Daily Archives: September 9, 2026

Authors: Research Scholar Kashmiraben K. Vihol, Professor (Dr.) Darsha Jani

Abstract: This article investigates the transformational effects of artificial intelligence (AI) and gamification on language translation and interpretation. Through a comprehensive analysis of current research, the study demonstrates how AI improves translation accuracy and efficiency, while gamification increases motivation and engagement in learning and professional training. The integration of these technologies into apps and educational frameworks is investigated, revealing benefits such as individualized learning and enhanced outcomes, as well as drawbacks such as cultural errors and an overreliance on automation. The findings indicate that human-AI collaboration is critical for nuanced language services. Implications for educators, translators, and developers are examined, along with suggestions for further research. We review technological advances in machine translation, summarize evidence on gamification in language tasks and crowdsourcing, propose an integrative four-layer framework that aligns AI, human expertise, gamified participation, and governance, and describe an empirical design to assess effects on translation quality, productivity, and participant motivation. We examine the ethical, economic, and practical ramifications and provide specific design suggestions for academics and practitioners.

DOI: http://doi.org/

Published by: vikaspatanker

Authors: Mohammad Monzur Morshed, Professor Dr. Hirofumi Toyota

Abstract: The small-strain stiffness of sands is an important characteristic in geotechnical earthquake engineering because it governs the first response of soil deposits to dynamic loads. This measure also provides important information on the stress condition, liquefaction susceptibility, density and soil fabric. Conventional triaxial testing, relying on external displacement measurements, is often unable to discern the very modest strains associated with the initiation of the stress–strain response. The development of bender element testing and local strain measurement techniques has substantially improved the characterization of sand stiffness over very small to small strain ranges. Local strain transducers directly measure the stress–strain stiffness and its deterioration with increasing strain. Bender elements offer an indirect estimate of the maximum or very-small-strain shear modulus, Gmax or Gmin, by measuring shear-wave velocity. This review critically assesses the theoretical basis, experimental interpretation and limitations of the two alternative approaches, with special regard to their consequences for liquefaction behavior. The review has a significant impact on effective stress, void ratio, fabric, particle properties, stress anisotropy and saturation circumstances. A high small-strain stiffness does not necessarily imply a high liquefaction resistance, but provides useful insight into the initial condition of a sand and can be related to the cycle resistance, when the state variables are appropriately normalized. Recent work on silty sands has shown that normalized small-strain stiffness can be a useful link between laboratory shear-wave data and the assessment of liquefaction triggering. However, care must be taken to consider the uncertainties related with wave arrival-time interpretation, near-field effects, specimen boundary conditions, membrane compliance, bedding errors, and differences between dynamic and quasi-static strain amplitudes. A more reliable characterization is obtained by combining bender element measurements with local strain measurements and cyclic testing, rather than depending on one single parameter. The review continues with a discussion of research needs in the areas of state-dependent stiffness, fines effects, anisotropy, fabric evolution and the development of unified stiffness-liquefaction frameworks.

DOI: https://doi.org/10.5281/zenodo.22669336

Published by: vikaspatanker