific Information -- 4 Analytical Engine -- 4.1 Cancer Staging -- 4.2 Prognosis -- 4.3 Therapeutics -- 5 Knowledge Database -- 6 Software Stack and Data Management -- 7 Conclusion -- References -- Multi-omics Multi-scale Big Data Analytics for Cancer Genomics -- 1 Introduction -- 2 Available Data -- 2.1 DNA Level Data -- 2.2 RNA Level Data.
2.3 Clinical Data -- 2.4 Background Databases -- 3 Key Aims -- 4 Exploratory Data Analysis -- 4.1 Mutation Association with Cancer State -- 4.2 Differential Gene Expression -- 4.3 Patient Stratification -- 5 Multi-scale Integrative Analysis -- 6 Data Integration and Network Analysis -- 6.1 Functional Characterization Databases -- 6.2 Metabolic Network Reconstruction and Protein Interactions -- 7 Conclusions -- References -- Class Aware Exemplar Discovery from Microarray Gene Expression Data -- Abstract -- 1 Introduction -- 2 Overview of Our Approach -- 2.1 Gene Data -- 2.2 Gene-Gene Similarity -- 2.3 Class Aware Preference -- 2.4 Class Aware Message Passing -- 3 Experimental Evaluation -- 3.1 Description of Experimental Datasets -- 3.2 Comparison of Class Aware Exemplar Discovery with Affinity Propagation -- 3.3 Comparison of Class Aware Exemplar Discovery with Standard Feature Subset Selection Techniques -- 3.4 Comparison of Class Aware Exemplar Discovery with All Features -- 4 Conclusions -- References -- Multistage Classification for Cardiovascular Disease Risk Prediction -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 3.1 Data Set -- 4 Experiments and Results -- 4.1 Pre-processing -- 4.2 Feature Extraction -- 4.3 Classification -- 5 Conclusion -- Acknowledgement -- References -- Author Index.
Record Nr. UNISA-996466231503316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Big Data Analytics : 4th International Conference, BDA 2015, Hyderabad, India, December 15-18, 2015, Proceedings / / edited by Naveen Kumar, Vasudha Bhatnagar
Big Data Analytics : 4th International Conference, BDA 2015, Hyderabad, India, December 15-18, 2015, Proceedings / / edited by Naveen Kumar, Vasudha Bhatnagar
Edizione [1st ed. 2015.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015
Descrizione fisica 1 online resource (XII, 267 p. 104 illus. in color.)
Disciplina 006.312
Collana Information Systems and Applications, incl. Internet/Web, and HCI
Soggetto topico Data mining
Health informatics
Database management
Information storage and retrieval
Algorithms
Data Mining and Knowledge Discovery
Health Informatics
Database Management
Information Storage and Retrieval
Algorithm Analysis and Problem Complexity
ISBN 3-319-27057-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents -- Big Data: Security and Privacy -- Privacy Protection or Data Value: Can We Have Both? -- 1 Introduction -- 2 Big Data -- 3 Privacy -- 3.1 Individuals Own Data About Themselves -- 3.2 Corporations Own Data Collected -- 3.3 Shared Ownership of Data -- 3.4 Summary -- Ownership -- 4 Privacy Principles -- 5 A Call for a New Approach -- 5.1 User and Corporate Obligations -- 5.2 System Obligations -- 5.3 Data Acquisition Process -- 5.4 Managing Private Queries -- 6 Summary -- References -- Open Source Social Media Analytics for Intelligence and Security Informatics Applications -- 1 Introduction -- 1.1 Online Social Media -- 1.2 Intelligence and Security Informatics -- 2 Technical and Computational Challenges -- 3 Machine Learning and Data Mining Techniques -- 4 Case Studies -- 4.1 Identification of Extremist Content, Users and Communities -- 4.2 Event Forecasting for Civil Unrest Related Events -- 5 Characterization and Classification of Related Work -- 6 ISI Leading Conferences and Journals -- 7 Conclusions -- References -- Big Data in Commerce -- Information Exploration in E-Commerce Databases -- 1 Introduction -- 2 Search Interface in E-Commerce -- 3 Obstacles in Exploratory Search -- 3.1 Limited Feedback in the Query Panel -- 3.2 Low Adaptivity of the Result Panel -- 3.3 Information Loss from Hidden Attributes -- 4 Extensions to Facilitate Exploratory Search -- 4.1 Exploratory Search in Query Panel -- 4.2 Exploratory Search in Result Panel -- 5 Evaluation -- 6 Conclusion -- References -- A Framework to Harvest Page Views of Web for Banner Advertising -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Existing Framework -- 3.2 Proposed Framework -- 4 Design Issues -- 5 Summary and Conclusions -- References -- Utility-Based Control Flow Discovery from Business Process Event Logs.
1 Research Motivation and Aim -- 2 Related Work and Research Contributions -- 3 Research Framework and Solution Approach -- 4 Experimental Analysis and Results -- 4.1 Experimental Dataset -- 4.2 Experimental Results -- 4.3 Airport Dataset Results -- 4.4 BPI 2014 Dataset Results -- 5 Conclusion -- References -- An Efficient Algorithm for Mining High-Utility Itemsets with Discount Notion -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 Preliminary -- 3.2 UP-Hist Tree and UP-Hist Algorithm -- 3.3 Utility-List Data Structure and FHM Algorithm -- 3.4 Three-Phase Algorithm for Mining High-Utility Itemsets with Discount Strategies -- 4 Integration of Discount Notion in State-of-the-art Algorithms -- 4.1 UP-Hist Discount Algorithm -- 4.2 FHM Discount Algorithm -- 5 Mining High-Utility Itemsets -- 6 Experiments and Results -- 7 Conclusion and Future Work -- References -- Big Data: Models and Algorithms -- Design of Algorithms for Big Data Analytics -- 1 Introduction -- 2 Building FCA Lattice -- 2.1 Inefficient Map-Reduce Based Design -- 2.2 Efficient Map-Reduce Based Design -- 3 High Velocity Datasets -- 4 Conclusions -- References -- Mobility Big Data Analysis and Visualization (Invited Talk) -- 1 Introduction -- 2 Public Transportation Data Analysis -- 2.1 Framework for Analyzing Smart Card Data -- 2.2 Visual Fusion Analysis Environment -- 3 Vehicle Recorder Data Analysis -- 3.1 Relationships Between Drivers' Behaviors and Their Past Driving Histories -- 3.2 Visual Exploration of Caution Spots -- 4 Conclusions -- References -- Finding Periodic Patterns in Big Data -- 1 Introduction -- 2 Periodic Pattern Mining in Time Series -- 2.1 The Basic Model of Periodic Patterns -- 2.2 The Limitations of Basic Model -- 2.3 Research Efforts to Address the Limitations -- 3 Periodic Pattern Mining in Transactional Databases.
3.1 The Basic Model of Periodic-Frequent Patterns -- 3.2 The Performance Issues of the Periodic-Frequent Pattern Model -- 3.3 Research Efforts to Address the Performance Issues -- 4 Experimental Results -- 4.1 Experimental Setup -- 4.2 Generation of Periodic-Frequent Patterns -- 4.3 Interesting Patterns Discovered in Accidents Database -- 4.4 Interesting Patterns Discovered in Shop-4 Database -- 5 Conclusions -- References -- VDMR-DBSCAN: Varied Density MapReduce DBSCAN -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 3.1 Partitioning Phase -- 3.2 Map Phase -- 3.3 Reduce Phase -- 3.4 Merge Phase -- 3.5 Relabeling of Data Points -- 4 Results and Discussions -- 4.1 Experimental Settings -- 4.2 Experimental Results -- 4.3 Clustering Results on Zahn_compound Dataset (DS1) -- 4.4 Clustering Results on Spiral Dataset (DS2) -- 4.5 Large Synthetic Dataset (DS3) -- 5 Conclusions and Future Work -- References -- Concept Discovery from Un-Constrained Distributed Context -- Abstract -- 1 Introduction -- 2 Definitions and Properties in FCA -- 3 Related Work -- 4 Methodology -- 4.1 Data Format and Input -- 4.2 Data Aggregation -- 4.3 Concept Finding Approach -- 4.4 Additional Important Insights -- 5 Implementation Using Spark -- 6 Evaluation and Results -- 7 Discussion -- 7.1 Scalability with Respect to Context -- 7.2 Comparison with Distributed Frequent Item-Set Mining -- 7.3 Concept Explosion -- 7.4 Mining Links Between Concepts -- 8 Conclusion -- Acknowledgments -- References -- Khanan: Performance Comparisonand Programming -Miner Algorithm in Column-Oriented and Relational Database Query Languages -- 1 Research Motivation and Aim -- 2 Related Work and Novel Contributions -- 2.1 Implementation of Mining Algorithms in Row-Oriented Databases -- 2.2 Implementation of Mining Algorithms in Column-Oriented Databases.
2.3 Performance Comparison of Mining Algorithms in Column-Oriented and Graph Databases -- 3 -Miner Algorithm -- 4 Implementation of -Miner Algorithm in SQL on Row-Oriented Database (MySQL) -- 5 Implementation of -Miner Algorithm on NoSQL Column-Oriented Database Cassandra -- 6 Experimental Dataset -- 7 Benchmarking and Performance Comparison -- 8 Conclusion -- References -- A New Proposed Feature Subset Selection Algorithm Based on Maximization of Gain Ratio -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Theoretical Background -- 4 Algorithm and Analysis -- 5 Empirical Study -- 5.1 Datasets -- 5.2 Experimental Results and Comparisons -- 5.3 Dimension Wise Comparison of Feature Selection Algorithms -- 5.4 Domain Wise Comparison of Feature Selection Algorithms -- 6 Conclusion -- References -- Big Data in Medicine -- Genomics 3.0: Big-Data in Precision Medicine -- 1 Introduction -- 2 Genomics 3.0 -- 3 Dimensions of Big-data -- 4 Genomic Big-data -- 4.1 Patient Data -- 4.2 Background Databases -- 5 Exploratory Data Analysis -- 6 Big-data to Information -- 7 Information to Knowledge -- 8 Integrative Systems Biology -- 9 Patient Stratification -- 10 Characteristics and Life of Genomic Big-data -- 11 Mark-up Languages to Represent Biological Data -- 12 The Big-data Genomics Platform iOMICS -- 13 Live Genome Research Case -- 14 Live Genomics and Precision Medicine Case -- References -- CuraEx - Clinical Expert System Using Big-Data for Precision Medicine -- 1 Introduction -- 2 CuraEx Overview -- 3 Patient Specific Information -- 4 Analytical Engine -- 4.1 Cancer Staging -- 4.2 Prognosis -- 4.3 Therapeutics -- 5 Knowledge Database -- 6 Software Stack and Data Management -- 7 Conclusion -- References -- Multi-omics Multi-scale Big Data Analytics for Cancer Genomics -- 1 Introduction -- 2 Available Data -- 2.1 DNA Level Data -- 2.2 RNA Level Data.
2.3 Clinical Data -- 2.4 Background Databases -- 3 Key Aims -- 4 Exploratory Data Analysis -- 4.1 Mutation Association with Cancer State -- 4.2 Differential Gene Expression -- 4.3 Patient Stratification -- 5 Multi-scale Integrative Analysis -- 6 Data Integration and Network Analysis -- 6.1 Functional Characterization Databases -- 6.2 Metabolic Network Reconstruction and Protein Interactions -- 7 Conclusions -- References -- Class Aware Exemplar Discovery from Microarray Gene Expression Data -- Abstract -- 1 Introduction -- 2 Overview of Our Approach -- 2.1 Gene Data -- 2.2 Gene-Gene Similarity -- 2.3 Class Aware Preference -- 2.4 Class Aware Message Passing -- 3 Experimental Evaluation -- 3.1 Description of Experimental Datasets -- 3.2 Comparison of Class Aware Exemplar Discovery with Affinity Propagation -- 3.3 Comparison of Class Aware Exemplar Discovery with Standard Feature Subset Selection Techniques -- 3.4 Comparison of Class Aware Exemplar Discovery with All Features -- 4 Conclusions -- References -- Multistage Classification for Cardiovascular Disease Risk Prediction -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 3.1 Data Set -- 4 Experiments and Results -- 4.1 Pre-processing -- 4.2 Feature Extraction -- 4.3 Classification -- 5 Conclusion -- Acknowledgement -- References -- Author Index.
Record Nr. UNINA-9910484457903321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Bioethanol production : past and present / / Neeraj K. Aggarwal, Naveen Kumar, and Mahak Mittal
Bioethanol production : past and present / / Neeraj K. Aggarwal, Naveen Kumar, and Mahak Mittal
Autore Aggarwal Neeraj K. <1973->
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (208 pages) : illustrations (chiefly color)
Disciplina 662.88
Collana Green Chemistry and Sustainable Technology
Soggetto topico Biomass energy
ISBN 3-031-05091-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Bioethanol : An Overview of Current Status and Future Direction Understanding of Different Processing Technologies for Bioethanol Production Current Trends in Pretreatment Technologies for Bioethanol Production: Biorefinery Concept A Feasible Approach for Bioethanol Production using Conventional and New Feed Stock Potential of Weed Biomass for Bioethanol Production Valorisation of Organic Fraction of Municipal Solid Waste (MSW) for Bioethanol Production Algae as Potential Feed Stock for Bioethanol Production
Record Nr. UNINA-9910574058103321
Aggarwal Neeraj K. <1973->  
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Modelling and Simulation of Diffusive Processes : Methods and Applications / / edited by S.K. Basu, Naveen Kumar
Modelling and Simulation of Diffusive Processes : Methods and Applications / / edited by S.K. Basu, Naveen Kumar
Edizione [1st ed. 2014.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Descrizione fisica 1 online resource (340 p.)
Disciplina 620.1064
Collana Simulation Foundations, Methods and Applications
Soggetto topico Computer simulation
Computer science - Mathematics
Bioinformatics
Computer Modelling
Mathematical Applications in Computer Science
Computational and Systems Biology
ISBN 3-319-05657-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Diffusive Processes and Modeling -- Diffusion and Transport of Molecules in Living Cells -- Modeling the Diffusion and Transport of Suspended Sediment in Open Channels, Using Two-Phase Flow Theory -- Mathematical Modeling of Peristaltic Pumping of Nano-Fluids -- Numerical Study on Isotachophoretic Separation of Ionic Samples in Microfluidics -- Thermal Characterization of Non-Homogeneous Media -- Scale Dependent Porous Dispersion Resulting from the Cumulative Effects of Velocity Fluctuations -- Modeling Nitrogen Fate and Transport at the Sediment-Water Interface -- Modeling Groundwater Flow in Unconfined Aquifers -- Two-Dimensional Solute Transport from a Varying Pulse-Type Point Source -- The Problem of Futile Cycles in Metabolic Flux Modeling -- Contaminant Concentration Prediction Along Unsteady Groundwater Flow -- Wavelet-Multigrid Method for Solving Modified Reynolds Equation Modeling Synovial Fluid Flow in a Normal Human Knee Joint -- A Basic Concept on Modeling Soil Organic Carbon -- Crop Growth Simulation Modeling.
Record Nr. UNINA-9910298566103321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui