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2010 9th IEEE International Conference on Cognitive Informatics
| 2010 9th IEEE International Conference on Cognitive Informatics |
| Pubbl/distr/stampa | [Place of publication not identified], : IEEE, 2010 |
| Descrizione fisica | 1 online resource (xiv, 987 pages) |
| Disciplina | 006.3 |
| Soggetto topico |
Artificial intelligence - Methodology
Artificial intelligence - Industrial applications |
| ISBN | 1-4244-8042-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996213766203316 |
| [Place of publication not identified], : IEEE, 2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
2010 9th IEEE International Conference on Cognitive Informatics
| 2010 9th IEEE International Conference on Cognitive Informatics |
| Pubbl/distr/stampa | [Place of publication not identified], : IEEE, 2010 |
| Descrizione fisica | 1 online resource (xiv, 987 pages) |
| Disciplina | 006.3 |
| Soggetto topico |
Artificial intelligence - Methodology
Artificial intelligence - Industrial applications |
| ISBN | 1-4244-8042-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910140942603321 |
| [Place of publication not identified], : IEEE, 2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances on smart and soft computing : proceedings of ICACIn 2021 / / Faisal Saeed [and three others]
| Advances on smart and soft computing : proceedings of ICACIn 2021 / / Faisal Saeed [and three others] |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (526 pages) |
| Disciplina | 006.3 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Artificial intelligence - Safety measures
Artificial intelligence - Methodology |
| ISBN |
981-16-5559-6
981-16-5558-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- ICACIN'21 Organizing Committee -- Preface -- Contents -- About the Editors -- Artificial Intelligence I -- Adaptive Learning Content Based on Learning Styles in Learning Management System -- 1 Introduction -- 2 Literature Review -- 2.1 Adaptive Content -- 2.2 Learning Style -- 2.3 Existing Personalization Taxonomy -- 2.4 Personalization Learning -- 3 Research Methodology -- 4 Results and Discussion -- 5 Conclusion -- References -- A Model-Based Approach for COVID-19 Propagation -- 1 Introduction -- 1.1 The Time-Dependent SIR Model -- 1.2 Differential Equation of Time-Dependent SIR Model -- 1.3 Estimation of β(t) and γ(t) Using L2 Regularization -- 1.4 Estimating the Model Parameters, (t) and (t) -- 1.5 The Basic Reproduction Number -- 2 Dataset -- 3 COVID-19 Exploratory Analysis -- 3.1 COVID-19 Cases in Morocco -- 4 Time Evolution of the Time-Dependent SIR Model -- 5 Conclusion and Future Work -- References -- Numerical Modeling of the Mechanical Behavior of Recycled Flexible PVC Loaded with Different Percentages of Chicken Feathers -- 1 Introduction -- 2 Numerical Study -- 2.1 Mesh and Geometry -- 3 Rho and Gamma Indicators -- 3.1 Mechanical Characteristics -- 4 Results and Discussion -- 5 Conclusion -- References -- Covid-19 Detection from Pneumonia Image Classification Using Deep Learning -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Covid-19 Dataset -- 3.2 Image Data Augmentation with Keras ImageDataGenerator -- 3.3 The Architectures Used for Transfer Learning: DenseNet121 and VGG16 -- 4 Experimental Results -- 5 Conclusion -- References -- Toward the Prediction of the Elasticity of Bio Loaded Polypropylene Using Artificial Neural Networks -- 1 Introduction -- 2 Materials and Methods -- 2.1 Materials -- 2.2 Methods -- 2.3 Smart Methods -- 3 Results and Discussion -- 4 Conclusion -- References.
Post-COVID-19: Deep Image Processing AI to Analyze Social Distancing in a Human Community -- 1 Introduction -- 2 Related Works -- 3 Proposed Approach -- 3.1 Human Detection Step -- 4 Faster R-CNN Design -- 5 Results and Discussion -- 5.1 Phase I-Person Detection Step -- 5.2 Phase II-Distance Computation Step -- 6 Conclusion -- References -- Design and Implementation of ImALeG Serious Game: Behavior of Non-playable Characters (NPC) -- 1 Introduction -- 2 Related Works -- 3 Design and Implementation -- 3.1 ImALeG Virtual Reality Game -- 3.2 Fuzzy Finite-state Machine Design -- 4 Emotional Impact -- 5 Conclusion -- References -- Detection of Personality Traits Through Handwriting Analysis Using Machine Learning Approach -- 1 Introduction -- 2 Literature Review -- 3 Research Methodology -- 3.1 Scanning -- 3.2 Preprocessing -- 3.3 Line Segmentation -- 3.4 Feature Extraction -- 3.5 Classification and Analysis -- 4 Results and Discussion -- 4.1 Preprocessing -- 4.2 Line Segmentation -- 4.3 Feature Extraction -- 4.4 Classification and Analysis -- 4.5 Handwriting Analysis Application -- 5 Conclusion and Future Work -- References -- Data Science -- Hybrid Students' Academic Performance and Dropout Prediction Models Using Recursive Feature Elimination Technique -- 1 Introduction -- 2 Related Works -- 2.1 Naïve Bayes -- 2.2 Support Vector Machine -- 2.3 Recursive Feature Elimination (RFE) Technique -- 3 Methodology -- 4 Results and Discussion -- 4.1 Results of the Autoclassifier Detection Stage -- 4.2 Results of the Feature Selection Layer -- 4.3 Results of the Classification Layer -- 4.4 Results of the Model Evaluation Layer -- 5 Conclusion -- References -- Stage Classification of Alzheimer's Disease Using Transfer Learning -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Set -- 3.2 Proposed Models -- 4 Results and Discussion. 4.1 Evaluation -- 4.2 Results -- 5 Conclusion -- References -- Predicting the e-Signing Likelihood of Loan Using Machine Learning Models Combining Clustering with Supervised Learning -- 1 Introduction -- 2 Related Work -- 3 Background -- 4 Approach Methodology -- 4.1 Dataset Description -- 4.2 Proposed Pipeline -- 5 Results and Discussion -- 5.1 Classical Approach-Logistic Regression -- 5.2 Machine Learning Approach -- 5.3 A Hybrid Approach Using a Pre-clustering Step to Enhance Performance Using Self-organizing Map Clustering -- 6 Conclusion and Future Work -- References -- Designing an Arabic Google Play Store User Review Dataset for Detecting App Requirement Issues -- 1 Introduction -- 2 Related Works -- 3 Dataset Design -- 3.1 Data Collection Phase -- 3.2 Feature Engineering Phase -- 4 Enabling Research -- 4.1 Sentiment Analysis -- 4.2 Dialect Identification -- 4.3 App Review -- 4.4 Gender Detection -- 4.5 Software Issue Detection -- 5 Conclusion and Future Work -- References -- A Survey of Machine Learning and Deep Learning Applications in Genome Editing -- 1 Introduction -- 2 Genomics -- 3 Genome Editing -- 3.1 Application of Machine Learning in Genome Editing -- 4 Summary and Discussion -- 5 Conclusion -- References -- Educational Data Mining Techniques for Detecting Undesirable Students' Behaviors and Predicting Students' Performance: A Comparative Study -- 1 Introduction -- 2 Educational Data Mining Tasks -- 2.1 Detecting Undesirable Students' Behaviors -- 2.2 Detecting Students' Performance -- 3 Discussion and Future work -- References -- COVID-19: Analysis and Measurement of the Influence of the Tweets to Help the Public Health Sector to Fight Coronavirus -- 1 Introduction -- 2 Coronaviruses (COVID-19) -- 3 Twitter -- 4 Influence: An Overview for Our Case -- 5 Related Work -- 5.1 TunkRank Algorithm. 5.2 Twitter Ratio (Followers and Following) -- 6 Method and Algorithm -- 6.1 Our Method -- 6.2 Influence Score Algorithm Inf(X, TempD) -- 7 Experiments Results and Discussion -- 7.1 The Influential Tweeted not About COVID-19 (Other Tweets) -- 7.2 The Influential Tweeted About COVID-19 -- 8 Conclusion -- References -- Data Analytics Model for Home Improvement Store -- 1 Introduction -- 2 Related Work -- 2.1 Introduction to a Home Improvement Store -- 2.2 Importance of Applying Data Analytics Model to Retail Business -- 2.3 Study on Existing Data Analytics Model -- 2.4 Research Methodology -- 3 Data Quality of Dataset -- 3.1 Issues in Current Dataset -- 3.2 Handling Data Quality Issues -- 3.3 Missing Data -- 3.4 Noisy Data -- 3.5 Output of Descriptive Analytics Model -- 3.6 Output of Predictive Analytics Model -- 4 Techniques and Tools Used -- 5 Result -- 6 Conclusion -- References -- Intelligent Models for Mining Social Media Data -- 1 Introduction -- 2 Research Methods -- 2.1 Dataset -- 2.2 Pre-processing Approach -- 2.3 Learning Algorithms -- 2.4 Evaluation Metrics -- 3 Model Implementation and Results -- 4 Related Work -- 5 Conclusion -- References -- Cloud Computing and Networking -- Routing and Charging of Electric Vehicles: Survey -- 1 Introduction -- 2 Electric Vehicles Routing Problems -- 2.1 Related Works -- 3 Charging of Electric Vehicles -- 4 Conclusion and Future Work -- References -- A Parallel Genetic Algorithm for Solving the Vehicle Routing Problem with Drone Medication Delivery -- 1 Introduction -- 2 Related Literature -- 3 Problem Formulation -- 4 Proposed Approach -- 5 Experiments and Results -- 6 Conclusion and Perspectives -- References -- Review on Blockchain and Access Control Systems -- 1 Introduction -- 2 Methodology -- 3 Preliminaries -- 3.1 Blockchain -- 3.2 Blockchain Layers -- 3.3 Access Control Systems (ACS). 4 Related Works -- 5 Discussion -- 6 Conclusion -- References -- Adoption of Docker Containers as an Infrastructure for Deploying Software Applications: A Review -- 1 Introduction -- 2 Motivation -- 2.1 Usage of Docker in the Practitioner -- 3 Research Method -- 3.1 Different Solutions/Observations and Studies for Docker -- 4 Docker Containers -- 4.1 Introduction to Docker Containers -- 4.2 Docker Container Architecture -- 4.3 Advantages of Docker Containers -- 4.4 Limitations of Docker Containers -- 4.5 Strategic Approaches to Overcome Docker Limitations -- 5 Docker and Other Corresponding Approaches -- 6 Docker Integration with Container Orchestration -- 7 Conclusion -- References -- Study of the Impact of the Profoundness of Tunnel in the Context of Transition from IPv4 to IPv6 at the Local, Regional, and National Levels -- 1 Introduction -- 2 Overview of Transition Methods -- 3 Related Works -- 4 Context of Study -- 5 Results and Analysis -- 5.1 End-to-End Delay -- 5.2 Variation in Delay -- 5.3 HTTP Response Time -- 6 Conclusion and Future Work -- References -- Artificial Intelligence II -- A Face-Mask Detection System Based on Deep Learning Convolutional Neural Networks -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Face Detection and Localization Step -- 3.2 Applying Face-Mask Classifier -- 4 Experimental Setup -- 4.1 Dataset -- 4.2 Architectural Details -- 5 Results and Discussion -- 5.1 Results for the "Uni-FaceMask" Model -- 5.2 Results for the "Multi-FaceMask" Model -- 6 Conclusion -- References -- Deep Learning for COVID-19 Cases-Based XCR and Chest CT Images -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Research Questions -- 3.2 Dataset -- 3.3 Classification -- 4 Computational Results and Discussion -- 4.1 Experimental Settings -- 4.2 Experimental Datasets -- 4.3 Experimental Results. 4.4 Results and Discussions. |
| Record Nr. | UNINA-9910743257903321 |
| Singapore : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial intelligence in industrial applications : approaches to solve the intrinsic industrial optimization problems / / Steven Lawrence Fernandes and Tarun K. Sharma
| Artificial intelligence in industrial applications : approaches to solve the intrinsic industrial optimization problems / / Steven Lawrence Fernandes and Tarun K. Sharma |
| Autore | Fernandes Steven Lawrence |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer International Publishing, , [2021] |
| Descrizione fisica | 1 online resource (203 pages) |
| Disciplina | 006.3 |
| Collana | Learning and Analytics in Intelligent Systems |
| Soggetto topico |
Artificial intelligence - Methodology
Artificial intelligence - Research |
| ISBN | 3-030-85383-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910522946303321 |
Fernandes Steven Lawrence
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| Cham, Switzerland : , : Springer International Publishing, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Augmented intelligence in healthcare : a pragmatic and integrated analysis / / Sushruta Mishra [and three others]
| Augmented intelligence in healthcare : a pragmatic and integrated analysis / / Sushruta Mishra [and three others] |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (503 pages) |
| Disciplina | 610.28563 |
| Collana | Studies in Computational Intelligence |
| Soggetto topico |
Artificial intelligence - Medical applications
Artificial intelligence - Methodology |
| ISBN | 981-19-1076-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910564698903321 |
| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Intelligent healthcare : applications of AI in eHealth / / Surbhi Bhatia [and four others], editors
| Intelligent healthcare : applications of AI in eHealth / / Surbhi Bhatia [and four others], editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (328 pages) |
| Disciplina | 610.28563 |
| Collana | EAI/Springer Innovations in Communication and Computing |
| Soggetto topico |
Artificial intelligence - Medical applications
Artificial intelligence - Methodology |
| ISBN | 3-030-67051-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgment -- Contents -- A Healthcare-Based Intelligent Monitoring Paradigm in Quantum Dot Cellular Automata (QCA) to Protect Against Novel Corona Outbreak -- 1 Introduction -- 2 Background -- QCA Concept -- Associative Memory Computation -- CAM Approach Towards Confinement of Associative Memory -- 3 QCA Circuits -- Fundamental Gates -- Memory Cell Structures -- Five-Input Minority Gate -- Five-Input Minority Gate-Based Multilayer CAM Cell -- 4 Scope -- 5 Proposed Paradigm of Healthcare Monitoring -- 6 Entire Operation for Process Flow of Implemented Design in Quantum Dot Cellular Automata (QCA) Nanotechnology -- 7 Results -- 8 Conclusion -- References -- Intelligent Healthcare -- 1 Introduction -- 2 Research Method -- 3 Labelling or Classification of Vital-Sign Data -- Existing One-Class Classification (OCC) Methods -- Existing Two-Class Classification (TCC) Methods -- 4 Results -- Graphical Analysis of Measurement of Systolic, Diastolic and Pulse Rate Parameters -- 5 Discussion -- 6 Conclusion -- References -- Big Data -- 1 Introduction -- 2 Recommendation System and Its Basic Concepts -- Phases of Recommendation System -- Information Collection Phase -- Methodism -- 3 Health Recommendation System -- Designing the Health Recommendation System -- Framework for HRS -- Methods to Design HRS -- Evaluation of HRS -- 4 Proposed Intelligent-Based HRS -- Big Data Analytics and Intelligence Healthcare Perspectives -- Architectural Outline Designed for Big Data Analytics in Health Care -- 5 Intelligence-Based Health Approval Classification via Big Data Analytics -- 6 Enhancing Workflows in Healthcare -- 7 Healthcare Knowledge Bases -- Making Better Doctors -- Optimization -- Diagnosing Disease -- Drug Discovery -- 3D Printing -- Bioprinting and Tissue Engineering -- Drug and Facilities -- Gene Care.
The Virtual and Growing Reality -- Health Treatment and Delivery -- Internet and Classroom Meetings -- Logging In -- Supply Chain Verification -- Entry to Medical Record -- Robot Movement -- Surgery with Robotic Aid -- Drones -- Intelligent Locations -- Hospitals Intelligent -- 8 Advantages and Disadvantages of the Proposed Health Recommendation System Using Big Data Analytics -- 9 Conclusion and Future Research -- References -- Implication of Statistical Methods on Patient Data: An Approach for Cancer Survivability Prediction -- 1 Introduction -- 2 Cancer Statistics -- Breast Cancer -- Ovarian Cancer -- 3 Basics of Survival Analysis -- Censoring -- Hazard Function -- Linear Regression and Its Limitations -- 4 Popular Survival Analysis Method -- Kaplan-Meier -- Log-Rank Test -- Cox Regression -- Random Forest Model -- 5 Result and Discussion -- Data Preparation -- Survival Analysis Using Kaplan-Meier (KM) -- Survival Analysis Using Cox Regression -- 6 Conclusion -- References -- Machine Learning with IoT and Big Data in Healthcare -- 1 Introduction -- 2 Background -- 3 Machine Learning -- Application Areas of Machine Learning in Intelligent Healthcare -- Advantages of Machine Learning -- 4 Big Data in Healthcare -- Big Data Characteristics for Intelligent Healthcare -- Stages of Big Data Analytics -- 5 IoT in Healthcare -- IoT Application Areas in Healthcare -- IoT Offers Following Advantages in Healthcare -- 6 Challenges -- 7 Solutions and Recommendations -- 8 Future Work -- 9 Conclusion -- References -- Modelling Covid-19: Transmission Dynamics Using Machine Learning Techniques -- 1 Background -- 2 Objective -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- An Innovative Pandemic Knowledgebase Using Machine Learning -- 1 Introduction -- 2 Historical Analysis of Epidemic and Pandemic -- 3 COVID - 19: Pandemic. 4 Data Analytics and Knowledgebase -- 5 Novel Case Studies -- International -- National -- 6 Rule-Based Learning in Healthcare Using Pandemic Knowledgebase -- 7 Conclusion -- References -- Reviewing Classification Methods on Health Care -- 1 Introduction to Supervised Learning -- Different Supervised Learning Methods -- Comparative Summary of Supervised Methods -- 2 Applications of Supervised Learning in Healthcare -- 3 Healthcare Datasets Used in the Study -- 4 Classification Metrics -- 5 Methodology -- 6 Results and Analysis -- 7 Conclusion and Future Work -- References -- Predicting and Managing Glycemia Levels Using Advanced Time Series Forecasting Methods -- 1 Introduction -- 2 Background Study -- Defining Time Series and Related Terms -- Various Researchers' Study on Time Series Analysis for Diabetes -- 3 Methodology -- Augmented Dickey-Fuller Test -- ACF and PACF Plots -- Techniques Applied for Time Series Analysis -- ARIMAX -- fbProphet -- Forecasting -- Evaluation Using Mean Absolute Error (MAE) -- 4 Experiment Results and Analysis -- Data Extraction -- Data Preparation -- ARIMAX Model Training -- ADF -- ACF and PACF -- Prophet Model -- Forecasting Model -- Interpreting the Results -- 5 Conclusion and Future Trends -- References -- Machine Learning Applications in Anti-cancer Drug Discovery -- 1 Introduction -- 2 Background -- Drug Repurposing -- Cancer Classification -- Drug Synergy Prediction -- 3 Research Gaps in Computational Drug Discovery -- 4 Future of Computational Drug Discovery -- Deep Learning for Drug Discovery -- Role of Deep Learning in Cancer Classification -- Role of Deep Learning in MicroRNA Analysis in NGS -- 5 Conclusion and Future Directions -- References -- Deep Learning in Healthcare -- 1 Introduction -- 2 Deep Convolution Neural Network (CNNs) in Healthcare -- 3 Deep Learning for Genomics -- 4 Deep Learning in Medicine. Electronic Health Record Data -- ICD-10 Codes -- Probabilistic Diagnoses with Bayesian Networks -- 5 Machine Learning for Microscopy -- Deterministic Super-Resolution Microscopy -- Stochastic Super-Resolution Microscopy -- 6 Natural Language Processing in Healthcare -- 7 Prediction Using EHR -- 8 Deep Learning Support in Healthcare -- 9 Applications of ML in Healthcare -- 10 Applications of ML in Clinical Workflows -- 11 Secure, Private, and Robust ML for Healthcare Solutions -- Data Protection-ML: ML -- 12 Conclusion -- References -- Self-Organized Deep Learning: A Novel Step to Fight Against Severe Acute Respiratory Syndrome -- 1 Introduction -- Overall Theme -- 2 Background -- Contextual Feature of the Book Chapter -- Need of Telemedicine for COVID-19 -- Previous Work -- 3 Working of Proposed Model -- 4 Deep Analysis -- 5 Conclusion -- References -- Clustering Algorithms in Healthcare -- 1 Introduction -- 2 Clustering -- K-Means Clustering -- K-Means Clustering Algorithm -- Mean-Shift Clustering Algorithm -- DBSCAN Clustering -- Expectation-Maximization (EM) Clustering Using Gaussian Mixture Models (GMM) -- Hierarchical Agglomerative Clustering -- 3 Experimental Analysis -- Performance Analysis -- 4 Conclusions -- References -- Multimodal Detection of COVID-19 Fake News and Public Behavior Analysis-Machine Learning Prospective -- 1 Introduction -- 2 Related Works -- 3 About COVID-19 Fake News -- 4 Methodology -- Multimodal Classifiers (MC) -- Support Vector Machines (SVM) -- Stochastic Gradient Descent (SGD) -- Gradient Boosting (GB) -- Bounded Decision Trees (BDT) -- Random Forests (RF) -- 5 Implementation Results -- 6 Conclusion -- 7 Future Scope -- References -- A Review of Machine Learning Approaches in Clinical Healthcare -- 1 Introduction -- 2 Applied Machine Learning in Healthcare -- 3 The Ethics of Using Algorithms in Healthcare. 4 Current Machine Learning Healthcare Applications -- 5 Machine Learning Algorithms -- 6 Future Possibilities in General Practice -- 7 Challenges -- Risks/Threats -- 8 Conclusion -- References -- Coronavirus Pandemic: A Review of a New-fangledRisk to Public Health -- 1 Introduction -- 2 Virion Structure -- 3 Objective -- 4 Methodology of Review -- 5 Epidemiology of COVID-19 -- 6 Total Coronavirus Cases -- 7 Transmission -- 8 Diagnosis -- 9 Prevention of Transmission -- 10 Quarantine -- 11 Treatment -- 12 Application of Nanotechnology to Combat Against Coronavirus -- Diagnosis and Treatment of CoV by Nanomaterials -- Nanomaterials for Facemasks Production -- Nanomaterials for Disinfectants -- Anti-COVID-19 Nanocoating -- 13 Conclusions -- References -- Impact of COVID-19 Pandemic on Obese and Asthma Patients: A Systematic Review -- 1 Introduction -- 2 Conjunction of COVID-19 and Asthma -- Effects of COVID-19 in Asthma Patients -- Symptoms of COVID-19 in Asthma Patients -- Precautions and Measures to Be Taken by Asthma Patients Against COVID-19 -- 3 A Conjunction of COVID-19 and Obesity -- Effects of COVID-19 in Obese Patients -- Symptoms of COVID-19 in Obese Patients -- Precautions and Measures to Be Taken by Obese Patients Against COVID-19 -- 4 Conclusion -- References -- Case Study on COVID-19 Scenario over HighlyAffected States of India -- 1 Introduction -- 2 Specific Healthcare Problems/Difficulties in Indian States -- Healthcare Facilities and Challenges in Maharashtra to Take Care of COVID-19 Scenario in Maharashtra -- Healthcare Facilities and Challenges in Tamil Nadu to Take Care of COVID-19 Scenario -- Healthcare Facilities and Challenges in Delhi to Take Care of COVID-19 Scenario -- Healthcare Facilities and Challenges in Gujarat to Take Care of COVID-19 Scenario. Healthcare Facilities and Challenges in Rajasthan to Take Care of COVID-19 Scenario. |
| Record Nr. | UNINA-9910488697903321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Machine Learning im Logistikmanagement - Entwicklung eines Gestaltungsansatzes zum Einsatz von ML-Anwendungen in logistischen Entscheidungsprozessen / / Manuel Weinke
| Machine Learning im Logistikmanagement - Entwicklung eines Gestaltungsansatzes zum Einsatz von ML-Anwendungen in logistischen Entscheidungsprozessen / / Manuel Weinke |
| Autore | Weinke Manuel |
| Pubbl/distr/stampa | Berlin, Germany : , : Universitätsverlag der Technischen Universität Berlin, , 2023 |
| Descrizione fisica | 1 online resource (xiv, 330 pages) |
| Disciplina | 006.3 |
| Soggetto topico |
Artificial intelligence - Social aspects
Artificial intelligence - Methodology |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | ger |
| Record Nr. | UNINA-9910682540503321 |
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Weinke Manuel
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| Berlin, Germany : , : Universitätsverlag der Technischen Universität Berlin, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Methodology and tools in knowledge-based systems / / José Mira, Angel Pasqual del Pobil, Moonis Ali, editors
| Methodology and tools in knowledge-based systems / / José Mira, Angel Pasqual del Pobil, Moonis Ali, editors |
| Edizione | [1st ed. 1998.] |
| Pubbl/distr/stampa | Berlin, Germany ; ; New York, New York : , : Springer, , [1998] |
| Descrizione fisica | 1 online resource (XLVIII, 892 p.) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence - Methodology
Artificial intelligence - Industrial applications Expert systems (Computer science) |
| ISBN | 3-540-69348-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910484612303321 |
| Berlin, Germany ; ; New York, New York : , : Springer, , [1998] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Methodology and tools in knowledge-based systems / / José Mira, Angel Pasqual del Pobil, Moonis Ali, editors
| Methodology and tools in knowledge-based systems / / José Mira, Angel Pasqual del Pobil, Moonis Ali, editors |
| Edizione | [1st ed. 1998.] |
| Pubbl/distr/stampa | Berlin, Germany ; ; New York, New York : , : Springer, , [1998] |
| Descrizione fisica | 1 online resource (XLVIII, 892 p.) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence - Methodology
Artificial intelligence - Industrial applications Expert systems (Computer science) |
| ISBN | 3-540-69348-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996466080503316 |
| Berlin, Germany ; ; New York, New York : , : Springer, , [1998] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Parsing the turing test [[electronic resource] ] : philosophical and methodological issues in the quest for the thinking computer / / Robert Epstein, Gary Roberts, Grace Beber, editors
| Parsing the turing test [[electronic resource] ] : philosophical and methodological issues in the quest for the thinking computer / / Robert Epstein, Gary Roberts, Grace Beber, editors |
| Edizione | [1st ed. 2009.] |
| Pubbl/distr/stampa | New York, : Springer, c2008 |
| Descrizione fisica | 1 online resource (532 p.) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
EpsteinRobert <1953->
RobertsGary BeberGrace |
| Soggetto topico |
Artificial intelligence
Artificial intelligence - Methodology |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-4020-6710-0
1-281-13868-1 9786611138684 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Setting the Stage -- The Quest for the Thinking Computer -- Alan Turing and the Turing Test -- Computing Machinery and Intelligence -- Commentary on Turing’s “Computing Machinery and Intelligence” -- The Ongoing Philosophical Debate -- The Turing Test -- If I Were Judge -- Turing on the “Imitation Game” -- On the Nature of Intelligence -- Turing’s Test -- The Turing Test: 55 Years Later -- Doing Justice to the Imitation Game -- The New Methodological Debates -- How to Hold a Turing Test Contest -- The Anatomy of A.L.I.C.E. -- The Social Embedding of Intelligence -- How My Program Passed the Turing Test -- Building a Machine Smart Enough to Pass the Turing Test -- Mind as Space -- Can People Think? Or Machines? -- The Turing Hub as a Standard for Turing Test Interfaces -- Conversation Simulation and Sensible Surprises -- A Computational Behaviorist Takes Turing’s Test -- Bringing AI to Life -- Laplace, Turing and the “Imitation Game” Impossible Geometry -- Going Under Cover: Passing as Human -- How not to Imitate a Human Being -- Who Fools Whom? -- Afterthoughts on Thinking Machines -- A Wager on the Turing Test -- The Gnirut Test -- The Artilect Debate. |
| Record Nr. | UNINA-9910453401803321 |
| New York, : Springer, c2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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