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Preface; Organization; Contents; Invited Papers; Deep Learning with Dense Random Neural Networks; 1 Introduction; 2 The Mathematical Model; 2.1 Nuclei with Inhibitory Cells; 2.2 Activation Only Through Some-to-Soma Interactions; 2.3 Random Selection of Soma-to-Soma Interactions; 3 An Improved Training Procedure for the RNN-MLA; 3.1 The Detailed Training Procedure; 4 RNN-MLA for Multi-channel Classification Datasets; 4.1 Modifications to the MCRNN-MLA; 5 Numerical Result Comparisons; 5.1 Application 1: Recognizing 3D Objects; 5.2 Application 2: Distinguishing Chemical Gases; 6 Conclusions

3.1 Research Methods3.2 Research Tools; 4 Experiment; 4.1 Main Features of the Data Set; 4.2 Pattern Strength Measure in Reference to Human Rating and Pattern Numerical Features; 4.3 New Statistical Input for the Measure Evaluation; 5 Conclusions; References; Typing Braille Code in the Air with the Leap Motion Controller; 1 Introduction; 2 Background; 3 Method; 3.1 Assumptions; 3.2 Analysis; 4 Evaluation; 5 Conclusions; References; Touchless Virtual Keyboard Controlled by Eye Blinking and EEG Signals; 1 Introduction; 2 Related Works; 3 Research Environment; 3.1 EEG Device; 3.2 Software Tool

4 Method5 Experiments; 6 Discuss; 7 Conclusions; References; OneHandBraille: An Alternative Virtual Keyboard for Blind People; 1 Introduction; 2 Related Works; 3 Method; 4 Evaluation; 4.1 The Choice of Test Sentences; 4.2 Participants and Procedure; 4.3 Results; 5 Conclusions; References; Automation in Human-Machine Networks: How Increasing Machine Agency Affects Human Agency; 1 Introduction; 2 Background; 2.1 Agency in Human-Machine Networks; 2.2 Automation
Changing the Balance in Human and Machine Agency; 2.3 Automation and Impact on Innovation and Change; 3 Research Questions; 4 Method

5 Findings5.1 Case 1 Traffic Management; 5.2 Case 2 Public Sector Crisis Management; 5.3 Case 3 Crowd Evacuation; 6 Discussion; 6.1 The Interrelation Between Human and Machine Actors (RQ1); 6.2 Strengthening the Synergy Between Machine and Human Actors Through Automation (RQ2); 6.3 Strengthening Innovation and Change Through Automation (RQ3); 6.4 Limitations and Future Work; References; Eye Movement Traits in Differentiating Experts and Laymen; 1 Introduction; 2 Basics of Eye Movement Analysis; 3 Experiment; 4 Data Analysis; 5 Conclusions; References

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