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Biblioteca

MARC Lista (tabellare)
Backscattering and RF sensing for future wireless communication / / editors, Qammer H. Abbasi [et al.]
Backscattering and RF sensing for future wireless communication / / editors, Qammer H. Abbasi [et al.]
Pubbl/distr/stampa Hoboken, NJ : , : Wiley, , [2021]
Descrizione fisica 1 online resource (227 pages)
Disciplina 621.3824
Soggetto topico Backscatter communication
Radio resource management (Wireless communications)
Soggetto genere / forma Electronic books.
ISBN 1-119-69568-6
1-119-69566-X
1-119-69572-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910554828703321
Hoboken, NJ : , : Wiley, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Backscattering and RF sensing for future wireless communication / / editors, Qammer H. Abbasi [et al.]
Backscattering and RF sensing for future wireless communication / / editors, Qammer H. Abbasi [et al.]
Pubbl/distr/stampa Hoboken, NJ : , : Wiley, , [2021]
Descrizione fisica 1 online resource (227 pages)
Disciplina 621.3824
Soggetto topico Backscatter communication
Radio resource management (Wireless communications)
ISBN 1-119-69568-6
1-119-69566-X
1-119-69572-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intelligent reflective surfaces : state of the art / Jalil ur Rehman Kazim, Hasan T. Abbas, Muhammad A. Imran, Qammer H. Abbasi.
Record Nr. UNINA-9910829950603321
Hoboken, NJ : , : Wiley, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Enabling 5G communication systems to support vertical industries / / edited by Muhammad Ali Imran, Yusuf Abdulrahman Sambo, Qammer H. Abbasi
Enabling 5G communication systems to support vertical industries / / edited by Muhammad Ali Imran, Yusuf Abdulrahman Sambo, Qammer H. Abbasi
Autore Imran Muhammad Ali
Pubbl/distr/stampa Hoboken, New Jersey ; ; Chichester, England : , : Wiley : , : IEEE Press, , [2019]
Descrizione fisica 1 online resource (289 pages)
Disciplina 621.38456
Collana THEi Wiley ebooks.
Soggetto topico 5G mobile communication systems
Marketing, Vertical
Business enterprises - Computer networks
ISBN 1-119-51555-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910555176403321
Imran Muhammad Ali  
Hoboken, New Jersey ; ; Chichester, England : , : Wiley : , : IEEE Press, , [2019]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Enabling 5G communication systems to support vertical industries / / edited by Muhammad Ali Imran, Yusuf Abdulrahman Sambo, Qammer H. Abbasi
Enabling 5G communication systems to support vertical industries / / edited by Muhammad Ali Imran, Yusuf Abdulrahman Sambo, Qammer H. Abbasi
Autore Imran Muhammad Ali
Pubbl/distr/stampa Hoboken, New Jersey ; ; Chichester, England : , : Wiley : , : IEEE Press, , [2019]
Descrizione fisica 1 online resource (289 pages)
Disciplina 621.38456
Collana THEi Wiley ebooks.
Soggetto topico 5G mobile communication systems
Marketing, Vertical
Business enterprises - Computer networks
ISBN 1-119-51555-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910824461103321
Imran Muhammad Ali  
Hoboken, New Jersey ; ; Chichester, England : , : Wiley : , : IEEE Press, , [2019]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Engineering and technology for healthcare / / edited by Muhammad Ali Imran, Rami Ghannam, Qammer H. Abbasi
Engineering and technology for healthcare / / edited by Muhammad Ali Imran, Rami Ghannam, Qammer H. Abbasi
Pubbl/distr/stampa Hoboken, New Jersey : , : IEEE Press : , : Wiley, , [2020]
Descrizione fisica 1 PDF
Disciplina 610.28
Soggetto topico Biomedical engineering
ISBN 1-119-64428-3
1-119-64422-4
1-119-64431-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Contributors -- 1.1. Introduction ix -- 1.2. Bibliography xv -- 2. Maximising the value of engineering and technology research in healthcare: development-focused health technology assessment -- 2.1. Introduction -- 2.2. What is HTA? -- 2.3. What is development-focused HTA? -- 2.4. Illustration of features of development-focused HTA? -- 2.4.1. Use-focused HTA? -- 2.4.2. Development-focused HTA? -- 2.5. Activities of development-focused HTA? -- 2.6. Analytical methods of development-focused HTA -- 2.6.1. Clinical value assessment -- 2.6.2. Economic value assessment -- 2.6.3. Evidence generation -- 2.7. What are the challenges in the development and assessment of medical devices? -- 2.7.1. What are the medical devices? -- 2.7.2. Challenges common to all medical devices -- 2.7.2.1. Licencing and regulation -- 2.7.2.2. Adoption -- 2.7.2.3. Evidence -- 2.7.3. Challenges specific to some categories of device -- 2.7.3.1. Learning curve -- 2.7.3.2. Short lifespan and incremental improvement -- 2.7.3.3. Workflow -- 2.7.3.4. Indirect health benefit -- 2.7.3.5. Behavioural and other contextual factors -- 2.7.3.6. Budgetary challenge -- 2.8. The contribution of DF-HTA in the development and translation of medical devices -- 2.8.1. Case study 1 - Identifying and confirming needs -- 2.8.2. Case study 2 - What difference could this device make? -- 2.8.3. Case study 3 - Which research project has the most potential? -- 2.8.4. Case study 4 - What is the required performance to deliver clinical utility? -- 2.8.5. Case study 5 - What are the key param-eters for evidence generation? -- 2.9. Conclusion -- 3. Contactless Radar Sensing for health monitoring -- 3.3.1. Introduction: healthcare provision and radar technology -- 3.3.2. Radar and Radar Data Fundamentals -- 3.3.2.1. Principles of radar systems -- 3.3.2.2. Principles of radar signal processing for health applications -- 3.3.3. Principles of machine learning applied to radar data -- 3.3.4. Complementary approaches: passive radar and channel state information sensing.
3.4. Radar technology in use for healthcare -- 3.4.1. Activities recognition and fall detection -- 3.4.2.Gait monitoring -- 3.4.3. Vital signs and sleep monitoring -- 3.5. Conclusion and outstanding challenges -- 3.6. Future Trends -- 4. Pervasive Sensing: Macro to Nanoscale -- 4.1 Introduction -- 4.2. The anatomy of a human skin -- 4.3. Chracteristic of human tissue -- 4.4 Tissue Sample Preparation -- 4.5. Measurement Apparatus -- 4.6. Simulating the human skin -- 4.6.1. Human body channel modelling -- 4.7. Networking and Communication Mech-anisms for Body-Centric WirelessNano-Networks -- 4.8. Concluding Remarks -- 5. Bio integrated Implantable Brain Devices -- 5.1. Background -- 5.2 Neural Device Interfaces -- 5.3. Implant Tissue Biointegration -- 5.4. MRI Compatibility of the NeuralDevices -- 5.5. Conclusion -- 6. Machine Learning for Decision Making in Healthcare -- 6.1. Introduction -- 6.2. Data Description -- 6.3. Proposed Methodology -- 6.3.1. Data collection -- 6.3.2. Window size selection -- 6.3.3. Feature Extraction -- 6.3.4. Feature Selection -- 6.3.5. Implementation of Machine learning Models -- 6.3.6. Model Evaluation -- 6.4. Results -- 6.5. Analysis and Discussion -- 6.5.1. Impact of Postures -- 6.5.2. Impact of Windows Size -- 6.5.2. Impact of Feature combination -- 6.5.3. Impact of Machine Learning algorithms -- 6.6. Conclusion -- 7. Information Retrieval from Electronic Health Records -- 7.1. Introduction -- 7.2. Methodology -- 7.2.1. Parallel LSI (PLSI) -- 7.2.2. Distributed LSI (DLSI) -- 7.3. Results and Analysis -- 7.4 Conclusion -- 8. Energy Harvesting for Wearable and Portable Devices -- 8.1. Introduction -- 8.2. Energy Harvesting Techniques -- 8.2.1. Photovoltaics -- 8.2.2. Piezoelectric Energy Harvesting -- 8.2.3. Thermal Energy Harvesting -- 8.2.3.1. Last Trends -- 8.2.4. RF Energy Harvesting -- 8.3. Conclusion -- 9. Wireless control for life-critical actions -- 9.1. Introduction -- 9.2. Wireless Control for Healthcare -- 9.3. Technical Requirements.
9.3.1. Ultra-Reliability -- 9.3.2. Low Latency -- 9.3.3. Security and Privacy -- 9.3.4. Edge Artificial Intelligence -- 9.4. Design Aspects -- 9.4.1. Independent Design -- 9.4.2. Co-Design -- 9.5. Co-Design System Model -- 9.5.1. Control Fusion -- 9.5.2. Performance Evaluation Criterion -- 9.5.2.1. Control Performance -- 9.5.2.2. Communication Performance -- 9.5.3. Effects of Different QoS -- 9.5.4. Simulation Results -- 9.6. Conclusion -- 10. ROLE OF D2D COMMUNICATIONS INMOBILE HEALTH APPLICATIONS: SECURITY THREATS AND REQUIREMENTS -- 10.1. Introduction -- 10.2. D2D Scenarios for Mobile Health Applications -- 10.3. D2D Security Requirements and Standardisation -- 10.3.1. Security Issues on Configuration -- 10.3.1.1. Configuration of the ProSe enabled UE -- 10.3.1.2. Security Issues on Device Discovery -- 10.3.1.2.1. Direct Request and Response Discovery -- 10.3.1.2.2. Open Direct Discovery -- 10.3.1.2.3. Restricted Directory -- 10.3.1.2.4. Registration in network-based ProSe Discovery -- 10.3.2. Security Issues on One-to-Many Communications -- 10.3.2.1. One-to-many communications between UEs -- 10.3.2.2. Key distribution for group communications -- 10.3.3. Security Issues on One-to-One Communication -- 10.3.3.1. One-to-one ProSe direct communication -- 10.3.3.2. One-to-one ProSe direct communication -- 10.3.4. Security Issues on ProSe Relays -- 10.3.4.1. Maintaining 3GPP communication security through relay -- 10.3.4.2. UE-Network relay -- 10.3.4.3. UE-to-UE relay -- 10.4. Existing Solutions -- 10.4.1. Key Management -- 10.4.2. Routing -- 10.4.3. Social Trust and social ties -- 10.4.4. Access Control -- 10.4.5. Physical Layer Security -- 10.4.6. Network Coding -- 10.5. Conclusion -- 11. Automated diagnosis of skin cancer for healthcare: Highlights and Procedures -- 11.1. Introduction -- 11.2. Framework of Computer-aided Skin Cancer Classification Systems -- 11.2.1. Image Acquisition -- 11.2.2. Image Pre-processing -- 11.2.2.1. Color Contrast Enhancement -- 11.2.2.2. Artificial Removal.
11.2.3. Image Segmentation -- 11.2.3.1. Thresholding-based Segmentation -- 11.2.3.2. Edge-based Segmentation -- 11.2.3.3. Region-based Segmentation -- 11.2.3.4. Active contours-based Segmentation -- 11.2.3.5. Artificial Intelligence-based Segmentation -- 11.2.4. Feature Extraction -- 11.2.4.1. Color-based Features -- 11.2.4.2. Dimensional Features -- 11.2.4.3. Textual-based Features -- 11.2.4.4. Dermoscopic Rules and Methods -- 11.2.4.4.1. ABCD Rule -- 11.2.4.4.2 Menzies Method -- 11.2.4.4.3 7-Point Checklist -- 11.2.5. Feature Selection -- 11.2.6. Classification -- 11.2.7. Classification Performance Evaluation -- 11.3. Conclusion -- 12. Conclusion.
Record Nr. UNINA-9910555268403321
Hoboken, New Jersey : , : IEEE Press : , : Wiley, , [2020]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Engineering and technology for healthcare / / edited by Muhammad Ali Imran, Rami Ghannam, Qammer H. Abbasi
Engineering and technology for healthcare / / edited by Muhammad Ali Imran, Rami Ghannam, Qammer H. Abbasi
Pubbl/distr/stampa Hoboken, New Jersey : , : IEEE Press : , : Wiley, , [2020]
Descrizione fisica 1 PDF
Disciplina 610.28
Soggetto topico Biomedical engineering
ISBN 1-119-64428-3
1-119-64422-4
1-119-64431-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Contributors -- 1.1. Introduction ix -- 1.2. Bibliography xv -- 2. Maximising the value of engineering and technology research in healthcare: development-focused health technology assessment -- 2.1. Introduction -- 2.2. What is HTA? -- 2.3. What is development-focused HTA? -- 2.4. Illustration of features of development-focused HTA? -- 2.4.1. Use-focused HTA? -- 2.4.2. Development-focused HTA? -- 2.5. Activities of development-focused HTA? -- 2.6. Analytical methods of development-focused HTA -- 2.6.1. Clinical value assessment -- 2.6.2. Economic value assessment -- 2.6.3. Evidence generation -- 2.7. What are the challenges in the development and assessment of medical devices? -- 2.7.1. What are the medical devices? -- 2.7.2. Challenges common to all medical devices -- 2.7.2.1. Licencing and regulation -- 2.7.2.2. Adoption -- 2.7.2.3. Evidence -- 2.7.3. Challenges specific to some categories of device -- 2.7.3.1. Learning curve -- 2.7.3.2. Short lifespan and incremental improvement -- 2.7.3.3. Workflow -- 2.7.3.4. Indirect health benefit -- 2.7.3.5. Behavioural and other contextual factors -- 2.7.3.6. Budgetary challenge -- 2.8. The contribution of DF-HTA in the development and translation of medical devices -- 2.8.1. Case study 1 - Identifying and confirming needs -- 2.8.2. Case study 2 - What difference could this device make? -- 2.8.3. Case study 3 - Which research project has the most potential? -- 2.8.4. Case study 4 - What is the required performance to deliver clinical utility? -- 2.8.5. Case study 5 - What are the key param-eters for evidence generation? -- 2.9. Conclusion -- 3. Contactless Radar Sensing for health monitoring -- 3.3.1. Introduction: healthcare provision and radar technology -- 3.3.2. Radar and Radar Data Fundamentals -- 3.3.2.1. Principles of radar systems -- 3.3.2.2. Principles of radar signal processing for health applications -- 3.3.3. Principles of machine learning applied to radar data -- 3.3.4. Complementary approaches: passive radar and channel state information sensing.
3.4. Radar technology in use for healthcare -- 3.4.1. Activities recognition and fall detection -- 3.4.2.Gait monitoring -- 3.4.3. Vital signs and sleep monitoring -- 3.5. Conclusion and outstanding challenges -- 3.6. Future Trends -- 4. Pervasive Sensing: Macro to Nanoscale -- 4.1 Introduction -- 4.2. The anatomy of a human skin -- 4.3. Chracteristic of human tissue -- 4.4 Tissue Sample Preparation -- 4.5. Measurement Apparatus -- 4.6. Simulating the human skin -- 4.6.1. Human body channel modelling -- 4.7. Networking and Communication Mech-anisms for Body-Centric WirelessNano-Networks -- 4.8. Concluding Remarks -- 5. Bio integrated Implantable Brain Devices -- 5.1. Background -- 5.2 Neural Device Interfaces -- 5.3. Implant Tissue Biointegration -- 5.4. MRI Compatibility of the NeuralDevices -- 5.5. Conclusion -- 6. Machine Learning for Decision Making in Healthcare -- 6.1. Introduction -- 6.2. Data Description -- 6.3. Proposed Methodology -- 6.3.1. Data collection -- 6.3.2. Window size selection -- 6.3.3. Feature Extraction -- 6.3.4. Feature Selection -- 6.3.5. Implementation of Machine learning Models -- 6.3.6. Model Evaluation -- 6.4. Results -- 6.5. Analysis and Discussion -- 6.5.1. Impact of Postures -- 6.5.2. Impact of Windows Size -- 6.5.2. Impact of Feature combination -- 6.5.3. Impact of Machine Learning algorithms -- 6.6. Conclusion -- 7. Information Retrieval from Electronic Health Records -- 7.1. Introduction -- 7.2. Methodology -- 7.2.1. Parallel LSI (PLSI) -- 7.2.2. Distributed LSI (DLSI) -- 7.3. Results and Analysis -- 7.4 Conclusion -- 8. Energy Harvesting for Wearable and Portable Devices -- 8.1. Introduction -- 8.2. Energy Harvesting Techniques -- 8.2.1. Photovoltaics -- 8.2.2. Piezoelectric Energy Harvesting -- 8.2.3. Thermal Energy Harvesting -- 8.2.3.1. Last Trends -- 8.2.4. RF Energy Harvesting -- 8.3. Conclusion -- 9. Wireless control for life-critical actions -- 9.1. Introduction -- 9.2. Wireless Control for Healthcare -- 9.3. Technical Requirements.
9.3.1. Ultra-Reliability -- 9.3.2. Low Latency -- 9.3.3. Security and Privacy -- 9.3.4. Edge Artificial Intelligence -- 9.4. Design Aspects -- 9.4.1. Independent Design -- 9.4.2. Co-Design -- 9.5. Co-Design System Model -- 9.5.1. Control Fusion -- 9.5.2. Performance Evaluation Criterion -- 9.5.2.1. Control Performance -- 9.5.2.2. Communication Performance -- 9.5.3. Effects of Different QoS -- 9.5.4. Simulation Results -- 9.6. Conclusion -- 10. ROLE OF D2D COMMUNICATIONS INMOBILE HEALTH APPLICATIONS: SECURITY THREATS AND REQUIREMENTS -- 10.1. Introduction -- 10.2. D2D Scenarios for Mobile Health Applications -- 10.3. D2D Security Requirements and Standardisation -- 10.3.1. Security Issues on Configuration -- 10.3.1.1. Configuration of the ProSe enabled UE -- 10.3.1.2. Security Issues on Device Discovery -- 10.3.1.2.1. Direct Request and Response Discovery -- 10.3.1.2.2. Open Direct Discovery -- 10.3.1.2.3. Restricted Directory -- 10.3.1.2.4. Registration in network-based ProSe Discovery -- 10.3.2. Security Issues on One-to-Many Communications -- 10.3.2.1. One-to-many communications between UEs -- 10.3.2.2. Key distribution for group communications -- 10.3.3. Security Issues on One-to-One Communication -- 10.3.3.1. One-to-one ProSe direct communication -- 10.3.3.2. One-to-one ProSe direct communication -- 10.3.4. Security Issues on ProSe Relays -- 10.3.4.1. Maintaining 3GPP communication security through relay -- 10.3.4.2. UE-Network relay -- 10.3.4.3. UE-to-UE relay -- 10.4. Existing Solutions -- 10.4.1. Key Management -- 10.4.2. Routing -- 10.4.3. Social Trust and social ties -- 10.4.4. Access Control -- 10.4.5. Physical Layer Security -- 10.4.6. Network Coding -- 10.5. Conclusion -- 11. Automated diagnosis of skin cancer for healthcare: Highlights and Procedures -- 11.1. Introduction -- 11.2. Framework of Computer-aided Skin Cancer Classification Systems -- 11.2.1. Image Acquisition -- 11.2.2. Image Pre-processing -- 11.2.2.1. Color Contrast Enhancement -- 11.2.2.2. Artificial Removal.
11.2.3. Image Segmentation -- 11.2.3.1. Thresholding-based Segmentation -- 11.2.3.2. Edge-based Segmentation -- 11.2.3.3. Region-based Segmentation -- 11.2.3.4. Active contours-based Segmentation -- 11.2.3.5. Artificial Intelligence-based Segmentation -- 11.2.4. Feature Extraction -- 11.2.4.1. Color-based Features -- 11.2.4.2. Dimensional Features -- 11.2.4.3. Textual-based Features -- 11.2.4.4. Dermoscopic Rules and Methods -- 11.2.4.4.1. ABCD Rule -- 11.2.4.4.2 Menzies Method -- 11.2.4.4.3 7-Point Checklist -- 11.2.5. Feature Selection -- 11.2.6. Classification -- 11.2.7. Classification Performance Evaluation -- 11.3. Conclusion -- 12. Conclusion.
Record Nr. UNINA-9910820877603321
Hoboken, New Jersey : , : IEEE Press : , : Wiley, , [2020]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Wireless automation as an enabler for the next industrial revolution / / edited by Muhammad Ali Imran, Sajid Hussain, Qammer H. Abbasi
Wireless automation as an enabler for the next industrial revolution / / edited by Muhammad Ali Imran, Sajid Hussain, Qammer H. Abbasi
Autore MUHAMMAD A. IMRAN; SAJJAD HUSSAIN; QAMMER H. ABBAS
Pubbl/distr/stampa HOBOKEN : , : JOHN WILEY, , 2019
Descrizione fisica 1 online resource (285 pages)
Disciplina 681.2
Soggetto topico Wireless sensor networks
ISBN 1-119-55262-1
1-119-55263-X
1-119-55258-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto List of Contributors xiii -- Preface xvii -- 1 Industrial Wireless Sensor Networks Overview 1 / Mohsin Raza and Huan X. Nguyen -- 1.1 Introduction 1 -- 1.2 Industry 4.0 3 -- 1.3 Industrial Wireless Sensor Networks (IWSNs) 6 -- 1.4 Applications of IWSNs 8 -- 1.4.1 Feedback Control Systems 8 -- 1.4.2 Motion and Robotics 9 -- 1.4.3 Safety Applications 9 -- 1.4.4 Environmental Monitoring 9 -- 1.4.5 Machine/Structural Health Monitoring 10 -- 1.5 Communication Topologies in IWSNs 10 -- 1.6 Research Developments and Communications Standards for Industry 11 -- 1.6.1 IEEE 802.15.4 12 -- 1.6.2 IEEE 802.15.4e 13 -- 1.6.3 Zigbee 13 -- 1.6.4 WirelessHART 14 -- 1.6.5 ISA100.11a 14 -- 1.6.6 6LoWPAN 14 -- Bibliography 15 -- 2 Life-span Extension for Sensor Networks in the Industry 19 / Metin Ozturk, Mona Jaber, and Muhammad A. Imran -- 2.1 Introduction 19 -- 2.2 Wireless Sensor Networks 21 -- 2.3 Industrial WSNs 24 -- 2.3.1 Requirements and Challenges 25 -- 2.3.2 Protocols and Standards 26 -- 2.3.3 IWSN Applications 27 -- 2.4 Life-span Extension for WSNs 28 -- 2.4.1 Energy Harvesting 29 -- 2.4.1.1 Solar Energy Harvesting 31 -- 2.4.1.2 Wind Energy Harvesting 31 -- 2.4.1.3 Radio Frequency Energy Harvesting 32 -- 2.4.1.4 Piezoelectric Energy Harvesting 32 -- 2.4.1.5 Thermal Energy Harvesting 33 -- 2.4.2 Energy Conservation 33 -- 2.4.2.1 Duty Cycling 34 -- 2.4.2.2 Data Driven Approaches 35 -- 2.4.2.3 Mobility Based Approaches 35 -- 2.4.2.4 Q Learning Assisted Energy Efficient Smart Connectivity 36 -- 2.5 Conclusion 40 -- Bibliography 41 -- 3 Multiple Access and Resource Sharing for Low Latency Critical Industrial Networks 47 / Mohsin Raza, Anas Amjad, and Sajjad Hussain -- 3.1 Introduction 47 -- 3.2 Research Developments 51 -- 3.2.1 CSMA/CA Based MAC Schemes 53 -- 3.2.2 TDMA Based MAC Schemes 53 -- 3.2.3 Multichannel MAC Schemes 54 -- 3.2.4 Priority Based MAC Schemes 55 -- 3.3 Priority Based Information Scheduling and Transmission 56 -- 3.4 Summary 61 -- Bibliography 61 -- 4 Narrowband Internet of Things (NB-IoT) for Industrial Automation 65 / Hassan Malik, Muhammad Mahtab Alam, Alar Kuusik, Yannick Le Moullec, and Sven P©Þrand.
4.1 Introduction 65 -- 4.2 Overview of NB-IoT 65 -- 4.3 NB-IoT Design Characteristics 68 -- 4.3.1 Low Device Complexity and Low Cost 68 -- 4.3.2 Coverage Enhancement (CE) 70 -- 4.3.3 Long Device Battery Lifetime 70 -- 4.3.4 Massive Device Support 71 -- 4.3.5 Deployment Flexibility 72 -- 4.3.6 Small Data Packet Transmission Support 74 -- 4.3.6.1 Control Plane CIoT EPS Optimization (CP) 74 -- 4.3.6.2 User Plane CIoT EPS Optimization (UP) 76 -- 4.3.7 Multicast Transmission Support 76 -- 4.3.8 Mobility Support 76 -- 4.4 NB-IoT Frame Structure 77 -- 4.4.1 Downlink Transmission Scheme 78 -- 4.4.1.1 Narrowband Reference Signal (NRS) 78 -- 4.4.1.2 Narrowband Primary and Secondary Synchronization Signals (NPSS and NSSS) 78 -- 4.4.1.3 Narrowband Physical Broadcast Channel (NPBCH) 79 -- 4.4.1.4 Narrowband Physical Downlink Control Channel (NPDCCH) 79 -- 4.4.1.5 Narrowband Physical Downlink Shared Channel (NPDSCH) 80 -- 4.4.2 Uplink Transmission Scheme 80 -- 4.4.2.1 Demodulation Reference Signal (DMRS) 80 -- 4.4.2.2 Narrowband Physical Random Access Channel (NPRACH) 81 -- 4.4.2.3 Narrowband Uplink Shared Channel (NPUSCH) 81 -- 4.4.3 NB-IoT Design Modification in Relation to LTE 81 -- 4.5 NB-IoT as an Enabler for Industry 4.0 81 -- 4.5.1 Process Automation 83 -- 4.5.2 HumańôMachine Interfaces 84 -- 4.5.3 Logistics and Warehousing 84 -- 4.5.4 Maintenance and Monitoring 85 -- 4.6 Summary 85 -- Bibliography 86 -- 5 Ultra Reliable Low Latency Communications as an Enabler For Industry Automation 89 / Jo©úo Pedro Battistella Nadas, Guodong Zhao, Richard Demo Souza, and Muhammad A. Imran -- 5.1 Introduction 89 -- 5.2 Opportunities for URLLC in Industry Automation 91 -- 5.2.1 URLLC Industrial Applications 91 -- 5.2.2 New Business Models 93 -- 5.3 Existing Solutions 94 -- 5.3.1 LTE 94 -- 5.3.2 WirelessHART and ISA100.11a 95 -- 5.4 Enabling Technologies 96 -- 5.4.1 Faster Channel Coding 96 -- 5.4.2 Latency Aware HARQ 97 -- 5.4.3 Joint Design 98 -- 5.4.3.1 Communication Model 100 -- 5.4.3.2 Proposed Solution 100.
5.4.3.3 Numerical Results and Conclusion 103 -- 5.5 Conclusion 104 -- Bibliography 104 -- 6 Anomaly Detection and Self-healing in Industrial Wireless Networks 109 / Ahmed Zoha, Qammer H. Abbasi, and Muhammad A. Imran -- 6.1 Introduction 109 -- 6.2 System Design 113 -- 6.2.1 COD Stage 113 -- 6.2.2 COC Stage 115 -- 6.3 Cell Outage Detection Framework 115 -- 6.3.1 Profiling Phase 115 -- 6.3.1.1 Local Outlier Factor Based Detector (LOFD) 119 -- 6.3.1.2 One-Class Support Vector Machine based Detector (OCSVMD) 120 -- 6.3.2 Detection and Localization Phase 122 -- 6.4 Cell Outage Compensation 122 -- 6.5 Simulation Results 124 -- 6.5.1 Simulation Setup 124 -- 6.5.1.1 Parameter Estimation and Evaluation 124 -- 6.5.2 Cell Outage Detection Results 127 -- 6.5.3 Localization 135 -- 6.5.4 Compensation 136 -- 6.6 Conclusion 138 -- Bibliography 138 -- 7 Cost Efficiency Optimization for Industrial Automation 141 / Hafiz Husnain Raza Sherazi, Luigi Alfredo Grieco, Gennaro Boggia, and Muhammad A. Imran -- 7.1 Introduction 141 -- 7.2 The Evolution of Low Energy Networking Protocols for Industrial Automation 144 -- 7.2.1 Radio Frequency Identification and Near Field Communication 144 -- 7.2.2 Bluetooth 145 -- 7.2.3 Zigbee 145 -- 7.2.4 Bluetooth Low Energy (BLE) 145 -- 7.2.5 Wi-Fi 146 -- 7.2.6 IPv6 Over Low Power Wireless Personal Area Networks (6LoWPAN) 146 -- 7.2.7 Low Power Wide Area Networks (LPWAN) 146 -- 7.2.7.1 Long Range Wide Area Networks (LoRaWAN) 148 -- 7.2.7.2 Sigfox 149 -- 7.2.7.3 Narrowband IoT (NB-IoT) 150 -- 7.3 An Overview of the Costs Involved in Industry 4.0 151 -- 7.3.1 Battery Replacement Cost 152 -- 7.3.2 Damage Penalty 152 -- 7.3.3 Cost Relationships and Trade-off Analysis 152 -- 7.4 Evaluating Costs in an Industrial Environment: A LoRaWAN Case study 153 -- 7.4.1 Battery Lifetime of Monitoring Nodes 155 -- 7.4.2 Battery Replacement Cost 156 -- 7.4.3 Damage Penalty 157 -- 7.5 Cost Analysis for Industrial Automation 158 -- 7.5.1 Statistics for Energy Consumption 158.
7.5.2 Statistics for Battery Replacement Cost 159 -- 7.5.3 Statistics for Damage Penalty in a Plain Industrial Environment 161 -- 7.5.4 The Cumulative Cost 163 -- 7.6 Cost Optimization through Energy Harvesting in Industrial Automation 164 -- 7.6.1 Extending the Battery Lifetime 165 -- 7.6.2 Tuning the Sensing Interval 165 -- 7.7 Conclusion 168 -- Bibliography 168 -- 8 A Non-Event Based Approach for Non-Intrusive Load Monitoring 173 / Ahmed Zoha, Qammer H. Abbasi, and Muhammad A. Imran -- 8.1 Introduction 173 -- 8.2 Probabilistic Modelling for Load Disaggregation 175 -- 8.2.1 Model Definition 177 -- 8.2.2 Inference 178 -- 8.3 Experimental Evaluations 180 -- 8.3.1 Experiment Design 181 -- 8.3.2 Feature Sub-Groups 182 -- 8.3.3 Performance Evaluation 183 -- 8.3.3.1 Binary and Multi-State Classification 183 -- 8.4 Live Deployment 187 -- 8.4.1 Energy Estimation 188 -- 8.5 Conclusion 190 -- Bibliography 191 -- 9 Wireless Networked Control 193 / Zhen Meng and Guodong Zhao -- 9.1 Introduction 193 -- 9.2 Industrial Automation 194 -- 9.3 WNC System Model 196 -- 9.3.1 WNC Model 196 -- 9.3.1.1 Wireless Networks 197 -- 9.3.1.2 Control System 198 -- 9.3.2 WNC System Requirements 199 -- 9.3.2.1 System Structure 199 -- 9.3.2.2 Real-Time Performance 200 -- 9.3.2.3 High Reliability 201 -- 9.3.2.4 Determinism 201 -- 9.3.2.5 Sample Data Traffic and Event Order 201 -- 9.3.3 Analysis of Influencing Factors 202 -- 9.3.3.1 Sampling Period 202 -- 9.3.3.2 Time Delay 202 -- 9.3.3.3 Packet Loss 203 -- 9.4 Network and System Control Co-design 203 -- 9.5 Conclusion 204 -- Bibliography 204 -- 10 Caching at the Edge in Low Latency Wireless Networks 209 / Ramy Amer, M. Majid Butt, and Nicola Marchetti -- 10.1 Introduction 209 -- 10.2 Living on the Edge 211 -- 10.3 Classifications of Wireless Caching Networks 214 -- 10.3.1 Wireless Caching Architecture 215 -- 10.4 Caching for Low Latency Wireless Networks 217 -- 10.5 Inter-cluster Cooperation for Wireless D2D Caching Networks 218 -- 10.5.1 Proposed Network Model 219.
10.5.2 Content Placement and Traffic Characteristics 222 -- 10.5.3 Caching Problem Formulation 224 -- 10.5.3.1 Arrival and Service Rates 224 -- 10.5.3.2 Network Average Delay 225 -- 10.5.4 Proposed Caching Schemes 226 -- 10.5.4.1 Caching Popular Files 226 -- 10.5.4.2 Greedy Caching Algorithm 227 -- 10.5.4.3 Outage Probability 228 -- 10.6 Results and Discussions 230 -- 10.7 Chapter Summary 234 -- Bibliography 235 -- 11 Application of Terahertz Sensing at Nano-Scale for Precision Agriculture 241 / Adnan Zahid, Hasan T. Abbas, Aifeng Ren, Akram Alomainy, Muhammad A. Imran, and Qammer H. Abbasi -- 11.1 Introduction 241 -- 11.1.1 Limitations of Conventional Methods 243 -- 11.1.2 Transformation from Micro- to Nanotechnology 243 -- 11.1.3 Evolution of Nanotechnology 245 -- 11.1.4 Potential Benefits of Nanotechnology in Agriculture 245 -- 11.1.5 Challenges in Nanotechnology 246 -- 11.1.5.1 Health and Environmental Impacts 246 -- 11.1.5.2 High Production Costs 246 -- 11.1.5.3 Risk Assessment 247 -- 11.1.6 Evolving Applications of Terahertz (THz) Technology 247 -- 11.1.7 Materials and Methods 249 -- 11.1.7.1 Experimental Setup 249 -- 11.1.7.2 Sample 249 -- 11.1.7.3 Thickness of Leaves 250 -- 11.1.8 Measurement Results 250 -- 11.1.8.1 Transmission Response 250 -- 11.1.8.2 Path-loss Response of Leaves 253 -- 11.1.9 Conclusion 254 -- Bibliography 255 -- Index 259.
Record Nr. UNINA-9910555172903321
MUHAMMAD A. IMRAN; SAJJAD HUSSAIN; QAMMER H. ABBAS  
HOBOKEN : , : JOHN WILEY, , 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Wireless automation as an enabler for the next industrial revolution / / edited by Muhammad Ali Imran, Sajid Hussain, Qammer H. Abbasi
Wireless automation as an enabler for the next industrial revolution / / edited by Muhammad Ali Imran, Sajid Hussain, Qammer H. Abbasi
Autore MUHAMMAD A. IMRAN; SAJJAD HUSSAIN; QAMMER H. ABBAS
Pubbl/distr/stampa HOBOKEN : , : JOHN WILEY, , 2019
Descrizione fisica 1 online resource (285 pages)
Disciplina 681.2
Soggetto topico Wireless sensor networks
ISBN 1-119-55262-1
1-119-55263-X
1-119-55258-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto List of Contributors xiii -- Preface xvii -- 1 Industrial Wireless Sensor Networks Overview 1 / Mohsin Raza and Huan X. Nguyen -- 1.1 Introduction 1 -- 1.2 Industry 4.0 3 -- 1.3 Industrial Wireless Sensor Networks (IWSNs) 6 -- 1.4 Applications of IWSNs 8 -- 1.4.1 Feedback Control Systems 8 -- 1.4.2 Motion and Robotics 9 -- 1.4.3 Safety Applications 9 -- 1.4.4 Environmental Monitoring 9 -- 1.4.5 Machine/Structural Health Monitoring 10 -- 1.5 Communication Topologies in IWSNs 10 -- 1.6 Research Developments and Communications Standards for Industry 11 -- 1.6.1 IEEE 802.15.4 12 -- 1.6.2 IEEE 802.15.4e 13 -- 1.6.3 Zigbee 13 -- 1.6.4 WirelessHART 14 -- 1.6.5 ISA100.11a 14 -- 1.6.6 6LoWPAN 14 -- Bibliography 15 -- 2 Life-span Extension for Sensor Networks in the Industry 19 / Metin Ozturk, Mona Jaber, and Muhammad A. Imran -- 2.1 Introduction 19 -- 2.2 Wireless Sensor Networks 21 -- 2.3 Industrial WSNs 24 -- 2.3.1 Requirements and Challenges 25 -- 2.3.2 Protocols and Standards 26 -- 2.3.3 IWSN Applications 27 -- 2.4 Life-span Extension for WSNs 28 -- 2.4.1 Energy Harvesting 29 -- 2.4.1.1 Solar Energy Harvesting 31 -- 2.4.1.2 Wind Energy Harvesting 31 -- 2.4.1.3 Radio Frequency Energy Harvesting 32 -- 2.4.1.4 Piezoelectric Energy Harvesting 32 -- 2.4.1.5 Thermal Energy Harvesting 33 -- 2.4.2 Energy Conservation 33 -- 2.4.2.1 Duty Cycling 34 -- 2.4.2.2 Data Driven Approaches 35 -- 2.4.2.3 Mobility Based Approaches 35 -- 2.4.2.4 Q Learning Assisted Energy Efficient Smart Connectivity 36 -- 2.5 Conclusion 40 -- Bibliography 41 -- 3 Multiple Access and Resource Sharing for Low Latency Critical Industrial Networks 47 / Mohsin Raza, Anas Amjad, and Sajjad Hussain -- 3.1 Introduction 47 -- 3.2 Research Developments 51 -- 3.2.1 CSMA/CA Based MAC Schemes 53 -- 3.2.2 TDMA Based MAC Schemes 53 -- 3.2.3 Multichannel MAC Schemes 54 -- 3.2.4 Priority Based MAC Schemes 55 -- 3.3 Priority Based Information Scheduling and Transmission 56 -- 3.4 Summary 61 -- Bibliography 61 -- 4 Narrowband Internet of Things (NB-IoT) for Industrial Automation 65 / Hassan Malik, Muhammad Mahtab Alam, Alar Kuusik, Yannick Le Moullec, and Sven P©Þrand.
4.1 Introduction 65 -- 4.2 Overview of NB-IoT 65 -- 4.3 NB-IoT Design Characteristics 68 -- 4.3.1 Low Device Complexity and Low Cost 68 -- 4.3.2 Coverage Enhancement (CE) 70 -- 4.3.3 Long Device Battery Lifetime 70 -- 4.3.4 Massive Device Support 71 -- 4.3.5 Deployment Flexibility 72 -- 4.3.6 Small Data Packet Transmission Support 74 -- 4.3.6.1 Control Plane CIoT EPS Optimization (CP) 74 -- 4.3.6.2 User Plane CIoT EPS Optimization (UP) 76 -- 4.3.7 Multicast Transmission Support 76 -- 4.3.8 Mobility Support 76 -- 4.4 NB-IoT Frame Structure 77 -- 4.4.1 Downlink Transmission Scheme 78 -- 4.4.1.1 Narrowband Reference Signal (NRS) 78 -- 4.4.1.2 Narrowband Primary and Secondary Synchronization Signals (NPSS and NSSS) 78 -- 4.4.1.3 Narrowband Physical Broadcast Channel (NPBCH) 79 -- 4.4.1.4 Narrowband Physical Downlink Control Channel (NPDCCH) 79 -- 4.4.1.5 Narrowband Physical Downlink Shared Channel (NPDSCH) 80 -- 4.4.2 Uplink Transmission Scheme 80 -- 4.4.2.1 Demodulation Reference Signal (DMRS) 80 -- 4.4.2.2 Narrowband Physical Random Access Channel (NPRACH) 81 -- 4.4.2.3 Narrowband Uplink Shared Channel (NPUSCH) 81 -- 4.4.3 NB-IoT Design Modification in Relation to LTE 81 -- 4.5 NB-IoT as an Enabler for Industry 4.0 81 -- 4.5.1 Process Automation 83 -- 4.5.2 HumańôMachine Interfaces 84 -- 4.5.3 Logistics and Warehousing 84 -- 4.5.4 Maintenance and Monitoring 85 -- 4.6 Summary 85 -- Bibliography 86 -- 5 Ultra Reliable Low Latency Communications as an Enabler For Industry Automation 89 / Jo©úo Pedro Battistella Nadas, Guodong Zhao, Richard Demo Souza, and Muhammad A. Imran -- 5.1 Introduction 89 -- 5.2 Opportunities for URLLC in Industry Automation 91 -- 5.2.1 URLLC Industrial Applications 91 -- 5.2.2 New Business Models 93 -- 5.3 Existing Solutions 94 -- 5.3.1 LTE 94 -- 5.3.2 WirelessHART and ISA100.11a 95 -- 5.4 Enabling Technologies 96 -- 5.4.1 Faster Channel Coding 96 -- 5.4.2 Latency Aware HARQ 97 -- 5.4.3 Joint Design 98 -- 5.4.3.1 Communication Model 100 -- 5.4.3.2 Proposed Solution 100.
5.4.3.3 Numerical Results and Conclusion 103 -- 5.5 Conclusion 104 -- Bibliography 104 -- 6 Anomaly Detection and Self-healing in Industrial Wireless Networks 109 / Ahmed Zoha, Qammer H. Abbasi, and Muhammad A. Imran -- 6.1 Introduction 109 -- 6.2 System Design 113 -- 6.2.1 COD Stage 113 -- 6.2.2 COC Stage 115 -- 6.3 Cell Outage Detection Framework 115 -- 6.3.1 Profiling Phase 115 -- 6.3.1.1 Local Outlier Factor Based Detector (LOFD) 119 -- 6.3.1.2 One-Class Support Vector Machine based Detector (OCSVMD) 120 -- 6.3.2 Detection and Localization Phase 122 -- 6.4 Cell Outage Compensation 122 -- 6.5 Simulation Results 124 -- 6.5.1 Simulation Setup 124 -- 6.5.1.1 Parameter Estimation and Evaluation 124 -- 6.5.2 Cell Outage Detection Results 127 -- 6.5.3 Localization 135 -- 6.5.4 Compensation 136 -- 6.6 Conclusion 138 -- Bibliography 138 -- 7 Cost Efficiency Optimization for Industrial Automation 141 / Hafiz Husnain Raza Sherazi, Luigi Alfredo Grieco, Gennaro Boggia, and Muhammad A. Imran -- 7.1 Introduction 141 -- 7.2 The Evolution of Low Energy Networking Protocols for Industrial Automation 144 -- 7.2.1 Radio Frequency Identification and Near Field Communication 144 -- 7.2.2 Bluetooth 145 -- 7.2.3 Zigbee 145 -- 7.2.4 Bluetooth Low Energy (BLE) 145 -- 7.2.5 Wi-Fi 146 -- 7.2.6 IPv6 Over Low Power Wireless Personal Area Networks (6LoWPAN) 146 -- 7.2.7 Low Power Wide Area Networks (LPWAN) 146 -- 7.2.7.1 Long Range Wide Area Networks (LoRaWAN) 148 -- 7.2.7.2 Sigfox 149 -- 7.2.7.3 Narrowband IoT (NB-IoT) 150 -- 7.3 An Overview of the Costs Involved in Industry 4.0 151 -- 7.3.1 Battery Replacement Cost 152 -- 7.3.2 Damage Penalty 152 -- 7.3.3 Cost Relationships and Trade-off Analysis 152 -- 7.4 Evaluating Costs in an Industrial Environment: A LoRaWAN Case study 153 -- 7.4.1 Battery Lifetime of Monitoring Nodes 155 -- 7.4.2 Battery Replacement Cost 156 -- 7.4.3 Damage Penalty 157 -- 7.5 Cost Analysis for Industrial Automation 158 -- 7.5.1 Statistics for Energy Consumption 158.
7.5.2 Statistics for Battery Replacement Cost 159 -- 7.5.3 Statistics for Damage Penalty in a Plain Industrial Environment 161 -- 7.5.4 The Cumulative Cost 163 -- 7.6 Cost Optimization through Energy Harvesting in Industrial Automation 164 -- 7.6.1 Extending the Battery Lifetime 165 -- 7.6.2 Tuning the Sensing Interval 165 -- 7.7 Conclusion 168 -- Bibliography 168 -- 8 A Non-Event Based Approach for Non-Intrusive Load Monitoring 173 / Ahmed Zoha, Qammer H. Abbasi, and Muhammad A. Imran -- 8.1 Introduction 173 -- 8.2 Probabilistic Modelling for Load Disaggregation 175 -- 8.2.1 Model Definition 177 -- 8.2.2 Inference 178 -- 8.3 Experimental Evaluations 180 -- 8.3.1 Experiment Design 181 -- 8.3.2 Feature Sub-Groups 182 -- 8.3.3 Performance Evaluation 183 -- 8.3.3.1 Binary and Multi-State Classification 183 -- 8.4 Live Deployment 187 -- 8.4.1 Energy Estimation 188 -- 8.5 Conclusion 190 -- Bibliography 191 -- 9 Wireless Networked Control 193 / Zhen Meng and Guodong Zhao -- 9.1 Introduction 193 -- 9.2 Industrial Automation 194 -- 9.3 WNC System Model 196 -- 9.3.1 WNC Model 196 -- 9.3.1.1 Wireless Networks 197 -- 9.3.1.2 Control System 198 -- 9.3.2 WNC System Requirements 199 -- 9.3.2.1 System Structure 199 -- 9.3.2.2 Real-Time Performance 200 -- 9.3.2.3 High Reliability 201 -- 9.3.2.4 Determinism 201 -- 9.3.2.5 Sample Data Traffic and Event Order 201 -- 9.3.3 Analysis of Influencing Factors 202 -- 9.3.3.1 Sampling Period 202 -- 9.3.3.2 Time Delay 202 -- 9.3.3.3 Packet Loss 203 -- 9.4 Network and System Control Co-design 203 -- 9.5 Conclusion 204 -- Bibliography 204 -- 10 Caching at the Edge in Low Latency Wireless Networks 209 / Ramy Amer, M. Majid Butt, and Nicola Marchetti -- 10.1 Introduction 209 -- 10.2 Living on the Edge 211 -- 10.3 Classifications of Wireless Caching Networks 214 -- 10.3.1 Wireless Caching Architecture 215 -- 10.4 Caching for Low Latency Wireless Networks 217 -- 10.5 Inter-cluster Cooperation for Wireless D2D Caching Networks 218 -- 10.5.1 Proposed Network Model 219.
10.5.2 Content Placement and Traffic Characteristics 222 -- 10.5.3 Caching Problem Formulation 224 -- 10.5.3.1 Arrival and Service Rates 224 -- 10.5.3.2 Network Average Delay 225 -- 10.5.4 Proposed Caching Schemes 226 -- 10.5.4.1 Caching Popular Files 226 -- 10.5.4.2 Greedy Caching Algorithm 227 -- 10.5.4.3 Outage Probability 228 -- 10.6 Results and Discussions 230 -- 10.7 Chapter Summary 234 -- Bibliography 235 -- 11 Application of Terahertz Sensing at Nano-Scale for Precision Agriculture 241 / Adnan Zahid, Hasan T. Abbas, Aifeng Ren, Akram Alomainy, Muhammad A. Imran, and Qammer H. Abbasi -- 11.1 Introduction 241 -- 11.1.1 Limitations of Conventional Methods 243 -- 11.1.2 Transformation from Micro- to Nanotechnology 243 -- 11.1.3 Evolution of Nanotechnology 245 -- 11.1.4 Potential Benefits of Nanotechnology in Agriculture 245 -- 11.1.5 Challenges in Nanotechnology 246 -- 11.1.5.1 Health and Environmental Impacts 246 -- 11.1.5.2 High Production Costs 246 -- 11.1.5.3 Risk Assessment 247 -- 11.1.6 Evolving Applications of Terahertz (THz) Technology 247 -- 11.1.7 Materials and Methods 249 -- 11.1.7.1 Experimental Setup 249 -- 11.1.7.2 Sample 249 -- 11.1.7.3 Thickness of Leaves 250 -- 11.1.8 Measurement Results 250 -- 11.1.8.1 Transmission Response 250 -- 11.1.8.2 Path-loss Response of Leaves 253 -- 11.1.9 Conclusion 254 -- Bibliography 255 -- Index 259.
Record Nr. UNINA-9910830687903321
MUHAMMAD A. IMRAN; SAJJAD HUSSAIN; QAMMER H. ABBAS  
HOBOKEN : , : JOHN WILEY, , 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui