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A word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Amihai, I., Kotriwala, A. M., Chioua, M., Lenders, F., Janka, D., Hollender, M., Schlake, J. C., Abukwaik, H., & Kloepper, B. (2021). Training an artificial intelligence module for industrial applications. [Formation d'un module d'intelligence artificielle pour applications industrielles]. (Patent Application no. CA3173428). External link
Amihai, I., Kotriwala, A., Pareschi, D., Chioua, M., & Gitzel, R. (2021, July). Using learned health indicators and deep sequence models to predict industrial machine health [Paper]. 7th International Conference on Time Series and Forecasting (ITISE 2021), Gran Canaria, Spain (9 pages). Published in Engineering Proceedings, 5(1). Available
Amihai, I., Subbiah, S., Kotriwala, A. M., & Chioua, M. (2020). Apparatus for predicting equipment damage. [Appareil pour prédire une détérioration d'équipement]. (Patent Application no. WO2020193314). External link
Amihai, I., Chioua, M., Gitzel, R., Kotriwala, A. M., Pareschi, D., Sosale, G., & Subbiah, S. (2018, July). Modeling Machine Health Using Gated Recurrent Units with Entity Embeddings and K-Means Clustering [Paper]. 16th IEEE International Conference on Industrial Informatics (INDIN 2018), Porto, Portugal. External link
Kloepper, B., Schmidt, B., Amihai, I., Chioua, M., Schlake, J. C., Kotriwala, A. M., Hollender, M., Janka, D., Lenders, F., & Abukwaik, H. (2021). Data processing for industrial machine learning. [Traitement de donnees pour apprentissage machine industriel]. (Patent Application no. CA3173398). External link
Schmidt, B., Amihai, I., Chioua, M., Kotriwala, A. M., Hollender, M., Janka, D., Lenders, F., Schlake, J. C., Kloepper, B., & Abukwaik, H. (2023). Method and apparatus for monitoring machine learning models. [Procédé et appareils de surveillance de modèle d'apprentissage automatique]. (Patent Application no. EP4127846). External link
Schmidt, B., Amihai, I., Kotriwala, A. M., Chioua, M., Janka, D., Lenders, F., Schlake, J. C., Hollender, M., Abukwaik, H., & Kloepper, B. (2023). Method of transfer learning for a specific production process of an industrial plant. [Procédé d'apprentissage de transfert pour un procédé de production spécifique d'une installation industrielle]. (Patent Application no. EP4128071). External link