July 10 · Article · Electronics · Artificial Intelligence
Neural machine translation (NMT) systems are widely used, but their performance remains strongly dependent on the availability of large-scale digital corpora, making translation for low-resource languages a persistent challenge. In parallel, large language models (LLMs) have recently emerged as a promising paradigm for multilingual text generation and translation; however, their behavior in low-resource settings remains largely underexplored. The challenge becomes even more acute for historical languages. Chagatai, a historical Turkic literary language of Central Asia with no native speakers, unstable orthography, and parallel data, represents an extreme case of such a condition. This study investigates whether transliteration significantly affects translation performance and how LLM-based and NMT-based systems compare under an extremely low-resource setting. To address these questions, we evaluated four source-text configurations (original Arabic script, expert manual transliteration, LLM-based transliteration, and rule-based Uroman transliteration) for translation into six target languages: Kazakh, English, Uzbek, Uyghur, Turkish, Russian, and Arabic. The results show that manual transliteration consistently yields the best translation performance, while noisy automatic romanization reduces these gains. For model comparison, GPT-4o was assessed alongside two fine-tuned NMT baselines, NLLB and TranslateGemma. The findings further show that LLM-based translation can be competitive with, and in some settings outperform, fine-tuned NMT systems, although this advantage comes with lower interpretability. Overall, these findings show that, for extremely low-resource historical languages written in non-Latin scripts, source-side representation is a decisive factor and may be as important as the choice of translation model itself.
Nurassyl BeisenbekOpen access
July 31 · Article · International Journal of Electronics and Telecommunications · Information Systems
The growing number of cyber attacks in the world emphasises the importance of protecting critical computer systems (CCS), including automated process control systems (APCS). Ensuring the cybersecurity of CCSs becomes an essential element of resilience and reliability of modern information technologies. This paper considers the possibility of applying cognitive and cybernetic modelling and investigates the concepts that affect the cybersecurity risks of APCS. The methods of cognitive and cybernetic modelling made it possible to identify the links between the considered concepts, which made it possible to better understand the dynamics of changes in the system of APCS risk management.
VLValerii LakhnoOpen access
July 31 · Article · Discover Sustainability · Strategy and Management
The paper examines the construct of digital transformation (DT) and its role in the sustainable competitive advantage (SCA) in project-based firms in Pakistan, namely in the construction, information technology, manufacturing, and service industries. The paper investigates the effects of DT on SCA, as a mediator through organisational agility (OA) and a moderator through knowledge sharing (KS). The study is based on the Dynamic Capability Theory (DCT), according to which the correspondence between the internal capabilities helps organisations to attain adaptability and long-term competitiveness. The information obtained comprised 625 practitioners in project-based organisations, and the data were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). Results show that DT alone has minimal influence on SCA, but when OA is used as a transformational process, SCA is enhanced. KS has a robust direct influence on SCA, but when knowledge flows become excessive or unstructured, they may negatively affect the OASCA relationship, suggesting the existence of boundary conditions. This paper builds on DCT and highlights the nonlinear, context-dependent nature of knowledge processes in new economies. Deliberative managerial implications highlight the need to adopt orchestrated knowledge-sharing behaviours, nimble-friendly processes, and digital investments to achieve sustainable competitive advantage. It stresses the need for organized knowledge management and digital strategies to enhance agility. For policy, it suggests that in developing nations, governments should focus on both digital infrastructure and programs that strengthen organizational capabilities, ensuring these digital efforts lead to lasting economic success.
OMOrken MamyrbayevOpen access
