Technical Science Integrated Research
https://altumnova.com/index.php/tsir
<p>Technical Science Integrated Research (ISSN 3051-3855) is a peer-reviewed academic journal dedicated to the publication of original research, theoretical studies, and practical developments in the broad field of technical sciences. The journal seeks to bridge diverse disciplines such as engineering, applied physics, computer science, materials science, and industrial technologies by fostering an integrated approach to solving contemporary scientific and technical challenges. Emphasizing interdisciplinary collaboration and innovative methodologies, the journal provides a platform for scholars, practitioners, and industry experts to present advancements that contribute to the development of effective, sustainable, and technologically-driven solutions. With a focus on both fundamental investigations and real-world applications, Technical Science Integrated Research aims to support scientific excellence and encourage the translation of research findings into impactful technologies and systems across various sectors.</p>en-USTechnical Science Integrated Research3051-3855Multi-Tier Cultivation Units in Protected Ground: A Systematic Review of Construction Types, Resource Performance and the Normative Coverage Gap
https://altumnova.com/index.php/tsir/article/view/94
Purpose. Multi-tier (vertical) cultivation units are consolidating into an independent class of protected-ground engineering, yet research attention and normative regulation remain concentrated on the industrial end of the size spectrum. This review aims to systematise the construction types of multi-tier cultivation units, to consolidate their technological and resource- use indicators on a common scale, and to quantify - rather than merely assert - the gap in the normative framework that applies to small-volume units. Methods. A critical-analytical review was carried out on four source groups: international peer-reviewed literature, the engineering school of the CIS countries, national legal and building-code documents of Uzbekistan, and EN, ISO and ANSI/ASABE standards. Protected-ground facilities were classified by nine independent attributes expressed as a classification vector; four construction classes were compared across nine indicators; covering materials were compared by light transmittance, heat transfer coefficient and service life; and eleven normative documents were assessed against eight criteria on a three-level scale, with a coverage index computed for each criterion. Sh.Kh.Juraboev
Copyright (c) 2026
https://creativecommons.org/licenses/by/4.0
2026-09-102026-09-1029318From Manual Curation to Automated Extraction: The Economic and Scholarly Case for Multilingual Metadata Systems in Academic Publishing
https://altumnova.com/index.php/tsir/article/view/95
Metadata is the connective tissue of scholarly communication, it determines whether a published article can be found, indexed, cited, and correctly attributed within the global research infrastructure. Yet the manual creation and verification of bibliographic metadata remains a slow, labour-intensive, and error-prone process, and this burden falls disproportionately on journals that publish outside the small set of languages and layout conventions for which existing extraction tools were designed. This paper examines the scholarly and economic case for automated, multilingual metadata extraction, using MetaExtract - a rule-based and named-entity-recognition hybrid system built for Uzbek (Latin and Cyrillic), Russian, and English academic journal articles - as a case study. Evaluated on a stratified 150-article gold-standard corpus, the system achieved an overall F1 score of approximately 0.965 across six core metadata fields, while processing a single document in an average of 2.62 seconds on modest, GPU-free hardware. We situate these results within the broader literature on metadata quality, discoverability, and the resource economics of extraction approaches, and argue that lightweight, format-aware hybrid architectures offer a more sustainable path to metadata automation for linguistically underserved journals than either purely manual workflows or resource-intensive large-model approaches.Rashid Turgunbaev
Copyright (c) 2026
https://creativecommons.org/licenses/by/4.0
2026-09-102026-09-10291926