19 Result(s)
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Chapter and Conference Paper
An Untold Tale of Scientific Collaboration: SCCH and AC \(^2\) T
In the last two decades, the application of artificial intelligence (AI) in different fields has increased significantly. As an interdisciplinary field, AI methods are improving toward efficiency and applicabi...
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Chapter and Conference Paper
KI-Net: AI-Based Optimization in Industrial Manufacturing—A Project Overview
Artificial intelligence (AI) is a crucial technology of industrial digitalization. Especially in the production industry, a great potential is present in optimizing existing processes, e.g., concerning resourc...
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Chapter and Conference Paper
Towards Practical Secure Privacy-Preserving Machine (Deep) Learning with Distributed Data
A methodology for practical secure privacy-preserving distributed machine (deep) learning is proposed via addressing the core issues of fully homomorphic encryption, differential privacy, and scalable fast mac...
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Chapter and Conference Paper
Membership-Map**s for Data Representation Learning: A Bregman Divergence Based Conditionally Deep Autoencoder
This paper suggests to use membership-map** as the building block of deep models. An alternative idea of deep autoencoder, referred to as Bregman Divergence Based Conditionally Deep Autoencoder (that consists o...
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Chapter and Conference Paper
Deep Learning Rule for Efficient Changepoint Detection in the Presence of Non-Linear Trends
This study presents our ongoing research on designing new methods for changepoint detection in industrial environments using a CUSUM method variant. The changepoint detection refers to identifying the location...
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Chapter and Conference Paper
Membership-Map**s for Data Representation Learning: Measure Theoretic Conceptualization
A fuzzy theoretic analytical approach was recently introduced that leads to efficient and robust models while addressing automatically the typical issues associated to parametric deep models. However, a formal...
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Chapter and Conference Paper
Variational Optimization of Informational Privacy
The datasets containing sensitive information can’t be publicly shared as a privacy-risk posed by several types of attacks exists. The data perturbation approach uses a random noise adding mechanism to preserv...
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Chapter and Conference Paper
General Model for Tracking Manufacturing Products Using Graph Databases
One of the major problems in the manufacturing industry consists of the fact that, when manufacturing a product, many parts from different lots are supplied and mixed to a certain degree during an indeterminat...
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Chapter and Conference Paper
Enhancing Industrial Maintenance Through Intelligent Data Analysis
For years, the amount of data generated in many industrial production plants has been said to have great potential for improving maintenance processes. In order to leverage this potential in practice, however,...
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Chapter and Conference Paper
Multiple Choice Question Answering in the Legal Domain Using Reinforced Co-occurrence
Nowadays, the volume of legal information available is continuously growing. As a res...
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Chapter and Conference Paper
Deriving an Optimal Noise Adding Mechanism for Privacy-Preserving Machine Learning
Differential privacy is a standard mathematical framework to quanti...
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Chapter and Conference Paper
Maintaining and Analyzing Production Process Definitions Using a Tree-Based Similarity Measure
In this work a Case-Based reasoning system for managing production processes, declarative production process definitions in particular, with main focus on analysis and maintenance is introduced whereby each pr...
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Chapter and Conference Paper
Adaptive Flood Forecasting for Small Catchment Areas
In this paper a prototypical flood forecasting system for small catchment areas is presented. Due to the fact that flood forecasting models for small rivers normally not exist we developed an approach by combi...
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Chapter and Conference Paper
Combining Relational and NoSQL Database Systems for Processing Sensor Data in Disaster Management
In disaster and emergency management the integration of different kinds of sensor networks gains in importance and consequently more and more data becomes available. The upcoming NoSQL database systems are fle...
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Chapter and Conference Paper
BIAccelerator – A Template-Based Approach for Rapid ETL Development
Business Intelligence projects include a big variety of challenges for all involved parties. Due to individual and changeable customer requirements or lacking standardization, there is much legwork which BI de...
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Chapter and Conference Paper
Using GPS Trajectories to Create a Dynamic Network of Significant Locations as an Abstraction of Road Maps
This contribution discusses an approach on finding significant locations from a set of GPS tracks, called Hotspots in this contribution. Based on that, a model where traffic infrastructure is represented by a ...
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Chapter and Conference Paper
On Transforming a Knowledge Base from Topic Maps to OWL
In this contribution we show, how we could overcome the shortcomings of the Topic-Map representation by applying our developed transformation concept for the particular system VCEDECIS. At a passive decision s...
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Chapter and Conference Paper
CBRSHM – A Case-Based Decision Support System for Semi-Automated Assessment of Structures in Terms of Structural Health Monitoring
This contribution describes a case-based decision support system which is intended for being used in the field of Structural Health Monitoring to support the assessment of structures (by using the example of l...
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Chapter and Conference Paper
On Similarity in Case-Based Reasoning for Structural Health Monitoring
This contribution deals with the importance of similarity in Case-based Reasoning and the application for problems in the field of Structural Health Monitoring. Case-based Reasoning and different methodologies...
