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Applications of Hybrid Metaheuristic Algorithms for Image Processing / / edited by Diego Oliva, Salvador Hinojosa
| Applications of Hybrid Metaheuristic Algorithms for Image Processing / / edited by Diego Oliva, Salvador Hinojosa |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (486 pages) |
| Disciplina | 621.367 |
| Collana | Studies in Computational Intelligence |
| Soggetto topico |
Computational intelligence
Artificial intelligence Signal processing Image processing Speech processing systems Computational Intelligence Artificial Intelligence Signal, Image and Speech Processing |
| ISBN | 3-030-40977-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Segmentation Of Thermal Images By Means Of Metaheuristic Algorithms, For Failure Detection And Preventive Maintenance Of Electronic Systems -- A Survey on Image Processing for Hyperspectral and Remote Sensing Images -- Hybrid Grey-Wolf Optimizer Based Fractional Order Optimal Filtering for Texture Aware Quality Enhancement for Remotely Sensed Images -- Robust K- Means Technique For Band Reduction On Hyperspectral Image Segmentation -- Ethnic Characterization In Amalgamated People For Airport Security Using A Repository Of Images And Pigeon-Inspired Optimization (Pio) Algorithm For The Improvement Of Their Results} -- Multi-Level Image Thresholding Segmentation Using Non-Local Means 2d Histogram And Metaheuristics Algorithms -- Comparison Of Metaheuristic Methods For Template Matching -- Novel Feature Extraction Strategies Supporting 2d Shape Description And Retrieval -- Clustering Data Using Techniques Of Image Processing Erode And Dilate To Avoid The Use Of Euclidian Distance -- Estimation Of The Homography Matrix To Image Stitching -- Active Contour Model in Deep Learning Era: A Revise and Review -- Comparison of Evolutionary Techniques for Car Accident Prediction -- Salp Swarm Algorithm: A Comprehensive Review -- Segmentation Of Magnetic Resonance Brain Images Through The Self-Adaptive Differential Evolution Algorithm And The Minimum Cross-Entropy Criterion -- Automatic Detection Of Malignant Masses In Digital Mammograms Based On A Mcet-Hho Approach -- Cancer Cell Prediction using Machine Learning and Evolutionary Algorithms -- Meta Heuristic Approach of RMDL Classification of Parkinson's disease -- Fuzzy- Crow Search Optimization for Medical Image Segmentation -- Intelligent System For The Visual Support Of Caloric Intake Of Food In Inhabitants Of A Smart City Using A Deep Learning Model -- Image Thresholding with Metaheuristic Algorithms for Cerebral Injuries -- Generative Adversarial Network And Retinal Image Segmentation. |
| Record Nr. | UNINA-9910485011103321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Artificial intelligence for COVID-19 / / Diego Oliva, Said Ali Hassan, Ali Mohamed, editors
| Artificial intelligence for COVID-19 / / Diego Oliva, Said Ali Hassan, Ali Mohamed, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (585 pages) |
| Disciplina | 610.285 |
| Collana | Studies in systems, decision and control |
| Soggetto topico |
COVID-19
Intel·ligència artificial en medicina Processament de dades Artificial intelligence - Medical applications |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-69744-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Simulation of the Relation Between the Number of COVID-19 Death Cases as a Result of the Number of Handwashing Facilities by Using Artificial Intelligence -- 1 Literature Review -- 2 Aim of the Research -- 2.1 Statement of the Problem -- 2.2 Research Methodology -- 2.3 Research Setting and Research Paradigm -- 2.4 Limitations of the Method -- 3 Results and Discussion -- 4 Conclusion -- References -- Big Data and Data Analytics for an Enhanced COVID-19 Epidemic Management -- 1 Introduction -- 2 Big Data and Big Data Analytics for COVID-19 -- 2.1 Big Data Analytics Life Cycle -- 3 The Opportunities of Big Data and Big Data Analytics in COVID-19 Pandemic -- 4 Challenges of Big Data and Big Data Analytics During COVID-19 Pandemic -- 5 Conclusion -- References -- Application of COVID-19 Pandemic Using Artificial Intelligence -- 1 Introduction -- 2 Premature Detection of the Coronavirus (COVID-19) -- 3 Succinct Review on Transferable Syndrome Outburst in the Year 2020 -- 4 Applications of Artificial Intelligence in COVID-19 Pandemic -- 4.1 Premature Detection and Diagnosis of Infection -- 4.2 Protrusion of Suitcases and Transience -- 4.3 Progress of Drugs and Vaccines -- 4.4 Tumbling the Work of Healthcare Employees -- 5 The Original AI Capability of Bluedot and Metabiota -- 5.1 Bluedot -- 5.2 Metabiota -- 6 Conclusion -- References -- Application of Artificial Intelligence for COVID-19 Epidemic: An Exploratory Study, Opportunities, Challenges, and Future Prospects -- 1 Introduction -- 2 Artificial Intelligence (AI) Techniques in COVID-19 Outbreak -- 3 The Applicability of Artificial Intelligence During COVID-19 Pandemic -- 4 The Challenges Applying Artificial Intelligence During COVID-19 Pandemic -- 5 Conclusion -- References -- Diagnosing COVID-19 Virus in the Cardiovascular System Using ANN -- 1 Introduction.
1.1 Electrocardiography -- 1.2 Cardiovascular Risk Factors Associated with the Worse Outcomes of COVID-19 -- 2 COVID-19 Cardiovascular Manifestations -- 2.1 COVID-19 and Cardiac Arrhythmia -- 2.2 COVID-19 Myocardial Injury and Heart Failure -- 2.3 COVID-19 and Myocarditis -- 2.4 Variability in Heart Rate -- 2.5 COVID-19 and Ischemic Heart Disease -- 3 Results and Discussion -- 4 Results from Artificial Neural Network -- 5 Conclusion -- References -- An Efficient Mixture of Deep and Machine Learning Models for COVID-19 and Tuberculosis Detection Using X-Ray Images in Resource Limited Settings -- 1 Introduction -- 2 Methodology -- 2.1 COVID-19 5-Class Balanced Dataset -- 2.2 The Pipeline of Deep Feature Extraction from Pretrained Networks and Machine Learning Classification -- 2.3 Performance Evaluation of the Proposed COVID-19 Detection Pipeline -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- Understanding Role of Information and Communication Technology Application in Vietnam's Prevention and Control of COVID-19 Pandemic -- 1 Introduction -- 2 Literature Review -- 3 The Role of the Communication in Propagating Against COVID-19 in Vietnam -- 4 The Role of Information Technology Application in Warning and Detecting COVID-19 Patients -- 4.1 The Role of Information Technology in Digitizing Public Services Towards Reducing Risk of Infection -- 5 Discussion and Conclusion -- 6 Study Limitations and Contributions -- References -- Robotics and Automation: The Rescuers of COVID Era -- 1 Introduction -- 2 Importance of Robotics and Automation During Coronavirus -- 3 Applications of Robotics & -- Automation -- 3.1 Applications (Pre- COVID) -- 3.2 Applications (Post- COVID) -- 4 Problems Associated with Robotics & -- Automation -- 5 Types of Robotics and Automation. 6 Different Applications for Which Robots Are Used All Over World During Coronavirus -- 7 Future Development and Investment on Robotics -- 8 Conclusions and Suggestions -- References -- Nonparametric Tests for Comparing COVID-19 Machine Learning Forecasting Models -- 1 Introduction -- 2 Challenges of Forecasting of COVID-19 Outbreak -- 2.1 Forecasting Models for COVID-19 Outbreak -- 2.2 Nonparametric Methods for Comparing Forecast Models -- 3 Klyushin-Petunin Nonparametric Test for Homogeneity -- 4 Estimation of Forecast Model Using the P-Statistics -- 5 Conclusion and Scope for the Future Work -- References -- Artificial Intelligence and the Control of COVID-19: A Review of Machine and Deep Learning Approaches -- 1 Introduction -- 2 Knowledge Areas of AI in COVID-19 Control -- 2.1 Prediction, Tracking and Social Control -- 2.2 Cures and Treatments -- 2.3 Prognosis and Diagnosis -- 2.4 Data Dashboards -- 3 Generalized AI Response to COVID-19 -- 4 Challenges -- 4.1 Small Data Sample Size -- 4.2 Daily Case of Occurrences -- 4.3 Overlapping of Disease Symptoms -- 4.4 Need for Robust and Effective for COVID-19 -- 5 Conclusion -- References -- Optimization of the International Trade Activities in the Period of COVID-19 by Proposing an Algorithm -- 1 Introduction -- 2 Application Model in International Exchange for the Proper Management of the COVID-19 Containment Period -- 3 Principle of Operation of the Optimization Model in International Trade -- 3.1 Taking Quality into Account in Flows -- 3.2 Deterministic Model-Wait and See (WS) -- 4 The Application's Algorithm for Optimizing the Operations of International Trade Companies -- 4.1 The Algorithm -- 4.2 Discussion and Interpretation -- 5 Conclusion -- References -- Internet of Things (IoT) and Real Time Applications -- 1 Introduction and Key Discoveries. 1.1 Year-on-Year Utilization of IoT Stages by Industry -- 1.2 IoT Safekeeping and Information Secrecy -- 2 Malware Recognition Methods -- 2.1 IoT Precautions Code of Behaviors -- 2.2 Confidentiality in IoT -- 3 Real Time Application of IoT -- 3.1 A Real Time IoT-Based Wearable Communication Enabled Jacket to Monitor and Analyze the COVID-19 -- 3.2 Microstrip Patch Antennas -- 3.3 Block Diagram of Navigation System -- 4 Conclusion -- References -- Optimum Scheduling of the Disinfection Process for COVID-19 in Public Places with a Case Study from Egypt, a Novel Discrete Binary Gaining-Sharing Knowledge-Based Metaheuristic Algorithm -- 1 Introduction -- 2 Disinfection Scheduling Strategies for Public Places -- 3 Mathematical Model Formulation for the Disinfection Scheduling Strategies -- 3.1 Mathematical Model -- 4 A Real Application Case Study: Educational Institutions, Cairo, Egypt -- 5 The Proposed Methodology -- 5.1 Gaining Sharing Knowledge-Based Optimization Algorithm (GSK) -- 5.2 Discrete Binary Gaining Sharing Knowledge-Based Optimization Algorithm (DBGSK) -- 6 Experimental Results -- 7 Conclusions and Points for Future Researches -- References -- Predicating COVID19 Epidemic in Nepal Using the SIR Model -- 1 Introduction -- 2 Materials and Methods -- 2.1 Study Area -- 2.2 Data Collection -- 2.3 Methods -- 3 Results -- 4 Discussion -- 5 Conclusions -- References -- Feature Extraction of Coronavirus X-Ray Images by RNN, Correlational Networks, and PNN -- 1 Introduction -- 2 Related Work -- 3 About Coronavirus X-Ray Images -- 3.1 A Common Finding of CT Images -- 3.2 Changes in Chronological CT -- 4 Methodology -- 5 Implementation -- 5.1 Dataset -- 5.2 Evaluation Metrics -- 6 Discussion -- 7 Conclusion -- 8 Future Enhancement -- References -- Text Mining for Covid-19 Analysis in Latin America -- 1 Introduction -- 1.1 Covid-19 Outbreak in the World. 1.2 Covid-19 in Latin America -- 1.3 Text Mining Applications -- 1.4 Research in Latin America -- 1.5 PubMed -- 2 NLP Applied to South America -- 2.1 March -- 2.2 April -- 2.3 May -- 2.4 June -- 2.5 July -- 3 NLP Applied to Central America -- 4 NLP Applied to North America -- 5 Conclusions -- 6 Future Work -- References -- Spread of COVID-19 in Odisha (India) Due to Influx of Migrants and Stability Analysis Using Mathematical Modeling -- 1 Introduction -- 2 Mathematical Modeling and Basic Assumptions -- 2.1 Basic Assumptions -- 2.2 Existence of Boundedness and Positive Invariant of the Solutions -- 2.3 Basic Reproduction Number and Existence of Equilibrium -- 2.4 Local Stability Analysis -- 2.5 Global Stability for the Endemic Equilibrium -- 3 Interpretation of the Numerical Results -- 4 Conclusion -- References -- COVID-19 Epidemic Analysis and Prediction in Virudhunagar District Using Machine Learning -- 1 Introduction -- 1.1 Preventive Measures -- 2 Coronavirus Pandemic in Virudhunagar District, Tamilnadu Literature -- 2.1 History of Virudhunagar -- 2.2 Significance of the Study -- 2.3 Review of Literature -- 3 Materials and Methods -- 3.1 Data Collection -- 3.2 Data Preprocessing -- 3.3 Machine Learning Classifiers -- 4 Results and Discussions -- 4.1 Data Visualization of Sivakasi and Virudhunagar -- 4.2 Infection Rate Growth Phase -- 4.3 Reasons and Outbreaks -- 5 Conclusion -- References -- Internet of Things and Covid-19 Safety Precautions: Roles of Information Communication Technology in Health Emergency Control for Global Development -- 1 Introduction -- 2 Methodology -- 3 Review of Literature -- 4 History of IoT and IoMT -- 5 IoT and IoMT as a Technology-Based Tool for Treatment -- 5.1 Internet of Medical Things (IoMT) -- 6 Usefulness of IoT -- 7 Problems Faced by IoMT -- 8 Corona Virus or Covid-19 -- 9 Effects of Corona Virus. 10 Safety Precautions During Covid-19. |
| Record Nr. | UNINA-9910495348203321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Differential evolution : from theory to practice / / B. Vinoth Kumar, Diego Oliva, P. N. Suganthan, editors
| Differential evolution : from theory to practice / / B. Vinoth Kumar, Diego Oliva, P. N. Suganthan, editors |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (389 pages) |
| Disciplina | 515.353 |
| Collana | Studies in Computational Intelligence |
| Soggetto topico | Evolution equations |
| ISBN |
981-16-8082-5
981-16-8081-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910743384403321 |
| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Evolutionary Computation Techniques: A Comparative Perspective / / by Erik Cuevas, Valentín Osuna, Diego Oliva
| Evolutionary Computation Techniques: A Comparative Perspective / / by Erik Cuevas, Valentín Osuna, Diego Oliva |
| Autore | Cuevas Erik |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XV, 222 p. 74 illus., 33 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Studies in Computational Intelligence |
| Soggetto topico |
Computational intelligence
Artificial intelligence Computational Intelligence Artificial Intelligence |
| ISBN | 3-319-51109-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface -- Introduction -- Multilevel segmentation in digital images -- Multi-Circle detection on images -- Template matching -- Motion estimation -- Photovoltaic cell design -- Parameter identification of induction motors -- White blood cells Detection in images -- Estimation of view transformations in images -- Filter Design. |
| Record Nr. | UNINA-9910254354703321 |
Cuevas Erik
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Handbook of nature-inspired optimization algorithms . Volume II Solving contrained single objective real-parameter optimization problems : the state of the art / / Ali Wagdy Mohamed, Diego Oliva, Ponnuthurai Nagaratnam Suganthan, editors
| Handbook of nature-inspired optimization algorithms . Volume II Solving contrained single objective real-parameter optimization problems : the state of the art / / Ali Wagdy Mohamed, Diego Oliva, Ponnuthurai Nagaratnam Suganthan, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (220 pages) |
| Disciplina | 519.3 |
| Collana | Studies in systems, decision and control |
| Soggetto topico |
Mathematical optimization
Nature-inspired algorithms |
| ISBN | 3-031-07516-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Particle Swarm Optimization Based Optimization for Industry Inspection -- 1 Introduction -- 2 Image Acquisition, Feature Extraction and Processing -- 2.1 Gabor Feature Extraction and Image Processing -- 3 Experimental Process and Results -- 3.1 Effect with Different Iterations of Parameter Optimization Using PSO -- 4 Conclusion -- References -- Ant Algorithms: From Drawback Identification to Quality and Speed Improvement -- 1 Introduction -- 2 Classic Ant Algorithms -- 3 Ant Algorithms and Truck Loading -- 4 Ant Algorithms and Job Scheduling -- 5 Ant Algorithms and Graph Coloring -- 6 Conclusion -- References -- Fault Location Techniques Based on Traveling Waves with Application in the Protection of Distribution Systems with Renewable Energy and Particle Swarm Optimization -- 1 Introduction -- 2 Basic Principle of Fault Determination -- 2.1 Fault Section Determination -- 3 Determination of the Interphase Short Circuit Fault Location -- 4 Traveling Waves -- 4.1 Wavelet Transform -- 5 Fundamentals of Particle Swarm Optimization -- 6 Determination of Fault Location for Electric Power Distribution Networks with DGs -- 6.1 Dynamic Protection Suitable for the High Incorporation of Renewable Energy Sources into the Electric Energy Distribution System -- 6.2 Microgrid Protection with High Incorporation of Renewable Energies -- 7 Applicability of Dynamic Protection Based on Traveling Waves in Electrical Systems with High Incorporation of Renewable Energy Sources -- 8 Particle Swarm Optimization Algorithm -- 9 Future Applications -- 10 Conclusion -- References -- Improved Particle Swarm Optimization and Non-quadratic Penalty Method for Non-linear Programming Problems with Equality Constraints -- 1 Introduction -- 1.1 Penalty Function Method -- 1.2 Penalty Function -- 2 Particle Swarm Optimization -- 2.1 Improvements in PSO.
3 Methodology -- 4 Parameter Setup -- 5 Experimental Setup -- 6 Conclusion -- 7 Future Work -- References -- Recent Trends in Face Recognition Using Metaheuristic Optimization -- 1 Introduction -- 2 Metaheuristic Optimization Approaches -- 2.1 Genetic Algorithms (GAs) -- 2.2 Particle Swarm Optimization (PSO) -- 2.3 Ant Colony Optimization (ACO) -- 2.4 Bacterial Foraging Optimization Algorithm (BFOA) -- 2.5 Firefly Algorithm (FA) -- 3 Biometrics Modalities -- 3.1 Face Recognition System -- 3.2 Performance Metrics -- 4 Face Recognition Based Optimization Approaches -- 5 Databases and Discussion -- 5.1 Databases -- 5.2 Discussion -- 5.3 Future Trends -- 6 Conclusion -- References -- Chaos Game Optimization Algorithm with Crossover Operator for Solving Constraint Engineering Optimization Problems -- 1 Introduction -- 2 Chaos Game Optimization (CGO) -- 3 Crossover Based Chaos Game Optimization (CrCGO) -- 4 Numerical Results -- 4.1 Benchmark Optimization Problems -- 4.2 Contender Methods -- 4.3 Evaluation Criteria -- 4.4 Non-parametric Statistical Tests -- 4.5 Results and Discussions -- 5 Conclusion -- References -- UAV-Assisted IoT Data Collection Optimization Using Gaining-Sharing Knowledge Algorithm -- 1 Introduction -- 2 System Model and Problem Formulation -- 3 Gaining-sharing Knowledge (GSK) Algorithm -- 4 Results and Discussion -- 5 Conclusion -- References -- Energy Aware Tikhonov-Regularized FPA Technique for Task Scheduling in Wearable Biomedical Devices -- 1 Introduction -- 2 Wearable Biomedical System Overview -- 3 Problem Formulation -- 3.1 Objective Function -- 3.2 Tikhonov Regularization and Operation Constraints -- 3.3 Flower Pollination Optimization Algorithm -- 4 Experiments and Discussion -- 4.1 Energy Consumption Profiling -- 4.2 Parameters Setup and Trials -- 5 Conclusion -- References. Material Generation Algorithm Combined with Epsilon Constraint Handling Scheme for Engineering Optimization -- 1 Introduction -- 2 Material Generation Algorithm -- 3 Problem Statement -- 3.1 Constrained Optimization -- 3.2 Constraint Handling -- 4 Engineering Design Problems of CEC 2020 -- 5 Numerical Investigations -- 6 Conclusion -- References -- Optimum Design of Truss Structures with Atomic Orbital Search Considering Discrete Design Variables -- 1 Introduction -- 2 Atomic Orbital Search -- 3 Problem Statement -- 4 Numerical Investigations -- 4.1 10-Bar Truss Structure -- 4.2 25-Bar Truss Structure -- 4.3 52-Bar Truss Structure -- 4.4 160-Bar Truss Structure -- 5 Conclusion -- References. |
| Record Nr. | UNINA-9910591038103321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Handbook of nature-inspired optimization algorithms . Volume I Solving single objective bound-constrained real-parameter numerical optimization problems : the state of the art / / Ali Mohamed, Diego Oliva and Ponnuthurai Nagaratnam, editors
| Handbook of nature-inspired optimization algorithms . Volume I Solving single objective bound-constrained real-parameter numerical optimization problems : the state of the art / / Ali Mohamed, Diego Oliva and Ponnuthurai Nagaratnam, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (282 pages) |
| Disciplina | 519.3 |
| Collana | Studies in Systems, Decision and Control |
| Soggetto topico |
Mathematical optimization
Nature-inspired algorithms |
| ISBN | 3-031-07512-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910590081903321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Metaheuristics in machine learning : theory and applications / / Diego Oliva, Essam H. Houssein, Salvador Hinojosa, editors
| Metaheuristics in machine learning : theory and applications / / Diego Oliva, Essam H. Houssein, Salvador Hinojosa, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (765 pages) |
| Disciplina | 670.151 |
| Collana | Studies in computational intelligence |
| Soggetto topico | Metaheuristics |
| ISBN | 3-030-70542-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910492143403321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2020) / / edited by Aboul-Ella Hassanien, Ahmad Taher Azar, Tarek Gaber, Diego Oliva, Fahmy M. Tolba
| Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2020) / / edited by Aboul-Ella Hassanien, Ahmad Taher Azar, Tarek Gaber, Diego Oliva, Fahmy M. Tolba |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (880 pages) |
| Disciplina | 006.3 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Computational intelligence
Optical data processing Artificial intelligence Computational Intelligence Image Processing and Computer Vision Artificial Intelligence |
| ISBN | 3-030-44289-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910483171103321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Technological and Industrial Applications Associated with Industry 4. 0
| Technological and Industrial Applications Associated with Industry 4. 0 |
| Autore | Ochoa-Zezzatti Alberto |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing AG, , 2021 |
| Descrizione fisica | 1 online resource (344 pages) |
| Altri autori (Persone) |
OlivaDiego
HassanienAboul Ella |
| Collana | Studies in Systems, Decision and Control Ser. |
| Soggetto genere / forma | Electronic books. |
| ISBN | 3-030-68663-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Introduction -- Contents -- Mobile Applications and Web Applications to Improve Competitiveness in Industry 4.0 -- Implementation of an Intelligent Model Based on Convolutional Neural Network for the Detection of Diseases in Citrus Crops Caused by Bird Pests Using an Intelligent Drone -- 1 Introduction -- 2 Project Development -- 2.1 Object Classifier and Object Detector -- 2.2 Artificial Neural Network -- 2.3 Convolutional Neural Network -- 2.4 Comparison Between an Artificial Neural Network and a CNN -- 2.5 Pixels and Neurons -- 2.6 Choice of the Crop to Be Analyzed -- 2.7 Process to Be Automated -- 3 Materials and Methods -- 3.1 Acquisition of the Images -- 3.2 Development of the Application -- 4 Results -- 5 Experimentation -- 6 Conclusions and Future Research -- References -- Intelligent Application to Detection of Arachnid Bites in Children Implementing Deep Learning Techniques, an AmI-Based Solution -- 1 Introduction -- 2 Implementation of the Intelligent Application -- 3 Spider Bite Recognition -- 3.1 Diagnosis, Prognosis and Follow-up -- 3.2 Treatment -- 3.3 Prevention -- 3.4 Methodological Proposal for the Recognition of an Arachnid Bite -- 4 Test Development -- 4.1 Module for the Recognition of Arachnids and their Bites -- 4.2 Results -- 5 Conclusions and Future Work -- References -- Evacuation Route Optimization in the Plaza de la Mexicanidad, Using Humanitarian Logistics -- 1 Introduction -- 2 Behavior of the Masses -- 2.1 Stampedes of the Masses -- 2.2 Pre-disaster Planning -- 2.3 Implementation of a Mass Victim Assistance System -- 3 Simulation Models -- 3.1 State of the Art -- 3.2 Mathematical Model -- 3.3 Simulated Case Studies and Comparison with Reality -- 3.4 Trajectory Simulation -- 4 Voronoi Diagram -- 5 Future Research and Works -- 6 Conclusions and Future Challenges -- References.
Automatic Fall Detection for the Care of Older Adults in Smart Cities -- 1 Introduction -- 2 Theory -- 2.1 Machine Learning -- 2.2 Layers -- 3 Proposed Methodology -- 3.1 Activation Functions -- 3.2 Training Parameters of a Neural Network -- 3.3 Tools Used for the Development of ANN Architectures -- 3.4 Video Processing -- 3.5 Action Recognition Through Video Sequences -- 4 Methods -- 4.1 Fall and Non-fall Labelling -- 4.2 Pre-processing -- 4.3 Architecture -- 4.4 Evaluation Metrics -- 5 Results -- 5.1 Training Results -- 5.2 Test Set Evaluation -- 6 Conclusions -- References -- Automatic Tumor Segmentation in Mammogram Images for Healthcare Systems in Smart Cities -- 1 Introduction -- 2 Literature Review -- 3 Theory Background -- 3.1 Deep Learning -- 3.2 Depthwise Layers -- 3.3 Non-local Processing -- 4 Mammogram Database -- 5 Deep Learning Architecture for Breast Tumor Detection -- 5.1 Architecture Design -- 5.2 Training -- 5.3 Implementation -- 6 Validation -- 7 Conclusions -- References -- Impact of Industry 4.0: Improving Hybrid Laser-Arc Welding with Big Data for Subsequent Functionality in Underwater Welding -- 1 Introduction -- 2 Industry 4.0 -- 2.1 The Origins -- 2.2 Industry 4.0 Techniques -- 3 Welding Technologies -- 3.1 Laser Beam Welding (LBW) -- 3.2 Gas Metal Arc Welding (GMAW) -- 3.3 Hybrid Welding -- 4 Optimization -- 4.1 Database -- 4.2 Multilayer Perceptron (MLP) -- 4.3 Sequential Minimal Optimization (SMO) -- 4.4 Other Techniques -- 5 Conclusions and Future Challenges -- References -- Interpersonal Relationships and Reciprocity: Their Influence in Knowledge Transfer Inside of Mexican Hotels -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusions -- References -- Modern Technology Applications Including Metaheuristics and Artificial Intelligence Based Applications for Industry 4.0. Brainwaves Behavior During the Learning Curve Associated with the Manufacturing of a Product with Legos -- 1 Introduction -- 1.1 Theoretical Framework -- 2 Methodology -- 2.1 Standard Time Determination -- 2.2 Participants Involved in the Study -- 2.3 Experiment and Data Processing -- 2.4 Statistical Analysis -- 3 Results -- 4 Discussion -- 5 Conclusions and Future Challenges -- References -- Audio Features Extraction to Develop a Child Activity Recognition Model Using Support Vector Machine to Monitoring Security in a Smart City -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset Description -- 2.2 Data Analysis -- 2.3 Model Validation -- 3 Experiments -- 3.1 Audio Recordings -- 3.2 Feature Extraction -- 3.3 Classification Model -- 3.4 Classification Process -- 4 Conclusion and Future Research -- References -- Sentiment Analysis Using Natural Language Processing Through a Speech Recognition System Using a Hybrid Mobile App -- 1 Introduction -- 2 Voice Recognition Algorithm Using Go -- 3 Sentiment Analysis Using a Rating System with Go -- 4 Hybrid Mobile App with Google Flutter Framework -- References -- Logistics of Hospitalization Patients with COVID and Ambulances Required -- 1 Introduction -- 2 Descriptions of the Model Components -- 2.1 The Shortest Route -- 2.2 The Shortest Path Algorithm -- 3 Proposal Methodology -- 3.1 Case-Based Reasoning to Solve Route Problems -- 4 The Proposed Model of Our Hybrid Algorithm -- 5 Experimental Results -- 6 Conclusion and Future Research -- References -- A Heuristic Method for Oil Distribution Networks Applied to the Switching Behavior in the Oil Industry -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- References -- Metaheuristics for Order Picking Optimisation: A Comparison Among Three Swarm-Intelligence Algorithms -- 1 Introduction -- 2 Literature Review. 2.1 Order Picking -- 2.2 Ant Colony Optimisation -- 2.3 Elephant Herding Optimisation -- 2.4 Bat Algorithm -- 3 Data Description -- 4 Computational Tests -- 5 Conclusions and Further Research -- References -- Implementation of an Intelligent Framework for the Analysis of Body Movements Through an Avatar Adapted to the Context of Industry 4.0 for the Recruitment of Personnel -- 1 Introduction -- 2 Theory -- 3 Equipment -- 3.1 Display -- 3.2 Virtual Reality Simulation Lens -- 3.3 The Mid-Range Cpu Intel Core I5-10600 K Versus Amd Ryzen 5 3600 -- 3.4 Graphic Card -- 4 Softwares -- 4.1 Body Tracking SDK Azure Kinect Integration -- 4.2 Procedure of Conducting the SDK Kinect Software -- 4.3 SQL Environment -- 5 Implemented Intelligent Application -- 5.1 Experiment and Implementation -- 5.2 Summary Statistics for Determine Industrial Process to Model -- 6 Conclusions -- References -- Industry 4.0 Optimization and Its Future Effects on Z Generation Focused on the Paradigm Shift of an Innovation Ecosystem -- Selection of Factors Influencing for Reliable Electrical Power Transmission Design in Industry 4.0 -- 1 Introduction -- 1.1 Thermal Behavior of the Power Cable -- 2 Underground Cable System in Industry 4.0 -- 3 Design of Experiments -- 4 Experimentation and Results -- 5 Conclusion -- References -- Analysis of Transport Logistics Operations at a Link in a Reverse Supply Chain that Values Used Cooking Oil -- 1 Introduction -- 2 Reverse Supply Chains and Logistics Transport Operations -- 3 Analysis of Transport Logistics Operations of Used Cooking Oil -- 3.1 The Mode of Transport Definition and Operation -- 3.2 Management of the Vehicle Capacity -- 3.3 Transport Risk Analysis -- 4 Results -- 5 Conclusions -- References -- The Transformation of Supply Chains in the Circular Economy from International Experiences to the Mexican Cases -- 1 Introduction. 2 Circular Economy and Supply Chains -- 3 Methodology -- 3.1 Literature Review -- 3.2 Economic Units (EU) Exploration by Kind of Material -- 4 Analysis of Descriptive Statistics -- 5 Challenges and Opportunities -- 6 Companies by Material, Link and Entity -- 7 Conclusions -- References -- Nanostores' Density and Geographical Location: An Empirical Study Under Urban Logistics Approach -- 1 Introduction -- 2 Empirical Study Design -- 3 Results Analysis -- 4 Findings, Limitations and Future Work -- 5 Conclusions -- References -- Blockchain Model Implementation to Select the Best Bid in an Industrial Supply Chain -- 1 Introduction -- 2 Related Works -- 3 Proposed Model -- 3.1 Content Modeling -- 4 Results -- 5 Conclusions -- 6 Future Works -- References -- Sociodemographic Analysis of the Location of MSW Collection Centers in Mexico City -- 1 Introduction -- 2 Theoretical Framework -- 3 Materials and Methods -- 4 Results and Discussion -- 5 Conclusions -- References -- Classification System to Detect Diseases in Apples by Using a Convolutional Neural Network -- 1 Introduction -- 2 The Problem -- 3 The Solution -- 4 Conclusions and Future Research -- References. |
| Record Nr. | UNINA-9910497090903321 |
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Ochoa-Zezzatti Alberto
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| Cham : , : Springer International Publishing AG, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Technological and industrial applications associated with Industry 4.0 / / Alberto Ochoa-Zezzatti, Diego Oliva, Aboul Ella Hassanien, editors
| Technological and industrial applications associated with Industry 4.0 / / Alberto Ochoa-Zezzatti, Diego Oliva, Aboul Ella Hassanien, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (344 pages) |
| Disciplina | 658.4038028563 |
| Collana | Studies in Systems, Decision and Control |
| Soggetto topico | Industry 4.0 |
| ISBN | 3-030-68663-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Introduction -- Contents -- Mobile Applications and Web Applications to Improve Competitiveness in Industry 4.0 -- Implementation of an Intelligent Model Based on Convolutional Neural Network for the Detection of Diseases in Citrus Crops Caused by Bird Pests Using an Intelligent Drone -- 1 Introduction -- 2 Project Development -- 2.1 Object Classifier and Object Detector -- 2.2 Artificial Neural Network -- 2.3 Convolutional Neural Network -- 2.4 Comparison Between an Artificial Neural Network and a CNN -- 2.5 Pixels and Neurons -- 2.6 Choice of the Crop to Be Analyzed -- 2.7 Process to Be Automated -- 3 Materials and Methods -- 3.1 Acquisition of the Images -- 3.2 Development of the Application -- 4 Results -- 5 Experimentation -- 6 Conclusions and Future Research -- References -- Intelligent Application to Detection of Arachnid Bites in Children Implementing Deep Learning Techniques, an AmI-Based Solution -- 1 Introduction -- 2 Implementation of the Intelligent Application -- 3 Spider Bite Recognition -- 3.1 Diagnosis, Prognosis and Follow-up -- 3.2 Treatment -- 3.3 Prevention -- 3.4 Methodological Proposal for the Recognition of an Arachnid Bite -- 4 Test Development -- 4.1 Module for the Recognition of Arachnids and their Bites -- 4.2 Results -- 5 Conclusions and Future Work -- References -- Evacuation Route Optimization in the Plaza de la Mexicanidad, Using Humanitarian Logistics -- 1 Introduction -- 2 Behavior of the Masses -- 2.1 Stampedes of the Masses -- 2.2 Pre-disaster Planning -- 2.3 Implementation of a Mass Victim Assistance System -- 3 Simulation Models -- 3.1 State of the Art -- 3.2 Mathematical Model -- 3.3 Simulated Case Studies and Comparison with Reality -- 3.4 Trajectory Simulation -- 4 Voronoi Diagram -- 5 Future Research and Works -- 6 Conclusions and Future Challenges -- References.
Automatic Fall Detection for the Care of Older Adults in Smart Cities -- 1 Introduction -- 2 Theory -- 2.1 Machine Learning -- 2.2 Layers -- 3 Proposed Methodology -- 3.1 Activation Functions -- 3.2 Training Parameters of a Neural Network -- 3.3 Tools Used for the Development of ANN Architectures -- 3.4 Video Processing -- 3.5 Action Recognition Through Video Sequences -- 4 Methods -- 4.1 Fall and Non-fall Labelling -- 4.2 Pre-processing -- 4.3 Architecture -- 4.4 Evaluation Metrics -- 5 Results -- 5.1 Training Results -- 5.2 Test Set Evaluation -- 6 Conclusions -- References -- Automatic Tumor Segmentation in Mammogram Images for Healthcare Systems in Smart Cities -- 1 Introduction -- 2 Literature Review -- 3 Theory Background -- 3.1 Deep Learning -- 3.2 Depthwise Layers -- 3.3 Non-local Processing -- 4 Mammogram Database -- 5 Deep Learning Architecture for Breast Tumor Detection -- 5.1 Architecture Design -- 5.2 Training -- 5.3 Implementation -- 6 Validation -- 7 Conclusions -- References -- Impact of Industry 4.0: Improving Hybrid Laser-Arc Welding with Big Data for Subsequent Functionality in Underwater Welding -- 1 Introduction -- 2 Industry 4.0 -- 2.1 The Origins -- 2.2 Industry 4.0 Techniques -- 3 Welding Technologies -- 3.1 Laser Beam Welding (LBW) -- 3.2 Gas Metal Arc Welding (GMAW) -- 3.3 Hybrid Welding -- 4 Optimization -- 4.1 Database -- 4.2 Multilayer Perceptron (MLP) -- 4.3 Sequential Minimal Optimization (SMO) -- 4.4 Other Techniques -- 5 Conclusions and Future Challenges -- References -- Interpersonal Relationships and Reciprocity: Their Influence in Knowledge Transfer Inside of Mexican Hotels -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusions -- References -- Modern Technology Applications Including Metaheuristics and Artificial Intelligence Based Applications for Industry 4.0. Brainwaves Behavior During the Learning Curve Associated with the Manufacturing of a Product with Legos -- 1 Introduction -- 1.1 Theoretical Framework -- 2 Methodology -- 2.1 Standard Time Determination -- 2.2 Participants Involved in the Study -- 2.3 Experiment and Data Processing -- 2.4 Statistical Analysis -- 3 Results -- 4 Discussion -- 5 Conclusions and Future Challenges -- References -- Audio Features Extraction to Develop a Child Activity Recognition Model Using Support Vector Machine to Monitoring Security in a Smart City -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset Description -- 2.2 Data Analysis -- 2.3 Model Validation -- 3 Experiments -- 3.1 Audio Recordings -- 3.2 Feature Extraction -- 3.3 Classification Model -- 3.4 Classification Process -- 4 Conclusion and Future Research -- References -- Sentiment Analysis Using Natural Language Processing Through a Speech Recognition System Using a Hybrid Mobile App -- 1 Introduction -- 2 Voice Recognition Algorithm Using Go -- 3 Sentiment Analysis Using a Rating System with Go -- 4 Hybrid Mobile App with Google Flutter Framework -- References -- Logistics of Hospitalization Patients with COVID and Ambulances Required -- 1 Introduction -- 2 Descriptions of the Model Components -- 2.1 The Shortest Route -- 2.2 The Shortest Path Algorithm -- 3 Proposal Methodology -- 3.1 Case-Based Reasoning to Solve Route Problems -- 4 The Proposed Model of Our Hybrid Algorithm -- 5 Experimental Results -- 6 Conclusion and Future Research -- References -- A Heuristic Method for Oil Distribution Networks Applied to the Switching Behavior in the Oil Industry -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- References -- Metaheuristics for Order Picking Optimisation: A Comparison Among Three Swarm-Intelligence Algorithms -- 1 Introduction -- 2 Literature Review. 2.1 Order Picking -- 2.2 Ant Colony Optimisation -- 2.3 Elephant Herding Optimisation -- 2.4 Bat Algorithm -- 3 Data Description -- 4 Computational Tests -- 5 Conclusions and Further Research -- References -- Implementation of an Intelligent Framework for the Analysis of Body Movements Through an Avatar Adapted to the Context of Industry 4.0 for the Recruitment of Personnel -- 1 Introduction -- 2 Theory -- 3 Equipment -- 3.1 Display -- 3.2 Virtual Reality Simulation Lens -- 3.3 The Mid-Range Cpu Intel Core I5-10600 K Versus Amd Ryzen 5 3600 -- 3.4 Graphic Card -- 4 Softwares -- 4.1 Body Tracking SDK Azure Kinect Integration -- 4.2 Procedure of Conducting the SDK Kinect Software -- 4.3 SQL Environment -- 5 Implemented Intelligent Application -- 5.1 Experiment and Implementation -- 5.2 Summary Statistics for Determine Industrial Process to Model -- 6 Conclusions -- References -- Industry 4.0 Optimization and Its Future Effects on Z Generation Focused on the Paradigm Shift of an Innovation Ecosystem -- Selection of Factors Influencing for Reliable Electrical Power Transmission Design in Industry 4.0 -- 1 Introduction -- 1.1 Thermal Behavior of the Power Cable -- 2 Underground Cable System in Industry 4.0 -- 3 Design of Experiments -- 4 Experimentation and Results -- 5 Conclusion -- References -- Analysis of Transport Logistics Operations at a Link in a Reverse Supply Chain that Values Used Cooking Oil -- 1 Introduction -- 2 Reverse Supply Chains and Logistics Transport Operations -- 3 Analysis of Transport Logistics Operations of Used Cooking Oil -- 3.1 The Mode of Transport Definition and Operation -- 3.2 Management of the Vehicle Capacity -- 3.3 Transport Risk Analysis -- 4 Results -- 5 Conclusions -- References -- The Transformation of Supply Chains in the Circular Economy from International Experiences to the Mexican Cases -- 1 Introduction. 2 Circular Economy and Supply Chains -- 3 Methodology -- 3.1 Literature Review -- 3.2 Economic Units (EU) Exploration by Kind of Material -- 4 Analysis of Descriptive Statistics -- 5 Challenges and Opportunities -- 6 Companies by Material, Link and Entity -- 7 Conclusions -- References -- Nanostores' Density and Geographical Location: An Empirical Study Under Urban Logistics Approach -- 1 Introduction -- 2 Empirical Study Design -- 3 Results Analysis -- 4 Findings, Limitations and Future Work -- 5 Conclusions -- References -- Blockchain Model Implementation to Select the Best Bid in an Industrial Supply Chain -- 1 Introduction -- 2 Related Works -- 3 Proposed Model -- 3.1 Content Modeling -- 4 Results -- 5 Conclusions -- 6 Future Works -- References -- Sociodemographic Analysis of the Location of MSW Collection Centers in Mexico City -- 1 Introduction -- 2 Theoretical Framework -- 3 Materials and Methods -- 4 Results and Discussion -- 5 Conclusions -- References -- Classification System to Detect Diseases in Apples by Using a Convolutional Neural Network -- 1 Introduction -- 2 The Problem -- 3 The Solution -- 4 Conclusions and Future Research -- References. |
| Record Nr. | UNINA-9910523738103321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
