Modern bio-inspired robotic fish design increasingly focuses on integrating biological inspiration with engineering-oriented structural solutions to enhance locomotion performance and meet practical application demands. Among these, the crank-linkage...
This paper evaluates the use of impedance spectroscopy combined with artificial intelligence. Both technologies have been widely used in food classification and it is proposed a way to improve classifications using recurrent neural networks that trea...
In this study, we identified and screened nine novel umami peptides derived from yellowfin tuna (Thunnus albacares) utilizing peptidomics combined with various machine learning based umami screening methodologies, including UMPred-FRL, TPDM, Umami-MR...
Sports image classification is a complex undertaking that necessitates the utilization of precise and robust techniques to differentiate between various sports activities. This study introduces a novel approach that combines the deep neural network (...
Artificial fish-like robots developed to date often focus on the external morphology of fish and have rarely addressed the contribution of the structure and morphology of biological muscle. However, biological studies have proven that fish utilize th...
Tunas are flexible, high-performance open ocean swimmers that operate at high frequencies to achieve high swimming speeds. Most fish-like robotic systems operate at low frequencies (≤3 Hz) resulting in low swim speeds (≤1.5 body lengths per second), ...
Closed-cycle aquaculture using hatchery produced seed stocks is vital to the sustainability of endangered species such as Pacific bluefin tuna (Thunnus orientalis) because this aquaculture system does not depend on aquaculture seeds collected from th...
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