E-Book, Englisch, Band 310, 203 Seiten, eBook
Tjoa / Zheng / Zou Research and Practical Issues of Enterprise Information Systems
Erscheinungsjahr 2018
ISBN: 978-3-319-94845-4
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
11th IFIP WG 8.9 Working Conference, CONFENIS 2017, Shanghai, China, October 18-20, 2017, Revised Selected Papers
E-Book, Englisch, Band 310, 203 Seiten, eBook
Reihe: Lecture Notes in Business Information Processing
ISBN: 978-3-319-94845-4
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
EIS concepts, Theory and Methods.- Modeling of Service Time in Public Organization Based on Business Processes.- A Behavior Analysis Method towards Product Quality Management.- Method of Domain Specific Code Generation Based on Knowledge Graph for Quantitative Trading.- Image Database Management Architecture: Logical Structure and Indexing Methods.- IoT and Emerging Paradigm.- Internet of Things or Surveillance of Things.- The Economic Value of An Emergency Call System.- An IoT-Big Data Based Machine Learning Technique for Forecasting Water Requirement in Irrigation Field.- EIS for Industry 4.0.- Penetration of Industry 4.0 Principles into ERP Products – A Central European Study.- Systematic Analysis of future competences affected by Industry 4.0.- Process-Based Analysis of Digitally Transforming Skills.- Big Data Analytics.- Big Data Analytics – Geolocation from the Perspective of Mobile Network Operator.- Pattern Discovery from Big Data of Food Sampling Inspections Based on Extreme Learning Machine.- Big Data Analytics Using SQL: Quo Vadis.- Intelligent Electronics and Systems for Industrial IoT.- Rethinking “Things” - Fog Layer Interplay in IoT: A Mobile Code Approach.- A Security Framework for Fog Networks based on Role-Based Access Control and Trust Models.- IoT Platform for Real-time Multichannel ECG Monitoring and Classification with Neural Networks.- Deep Ensemble Effectively and Efficiently for Vehicle Instance Retrieval.