Multimodal and Tensor Data Analytics for Industrial Systems Improvement (Record no. 59891)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 05614nam a22005655i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-031-53092-0 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20251030112044.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 240516s2024 sz | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9783031530920 |
| -- | 978-3-031-53092-0 |
| 024 7# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 10.1007/978-3-031-53092-0 |
| Source of number or code | doi |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | QA402.5-402.6 |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | PBU |
| Source | bicssc |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | MAT042000 |
| Source | bisacsh |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | PBU |
| Source | thema |
| 245 10 - TITLE STATEMENT | |
| Title | Multimodal and Tensor Data Analytics for Industrial Systems Improvement |
| Medium | [electronic resource] / |
| Statement of responsibility, etc. | edited by Nathan Gaw, Panos M. Pardalos, Mostafa Reisi Gahrooei. |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2024. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Place of production, publication, distribution, manufacture | Cham : |
| Name of producer, publisher, distributor, manufacturer | Springer International Publishing : |
| -- | Imprint: Springer, |
| Date of production, publication, distribution, manufacture, or copyright notice | 2024. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | X, 394 p. 100 illus., 95 illus. in color. |
| Other physical details | online resource. |
| 336 ## - CONTENT TYPE | |
| Content type term | text |
| Content type code | txt |
| Source | rdacontent |
| 337 ## - MEDIA TYPE | |
| Media type term | computer |
| Media type code | c |
| Source | rdamedia |
| 338 ## - CARRIER TYPE | |
| Carrier type term | online resource |
| Carrier type code | cr |
| Source | rdacarrier |
| 347 ## - DIGITAL FILE CHARACTERISTICS | |
| File type | text file |
| Encoding format | |
| Source | rda |
| 490 1# - SERIES STATEMENT | |
| Series statement | Springer Optimization and Its Applications, |
| International Standard Serial Number | 1931-6836 ; |
| Volume/sequential designation | 211 |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Chapter 1: Introduction to multimodal and tensor data analytics -- Chapter 2: Functional Methods for Multimodal Data Analysis -- Chapter 3: Advanced Data Analytical Techniques for Profile Monitoring -- Chapter 4: Statistical process monitoring methods based on functional data analysis -- Chapter 5: Tensor and multimodal data analysis -- Chapter 6: Tensor Data Analytics in Advanced Manufacturing Processes -- Chapter 7: Spatiotemporal Data Analysis – A Review of Techniques, Applications, and Emerging Challenges -- Chapter 8: Offshore Wind Energy Prediction Using Machine Learning with Multi-Resolution Inputs -- Chapter 9: Sparse Decomposition Methods for Spatio-temporal Anomaly Detection -- Chapter 10: Multimodal Deep Learning -- Chapter 11: Multimodal Deep Learning for Manufacturing Systems: Recent Progress and Future Trends -- Chapter 12: Synergy of Engineering and Statistics: Multimodal data Fusion for Quality Improvement -- Chapter 13: Manufacturing data fusion: a case study with steel rollingprocesses -- Chapter 14: AI-enhanced Fault Detection using Multi-structured Data in Semiconductor Manufacturing -- Chapter 15: A Survey of Advances in Multimodal Federated Learning with Applications -- Chapter 16: Bayesian Multimodal Data Analytics: An introduction -- Chapter 17: Bayesian approach to multimodal data in human factors engineering -- Chapter 18: Bayesian Multimodal Models for Risk Analyses of Low-Probability High-Consequence Events. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | This volume covers the latest methodologies for using multimodal data fusion and analytics across several applications. The curated content presents recent developments and challenges in multimodal data analytics and shines a light on a pathway toward new research developments. Chapters are composed by eminent researchers and practitioners who present their research results and ideas based on their expertise. As data collection instruments have improved in quality and quantity for many applications, there has been an unprecedented increase in the availability of data from multiple sources, known as modalities. Modalities express a large degree of heterogeneity in their form, scale, resolution, and accuracy. Determining how to optimally combine the data for prediction and characterization is becoming increasingly important. Several research studies have investigated integrating multimodality data and discussed the challenges and limitations of multimodal data fusion. This volume provides a topical overview of various methods in multimodal data fusion for industrial engineering and operations research applications, such as manufacturing and healthcare. Advancements in sensing technologies and the shift toward the Internet of Things (IoT) has transformed and will continue to transform data analytics by producing new requirements and more complex forms of data. The abundance of data creates an unprecedented opportunity to design more efficient systems and make near-optimal operational decisions. On the other hand, the structural complexity and heterogeneity of the generated data pose a significant challenge to extracting useful features and patterns for making use of the data and facilitating decision-making. Therefore, continual research is needed to develop new statistical and analytical methodologies that overcome these data challenges and turn them into opportunities. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | |
| 9 (RLIN) | 65522 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | |
| 9 (RLIN) | 65982 |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | |
| 9 (RLIN) | 65528 |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | |
| 9 (RLIN) | 65982 |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Gaw, Nathan. |
| Relator term | editor. |
| Relator code | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 9 (RLIN) | 76892 |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Pardalos, Panos M. |
| Relator term | editor. |
| Relator code | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 9 (RLIN) | 68568 |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Gahrooei, Mostafa Reisi. |
| Relator term | editor. |
| Relator code | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 9 (RLIN) | 76893 |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY | |
| Title | Springer Nature eBook |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Relationship information | Printed edition: |
| International Standard Book Number | 9783031530913 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Relationship information | Printed edition: |
| International Standard Book Number | 9783031530937 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Relationship information | Printed edition: |
| International Standard Book Number | 9783031530944 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| Uniform title | Springer Optimization and Its Applications, |
| International Standard Serial Number | 1931-6836 ; |
| Volume number/sequential designation | 211 |
| 9 (RLIN) | 73211 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://doi.org/10.1007/978-3-031-53092-0">https://doi.org/10.1007/978-3-031-53092-0</a> |
| 912 ## - | |
| -- | ZDB-2-SMA |
| 912 ## - | |
| -- | ZDB-2-SXMS |
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