Abstract Accurately predicting tool wear is crucial for intelligent machining process monitoring, control, and quality improvement. Recent studies on tool wear prediction predominantly apply deep learning-based data-driven approaches that u... Read More
Abstract Transparent solar cells (TSCs) hold substantial potential as continuous energy generators, enabling their use in situations where conventional devices may not be feasible. However, research aimed at modularizing TSCs for the purpos... Read More
Abstract A well-developed perovskite crystal at the beginning of a crystal lattice facilitates favourable growth orientation for efficient charge transport and the elimination of buried interfaces. However, rapid and uncontrollable crystall... Read More
Abstract The adoption of mobile robots in industrial automation is rapidly expanding, driven by not only economic advantages but also considerations for environmental conservation and worker safety. Dynamic wireless power transfer systems f... Read More
UNIST is excited to announce the launch of the ‘UNIST AI Image Generation Contest,’ an initiative dedicated to capturing the innovative achievements of the university through the lens of AI-generated imagery. This contest invite... Read More
Dr. Myeonggyun Han, a recent Ph.D. graduate from UNIST as of February 2024, has been appointed as an assistant professor in the Department of Computer Science and Engineering at Kyungpook National University (KNU). Dr. Han, who holds both h... Read More
Abstract Highly efficient and high-definition displays with deformable form factors are highly desirable for next-generation electronic devices. Despite the unique advantages of quantum dots (QDs), including high photoluminescence quantum y... Read More
Abstract Recent advances in the diffusion models have significantly improved text-to-image generation. However, generating videos from text is a more challenging task than generating images from text, due to the much larger dataset and high... Read More
Abstract 1 This study presents a novel, ultralow-power single-sensor-based electronic nose (e-nose) system for real-time gas identification, distinguishing itself from conventional sensor-array-based e-nose systems, whose power consumption... Read More
Abstract Targeted drug delivery systems based on metal–organic frameworks (MOFs) have progressed tremendously since inception and are now widely applicable in diverse scientific fields. However, translating MOF agents directly to targeted d... Read More
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