An explainable semi-personalized federated learning model
Training a model using batch learning requires uniform data storage in a repository. This approach is intrusive, as users have to expose their privacy and exchange sensitive data by sending them to central entities to be preprocessed. Unlike the ...
Ontology-based Meta AutoML
Automated machine learning (AutoML) supports ML engineers and data scientist by automating single tasks like model selection and hyperparameter optimization, automatically generating entire ML pipelines. This article presents a survey of 20 state-...
A hybrid approach for improving the flexibility of production scheduling in flat steel industry
- Vincenzo Iannino,
- Valentina Colla,
- Alessandro Maddaloni,
- Jens Brandenburger,
- Ahmad Rajabi,
- Andreas Wolff,
- Joaquin Ordieres,
- Miguel Gutierrez,
- Erwin Sirovnik,
- Dirk Mueller,
- Christoph Schirm
Nowadays the steel market is becoming ever more competitive for European steelworks, especially as far as flat steel products are concerned. As such competition determines the price products, profit can be increased only by lowering production and ...
Vulnerability prediction for secure healthcare supply chain service delivery
Healthcare organisations are constantly facing sophisticated cyberattacks due to the sensitivity and criticality of patient health care information and wide connectivity of medical devices. Such attacks can pose potential disruptions to critical ...
Coordinating heterogeneous mobile sensing platforms for effectively monitoring a dispersed gas plume
- Georgios D. Karatzinis,
- Panagiotis Michailidis,
- Iakovos T. Michailidis,
- Athanasios Ch. Kapoutsis,
- Elias B. Kosmatopoulos,
- Yiannis S. Boutalis
In order to sufficiently protect active personnel and physical environment from hazardous leaks, recent industrial practices integrate innovative multi-modalities so as to maximize response efficiency. Since the early detection of such incidents ...
A hardware efficient intra-cortical neural decoding approach based on spike train temporal information
- Danial Katoozian,
- Hossein Hosseini-Nejad,
- Mohammad-Reza Abolghasemi Dehaqani,
- Afshin Shoeibi,
- Juan Manuel Gorriz
Motor intention decoding is one of the most challenging issues in brain machine interface (BMI). Despite several important studies on accurate algorithms, the decoding stage is still processed on a computer, which makes the solution impractical ...
