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Logistics and Supply Chain Innovation : Bridging the Gap between Theory and Practice / / edited by Henk Zijm, Matthias Klumpp, Uwe Clausen, Michael ten Hompel
Logistics and Supply Chain Innovation : Bridging the Gap between Theory and Practice / / edited by Henk Zijm, Matthias Klumpp, Uwe Clausen, Michael ten Hompel
Edizione [1st ed. 2016.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Descrizione fisica 1 online resource (432 p.)
Disciplina 658.7
Collana Lecture Notes in Logistics
Soggetto topico Industrial Management
Production management
Electronic data processing - Management
Operations Management
IT Operations
ISBN 3-319-22288-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Logistics and Supply Chain Management: trends and developments -- . Synchromodal Transport Planning at a Logistics Service Provider -- DAVINC3I: Towards Collaborative Response Logistics Networks in Floriculture -- Towards Efficient Multimodal Hinterland Networks -- Current Deficiencies and Paths for Future Improvement in Corporate Sustainability Reporting -- Sustainable fuels for the transport and maritime sector: A Blueprint of the LNG distribution network -- Efficiency optimization for cold store warehouses through an electronic cooperation platform -- Urban Freight Transportation: Challenges, Failures and Successes -- The role of fairness in governing supply chain collaborations – a case-study in the Dutch floriculture industry -- Reducing the environmental impact of urban parcel distribution -- Order fulfillment and logistics considerations for multichannel retailers -- Connecting inventory and repair shop control for repairable items -- Knowledge lost in data: Organizational impediments to Condition-Based Maintenance in the process industry -- Planning Services: a Control Tower Solution for Managing Spare Parts -- Impediments to the adoption of reverse factoring for logistics service providers -- Towards an approach for long term AIS-based prediction of vessel arrival times.
Record Nr. UNINA-9910734899903321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Machine Learning under Resource Constraints. Applications / / ed. by Katharina Morik, Christian Wietfeld, Jörg Rahnenführer
Machine Learning under Resource Constraints. Applications / / ed. by Katharina Morik, Christian Wietfeld, Jörg Rahnenführer
Edizione [1st ed.]
Pubbl/distr/stampa Berlin ; ; Boston : , : De Gruyter, , [2022]
Descrizione fisica 1 online resource (VIII, 470 p.)
Disciplina 006.31
Collana De Gruyter STEM
Soggetto topico SCIENCE / Chemistry / General
Soggetto non controllato Artificial Intelligence
Big Data and Machine Learning
Cyber-physical systems
Data mining for Ubiquitous System Software
Embedded Systems and Machine Learning
Highly Distributed Data
ML on Small devices
Machine learning for knowledge discovery
Machine learning in high-energy physics
Resource-Aware Machine Learning
Resource-Constrained Data Analysis
ISBN 3-11-078598-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Frontmatter -- Contents -- 1 Editorial -- 2 Health / Medicine -- 2.1 Machine Learning in Medicine -- 2.2 Virus Detection -- 2.3 Cancer Diagnostics and Therapy from Molecular Data -- 2.4 Bayesian Analysis for Dimensionality and Complexity Reduction -- 2.5 Survival Prediction and Model Selection -- 2.6 Protein Complex Similarity -- 3 Industry 4.0 -- 3.1 Keynote on Industry 4.0 -- 3.2 Quality Assurance in Interlinked Manufacturing Processes -- 3.3 Label Proportion Learning -- 3.4 Simulation and Machine Learning -- 3.5 High-Precision Wireless Localization -- 3.6 Indoor Photovoltaic Energy Harvesting -- 3.7 Micro-UAV Swarm Testbed for Indoor Applications -- 4 Smart City and Traffic -- 4.1 Inner-City Traffic Flow Prediction with Sparse Sensors -- 4.2 Privacy-Preserving Detection of Persons and Classification of Vehicle Flows -- 4.3 Green Networking and Resource Constrained Clients for Smart Cities -- 4.4 Vehicle to Vehicle Communications: Machine Learning-Enabled Predictive Routing -- 4.5 Modelling of Hybrid Vehicular Traffic with Extended Cellular Automata -- 4.6 Embedded Crowdsensing for Pavement Monitoring and its Incentive Mechanisms -- 5 Communication Networks -- 5.1 Capacity Analysis of IoT Networks in the Unlicensed Spectrum -- 5.2 Resource-Efficient Vehicle-to-Cloud Communications -- 5.3 Mobile-Data Network Analytics Highly Reliable Networks -- 5.4 Machine Learning-Enabled 5G Network Slicing -- 5.5 Potential of Millimeter Wave Communications -- 6 Privacy -- 6.1 Keynote: Construction of Inference-Proof Agent Interactions -- Bibliography -- Index -- List of Contributors
Record Nr. UNISA-996503570503316
Berlin ; ; Boston : , : De Gruyter, , [2022]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Machine Learning under Resource Constraints. Applications / / ed. by Katharina Morik, Christian Wietfeld, Jörg Rahnenführer
Machine Learning under Resource Constraints. Applications / / ed. by Katharina Morik, Christian Wietfeld, Jörg Rahnenführer
Edizione [1st ed.]
Pubbl/distr/stampa Berlin ; ; Boston : , : De Gruyter, , [2022]
Descrizione fisica 1 online resource (VIII, 470 p.)
Disciplina 006.31
Collana De Gruyter STEM
Soggetto topico SCIENCE / Chemistry / General
Soggetto non controllato Artificial Intelligence
Big Data and Machine Learning
Cyber-physical systems
Data mining for Ubiquitous System Software
Embedded Systems and Machine Learning
Highly Distributed Data
ML on Small devices
Machine learning for knowledge discovery
Machine learning in high-energy physics
Resource-Aware Machine Learning
Resource-Constrained Data Analysis
ISBN 3-11-078598-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Frontmatter -- Contents -- 1 Editorial -- 2 Health / Medicine -- 2.1 Machine Learning in Medicine -- 2.2 Virus Detection -- 2.3 Cancer Diagnostics and Therapy from Molecular Data -- 2.4 Bayesian Analysis for Dimensionality and Complexity Reduction -- 2.5 Survival Prediction and Model Selection -- 2.6 Protein Complex Similarity -- 3 Industry 4.0 -- 3.1 Keynote on Industry 4.0 -- 3.2 Quality Assurance in Interlinked Manufacturing Processes -- 3.3 Label Proportion Learning -- 3.4 Simulation and Machine Learning -- 3.5 High-Precision Wireless Localization -- 3.6 Indoor Photovoltaic Energy Harvesting -- 3.7 Micro-UAV Swarm Testbed for Indoor Applications -- 4 Smart City and Traffic -- 4.1 Inner-City Traffic Flow Prediction with Sparse Sensors -- 4.2 Privacy-Preserving Detection of Persons and Classification of Vehicle Flows -- 4.3 Green Networking and Resource Constrained Clients for Smart Cities -- 4.4 Vehicle to Vehicle Communications: Machine Learning-Enabled Predictive Routing -- 4.5 Modelling of Hybrid Vehicular Traffic with Extended Cellular Automata -- 4.6 Embedded Crowdsensing for Pavement Monitoring and its Incentive Mechanisms -- 5 Communication Networks -- 5.1 Capacity Analysis of IoT Networks in the Unlicensed Spectrum -- 5.2 Resource-Efficient Vehicle-to-Cloud Communications -- 5.3 Mobile-Data Network Analytics Highly Reliable Networks -- 5.4 Machine Learning-Enabled 5G Network Slicing -- 5.5 Potential of Millimeter Wave Communications -- 6 Privacy -- 6.1 Keynote: Construction of Inference-Proof Agent Interactions -- Bibliography -- Index -- List of Contributors
Record Nr. UNINA-9910774815903321
Berlin ; ; Boston : , : De Gruyter, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui