
Database and Expert Systems Applications - DEXA 2022 Workshops
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This volume constitutes the refereed proceedings of the workshops held at the 33rd International Conference on Database and Expert Systems Applications, DEXA 2022, held in Vienna, Austria, in August 2022: The 6th International Workshop on Cyber-Security and Functional Safety in Cyber-Physical Systems (IWCFS 2022); 4th International Workshop on Machine Learning and Knowledge Graphs (MLKgraphs 2022); 2nd International Workshop on Time Ordered Data (ProTime2022); 2nd International Workshop on AI System Engineering: Math, Modelling and Software (AISys2022); 1st International Workshop on Distributed Ledgers and Related Technologies (DLRT2022); 1st International Workshop on Applied Research, Technology Transfer and Knowledge Exchange in Software and Data Science (ARTE2022).
The 40 papers were thoroughly reviewed and selected from 62 submissions, and discuss a range of topics including: knowledge discovery, biological data, cyber security, cyber-physical system, machine learning, knowledge graphs, information retriever, data base, and artificial intelligence.
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Content
- Intro
- Preface
- Organization
- Contents
- AI System Engineering: Math, Modelling and Software
- Unboundedness of Linear Regions of Deep ReLU Neural Networks
- 1 Introduction
- 2 Preliminaries
- 3 Representation and Analysis via Code Space
- 4 Experiments
- 5 Outlook and Future Work
- References
- Applying Time-Inhomogeneous Markov Chains to Math Performance Rating
- 1 Introduction
- 1.1 The Story Behind - Origins of the Use Case
- 1.2 An Adaptive Mobile App for Math Training
- 2 Ranking Based on the Elo System
- 2.1 Automated Estimation of Skill and Difficulty as a Problem-Solving Match Between Learner and Exercise
- 2.2 Time-inhomogeneous Markov Chains
- 3 Data and Experiment
- 4 Analysis and Results
- 5 Conclusions - Practical Use of the Ranking System
- References
- A Comparative Analysis of Anomaly Detection Methods for Predictive Maintenance in SME
- 1 Introduction
- 1.1 Anomaly Detection Techniques:
- 2 Literature Review
- 3 Methodology
- 3.1 Data
- 3.2 Model Description
- 3.3 Test Description
- 4 Results
- 4.1 Performance Comparison
- 5 Conclusion
- References
- A Comparative Study Between Rule-Based and Transformer-Based Election Prediction Approaches: 2020 US Presidential Election as a Use Case
- 1 Introduction
- 2 Related Work
- 3 Methodology
- 3.1 Data Collection
- 3.2 Pre-processing and Filtering
- 3.3 Sentiment Analysis
- 3.4 Vote-Share
- 4 Results and Discussion
- 4.1 Sentiment Analysis
- 4.2 Vote-Share
- 5 Conclusion
- References
- Detection of the 3D Ground Plane from 2D Images for Distance Measurement to the Ground
- 1 Introduction
- 2 Related Work
- 2.1 Depth Estimation
- 2.2 Plane Detection
- 3 Extraction of 3D Ground Plane Equation from RGB Images
- 3.1 Depth Estimation
- 3.2 3D Ground Plane Detection
- 4 Experiments and Results
- 4.1 3D Ground Plane Detection from RGB Images (Entire Workflow)
- 4.2 3D Ground Plane Detection from Groundtruth Depth Maps (Intermediate Workflow)
- 4.3 Influence of Bounding Point Selection on Ground Plane Detection
- 5 Conclusion and Outlook
- References
- Towards Practical Secure Privacy-Preserving Machine (Deep) Learning with Distributed Data
- 1 Introduction
- 1.1 The State-of-Art
- 1.2 Requirements for a Practical Secure Privacy-Preserving Machine Learning
- 2 Proposed Methodology
- 3 A Biomedical Application Example
- 4 Concluding Remarks
- References
- Applied Research, Technology Transfer and Knowledge Exchange in Software and Data Science
- Collaborative Aspects of Solving Rail-Track Multi-sensor Data Fusion
- 1 Introduction
- 2 Problem Statement
- 3 Collaborative Problem Solving Approach
- 3.1 Roles and Competences
- 3.2 Collaborative Development of a Calibration Object
- 3.3 Feedback-driven, Iterative Data Recording
- 3.4 Project Results
- 4 Knowledge Buildup and Transfer
- 5 Insights Gained Within the Project
- 5.1 Avoiding Cross-Source Registration by Using a Reference Dataset
- 5.2 Generating Datasets Serving for Point Cloud Segmentation Model Training
- 5.3 Collaborative Problem Solving Approach
- References
- From Data to Decisions - Developing Data Analytics Use-Cases in Process Industry
- 1 Introduction
- 2 Use Case Description - Project Vision
- 3 Workflow for a Digitalization Process
- 3.1 Project Outline - Definition of Project Vision, Project Goals and Use Cases
- 3.2 Data Analytics Infrastructure - Building Up, Data Management and Preparation
- 3.3 Data Analysis - Development of Data-Driven Approaches and Exploitation of Analysis Results
- 4 Discussion and Conclusion
- References
- Challenges in Mass Flow Estimation on Conveyor Belts in the Mining Industry: A Case Study
- 1 Introduction
- 2 Related Work
- 3 Case Study
- 3.1 Initial System Design
- 3.2 New Design
- 3.3 Data Aquisition
- 4 Mass Flow Estimation Model and Results
- 5 Discussion
- 5.1 Challenges
- 5.2 Academia-Industry Collaboration
- 6 Conclusions
- References
- A Table Extraction Solution for Financial Spreading
- 1 Introduction
- 2 Related Work
- 2.1 Table Extraction Technologies
- 2.2 Quality Evaluation Methods
- 3 Table Extraction for Financial Spreading
- 3.1 Extraction Pipeline for Financial Spreading
- 3.2 How to Identify Financial Tables
- 3.3 How to Extract a Table from a Document
- 4 Performance Evaluation
- 4.1 Evaluation Measure
- 4.2 Evaluation Method
- 4.3 Datasets
- 4.4 Results and Discussion
- 5 Conclusions and Perspectives
- References
- Synthetic Data in Automatic Number Plate Recognition
- 1 Introduction
- 2 Methodology
- 2.1 Automatic Number Plate Recognition
- 2.2 Use Cases
- 3 Outlook
- 4 Collaboration and Knowledge Transfer
- References
- An Untold Tale of Scientific Collaboration: SCCH and AC2T
- 1 Introduction
- 2 Involved Partners
- 2.1 SCCH
- 2.2 AC2T
- 2.3 History of the Collaboration
- 3 Discussion on the Projects
- 3.1 Proj N.1: Online Change Point Detection in RIC/Wear Progress
- 3.2 Proj N.2: Feature Detection via Transfer Learning
- 4 Quality of the Collaboration
- 5 Conclusion
- References
- On the Creation and Maintenance of a Documentation Generator in an Applied Research Context
- 1 Introduction
- 2 Context
- 2.1 Research Context
- 2.2 Industry Context
- 2.3 Documentation Generator - ReDoc
- 3 Project Phases
- 3.1 Prototyping
- 3.2 Development
- 3.3 Maintenance
- 4 Observations and Insights
- 4.1 Prototyping
- 4.2 Development
- 4.3 Maintenance
- 5 Conclusion
- References
- Towards the Digitalization of Additive Manufacturing
- 1 Introduction
- 2 Problem Definition
- 3 Methodology
- 3.1 Digitalization of the AM Data Chain
- 3.2 Digitalization of the AM Process Data
- 4 Dataset
- 5 Conclusion
- References
- Twenty Years of Successful Translational Research: A Case Study of Three COMET Centers
- 1 Motivation
- 2 The COMET Program
- 3 The Three Centers
- 4 Factors for Successful Translational Research Within the COMET Framework
- 4.1 Initiating Successful Industry Collaborations
- 4.2 Maintaining Long Term Relationships with Industry Partners
- 4.3 Teaming Up with Academia
- 4.4 Conducting Knowledge and Technology Transfer
- 5 Conclusion
- References
- Data Integration, Management, and Quality: From Basic Research to Industrial Application
- 1 Introduction
- 2 Industrial Use Cases
- 2.1 UC1 - Data Integration for Discrete Manufacturing
- 2.2 UC2 - Data Integration for Continuous Manufacturing
- 2.3 UC3 - Missing and Outlying Data in Steel Production
- 2.4 UC4 - Metadata Management for Manufacturing
- 3 Knowledge Transfer: Methods and Tools to Solve Data Challenges
- 3.1 Project Initialization: Ask the Right Questions
- 3.2 Methods and Tools to Address Data Integration
- 3.3 Methods and Tools to Address Data Quality
- 3.4 Methods and Tools to Address Metadata Management
- 4 Lessons Learned
- 4.1 Awareness for Different Types of Data Assets
- 4.2 Distinction Between Data Quality, Product Quality, and Outliers
- 4.3 Determination of the Correct Level of Metadata Management
- 4.4 Consideration of Process-Related Uncertainty
- 4.5 Use a Feature Store for Feature Engineering
- 5 Conclusion and Future Work
- References
- Building a YouTube Channel for Science Communication
- 1 Introduction
- 2 Background and Related Work
- 2.1 Knowledge Transfer and Traditional Ways of Sharing Knowledge in Our Research Project
- 2.2 Videos and YouTube as a Way of Doing Science Communication
- 3 First Steps Regarding Videos and Streaming
- 3.1 Objective
- 3.2 Idea
- 3.3 Implementation
- 4 Experiences Regarding Videos and Streaming
- 4.1 Lessons Learned on Hardware
- 4.2 Lessons Learned on Style and Content
- 4.3 Analysis of the Current Video Content
- 5 Summary and Conclusion
- References
- Introduction of Visual Regression Testing in Collaboration Between Industry and Academia
- 1 Introduction
- 2 Background
- 3 Approach
- 3.1 Step 1: Identify Potential Improvement Areas Based on Industry Needs
- 3.2 Step 2: Formulate a Research Agenda
- 3.3 Step 3: Formulate a Candidate Solution
- 3.4 Step 4: Conduct Lab Validation
- 3.5 Step 5: Perform Static Validation
- 3.6 Step 6: Perform Dynamic Validation
- 3.7 Step 7: Release the Solution
- 4 Results
- 4.1 Challenges
- 4.2 Success Factors
- 5 Conclusion
- References
- Vibration Analysis for Rotatory Elements Wear Detection in Paper Mill Machine
- 1 Introduction
- 2 Related Work
- 2.1 Vibration Analysis in Industry
- 3 Methodology
- 3.1 General Approach for Analyzing Anomalous Severity Values
- 4 Case Study
- 4.1 Data
- 4.2 Variables
- 4.3 Training
- 4.4 Results
- 5 Conclusions
- References
- Introducing Data Science Techniques into a Company Producing Electrical Appliances
- 1 Introduction
- 2 State of the Art
- 3 Case Study
- 3.1 Context
- 3.2 Collaboration Approach
- 3.3 Finding an Objective
- 3.4 Data Selection and Preprocessing
- 3.5 Model Training and Visualization
- 4 Results and Discussion
- 4.1 Outcome of the Collaboration
- 4.2 Collaboration Process
- 4.3 Lessons Learned
- 5 Conclusion
- References
- A Technology Transfer Portal to Promote Industry-Academia Collaboration in South-Tyrol
- 1 Introduction
- 2 Smart Data Factory
- 3 State of the Art
- 4 The Technology Transfer Portal of the SDF
- 4.1 Requirements
- 4.2 Implementation
- 5 Evaluation
- 6 Conclusion and Future Developments
- References
- Fast and Automatic Object Registration for Human-Robot Collaboration in Industrial Manufacturing
- 1 Introduction
- 2 Use Case
- 3 Model and Training Workflow
- 3.1 Model Architecture
- 3.2 Data and Training Procedure
- 4 Inference on FPGA
- 5 Automatic Generation of Images and Labels
- 6 Open World Challenge: The Objectosphere Loss
- 6.1 Methods
- 6.2 Results and Discussion
- 7 Summary
- References
- Distributed Ledgers and Related Technologies
- Sending Spies as Insurance Against Bitcoin Pool Mining Block Withholding Attacks
- 1 Introduction
- 1.1 Bitcoin, Pool Mining and Block Withholding Attacks
- 1.2 Literature Review and Previous Approaches
- 1.3 Contribution of This Paper
- 2 Results
- 2.1 Model Definition
- 2.2 Model 1: Confirming the Miner's Dilemma
- 2.3 Model 2: Punishment System
- 2.4 Model 3: Deposit System
- 2.5 Model 4: Distributing the Lost Deposit
- 3 Conclusion
- A Proof of Theorems
- A.1 Proof of Theorem 1
- A.2 Proof of Theorem 2
- References
- Risks in DeFi-Lending Protocols - An Exploratory Categorization and Analysis of Interest Rate Differences
- 1 Introduction
- 2 DeFi-Lending Protocols
- 2.1 Key Concepts and Components
- 2.2 DeFi-Lending Process
- 2.3 Risk Factors in DeFi-Lending
- 3 Methodology
- 3.1 Framework Development
- 3.2 Multiple Case Study
- 4 Results
- 4.1 DeFi-Risk Framework
- 4.2 Observations on DeFi Risk Categories
- 5 Conclusion
- References
- Battling the Bullwhip Effect with Cryptography
- 1 Introduction
- 2 Literature Review
- 3 Modelling Approach
- 3.1 Basic Model
- 3.2 Considered Policies
- 3.3 Model Implementation
- 4 Case Study and Results
- 5 Conclusion
- References
- Reporting of Cross-Border Transactions for Tax Purposes via DLT
- 1 Introduction
- 2 Aim and Concept
- 2.1 State of Existing EOI System
- 2.2 State of the Distributed Ledger Technology
- 3 Implementation of Blockchain in the EOI System (POC)
- 3.1 Processing Invoices
- 3.2 Implications of Blockchain in the EOI System
- 4 Conclusion
- References
- Securing File System Integrity and Version History Via Directory Merkle Trees and Blockchains
- 1 Introduction
- 2 Towards a Verifiable Versioned Archive
- 2.1 Directory Merkle Tree
- 2.2 Versioning
- 2.3 The Archiving Process
- 2.4 The Verification Process
- 2.5 Performance Evaluation
- 3 Discussion and Related Work
- 4 Conclusion and Future Work
- References
- Taxation of Blockchain Staking Rewards: Propositions Based on a Comparative Legal Analysis
- 1 Introduction
- 2 Proof-of-Stake Consensus Algorithms
- 3 Comparative Legal Analysis
- 3.1 Germany
- 3.2 Austria
- 3.3 Switzerland
- 4 Propositions
- 4.1 Proposition 1: Staking Should Only Qualify as a Business Activity Under Clearly Defined and Restrictive Circumstances
- 4.2 Proposition 2: Staking Rewards Should Not Be Taxed Upon Receipt If They Do Not Originate from a Main Business Activity
- 4.3 Proposition 3: Staking Rewards Should Be Taxed Upon Disposal
- 4.4 Proposition 4: Staking Should Not Cause Further Tax Consequences for Staked Coins
- 5 Conclusion
- References
- Comparison Framework for Blockchain Interoperability Implementations
- 1 Introduction
- 2 Background
- 3 Methods and Data Sources
- 4 Results
- 4.1 Identified BCI Implementations
- 4.2 Comparison Framework for BCI Implementations
- 4.3 Assessment of Identified BCI Implementations
- 5 Discussion
- 6 Limitations
- 7 Future Work
- 8 Conclusion
- References
- Cyber-security and Functional Safety in Cyber-physical Systems
- Towards Strategies for Secure Data Transfer of IoT Devices with Limited Resources
- 1 Introduction
- 2 Internet of Things
- 2.1 Resources Management
- 2.2 Security
- 3 Problem and Motivation
- 4 Approach
- 5 Case Study Design
- 6 Conclusion
- References
- Application of Validation Obligations to Security Concerns
- 1 Introduction
- 2 The Event-B Method
- 3 Validation Obligations
- 4 Application of VOs to Security Concerns
- 4.1 Illustrative Example
- 4.2 Formal Model
- 4.3 Ensuring Soundness and Conflict Freeness of Requirements
- 4.4 Creating Views
- 5 Related Work
- 6 Conclusion and Future Work
- References
- Mode Switching for Secure Edge Devices
- 1 Introduction
- 2 Mode Switching
- 3 Securing Edge Devices
- 4 Edge Device Modes
- 4.1 Implementation
- 4.2 Fail2ban Sample Scenario
- 5 Automation
- 6 Discussion
- 7 Limitations
- 8 Conclusion
- References
- Machine Learning and Knowledge Graphs
- A Lifecycle Framework for Semantic Web Machine Learning Systems
- 1 Introduction
- 2 Related Work
- 2.1 Machine Learning Lifecycles
- 2.2 Semantic Web Lifecycles
- 3 SWeMLS Lifecycle Framework
- 3.1 Scope of Framework
- 3.2 ML Lifecycle
- 3.3 SW Lifecycle
- 4 Case Study
- 5 Conclusion
- References
- Enhancing TransE to Predict Process Behavior in Temporal Knowledge Graphs
- 1 Introduction
- 2 Method: Enhance TransE to Predict Process Behavior
- 3 Experiments and Results
- 4 Conclusion and Outlook
- References
- An Explainable Multimodal Fusion Approach for Mass Casualty Incidents
- 1 Introduction
- 2 Background and Related Work
- 3 Methodology
- 4 Conclusion and Future Work
- References
- Time Ordered Data
- Log File Anomaly Detection Based on Process Mining Graphs
- 1 Introduction
- 1.1 Discussion on Existing Approaches and Related Work
- 2 Methods
- 2.1 Preparation of Event-Logs
- 2.2 Spectral Gap Calculation Using Event-Logs
- 3 Experiments and Discussion
- 3.1 Event-Logs Structure
- 3.2 Experimental Setup and Evaluation
- 3.3 Discussion
- 4 Discussion and Conclusion
- References
- A Scalable Microservice Infrastructure for Fleet Data Management
- 1 Introduction
- 1.1 Problem Statement
- 1.2 Related Work
- 2 Method
- 2.1 Dataset
- 2.2 Infrastructure
- 2.3 RouteAggregator
- 2.4 DataRetriever
- 2.5 Motorpool
- 3 Evaluation
- 4 Discussion
- 5 Outlook
- References
- Learning Entropy: On Shannon vs. Machine-Learning-Based Information in Time Series
- 1 Introduction
- 2 Probabilistic vs. Learning-Based Information
- 3 LE for Multichannel Data
- 4 Approaches for Comparison
- 5 Experimental Analysis
- 6 Conclusions
- Appendix
- References
- Using Property Graphs to Segment Time-Series Data
- 1 Introduction
- 2 Background Study
- 3 Our Approach
- 4 Use Case
- 5 Discussion and Outlook
- 6 Conclusion
- References
- A Synthetic Dataset for Anomaly Detection of Machine Behavior
- 1 Introduction
- 2 Existing Datasets
- 3 Method
- 3.1 Setup
- 3.2 Workflow Deviations
- 3.3 Dataset Generation Workflow
- 4 Conclusion
- References
- Author Index
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