Dear Readers, It gives me great pleasure to announce the third regular issue of 2024. In this issue, 6 papers by 20 authors from 6 countries - China, Ecuador, Spain, The Netherlands, Turkey, United Kingdom - cover various topical aspects of computer science. In a continuous effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong 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.  As always, 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. I also want to thank the readers for their interest on our articles indicated by an increasing access number and PDF downloads. These contributions, together with the generous support of the consortium members, sustain the quality of our journal.  In the third regular issue, I am very pleased to introduce the following 6 accepted articles: In a collaboration between researchers from The Netherlands and the United Kingdom, Jan Bergstra and John V. Tucker discuss their research on synthetic fracterm calculus, more specifically they introduce a new intermediate and informal axiomatisation of elementary arithmetic. Yasir Yakup Demircan and Serhat Ozekes from Turkey highlight their research on least significant bit steganography technique based on image segmentation. In a collaborative research effort between Spain and Ecuador, Alberto Jimenez-Macias, Pedro Muñoz-Merino, Margarita Ortiz-Rojas, Mario Muñoz-Organero, and Carlos Delgado-Kloos present their study on a systematic literature review on content modeling using machine learning algorithms in smart learning environments considering content indicators based on student interaction. Melih Kuncan, Kaplan Kaplan, Yılmaz Kaya, Mehmet Recep Minaz, and H. Metin Ertunç from Turkey focus on computer numerical control (CNC) systems, more specifically on classification of CNC vibration speeds by Heralick features. Lifang Ren, Jing Li, and Wenjian Wang from China address in their research support vector regression (SVR) and the location-aware method for mobile QoS prediction to overcome the difficulty caused by the sparsity of data and to predict the unknown QoS more accurately. Last but not least, Emre Sadıkoğlu, İrfan Kösesoy, and Murat Gök from Turkey look into the vulnerability of artificial systems to cyber-attacks by applying a gradient descent-based method to generate fake data. Enjoy Reading! Cordially,  Christian Gütl, Managing Editor-in-Chief Graz University of Technology, Graz, Austria
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