Theory into poetry [[electronic resource] ] : new approaches to the lyric / / edited by Eva Müller-Zettelmann, Margarete Rubik

• Record Nr.: UNINA9910451536603321
• Pubbl/distr/stampa: Amsterdam, : Rodopi, 2005
• ISBN: 94-012-0251-6; 1-4237-9119-3
• Descrizione fisica: 1 online resource (376 p.)
• Collana: Internationale Forschungen zur allgemeinen und vergleichenden Literaturwissenschaft ; ; 89
• Altri autori (Persone): Müller-ZettelmannEva; RubikMargarete <1950->
• Disciplina: 821.08
• Soggetti: Lyric poetry - History and criticism; Poetry, Modern - History and criticism; Electronic books.
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references.
• Nota di contenuto: Table of Contents; Introduction; DEFINING THE LYRIC; The Lyric: Problems of Definition and a Proposal for Reconceptualisation; The Mental Context of Poetry: From Philosophical Concepts of Self to a Model of Poetic Consciousness (Ethos - Mode - Voice); Eat My Words: Poetry as Transgression; NARRATOLOGY AND BEYOND; Allegory, Metaphor, Scene and Expression. The Example of English Medieval and Early Modern Lyric Poetry; "A Frenzied Oscillation": Auto-Reflexivity in the Lyric; Plotting the Lyric: Forms of Narration in Poetry; The Lyric Insertion in Fiction and Drama: Theory and Practice; In Deep Waters. Or: What's the Difference between Drowning in Poetry and in Prose?"As an unperfect actor on the stage": Notes Towards a Definition of Performance and Performativity in Shakespeare's Sonnets; Diagrammatic Iconicity in Poetry; MAPPING (POST) MODERN POETRY; Inhuman Aesthetics. From Poe, Mallarmé and Valéry to Adorno and Lyotard; Generic Description and the Postmodern Lyric Discourse/Mode: Carol Ann Duffy's "Anne Hathaway"; Poetry under Erasure; The Virtual Muse. Forms and Theory of Digital Poetry; CONSTRUCTING GROUP IDENTITY; Courtship Rituals as Paradigmatic Forms of Poetry: A textual and anthropological perspectivePoetry, Cultural Memory and the English Lyric Tradition; Notes on Contributors
• Sommario/riassunto: At the beginning of the 21st century, there is still no generally accepted comprehensive definition of the lyric or differentiated modern toolkit for its analysis. The reception of poetry is largely characterised either by an empathetic identification of critics with the lyric persona or by exclusive interest in formal patterning. The present volume seeks to remedy this deficit. All the contributors 'theorise' the lyric to overcome the impasse of an impressionistic and narrowly formalistic critical debate on the genre. Their papers focus on a variety of different questions: the problem of esta

The new advanced society : artificial intelligence and industrial Internet of Things paradigm / / edited by Ke Zhang, Yang Hong, and Amir AghaKouchak

• Record Nr.: UNINA9910643177803321
• Pubbl/distr/stampa: Hoboken, New Jersey : , : John Wiley & Sons, Incorporated, , [2022]; ©2022
• ISBN: 1-119-88438-1; 1-119-88439-X; 1-119-88437-3
• Descrizione fisica: 1 online resource (512 pages)
• Collana: Wiley-Scrivener Ser.
• Disciplina: 620.0028563
• Soggetti: Artificial intelligence - Industrial applications; Internet of things
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Cover -- Half-Title Page -- Series Page -- Title Page -- Copyright Page -- Dedication -- Contents -- Preface -- Acknowledgments -- 1 Post Pandemic: The New Advanced Society -- 1.1 Introduction -- 1.1.1 Themes -- 1.1.1.1 Theme: Areas of Management -- 1.1.1.2 Theme: ; Financial Institutions Cyber Crime -- 1.1.1.3 Theme: Economic Notion -- 1.1.1.4 Theme: Human Depression -- 1.1.1.5 Theme: Migrant Labor -- 1.1.1.6 Theme: Digital Transformation (DT) of Educational Institutions -- 1.1.1.7 School and College Closures -- 1.2 Conclusions -- References -- 2 Distributed Ledger Technology in the Construction Industry Using Corda -- 2.1 Introduction -- 2.2 Prerequisites -- 2.2.1 DLT vs Blockchain -- 2.3 Key Points of Corda -- 2.3.1 Some Salient Features of Corda -- 2.3.2 States -- 2.3.3 Contract -- 2.3.3.1 Create and Assign Task (CAT) Contract -- 2.3.3.2 Request for Cash (RT) Contract -- 2.3.3.3 Transfer of Cash (TT) Contract -- 2.3.3.4 Updation of the Task (UOT) Contract -- 2.3.4 Flows -- 2.3.4.1 Flow Associated With CAT Contract -- 2.3.4.2 Flow Associated With RT Contract -- 2.3.4.3 Flow Associated With TT Contract -- 2.3.4.4 Flow Associated With UOT Contract -- 2.4 Implementation -- 2.4.1 System Overview -- 2.4.2 Working Flowchart -- 2.4.3 Experimental Demonstration -- 2.5 Future Work -- 2.6 Conclusion -- References -- 3 Identity and Access Management for Internet of Things Cloud -- 3.1 Introduction -- 3.2 Internet of Things (IoT) Security -- 3.2.1 IoT Security Overview -- 3.2.2 IoT Security Requirements -- 3.2.3 Securing the IoT Infrastructure -- 3.3 IoT Cloud -- 3.3.1 Cloudification of IoT -- 3.3.2 Commercial IoT Clouds -- 3.3.3 IAM of IoT Clouds -- 3.4 IoT Cloud Related Developments -- 3.5 Proposed Method for IoT Cloud IAM -- 3.5.1 Distributed Ledger Approach for IoT Security -- 3.5.2 Blockchain for IoT Security Solution.; 3.5.3 Proposed Distributed Ledger-Based IoT Cloud IAM -- 3.6 Conclusion -- References -- 4 Automated TSR Using DNN Approach for Intelligent Vehicles -- 4.1 Introduction -- 4.2 Literature Survey -- 4.3 Neural Network (NN) -- 4.4 Methodology -- 4.4.1 System Architecture -- 4.4.2 Database -- 4.5 Experiments and Results -- 4.5.1 FFNN -- 4.5.2 RNN -- 4.5.3 CNN -- 4.5.4 CNN -- 4.6 Discussion -- 4.7 Conclusion -- References -- 5 Honeypot: A Trap for Attackers -- 5.1 Introduction -- 5.1.1 Research Honeypots -- 5.1.2 Production Honeypots -- 5.2 Method -- 5.2.1 Low-Interaction Honeypots -- 5.2.2 Medium-Interaction Honeypots -- 5.2.3 High-Interaction Honeypots -- 5.3 Cryptanalysis -- 5.3.1 System Architecture -- 5.3.2 Possible Attacks on Honeypot -- 5.3.3 Advantages of Honeypots -- 5.3.4 Disadvantages of Honeypots -- 5.4 Conclusions -- References -- 6 Examining Security Aspects in Industrial-Based Internet of Things -- 6.1 Introduction -- 6.2 Process Frame of IoT Before Security -- 6.2.1 Cyber Attack -- 6.2.2 Security Assessment in IoT -- 6.2.2.1 Security in Perception and Network Frame -- 6.3 Attacks and Security Assessments in IIoT -- 6.3.1 IoT Security Techniques Analysis Based on its Merits -- 6.4 Conclusion -- References -- 7 A Cooperative Navigation for Multi-Robots in Unknown Environments Using Hybrid Jaya-DE Algorithm -- 7.1 Introduction -- 7.2 Related Works -- 7.3 Problem Formulation -- 7.4 Multi-Robot Navigation Employing Hybrid Jaya-DE Algorithm -- 7.4.1 Basic Jaya Algorithm -- 7.5 Hybrid Jaya-DE -- 7.5.1 Mutation -- 7.5.2 Crossover -- 7.5.3 Selection -- 7.6 Simulation Analysis and Performance Evaluation of Jaya-DE Algorithm -- 7.7 Total Navigation Path Deviation (TNPD) -- 7.8 Average Unexplored Goal Distance (AUGD) -- 7.9 Conclusion -- References -- 8 Categorization Model for Parkinson's Disease Occurrence and Severity Prediction -- 8.1 Introduction.; 8.2 Applications -- 8.2.1 Machine Learning in PD Diagnosis -- 8.2.2 Challenges of PD Detection -- 8.2.3 Structuring of UPDRS Score -- 8.3 Methodology -- 8.3.1 Overview of Data Driven Intelligence -- 8.3.2 Comparison Between Deep Learning and Traditional Machine -- 8.3.3 Deep Learning for PD Diagnosis -- 8.3.4 Convolution Neural Network ; for PD Diagnosis -- 8.4 Proposed Models -- 8.4.1 Classification of Patient and Healthy Controls -- 8.4.2 Severity Score Classification -- 8.5 Results and Discussion -- 8.5.1 Performance Measures -- 8.5.2 Graphical Results -- 8.6 Conclusion -- References -- 9 AI-Based Smart Agriculture Monitoring Using Ground-Based and Remotely Sensed Images -- 9.1 Introduction -- 9.2 Automatic Land-Cover Classification Techniques Using Remotely Sensed Images -- 9.3 Deep Learning-Based Agriculture Monitoring -- 9.4 Adaptive Approaches for Multi-Modal Classification -- 9.4.1 Unsupervised DA -- 9.4.2 Semi-Supervised DA -- 9.4.3 Active Learning-Based DA -- 9.5 System Model -- 9.6 IEEE 802.15.4 -- 9.6.1 802.15.4 MAC -- 9.6.2 DSME MAC -- 9.6.3 TSCH MAC -- 9.7 Analysis of IEEE 802.15.4 for Smart Agriculture -- 9.7.1 Effect of Device Specification -- 9.7.1.1 Low-Power -- 9.7.2 Effect of MAC Protocols -- 9.8 Experimental Results -- 9.9 Conclusion &amp -- Future Directions -- References -- 10 Car Buying Criteria Evaluation Using Machine Learning Approach -- 10.1 Introduction -- 10.2 Literature Survey -- 10.3 Proposed Method -- 10.4 Dataset -- 10.5 Exploratory Data Analysis -- 10.6 Splitting of Data Into Training Data and Test Data -- 10.7 Pre-Processing -- 10.8 Training of Our Models -- 10.8.1 Gaussian Naïve Bayes -- 10.8.2 Decision Tree Classifier -- 10.8.3 Tuning the Model -- 10.8.4 Karnough Nearest Neighbor Classifier -- 10.8.5 Tuning the Model -- 10.8.6 Neural Network -- 10.8.7 Tuning the Model -- 10.9 Result Analysis.; 10.9.1 Confusion Matrix -- 10.9.2 Gaussian Naïve Bayes -- 10.9.3 Decision Tree Classifier -- 10.9.4 Karnough Nearest Neighbor Classifier -- 10.9.5 Neural Network -- 10.9.6 Accuracy Scores -- 10.10 Conclusion and Future Work -- References -- 11 Big Data, Artificial Intelligence and Machine Learning: A Paradigm Shift in Election Campaigns -- 11.1 Introduction -- 11.2 Big Data Reveals the Voters' Preference -- 11.2.1 Use of Software Applications in Election Campaigns -- 11.2.1.1 Team Joe App -- 11.2.1.2 Trump 2020 -- 11.2.1.3 Modi App -- 11.3 Deep Fakes and Election Campaigns -- 11.3.1 Deep Fake in Delhi Elections -- 11.4 Social Media Bots -- 11.5 Future of Artificial Intelligence and Machine Learning in Election Campaigns -- References -- 12 Impact of Optimized Segment Routing in Software Defined Networks -- 12.1 Introduction -- 12.2 Software-Defined Network -- 12.3 SDN Architecture -- 12.4 Segment Routing -- 12.5 Segment Routing in SDN -- 12.6 Traffic Engineering in SDN -- 12.7 Segment Routing Protocol -- 12.8 Simulation and Result -- 12.9 Conclusion and Future Work -- References -- 13 An Investigation into COVID-19 Pandemic in India -- 13.1 Introduction -- 13.1.1 Symptoms of COVID-19 -- 13.1.2 Precautionary Measures -- 13.1.3 Ways of Spreading the Coronavirus -- 13.2 Literature Survey -- 13.3 Technologies Used to Fight COVID-19 -- 13.3.1 Robots -- 13.3.2 Drone Technology -- 13.3.3 Crowd Surveillance -- 13.3.4 Spraying the Disinfectant -- 13.3.5 Sanitizing the Contaminated Areas -- 13.3.6 Monitoring Temperature Using Thermal Camera -- 13.3.7 Delivering Essential Things -- 13.3.8 Public Announcement in the Infected Areas -- 13.4 Impact of COVID-19 on Business -- 13.4.1 Impact on Financial Markets -- 13.4.2 Impact on Supply Side -- 13.4.3 Impact on Demand Side -- 13.4.4 Impact on International Trade -- 13.5 Impact of COVID-19 on Indian Economy.; 13.6 Data and Result Analysis -- 13.7 Conclusion and Future Scope -- References -- 14 Skin Cancer Classification: Analysis of Different CNN Models via Classification Accuracy -- 14.1 Introduction -- 14.2 Literature Survey -- 14.3 Methodology -- 14.3.1 Dataset Preparation -- 14.3.2 Dataset Loading and Data Pre-Processing -- 14.3.3 Creating Models -- 14.4 Models Used -- 14.5 Simulation Results -- 14.5.1 ; Changing Size of MaxPool2D(n,n) -- 14.5.2 Changing Size of AveragePool2D(n,n) -- 14.5.3 Changing Number of con2d(32n-64n) Layers -- 14.5.4 Changing Number of con2d-32*n Layers -- 14.5.5 ROC Curves and MSE Curves -- 14.6 Conclusion -- References -- 15 Route Mapping of Multiple Humanoid Robots Using Firefly-Based Artificial Potential Field Algorithm in a Cluttered Terrain -- 15.1 Introduction -- 15.2 Design of Proposed Algorithm -- 15.2.1 Mechanism of Artificial Potential Field -- 15.2.1.1 Potential Field Generated by Attractive Force of Goal -- 15.2.1.2 Potential Field Generated by Repulsive Force of Obstacle -- 15.2.2 Mechanism of Firefly Algorithm -- 15.2.2.1 Architecture of Optimization Problem Based on Firefly Algorithm -- 15.2.3 Dining Philosopher Controller -- 15.3 Hybridization Process of Proposed Algorithm -- 15.4 Execution of Proposed Algorithm in Multiple Humanoid Robots -- 15.5 Comparison -- 15.6 Conclusion -- References -- 16 Innovative Practices in Education Systems Using Artificial Intelligence for Advanced Society -- 16.1 Introduction -- 16.2 Literature Survey -- 16.2.1 AI in Auto-Grading -- 16.2.2 AI in Smart Content -- 16.2.3 AI in Auto Analysis on Student's Grade -- 16.2.4 AI Extends Free Intelligent Tutoring -- 16.2.5 AI in Predicting Student Admission and Drop-Out Rate -- 16.3 Proposed System -- 16.3.1 Data Collection Module -- 16.3.2 Data Pre-Processing Module -- 16.3.3 Clustering Module -- 16.3.4 Partner Selection Module.; 16.4 Results.