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Umfang: XIII, 493 p. 448 illus., 190 illus. in color. , online resource.

Ausgabe: 1st ed. 2024.

ISBN: 9783658453923

Inhalt: This book teaches you, based on the open-source programming language R, how to read, process, and analyze data from various formats and sources, and how to use Artificial Intelligence and Machine Learning in your company. It specifically explains the three types of Machine Learning and selected, widely-used algorithms that form the basis of Artificial Intelligence. Additionally, the author provides you with the datasets used through his R package "machinelearning," so you can run the code examples presented in the book yourself. The package also includes interactive self-learning tutorials for R. Contents Benefits of Machine Learning and Artificial Intelligence Best Practices Fundamentals of the R Programming Language Fundamentals of Machine Learning with R, including preprocessing, exploratory data analysis, modeling, evaluation, and parameter tuning Application of Machine Learning with R for predictions, classification, clustering, and recommendation systems The Author Bernd Heesen is a professor at the Faculty of Economics at Ansbach University of Applied Sciences in Bavaria. Before his tenure at the university, he worked for more than 10 years as a business consultant both domestically and internationally. He continues to advise companies on the use of IT innovations. The translation was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content. This book is a translation of an original German edition. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation.

Anmerkung: Benefits of Machine Learning and Artificial Intelligence -- Machine Learning -- Best Practices -- Setting Up the R Development Environment -- Fundamentals of the R Programming Language -- Machine Learning with R -- Application of Machine Learning with R -- Outlook.

In: Springer Nature eBook

Weitere Ausg.: Printed edition: ISBN 9783658453916

Weitere Ausg.: Printed edition: ISBN 9783658453930

Sprache: Englisch

DOI: 10.1007/978-3-658-45392-3

URL: https://doi.org/10.1007/978-3-658-45392-3

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Umfang: 1 online resource (192 pages)

Ausgabe: 1st ed.

ISBN: 9783031552724

Serie: Palgrave Studies in Creativity and Culture Series

Anmerkung: Intro -- Acknowledgements -- Contents -- Notes on Contributors -- List of Figures -- Part I Creative Applications of Artificial Intelligence in Education -- 1 Creative Application of Artificial Intelligence in Education -- Introduction -- From Human Intelligence Emulation to Human-AI Creativity -- AI in Education, a Critical Domain for the Society -- The Organisation of the Book -- References -- 2 Preserving Teacher and Student Agency: Insights from a Literature Review -- Introduction -- Artificial Intelligence Applied to Education -- AI Through the Prism of the Technological System -- Agency to Understand and Situate Human Activity -- Research Question -- Method: A Literature Review on Ethical Issues -- Results Related to the Agency of Teachers and Students -- Results for Teacher Agency -- Student Agency Results -- Discussion: Some Nuances and Ways to Guard Against Risks -- Discussion of the Technical System -- Discussion in Relation to Agency -- Avenues for the Development of AI-Based Tools that Preserve Agency -- Conclusion -- References -- 3 Learning Artificial Intelligence Through Open Educational Resources -- Introduction -- AI as an Adaptive Learning Tool -- AI as a Model for Understanding Human Learning -- AI and Citizen Education -- A Shift in Our Way of Thinking -- References -- 4 Digital Acculturation in the Era of Artificial Intelligence -- Introduction -- Digital Acculturation from the Lens of Information and Communication Studies -- The Three Levels of Digital Acculturation -- First Level of Digital Acculturation -- Second Level of Digital Acculturation -- Third Level of Digital Acculturation -- Digital Acculturation Within the Integration of Digital Technologies at School -- Perspectives for Digital Acculturation with Regard to the Perspectives of AI in Learning and Education -- References. , 5 Citizenship, Censorship, and Democracy in the Age of Artificial Intelligence -- Introduction -- Current Problems in the Integration of AI into Education -- Discussion -- References -- Part II Artificial Intelligence in K-12 Education -- 6 International Initiatives and Regional Ecosystems for Supporting Artificial Intelligence Acculturation -- Introduction -- AI Acculturation in the House of Artificial Intelligence -- The Outreach Curriculum for the Acculturation to AI -- Entrepreneurship in the Age of AI -- Gender Perspectives in the Acculturation to AI -- The Smart Hive Interdisciplinary Project -- A Regional Ecosystem for Supporting AI Acculturation -- Discussion -- References -- 7 Informal Education Practices for Human-AI Creative Pedagogy for Accessibility and Inclusivity -- Introduction -- Equal Opportunity Through Science -- Collaborations and Projects -- The Scientotheque Library's Educational Approach to AI -- A Catalogue of Educational Resources on AI -- Teacher Support -- Learning Activities for Better Understanding of AI in Education -- Perspectives -- References -- 8 Students' Perspective on the Use of Artificial Intelligence in Education -- Introduction -- Higher Education Students' Perspective on the Use of AI in Education -- Middle Schoolers Perspectives on AI -- The Life Bloom Academy -- Procedure -- Middle Student Perspectives on AI in Education -- Students Perception of the Nature of AI -- Students' Concerns About Privacy and Social Control in the Era of AI -- Students Perception of AI in the Service of Sustainable Development -- Students' Perception of the Potential of AI in Healthcare -- Students' Expectations of AI at the Service of Education -- Discussion -- References -- Part III Artificial Intelligence in Higher Education -- 9 Affordances for AI-Enhanced Digital Game-Based Learning -- Introduction. , Design Affordances for AI Tools in Education -- Pedagogical Affordances in AI Tools for Education -- Social Affordances in AI for Education -- Technical Affordances in AI for Education -- Affordances Perception, Learning Analytics, and Machine Learning -- Discussion -- References -- 10 Generative Artificial Intelligence in Higher Education -- Introduction -- Uses of AI in Higher Education -- AI for Language Learning and Translation -- Chatbots in Higher Education -- Responsible Use of Generative AI Tools in Academia -- References -- 11 Artificial Intelligence in Professional and Vocational Training -- Introduction -- The Use of Professional Analytics in Designing AI Tools -- Exploring AI in Vocational Training: The Case of French Comté Cheese -- AI Support in Simulated Environments: The Silva Numerica Project -- The Challenges of Utilising AI and Intelligent Tutors in Professional Learning -- Conclusion: Navigating the Terrain of AI in the Field of Professional Learning -- References -- 12 Manifesto in Defence of Human-Centred Education in the Age of Artificial Intelligence -- Introduction -- Empowering Students and Teachers as Decision-Makers -- Impact of Artificial Intelligence on Existing Educational Paradigms -- Artificial Intelligence in Human-Centred Education -- Hybrid Intelligence -- Creative Uses of Artificial Intelligence in Education -- Inclusivity and Diversity in Artificial Intelligence -- Advancing Towards an Increased Human-Centred Education in the Age of AI -- References -- Index.

Weitere Ausg.: Print version: Urmeneta, Alex Creative Applications of Artificial Intelligence in Education Cham : Palgrave Macmillan,c2024 ISBN 9783031552717

Sprache: Englisch

Schlagwort(e): Electronic books. ; Aufsatzsammlung

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Umfang: 1 online resource (192 pages)

Ausgabe: 1st ed.

ISBN: 9783319785035

Anmerkung: Intro -- Preface -- Objectives -- Organisation of Book Chapters -- Intended Readers -- Limitations -- Book Project During Sabbatical Stay in Sydney -- Aims -- Acknowledgements -- Contents -- 1 Introduction -- 1.1 Early Work and Review Articles -- 2 The History of the Patient Record and the Paper Record -- 2.1 The Egyptians and the Greeks -- 2.2 The Arabs -- 2.3 The Swedes -- 2.4 The Paper Based Patient Record -- 2.5 Greek and Latin Used in the Patient Record -- 2.6 Summary of the History of the Patient Record and the Paper Record -- 3 User Needs: Clinicians, Clinical Researchers and Hospital Management -- 3.1 Reading and Retrieving Efficiency of Patient Records -- 3.2 Natural Language Processing on Clinical Text -- 3.3 Electronic Patient Record System -- 3.4 Different User Groups -- 3.5 Summary -- 4 Characteristics of Patient Records and Clinical Corpora -- 4.1 Patient Records -- 4.2 Pathology Reports -- 4.3 Spelling Errors in Clinical Text -- 4.4 Abbreviations -- 4.5 Acronyms -- 4.6 Assertions -- 4.6.1 Negations -- 4.6.2 Speculation and Factuality -- Levels of Certainty -- Negation and Speculations in Other Languages, Such as Chinese -- 4.7 Clinical Corpora Available -- 4.7.1 English Clinical Corpora Available -- 4.7.2 Swedish Clinical Corpora -- 4.7.3 Clinical Corpora in Other Languages than Swedish -- 4.8 Summary -- 5 Medical Classifications and Terminologies -- 5.1 International Statistical Classification of Diseases and Related Health Problems (ICD) -- 5.1.1 International Classification of Diseases for Oncology (ICD-O-3) -- 5.2 Systematized Nomenclature of Medicine: Clinical Terms (SNOMED CT) -- 5.3 Medical Subject Headings (MeSH) -- 5.4 Unified Medical Language Systems (UMLS) -- 5.5 Anatomical Therapeutic Chemical Classification (ATC) -- 5.6 Different Standards for Interoperability -- 5.6.1 Health Level 7 (HL7). , Fast Healthcare Interoperability Resources (FHIR) -- 5.6.2 OpenEHR -- 5.6.3 Mapping and Expanding Terminologies -- 5.7 Summary of Medical Classifications and Terminologies -- 6 Evaluation Metrics and Evaluation -- 6.1 Qualitative and Quantitative Evaluation -- 6.2 The Cranfield Paradigm -- 6.3 Metrics -- 6.4 Annotation -- 6.5 Inter-Annotator Agreement (IAA) -- 6.6 Confidence and Statistical Significance Testing -- 6.7 Annotation Tools -- 6.8 Gold Standard -- 6.9 Summary of Evaluation Metrics and Annotation -- 7 Basic Building Blocks for Clinical Text Processing -- 7.1 Definitions -- 7.2 Segmentation and Tokenisation -- 7.3 Morphological Processing -- 7.3.1 Lemmatisation -- 7.3.2 Stemming -- 7.3.3 Compound Splitting (Decompounding) -- 7.3.4 Abbreviation Detection and Expansion -- A Machine Learning Approach for Abbreviation Detection -- 7.3.5 Spell Checking and Spelling Error Correction -- Spell Checking of Clinical Text -- Open Source Spell Checkers -- Search Engines and Spell Checking -- 7.3.6 Part-of-Speech Tagging (POS Tagging) -- 7.4 Syntactical Analysis -- 7.4.1 Shallow Parsing (Chunking) -- 7.4.2 Grammar Tools -- 7.5 Semantic Analysis and Concept Extraction -- 7.5.1 Named Entity Recognition -- Machine Learning for Named Entity Recognition -- 7.5.2 Negation Detection -- Negation Detection Systems -- Negation Trigger Lists -- NegEx for Swedish -- NegEx for French, Spanish and German -- Machine Learning Approaches for Negation Detection -- 7.5.3 Factuality Detection -- 7.5.4 Relative Processing (Family History) -- 7.5.5 Temporal Processing -- TimeML and TIMEX3 -- HeidelTime -- i2b2 Temporal Relations Challenge -- Temporal Processing for Swedish Clinical Text -- Temporal Processing for French Clinical Text -- Temporal Processing for Portuguese Clinical Text -- 7.5.6 Relation Extraction -- 2010 i2b2/VA Challenge Relation Classification Task. , Other Approaches for Relation Extraction -- 7.5.7 Anaphora Resolution -- i2b2 Challenge in Coreference Resolution for Electronic Medical Records -- 7.6 Summary of Basic Building Blocks for Clinical Text Processing -- 8 Computational Methods for Text Analysis and Text Classification -- 8.1 Rule-Based Methods -- 8.1.1 Regular Expressions -- 8.2 Machine Learning-Based Methods -- 8.2.1 Features and Feature Selection -- Term Frequency-Inverse Document Frequency, tf-idf -- Vector Space Model -- 8.2.2 Active Learning -- 8.2.3 Pre-Annotation with Revision or Machine Assisted Annotation -- 8.2.4 Clustering -- 8.2.5 Topic Modelling -- 8.2.6 Distributional Semantics -- 8.2.7 Association Rules -- 8.3 Explaining and Understanding the Results Produced -- 8.4 Computational Linguistic Modules for Clinical Text Processing -- 8.5 NLP Tools: UIMA, GATE, NLTK etc -- 8.6 Summary of Computational Methods for Text Analysis and Text Classification -- 9 Ethics and Privacy of Patient Records for Clinical Text Mining Research -- 9.1 Ethical Permission -- 9.2 Social Security Number -- 9.3 Safe Storage -- 9.4 Automatic De-Identification of Patient Records -- 9.4.1 Density of PHI in Electronic Patient Record Text -- 9.4.2 Pseudonymisation of Electronic Patient Records -- 9.4.3 Re-Identification and Privacy -- Black Box Approach -- 9.5 Summary of Ethics and Privacy of Patient Records for Clinical Text Mining Research -- 10 Applications of Clinical Text Mining -- 10.1 Detection and Prediction of Healthcare Associated Infections (HAIs) -- 10.1.1 Healthcare Associated Infections (HAIs) -- 10.1.2 Detecting and Predicting HAI -- 10.1.3 Commercial HAI Surveillance Systems and Systems in Practical Use -- 10.2 Detection of Adverse Drug Events (ADEs) -- 10.2.1 Adverse Drug Events (ADEs) -- 10.2.2 Resources for Adverse Drug Event Detection -- 10.2.3 Passive Surveillance of ADEs. , 10.2.4 Active Surveillance of ADEs -- 10.2.5 Approaches for ADE Detection -- An Approach for Swedish Clinical Text -- An Approach for Spanish Clinical Text -- A Joint Approach for Spanish and Swedish Clinical Text -- 10.3 Suicide Prevention by Mining Electronic Patient Records -- 10.4 Mining Pathology Reports for Diagnostic Tests -- 10.4.1 The Case of the Cancer Registry of Norway -- 10.4.2 The Medical Text Extraction (Medtex) System -- 10.5 Mining for Cancer Symptoms -- 10.6 Text Summarisation and Translation of Patient Record -- 10.6.1 Summarising the Patient Record -- 10.6.2 Other Approaches in Summarising the Patient Record -- 10.6.3 Summarising Medical Scientific Text -- 10.6.4 Simplification of the Patient Record for Laypeople -- 10.7 ICD-10 Diagnosis Code Assignment and Validation -- 10.7.1 Natural Language Generation from SNOMED CT -- 10.8 Search Cohort Selection and Similar Patient Cases -- 10.8.1 Comorbidities -- 10.8.2 Information Retrieval from Electronic Patient Records -- 10.8.3 Search Engine Solr -- 10.8.4 Supporting the Clinician in an Emergency Department with the Radiology Report -- 10.8.5 Incident Reporting -- 10.8.6 Hypothesis Generation -- 10.8.7 Practical Use of SNOMED CT -- 10.8.8 ICD-10 and SNOMED CT Code Mapping -- 10.8.9 Analysing the Patient's Speech -- 10.8.10 MYCIN and Clinical Decision Support -- 10.8.11 IBM Watson Health -- 10.9 Summary of Applications of Clinical Text Mining -- 11 Networks and Shared Tasks in Clinical Text Mining -- 11.1 Conferences, Workshops and Journals -- 11.2 Summary of Networks and Shared Tasks in Clinical Text Mining -- 12 Conclusions and Outlook -- 12.1 Outcomes -- References -- Index.

Weitere Ausg.: Print version: Dalianis, Hercules Clinical Text Mining Cham : Springer International Publishing AG,c2018 ISBN 9783319785028

Sprache: Englisch

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Umfang: 1 online resource (509 pages)

Ausgabe: 1st ed. 2024.

ISBN: 9789819738106

Serie: Lecture Notes in Networks and Systems, 1006

Inhalt: This book presents high-quality, peer-reviewed papers from 3rd International Conference on “Universal Threats in Expert Applications and Solutions" (UNI-TEAS 2024), jointly being organized by IES University, Bhopal, and Shree KKarni Universe College, Jaipur, in association with CSI Jaipur Chapter and Jaipur ACM Professional Chapter during January 6–9, 2024. The book is a collection of innovative ideas from researchers, scientists, academicians, industry professionals, and students. The book covers a variety of topics, such as expert applications and artificial intelligence/machine learning; advance web technologies such as IoT, big data, cloud computing in expert applications; information and cyber security threats and solutions, multimedia applications in forensics, security and intelligence; advancements in app development; management practices for expert applications; and social and ethical aspects in expert applications through applied sciences.

Anmerkung: Intro -- Preface -- Acknowledgements -- About This Book -- Contents -- Editors and Contributors -- An Advanced Algorithm and Utility for Identifying Critical Web Vulnerabilities with Exceptional Performance -- 1 Introduction -- 1.1 Automated Testing Mechanisms -- 1.2 Use of Machine Learning Techniques -- 1.3 Techniques for Reducing Input Data Space -- 1.4 Scanning Tool Development -- 2 Considered Website Vulnerability -- 2.1 SQL Injection -- 2.2 Cross-Site Scripting -- 3 Related Study -- 4 Proposed and Improved Algorithms -- 5 Algorithm for Detecting XSS -- 6 Enhancing Vulnerability Detection through the Application of Machine Learning -- 7 Scanning Tool -- 8 Systematic Flow of GKD Website Scanner -- 9 Conclusion -- References -- Potential Impacts of Online-Based Learning 2.0 and Certification on Employability -- 1 Introduction -- 1.1 Background -- 1.2 Statement of the Problem -- 1.3 Study Rationale -- 1.4 Purpose of This Work -- 1.5 Limitations and Scope of the Work -- 1.6 Research Hypothesis -- 2 Research Methodology -- 2.1 The Sample Size of the Work -- 2.2 Data Collection -- 3 Data Analysis, Results, and Discussions -- 3.1 Average Age -- 3.2 Education Background -- 3.3 Employment -- 3.4 Online Certification -- 3.5 Online-Based Certification Availability -- 3.6 Online-Based Certification Acceptance -- 3.7 Online Certification Improves Skill Development -- 3.8 Online-Based Certification Increases Employability -- 3.9 Online Learning Fosters the Development of Reflective and Critical Thinking -- 3.10 Online Education is Useful for a Wide Range of Professions in Many Industries -- 3.11 Online-Based Learning Provides Knowledge as Required -- 3.12 Online Learning is Advantageous for Career Development and Ongoing Education -- 4 Conclusion -- References. , An Intelligent Self-Driving Car's Design and Development, Including Lane Detection Using ROS and Machine Vision Algorithms -- 1 Existing Work -- 2 Proposed System -- 2.1 Mechanical -- 2.2 Electrical -- 2.3 Algorithm and Machine Vision -- 3 Implementation -- 3.1 Canny Edge Detection -- 3.2 Region of Interest -- 3.3 Hough Transform -- 3.4 Average Slope Intercept -- 3.5 Curvature Calculation -- 3.6 Sliding Window Approach -- 4 Results and Discussion -- 5 Conclusion -- References -- Text Summarization for Kannada Text Documents: A Review -- 1 Introduction -- 2 Review of Literature -- 3 Datasets -- 3.1 Kannada Treebank -- 3.2 Kannada-MNIST: A New Handwritten Digit Dataset for the Kannada Language -- 3.3 Samanantar: Parallel Corpora Collection for 11 Indic Languages -- 3.4 MLe2e -- 3.5 IndicCorp -- 4 Evaluation Measures -- 5 Conclusion and Future Works -- References -- Solar Panel Tracking with Battery-Assisted and Battery Charging Modes -- 1 Introduction -- 2 Literature Review -- 3 Methods and Materials -- 3.1 Implementation Using MATLAB -- 3.2 Charging Mode -- 3.3 Discharging Mode -- 4 Results and Discussion -- 4.1 Hardware Implementation -- 5 Conclusion -- References -- Elevator-Based Earth Tremor Sentinel Technique with MQTT Protocol -- 1 Introduction -- 2 Related Work -- 2.1 Perseverance of Artificial Neural Networks (ANN) in Elevators -- 2.2 Purpose of Accelerometer in Elevators -- 2.3 Precedence of MQTT -- 3 Methodology -- 3.1 The Layout of the Proposed Model -- 3.2 Machine Learning Models for Earthquake Detection -- 3.3 Programming an AI Neural Network -- 4 Discussion -- 5 Conclusion -- References -- An Efficient System Model for Identification of Drug Addiction -- 1 Introduction -- 2 Related Work -- 3 Prpopsed Methodology -- 3.1 Attribute Selection -- 3.2 ID3 Algorithm -- 4 Results and Discussion -- 5 Conclusion and Future Scope -- References. , Design and Analysis of a Multipath Routing Protocol to Enhance QoS in MANET -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Work -- 3.1 Proposed Algorithm -- 4 Results Analysis -- 4.1 Simulation Parameters -- 4.2 Packet Sents -- 4.3 Packet Receives -- 4.4 Percentage of Data Receives (PDR) -- 4.5 Normal Routing Load (NRL) -- 5 Conclusion -- References -- Tagging of Uterine Cervix Cases at Cell and Slide Level Through Transfer Learning -- 1 Introduction -- 1.1 Deep Neural Network -- 1.2 Transfer Learning -- 1.3 ResNet50 -- 1.4 Cervical Cancer -- 2 Literature Review -- 3 Material and Method -- 3.1 Data -- 3.2 Methodology -- 4 Result and Analysis -- References -- Estimation of Medical Expenses Using Machine Learning -- 1 Introduction -- 2 Methodology Applied -- 2.1 Dataset -- 2.2 Feature Engineering -- 2.3 Feature Importance Analysis -- 3 Used Models and Algorithms -- 4 Experiment Results -- 5 Conclusion -- Challenges in Making OCR of Gujarati Newspaper -- 1 Introduction -- 2 Review of Literature -- 2.1 Review on Segmentation -- 2.2 Review on Recognition Text -- 3 Problem in Gujrati Language Newspaper -- 3.1 Scanner Image Quality -- 3.2 Background Noise -- 3.3 Font and Style Variation -- 3.4 Text Size Variation -- 3.5 Complex Ligatures in the Script -- 3.6 Limited Trained Data -- 4 Observation -- 5 Conclusion -- References -- A Hybrid Methodology for Software Development and IT Team Analysis in Manufacturing -- 1 Introduction -- 2 Methods -- 2.1 A Comparison of Project Durations Before and After Model Release -- 2.2 Before and After the Model's Release on DRE -- 2.3 A Comparison of the Costs of Development and Maintenance -- 2.4 Criticality-Based Development to Maintenance Ratio of a Project -- 2.5 A Maintenance Ratio Determined by the Number of Lines of Code -- 3 Conclusion -- References. , AI Enabled Convolutional Neural Networks to Detect Brain Tumors -- 1 Introduction -- 2 Literature Review -- 3 Problem Statement -- 4 Proposed Methodology -- 4.1 Image Database -- 4.2 Data Augmentation with Pre-Processing -- 4.3 Data Split -- 5 Results -- 6 Analysis -- 7 Conclusion -- References -- Increasing Productivity in Software Development Through the Use of Docker Technology -- 1 Introduction of Dockers -- 1.1 Docker -- 1.2 Docker File -- 1.3 Docker Image -- 2 Experiment -- 2.1 Docker Java Image File -- 2.2 Python-Enabled Docker Image File -- 2.3 Comparative Results -- 3 Conclusion -- 4 Future Scope -- References -- Multimodal Fusion-Based Hybrid CRNN Model for Emotion Prediction in Music -- 1 Introduction -- 1.1 Key Contribution -- 2 Article Organization -- 3 Related Work -- 4 Methodology -- 4.1 Data Description -- 4.2 Pre-Processing -- 4.3 Feature Extraction -- 5 Proposed Model -- 5.1 Multimodel Fusion -- 6 Result and Discussion -- 6.1 Experimental Setup for the Proposed System -- 6.2 Implementation Details -- 7 Conclusion -- References -- Multimodal Analysis of Induction Motor Signals for Power Quality Abnormality Detection Using Wavelet-RBF Approach -- 1 Introduction -- 2 Research Contribution -- 3 Proposed Methodology -- 3.1 Wavelet Transform -- 3.2 RBF Neural Networks -- 4 Result Analysis and Discussion -- 4.1 Vibration Analysis Using Sensor and Current Transformer -- 5 Conclusion -- References -- Smart Electronic Speaking Glove for Physically Challenged Person -- 1 Introduction -- 1.1 Research Contribution -- 2 Proposed Methodology -- 3 Implementation and Execution -- 3.1 Hardware Description -- 3.2 Implemented in Proteus Simulation -- 4 Result and Discussion -- 5 Conclusion -- References -- COVID-19 Detection Using Fourier-Bessel Series Expansion-Based Dyadic Decomposition and Custom CNN -- 1 Introduction -- 1.1 Author Contribution. , 2 Article Organisation -- 3 Related Work -- 4 Methodology -- 4.1 Data Description -- 4.2 Image Preprocessing -- 4.3 FBD Methodology -- 5 Proposed Model -- 5.1 SMOTETomek -- 5.2 Keras Tunner -- 6 Result and Discussion -- 6.1 Experimental Configuration for the Suggested System -- 7 Conclusion -- References -- Instantaneous Interpretation into Sign Language for the Hearing Impaired -- 1 Introduction -- 1.1 Feature Extraction -- 1.2 NLP -- 1.3 CNN -- 2 Literature Survey -- 2.1 Improvement of Speech -- 2.2 Translation from Speech to Sign Language -- 2.3 Converter from Speech to Sign Language -- 3 Proposed Methodology -- 3.1 Deaf People's Model -- 3.2 Mute People Model -- 4 Analysis by Comparison to the Current Model -- 5 Conclusion -- 6 Future Scope -- References -- A Review of Anomaly Based Multiple Intrusion Detection Methods Using a Feature Based Deep Learning Approach -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results and Discussions -- 5 Conclusion -- References -- Correlation of Traditional Technique and ML-Based Technique for Efficient Effort Estimation: In Agile Frameworks -- 1 Introduction -- 2 Related Work -- 2.1 Non-Algorithmic Technique-Based Effort Estimation in Agile -- 2.2 Algorithmic Technique-Based Effort Estimation in Agile -- 2.3 Machine Learning-Based Effort Estimation in Agile -- 3 Research Objective -- 3.1 Research Question -- 3.2 Question Objective -- 4 Research Methodology -- 4.1 (RQ1) What Are the Various Traditional Techniques for Effort Estimation in an Agile Context? -- 4.2 (RQ2) What Are the Different ML Techniques for Effort Estimation in an Agile Context? -- 4.3 (RQ3) Which ML Algorithm Outperformed Among Themselves and What Are the Different Metrics Used to Determine the Accuracy of ML Techniques? -- 5 Results -- 6 Conclusion and Discussion -- References. , NLP-Based Processing of Gujarati Compound Word Sandhi's Generation and Segmentation.

Weitere Ausg.: Print version: Rathore, Vijay Singh Universal Threats in Expert Applications and Solutions Singapore : Springer,c2024 ISBN 9789819738090

Sprache: Englisch

DOI: 10.1007/978-981-97-3810-6

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URL: https://doi.org/10.1007/978-981-97-3810-6

UID:

Umfang: 1 online resource (459 pages)

Ausgabe: 1st ed. 2024.

ISBN: 9789819732456

Serie: Lecture Notes in Networks and Systems, 998

Inhalt: This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence, and data analytics, along with advances in network technologies. The book is a collection of peer-reviewed research papers presented at 8th International Conference on Data Management, Analytics and Innovation (ICDMAI 2024), held during 19–21 January 2024 in Vellore Institute of Technology, Vellore, India. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry. The book is divided into two volumes.

Anmerkung: Intro -- Preface -- Contents -- Editors and Contributors -- Comprehensive Survey of Nonverbal Emotion Recognition Techniques -- 1 Introduction -- 2 Applications Based on Understanding Nonverbal Emotion -- 3 Machine/Deep Learning Methods for Recognition of Nonverbal Emotion -- 3.1 Facial Expressions Recognition Machine/deep Learning Methods -- 3.2 Hand Gestures Recognition Machine/Deep Learning Methods -- 3.3 Body Language Recognition Machine/Deep Learning Methods -- 4 Findings -- 5 Conclusion -- References -- A Two-Stage CNN Based Satellite Image Analysis Framework for Estimating Building-Count in Residential Built-Up Area -- 1 Introduction -- 2 Review of the Relevant Research Work -- 3 Background Study -- 3.1 Mask R-CNN -- 3.2 Regression Using CNN -- 4 Proposed Methodology -- 4.1 Overview of Proposed Methodology -- 4.2 Mask R-CNN Top-Down Approach for Segmentation of Built Up Area -- 4.3 CNN Based Regression Model to Estimate Building-Count Within Segmented Built-Up Area -- 5 Experimental Evaluation of the Proposed Framework -- 5.1 Dataset Used -- 5.2 Experimental Setup -- 5.3 Experimental Evaluation Metric -- 5.4 Experimental Results and Discussion -- 6 Conclusion -- References -- Forecast of Energy Demand Using Temporal Fusion Transformer -- 1 Introduction -- 2 Survey of Literature -- 3 Proposed Work -- 3.1 Data Collection and Preprocessing -- 3.2 TFT Model Architecture -- 3.3 Training and Validation -- 4 Results -- 4.1 Forecasts -- 4.2 Interpreting the Seasonality -- 4.3 Detecting Some Accidental or Extreme Events -- 4.4 Ranking the Features -- 5 Conclusion -- References -- Mental Health Prediction Using Artificial Intelligence -- 1 Introduction -- 2 Literature Survey -- 3 Design -- 4 Methodology -- 5 Results -- 6 Future Directions and Limitations -- 7 Conclusion -- References. , VGGish Deep Learning Model: Audio Feature Extraction and Analysis -- 1 Introduction -- 1.1 Feature Extraction -- 1.2 Dataset -- 2 Related Work -- 3 Proposed System -- 3.1 Preprocessing -- 3.2 Feature Extraction -- 3.3 Feature Concatenation and Selection -- 3.4 Classification -- 3.5 Output -- 4 Proposed Algorithm -- 4.1 Initialization -- 5 Results -- 6 Conclusion -- References -- Stacking Ensemble-Based Approach for Sarcasm Identification with Multiple Contextual Word Embeddings -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 Preprocessing -- 3.2 Contextual Word Embeddings -- 3.3 Proposed Model -- 4 Materials and Methods -- 4.1 Dataset -- 4.2 Experimental Setup -- 4.3 Results and Analysis -- 5 Conclusion -- References -- Trigger-Based Pothole Detection, and Warning System with RQ and PHR Mapping -- 1 Introduction -- 2 Related Work and Comparative Study -- 3 Methodology -- 4 Flowcharts -- 5 Result and Discussions -- 6 Conclusion -- References -- Blending Motion Capture and 3D Human Reconstruction Techniques for Enhanced Character Animation -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Technologies Used for 3D Model Building -- 3.2 Technology Used for MoCap -- 3.3 Integration of the Technologies Used -- 3.4 Constraints of the Proposed System -- 4 Result -- 5 Future Scope -- References -- A Comprehensive Survey of Regression-Based Loss Functions for Time Series Forecasting -- 1 Introduction -- 2 Time Series Data -- 3 Regression Loss Functions -- 3.1 Mean Absolute Error (MAE) -- 3.2 Mean Squared Error (MSE) -- 3.3 Mean Bias Error (MBE) -- 3.4 Relative Absolute Error (RAE) -- 3.5 Relative Squared Error (RSE) -- 3.6 Mean Absolute Percentage Error (MAPE) -- 3.7 Root Mean Squared Error (RMSE) -- 3.8 Mean Squared Logarithmic Error (MSLE) -- 3.9 Root Mean Squared Logarithmic Error (RMSLE). , 3.10 Normalized Root Mean Squared Error (NRMSE) -- 3.11 Relative Root Mean Squared Error (RRMSE) -- 3.12 Huber Loss -- 3.13 Log-Cosh Loss -- 3.14 Quantile Loss -- 4 Experiments -- 4.1 Datasets -- 4.2 Performance Metrics -- 5 Conclusion -- References -- Diabetic Retinopathy Detection Using Real-World Datasets of Fundus Images -- 1 Introduction -- 1.1 Diabetic Retinopathy -- 1.2 Severity and Stages -- 2 Literature Review -- 2.1 Research Gaps -- 3 The Dataset -- 3.1 Retinal Image Collection -- 4 Related Work -- 5 Methodology -- 5.1 Data Distribution of Retinal Image Collection -- 5.2 Filtering Out Images with Noise -- 5.3 Image Cropping for Removal of Unnecessary Content -- 6 Model Architecture -- 7 Experimental Analysis -- 8 Results and Discussion -- 8.1 Deep Learning Models Overview -- 8.2 Diagnosis & -- Preventative Measures -- 9 Comparative Analysis -- 10 Future Scope -- 11 Conclusion -- References -- Deep Learning for MRI-Based Brain Tumour Identification and Classification -- 1 Introduction -- 1.1 Viewing Brains -- 1.2 PET Scans -- 1.3 CGI -- 1.4 MRI -- 1.5 Diffusion Scaling Imaging -- 2 Literature Survey -- 3 Proposed Method -- 3.1 Pre Processing -- 3.2 Classification -- 3.3 Characterisation -- 3.4 Grouping -- 3.5 Convolution Neural Network -- 4 Results and Discussion -- 5 Conclusion -- References -- Preserving Tamil Brahmi Letters on Ancient Inscriptions: A Novel Preprocessing Technique for Diverse Applications -- 1 Introduction -- 2 Literature Review -- 3 Methodology for Inscription Translation -- 3.1 Image Blurring -- 3.2 Binarization -- 3.3 Edge Detection -- 4 Results and Discussion -- 5 Conclusion -- References -- Analysis of Regular Machine Learning and Ensemble Learning Approaches for Term Insurance Prediction in Banking Data -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Acquisition of Data -- 3.2 Analysis. , 3.3 Data Preprocessing -- 3.4 Training and Analysis of Models -- 4 Results -- 5 Conclusion -- References -- Platform Independent Satellite Image Processing Using GPGPU -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 3.1 Operating System Portability and Hardware Independence -- 3.2 GPU Detection and Parallel Computing -- 3.3 Change Detection -- 3.4 Algorithms -- 4 Results and Discussions -- 4.1 Evaluation Environment -- 4.2 Evaluation Result -- 5 Conclusion -- 6 Future Scope -- References -- Blending Psychological Models with Modern HCI Techniques to Develop Artificial Emotional Intelligent "Affective" Systems -- 1 Introduction -- 1.1 Understanding Affective Computing -- 1.2 Human Emotions -- 1.3 Paper Organization -- 2 Literature Review -- 3 HCI Techniques for Utilizing Emotion Models -- 3.1 HCI Background -- 3.2 Modern HCI Systems & -- Interaction Modalities -- 4 Blending HCI Approaches with Psychological Models and ML Techniques -- 5 Conclusion -- 5.1 Future Scope -- References -- An Enhanced Deep Learning Method to Generate Synthetic Images with Features That are Comparable to Original Images Using Neural Style Transfer -- 1 Introduction -- 2 Network Architecture -- 2.1 Loss -- 2.2 Content Loss -- 2.3 Style Loss -- 3 Results -- 3.1 Comparative Evaluation -- 4 Conclusion -- References -- Improving Sentiment Analysis by Handling Negation on Twitter Data Using Deep Learning Approaches -- 1 Introduction -- 1.1 Contributions -- 1.2 Organization -- 2 Related Work -- 3 Proposed Methodology -- 3.1 WordNet -- 3.2 Preprocessing -- 3.3 Negation Handling -- 3.4 Classification -- 4 Results -- 4.1 Dataset Description -- 4.2 Experimental Results -- 5 Conclusion -- References -- Comparative Analysis of Deep Learning Models for Car Part Image Segmentation -- 1 Introduction -- 2 Related Works -- 3 Dataset Description -- 4 Methodology. , 4.1 YOLOv8 Segmentation Model -- 4.2 Detectron2 Mask R-CNN Resnet 101 FPN -- 4.3 Detectron 2 Mask R-CNN ResNeXt 101 32×8d FPN -- 5 Experimental Results and Observations -- 6 Conclusion -- References -- Boosting Tiny Object Detection in Complex Backgrounds Through Deep Multi-Instance Learning -- 1 Introduction -- 2 Literature Survey -- 2.1 Multi Instance Metric Learning and Bags -- 3 Methodology -- 3.1 Dataset Preparation -- 3.2 Experimental Design -- 4 Results and Discussion -- 4.1 Experimental Setup -- 5 Conclusion -- References -- Driver Drowsiness Detection System Using YoloV5 -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Technology Used -- 4.1 Design and Analysis -- 5 Result and Experiment -- 5.1 Design and Analysis -- 5.2 Preprocessing -- 5.3 Performance of the Model -- 5.4 Result and Discussion -- 6 Future Scope -- 7 Conclusion -- References -- Shift of Customer from Unorganised to Organised Sector in Retail: Is Adoption of Technology a Catalyst -- 1 Introduction -- 1.1 Background of the Problem -- 1.2 Research Problem and Relevance -- 2 Theoretical Framework and Hypothesis Development -- 3 Research Methodology -- 4 Result and Analysis -- 5 Findings and Discussions -- 6 Conclusion -- 6.1 Usage and Limitations -- References -- E-CNN-FFE: An Enhanced Convolutional Neural Network for Facial Feature Extraction and Its Comparative Analysis with FaceNet, DeepID, and LBPH Methods -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Implementation -- 5 Conclusion -- References -- A Graphical Neural Network-Based Chatbot Model for Assisting Cancer Patients with Dietary Assessment in their Survivorship -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 Material -- 3.2 Software and Hardware Requirements -- 3.3 Method -- 4 Results and Discussion -- 4.1 Time Complexity -- 5 Conclusion -- References. , Plant Identification and Disease Detection System Using Deep Convolutional Neural Networks.

Weitere Ausg.: Print version: Sharma, Neha Data Management, Analytics and Innovation Singapore : Springer,c2024 ISBN 9789819732449

Sprache: Englisch

DOI: 10.1007/978-981-97-3245-6

URL: Volltext  (URL des Erstveröffentlichers)

URL: https://doi.org/10.1007/978-981-97-3245-6

UID:

Umfang: 1 online resource (258 pages)

Ausgabe: 1st ed. 2024.

ISBN: 9783662689806

Inhalt: How does artificial intelligence (AI) work and are there parallels to the human brain? What do natural and artificial intelligence have in common, and what are the differences? Is the brain nothing more than a biological computer? What are neural networks and how can the term deep learning be explained simply? Since the cognitive revolution in the middle of the last century, AI and brain research have been closely intertwined. There have been several spectacular breakthroughs in the field of AI in recent years, from alphaGo to DALL-E 2 and ChatGPT, which were completely unthinkable until recently. However, researchers are already working on the innovations of tomorrow, such as hybrid machine learning or neuro-symbolic AI. But what does this actually mean? Based on current research findings and exciting practical examples, this non-fiction book provides an understandable introduction to the basics and challenges of these fascinating disciplines. You will learn what neuroscience and psychology know about how the brain works and how artificial intelligence works. You will also learn how AI has revolutionized our understanding of the brain and how findings from brain research are used in computer science to further develop AI algorithms. Discover the fascinating world of these two disciplines. Find out why artificial intelligence and brain research are two sides of the same coin and how they will shape our future. The author Patrick Krauss studied medicine, computer science and physics. After completing his doctorate in neuroscience, he habilitated in linguistics on the subject of language processing in neural networks and the brain. He researches and teaches at the University of Erlangen-Nuremberg and the University Hospital Erlangen on topics at the interface of neuroscience, artificial intelligence and language. His scientific work includes over 80 publications. The translation was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content. .

Anmerkung: Part I: Brain research -- The most complex system in the universe -- Building blocks of the nervous system -- Organization of the nervous system -- Organization of the cortex -- Imaging techniques: Watching the brain think -- Memory -- Language -- Cognitive maps and navigation in mental spaces -- Consciousness -- Part II: Artificial intelligence -- What is artificial intelligence -- How does artificial intelligence learn -- Playful artificial intelligence -- Recurrence: learning is not a one-way street -- Creativity: generative artificial intelligence -- Language-talented AI: ChatGPT and co -- How AI learns to learn -- What are AI developers researching today? -- Part III: Challenges -- What is a toaster? Dangerous stickers and other attacks -- Images in rain and sun: It's all about the data -- Hallucinating machines: Fact checks and world models -- Alchemy, reproducibility and black boxes -- A critical appraisal: What AI can't (yet) do -- Challenges of brain research -- What does it mean to understand a system? -- Part IV: Integration -- AI as a tool in brain research -- AI as a model for the brain -- Neuroscience 20: Using brain research to understand AI -- The brain as a template for AI -- Conscious machines? -- Outlook: Holodecks, uploads, brains in tanks and the singularity.

Weitere Ausg.: Print version: Krauss, Patrick Artificial Intelligence and Brain Research Berlin, Heidelberg : Springer Berlin / Heidelberg,c2024 ISBN 9783662689790

Sprache: Englisch

DOI: 10.1007/978-3-662-68980-6

URL: Volltext  (URL des Erstveröffentlichers)

URL: lizenzpflichtig

URL: https://doi.org/10.1007/978-3-662-68980-6

UID:

Umfang: 1 online resource (VII, 382 p.)

ISBN: 3-11-074482-1

Serie: Studies in Digital History and Hermeneutics , 5

Inhalt: As in all fields and disciplines of the humanities, Jewish Studies scholars find themselves confronted with the rapidly increasing availability of digital resources (data), new technologies to interrogate and analyze them (tools), and the question of how to critically engage with these developments. This volume discusses how the digital turn has affected the field of Jewish Studies. It explores the current state of the art and probes how digital developments can be harnessed to address the specific questions, challenges and problems that Jewish Studies scholars confront. In a field characterised by dispersed sources, and heterogeneous scripts and languages that speak to a multitude of cultures and histories, of abundance as well as loss, what is the promise of Digital Humanities methods--and what are the challenges and pitfalls? The articles in this volume were originally presented at the international conference #DHJewish - Jewish Studies in the Digital Age, which was organised at the Centre for Contemporary and Digital History (C²DH) at University of Luxembourg in January 2021. The first big international conference of its kind, it brought together more than sixty scholars and heritage practitioners to discuss how the digital turn affects the field of Jewish Studies.

Anmerkung: Frontmatter -- , Contents -- , Jewish Studies in the Digital Age: Introduction -- , Collections -- , Digitizing Holocaust Memories -- , The Culture of the Very Rich and Very Poor: Do Digital Museum Collections Tell us Anything about Jewish Culture? -- , How “Tools” Produce “Data”: Searching in a Large Digital Corpus of Audiovisual Holocaust Testimonies -- , N-gram-based Content Indexing: Semiautomated Analysis of Holocaust Testimonies -- , Spatiality -- , Mapping Forced Academic Migration -- , The GIS prism: Beyond the Myth of Stockholm’s Ostjuden -- , Archival Research, Virtual Reality, and 3D Modeling: Toward a Comprehensive Reconstruction of the Ghetto of Florence -- , Introducing “Kol ha-Nekudot”/“All the Points”/“Kull al-Nuqaṭ”: Interactive, Online Mapping of the Israeli-Palestinian Region (1840–Present) -- , Text -- , The Digital Humanities and the Ladino Press: Using Machine Learning to Extract and Analyze Visual Content in Historic Ladino Newspapers -- , Using Nodegoat to Track Gendered Political Networks: Henrietta Klotz’s Influence on Henry Morgenthau Jr.’s Advocacy for Jewish Refugees and the State of Israel -- , Constructing the Modern Jewish “Present”: Time and Time Cycles in HaTzfira -- , “Not a Day Without a Line”: Studying the Petitions of Soviet Jewish Refuseniks with the Visualization Tools in R -- , Computational -- , Digitizing Kennicott’s Collation of the Hebrew Bible: Experiences of Encoding and of Computer-assisted Stemmatic Analysis -- , Automatic Identification of Biblical Citations and Allusions in Hebrew Texts -- , Is a Deep Learning Algorithm Effective for the Classification of Medieval Hebrew Scripts? -- , Projecting Punctuation From an Interpolated Translation and Commentary -- , List of Contributors , Issued also in print. , In English.

Weitere Ausg.: ISBN 3-11-074469-4

Sprache: Englisch

Schlagwort(e): Conference papers and proceedings. ; Conference papers and proceedings.

DOI: 10.1515/9783110744828

URL: kostenfrei

URL: kostenfrei

URL: Cover

UID:

Umfang: XXVIII, 970 p. 440 illus., 309 illus. in color. , online resource.

Ausgabe: 1st ed. 2023.

ISBN: 9783031263842

Serie: Lecture Notes in Networks and Systems, 637

Inhalt: This book describes the potential contributions of emerging technologies in different fields as well as the opportunities and challenges related to the integration of these technologies in the socio-economic sector. In this book, many latest technologies are addressed, particularly in the fields of computer science and engineering. The expected scientific papers covered state-of-the-art technologies, theoretical concepts, standards, product implementation, ongoing research projects, and innovative applications of Sustainable Development. This new technology highlights, the guiding principle of innovation for harnessing frontier technologies and taking full profit from the current technological revolution to reduce gaps that hold back truly inclusive and sustainable development. The fundamental and specific topics are Big Data Analytics, Wireless sensors, IoT, Geospatial technology, Engineering and Mechanization, Modeling Tools, Risk analytics, and preventive systems.

Anmerkung: Using Blockchain in University Management Systems- state of art -- Graph Neural Networks to improve Knowledge Graph Embedding: A survey -- Tifinagh Handwritten Character Recognition Using Machine Learning Algorithms -- Maintenance prediction based on Long Short-Term Memory algorithm -- Towards an approach for studying the evolution of learners' learning in E-learning -- Chatbots Technology and its Challenges: An Overview -- Machine Learning, Deep Neural Network and Natural Language Processing based Recommendation System -- Artificial intelligence for fake news -- Traffic congestion and road anomalies detection using CCTVs images processing, challenges & opportunities -- Text-based Sentiment analysis -- Smart tourism destinations as complex adaptive systems: A theoretical framework of resilience and sustainability -- Machine learning algorithms for automotive software defect prediction -- Agile User Stories' Driven Method: A Novel Users Stories Meta-model in the MDA Approach -- AI-based adaptive learning - State of the art -- A new Predictive analytics model to assess the employability of academic careers, based on genetic algorithms -- New approach for anomaly detection and prevention -- FunLexia: an Intelligent Game for Children with Dyslexia to Learn Arabic -- Artificial Neural Networks Cryptanalysis of Merkle-Hellman Knapsack Cryptosystem -- Using machine learning algorithms to increase the supplier selection process efficiency in supply chain 4.0 -- A new approach to intelligent-oriented analysis and design of urban traffic control: Case of a traffic light -- Spatio-temporal crime forecasting: Approaches, datasets, and comparative study -- Data migration from relational to NoSQL database : Review & Comparative study -- Recommendation system: technical study -- The appropriation of the agile approach in public sector: Modeling the achievement of good governance -- The contribution of Deep learning models: application of LSTM to predict the Moroccan GDP growth using drought indexes -- Natural Language Processing and Motivation for Language Learning -- Generating Artworks using One Class SVM with RBF kernel -- Multiobjective Evolutionary Algorithms for Engineering Design Problems -- Designing Hybrid Storage Architectures with RDBMS and NoSQL Systems: A Survey -- Analysis of the pedagogical effectiveness of teacher qualification cycle in Morocco: A Machine learning model approach -- Smart education - A case study on a simulation for climate change awareness & engagement -- Towards an E-commerce personalized recommendation system with KNN classification method -- Convolutional Long Short-Term Memory Network Model for Dynamic Texture Classification: A Case Study -- Towards an accident severity prediction system with Logistic Regression -- FUZZY C-MEANS Based Extended Isolation Forest for Anomaly Detection -- Fashion Image Classification using Convolutional Neural Network-VGG16 and eXtreme Gradient Boosting Classifier -- MentorBot: A Traceability-Based Recommendation Chatbot for Moodle -- Regularization in CNN: A mathematical study for L1, L2 and Dropout regularizers -- Shipment consolidation using K-means and a combined DBSCAN-KNN approach -- A new approach to protect Data in-Use at Document Oriented Databases -- A Dual Carriageway Smart Street Lighting Controller Based On Multi-Variate Traffic Forecast.-Blockchain-based Self Sovereign Identity Systems: high-level processing and a challenges-based comparative analysis -- Impact of Machine Learning on The Improvement of Accounting Information Quality -- NLP Methods' Information Extraction for Textual Data: An Analytical Study -- Handwriting recognition in historical manuscripts using a deep learning approach -- Artificial intelligence for a sustainable finance: A bibliometric analysis -- Geoparsing Recognition and Extraction from Amazigh corpus using The NooJ Complex Annotation Structures -- Agent-based merchandise management and real-time decision support systems -- Selecting the Best Moroccan Tourist Destination Using the Fuzzy Analytic Hierarchy Process -- Improving model performance of the prediction of online shopping using oversampling and feature selection -- Combining Descriptors for Efficient Retrieval in Databases Images -- TOWARDS AN EDUCATIONAL PLANNING INFORMATION SYSTEM IN BIG DATA ENVIRONMENT -- CNN-based Face Emotion Detection and Mouse Movement Analysis to Detect Student's Engagement Level -- Data Cleaning in Machine Learning : Improving Real Life Decisions and Challenges -- Blockchain-Based Cloud Computing: Model-Driven Engineering Approach -- Student Attention Estimation Based on Body Gesture -- Cat Swarm Optimization Algorithm for DNA Fragment Assembly Problem -- DSGE AND ABM, TOWARDS A "TRUE" REPRESENTATION OF THE REAL WORLD? -- Predictive Hiring System: Information Technology Consultants Soft Skills -- Automated Quality Inspection Using Computer Vision: a Review -- A Comparative Study of Adaptative Learning Algorithms for Students' Performance Prediction: Application in a Moroccan University Computer Science Course -- Pedestrian Orientation Estimation using Deep Learning -- Artificial intelligence application in drought assessment, monitoring and forecasting using available remote sensed data -- CSR communication through social networks: the case of committed brandbanks in Morocco -- Content-Based Image Retrieval Using Octree Quantization Algorithm -- Release Planning Process Model in Agile Global Software Development -- Developing a New Indicator Model to Trade Gold Market -- A new model indicator to trade Foreign Exchange market -- Improving Arabic to English Machine Translation -- Artificial Neural Network with Learning Analytics for Student Performance Prediction in Online Learning Environment -- Attentive Neural Seq2Seq for Arabic Question Generation -- Microservice-Specific Language, a step to the Low-code platforms -- Case Study of Economic Dispatch Problem in Smart Grid System -- Teaching Soft Skills online, what are the most appropriate pedagogical paradigms? -- Road Object Detection: A Case Study of Deep Learning-Based Algorithms -- A comparative review of Tweets Automatic Sarcasm Detection in Arabic and English -- Mobile payment as a lever for financial inclusion -- New Approach to Interconnect Hybride Blockchains -- A Variable Neighborhood Search (VNS) heuristic algorithm based classifier for credit scoring -- Application of Machine Learning Techniques To Enhance Decision Making Lifecycle -- A Smart interactive decision support system for real-time adaptation in the mobility strategy for optimization of the employee's transportation -- A Hesitant fuzzy Holdout method for models' selection in Machine Learning -- Interpretable Credit Scoring Model Via Rule Ensemble -- A New Distributed Architecture Based on Reinforcement Learning for Parameter Estimation in Image Processing -- Smart Sourcing Framework for Public Procurement Announcements Using Machine Learning Models -- An MCDM-Based Methodology for Influential Nodes Detection in a Social Network. Facebook as a Case Study -- A Predictive Approach based on Feature Selection to Improve Email Marketing Campaign Success Rate -- DIAGNOSIS AND ADJUSTMENT FOR SUSTAINABLE TOURISM.

In: Springer Nature eBook

Weitere Ausg.: Printed edition: ISBN 9783031263835

Weitere Ausg.: Printed edition: ISBN 9783031263859

Sprache: Englisch

DOI: 10.1007/978-3-031-26384-2

URL: https://doi.org/10.1007/978-3-031-26384-2

URL: Volltext  (URL des Erstveröffentlichers)

UID:

Umfang: XV, 731 p. 343 illus., 259 illus. in color. , online resource.

Ausgabe: 1st ed. 2023.

ISBN: 9789811926006

Serie: Lecture Notes on Data Engineering and Communications Technologies, 137

Inhalt: This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence, and data analytics, along with advances in network technologies. The book is a collection of peer-reviewed research papers presented at Sixth International Conference on Data Management, Analytics and Innovation (ICDMAI 2022), held virtually during January 14-16, 2022. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.

Anmerkung: Part I: Machine Learning -- Recognizing similar relationships within ontology to fine tune Ontology -- Object Detection using Peak, Balanced Division Point and Shape based Features -- End to End Agile and Automated Machine Learning Framework for Trustworthy, Reliable and Sustainable Artificial Intelligence -- Automated Structured Data Extraction from Scanned Document Images -- Effective Sentiment Analysis of Bengali Corpus by using the Machine Learning approach -- Review on Android Malware Detection System -- Hypothesis Testing of Tweet Text using NLP -- Forecasting Severe Thunderstorm by applying SVM Technique on Cloud imageries -- Breast Cancer Prediction using MachineLearning Techniques -- Ontology-Driven Scientific Literature Classification using Clustering and Self-Supervised Learning -- Modeling and forecasting Tuberculosis cases using machine learning and deep learning approaches: A Comparative Study -- Drone Integrated Detection and Rebarbative System with Variable Frequency for Agricultural Farm Invading Animals -- Support Vector Machines and Random Forest Classification models for identification of Stability in Extrusion Film Casting Process -- Predicting CO2 emissions by Vehicles using Machine Learning -- Augmented Feature Generation using Maximum Mutual Information Minimum Correlation -- Impact of Energy Sector on Climate Change in India using Forecasting Models -- Towards Efficient Edge Computing Through Adoption of Reinforcement Learning Strategies: A Review -- Thematic Classification Based On Topological Traits -- Machine Learning based Earthquake Early Warning (EEW) System: A case study of Himalayan Region -- Topic Modelling Based Semantic Search -- Machine Learning based Automated Process for Predicting the Anomaly in AIS Data -- A Hybrid Machine Learning Model for Estimation of Obesity Levels -- Part II: AI & Deep Learning -- Regulations 4.0: Digitally Transforming the Regulatory Space -- Speech To Text for Data Entry - Opportunities and Challenges -- A Gamification Architecture For Online Learning Platform using Neural Network -- Literature Review on Sign Language Generation -- Indoor Navigation Using Augmented Reality -- Foreign object detection on an assembly line -- Inverse Contexture Abstractive Term Frequency Model using Surf Scale Diffusive Neural Network for analysis of fake social content in public forum -- Literature Review on Machine Translation Systems for Sign Language Generation -- Depression Detection from Twitter Data using Two Level Multi-modal Feature Extraction -- COVID-19 Regulations Check: Social Distancing, People Counting and Mask Wear Check -- Urdu & Hindi Poetry Generation using Neural Networks -- Implementation of Open Domain Question Answering System -- Design and Implementation of Surround View Monitoring System in View of Autonomous Vehicle -- Generation of Indian Sign Language Animation from Audio and Video Content using Natural Language Processing -- Histogram Based Initial Centroids Selection for K-Means Clustering -- Siamese Network-based system for criminal identification -- Track-III: Data Storage Management & Innovation -- Organization Network Analysis for study of employee techno-social connects and effect of human behavior and organizational culture on the underlying network -- Track IV: Enabling Technologies & Applications -- Sky Computing Smart Locality Aware approach for Health Analytics -- Citation Biases: Detecting Communities from Patterns of Temporal Variation in Journal Citation Networks -- Enhancing the Performance of Multiple Wi-Fi Network -- ARCaddy: Augmented Reality App Suite for Aircraft Maintenance -- Meditation Therapy for Stress Management Using Brainwave Computing and Real Time Virtual Reality Feedback -- Real Time Carbon Emissions Calculator for Personal Computers -- Track-V: Data Science Techniques for handling Pandemic -- Navigation System for Visually Impaired People -- Design aspects of a Multi-dimensional Hybrid analytical processing system -- A data science approach to evaluate drug effectiveness: Case Study of Remdesivir for Covid-19 patients in India -- A Softcomputing Approach For Predicting And Categorising Learner's Performance Using Fuzzy Model.

In: Springer Nature eBook

Weitere Ausg.: Printed edition: ISBN 9789811925993

Weitere Ausg.: Printed edition: ISBN 9789811926013

Weitere Ausg.: Printed edition: ISBN 9789811926020

Sprache: Englisch

DOI: 10.1007/978-981-19-2600-6

URL: https://doi.org/10.1007/978-981-19-2600-6

URL: Volltext  (URL des Erstveröffentlichers)

UID:

Umfang: 1 online resource (443 pages)

Ausgabe: 1st ed.

ISBN: 9781040108765

Inhalt: Doing Feminist Urban Research introduces the reader to the newly emerging 21st century global landscape of feminist urban research. It showcases decolonising practices, partnerships and teamwork, new standards such as EDI, geo-ethnographic methodologies, software-enhanced qualitative data analysis, and knowledge mobilisation.

Anmerkung: Cover -- Half Title -- Title -- Copyright -- Series -- Dedication -- Brief contents -- Detailed contents -- List of figures and tables -- List of companion website materials -- List of editor, author, and contributor biographies -- Acknowledgements -- 0 Introducing GenUrb -- Section 1. Introducing Doing feminist urban research: insights from the GenUrb project -- Section 2. Introducing GenUrb -- (i) The GenUrb partnership -- GenUrb example 0.1: The evolution of the GenUrb partnership -- (ii) The cities in GenUrb -- (iii) The people in GenUrb -- GenUrb example 0.2: Feminist friendships and mentoring in the Delhi City Research Team -- GenUrb example 0.3: Members of GenUrb's York University team -- Section 3. How this book is organised -- (i) Part I. The building blocks for decolonising feminist urban research -- (ii) Part II. The context of 21st-century urban feminist research -- (iii) Part III. Feminist research standards -- (iv) Part IV. Feminist methodologies and methods -- (v) Part V. Feminist qualitative data analysis -- (vi) Part VI. Feminist approaches to knowledge mobilisation -- Section 4. Chapter structure -- Section 5. Summary -- Part I The building blocks for decolonising feminist urban research -- 1 Feminist comparative urban research -- Learning objectives -- Section 1. The global South -- (i) Evolution of the terminology of the global South -- (ii) The employment of global South terminology -- GenUrb example 1.1: The standing of the term 'global South' -- Reflection exercise 1.1: Determining your usage of the term global South -- (iii) The urban global South -- Section 2. Comparative urban research -- Section 3. Lineages of feminist comparative urban research -- (i) Track one: Policy- and development-driven comparison for women's inclusion -- (ii) Track two: Transnational epistemologies of the gendered production of urban space. , (iii) Track three: Comparison as feminist global urban theory building -- Reflection exercise 1.2: The post-colonial, anti-colonial, and decolonial -- Section 4. GenUrb and the comparative -- Section 5. Summary -- 2 Decolonising feminist knowledge production -- Learning objectives -- Section 1. Decolonising knowledge production in feminist urban research -- GenUrb example 2.1: Decolonising feminist research: the perspective of Red Thread -- Section 2. Decoding affinity and difference in a feminist project -- Reflection exercise 2.1: Lines of affinity and difference -- Section 3. Circulations of spatial and temporal difference -- GenUrb example 2.2: Feminist enactments (i) Peer-mentoring -- Reflection exercise 2.2: Generational positionality and mentoring -- Section 4. Circulations of labour in feminist knowledge production -- GenUrb example 2.3: Feminist enactments (ii) Training -- Section 5. Co-learning across difference -- GenUrb example 2.4: Feminist enactments (iii) Co-learning across difference -- Reflection exercise 2.3: Collaboration and community in and beyond the academy -- Section 6. Summary -- 3 Feminist engagements with translation -- Learning objectives -- Section 1. 'Translation', 'interpreting', and making meaning across difference -- GenUrb example 3.1: Languages and dialects spoken by members and participants in the GenUrb project -- Section 2. Anglophone hegemony -- Reflection exercise 3.1: Citational politics -- Section 3. Decolonising translation -- Reflection exercise 3.2: Translation, difference, and power -- Section 4. Decolonial feminist approaches -- Section 5. Summary -- 4 Feminist scholar-activism -- Learning objectives -- Section 1. The academy and feminist scholar-activism -- Section 2. Being a feminist scholar-activist -- Reflection exercise 4.1: Situating the self in feminist activist praxis. , Section 3. Defending space for feminist activism in the neoliberal university -- GenUrb example 4.1: Types of engagement adopted by GenUrb inside and beyond the academy -- Reflection exercise 4.2: Connecting with communities, creating solidarities -- Section 4. The challenges of feminist scholar-activist research in transnational contexts -- (i) Feminist scholar-activist research and transnational power dynamics -- (ii) Co-authorship as feminist alliance work -- GenUrb example 4.2: Issues of co-authorship on academic publications -- Section 4. Summary -- Part II The context of 21st-century feminist urban research and policy -- 5 Feminist urban research in the time of COVID-19 -- Learning objectives -- Section 1. Pandemics and urban society -- Section 2. The gendered and racialised social impacts of COVID-19 on everyday urban life -- (i) Gender and the pandemic geographies of social reproduction -- GenUrb example 5.1: Research on everyday life during the pandemic -- (ii) The carceral logics of pandemic geographies -- Section 3. Practicing feminist urban research in a time of ecological crisis -- (i) Shifting methodological perspectives in research during a time of crisis -- Reflection exercise 5.1: Collecting data when not in the field -- (ii) Adapting research methods in a time of crisis -- GenUrb example 5.2: Adapting research methods during the COVID-19 pandemic -- Reflection exercise 5.2: Doing research in a time of global crisis -- Section 4. COVID-19, feminist policy, and data disaggregation -- Reflection exercise 5.3: Data limitations and feminist policy research -- Section 5. Summary -- 6 Feminist urban policy and the Sustainable Development Goals -- Learning objectives -- Section 1. Feminist approaches to urban policy -- (i) Gender-responsive urban policy -- Reflection exercise 6.1: A women's charter for the right to the city. , (ii) Feminist engagements with global frameworks for urban governance -- Section 2. The Sustainable Development Goals -- Reflection exercise 6.2: Gender and the Sustainable Development Goals -- Section 3. The synergies between SDG 5 and SDG 11 -- GenUrb example 6.2: Research on SDG 5 and SDG 11 -- Section 4. Local adaptation of the Sustainable Development Goals -- GenUrb example 6.2: Understanding local adaptation of the Sustainable Development Goals -- Section 5. Connecting research and policy -- Reflection exercise 6.3: Crafting a policy memorandum -- Section 6. Summary -- Part III Feminist research standards -- 7 Feminist research ethics -- Learning objectives -- Section 1. Ethics and research -- Reflection exercise 7.1: Values in feminist research -- Section 2. Towards a feminist ethics -- Section 3. Feminist ethics and research -- GenUrb example 7.1: Examples of common ethical issues -- GenUrb example 7.2: Muddling through ethical decision-making -- Reflection exercise 7.2: Enacting an ethics of care -- Section 4. Summary -- 8 Professional standards in feminist research -- Learning objectives -- Section 1. Professional standards in the academy -- (i) Professional standards in academic work -- (ii) Feminist engagements with and critiques of professional standards -- Reflection exercise 8.1: Professional standards at your university -- Section 2. Ethics policies -- Reflection exercise 8.2: Research ethics policies at your university -- Section 3. Equity, diversity, and inclusion -- Reflection exercise 8.3: EDI at your university -- Section 4. Monitoring and evaluation -- GenUrb example 8.1: Monitoring and evaluation indicators used to measure how knowledge mobilisation is applied to different groups of knowledge producers and users -- GenUrb example 8.2: Monitoring and evaluation challenges. , Reflection exercise 8.4: Engaging in monitoring and evaluation in your research -- Section 5. Knowledge mobilisation -- Section 6. Summary -- 9 Partnerships and teamwork in feminist collaborations -- Learning objectives -- Section 1. Research partnerships -- GenUrb example 9.1: The formal GenUrb partnership -- GenUrb example 9.2: The value of the GenUrb partnership -- (i) Establishing partnerships -- (ii) Managing partnerships -- GenUrb example 9.3: A day in the life of a project manager -- (iii) Partnerships and leadership -- GenUrb example 9.4: Developing a feminist leadership style -- Reflection exercise 9.1: Research partnerships across difference -- Section 2. Partnership challenges -- GenUrb example 9.5: Challenges to managing partnerships -- Section 3. Transnational feminist praxis and teamwork -- (i) Transnational feminist praxis -- (ii) Teamwork -- Reflection exercise 9.2: Issues in feminist team research -- Section 4. Summary -- 10 Data management in feminist research projects -- Learning objectives -- Section 1. Mainstream and feminist conceptions of data -- Reflection exercise 10.1: Types of data and their implicit values -- Section 2. Research data management -- (i) The data management plan -- GenUrb example 10.1: Data management issues -- (ii) Devising your own data management plan -- Reflection exercise 10.2: Brainstorming a data management plan -- (iii) Addressing data ownership in feminist research -- GenUrb example 10.2: Questions of data ownership -- Reflection exercise 10.3: Problematising ownership of and access to data as feminist researchers -- Section 3. Feminist perspectives on data management -- (i) Feminist data studies -- Reflection exercise 10.4: Navigating the feminist ethics of sharing sensitive data -- (ii) Feminist engagement with machine learning and open access data practices -- (iii) Archiving data. , GenUrb example 10.3: Archiving data.

Weitere Ausg.: Print version: Peake, Linda Doing Feminist Urban Research Oxford : Taylor & Francis Group,c2024 ISBN 9781032668680

Sprache: Englisch

Schlagwort(e): Electronic books.

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