A5004215103- Advanced Vision and Imaging
- Semiconductor materials and devices
- Cold Atom Physics and Bose-Einstein Condensates
- Domain Adaptation and Few-Shot Learning
- Nonlocal and gradient elasticity in micro/nano structures
- 3D Shape Modeling and Analysis
- Ferroelectric and Piezoelectric Materials
- Composite Structure Analysis and Optimization
- Gear and Bearing Dynamics Analysis
- Metal and Thin Film Mechanics
- Numerical methods in engineering
- Optical measurement and interference techniques
- Multimodal Machine Learning Applications
- COVID-19 diagnosis using AI
- Advancements in Semiconductor Devices and Circuit Design
- Computer Graphics and Visualization Techniques
- Atomic and Subatomic Physics Research
- Metallurgy and Material Forming
- Syntax, Semantics, Linguistic Variation
- Internet of Things and Social Network Interactions
- Topic Modeling
- Information Retrieval and Search Behavior
- Combustion and flame dynamics
- Physics of Superconductivity and Magnetism
- Natural Language Processing Techniques
University of Maryland, College Park
2021-2024
Korea Advanced Institute of Science and Technology
2014-2024
Boston University
2023-2024
Jeonbuk National University
2020-2023
Soongsil University
2023
Sixin (China)
2023
Korea Institute of Machinery and Materials
2023
Seoul National University
2018-2021
Naver (South Korea)
2020-2021
Korea Institute of Science and Technology
2018-2020
Can a gas of spin-up and spin-down fermions become ferromagnetic because repulsive interactions? We addressed this question, for which there is not yet definitive theoretical answer, in an experiment with ultracold two-component Fermi gas. The observation nonmonotonic behavior lifetime, kinetic energy, size increasing interactions provides strong evidence phase transition to state. Our observations imply that itinerant ferromagnetism delocalized possible without lattice band structure, our...
Deep learning-based semantic segmentation methods have an intrinsic limitation that training a model requires large amount of data with pixel-level annotations. To address this challenging issue, many researchers give attention to unsupervised domain adaptation for segmentation. Unsupervised seeks adapt the trained on source target domain. In paper, we introduce self-ensembling technique, one successful in classification. However, applying is very difficult because heavily-tuned manual...
Deep learning-based object detectors have shown remarkable improvements. However, supervised methods perform poorly when the train data and test different distributions. To address issue, domain adaptation transfers knowledge from label-sufficient (source domain) to label-scarce (target domain). Self-training is one of powerful ways achieve since it helps class-wise adaptation. Unfortunately, a naive approach that utilizes pseudo-labels as ground-truth degenerates performance due incorrect...
As the volume of publications rapidly increases, searching for relevant information from literature becomes more challenging. To complement standard search engines such as PubMed, it is desirable to have an advanced tool that directly returns biomedical entities targets, drugs, and mutations rather than a long list articles. Some existing tools submit query PubMed process retrieved abstracts extract at time, resulting in slow response time limited coverage only fraction corpus. Other...
RNA plays an indispensable role in mammalian cell functions. Cas13, a class of RNA-guided ribonuclease, is flexible tool for modifying and regulating coding non-coding RNAs, with enormous potential creating new However, the lack control over Cas13 activity has limited its engineering capability. Here, we present CRISTAL (Control Inducible SpliT CAs13 Orthologs Exogenous Ligands) platform. powered by collection (10 total) orthogonal split inducible effectors that can be turned ON or OFF via...
We describe the formation of fermionic NaLi Feshbach molecules from an ultracold mixture bosonic ${}^{23}$Na and ${}^{6}$Li. Precise magnetic field sweeps across a narrow resonance at 745 G result in molecule conversion fraction $5%$ for our experimental densities temperatures, corresponding to number $5\ifmmode\times\else\texttimes\fi{}{10}^{4}$. The observed molecular decay lifetime is $1.3$ ms after removing free Li Na atoms trap. Due its extremely low reactivity, ground state will have...
To learn target discriminative representations, using pseudo-labels is a simple yet effective approach for unsupervised domain adaptation. However, the existence of false pseudo-labels, which may have detrimental influence on learning remains major challenge. overcome this issue, we propose pseudo-labeling curriculum based density-based clustering algorithm. Since samples with high density values are more likely to correct leverage these subsets train our network at early stage, and utilize...
Higher-order deformation theories, such as the couple stress and strain gradient theory, have been widely used to predict mechanical behavior of micro/nano-scale structures. In this paper, additional length scale parameter introduced in theory is measured by performing bulk-scale tensile micro-scale cantilever bending experiments. Bulk-scale characterization provided microstructural information polycrystalline copper plate along with macroscopic properties. Micro-scale cantilevers...
Social network sites (SNSs) have attracted millions of users who interact with each other and companies.However, few studies examined the impact knowledge sharing through electronic word mouth (eWOM) in context SNSs.This paper investigates relationship among use SNSs, users' social capital, sharing, eWOM.The results show that intensity SNSs is positively related to trust identification which a positive effect on eWOM quality.In addition, quality has sharing.Female feel more strongly about...
We introduce a large-scale 3D shape understanding benchmark using data and annotation from ShapeNet object database. The consists of two tasks: part-level segmentation shapes reconstruction single view images. Ten teams have participated in the challenge best performing outperformed state-of-the-art approaches on both tasks. A few novel deep learning architectures been proposed various representations report techniques used by each team corresponding performances. In addition, we summarize...
Fermi gases with repulsive interactions are characterized by measuring their compressibility as a function of interaction strength. The is obtained from in-trap density distributions monitored phase-contrast imaging. For parameters ${k}_{F}a>0.25$, fast decay the gas prevents observation equilibrium profiles. smaller parameters, results adequately described first-order perturbation theory. We have developed imaging method that compensates for dispersive distortions images.
Self-supervised monocular depth estimation has emerged as a promising method because it does not require groundtruth maps during training. As an alternative for the map, photometric loss enables to provide self-supervision on prediction by matching input image frames. However, causes various problems, resulting in less accurate values compared with supervised approaches. In this paper, we propose SAFENet that is designed leverage semantic information overcome limitations of loss. Our key...
Personal names tend to have many variations differing from country country. Though there exists a large amount of personal on the Web, nationality prediction solely based has not been fully studied due its difficulties in extracting subtle character level features. We propose recurrent neural network model which predicts nationalities each name using automatic feature extraction. Evaluation Olympic record data shows that our achieves greater accuracy than previous approaches tasks. also...
Summary In this paper, a 3‐node C 0 triangular element for the modified couple stress theory is proposed. Unlike classical continuum theory, second‐order derivative of displacement included in weak form equilibrium equations. Thus, first‐order displacement, such as rotation, should be approximated by continuous function. proposed element, defined at node using node‐based smoothed finite method. The fields, between elements and linear an are with shape functions element. Both field expressed...