Details

Subject(s)

• Computational intelligence [Browse]
• Engineering—Data processing [Browse]
• Machine learning [Browse]

Editor

• Biele, Cezary [Browse]

Series

• Advances in Intelligent Systems and Computing, 1376 [More in this series]
• Advances in Intelligent Systems and Computing, 2194-5365 ; 1376 [More in this series]

Summary note

This book presents the Proceedings of MIDI’2020 – 8th Machine Intelligence and Digital Interaction Conference, December 9–10, 2020, Warsaw, Poland, held online. The rapid development of artificial intelligence (AI) and its growing applications in many fields, such as intelligent voice assistants, e-commerce (chatbots) or navigation, make end users increasingly exposed to such systems. In a world where technological solutions based on artificial intelligence are created by people for people, the final success or failure of a newly created product depends on the focus on human needs. Therefore, it is important to integrate so far independent scientific areas: broadly defined artificial intelligence and human–technology interaction. This book is intended for specialists in the above fields and attempts to integrate the perspectives of engineers and social scientists. The book is a source of inspiration as well as practical and theoretical knowledge for all readers interested in new trends in the field of user-centered AI solutions.

Bibliographic references

Includes bibliographical references.

Contents

• Intro
• Preface
• Contents
• Machine Intelligence
• Neural Machine Translation for Turkish to English Using Deep Learning
• 1 Introduction
• 2 Related Work
• 3 Data Collection, Preprocessing and Test Environment
• 3.1 Data Collection
• 3.2 Preprocessing and Test Environment
• 4 Methodology
• 5 Results and Discussion
• 6 Conclusion and Future Work
• References
• Text Similarity Detection Using Machine Learning Algorithms with Character-Based Similarity Measures
• 2 Literature Review
• 3 Methodology
• 3.1 Character-Based Similarity Methods
• 3.2 Classification Methods
• 4 Experiments
• 4.1 Data Collection and Preprocessing
• 4.2 Training and Model Hyperparameters
• 4.3 Results
• 5 Conclusion
• Palm Tree Detection in Drone Images Using Deep Convolutional Neural Networks: Investigating the Effective Use of YOLO V3
• 1 Introduction and Literature Review
• 2 Research Dataset
• 3 Research Methodology
• 3.1 Training Strategy
• 4 Experiments, Results and Discussion
• 4.1 Evaluation Metrics
• Training and Evaluation of Word Embedding Models for Azerbaijani Language
• 3 Word Embedding Models
• 3.1 Word2Vec
• 3.2 Glove
• 4 Data
• 5 Evaluation of Models
• 5.1 Intrinsic Evaluation
• 5.2 Extrinsic Evaluation
• 6 Conclusion
• Determining Geo-location of Tweets Using Cognitive Intelligence
• 2 Dataset Information
• 3 Experiments
• 3.1 Data Preprocessing and Modeling
• 3.2 Feature Engineering
• 3.3 Classification and Immediate Observation
• 4 Results and Discussions
• 5 Conclusion and Future Work
• Prediction of Locations Using Unsupervised Learning Method to Open a Restaurant Branch
• 2 Literature Survey
• 3.1 Data Collection.
• 3.2 Data Preparation
• 3.3 Data Analysis
• 3.4 Algorithm
• 4 Result and Discussion
• A Framework to Support Creation of AI Applications for Low-Power WSN Nodes
• 1 Motivation
• 2 Embedded AI Use Cases
• 3 Concept Description
• 3.1 Device and Structure Configuration Process
• 3.2 Structure Edition Process
• 3.3 Code Generation Process
• 4 Current Status
• 5 Next Steps
• 6 Conclusions
• Effectiveness of State-of-the-Art Super Resolution Algorithms in Surveillance Environment
• 2 Background
• 3 Working Methodology of Selected SR Algorithms
• 3.1 Learning-Based Super Resolution
• 3.2 Self-similarity-Based Super Resolution
• 3.3 CNN Based Super Resolution
• 3.4 GAN Based Super Resolution
• 4 Implementation
• 5 Experimental Results and Discussions
• Digital Interaction
• Interpersonal Distance in VR: Reactions of Older Adults to the Presence of a Virtual Agent
• 1 Theoretical Context
• 1.1 Serious Virtual Environments
• 1.2 Older Adults' Population
• 2 Method
• 2.1 Participants
• 2.2 Apparatus
• 2.3 Procedure
• 3 Results
• 4 Discussion
• 5 Implications and Further Directions
• UX in Virtual Reality. Qualitative Assessment Based on a Range of Applications
• 3 Method
• 4 Results
• 4.1 Immersion
• 4.2 Level of Presence
• 4.3 Interactivity
• 4.4 Control Modes
• 4.5 Other Observations
• 5 Discussion and Conclusions
• 6 Limitations and Future Directions
• Appendix Topics Discussed in the Qualitative Interview
• Patterns of Digital Users' Irrationality in the Moment of Digital Transformation of the Media
• 1 Our Hypothesis and Its Premises
• 2 Background of the Study
• 3.1 Study Participants and Sample.
• 3.2 Division of Respondents by the Intensity of Internet Use
• 4.1 Insight 1. Digital Intensiveness is a Predictor of Mythical Thinking
• 4.2 Insight 2. Digital Intensiveness is a Predictor of Other Media Decrease in Importance
• 4.3 Insight 3. Digital Intensiveness is a Predictor of Feeling Empowered
• 5 Conclusions
• All Factors Should Matter! Reference Checklist for Describing Research Conditions in Pursuit of Comparable IVR Experiments
• 2 What Factors Matter and Why
• 3 Reference Checklist
• 4 Conclusions
• A Learning Analytics Case Study: Relation of Students Learning Approach to Online Learning Environment Behaviours
• 1.1 Learning Approaches
• 1.2 Online Learning
• 1.3 Learning Analytics
• 2.1 Purpose of the Research
• 2.2 Research Questions
• 2.3 Research Design
• 2.4 Participants
• 2.5 Data Collection Tools
• 4 Conclusion
• Deploying Crowdsourcing for Workflow Driven Business Process-A Brief Proposal
• 2 An Overview of Methods and Practice
• 2.1 Crowdsourcing Platforms
• 2.2 Workflow Management Systems
• 3 Integrating Crowdsourcing Interaction into Business Process Management Platforms
• 3.1 Delegation of the Task by the User to an External PCS
• 3.2 Proposed Workflow Systems Modifications
• Exploration of Voice User Interfaces for Older Adults-A Pilot Study to Address Progressive Vision Loss
• 3 Initial Exploratory Study
• 3.1 Methods
• 3.2 Results and Discussion
• 4 Follow-up In-depth Pilot Study
• 4.1 Methods
• 4.2 Results and Discussion
• Copresence and Well-being in the Time of Covid-19: Is a Video Call Enough to be and Work Together?
• 1 Theoretical Context.
• 1.1 Copresence
• 1.2 Mental Well-being
• 1.3 Research Questions and Hypotheses
• 2.1 Sample and Data Collection
• 2.2 Scales
• 2.3 Data Analysis
• 3.1 Descriptive Statistics
• 3.2 Validation of the Short Singapore Mental Wellbeing Scale in Polish
• 3.3 Predictors of Copresence
• 3.4 Predictors of Mental Well-being
• Technology Enables Struggling with Everyday Life's Chores: Working Women with Two or More Small Children Are Confident Technology Users
• 1 Introduction: Gender, Stress and Technology
• 2 Aim of the Study
• 3 Method (Fieldwork, Respondents, Dates and the Sample)
• 5 Discussion
• References.

Show 149 more Contents items

ISBN

3-030-74728-X

OCLC

1258658043

Doi

• 10.1007/978-3-030-74728-2

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