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Intelligent connectivity : AI, IoT, and 5G / / Abdulrahman Yarali
| Intelligent connectivity : AI, IoT, and 5G / / Abdulrahman Yarali |
| Autore | Yarali Abdulrahman |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , [2022] |
| Descrizione fisica | 1 online resource (353 pages) |
| Disciplina | 004.678 |
| Collana | IEEE Press |
| Soggetto topico |
Internet of things
5G mobile communication systems Artificial intelligence - Industrial applications |
| ISBN |
9781119685180
9781119685265 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Acknowledgement -- Introduction -- Chapter 1 Technology Adoption and Emerging Trends -- 1.1 Introduction -- 1.2 Trends in Business Technology -- 1.2.1 Trends that Could Disrupt the Industry -- 1.2.2 Adopting New Technologies -- 1.2.3 Best Practices and Risks Associated with Emerging Technologies -- 1.2.4 Power of Disruptive Technologies -- 1.2.5 Driving Strategy Around Our Priority -- 1.2.6 Strategic Partnerships to be Pursued -- 1.3 AI-Fueled Organizations -- 1.4 Connectivity of Tomorrow -- 1.4.1 Intelligent Interfaces -- 1.5 Moving Beyond Marketing -- 1.6 Cloud Computing -- 1.7 Cybersecurity, Privacy, and Risk Management -- 1.8 Conclusion -- References -- Chapter 2 Telecommunication Transformation and Intelligent Connectivity -- 2.1 Introduction -- 2.1.1 Learning Algorithm and Its Connections to AI -- 2.1.2 Machine Learning as a Precursor to AI -- 2.1.3 Deep Learning and Realization of AI -- 2.1.4 Consideration of the Next Generation Wireless Technology -- 2.1.5 Potential of AI and 5G Network Technology Together -- 2.2 Cybersecurity Concerns in the 5G World -- 2.2.1 5G's Potential in Making Security a Priority -- 2.2.2 Key Features -- 2.3 Positive Effects of Addressing Cybersecurity Challenges in 5G -- 2.4 Intelligent Connectivity Use-Cases -- 2.4.1 Transportation and Logistics -- 2.4.2 AI-based Driver Assistance and Monitoring -- 2.4.3 Self-Driving Vehicles -- 2.4.4 Deliveries with Unmanned Vehicles -- 2.5 Industrial and Manufacturing Operations -- 2.5.1 Factory Automation and Remote Control of Industrial Robots -- 2.5.2 Remote Inspections and Maintenance, and Worker's Training -- 2.6 Healthcare -- 2.6.1 Remote Health Monitoring and Illness Prevention -- 2.6.2 Remote Diagnosis and Medical Operation -- 2.7 Public Safety and Security.
2.7.1 Intelligent Video-Surveillance and Security Systems -- 2.7.2 Emergency Services and Border Controls -- 2.7.3 Other Sectors -- 2.8 Conclusion -- References -- Chapter 3 The Internet of Things (IoT): Potentials and the Future Trends -- 3.1 Introduction -- 3.2 Achieving the Future of IoT -- 3.3 Commercial Opportunities for IoT -- 3.4 The Industrial Internet of Things -- 3.4.1 How IIoT Works -- 3.4.2 Benefits of IIoT -- 3.4.3 IIoT versus IoT -- 3.4.4 IIoT Applications and Examples -- 3.4.5 Vendors in IIoT -- 3.4.6 The Future of IIoT -- 3.5 Future Impact of IoT in Our Industry -- 3.6 Data Sharing in the IoT Environment -- 3.7 IoT Devices for Environment Operation -- 3.7.1 Step One: Pick Your Protocol -- 3.7.2 Step Two: Understand Coexistence -- 3.7.3 Step Three: Pick Your Technique -- 3.7.4 Step Four: Create Your Test Plan -- 3.8 Interoperability Issues of IoT -- 3.9 IoT-Cloud - Application -- 3.10 Regulation and Security Issues of IoT -- 3.11 Achieving IoT Innovations While Tackling Security and Regulation Issues -- 3.12 Future of IoT -- 3.13 Conclusion -- References -- Chapter 4 The Wild Wonders of 5G Wireless Technology -- 4.1 Introduction -- 4.1.1 First Generation (1G) -- 4.1.2 Second Generation (2G) -- 4.1.3 Third Generation (3G) -- 4.1.4 Advanced Third Generation (3.5G) -- 4.1.5 Fourth Generation (4G) -- 4.1.6 Fifth Generation (5G) -- 4.2 5G Architecture -- 4.2.1 Realizing New 5G Possibilities with the Intelligent Edge -- 4.3 5G Applications -- 4.3.1 5G and Video Surveillance -- 4.3.2 5G and Fixed Wireless Access (FWA) -- 4.4 5G Network Architecture -- 4.5 Security and Issues of 5G -- 4.6 IoT Devices in 5G Wireless -- 4.7 Big Data Analytics in 5G -- 4.8 AI Empowers a Wide Scope of Use Cases -- 4.9 Conclusion -- References -- Chapter 5 Artificial Intelligence Technology -- 5.1 Introduction -- 5.2 Core Concepts of Artificial Intelligence. 5.3 Machine Learning and Applications -- 5.4 Deep Learning -- 5.5 Neural Networks Follow a Natural Model -- 5.6 Classifications of Artificial Intelligence -- 5.7 Trends in Artificial Intelligence -- 5.7.1 Artificial Intelligence in Energy -- 5.7.2 Artificial Intelligence in Healthcare -- 5.7.3 Artificial Intelligence in Education -- 5.7.4 Artificial Intelligence in Manufacturing -- 5.7.5 Artificial Intelligence in Financial Services -- 5.7.6 Artificial Intelligence in Transport -- 5.8 Challenges of Artificial Intelligence -- 5.8.1 Data -- 5.9 Funding Trends in Artificial Intelligence -- 5.9.1 Artificial Readiness -- 5.9.2 Foundational Readiness -- 5.9.3 Operational Readiness -- 5.9.4 Transformational Readiness -- 5.10 Conclusion -- References -- Chapter 6 AI, 5G, and IoT: Driving Forces Towards the Industry Technology Trends -- 6.1 Introduction -- 6.2 Fifth Generation of Network Technology -- 6.3 Internet of Things (IoT) -- 6.4 Industrial Internet of Things -- 6.5 IoT in the Automotive Industry -- 6.6 IoT in Agriculture -- 6.7 AI, IoT, and 5G Security -- 6.8 Conclusion -- References -- Chapter 7 Intelligent Connectivity: New Capabilities to Bring Complex Use Cases -- 7.1 Introduction -- 7.1.1 Artificial Intelligence -- 7.1.2 The Fifth Generation Networks -- 7.1.3 The Internet of Things -- 7.2 Machine-to-Machine Communication and the Internet of Things -- 7.3 Convergence of Internet of Things, Artificial Intelligence, and 5G -- 7.3.1 The Benefits of Intelligent Connectivity -- 7.4 Intelligent Connectivity Applications -- 7.4.1 Industry -- 7.4.2 Transport and Logistics -- 7.4.3 Healthcare -- 7.4.4 Security -- 7.4.5 Smart Homes and Personal Assistant -- 7.4.6 Wearable Technology -- 7.4.7 Entertainment -- 7.4.8 Communication -- 7.4.9 Resource Management -- 7.4.10 Agriculture -- 7.4.11 Education -- 7.5 Challenges and Risks of Intelligent Connectivity. 7.5.1 Economic Risks -- 7.5.2 Risks to Human Safety and Agency -- 7.5.3 Social Risk -- 7.5.4 Secondary Risks -- 7.5.5 Confidentiality and Scalability -- 7.6 Recommendations -- 7.7 Conclusion -- References -- Chapter 8 IoT: Laws, Policies, and Regulations -- 8.1 Introduction -- 8.2 Recently Published Laws and Regulations -- 8.2.1 IoT Cybersecurity Improvement Act of 2017 -- 8.3 Developing Innovation and Growing the Internet of Things (DIGIT) Act -- 8.4 General View -- 8.5 Relaxation of Laws by the Federal Aviation Administration (FAA) -- 8.6 Supporting Innovation of Self-Driving Cars by Government Policies -- 8.6.1 Investment by US Department of Homeland Security -- 8.6.2 United States Guiding Principles for IoT Security -- 8.6.3 The United Kingdom on IoT -- 8.6.4 United States Department of Commerce -- 8.6.5 Federal Trade Commission and Creating an IoT Security Solution -- 8.7 Recommendations -- 8.8 Conclusion -- References -- Chapter 9 Artificial Intelligence and Blockchain -- 9.1 Introduction -- 9.2 Decentralized Intelligence -- 9.2.1 Data Protection -- 9.2.2 Trusting AI Decision Making -- 9.2.3 AI and Encryption -- 9.3 Applications -- 9.3.1 The Coordination of Blockchain into AI -- 9.3.2 Essential Blockchain Benefits -- 9.4 How Artificial Intelligence and Blockchain Will Affect Society -- 9.4.1 Banking and Payments -- 9.4.2 Cybersecurity -- 9.4.3 Internet of Things -- 9.4.4 Unified Communications -- 9.4.5 Government -- 9.4.6 Crowdfunding and Donating to Charities -- 9.4.7 Healthcare -- 9.4.8 Rentals and Ride-Sharing -- 9.5 Augmented Reality -- 9.5.1 Augmented Reality in the Production Context -- 9.5.2 How Augmented Reality Works -- 9.5.3 Marker and Marker-Less AR -- 9.5.4 Layered AR -- 9.5.5 Projection AR -- 9.5.6 AR in Education -- 9.5.7 AR in Navigation -- 9.5.8 AR in Games -- 9.6 Mixed Reality -- 9.7 Virtual Reality -- 9.7.1 Virtual World. 9.7.2 Mental Immersion -- 9.7.3 Physical Immersion -- 9.7.4 Tangible Feedback -- 9.7.5 Intelligence -- 9.7.6 Types of Virtual Reality -- 9.7.7 Semi-Immersive -- 9.7.8 Completely Immersive -- 9.8 Key Components in a Virtual Reality System -- 9.8.1 PC (Personal Computer)/Console/Smartphone -- 9.8.2 Head-Mounted Display -- 9.8.3 Information Devices -- 9.8.4 Augmented Reality versus Virtual Reality -- 9.8.5 Benefits of Augmented Reality -- 9.9 Augmented Reality Uses -- 9.9.1 Retail -- 9.9.2 Real Estate -- 9.9.3 Interior Design -- 9.9.4 Tourism and Maps -- 9.9.5 Training and Education -- 9.9.6 Healthcare -- 9.10 Applications of Virtual Reality in Business -- 9.10.1 Training -- 9.10.2 Retail -- 9.10.3 Construction -- 9.10.4 Data Representation -- 9.10.5 Manufacture -- 9.11 The Future of Blockchain -- 9.12 Blockchain Applications -- 9.12.1 National Cryptographic Money -- 9.12.2 Blockchain into Government -- 9.12.3 Blockchain Specialists -- 9.13 Blockchain and the Internet of Things -- 9.14 Law Coordination -- 9.15 Collaboration for Blockchain Success -- References -- Chapter 10 Digital Twin Technology -- 10.1 Introduction -- 10.2 The Timeline and History of Digital Twin Technology -- 10.3 Technologies Employed in Digital Twin Models -- 10.3.1 Cloud Services -- 10.3.2 Cyber-Physical Systems -- 10.4 The Dimension of Digital Twin Models -- 10.4.1 Digital Twin Data -- 10.4.2 Services in Digital Twins -- 10.4.3 Connection in Digital Twins -- 10.4.4 Physical Assets in Digital Twins -- 10.4.5 Virtual Entities in Digital Twins -- 10.5 Digital Twin and Other Technologies -- 10.5.1 Digital Twins and Internet of Things -- 10.5.2 Digital Twins and Artificial Intelligence -- 10.5.3 Digital Twins and Analytics -- 10.5.4 Digital Twins and Connectivity -- 10.5.5 Digital Twins and Machine Learning -- 10.6 Digital Twin Technology Implementation. 10.7 Benefits of Digital Twins. |
| Record Nr. | UNINA-9910830742203321 |
Yarali Abdulrahman
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| Hoboken, New Jersey : , : Wiley, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Intelligent resource management for network slicing in 5G and beyond / / Qiang Ye and Weihua Zhuang
| Intelligent resource management for network slicing in 5G and beyond / / Qiang Ye and Weihua Zhuang |
| Autore | Ye Qiang <1985-> |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (202 pages) |
| Disciplina | 621.3821 |
| Collana | Wireless Networks |
| Soggetto topico |
Mobile communication systems
5G mobile communication systems Radio resource management (Wireless communications) |
| ISBN | 3-030-88666-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996464381003316 |
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Ye Qiang <1985->
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| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Intelligent resource management for network slicing in 5G and beyond / / Qiang Ye and Weihua Zhuang
| Intelligent resource management for network slicing in 5G and beyond / / Qiang Ye and Weihua Zhuang |
| Autore | Ye Qiang <1985-> |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (202 pages) |
| Disciplina | 621.3821 |
| Collana | Wireless Networks |
| Soggetto topico |
Mobile communication systems
5G mobile communication systems Radio resource management (Wireless communications) |
| ISBN | 3-030-88666-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910520085703321 |
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Ye Qiang <1985->
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| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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An introduction to 5G : the new radio, 5G network and beyond / / Christopher Cox
| An introduction to 5G : the new radio, 5G network and beyond / / Christopher Cox |
| Autore | Cox Christopher (Christopher Ian), <1965-> |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , [2020] |
| Descrizione fisica | 1 online resource (448 pages) |
| Disciplina | 621.38456 |
| Soggetto topico | 5G mobile communication systems |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-119-60271-8
1-5231-3711-8 1-119-60269-6 1-119-60268-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910554831403321 |
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Cox Christopher (Christopher Ian), <1965->
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| Hoboken, New Jersey : , : Wiley, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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An introduction to 5G : the new radio, 5G network and beyond / / Christopher Cox
| An introduction to 5G : the new radio, 5G network and beyond / / Christopher Cox |
| Autore | Cox Christopher (Christopher Ian), <1965-> |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , [2020] |
| Descrizione fisica | 1 online resource (448 pages) |
| Disciplina | 621.38456 |
| Soggetto topico | 5G mobile communication systems |
| ISBN |
1-119-60271-8
1-5231-3711-8 1-119-60269-6 1-119-60268-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910677118503321 |
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Cox Christopher (Christopher Ian), <1965->
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| Hoboken, New Jersey : , : Wiley, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
An introduction to 5G : the new radio, 5G network and beyond / / Christopher Cox
| An introduction to 5G : the new radio, 5G network and beyond / / Christopher Cox |
| Autore | Cox Christopher (Christopher Ian), <1965-> |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , [2020] |
| Descrizione fisica | 1 online resource (448 pages) |
| Disciplina | 621.38456 |
| Soggetto topico | 5G mobile communication systems |
| ISBN |
1-119-60271-8
1-5231-3711-8 1-119-60269-6 1-119-60268-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910808308103321 |
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Cox Christopher (Christopher Ian), <1965->
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| Hoboken, New Jersey : , : Wiley, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Key 5G physical layer technologies : enabling mobile and fixed wireless access / / Douglas H. Morais
| Key 5G physical layer technologies : enabling mobile and fixed wireless access / / Douglas H. Morais |
| Autore | Morais Douglas H. |
| Edizione | [Second edition.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (337 pages) |
| Disciplina | 621.38456 |
| Soggetto topico |
5G mobile communication systems
Communications mobiles 5G |
| ISBN |
9783030892098
9783030892081 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910522927803321 |
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Morais Douglas H.
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| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Microwave and millimeter-wave antenna design for 5G smartphone applications / / Wonbin Hong, Chow-Yen Desmond Sim
| Microwave and millimeter-wave antenna design for 5G smartphone applications / / Wonbin Hong, Chow-Yen Desmond Sim |
| Autore | Hong Wonbin |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2023] |
| Descrizione fisica | 1 online resource (365 pages) |
| Disciplina | 621.3813 |
| Soggetto topico |
5G mobile communication systems
Microwave antennas Millimeter wave devices |
| ISBN |
1-394-18245-7
1-394-18243-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910830166903321 |
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Hong Wonbin
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| Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Mobile radio communications and 5G networks : proceedings of third MRCN 2022 / / Nikhil Marriwala [and three others], editors
| Mobile radio communications and 5G networks : proceedings of third MRCN 2022 / / Nikhil Marriwala [and three others], editors |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (687 pages) |
| Disciplina | 621.38456 |
| Collana | Lecture notes in networks and systems |
| Soggetto topico | 5G mobile communication systems |
| ISBN | 981-19-7982-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Android Malwares with their Characteristics and Threats -- Design of a Novel Side Chaining Model for Improving the Performance of Security Aware E-Voting Application -- Optimized Activation Function based SAR Ship Detection -- Elimination and Restoring De-duplicated Storage for Multi-Level Integrated Approach with Cost Estimation -- DEEC Protocol with ACO Based Cluster Head Selection in Wireless Sensor Network -- Effective Communication in NDN via Transient Popular Content Caching at Edge -- Performance of HMRF Based Unsupervised Segmentation & Random Walk Segmentation Algorithms for Gall Bladder MRI -- Breast Cancer Detection Using Deep Learning -- Transferring Pre-Trained Deep CNNs on Plantar Thermograms for Diabetic Foot Disease -- Sensory Nerve Conduction System with Non-Invasive Glucose Monitoring using IOT Based Assessment -- Detection and Classification of Waste for Segregation based on Machine Learning -- Healthcare Framework for Privacy-Preserving based on Hyperledger Fabric -- A Modified Approach for Accuracy Enhancement in Intruder Detection with Optimally Certain Features -- An Ensemble (CNN-LSTM) Model for Severity Detection of Bacterial Blight Rice Disease -- Intelligent Detection of DDoS Attack in IOT Network. |
| Record Nr. | UNINA-9910672448803321 |
| Singapore : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Mobile radio communications and 5G networks : proceedings of second MRCN 2021 / / edited by Nikhil Marriwala, [and three others]
| Mobile radio communications and 5G networks : proceedings of second MRCN 2021 / / edited by Nikhil Marriwala, [and three others] |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (687 pages) |
| Disciplina | 025.063510941 |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico | 5G mobile communication systems |
| ISBN |
981-16-7017-X
981-16-7018-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Editors and Contributors -- Manual and Automatic Control of Appliances Based on Integration of WSN and IOT Technology -- 1 Introduction -- 2 Related Work -- 2.1 Existing System -- 3 Proposed System -- 4 Hardware Implementation -- 4.1 Aurdino UNO -- 4.2 Bluetooth -- 4.3 PIR -- 4.4 Metal Detector -- 4.5 LDR Sensor -- 4.6 Water Level Sensor -- 4.7 Relay Module -- 4.8 GSM -- 5 Conclusion -- References -- Face Recognition System Based on Convolutional Neural Network (CNN) for Criminal Identification -- 1 Introduction -- 1.1 Convolution -- 1.2 ReLU -- 1.3 Pooling -- 2 Literature Survey -- 2.1 Uchôa, Britto, Veras, Aires and Paiva [1] -- 2.2 Srivastava, Dubey and Murali [2] -- 2.3 Mr. Deepak B. Desai, Prof. Kavitha S. N. [3] -- 2.4 Radhika C. and Bazeshree V. [4] -- 2.5 C. Nagpal and S. R. Dubey [5] -- 2.6 E. Winarno, H. Februariyanti, Anwar and I. H. Al Amin [6] -- 2.7 Yinfa Yan, Cheng Li, Yuanyuan Lu [7] -- 2.8 Anugrah Bintang Perdana, Adhi Prahara [8] -- 3 Implementation and Result Analysis -- 4 Conclusion -- References -- A Novel Support Vector Machine-Red Deer Optimization Algorithm for Enhancing Energy Efficiency of Spectrum Sensing in Cognitive Radio Network -- 1 Introduction -- 2 Related Works -- 3 Energy-Efficient Optimization Factor -- 3.1 The EE Through Spectrum Sensing and Data Transfer in Terms of Overall Opportunistic Throughput and Energy Utilization -- 3.2 System Model for Sensing the Spectrum -- 4 Description of Conventional Red Deer Algorithm and Support Vector Machine -- 4.1 Red Deer Algorithm -- 4.2 Support Vector Machine (SVM) -- 5 Proposed Methodology: Support Vector Machine-Red Deer Algorithm (SVM-RDA) -- 6 Simulation Results -- 6.1 Simulation Results of the Optimization Algorithms -- 7 Conclusion -- References.
Deceptive Product Review Identification Framework Using Opinion Mining and Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Experimental Results -- 5 Feature Extraction -- 6 Conclusion -- References -- Detecting Six Different Types of Thyroid Diseases Using Deep Learning -- 1 Introduction -- 2 Related Work -- 3 Objective -- 4 Motivation -- 5 Existing System -- 6 Proposed System -- 7 Architecture Diagram -- 8 Modules -- 9 Algorithm -- 10 Flow Chart -- 11 Workflow -- 12 Conclusion -- References -- Random Forest Classifier Used for Modelling and Classification of Herbal Plants Considering Different Features Using Machine Learning -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Image Acquisition -- 3.2 Preprocessing -- 3.3 Feature Extraction -- 3.4 Classification -- 3.5 Performance Evaluation -- 4 Result and Discussion -- 4.1 Discussion (Using Random Forest Model) -- 5 Conclusion -- References -- EEG Based Emotion Classification Using Xception Architecture -- 1 Introduction -- 2 Related Work -- 2.1 Xception Model -- 3 Materials and Methods -- 3.1 Proposed Methodology -- 3.2 Dataset -- 3.3 Implementation -- 4 Results -- 5 Conclusion -- References -- Automated Discovery and Patient Monitoring of nCOVID-19: A Multicentric In Silico Rapid Prototyping Approach -- 1 Introduction -- 2 Related Works -- 3 Proposed Algorithm and Methodology -- 3.1 Training of Network -- 3.2 Algorithms Used -- 4 Empirical Results -- 5 Conclusion and Future Research Directions -- References -- Estimation of Location and Fault Types Detection Using Sequence Current Components in Distribution Cable System Using ANN -- 1 Introduction -- 2 MATLAB Simulink Model of Distribution Underground Cable -- 3 Collection of DATA -- 4 Simulation Results -- 5 Conclusion -- References. LabVIEW Implemented Smart Security System Using National Instruments myRIO -- 1 Introduction -- 2 Technical Approach -- 3 Methodology -- 3.1 Module 1: Buzzer Code -- 3.2 Module 2: Camera Code -- 3.3 Module 3: Email Code -- 4 Experimental Results -- 4.1 Detection of the Movement -- 4.2 Streaming Video Being Recorded -- 4.3 Mail Attachment to the Registered Account -- 5 Conclusion -- References -- Design and Analysis of Modified Sense Amplifier-Based 6/3T SRAM Using CMOS 45 nm Technology -- 1 Literature Survey -- 2 Introduction -- 3 Implementation -- 3.1 Conventional Sense Amplifier -- 4 Experimental Results Comparison -- 5 Conclusion and Future Scope -- References -- Design and Implementation of Low Power GDI-LFSR at Low-Static Power Consumption -- 1 Introduction -- 2 Literature Survey -- 3 Implementation -- 3.1 CMOS D Flip Flop -- 3.2 CMOS GDI Linear Feedback Shift Register (LFSR) -- 3.3 IDDQ Test -- 4 Conclusion -- References -- Lion Optimization Algorithm for Antenna Selection in Cognitive Radio Networks -- 1 Introduction -- 2 Lion Optimization Algorithm -- 3 LOA for Transmit Antenna Selection(TAS) in Cognitive Radio Networks -- 4 Results -- 5 Conclusions and Future Scope -- References -- Sub-band Selection-Based Dimensionality Reduction Approach for Remote Sensing Hyperspectral Images -- 1 Introduction -- 2 Literature Survey -- 3 High Dimensional Reduction Technique -- 3.1 Feature Selection -- 3.2 Feature Extraction -- 4 Results and Discussion -- 4.1 Salinas Dataset -- 4.2 Sub-band Selection -- 5 Conclusion -- References -- An Efficient Network Intrusion Detection System Based on Feature Selection Using Evolutionary Algorithm Over Balanced Dataset -- 1 Introduction -- 2 Related Work -- 3 Dataset Used -- 3.1 NSL KDD Dataset -- 4 Intrusion Detection Process -- 4.1 Data Preprocessing -- 4.2 Data Sampling -- 4.3 Feature Selection -- 4.4 Classification. 5 Results and Discussion -- 5.1 Impact of Class Imbalance -- 5.2 Performance of the Proposed Work -- 6 Conclusion -- References -- A Novel Hybrid Imputation Method to Predict Missing Values in Medical Datasets -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 3.1 Methodology -- 3.2 State-of-the-Art Imputation Methods -- 3.3 Classifiers -- 3.4 Performance Parameter -- 4 Results and Discussion -- 5 Conclusion and Future Scope -- References -- Optimal LQR and Smith Predictor Based PID Controller Design for NMP System -- 1 Introduction -- 2 Description of Non-minimum Phase System -- 3 PID Controller -- 3.1 Ziegler-Nichols (Z-N) and Related Methods -- 3.2 The Chein, Hrones and Reswick Method -- 4 The Smith Predictor General Structure -- 5 Linear Quadratic Regulator (LQR) -- 6 Results and Discussions -- 7 Conclusion -- References -- Detection of Cracks in Surfaces and Materials Using Convolutional Neural Network -- 1 Introduction -- 1.1 Types of Concrete Cracks -- 1.2 Types of Cracks on Mechanical Components -- 1.3 Effects of Crack in Structures -- 2 Literature Review -- 3 Objectives -- 4 Proposed Solution -- 4.1 CNN -- 5 Methodology -- 5.1 Stage 1 -- 5.2 Stage 2 -- 5.3 Stage 3 -- 6 Experimental Results -- 6.1 Images with Crack -- 6.2 Images Without Crack -- 7 Conclusion -- References -- Performance Analysis of TDM-PON and WDM-PON -- 1 Introduction -- 2 Optical Network -- 3 System Modeling -- 3.1 TDM-PON -- 3.2 Unidirectional WDM-PON -- 4 Results and Discussion -- 4.1 Performance Analysis of Unidirectional TDM-PON -- 4.2 Performance Analysis of Unidirectional WDM-PON -- 5 Conclusion -- References -- Detection of Microcalcifications in Mammograms Using Edge Detection Operators and Clustering Algorithms -- 1 Introduction -- 2 Related Work -- 3 Preprocessing -- 3.1 Brightness Preserving Bi-Histogram Equalization (BBHE) -- 4 Segmentation. 4.1 Fuzzy C-Means Clustering -- 4.2 K-Means Clustering -- 5 Experimental Analysis -- 6 Conclusion and Future Scope -- References -- Analysis of the Proposed CNN Model for the Recognition of Gurmukhi Handwritten City Names of Punjab -- 1 Introduction -- 2 Methodology -- 2.1 Dataset -- 2.2 Digitization and Pre-processing -- 2.3 Processing -- 3 Experiments and Results -- 3.1 Recognition Results Achieved by Using LR of 0.00001 -- 3.2 Recognition Results Achieved by Using LR of 0.0001 -- 3.3 Recognition Results Achieved by Using LR of 0.001 -- 3.4 Recognition Results Achieved by Using LR of 0.01 -- 3.5 Recognition Results Achieved by Using LR of 0.1 -- 4 Comparative Analysis of Different LRs -- 5 Conclusion -- References -- Modeling and Analysis of Positive Feedback Adiabatic Logic CMOS-Based 2:1 Mux and Full Adder and Its Power Dissipation Consideration -- 1 Introduction -- 2 PFAL Design and Modeling -- 3 Results and Discussions -- 4 Conclusion -- References -- A Smart Healthcare System Based on Classifier DenseNet 121 Model to Detect Multiple Diseases -- 1 Introduction -- 1.1 Deep Learning -- 1.2 Background -- 2 Related Works -- 3 Materials and Methods -- 3.1 Pathology Chest X-Ray Dataset and Specification -- 3.2 Preprocessing of Data -- 3.3 Transfer Learning -- 3.4 Model Deployment -- 4 Results and Discussions -- 5 Conclusion and Future Work Scope -- References -- An Effective Algorithm of Remote Sensing Image Fusion Based on Discrete Wavelet Transform -- 1 Introduction -- 1.1 Continuous Wavelet Transforms (CWT) -- 1.2 Discrete Wavelet Transforms (DWT) -- 2 Wavelets for 2D Signals -- 3 Proposed Model -- 4 Image Fusion Using Different Fusion Arithmetic Operations -- 5 Conclusion -- References -- QoS-Based Load Balancing in Fog Computing -- 1 Introduction -- 2 Related Work -- 3 Proposed Architecture -- 3.1 Success Rate of Node i (SVi). 3.2 VM Availability (VAi). |
| Record Nr. | UNINA-9910743239503321 |
| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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