Nordic Artificial Intelligence Research and Development: 4th Symposium of the Norwegian AI Society, NAIS 2022 Oslo, Norway, May 31 – June 1, 2022 Revised Selected Papers

Description

This book constitutes the refereed proceedings of the 4th Symposium of the Norwegian AI Society, NAIS 2022, held in Oslo, Norway, during May 31–June 1, 2022.  The 11 full papers included in this book were carefully reviewed and selected from 17 submissions. They were organized in topical sections as follows: robotics and intelligent systems; ai in cyber and digital sphere; ai in biological applications and medicine; and towards new ai methods. This is an open access book. Preface Organization Contents Robotics and Intelligent Systems Knowledge Infused Representations Through Combination of Expert Knowledge and Original Input 1 Introduction 2 Related Work 3 Methods 3.1 Model 3.2 Combination Paradigms 3.3 Combination Mechanisms 4 Experiments 4.1 Data 4.2 Hyperparameters 4.3 Results 4.4 Future Potential of Model 5 Conclusion References Cognitive Robotics - Towards the Development of Next-Generation Robotics and Intelligent Systems 1 Introduction 2 Cognition-Enabled Robotics 3 Cognitive Architectures 4 Position 5 Summary References Pattern Based Software Architecture for Predictive Maintenance 1 Introduction 2 Related Work 3 Matrix Profile Method for Predictive Maintenance 3.1 Matrix Profile in Our Case Study 4 General Architecture and Patterns 4.1 Domain Modeling, UML Class Diagrams and Patterns 4.2 Patterns for Predictive Maintenance 4.3 Observation and Indicator Patterns 4.4 Time Series Estimates Using Matrix Profile 4.5 Methods for Calculating Estimates 4.6 Rules and Alert Rules 5 Conclusions References AI in Cyber and Digital Sphere An Overview of Artificial Intelligence Used in Malware 1 Introduction 2 Literature Review on AI-Powered Malware 2.1 Literature Search 2.2 Findings 2.3 Surveys 2.4 AI-Enabled Attacks on Authentication Factors 2.5 Techniques for Hiding Malware Code from Detection 2.6 Evading Network Traffic Detection 2.7 Other AI Deployment 3 Discussion of Findings References Fake News Detection by Weakly Supervised Learning Based on Content Features 1 Introduction 2 Related Work 3 Dataset 4 Architecture, Experiments and Results 4.1 Data Pre-processing 4.2 Feature Engineering 4.3 Weak Labeling System 4.4 Document Representation 4.5 Weakly Supervised Learning 5 Conclusions and Future Work References Improving the Usability of Tabular Data Through Data Annotation, Repair and Augmentation 1 Introduction 2 Related Work 3 The SINATRA Approach 4 Evaluation and Demonstration 4.1 Datasets, Ground Truths and Measures 4.2 Evaluation Results and Demonstration 5 Conclusion and Future Work References AI in Biological Applications and Medicine Detecting Human Embryo Cleavage Stages Using YOLO V5 Object Detection Algorithm 1 Introduction 2 Methods and Materials 2.1 Data 2.2 Object Detection 2.3 Colored Circular Overlay Algorithm 3 Results 3.1 Comparison with Embryologists 3.2 Cell Counting Performance 3.3 Computational Efficiency 3.4 Anomaly Detection 4 Discussion 5 Conclusion References References Phenotyping of Cervical Cancer Risk Groups via Generalized Low-Rank Models Using Medical Questionnaires 1 Introduction 1.1 Cervical Cancer Screening Programme 1.2 Uncovering Phenotypes and Co-Factors is Ongoing Research 2 Materials and Methods 2.1 Questionnaire Description and Preprocessing 2.2 Generalized Low-Rank Models 3 Experiments 3.1 Implementation Details and Experimental Set-Up 3.2 Model Selection 3.3 General Cervical Cancer Risk Factors 3.4 Phenotypes for Higher Number of Components 4 Discussion 5 Future Work 6 Conclusion References Automatic Unsupervised Clustering of Videos of the Intracytoplasmic Sperm Injection (ICSI) Procedure 1 Introduction 2 Data and Method 3 Results 4 Discussion 5 Conclusion References Towards New AI Methods The Kernelized Taylor Diagram 1 Introduction 2 The Kernelized Taylor Diagram 3 Experiments 4 Conclusion References Simulating University Application Data for Fair Matchings 1 Introduction 2 University Admissions in Norway 2.1 Admission Process 2.2 Data 3 Simulator 3.1 Prepossessing and Training 3.2 Generating Student Features, Preferences and Outcomes 3.3 Simulating Admission Decisions (Work in Progress) 4 Fair Matchings 5 Conclusion References Author Index