https://zienjournals.com/index.php/tjet <p><strong>Texas Journal of Engineering and Technology</strong> provides the opportunity to the authors to publish their original research articles in field of Engineering and Technological Advancements. </p> <p><strong>Frequency of Publication:</strong> Monthly</p> <p><strong>Acceptance Notification:</strong> 45 Days</p> <p><strong>ISSN (Online):</strong> <a href="https://portal.issn.org/resource/ISSN/2770-4491">2770-4491</a></p> <p><strong>doi Prefix:</strong> 10.62480</p> <p> </p> Zien Journals en-US Texas Journal of Engineering and Technology 2770-4491 <h3><strong>User Rights</strong></h3> <p>Under the <strong>Creative Commons Attribution-<a href="https://creativecommons.org/licenses/by-nc/4.0/">NonCommercial 4.0 International (CC-BY-NC)</a></strong><a href="https://creativecommons.org/licenses/by-nc/4.0/">,</a> the author (s) and users are free to share (copy, distribute and transmit the contribution).</p> <p><strong>Rights of Authors</strong></p> <p>Authors retain the following rights:<br />1. Copyright and other proprietary rights relating to the article, such as patent rights,<br />2. the right to use the substance of the article in future works, including lectures and books,<br />3. the right to reproduce the article for own purposes, provided the copies are not offered for sale,<br />4. the right to self-archive the article.</p> https://zienjournals.com/index.php/tjet/article/view/5873 <p>This article focuses on the development of deep learning models and algorithms specifically designed for Uzbek language processing within the IT field. A comprehensive approach involving data collection, preprocessing, model selection, and evaluation was employed. Experiments with RNN, LSTM, and transformer-based models like BERT and GPT were conducted, with transformer models yielding superior results. Key challenges included limited datasets and the complex morphological structure of Uzbek. The findings suggest that fine-tuned transformer models, especially with language-specific preprocessing, can significantly improve performance in language understanding tasks for low-resource languages</p> Suyunova Zamira Erkinova Dilnoza Copyright (c) 2025 Suyunova Zamira, Erkinova Dilnoza https://creativecommons.org/licenses/by-nc/4.0 2025-01-10 2025-01-10 40 1 4 10.62480/tjet.2025.vol40.pp1-4 https://zienjournals.com/index.php/tjet/article/view/5889 <p>Intranuclear leakage of liquid protons was experimentally observed during the deceleration phase of the spiral-waved jet emitted from Kholmurad Khasanov's dynamic emitter. The gas stream from the nozzle forms supersonic spiral-type jets with spatially modulated extreme density, enhanced by shockwave structures. In these jets, phenomena such as over-compression and over-acceleration occur, creating a high-density energy field as the internal energy of the gas or liquid decreases. The resulting instability within the jet leads to explosions accompanied by intense ultraviolet light flares. These conditions are hypothesized to promote the synthesis of new elements and increase radionuclide activity, as verified by gamma-spectrometric analysis. In the experiments, elements such as carbon, calcium, silicon, and aluminum—previously absent in the original samples—were detected on solid surfaces after exposure to the jet</p> Kholmurad Khasanov Elena Urusova Rashid Eshburiev Copyright (c) 2025 https://creativecommons.org/licenses/by-nc/4.0 2025-01-21 2025-01-21 40 5 13 10.62480/tjet.2025.vol40.pp5-13