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DBIS

Kategorie: ‘Theses’

Effects of Generative Replay-based methods on CF in DA on healthcare data

January 30th, 2023 | by

From Simulation to Real Settings: Investigating the Testability of Distributed Analytics Experiments

January 30th, 2023 | by

Establishing Trust in P2P Distributed Analytics Infrastructures

January 30th, 2023 | by

Predict privacy risk score

January 23rd, 2023 | by

Mastering the Game of Contract Bridge: Strategy Optimization via Deep Reinforcement Learning and Knowledge Representation and Reasoning

January 15th, 2023 | by

This thesis aims to explore Deep Reinforcement Learning based methods for strategy optimization in the Contract Bridge game, such as Multi-agent Reinforcement Learning, Value-based Learning, and Policy-based Learning, as well as Knowledge Representation and Reasoning based methods such as Multi-agent Epistemic Situation Calculus

Adversarial Attacks against Face Detection Systems

December 25th, 2022 | by

Improved Bottom-up Deep Learning Approach for Neuronal Cell Instance Segmentation

December 25th, 2022 | by

Offloading of IoT Workloads in Peer-to-Peer Networks using WebAssembly

December 9th, 2022 | by

Edge computing offers a framework for offloading the computational effort required by IoT applications.
However, privacy issues and cost constraints for cloud infrastructures pose substantial difficulties to IoT service deployment. We wish to look at the possibilities of Peer-to-Peer networks and WebAssembly for IoT task offloading. As a result, a comparison of existing offloading tactics and information structures based on peer-to-peer and client-side solutions employing modern Web protocols such as WebRTC and WebAssembly is made.

Sensor Based Human Motion Comparison

November 16th, 2022 | by

The aim of this thesis is to build a MLOps-based system to compare the variations in the motions executed while performing various sports-related movements. In essence, we are interested in comparing movements across multiple sensor-suit based recording sessions.

European Parliaments On Twitter during the Ukraine War: Analyzing Parliamential Influentials and Communities over Time

November 16th, 2022 | by

Politicians are highly public individuals. A lot of data on them is available online. Many try to use social media such as Twitter to express their views, support other members of their party or interest groups, and interact with the public. Some also use it to branch out and connect to other countries’ politicians or respond to international events. With all of this, they form social graphs with them as nodes and their interactions as edges. A politician’s job, however, also often comes with balancing different interests, especially in times of uncertainty; this may lead to changing opinions based on the current state of events. However, as they try to influence the public on social media, other actors may use their posts to do the same or influence the politicians themselves.