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Editorial

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Dear Readers, First of all, I am very happy to announce that the funding round of the KOALA initiative initiated by the TIB was successful and that our journal will be part of the computer science and mathematics cluster for the next three years. The entire J.UCS team is very grateful for the great efforts of the KOALA team and for the support of the J.UCS community. This enables us to continue our work to maintain J.UCS as a diamond open access journal and to further improve the service and scientific quality. Also, I would like to thank all the authors for their sound research and the editorial board for their extremely valuable review effort and suggestions for improvement. These contributions, together with the generous support of the consortium members, contribute to the quality of our journal. It gives me great pleasure to announce the eleventh regular issue of 2024. In this issue, 6 papers by 21 authors from 5 countries - Brazil, India, Algeria, Italy, Sweden - cover various topical aspects of computer science. In an ongoing effort to further strengthen our journal, I am continuously looking for new editorial board members: If you are a tenured associate professor or higher with a good publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends. Geová Junio da Silva Tavares and Nelson Souto Rosa from Brazil present the results of a survey on humans in the loop for self-adaptive systems. Aluizio Haendchen Filho, Adson Marques da Silva Esteves, Hércules Antonio do Prado, Edilson Ferneda and André Luis Alice Raabe from Brazil discuss their study on adaptive content recommendations to improve logic and programming teaching and learning by using learning paths to group students and provide personalized recommendations based on peers' progress. Rupesh Kumar Verma, A. J. Khan, Sunil Kashyap and Manoj Kumar Chande from India conduct their study on the certificateless aggregate signature scheme in terms of their computational performance and security, which can be widely used in areas such as IoT or healthcare systems. Besma Hezili and Hichem Talbi from Algeria address the collaborative auto-diversified optimization scheme (CADOS) for solving continuous and combinatorial optimization problems by exploring the synergy of various optimization algorithms and enhance their effectiveness and efficiency, particularly for higher-dimensional problems. Maroua Chemlal, Amina Zedadra, Ouarda Zedadra, Antonio Guerrieri and Med Nadjib Kouahla from Algeria outline their approach and findings on a multi-criteria food and restaurant recommendation system. And last but not least, Ashish Ranjan Mishra, Rakesh Kumar and Rajkumar Saini from India present their study on the improvement of the effectiveness of person authentication by using deep learning techniques on electroencephalogram (EEG) signals by applying a multiscale convolutional neural network (CNN) and a Bidirectional LSTM (BiLSTM) model to extract features and classify raw EEG data. Enjoy Reading! Kind regards, Christian Gütl, Managing Editor Graz University of Technology, Graz, Austria
Title: Editorial
Description:
Dear Readers, First of all, I am very happy to announce that the funding round of the KOALA initiative initiated by the TIB was successful and that our journal will be part of the computer science and mathematics cluster for the next three years.
The entire J.
UCS team is very grateful for the great efforts of the KOALA team and for the support of the J.
UCS community.
This enables us to continue our work to maintain J.
UCS as a diamond open access journal and to further improve the service and scientific quality.
Also, I would like to thank all the authors for their sound research and the editorial board for their extremely valuable review effort and suggestions for improvement.
These contributions, together with the generous support of the consortium members, contribute to the quality of our journal.
It gives me great pleasure to announce the eleventh regular issue of 2024.
In this issue, 6 papers by 21 authors from 5 countries - Brazil, India, Algeria, Italy, Sweden - cover various topical aspects of computer science.
In an ongoing effort to further strengthen our journal, I am continuously looking for new editorial board members: If you are a tenured associate professor or higher with a good publication record, you are welcome to apply to join our editorial board.
We are also interested in high-quality proposals for special issues on new topics and trends.
Geová Junio da Silva Tavares and Nelson Souto Rosa from Brazil present the results of a survey on humans in the loop for self-adaptive systems.
Aluizio Haendchen Filho, Adson Marques da Silva Esteves, Hércules Antonio do Prado, Edilson Ferneda and André Luis Alice Raabe from Brazil discuss their study on adaptive content recommendations to improve logic and programming teaching and learning by using learning paths to group students and provide personalized recommendations based on peers' progress.
Rupesh Kumar Verma, A.
J.
Khan, Sunil Kashyap and Manoj Kumar Chande from India conduct their study on the certificateless aggregate signature scheme in terms of their computational performance and security, which can be widely used in areas such as IoT or healthcare systems.
Besma Hezili and Hichem Talbi from Algeria address the collaborative auto-diversified optimization scheme (CADOS) for solving continuous and combinatorial optimization problems by exploring the synergy of various optimization algorithms and enhance their effectiveness and efficiency, particularly for higher-dimensional problems.
Maroua Chemlal, Amina Zedadra, Ouarda Zedadra, Antonio Guerrieri and Med Nadjib Kouahla from Algeria outline their approach and findings on a multi-criteria food and restaurant recommendation system.
And last but not least, Ashish Ranjan Mishra, Rakesh Kumar and Rajkumar Saini from India present their study on the improvement of the effectiveness of person authentication by using deep learning techniques on electroencephalogram (EEG) signals by applying a multiscale convolutional neural network (CNN) and a Bidirectional LSTM (BiLSTM) model to extract features and classify raw EEG data.
Enjoy Reading! Kind regards, Christian Gütl, Managing Editor Graz University of Technology, Graz, Austria.

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