Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
2017 Eighth International Green and Sustainable Computing Conference : 23-25 October 2017, Orlando, FL, USA / / IEEE Computer Society
| 2017 Eighth International Green and Sustainable Computing Conference : 23-25 October 2017, Orlando, FL, USA / / IEEE Computer Society |
| Pubbl/distr/stampa | Piscataway, New Jersey : , : Institute of Electrical and Electronics Engineers, , 2017 |
| Descrizione fisica | 1 online resource (48 pages) |
| Disciplina | 004 |
| Soggetto topico |
Computer systems - Energy conservation
Information technology - Environmental aspects Green technology |
| ISBN | 1-5386-3470-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996279524603316 |
| Piscataway, New Jersey : , : Institute of Electrical and Electronics Engineers, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
2017 Eighth International Green and Sustainable Computing Conference : 23-25 October 2017, Orlando, FL, USA / / IEEE Computer Society
| 2017 Eighth International Green and Sustainable Computing Conference : 23-25 October 2017, Orlando, FL, USA / / IEEE Computer Society |
| Pubbl/distr/stampa | Piscataway, New Jersey : , : Institute of Electrical and Electronics Engineers, , 2017 |
| Descrizione fisica | 1 online resource (48 pages) |
| Disciplina | 004 |
| Soggetto topico |
Computer systems - Energy conservation
Information technology - Environmental aspects Green technology |
| ISBN | 1-5386-3470-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910265159803321 |
| Piscataway, New Jersey : , : Institute of Electrical and Electronics Engineers, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Green computing and predictive analytics for healthcare / / edited by Sourav Banerjee, Chinmay Chakraborty, Kousik Dasgupta
| Green computing and predictive analytics for healthcare / / edited by Sourav Banerjee, Chinmay Chakraborty, Kousik Dasgupta |
| Edizione | [First edition] |
| Pubbl/distr/stampa | Boca Raton : , : Chapman & Hall/CRC, , 2021 |
| Descrizione fisica | 1 online resource : portraits |
| Disciplina | 362.10285 |
| Soggetto topico |
Medical care - Data processing
Computer systems - Energy conservation |
| ISBN |
1-000-22394-9
1-000-22400-7 0-429-31722-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Half Title -- Title Page -- Copyright Page -- Table of Contents -- Preface -- About the Editors -- List of Contributors -- Chapter 1 Healthcare Data Monitoring under Internet of Things -- 1.1 Introduction -- 1.1.1 Healthcare Data - Efficient Storage of Big Data -- 1.2 Digitization of Healthcare-Oriented Big Data -- 1.3 Healthcare - IoT and Mobile Health -- 1.4 Management of Big Data -- 1.4.1 Electronic Medical Record (EMR) or Electronic Health Record (EHR) -- 1.4.2 Healthcare Analytics -- 1.5 Medical Data Analysis and Disease Predictions through ML -- 1.6 Applications of Big Data in the Medical Field -- 1.7 Analytics of Medical Data in the Mercantile Platform -- 1.8 Related Work -- 1.9 Challenges and Constraints Related to Healthcare-Based Big Data Concepts (Including Privacy and Security Issue) -- 1.10 Conclusion and Future Trends -- References -- Chapter 2 A Framework for Emergency Remote Care and Monitoring Using Internet of Things -- 2.1 Introduction -- 2.2 The IoT Architecture and Applications -- 2.2.1 Stage 1 (Sensors/Actuators) -- 2.2.2 Stage 2 (Data Acquisition Systems) -- 2.2.3 Stage 3 (Edge Analytics) -- 2.2.4 Stage 4 (Cloud Analytics) -- 2.3 Literature Survey -- 2.4 A Proposed Framework for Emergency Remote Care and Monitoring Using Internet of Things -- 2.4.1 Parameters for Prediction -- 2.5 Proposed Work -- 2.6 Results and Discussion -- 2.7 Conclusion and Future Work -- References -- Chapter 3 Big Data Analytics and K-Means Clustering -- 3.1 Introduction -- 3.2 Big Data -- 3.3 Predictive Analytics -- 3.4 Predictive Modeling -- 3.5 MapReduce Abstraction -- 3.6 Resilient Distributed Datasets (RDDs) -- 3.7 Computational Phenotyping -- 3.8 Clustering -- 3.9 Medicinal Oncology -- 3.10 Dimensionality Reduction -- 3.11 Patient Similarity -- 3.12 Distance Metric Learning -- 3.13 Graph-Based Similarity Learning.
3.14 Clustering Challenges of Big Data -- 3.15 Algorithms for Large Datasets in Clustering -- 3.16 Privacy and Security -- 3.17 Various Approaches for Predictive Analytics -- 3.18 Why Predictive Analytics and Big Data for Electronic Health Records? -- 3.19 K-Means Clustering for Analysis of EHR -- 3.20 K-Means for Very Large-Scale Dataset -- 3.20.1 Tools and Applications in the Healthcare System -- 3.20.2 Application of Big Data in Healthcare -- 3.20.3 K-Means Clustering -- 3.21 Partitioning Around Medoids (PAM) -- 3.22 Hierarchical -- 3.23 Density-Based Spatial Bunching of Applications with Noise (DBSCAN) -- 3.24 Compatibility Issues -- 3.25 Different Solutions, Supplementary Tasks? -- 3.26 Priorities Engagement toward Analytics -- 3.27 Paid, Free or Open Source Vendors? -- 3.28 Data Clustering Strategy -- 3.29 The Brilliant Future of Big Data in Healthcare -- 3.30 Fueling the Big Data Healthcare Revolution -- 3.31 Conclusion -- References -- Chapter 4 Machine Learning-Based Rapid Prediction of Sudden Cardiac Death (SCD) Using Precise Statistical Features of Heart Rate Variability for Single Lead ECG Signal -- 4.1 Introduction -- 4.2 Literature Survey -- 4.3 Nature of ECG Signal -- 4.4 Matters and Methodology -- 4.4.1 Processing and Analysis of ECG Signal -- 4.4.2 Feature Extraction -- 4.4.3 Algorithm for Prediction of SCD -- 4.4.4 Classification -- 4.4.4.1 Logistic Regression -- 4.4.4.2 Support Vector Machine -- 4.5 Results and Discussion -- 4.6 Conclusion -- References -- Chapter 5 Computer Vision for Brain Tissue Segmentation -- 5.1 Introduction -- 5.2 Materials and Methods -- 5.2.1 Magnetic Resonance Imaging (MRI) -- 5.2.2 Segmentation Methods for Brain Images -- 5.2.3 Clustering Techniques -- 5.2.4 Fuzzy Clustering Method for Brain Image Segmentation -- 5.2.4.1 Fuzzy C-Means Clustering (FCM) -- 5.2.4.2 Fuzzy Local Information C-Means (FLICM). 5.2.4.3 Reformulated Fuzzy Information C-Means (RFLICM) -- 5.2.5 Convolution Neural Network -- 5.3 Experimental Outcomes -- 5.4 Conclusion -- References -- Chapter 6 A Study on Energy-Efficient and Green IoT for Healthcare Applications -- 6.1 Introduction -- 6.1.1 Emerging Technologies, Challenges and Issues in IoT -- 6.1.1.1 Emerging Technologies in IoT -- 6.1.1.2 Challenges and Issues in IoT -- 6.1.2 Application of IoT -- 6.1.2.1 Applications, Features and Products of IoT -- 6.1.2.2 Smart Homes -- 6.1.2.3 Wearable Technology -- 6.1.2.4 Smart City -- 6.1.2.5 Smart Grid -- 6.1.2.6 Smart Industries -- 6.1.2.7 Smart Traffic -- 6.1.2.8 Smart Healthcare -- 6.1.2.9 Smart Retail -- 6.1.2.10 Smart Supply Chain -- 6.1.2.11 Smart Agricultural -- 6.2 Green Internet of Things -- 6.2.1 Emerging Technologies, Challenges and Issues in Green IoT -- 6.2.2 Applications of Green IoT -- 6.2.2.1 Smart Green Cities -- 6.2.2.2 Smart Green Home -- 6.2.2.3 Smart Green Healthcare -- 6.2.2.4 Smart Green Grid -- 6.2.2.5 Smart Agriculture -- 6.3 Energy Efficiency in WBAN for IoT -- 6.3.1 Introduction -- 6.3.2 Energy Efficient Protocols -- 6.3.3 IEEE 802.15.4 Superframe Structure -- 6.3.3.1 Description of IEEE 802.15.4 MAC Protocol -- 6.4 Conclusion -- References -- Chapter 7 Cyber Security in Terms of IoT System and Blockchain Technologies in E-Healthcare Systems -- 7.1 Introduction -- 7.2 The IoT Device Life-Cycle -- 7.2.1 Introduction -- 7.2.2 Explanation of the Different Stages in the Life-Cycle -- 7.2.2.1 Design -- 7.2.2.2 Research and Development -- 7.2.2.3 Integration -- 7.2.2.4 Operation and Maintenance -- 7.2.2.5 Disposal -- 7.2.3 Summary -- 7.3 Aspects of Interoperability -- 7.3.1 Introduction -- 7.3.2 Discussion of Standards regarding Interoperability -- 7.3.2.1 IPSO (IP Smart Object) Alliance). 7.3.2.2 ETSI (European Telecommunication Standard Institute) Standardization -- 7.3.2.3 OIC (Open Interconnect Consortium) -- 7.3.3 Strength of Interoperability -- 7.3.4 Summary -- 7.4 Privacy Preservation with Trust and Authentication -- 7.4.1 Introduction -- 7.4.2 Different Aspects of Privacy Preservation with Discussion of Frameworks -- 7.4.2.1 Privacy -- 7.4.2.2 Privacy Framework -- 7.4.3 Trust: Its Properties and Objectives with Proper Management -- 7.4.3.1 Trust Properties -- 7.4.3.2 An IoT Trust Management -- 7.4.4 Authentication -- 7.4.4.1 Authentication Model Depending on Blockchain -- 7.4.5 Summary -- 7.5 Vulnerabilities, Attacks and Countermeasures in the Light of Security Engineering in IoT -- 7.5.1 Introduction -- 7.5.2 Information Assurance -- 7.5.3 Vulnerabilities -- 7.5.4 Attacks -- 7.5.5 Fault Tree and Attack Tree -- 7.5.5.1 Attack Tree -- 7.5.5.2 Fault Tree -- 7.5.5.3 Differences and Collaboration of Fault and Attack Tree -- 7.5.6 Countermeasures -- 7.6 Cryptographical Perspective of IoT Security -- 7.6.1 Introduction -- 7.6.2 Primitives of Cryptography Keeping IoT in Mind -- 7.6.2.1 Symmetric Key Cryptography -- 7.6.2.2 Public Key Encryption -- 7.6.2.3 Digital Signature -- 7.6.2.4 Hashes -- 7.7 Cloud Security -- 7.7.1 IoT Device Security Threat from Cloud Usage -- 7.7.2 Cloud IoT Security Control -- 7.7.3 Framework and Architecture -- 7.7.3.1 Fog Computing-Based Model -- 7.7.4 New Scope -- 7.7.5 Summary -- 7.8 Blockchain Technology -- 7.8.1 Introduction -- 7.8.2 Structure -- 7.8.3 Security Challenges and Probable Remedies -- 7.8.3.1 Challenges -- 7.8.3.2 A Remedy Model Using Blockchain Technology -- 7.9 Social Awareness -- 7.9.1 Introduction -- 7.9.2 Opportunistic IoT -- 7.9.3 Concern -- 7.10 Future Scope and Conclusion -- References -- Chapter 8 Domestic Medical Tourism for National Healthcare Systems -- 8.1 Introduction. 8.2 Medical Tourism -- 8.3 Important Factors behind the Growth of Medical Tourism -- 8.4 Medical Tourism: Emerging Trends -- 8.5 Healthcare Market Size -- 8.6 Medical Tourism Industry Perspective -- 8.7 Domestic Medical Tourism -- 8.8 Methodology -- 8.8.1 Results -- 8.8.2 Discussion of Results -- 8.9 Conclusion -- References -- Chapter 9 Study on Edge Computing Using Machine Learning Approaches in IoT Framework -- 9.1 Introduction -- 9.2 Review of IoT and Edge Computing -- 9.2.1 Internet of Things -- 9.2.1.1 Communication between Machines -- 9.2.1.2 Communication within Machine and Cloud -- 9.2.1.3 Machine-to-Gateway Communication -- 9.2.2 IoT Components -- 9.2.2.1 Sensors/Devices -- 9.2.2.2 IoT Gateways -- 9.2.2.3 Cloud-Based Core Network -- 9.2.3 Edge Computing -- 9.3 Edge Computing Paradigm in a Cloud Environment -- 9.3.1 Collection Proxy Technology -- 9.3.2 Data Validation -- 9.3.3 Annotation of Metadata -- 9.3.4 Security -- 9.3.5 Virtual IoT Device -- 9.3.6 Actuation -- 9.4 Edge Computing for Architecture -- 9.4.1 Front Structure -- 9.4.2 Near Structure -- 9.4.3 Far Structure -- 9.5 IoT and Edge Technology Integration -- 9.5.1 Overview -- 9.5.2 IoT Performance Demands -- 9.5.2.1 Transmission -- 9.5.2.2 Storage -- 9.5.2.3 Computation -- 9.6 Applications of IoT -- 9.6.1 IoT-Based Industrial Applications -- 9.6.1.1 Smart Grids -- 9.6.1.2 Manufacturing Process Monitoring -- 9.6.2 Healthcare Applications of IoT -- 9.6.2.1 IoT Health-Related Service -- 9.6.2.2 Glucose-Level Monitoring -- 9.6.2.3 Blood Pressure Monitoring -- 9.7 Advantages of Edge Computing-Based IoT -- 9.7.1 Transmission -- 9.7.2 Latency/Delay -- 9.7.3 Bandwidth -- 9.7.4 Energy -- 9.7.5 Overhead -- 9.7.6 Storage -- 9.7.6.1 Storage Balancing -- 9.7.6.2 Recovery Policy -- 9.8 Edge Computing-Based IoT Challenges -- 9.8.1 System Integration -- 9.8.2 Resource Management. 9.8.3 Security and Privacy. |
| Record Nr. | UNINA-9910860842003321 |
| Boca Raton : , : Chapman & Hall/CRC, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The green computing book : tackling energey efficiency at large scale / / edited by Wu-chun Feng, Virginia Polytechnic Institute and State University, Blacksburg, USA
| The green computing book : tackling energey efficiency at large scale / / edited by Wu-chun Feng, Virginia Polytechnic Institute and State University, Blacksburg, USA |
| Pubbl/distr/stampa | Boca Raton, [Florida] : , : CRC Press, , [2014] |
| Descrizione fisica | 1 online resource (341 p.) |
| Disciplina | 628 |
| Collana | Chapman & Hall/CRC Computational Science Series |
| Soggetto topico |
Information technology - Environmental aspects
Information technology - Energy consumption Computer systems - Energy conservation Green technology |
| ISBN |
0-429-10432-4
1-4398-1987-4 |
| Classificazione | COM000000MAT021000TEC010000 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Table of Contents; Preface; Contributors; CHAPTER 1: Low-Power, Massively Parallel, Energy-Efficient Supercomputers; CHAPTER 2: Compiler-Driven Energy Efficiency; CHAPTER 3: An Adaptive Run-Time System for Improving Energy Efficiency; CHAPTER 4: Energy-Efficient Multithreading through Run-Time Adaptation; CHAPTER 5: Exploring Trade-Offs between Energy Savings and Reliability in Storage Systems; CHAPTER 6: Cross-Layer Power Management; CHAPTER 7: Energy-Efficient Virtualized Systems; CHAPTER 9: Implications of Recent Trends in Performance, Costs, and Energy Use for Servers
Back Cover |
| Record Nr. | UNINA-9910787850103321 |
| Boca Raton, [Florida] : , : CRC Press, , [2014] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The green computing book : tackling energey efficiency at large scale / / edited by Wu-chun Feng, Virginia Polytechnic Institute and State University, Blacksburg, USA
| The green computing book : tackling energey efficiency at large scale / / edited by Wu-chun Feng, Virginia Polytechnic Institute and State University, Blacksburg, USA |
| Pubbl/distr/stampa | Boca Raton, [Florida] : , : CRC Press, , [2014] |
| Descrizione fisica | 1 online resource (341 p.) |
| Disciplina | 628 |
| Collana | Chapman & Hall/CRC Computational Science Series |
| Soggetto topico |
Information technology - Environmental aspects
Information technology - Energy consumption Computer systems - Energy conservation Green technology |
| ISBN |
0-429-10432-4
1-4398-1987-4 |
| Classificazione | COM000000MAT021000TEC010000 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Table of Contents; Preface; Contributors; CHAPTER 1: Low-Power, Massively Parallel, Energy-Efficient Supercomputers; CHAPTER 2: Compiler-Driven Energy Efficiency; CHAPTER 3: An Adaptive Run-Time System for Improving Energy Efficiency; CHAPTER 4: Energy-Efficient Multithreading through Run-Time Adaptation; CHAPTER 5: Exploring Trade-Offs between Energy Savings and Reliability in Storage Systems; CHAPTER 6: Cross-Layer Power Management; CHAPTER 7: Energy-Efficient Virtualized Systems; CHAPTER 9: Implications of Recent Trends in Performance, Costs, and Energy Use for Servers
Back Cover |
| Record Nr. | UNINA-9910800186503321 |
| Boca Raton, [Florida] : , : CRC Press, , [2014] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The green computing book : tackling energey efficiency at large scale / / edited by Wu-chun Feng, Virginia Polytechnic Institute and State University, Blacksburg, USA
| The green computing book : tackling energey efficiency at large scale / / edited by Wu-chun Feng, Virginia Polytechnic Institute and State University, Blacksburg, USA |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Boca Raton, [Florida] : , : CRC Press, , [2014] |
| Descrizione fisica | 1 online resource (341 p.) |
| Disciplina | 628 |
| Collana | Chapman & Hall/CRC Computational Science Series |
| Soggetto topico |
Information technology - Environmental aspects
Information technology - Energy consumption Computer systems - Energy conservation Green technology |
| ISBN |
1-04-005970-8
0-429-10432-4 1-4398-1987-4 |
| Classificazione | COM000000MAT021000TEC010000 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Table of Contents; Preface; Contributors; CHAPTER 1: Low-Power, Massively Parallel, Energy-Efficient Supercomputers; CHAPTER 2: Compiler-Driven Energy Efficiency; CHAPTER 3: An Adaptive Run-Time System for Improving Energy Efficiency; CHAPTER 4: Energy-Efficient Multithreading through Run-Time Adaptation; CHAPTER 5: Exploring Trade-Offs between Energy Savings and Reliability in Storage Systems; CHAPTER 6: Cross-Layer Power Management; CHAPTER 7: Energy-Efficient Virtualized Systems; CHAPTER 9: Implications of Recent Trends in Performance, Costs, and Energy Use for Servers
Back Cover |
| Record Nr. | UNINA-9910823473903321 |
| Boca Raton, [Florida] : , : CRC Press, , [2014] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Green computing in smart cities : simulation and techniques / / Balamurugan Balusamy, Naveen Chilamkurti, Seifedine Kadry, editors
| Green computing in smart cities : simulation and techniques / / Balamurugan Balusamy, Naveen Chilamkurti, Seifedine Kadry, editors |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (X, 206 p. 80 illus., 64 illus. in color.) |
| Disciplina | 004.0286 |
| Collana | Green energy and technology |
| Soggetto topico |
Computer systems - Energy conservation
Information technology - Environmental aspects Data processing service centers - Energy conservation |
| ISBN | 3-030-48141-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Smart cities: redefining urban energy -- From smart energy to smart cities -- Energy management and planning in smart cities -- Energy technologies: Recommendations for future smart cities -- Green Technology for Smart Cities -- Optimal Renewable Energy Systems for Smart Cities -- Smart Parking: Green IoT for Smart City -- Green Internet of Things for Smart Cities -- Design of Cloud-Based Green IoT Architecture for Smart Cities -- Green-energy, water-autonomous greenhouse system -- Energy-Efficient Device-to-Device Communications for Green Smart Cities -- Greening the Smart Cities: Energy-Efficient Massive Content Delivery via D2D Communications -- Green Communications in Smart City -- Smart City Community Green Computing with Cyber Security -- Smart Cities: Environmental Challenges and Green Computing -- Ubiquitous Green Computing Techniques for High Demand Applications in Smart Environments -- Green Computing and Communications -- Toward Big Data in Green City -- How Green Building In Smart Cities Attaining Energy Efficiency? |
| Record Nr. | UNINA-9910484891103321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
ICECCS 2014 : proceedings : 2014 3rd International Conference on Eco-friendly Computing and Communication Systems : 18-21 December, 2014, Mangalore, Karnataka, India
| ICECCS 2014 : proceedings : 2014 3rd International Conference on Eco-friendly Computing and Communication Systems : 18-21 December, 2014, Mangalore, Karnataka, India |
| Pubbl/distr/stampa | New York : , : IEEE, , 2015 |
| Descrizione fisica | 1 online resource (372 pages) |
| Soggetto topico |
Green technology
Computer systems - Energy conservation Sustainable development - Data processing |
| ISBN | 1-4799-7002-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996281141203316 |
| New York : , : IEEE, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
ICECCS 2014 : proceedings : 2014 3rd International Conference on Eco-friendly Computing and Communication Systems : 18-21 December, 2014, Mangalore, Karnataka, India
| ICECCS 2014 : proceedings : 2014 3rd International Conference on Eco-friendly Computing and Communication Systems : 18-21 December, 2014, Mangalore, Karnataka, India |
| Pubbl/distr/stampa | New York : , : IEEE, , 2015 |
| Descrizione fisica | 1 online resource (372 pages) |
| Soggetto topico |
Green technology
Computer systems - Energy conservation Sustainable development - Data processing |
| ISBN | 1-4799-7002-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910131604303321 |
| New York : , : IEEE, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
IGSC 2018 : 2018 ninth International Green and Sustainable Computing Conference : Pittsburgh, Pennsylvania, USA, 22 October -24 October, 2018 / / Institute of Electrical and Electronics Engineers
| IGSC 2018 : 2018 ninth International Green and Sustainable Computing Conference : Pittsburgh, Pennsylvania, USA, 22 October -24 October, 2018 / / Institute of Electrical and Electronics Engineers |
| Pubbl/distr/stampa | Piscataway, New Jersey : , : Institute of Electrical and Electronics Engineers, , 2018 |
| Descrizione fisica | 1 online resource (117 pages) |
| Disciplina | 004 |
| Soggetto topico |
Information technology - Environmental aspects
Computer systems - Energy conservation |
| ISBN | 1-5386-7466-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910330351803321 |
| Piscataway, New Jersey : , : Institute of Electrical and Electronics Engineers, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
