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5G Edge Computing : Technologies, Applications and Future Visions / / by Xiao Ma, Mengwei Xu, Qing Li, Yuanzhe Li, Ao Zhou, Shangguang Wang
| 5G Edge Computing : Technologies, Applications and Future Visions / / by Xiao Ma, Mengwei Xu, Qing Li, Yuanzhe Li, Ao Zhou, Shangguang Wang |
| Autore | Ma Xiao |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (209 pages) |
| Disciplina | 005.758 |
| Altri autori (Persone) |
XuMengwei
LiQing LiYuanzhe ZhouAo WangShangguang |
| Soggetto topico |
Mobile computing
Cloud computing Algorithms Electronic digital computers - Evaluation Computational complexity Mobile Computing Cloud Computing Design and Analysis of Algorithms System Performance and Evaluation Computational Complexity |
| ISBN | 9789819702138 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Background -- Chapter 2. Recent Advancements of Public Edge Platforms -- Chapter 3. Edge Workload Prediction based on Deep Learning -- Chapter 4. Edge Computing based Computation Offloading -- Chapter 5. DynamicWorkload Scheduling in Edge Computing -- Chapter 6. Edge Service Caching -- Chapter 7. Edge Resource Provisioning -- Chapter 8. Edge Computing for 5G and 5G-based Mobile Edge Computing System -- Chapter 9. Visions of Edge Computing in 6G -- Chapter 10 Conclusions and Future Directions. |
| Record Nr. | UNINA-9910855384903321 |
Ma Xiao
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in Data-Driven Computing and Intelligent Systems : Selected Papers from ADCIS 2023, Volume 2 / / edited by Swagatam Das, Snehanshu Saha, Carlos A. Coello Coello, Jagdish C. Bansal
| Advances in Data-Driven Computing and Intelligent Systems : Selected Papers from ADCIS 2023, Volume 2 / / edited by Swagatam Das, Snehanshu Saha, Carlos A. Coello Coello, Jagdish C. Bansal |
| Autore | Das Swagatam |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (536 pages) |
| Disciplina | 621.382 |
| Altri autori (Persone) |
SahaSnehanshu
Coello CoelloCarlos A BansalJagdish C |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Telecommunication
Electronic circuits Cloud computing Artificial intelligence Signal processing Communications Engineering, Networks Electronic Circuits and Systems Cloud Computing Artificial Intelligence Signal, Speech and Image Processing |
| ISBN |
9789819995219
9819995213 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Deep learning models for classification of remotely sensed data of sugarcane -- Detection and Analysis of Wormhole Attacks in the AODV Routing Protocol with IEEE 802.11p for the Internet of Vehicles -- A Systematic Review of NLP Applications in Clinical Healthcare: Advancement and Challenges -- An Investigational Analysis of Automatic Speech Recognition on Deep Neural Networks and Gated Recurrent Unit Model -- Matched Filter and Kirsch’s Template based approach for Retinal Vessel Segmentation -- Prediction of abnormality in kidney function using classification techniques and fuzzy systems -- Implementation of Parallel Applications on the Hypercube Topology by Using Multistage Network -- Integrating Artificial Intelligence for Adaptive Decision-Making in Complex System -- Qualitative Research Reasoning on Dementia Fore-cast using Machine Learning Techniques -- Implementation of Vision Transformers on SPECT Heart Dataset: A Comparative Study -- CSR U-Net: A Novel Approach for Enhanced Skin CancerLesion Image Segmentation -- Automatic Detection and Classification System for Mesothelioma Cancer using Deep Learning Models with HPO -- A systematic literature survey on IoT in Healthcare: Security and Privacy Threats -- Hybrid Deep Learning Framework for Glaucoma Detection Using Fundus Images -- Sunflower Optimization with Elite Learning Strategy (SFO-ELS) for Antenna Selection in Massive MIMO Sub Array Switching Architecture -- Machine Learning Models for Human Activity Recognition: A Comparative Study. |
| Record Nr. | UNINA-9910841868803321 |
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Das Swagatam
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in Data-Driven Computing and Intelligent Systems : Selected Papers from ADCIS 2022, Volume 1 / / edited by Swagatam Das, Snehanshu Saha, Carlos A. Coello Coello, Jagdish Chand Bansal
| Advances in Data-Driven Computing and Intelligent Systems : Selected Papers from ADCIS 2022, Volume 1 / / edited by Swagatam Das, Snehanshu Saha, Carlos A. Coello Coello, Jagdish Chand Bansal |
| Autore | Das Swagatam |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (885 pages) |
| Disciplina | 006.33 |
| Altri autori (Persone) |
SahaSnehanshu
Coello CoelloCarlos A BansalJagdish Chand |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Telecommunication
Electronic circuits Cloud computing Artificial intelligence Signal processing Communications Engineering, Networks Electronic Circuits and Systems Cloud Computing Artificial Intelligence Signal, Speech and Image Processing |
| ISBN |
9789819932504
9819932505 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Editors and Contibutors -- Adaptive Volterra Noise Cancellation Using Equilibrium Optimizer Algorithm -- 1 Introduction -- 2 Problem Formulation -- 3 Proposed Equilibrium Optimizer Algorithm-Based Adaptive Volterra Noise Cancellation -- 3.1 Gbest -- 3.2 Exploration Stage (F) -- 3.3 Exploitation Stage (Rate of Generation G) -- 4 Simulation Outcomes -- 4.1 Qualitative Performance Analysis -- 4.2 Quantitative Performance Analysis -- 5 Conclusion and Scope -- References -- SHLPM: Sentiment Analysis on Code-Mixed Data Using Summation of Hidden Layers of Pre-trained Model -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 BERT -- 3.2 RoBERTa -- 3.3 SHLPM -- 4 Implementation Details -- 4.1 Dataset and Pre-processing -- 4.2 SHLPM-BERT -- 4.3 SHLPM-XLM-RoBERTa -- 5 Results and Discussion -- 6 Conclusion -- References -- Comprehensive Analysis of Online Social Network Frauds -- 1 Introduction -- 1.1 Statistics of Online Social Network Frauds -- 2 Interrelationship between OSN Frauds, Social Network Threats, and Cybercrime -- 3 Types of Frauds in OSN -- 3.1 Social Engineering Frauds (SEF) -- 3.2 Human-Targeted Frauds (Child/Adults) -- 3.3 False Identity -- 3.4 Misinformation -- 3.5 E-commerce Fraud (Consumer Frauds) -- 3.6 Case Study for Facebook Security Fraud -- 4 OSN Frauds Detection Using Machine Learning -- 4.1 Pros and Cons -- 5 Conclusion -- References -- Electric Vehicle Control Scheme for V2G and G2V Mode of Operation Using PI/Fuzzy-Based Controller -- 1 Introduction -- 2 Motivation -- 3 System Description -- 4 Mathematical Model Equipments Used -- 4.1 Bidirectional AC-DC Converter -- 4.2 Bidirectional Buck-Boost Converter -- 4.3 Battery Modeling -- 4.4 Control of 1-∅-Based Bidirectional AC-DC Converter Strategy -- 5 Fuzzy Logic Controller -- 6 Control Strategy -- 6.1 Constant Voltage Strategy.
6.2 Constant Current Strategy -- 7 Results and Discussion -- 7.1 PI Controller -- 7.2 Fuzzy Logic Controller -- 7.3 Comparison of Harmonic Profile -- 8 Conclusion -- References -- Experimental Analysis of Skip Connections for SAR Image Denoising -- 1 Introduction -- 2 Related Works -- 2.1 Residual Network -- 2.2 Existing ResNet-Based Denoising Works -- 3 Implementation of the Different Patterns of Skip Connections -- 3.1 Datasets and Pre-processing -- 3.2 Loss Function -- 4 Results and Discussions -- 4.1 Denoising Results on Synthetic Images -- 4.2 Denoising Results on Real SAR Images -- 5 Conclusion -- References -- A Proficient and Economical Approach for IoT-Based Smart Doorbell System -- 1 Introduction -- 2 Literature Review -- 3 System Design and Implementation -- 3.1 System Design -- 3.2 Implementation -- 4 Results and Discussion -- 4.1 Performance Results -- 4.2 Comparison with an Existing System -- 4.3 Cost Analysis -- 5 Limitations -- 6 Conclusion -- References -- Predicting Word Importance Using a Support Vector Regression Model for Multi-document Text Summarization -- 1 Introduction -- 2 Related Work -- 3 Description of Dataset -- 4 Proposed Methodology -- 4.1 Preprocessing -- 4.2 Word Importance Prediction Using Support Vector Regression Model -- 4.3 Sentence Scoring -- 4.4 Summary Generation -- 5 Evaluation, Experiment, and Results -- 5.1 Evaluation -- 5.2 Experiment -- 5.3 Results -- 6 Conclusion and Future Works -- References -- A Comprehensive Survey on Deep Learning-Based Pulmonary Nodule Identification on CT Images -- 1 Introduction -- 2 Datasets and Experimental Setup -- 2.1 LIDC/IDRI Dataset -- 2.2 LUNA16 Dataset -- 2.3 NLST Dataset -- 2.4 KAGGLE DATA SCIENCE BOWL (KDSB) Dataset -- 2.5 VIA/I-ELCAP -- 2.6 NELSON -- 2.7 Others -- 3 CAD System Structure -- 3.1 Data Acquisition -- 3.2 Preprocessing -- 3.3 Lung Segmentation. 3.4 Candidate Nodule Detection -- 3.5 False Positive Reduction -- 3.6 Nodule Categorization -- 4 CNN -- 4.1 Overview -- 4.2 CNN Architectures for Medical Imaging -- 4.3 Unique Characteristics of CNNs -- 4.4 CNN Software and Hardware Equipment -- 4.5 CNNs versus Conventional Models -- 5 Discussion -- 5.1 Research Trends -- 5.2 Challenges and Future Directions -- 6 Conclusion -- References -- Comparative Study on Various CNNs for Classification and Identification of Biotic Stress of Paddy Leaf -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 Proposed Methods -- 3 Experimental Results -- 3.1 Hardware Setup -- 3.2 Time Analysis with respect to GPU and CPU -- 3.3 Performance Analysis for Keras and PyTorch -- 3.4 Performance Analysis of CNN Models -- 3.5 Comparison of the Proposed CNN with Other State-of-the-Art Works -- 4 Conclusion -- References -- Studies on Machine Learning Techniques for Multivariate Forecasting of Delhi Air Quality Index -- 1 Introduction -- 2 Materials and Methodology -- 2.1 Delhi AQI Multivariate Data -- 2.2 Methodology -- 3 Experimental Setup and Simulation Results -- 4 Contrast Analysis Considering Dimensionality Reduction -- 5 Conclusions -- References -- Fine-Grained Voice Discrimination for Low-Resource Datasets Using Scalogram Images -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 3.1 Collection of Voice Dataset -- 3.2 Preprocessing of Available Dataset to Increase the Trainable Samples -- 3.3 Classification of Phonemes Using Deep Convolutional Neural Network (DCNN)-Based Image Classifiers -- 4 Implementation Result and Analysis -- 5 Conclusion and Future Work -- References -- Sign Language Recognition for Indian Sign Language -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Dataset -- 3.2 Data Preprocessing -- 3.3 Data Splitting -- 3.4 Data Augmentation -- 3.5 Model Compilation. 3.6 Model Training and Testing -- 4 Results -- 5 Novelty and Future Work -- 6 Conclusion -- References -- Buffering Performance of Optical Packet Switch Consisting of Hybrid Buffer -- 1 Introduction -- 2 Literature Survey -- 3 Description of the Optical Packet Switch -- 4 Simulation Results -- 4.1 Bernoulli Process -- 4.2 Results -- 5 Conclusions -- References -- Load Balancing using Probability Distribution in Software Defined Network -- 1 Introduction -- 2 Related Work -- 3 Grouping of Controllers in SDN -- 4 Load Balancing in SDN -- 4.1 Simulation and Evaluation Result -- 5 Conclusion -- References -- COVID Prediction Using Different Modality of Medical Imaging -- 1 Introduction -- 2 Principles of Support Vector Machine (SVM) -- 2.1 Linear Case -- 2.2 Nonlinear Case -- 3 Material and Methods -- 3.1 CT Image Dataset -- 3.2 X-Ray Image Dataset -- 3.3 Ultrasound Image Dataset -- 4 The Proposed Model -- 5 Experimental Result -- 6 Conclusion -- References -- Optimizing Super-Resolution Generative Adversarial Networks -- 1 Introduction -- 2 Related Work -- 3 Dataset -- 3.1 Training Dataset -- 3.2 Test Dataset -- 4 Proposed Methodology -- 5 Performance Metrics -- 5.1 Peak Signal-to-Noise Ratio (PSNR) -- 5.2 Structural Similarity Index (SSIM) -- 6 Results and Discussion -- 7 Conclusion -- References -- Prediction of Hydrodynamic Coefficients of Stratified Porous Structure Using Artificial Neural Network (ANN) -- 1 Introduction -- 2 Stratified Porous Structure -- 3 Experimental Setup -- 4 Artificial Neural Network -- 4.1 Dataset Used for ANN -- 4.2 ANN Model -- 5 Results and Discussions -- 6 Conclusions -- References -- Performance Analysis of Machine Learning Algorithms for Landslide Prediction -- 1 Introduction -- 2 Literature Survey -- 3 Methodology of the Performance Analysis Work -- 3.1 Data Acquisition Layer -- 3.2 Fog Layer -- 3.3 Cloud Layer. 4 Performance Analysis and Results -- 5 Conclusion -- References -- Brain Hemorrhage Classification Using Leaky ReLU-Based Transfer Learning Approach -- 1 Introduction -- 2 Related Works -- 3 Materials and Method -- 3.1 Dataset -- 3.2 Transfer Learning -- 3.3 ResNet50 -- 4 Proposed Methodology -- 4.1 Input Dataset -- 4.2 Pre-processing -- 4.3 Network Training -- 4.4 Transfer Learning-Based Feature Extraction -- 5 Results -- 6 Conclusion -- References -- Factors Affecting Learning the First Programming Language of University Students -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Collection -- 3.2 Experimental Design -- 3.3 Data Analysis -- 4 Result -- 4.1 Findings -- 5 Decision and Conclusion -- References -- Nature-Inspired Hybrid Virtual Machine Placement Approach in Cloud -- 1 Introduction -- 2 Related Work -- 3 Problem Formulation -- 4 Proposed Framework -- 4.1 Intelligent Water Drops (IWD) Algorithm -- 4.2 Water Cycle Algorithm (WCA) -- 4.3 Intelligent Water Drop Cycle Algorithm (IWDCA) -- 5 Result -- 5.1 Experiment Setup -- 5.2 Simulation Analysis of IWDCA -- 6 Conclusion -- References -- Segmented ε-Greedy for Solving a Redesigned Multi-arm Bandit Environment -- 1 Introduction -- 2 Previous Works -- 3 Methodology -- 4 Results -- 5 Conclusion and Future Work -- References -- Data-Based Time Series Modelling of Industrial Grinding Circuits -- 1 Introduction -- 2 Formulation -- 2.1 Grinding Circuit -- 2.2 Least Square Support Vector Regression -- 2.3 Proposed Algorithm -- 3 Results and Discussions -- 3.1 Results of Proposed Algorithm -- 3.2 LS-SVR Model Performance -- 3.3 Comparison with Arbitrarily Selected Model -- 4 Conclusions -- References -- Computational Models for Prognosis of Medication for Cardiovascular Diseases -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusion -- References. Develop a Marathi Lemmatizer for Common Nouns and Simple Tenses of Verbs. |
| Record Nr. | UNINA-9910736981503321 |
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Das Swagatam
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in Data-Driven Computing and Intelligent Systems : Selected Papers from ADCIS 2023, Volume 1 / / edited by Swagatam Das, Snehanshu Saha, Carlos A. Coello Coello, Jagdish C. Bansal
| Advances in Data-Driven Computing and Intelligent Systems : Selected Papers from ADCIS 2023, Volume 1 / / edited by Swagatam Das, Snehanshu Saha, Carlos A. Coello Coello, Jagdish C. Bansal |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (553 pages) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Telecommunication
Electronic circuits Cloud computing Artificial intelligence Signal processing Communications Engineering, Networks Electronic Circuits and Systems Cloud Computing Artificial Intelligence Signal, Speech and Image Processing |
| ISBN | 981-9995-24-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Influences of specimen and fiber sizes on the direct tensile resistance of ultra-high-performance fiber-reinforced concretes -- Conceptual Model for Data Collection and Processing in a Smart Medical Ward -- Parts-of-Speech Tagger in Assamese using LSTM and Bi-LSTM -- Detection of Explicit Lyrics in Hindi Music Using Different Machine Learning Algorithms -- Does the Resilience learning game foster workforce open innovation and sustainability attributes? Empirical evidence from Greek food industry -- Seizure Detection by Analyzing EEG Signals Using Deep Learning Networks -- Enhancing Intelligent Video Surveillance: Deep Learning Approaches for Human Anomalous Behavior Recognition -- GujFormer: A Vision Transformer Based Architecture for Gujarati Handwritten Character Recognition -- Prediction of Soil Properties for Agriculture using Ensemble Learning Techniques/- Classification of organic and recyclable waste using a Deep learning approach -- Machine Learning and its Application in Food Safety.-ISO/IEC 27001 Standard: Analytical and Comparative Overview -- Hybrid Deep Learning based Potato and Tomato Leaf Disease Classification -- Anti-Forensic Analysis for Image Splicing Detection through Advanced Filters -- Classification and prediction of vibration natural frequencies of a circular plate using Chladni patterns and deep learning techniques -- Multi-Sensor Data Fusion and Deep Machine Learning Models based Mental Stress Detection System -- Segmentation-based Transformer Network for Automated Skin Disease Detection. |
| Record Nr. | UNINA-9910841865203321 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in Data-Driven Computing and Intelligent Systems : Selected Papers from ADCIS 2023, Volume 3 / / edited by Swagatam Das, Snehanshu Saha, Carlos A. Coello Coello, Jagdish C. Bansal
| Advances in Data-Driven Computing and Intelligent Systems : Selected Papers from ADCIS 2023, Volume 3 / / edited by Swagatam Das, Snehanshu Saha, Carlos A. Coello Coello, Jagdish C. Bansal |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (567 pages) |
| Disciplina | 929.605 |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Telecommunication
Electronic circuits Cloud computing Artificial intelligence Signal processing Communications Engineering, Networks Electronic Circuits and Systems Cloud Computing Artificial Intelligence Signal, Speech and Image Processing |
| ISBN | 981-9995-18-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A comprehensive review: Sentiment Analysis for Indian local Languages -- Face Recognition-Based Surveillance System -- Comparative Analysis of Malware Classification using Supervised Machine Learning Algorithms -- Noise filtering algorithm based on Machine learning for identification of ground hitting photons in Jaipur city -- Data-driven interior plan generation for residential buildings in Vietnam -- A weekly scheduling of operating theaters using Multi Agent Planner -- Using website content for detecting phishing URLs: A Novel approach -- Attention and Residual-Atrous Convolutional Learning-Based CNN Architecture for Lung Nodule Segmentation and Classification -- Adaptive Segmentation on Extracting Textural and Fractal Patterns for Assessing Mangrove Dynamics using Multi-spectral Data -- Exploring Multivariate Chemometric Tool for Simultaneous Determination of Erectile Dysfunction Drugs in Pharmaceutical Formulation -- Mass transport of combined oscillating electroosmotic and pressure drivenflow through cylindrical nanopore considering ion partitioning effects -- Audio Signal Analysis and Classification of Bluetooth Vulnerabilities using Machine Learning Techniques -- Performance Evaluation of Thresholding-based Segmentation Algorithms for Aerial Imagery -- Estimation of particle Froude Number in Deposited Bed Condition using Hybrid Machine Learning Models -- An Image based Automated Potato Leaf Disease Detection Model -- Unsupervised Synthetic Code-Mixed Data Generation -- Automated Building Segmentation in Areal images using Boundary Edge Detection. |
| Record Nr. | UNINA-9910845086203321 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in Data-Driven Computing and Intelligent Systems : Selected Papers from ADCIS 2023, Volume 4 / / edited by Swagatam Das, Snehanshu Saha, Carlos A. Coello Coello, Hemant Rathore, Jagdish Chand Bansal
| Advances in Data-Driven Computing and Intelligent Systems : Selected Papers from ADCIS 2023, Volume 4 / / edited by Swagatam Das, Snehanshu Saha, Carlos A. Coello Coello, Hemant Rathore, Jagdish Chand Bansal |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (517 pages) |
| Disciplina | 006.33 |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Telecommunication
Electronic circuits Cloud computing Artificial intelligence Signal processing Communications Engineering, Networks Electronic Circuits and Systems Cloud Computing Artificial Intelligence Signal, Speech and Image Processing |
| ISBN | 981-9995-31-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910847582703321 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in Data-driven Computing and Intelligent Systems : Selected Papers from ADCIS 2022, Volume 2 / / edited by Swagatam Das, Snehanshu Saha, Carlos A. Coello Coello, Jagdish Chand Bansal
| Advances in Data-driven Computing and Intelligent Systems : Selected Papers from ADCIS 2022, Volume 2 / / edited by Swagatam Das, Snehanshu Saha, Carlos A. Coello Coello, Jagdish Chand Bansal |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (892 pages) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Telecommunication
Electronic circuits Cloud computing Artificial intelligence Signal processing Communications Engineering, Networks Electronic Circuits and Systems Cloud Computing Artificial Intelligence Signal, Speech and Image Processing |
| ISBN | 981-9909-81-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Scenario Based Neural Network Model for Integrated Lighting Schemes in Residential Buildings -- Electrical Muscle Stimulation Models Identification Based on Hammerstein Structure and Gravitational Search Algorithm -- Experimental analysis of “A novel swarm intelligence optimization approach: sparrow search algorithm” -- Solving FJSP using Multi-agent system with GA -- A Comparative Analysis on Optimal Power Allocation and Pairing of User in Downlink NOMA System. |
| Record Nr. | UNINA-9910734847803321 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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AIIPCC 2021 : The Second International Conference on Artificial Intelligence, Information Processing and Cloud Computing
| AIIPCC 2021 : The Second International Conference on Artificial Intelligence, Information Processing and Cloud Computing |
| Edizione | [Neuerscheinung] |
| Pubbl/distr/stampa | Berlin, : VDE Verlag, 2021 |
| Descrizione fisica | Online-Ressource (125 S.) |
| Soggetto topico |
Cloud Computing
Artificial Intelligence Audio replay Information Processing Visualization method |
| ISBN | 3-8007-5616-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996574900403316 |
| Berlin, : VDE Verlag, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Analysis and Design of Next-Generation Software Architectures : Generative AI, Cybersecurity, and Cloud Computing / / by Arthur M. Langer
| Analysis and Design of Next-Generation Software Architectures : Generative AI, Cybersecurity, and Cloud Computing / / by Arthur M. Langer |
| Autore | Langer Arthur M |
| Edizione | [2nd ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (XV, 327 p. 162 illus., 31 illus. in color.) |
| Disciplina | 005.1 |
| Soggetto topico |
Software engineering
Artificial intelligence Data protection Cloud computing Quantum computers Cooperating objects (Computer systems) Software Engineering Artificial Intelligence Data and Information Security Cloud Computing Quantum Computing Cyber-Physical Systems |
| ISBN | 9783031762123 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Introduction -- 2. Merging Internal Users and Consumer Requirements -- 3. Reviewing the Object Paradigm -- 4. Distributed Client/Server and Data -- 5. The Impact of High-Speed Wireless Communication: 5G to 6G -- 6. The Internet of Things -- 7. Blockchain Analysis and Design -- 8. Quantum Computing, AI, ML, and the Cloud -- 9. Generative AI and Systems Architecture -- 10. Cyber Security in Analysis and Design. |
| Record Nr. | UNINA-9911003591303321 |
|
Langer Arthur M
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Ansible for Kubernetes by Example : Automate Your Kubernetes Cluster with Ansible / / by Luca Berton
| Ansible for Kubernetes by Example : Automate Your Kubernetes Cluster with Ansible / / by Luca Berton |
| Autore | Berton Luca |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Berkeley, CA : , : Apress : , : Imprint : Apress, , 2023 |
| Descrizione fisica | 1 online resource (300 pages) |
| Disciplina | 005.3 |
| Soggetto topico |
Cloud computing
Open source software Software engineering - Management Computer networks Cloud Computing Open Source Software Management Computer Networks |
| ISBN |
9781484292853
1484292855 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1: Modern IT Infrastructure and Hello App -- Chapter 2: Ansible Language Code -- Chapter 3: Ansible For Containers -- Chapter 4: Ansible For K8s Tasks -- Chapter 5: Ansible For Data Plane -- Chapter 6:Ansible For Control Plane -- Chapter 7: Ansible For K8s Cloud Providers. |
| Record Nr. | UNINA-9910720060903321 |
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Berton Luca
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| Berkeley, CA : , : Apress : , : Imprint : Apress, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Soggetto topico
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Cloud Computing
(154)
- Cloud computing (135)
- Artificial Intelligence (48)
- Artificial intelligence (47)
- Computational Intelligence (32)