Zobrazeno 1 - 10
of 49 531
pro vyhledávání: '"Myoung An"'
Autor:
Nam, Myoung Jin
Ensuring system correctness, such as memory safety, can eliminate security vulnerabilities that attackers could exploit in the first place. However, high and unpredictable performance degradation remains a primary challenge. Recognizing that it is ex
Externí odkaz:
http://arxiv.org/abs/2408.15219
Localized states in graphene have garnered significant attention in quantum information science due to their potential applications. Despite graphene's superior transport and electronic properties compared to other semiconductors, achieving nanoscale
Externí odkaz:
http://arxiv.org/abs/2407.20148
Domain generalization aim to train models to effectively perform on samples that are unseen and outside of the distribution. Adversarial data augmentation (ADA) is a widely used technique in domain generalization. It enhances the model robustness by
Externí odkaz:
http://arxiv.org/abs/2407.15174
Syntactic elements, such as word order and case markers, are fundamental in natural language processing. Recent studies show that syntactic information boosts language model performance and offers clues for people to understand their learning mechani
Externí odkaz:
http://arxiv.org/abs/2407.09184
Autor:
Song, Junho, Jang, Jong-Hwan, Lee, Byeong Tak, Hong, DongGyun, Kwon, Joon-myoung, Jo, Yong-Yeon
Using foundation models enhanced by self-supervised learning (SSL) methods presents an innovative approach to electrocardiogram (ECG) analysis, which is crucial for cardiac health monitoring and diagnosis. This study comprehensively evaluates foundat
Externí odkaz:
http://arxiv.org/abs/2407.07110
Publikováno v:
Scripta Materialia (2025) 116407
High-cycle fatigue is a critical performance metric of structural alloys for many applications. The high cost, time, and labor involved in experimental fatigue testing call for efficient and accurate computer models of fatigue life. We present FIP-GN
Externí odkaz:
http://arxiv.org/abs/2406.08682
In information technology devices, current-driven state switching is crucial in various disciplines including spintronics, where the contribution of heating to the switching mechanism plays an inevitable role. Recently, current-driven antiferromagnet
Externí odkaz:
http://arxiv.org/abs/2405.11678
Autor:
Hamerly, Ryan, Laksono, Evan, Jankowski, Marc, Ng, Edwin, Flemens, Noah, Suh, Myoung-Gyun, Mabuchi, Hideo
We investigate a new mode-locking regime in the singly-resonant OPO employing simultaneous amplitude- and frequency-modulation of the intracavity field. This OPO exhibits deterministic, "turn-key" formation of a stable, broadband, chirped frequency c
Externí odkaz:
http://arxiv.org/abs/2405.04594
Publikováno v:
Cur. Appl. Phys. 68, 44-50 (2024)
We present a machine learning method for swiftly identifying nanobubbles in graphene, crucial for understanding electronic transport in graphene-based devices. Nanobubbles cause local strain, impacting graphene's transport properties. Traditional tec
Externí odkaz:
http://arxiv.org/abs/2404.15658
We discovered that abnormal Mott physics can emerge even in weakly correlated 4f fermions through their interplay with topological singularity. Employing ab initio many-body perturbation theory combined with dynamical mean field theory, we show that
Externí odkaz:
http://arxiv.org/abs/2403.11382