
Man-Machine Interactions 6
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This book includes a selection papers describing the latest advances and discoveries in the field of human-computer interactions, which were presented at the 6th International Conference on Man-Machine Interactions, ICMMI 2019, held in Cracow, Poland, in October 2019.
Human-computer interaction is a multidisciplinary field concerned with the design of computer technology and, in particular, the interaction between humans (the users) and computers. Over recent decades, this field has expanded from its initial focus on individual and generic user behavior to the widest possible spectrum of human experiences and activities. The book features papers covering a variety of topics, which are divided into five sections: 'human-computer interfaces,' 'artificial intelligence and knowledge discovery,' 'pattern recognition,' 'bio-data and bio-signal analysis,' and 'algorithms, optimization and signal processing.' Presenting the latest research in the field, this book provides a valuable reference resource for academics, industry practitioners and students.
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Persons
Content
- Intro
- Preface
- Organization
- Honorary Patronage
- Conference Chair
- Programme Committee
- Additional Reviewers
- Organizing Committee
- Contents
- Human-Computer Interfaces
- Head-Based Text Entry Methods for Motor-Impaired People
- 1 Introduction
- 2 Text-Entry Methods for Motor-Impairment
- 3 Head-Based Text Entry Methods
- 4 Evaluation
- 4.1 Participants and Procedure
- 4.2 Results
- 5 Conclusions
- References
- VEEP-The System for Motion Tracking in Virtual Reality
- 1 Introduction
- 2 The System Outline
- 2.1 VR Goggles
- 2.2 Game Engine
- 2.3 Motion Tracking
- 3 Localization of 2D Markers in Images
- 4 3D Position Calculation
- 4.1 Calibration and Tsai Model
- 4.2 Calculation of 3D Points
- 4.3 Tracking the Markers
- 5 Experimental Environment
- 6 Efficiency
- 6.1 Network Efficiency
- 6.2 Tracker Efficiency
- 6.3 Coupler Efficiency
- 7 Accuracy
- 8 Summary
- References
- Immersive Virtual Reality for Assisting in Inclusive Architectural Design
- 1 Introduction
- 2 Inclusive Architectural Design
- 3 Computer Aided Architectural Design Process
- 4 IVR in Architectural Design Case Study
- 5 Conclusion
- References
- Spatio-Temporal Filtering for Evoked Potentials Detection
- 1 Introduction
- 2 Methods
- 2.1 Spatio-Temporal Filtering
- 2.2 Learning Phase
- 3 Numerical Experiments
- 3.1 Quantitative Results
- 3.2 Qualitative Results
- 4 Conclusion
- References
- A Review on the Vehicle to Vehicle and Vehicle to Infrastructure Communication
- 1 Introduction
- 2 Wireless Technologies
- 2.1 Non-standard Data Transmission
- 2.2 Data Transmission with WiFi Standard
- 2.3 Data Transmission with DSRC Standard
- 2.4 Data Transmission with C-ITS Standard
- 2.5 Data Transmission with Cellular Networks
- 3 Comparison of Technologies
- 4 Conclusion
- References
- Artificial Intelligence and Knowledge Discovery
- Classifying Relation via Piecewise Convolutional Neural Networks with Transfer Learning
- 1 Introduction
- 2 Related Work
- 3 Methodology
- 3.1 The Neural Network Architecture
- 3.2 Transferring Knowledge of Parameters
- 4 Experiments
- 4.1 Experimental Settings
- 4.2 Comparison with Other Relation Classification Methods
- 4.3 Effect of Transfer Learning
- 4.4 Effect of Different Features
- 5 Conclusion and Future Works
- References
- Ensembles of Active Adaptive Incremental Classifiers
- 1 Introduction
- 2 Concept Drift Detection
- 3 Proposed Solution
- 4 Experiments and Results
- 4.1 Data Sets
- 4.2 Experimental Setup
- 4.3 Results
- 5 Conclusions
- References
- Influence of the Applied Outlier Detection Methods on the Quality of Classification
- 1 Introduction
- 1.1 Related Work
- 1.2 Contribution
- 1.3 Paper Structure
- 2 Outlier Detection Methods
- 2.1 Interquartile Method
- 2.2 Distance-Based Method
- 2.3 Local Outlier Factor
- 2.4 Angle Based Outlier Detection
- 3 Experiments
- 4 Conclusions and Future Work
- References
- Predictive Algorithms in Social Sciences - Problematic Internet Use Example
- 1 Introduction
- 2 Problematic Internet Use
- 2.1 Model and Aspects of Problematic Internet Use
- 2.2 Subscales
- 3 Need for Using Algorithms in Social Sciences
- 4 Data
- 5 Results
- 5.1 All Results
- 5.2 Best Results
- 6 Discussion
- 7 Conclusions
- References
- FIT2COMIn - Robust Clustering Algorithm for Incomplete Data
- 1 Introduction
- 2 Fuzzy Interval Type-2 C-Ordered Means for Incomplete Data
- 3 Experiments
- 3.1 Datasets
- 3.2 Numerical Experiments
- 4 Conclusions
- References
- GrFCM - Granular Clustering of Granular Data
- 1 Introduction
- 1.1 Data Granules
- 1.2 Extensional Fuzzy Numbers
- 1.3 Granular Fuzzy C-Means Clustering Algorithm
- 2 Experiments
- 2.1 Data Sets
- 2.2 Results
- 3 Conclusions
- References
- Pattern Recognition
- Evaluation of Cosine Similarity Feature for Named Entity Recognition on Tweets
- 1 Introduction
- 2 Tweet Data and Features
- 2.1 Tweet Data
- 2.2 Feature Set
- 3 Tests and Evaluation
- 3.1 Implementation
- 3.2 Test and Results
- 4 Conclusions
- References
- Deep Recurrent Neural Networks for Human Activity Recognition During Skiing
- 1 Introduction
- 2 Sensors Data
- 3 Deep Models
- 3.1 Recurrent Neural Network
- 3.2 Long Short-Term Memory
- 4 Experimental Setup
- 4.1 Proposed Network Architectures
- 4.2 Network Training
- 4.3 Performance Metrics
- 5 Results
- 6 Discussion
- 7 Conclusions
- References
- Recognition of Tennis Shots Using Convolutional Neural Networks Based on Three-Dimensional Data
- 1 Introduction
- 2 Literature Review
- 3 The Concept of the Convolutional Network
- 3.1 Inception Architecture
- 3.2 MobileNet Architecture
- 4 Tests
- 5 Results
- 6 Analysis of Results
- 7 Summary
- References
- On Unsupervised and Supervised Discretisation in Mining Stylometric Features
- 1 Introduction
- 2 Characteristics of Stylometric Features
- 3 Unsupervised and Supervised Discretisation
- 4 Conditions of Performed Experiments
- 4.1 Input Stylometric Data Sets
- 4.2 Classification Systems Used
- 4.3 Employed Discretisation Approaches
- 5 Discussion of Obtained Results
- 6 Conclusions
- References
- Bio-Data and Bio-Signal Analysis
- LCR-BLAST-A New Modification of BLAST to Search for Similar Low Complexity Regions in Protein Sequences
- 1 Introduction
- 2 Methods
- 2.1 Default Parameters for Short Sequences
- 2.2 Composition Based Statistics
- 2.3 Identity Scoring Matrix
- 2.4 Mean Score
- 2.5 Workflow
- 3 Data Analysis and Results
- 3.1 Analyses of Differences Among Alignments
- 4 Conclusion
- References
- Risk Susceptibility of Brain Tumor Classification to Adversarial Attacks
- 1 Introduction
- 2 Methodology
- 3 The Data Set
- 4 Results and Discussion
- 5 Conclusion
- References
- Prediction of Drug Potency and Latent Relation Analysis in Precision Cancer Treatment
- 1 Introduction
- 2 Methodology
- 3 The Data Set
- 4 Results and Discussion
- 5 Analysis of Latent Relations Between Gene, Variant, Drug and Disease
- 6 Conclusion
- References
- Predictions of Age and Mood Based on Changes in Saccades Parameters
- 1 Introduction
- 2 Methods of the Experiment
- 3 Computational Basis
- 4 Results
- 5 Discussion and Conclusions
- References
- Algorithms and Optimization
- Using Copula and Quantiles Evolution in Prediction of Multidimensional Distributions for Better Query Selectivity Estimation
- 1 Introduction
- 2 Theoretical Background
- 2.1 Copula in Selectivity Estimation for m-d Range Query
- 2.2 Quantile-Based Histogram
- 2.3 Applied Prediction Methods
- 3 The Proposed Method of Predicting Representation of m-d Distribution and Selectivity Estimation
- 4 Presenting the Method in Experimental Results
- 5 Conclusions
- References
- Audio-Visual TV Broadcast Signal Segmentation
- 1 Introduction
- 2 Audio-Visual Signal Segmentation
- 2.1 Audio Signal Segmentation
- 2.2 (Audio)Visual Signal Segmentation
- 3 Conclusion
- References
- Optimizing Training Data and Hyperparameters of Support Vector Machines Using a Memetic Algorithm
- 1 Introduction
- 2 Literature Review
- 3 Proposed Method
- 3.1 Chromosome Design
- 3.2 Fitness Calculation
- 4 Experiments and Discussion
- 4.1 Comparison to Random Search
- 4.2 Statistical Difference Test
- 4.3 Comparison to Other Classifiers
- 5 Conclusions
- References
- Induction of Centre-Based Biclusters in Terms of Boolean Reasoning
- 1 Introduction
- 2 Boolean Reasoning in Biclustering
- 3 Centre-Based Biclustering
- 3.1 Boolean Reasoning Formalization
- 3.2 Proofs
- 4 Case Study
- 5 Conclusions and Further Works
- References
- Issues on Performance of Reactive Programming in the Java Ecosystem with Persistent Data Sources
- 1 Introduction
- 2 Background
- 3 Reactive Programming in Spring WebFlux
- 4 Survey
- 4.1 Research Environment and Methods of Measurement
- 4.2 Measurement Methodology
- 4.3 Results
- 5 Summary
- References
- Author Index
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