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Artificial Intelligence-Enabled Businesses : How to Develop Strategies for Innovation
| Artificial Intelligence-Enabled Businesses : How to Develop Strategies for Innovation |
| Autore | Dixit Sweta |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2025 |
| Descrizione fisica | 1 online resource (544 pages) |
| Altri autori (Persone) |
MauryaMohit
JainVishal SubramaniamGeetha |
| ISBN |
9781394233991
139423399X 9781394234004 1394234007 9781394234028 1394234023 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910913799903321 |
Dixit Sweta
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| Newark : , : John Wiley & Sons, Incorporated, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Blockchain-Enabled Solutions for the Pharmaceutical Industry
| Blockchain-Enabled Solutions for the Pharmaceutical Industry |
| Autore | Wason Ritika |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2025 |
| Descrizione fisica | 1 online resource (580 pages) |
| Altri autori (Persone) |
AroraParul
NandParma JainVishal KukrejaVinay |
| ISBN |
9781394287956
139428795X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910918259403321 |
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Wason Ritika
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| Newark : , : John Wiley & Sons, Incorporated, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Cyber-Physical Systems : Foundations and Techniques
| Cyber-Physical Systems : Foundations and Techniques |
| Autore | Sharma Uzzal |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2022 |
| Descrizione fisica | 1 online resource (340 pages) |
| Altri autori (Persone) |
NandParma
ChatterjeeJyotir Moy JainVishal JhanjhiNoor Zaman SujathaR |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-119-83663-8
1-119-83662-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910585797703321 |
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Sharma Uzzal
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| Newark : , : John Wiley & Sons, Incorporated, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Deep Learning for Personalized Healthcare Services / / ed. by Vishal Jain, Hadi Hedayati, Salahddine Krit, Omer Deperlioglu, Jyotir Moy Chatterjee
| Deep Learning for Personalized Healthcare Services / / ed. by Vishal Jain, Hadi Hedayati, Salahddine Krit, Omer Deperlioglu, Jyotir Moy Chatterjee |
| Pubbl/distr/stampa | Berlin ; ; Boston : , : De Gruyter, , [2021] |
| Descrizione fisica | 1 online resource (XVIII, 250 p.) |
| Collana | Intelligent Biomedical Data Analysis |
| Soggetto topico | COMPUTERS / Social Aspects / General |
| Soggetto genere / forma | Electronic books. |
| ISBN | 3-11-070812-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter -- Preface -- Acknowledgments -- Contents -- Short Biography of Editors -- List of Contributors -- Deep learning for health and medicine -- Exploring Indian Yajna and mantra sciences for personalized health: pandemic threats and possible cures in twenty-first-century healthcare -- Advanced deep learning techniques and applications in healthcare services -- Visualizations of human bioelectricity with internal symptom captures: the Indo-Vedic concepts on Healthcare 4.0 -- Early cancer predictions using ensembles of machine learning and deep learning -- Deep learning in patient management and clinical decision making -- Patient health record system -- Prediction of multiclass cervical cancer using deep machine learning algorithms in healthcare services -- Comparative analysis for detecting skin cancer using SGD-based optimizer on a CNN versus DCNN architecture and ResNet-50 versus AlexNet on Adam optimizer -- Coronary heart disease analysis using two deep learning algorithms, CNN and RNN, and their sensitivity analyses -- An overview of the technological performance of deep learning in modern medicine -- Index |
| Record Nr. | UNINA-9910554282103321 |
| Berlin ; ; Boston : , : De Gruyter, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Machine Learning with Health Care Perspective : Machine Learning and Healthcare / / edited by Vishal Jain, Jyotir Moy Chatterjee
| Machine Learning with Health Care Perspective : Machine Learning and Healthcare / / edited by Vishal Jain, Jyotir Moy Chatterjee |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (418 pages) |
| Disciplina | 610.28563 |
| Collana | Learning and Analytics in Intelligent Systems |
| Soggetto topico |
Computational intelligence
Biomedical engineering Computational Intelligence Biomedical Engineering and Bioengineering |
| ISBN | 3-030-40850-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1: Machine learning for Healthcare: Introduction -- Chapter 2: Artificial Intelligence in Medical Diagnosis: Methods, algorithms and applications -- Chapter 3: Intelligent Learning Analytics in Healthcare Sector Using Machine Learning -- Chapter 4: Unsupervised Learning on Healthcare Survey Data with Particle Swarm Optimization -- Chapter 5: Machine Learning for Healthcare Diagnostics -- Chapter 6: Disease Detection System (DDS) Using Machine Learning Technique -- Chapter 7: Knowledge Discovery (Feature Identification) from Teeth, Wrist and Femur Images to determine Human Age and Gender -- Chapter 8: Deep Learning Solutions for Skin Cancer Detection and Diagnosis -- Chapter 9: Security of Healthcare Systems with Smart Health Records using Cloud Technology -- Chapter 10: Intelligent Heart Disease Prediction on Physical and Mental Parameters: A ML Based IoT and Big Data Application and Analysis -- Chapter 11: Medical Text and image processing: Applications, issues and challenges -- Chapter 12: Machine Learning Methods for Managing Parkinson’s Disease -- Chapter 13: An Efficient Method for Computer-aided Diagnosis of Cardiac Arrhythmias -- Chapter 14: Clinical decision support systems and predictive analytics -- Chapter 15: Yajna and Mantra Science Bringing Health and Comfort to Indo-Asian Public: A Healthcare 4.0 Approach and Computational Study -- Chapter 16: Identifying Diseases and Diagnosis using Machine Learning. |
| Record Nr. | UNINA-9910483000003321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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The smart cyber ecosystem for sustainable development / / edited by Pardeep Kumar, Vishal Jain, Vasaki Ponnusamy
| The smart cyber ecosystem for sustainable development / / edited by Pardeep Kumar, Vishal Jain, Vasaki Ponnusamy |
| Pubbl/distr/stampa | Hoboken, NJ : , : John Wiley & Sons, Inc., , [2021] |
| Descrizione fisica | 1 online resource (480 pages) |
| Disciplina | 006.3 |
| Soggetto topico |
Artificial intelligence
Internet of things Computer networks - Social aspects |
| ISBN |
1-119-76166-2
1-119-76165-4 1-119-76167-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910554856203321 |
| Hoboken, NJ : , : John Wiley & Sons, Inc., , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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The smart cyber ecosystem for sustainable development / / edited by Pardeep Kumar, Vishal Jain, Vasaki Ponnusamy
| The smart cyber ecosystem for sustainable development / / edited by Pardeep Kumar, Vishal Jain, Vasaki Ponnusamy |
| Pubbl/distr/stampa | Hoboken, NJ : , : John Wiley & Sons, Inc., , [2021] |
| Descrizione fisica | 1 online resource (480 pages) |
| Disciplina | 006.3 |
| Soggetto topico |
Artificial intelligence
Internet of things Computer networks - Social aspects |
| ISBN |
1-119-76166-2
1-119-76165-4 1-119-76167-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Half-Title Page -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Part 1: INTERNET OF THINGS -- 1 Voyage of Internet of Things in the Ocean of Technology -- 1.1 Introduction -- 1.1.1 Characteristics of IoT -- 1.1.2 IoT Architecture -- 1.1.3 Merits and Demerits of IoT -- 1.2 Technological Evolution Toward IoT -- 1.3 IoT-Associated Technology -- 1.4 Interoperability in IoT -- 1.5 Programming Technologies in IoT -- 1.5.1 Arduino -- 1.5.2 Raspberry Pi -- 1.5.3 Python -- 1.6 IoT Applications -- Conclusion -- References
2 AI for Wireless Network Optimization: Challenges and Opportunities -- 2.1 Introduction to AI -- 2.2 Self-Organizing Networks -- 2.2.1 Operation Principle of Self-Organizing Networks -- 2.2.2 Self-Configuration -- 2.2.3 Self-Optimization -- 2.2.4 Self-Healing -- 2.2.5 Key Performance Indicators -- 2.2.6 SON Functions -- 2.3 Cognitive Networks -- 2.4 Introduction to Machine Learning -- 2.4.1 ML Types -- 2.4.2 Components of ML Algorithms -- 2.4.3 How do Machines Learn? -- 2.4.4 ML and Wireless Networks -- 2.5 Software-Defined Networks -- 2.5.1 SDN Architecture -- 2.5.2 The OpenFlow Protocol 2.5.3 SDN and ML -- 2.6 Cognitive Radio Networks -- 2.6.1 Sensing Methods -- 2.7 ML for Wireless Networks: Challenges and Solution Approaches -- 2.7.1 Cellular Networks -- 2.7.2 Wireless Local Area Networks -- 2.7.3 Cognitive Radio Networks -- References -- 3 An Overview on Internet of Things (IoT) Segments and Technologies -- 3.1 Introduction -- 3.2 Features of IoT -- 3.3 IoT Sensor Devices -- 3.4 IoT Architecture -- 3.5 Challenges and Issues in IoT -- 3.6 Future Opportunities in IoT -- 3.7 Discussion -- 3.8 Conclusion -- References -- 4 The Technological Shift: AI in Big Data and IoT 4.1 Introduction -- 4.2 Artificial Intelligence -- 4.2.1 Machine Learning -- 4.2.2 Further Development in the Domain of Artificial Intelligence -- 4.2.3 Programming Languages for Artificial Intelligence -- 4.2.4 Outcomes of Artificial Intelligence -- 4.3 Big Data -- 4.3.1 Artificial Intelligence Methods for Big Data -- 4.3.2 Industry Perspective of Big Data -- 4.4 Internet of Things -- 4.4.1 Interconnection of IoT With AoT -- 4.4.2 Difference Between IIoT and IoT -- 4.4.3 Industrial Approach for IoT -- 4.5 Technical Shift in AI, Big Data, and IoT 4.5.1 Industries Shifting to AI-Enabled Big Data Analytics -- 4.5.2 Industries Shifting to AI-Powered IoT Devices -- 4.5.3 Statistical Data of These Shifts -- 4.6 Conclusion -- References -- 5 IoT's Data Processing Using Spark -- 5.1 Introduction -- 5.2 Introduction to Apache Spark -- 5.2.1 Advantages of Apache Spark -- 5.2.2 Apache Spark's Components -- 5.3 Apache Hadoop MapReduce -- 5.3.1 Limitations of MapReduce -- 5.4 Resilient Distributed Dataset (RDD) -- 5.4.1 Features and Limitations of RDDs -- 5.5 DataFrames -- 5.6 Datasets -- 5.7 Introduction to Spark SQL -- 5.7.1 Spark SQL Architecture |
| Record Nr. | UNINA-9910676561303321 |
| Hoboken, NJ : , : John Wiley & Sons, Inc., , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The smart cyber ecosystem for sustainable development / / edited by Pardeep Kumar, Vishal Jain, Vasaki Ponnusamy
| The smart cyber ecosystem for sustainable development / / edited by Pardeep Kumar, Vishal Jain, Vasaki Ponnusamy |
| Pubbl/distr/stampa | Hoboken, NJ : , : John Wiley & Sons, Inc., , [2021] |
| Descrizione fisica | 1 online resource (480 pages) |
| Disciplina | 006.3 |
| Soggetto topico |
Artificial intelligence
Internet of things Computer networks - Social aspects |
| ISBN |
1-119-76166-2
1-119-76165-4 1-119-76167-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Half-Title Page -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Part 1: INTERNET OF THINGS -- 1 Voyage of Internet of Things in the Ocean of Technology -- 1.1 Introduction -- 1.1.1 Characteristics of IoT -- 1.1.2 IoT Architecture -- 1.1.3 Merits and Demerits of IoT -- 1.2 Technological Evolution Toward IoT -- 1.3 IoT-Associated Technology -- 1.4 Interoperability in IoT -- 1.5 Programming Technologies in IoT -- 1.5.1 Arduino -- 1.5.2 Raspberry Pi -- 1.5.3 Python -- 1.6 IoT Applications -- Conclusion -- References
2 AI for Wireless Network Optimization: Challenges and Opportunities -- 2.1 Introduction to AI -- 2.2 Self-Organizing Networks -- 2.2.1 Operation Principle of Self-Organizing Networks -- 2.2.2 Self-Configuration -- 2.2.3 Self-Optimization -- 2.2.4 Self-Healing -- 2.2.5 Key Performance Indicators -- 2.2.6 SON Functions -- 2.3 Cognitive Networks -- 2.4 Introduction to Machine Learning -- 2.4.1 ML Types -- 2.4.2 Components of ML Algorithms -- 2.4.3 How do Machines Learn? -- 2.4.4 ML and Wireless Networks -- 2.5 Software-Defined Networks -- 2.5.1 SDN Architecture -- 2.5.2 The OpenFlow Protocol 2.5.3 SDN and ML -- 2.6 Cognitive Radio Networks -- 2.6.1 Sensing Methods -- 2.7 ML for Wireless Networks: Challenges and Solution Approaches -- 2.7.1 Cellular Networks -- 2.7.2 Wireless Local Area Networks -- 2.7.3 Cognitive Radio Networks -- References -- 3 An Overview on Internet of Things (IoT) Segments and Technologies -- 3.1 Introduction -- 3.2 Features of IoT -- 3.3 IoT Sensor Devices -- 3.4 IoT Architecture -- 3.5 Challenges and Issues in IoT -- 3.6 Future Opportunities in IoT -- 3.7 Discussion -- 3.8 Conclusion -- References -- 4 The Technological Shift: AI in Big Data and IoT 4.1 Introduction -- 4.2 Artificial Intelligence -- 4.2.1 Machine Learning -- 4.2.2 Further Development in the Domain of Artificial Intelligence -- 4.2.3 Programming Languages for Artificial Intelligence -- 4.2.4 Outcomes of Artificial Intelligence -- 4.3 Big Data -- 4.3.1 Artificial Intelligence Methods for Big Data -- 4.3.2 Industry Perspective of Big Data -- 4.4 Internet of Things -- 4.4.1 Interconnection of IoT With AoT -- 4.4.2 Difference Between IIoT and IoT -- 4.4.3 Industrial Approach for IoT -- 4.5 Technical Shift in AI, Big Data, and IoT 4.5.1 Industries Shifting to AI-Enabled Big Data Analytics -- 4.5.2 Industries Shifting to AI-Powered IoT Devices -- 4.5.3 Statistical Data of These Shifts -- 4.6 Conclusion -- References -- 5 IoT's Data Processing Using Spark -- 5.1 Introduction -- 5.2 Introduction to Apache Spark -- 5.2.1 Advantages of Apache Spark -- 5.2.2 Apache Spark's Components -- 5.3 Apache Hadoop MapReduce -- 5.3.1 Limitations of MapReduce -- 5.4 Resilient Distributed Dataset (RDD) -- 5.4.1 Features and Limitations of RDDs -- 5.5 DataFrames -- 5.6 Datasets -- 5.7 Introduction to Spark SQL -- 5.7.1 Spark SQL Architecture |
| Record Nr. | UNINA-9910824961003321 |
| Hoboken, NJ : , : John Wiley & Sons, Inc., , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||