Ahlam Mallak | Publikationen
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Comprehensive Machine and Deep Learning Fault Detection and Classification Approaches of Industry 4.0 Mechanical Machineries: With Application to A Hydraulic Test Rig
Dissertation, Universität Siegen, 2021
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Sensor and Component Fault Detection and Diagnosis for Hydraulic Machinery Integrating LSTM Autoencoder Detector and Diagnostic Classifiers
Sensors 2021, 21, 433
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Unsupervised Feature Selection Using Recursive k-Means Silhouette Elimination (RkSE): A Two-Scenario Case Study for Fault Classification of High-Dimensional Sensor Data
Aug. 2020, doi: 10.20944/preprints202008.0254.v1
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A Hybrid Approach: Dynamic Diagnostic Rules for Sensor Systems in Industry 4.0 Generated by Online Hyperparameter Tuned Random Forest
Sci, vol. 2, no. 3, Art. no. 3, Sep. 2020, doi: 10.3390/sci2030061
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SenGen: A Two-Phase Dynamic Simulation and Toolbox of An Indoor Mobile Wireless Sensor Network for Sensor Monitoring and Dataset Generation
6th Annual Conference on Computational Science and Computational Intelligence, 2019
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A Dynamic Sensor Fault Detection and Identification System in IoT using MATLAB and Simulink
MATLAB Expo 2019, Munich, Germany, July 2019
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ADISTES Ontology for Active Diagnosis of Sensors and Actuators in Distributed Embedded Systems
In: 2019 IEEE International Conference on Electro Information Technology (EIT), 2019
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A graph-based sensor fault detection and diagnosis for demand-controlled ventilation systems extracted from a semantic ontology
In 2018 IEEE 22nd International Conference on Intelligent Engineering Systems (INES) (pp. 000377-000382), Spain, June, 2018.
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Active Diagnosis Automotive Ontology for Distributed Embedded Systems
In: Proceedings of the 2017 IEEE European Technology and Engineering Management Summit(E-TEMS)
[Link] [Scholar][BibTex]
@inproceedings{mallak2017active, title={Active diagnosis automotive ontology for distributed embedded systems}, author={Mallak, Ahlam and Weber, Christian and Fathi, Madjid and Holland, Alexander}, booktitle={2017 IEEE European Technology and Engineering Management Summit (E-TEMS)}, pages={1--6}, year={2017}, organization={IEEE} }
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Fault injection framework for fault diagnosis based on machine learning in heating and demand-controlled ventilation systems
2017 IEEE 4th International Conference on Knowledge-Based Engineering and Innovation (KBEI), Tehran, 2017
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