92,618 results on '"Lee, Jae"'
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2. National Pride and Political Participation: The Case of South Korea
- Author
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Kim, Gidong and Lee, Jae Mook
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- 2021
- Full Text
- View/download PDF
3. On Kim Tong-In’s “The World Created by Self and Yŏm Sang-Sŏp’s “Individuality and Art”
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Lee, Jae-Yon
- Published
- 2021
4. Network analysis reveals news press landscape and asymmetric user polarization
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Lee, Byunghwee, Ryu, Hyo-sun, Lee, Jae Kook, Jeong, Hawoong, and Kim, Beom Jun
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Computer Science - Social and Information Networks ,Physics - Physics and Society - Abstract
Unlike traditional media, online news platforms allow users to consume content that suits their tastes and to facilitate interactions with other people. However, as more personalized consumption of information and interaction with like-minded users increase, ideological bias can inadvertently increase and contribute to the formation of echo chambers, reinforcing the polarization of opinions. Although the structural characteristics of polarization among different ideological groups in online spaces have been extensively studied, research into how these groups emotionally interact with each other has not been as thoroughly explored. From this perspective, we investigate both structural and affective polarization between news media user groups on Naver News, South Korea's largest online news portal, during the period of 2022 Korean presidential election. By utilizing the dataset comprising 333,014 articles and over 36 million user comments, we uncover two distinct groups of users characterized by opposing political leanings and reveal significant bias and polarization among them. Additionally, we reveal the existence of echo chambers within co-commenting networks and investigate the asymmetric affective interaction patterns between the two polarized groups. Classification task of news media articles based on the distinct comment response patterns support the notion that different political groups may employ distinct communication strategies. Our approach based on network analysis on large-scale comment dataset offers novel insights into characteristics of user polarization in the online news platforms and the nuanced interaction nature between user groups., Comment: 21 pages, 6 figures
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- 2024
5. WASP 0346-21: An EL CVn-Type Eclipsing Binary with Multiperiodic Pulsations in a Triple System
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Lee, Jae Woo, Hong, Kyeongsoo, Jeong, Min-Ji, and Wolf, Marek
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Astrophysics - Solar and Stellar Astrophysics - Abstract
VLT/UVES spectroscopic and TESS photometric observations for WASP 0346-21 allow the direct determination of its physical properties, along with the detection of a circumbinary object and oscillating signals. The high-resolution spectra yielded the radial velocities of all three stars and the atmospheric parameters of $T_{\rm eff,A}$ = 7225$\pm42$ K, [M/H] = 0.30$\pm$0.03 dex, and $v_{\rm A}$$\sin i$ = 78$\pm$5 km s$^{-1}$ of the primary component. The combined analysis of these observations resulted in the fundamental parameters of the eclipsing components and the third light of $l_3$ = 0.043$\pm$0.004, which is consistent with the light contribution of the tertiary star observed in the echelle spectra. WASP 0346-21 A resides within the overlapping main-sequence domain of $\delta$ Sct and $\gamma$ Dor variables, while the secondary component of $M_{\rm B}$ = 0.185$\pm$0.013 M$_\odot$, $R_{\rm B}$ = 0.308$\pm$0.023 R$_\odot$, $T_{\rm eff,B}$ = 10,655$\pm$146 K, and $L_{\rm B}$ = 1.09$\pm$0.17 L$_\odot$ matches well with the low-mass white dwarf (WD) model for $Z$ = 0.01, corresponding to the thick-disk population classified by the Galactic kinematics. Multifrequency analyses were performed on the residual TESS data after removing the binarity effects. The low frequencies around 26.348 day$^{-1}$ and 17.683 day$^{-1}$ are $\delta$ Sct pulsations originating from WASP 0346-21 A, and the high frequencies of 97.996 day$^{-1}$ and 90.460 day$^{-1}$ are considered to be extremely low-mass WD oscillations. These results demonstrate that WASP 0346-21 is a hierarchical triple system, consisting of an EL CVn binary with multiperiodic pulsations in each component and a distant outer tertiary., Comment: 29 pages, including 9 figures and 5 tables, accepted for publication in ApJ
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- 2024
6. RGB2Point: 3D Point Cloud Generation from Single RGB Images
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Lee, Jae Joong and Benes, Bedrich
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Computer Science - Computer Vision and Pattern Recognition - Abstract
We introduce RGB2Point, an unposed single-view RGB image to a 3D point cloud generation based on Transformer. RGB2Point takes an input image of an object and generates a dense 3D point cloud. Contrary to prior works based on CNN layers and diffusion denoising approaches, we use pre-trained Transformer layers that are fast and generate high-quality point clouds with consistent quality over available categories. Our generated point clouds demonstrate high quality on a real-world dataset, as evidenced by improved Chamfer distance (51.15%) and Earth Mover's distance (45.96%) metrics compared to the current state-of-the-art. Additionally, our approach shows a better quality on a synthetic dataset, achieving better Chamfer distance (39.26%), Earth Mover's distance (26.95%), and F-score (47.16%). Moreover, our method produces 63.1% more consistent high-quality results across various object categories compared to prior works. Furthermore, RGB2Point is computationally efficient, requiring only 2.3GB of VRAM to reconstruct a 3D point cloud from a single RGB image, and our implementation generates the results 15,133x faster than a SOTA diffusion-based model.
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- 2024
7. Tree-D Fusion: Simulation-Ready Tree Dataset from Single Images with Diffusion Priors
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Lee, Jae Joong, Li, Bosheng, Beery, Sara, Huang, Jonathan, Fei, Songlin, Yeh, Raymond A., and Benes, Bedrich
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Computer Science - Computer Vision and Pattern Recognition - Abstract
We introduce Tree D-fusion, featuring the first collection of 600,000 environmentally aware, 3D simulation-ready tree models generated through Diffusion priors. Each reconstructed 3D tree model corresponds to an image from Google's Auto Arborist Dataset, comprising street view images and associated genus labels of trees across North America. Our method distills the scores of two tree-adapted diffusion models by utilizing text prompts to specify a tree genus, thus facilitating shape reconstruction. This process involves reconstructing a 3D tree envelope filled with point markers, which are subsequently utilized to estimate the tree's branching structure using the space colonization algorithm conditioned on a specified genus., Comment: Accepted to ECCV24
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- 2024
8. Forcing quasirandomness with 4-point permutations
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Kráľ, Daniel, Lee, Jae-baek, and Noel, Jonathan A.
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Mathematics - Combinatorics ,Computer Science - Discrete Mathematics - Abstract
A combinatorial object is said to be quasirandom if it exhibits certain properties that are typically seen in a truly random object of the same kind. It is known that a permutation is quasirandom if and only if the pattern density of each of the twenty-four 4-point permutations is close to 1/24, which is its expected value in a random permutation. In other words, the set of all twenty-four 4-point permutations is quasirandom-forcing. Moreover, it is known that there exist sets of eight 4-point permutations that are also quasirandom-forcing. Breaking the barrier of linear dependency of perturbation gradients, we show that every quasirandom-forcing set of 4-point permutations must have cardinality at least five.
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- 2024
9. Is active motion beneficial for target search with resetting in a thermal environment?
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Pal, Priyo Shankar, Park, Jong-Min, Pal, Arnab, Park, Hyunggyu, and Lee, Jae Sung
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Condensed Matter - Statistical Mechanics - Abstract
Stochastic resetting has recently emerged as an efficient target-searching strategy in various physical and biological systems. The efficiency of this strategy depends on the type of environmental noise, whether it is thermal or telegraphic (active). While the impact of each noise type on a search process has been investigated separately, their combined effects have not been explored. In this work, we explore the effects of stochastic resetting on an active system, namely a self-propelled run-and-tumble particle immersed in a thermal bath. In particular, we assume that the position of the particle is reset at a fixed rate with or without reversing the direction of self-propelled velocity. Using standard renewal techniques, we compute the mean search time of this active particle to a fixed target and investigate the interplay between active and thermal fluctuations. We find that the active search can outperform the Brownian search when the magnitude and flipping rate of self-propelled velocity are large and the strength of environmental noise is small. Notably, we find that the presence of thermal noise in the environment helps reduce the mean first passage time of the run-and-tumble particle compared to the absence of thermal noise. Finally, we observe that reversing the direction of self-propelled velocity while resetting can also reduce the overall search time., Comment: 10 pages, 4 figures
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- 2024
10. A randomized, open-label, phase 3 trial of pembrolizumab plus epacadostat versus sunitinib or pazopanib as first-line treatment for metastatic renal cell carcinoma (KEYNOTE-679/ECHO-302).
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Lara, Primo, Villanueva, Luis, Ibanez, Carolina, Erman, Mustafa, Lee, Jae, Heinrich, Daniel, Lipatov, Oleg, Gedye, Craig, Gokmen, Erhan, Acevedo, Alejandro, Semenov, Andrey, Park, Se, Gafanov, Rustem, Kose, Fatih, Jones, Mark, Du, Xiaoqi, Munteanu, Mihaela, Perini, Rodolfo, Choueiri, Toni, and Motzer, Robert
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Epacadostat ,IDO1 ,Indoleamine 2 ,3-deoxygenase 1 ,PD-1 ,Pembrolizumab ,Programmed death 1 ,Renal cell carcinoma ,Humans ,Carcinoma ,Renal Cell ,Sunitinib ,Sulfonamides ,Male ,Female ,Antibodies ,Monoclonal ,Humanized ,Middle Aged ,Pyrimidines ,Antineoplastic Combined Chemotherapy Protocols ,Kidney Neoplasms ,Aged ,Indazoles ,Adult ,Aged ,80 and over ,Oximes - Abstract
BACKGROUND: Immunotherapy-based combinations have emerged as standard therapies for patients with metastatic renal cell carcinoma (mRCC). Pembrolizumab, a PD-1 inhibitor, combined with epacadostat, an indoleamine 2,3-deoxygenase 1 selective inhibitor, demonstrated promising antitumor activity in a phase 1 study in advanced solid tumors, including mRCC. METHODS: KEYNOTE-679/ECHO-302 was a randomized, open-label, parallel-group, multicenter, phase 3 study (NCT03260894) that compared pembrolizumab plus epacadostat with sunitinib or pazopanib as first-line treatment for mRCC. Eligible patients had histologically confirmed locally advanced or metastatic clear cell RCC and had not received systemic therapy. Patients were randomly assigned 1:1 to pembrolizumab 200 mg IV every 3 weeks plus epacadostat 100 mg orally twice daily versus sunitinib 50 mg orally once daily (4 weeks on treatment followed by 2 weeks off treatment) or pazopanib 800 mg orally once daily. Original dual primary end points were progression-free survival and overall survival. Enrollment was stopped when a phase 3 study in melanoma of pembrolizumab plus epacadostat compared with pembrolizumab monotherapy did not meet its primary end point. This protocol was amended, and primary end point was changed to investigator-assessed objective response rate (ORR) per RECIST 1.1. RESULTS: One-hundred-twenty-nine patients were randomly assigned to receive pembrolizumab plus epacadostat (n = 64) or sunitinib/pazopanib (n = 65). Median (range) follow-up, defined as time from randomization to data cutoff, was 10.3 months (2.2-14.3) and 10.3 months (2.7-13.8) in the pembrolizumab plus epacadostat and sunitinib/pazopanib arms, respectively. ORRs were similar between pembrolizumab plus epacadostat (31.3% [95% CI 20.2-44.1] and sunitinib/pazopanib (29.2% [18.6-41.8]). Grade 3-5 treatment-related adverse events occurred in 34.4% and 42.9% of patients in the pembrolizumab plus epacadostat and sunitinib/pazopanib arms, respectively. One patient in the sunitinib/pazopanib arm died of septic shock (not treatment-related). Circulating kynurenine levels decreased in the pembrolizumab plus epacadostat arm, but not to levels observed in healthy subjects. CONCLUSIONS: ORRs were similar between pembrolizumab plus epacadostat and sunitinib/pazopanib as first-line treatment in patients with mRCC. Safety and tolerability appeared similar between treatment arms; no new safety concerns were identified. Antitumor responses observed in patients with RCC receiving pembrolizumab plus epacadostat may be driven primarily by pembrolizumab. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov; NCT03260894 .
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- 2024
11. Mental Modeling of Reinforcement Learning Agents by Language Models
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Lu, Wenhao, Zhao, Xufeng, Spisak, Josua, Lee, Jae Hee, and Wermter, Stefan
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence ,Computer Science - Computation and Language ,Computer Science - Robotics - Abstract
Can emergent language models faithfully model the intelligence of decision-making agents? Though modern language models exhibit already some reasoning ability, and theoretically can potentially express any probable distribution over tokens, it remains underexplored how the world knowledge these pretrained models have memorized can be utilized to comprehend an agent's behaviour in the physical world. This study empirically examines, for the first time, how well large language models (LLMs) can build a mental model of agents, termed agent mental modelling, by reasoning about an agent's behaviour and its effect on states from agent interaction history. This research may unveil the potential of leveraging LLMs for elucidating RL agent behaviour, addressing a key challenge in eXplainable reinforcement learning (XRL). To this end, we propose specific evaluation metrics and test them on selected RL task datasets of varying complexity, reporting findings on agent mental model establishment. Our results disclose that LLMs are not yet capable of fully mental modelling agents through inference alone without further innovations. This work thus provides new insights into the capabilities and limitations of modern LLMs., Comment: https://lukaswill.github.io/
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- 2024
12. Discrete-time thermodynamic speed limit
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Lee, Sangyun, Lee, Jae Sung, and Park, Jong-Min
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Condensed Matter - Statistical Mechanics - Abstract
As a fundamental thermodynamic principle, speed limits reveal the lower bound of entropy production (EP) required for a system to transition from a given initial state to a final state. While various speed limits have been developed for continuous-time Markov processes, their application to discrete-time Markov chains remains unexplored. In this study, we investigate the speed limits in discrete-time Markov chains, focusing on two types of EP commonly used to measure the irreversibility of a discrete-time process: time-reversed EP and time-backward EP. We find that time-reversed EP satisfies the speed limit for the continuous-time Markov processes, whereas time-backward EP does not. Additionally, for time-reversed EP, we derive practical speed limits applicable to systems driven by cyclic protocols or with unidirectional transitions, where conventional speed limits become meaningless or invalid. We show that these relations also hold for continuous-time Markov processes by taking the time-continuum limit of our results. Finally, we validate our findings through several examples., Comment: 8 pages, 3 figures
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- 2024
13. Hamilton-Jacobi Based Policy-Iteration via Deep Operator Learning
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Lee, Jae Yong and Kim, Yeoneung
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Mathematics - Optimization and Control ,Computer Science - Artificial Intelligence ,Computer Science - Machine Learning ,Mathematics - Numerical Analysis ,68T20, 68U07, 35F21, 49L12, 49L25 - Abstract
The framework of deep operator network (DeepONet) has been widely exploited thanks to its capability of solving high dimensional partial differential equations. In this paper, we incorporate DeepONet with a recently developed policy iteration scheme to numerically solve optimal control problems and the corresponding Hamilton--Jacobi--Bellman (HJB) equations. A notable feature of our approach is that once the neural network is trained, the solution to the optimal control problem and HJB equations with different terminal functions can be inferred quickly thanks to the unique feature of operator learning. Furthermore, a quantitative analysis of the accuracy of the algorithm is carried out via comparison principles of viscosity solutions. The effectiveness of the method is verified with various examples, including 10-dimensional linear quadratic regulator problems (LQRs)., Comment: 24 pages, 5 figures
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- 2024
14. SmartRSD: An Intelligent Multimodal Approach to Real-Time Road Surface Detection for Safe Driving
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Tayeb, Adnan Md, Khatun, Mst Ayesha, Golam, Mohtasin, Rahaman, Md Facklasur, Aouto, Ali, Angelo, Oroceo Paul, Lee, Minseon, Kim, Dong-Seong, Lee, Jae-Min, and Kim, Jung-Hyeon
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Computer Science - Computer Vision and Pattern Recognition - Abstract
Precise and prompt identification of road surface conditions enables vehicles to adjust their actions, like changing speed or using specific traction control techniques, to lower the chance of accidents and potential danger to drivers and pedestrians. However, most of the existing methods for detecting road surfaces solely rely on visual data, which may be insufficient in certain situations, such as when the roads are covered by debris, in low light conditions, or in the presence of fog. Therefore, we introduce a multimodal approach for the automated detection of road surface conditions by integrating audio and images. The robustness of the proposed method is tested on a diverse dataset collected under various environmental conditions and road surface types. Through extensive evaluation, we demonstrate the effectiveness and reliability of our multimodal approach in accurately identifying road surface conditions in real-time scenarios. Our findings highlight the potential of integrating auditory and visual cues for enhancing road safety and minimizing accident risks, Comment: 4 pages
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- 2024
15. Details Make a Difference: Object State-Sensitive Neurorobotic Task Planning
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Sun, Xiaowen, Zhao, Xufeng, Lee, Jae Hee, Lu, Wenhao, Kerzel, Matthias, and Wermter, Stefan
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Computer Science - Artificial Intelligence ,Computer Science - Computation and Language ,Computer Science - Robotics - Abstract
The state of an object reflects its current status or condition and is important for a robot's task planning and manipulation. However, detecting an object's state and generating a state-sensitive plan for robots is challenging. Recently, pre-trained Large Language Models (LLMs) and Vision-Language Models (VLMs) have shown impressive capabilities in generating plans. However, to the best of our knowledge, there is hardly any investigation on whether LLMs or VLMs can also generate object state-sensitive plans. To study this, we introduce an Object State-Sensitive Agent (OSSA), a task-planning agent empowered by pre-trained neural networks. We propose two methods for OSSA: (i) a modular model consisting of a pre-trained vision processing module (dense captioning model, DCM) and a natural language processing model (LLM), and (ii) a monolithic model consisting only of a VLM. To quantitatively evaluate the performances of the two methods, we use tabletop scenarios where the task is to clear the table. We contribute a multimodal benchmark dataset that takes object states into consideration. Our results show that both methods can be used for object state-sensitive tasks, but the monolithic approach outperforms the modular approach. The code for OSSA is available at \url{https://github.com/Xiao-wen-Sun/OSSA}
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- 2024
16. Power of Cooperative Supervision: Multiple Teachers Framework for Enhanced 3D Semi-Supervised Object Detection
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Lee, Jin-Hee, Lee, Jae-Keun, Kim, Je-Seok, and Kwon, Soon
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Computer Science - Computer Vision and Pattern Recognition - Abstract
To ensure safe urban driving for autonomous platforms, it is crucial not only to develop high-performance object detection techniques but also to establish a diverse and representative dataset that captures various urban environments and object characteristics. To address these two issues, we have constructed a multi-class 3D LiDAR dataset reflecting diverse urban environments and object characteristics, and developed a robust 3D semi-supervised object detection (SSOD) based on a multiple teachers framework. This SSOD framework categorizes similar classes and assigns specialized teachers to each category. Through collaborative supervision among these category-specialized teachers, the student network becomes increasingly proficient, leading to a highly effective object detector. We propose a simple yet effective augmentation technique, Pie-based Point Compensating Augmentation (PieAug), to enable the teacher network to generate high-quality pseudo-labels. Extensive experiments on the WOD, KITTI, and our datasets validate the effectiveness of our proposed method and the quality of our dataset. Experimental results demonstrate that our approach consistently outperforms existing state-of-the-art 3D semi-supervised object detection methods across all datasets. We plan to release our multi-class LiDAR dataset and the source code available on our Github repository in the near future., Comment: under review
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- 2024
17. The standard generators of the tetrahedron algebra and their look-alikes
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Lee, Jae-Ho
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Mathematics - Rings and Algebras ,17B65, 17B05 - Abstract
The tetrahedron algebra $\boxtimes$ is an infinite-dimensional Lie algebra defined by generators $\{x_{ij} \mid i, j \in \{0, 1, 2, 3\}, i \neq j\}$ and some relations, including the Dolan-Grady relations. These twelve generators are called standard. We introduce a type of element in $\boxtimes$ that "looks like" a standard generator. For mutually distinct $h, i, j, k \in \{0, 1, 2, 3\}$, consider the standard generator $x_{ij}$ of $\boxtimes$. An element $\xi \in \boxtimes$ is called $x_{ij}$-like whenever both (i) $\xi$ commutes with $x_{ij}$; (ii) $\xi$ and $x_{hk}$ satisfy a Dolan-Grady relation. Pick mutually distinct $i,j,k \in \{0,1,2,3\}$. In our main result, we find an attractive basis for $\boxtimes$ with the property that every basis element is either $x_{ij}$-like or $x_{jk}$-like or $x_{ki}$-like. We discuss this basis from multiple points of view., Comment: 30 pages
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- 2024
18. Masked Spatial Propagation Network for Sparsity-Adaptive Depth Refinement
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Jun, Jinyoung, Lee, Jae-Han, and Kim, Chang-Su
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Computer Science - Computer Vision and Pattern Recognition - Abstract
The main function of depth completion is to compensate for an insufficient and unpredictable number of sparse depth measurements of hardware sensors. However, existing research on depth completion assumes that the sparsity -- the number of points or LiDAR lines -- is fixed for training and testing. Hence, the completion performance drops severely when the number of sparse depths changes significantly. To address this issue, we propose the sparsity-adaptive depth refinement (SDR) framework, which refines monocular depth estimates using sparse depth points. For SDR, we propose the masked spatial propagation network (MSPN) to perform SDR with a varying number of sparse depths effectively by gradually propagating sparse depth information throughout the entire depth map. Experimental results demonstrate that MPSN achieves state-of-the-art performance on both SDR and conventional depth completion scenarios.
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- 2024
19. Real-Time 4K Super-Resolution of Compressed AVIF Images. AIS 2024 Challenge Survey
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Conde, Marcos V., Lei, Zhijun, Li, Wen, Stejerean, Cosmin, Katsavounidis, Ioannis, Timofte, Radu, Yoon, Kihwan, Gankhuyag, Ganzorig, Lv, Jiangtao, Sun, Long, Pan, Jinshan, Dong, Jiangxin, Tang, Jinhui, Li, Zhiyuan, Wei, Hao, Ge, Chenyang, Zhang, Dongyang, Liu, Tianle, Chen, Huaian, Jin, Yi, Zhou, Menghan, Yan, Yiqiang, Gao, Si, Wu, Biao, Liu, Shaoli, Zheng, Chengjian, Zhang, Diankai, Wang, Ning, Qiu, Xintao, Zhou, Yuanbo, Wu, Kongxian, Dai, Xinwei, Tang, Hui, Deng, Wei, Gao, Qingquan, Tong, Tong, Lee, Jae-Hyeon, Choi, Ui-Jin, Yan, Min, Liu, Xin, Wang, Qian, Ye, Xiaoqian, Du, Zhan, Zhang, Tiansen, Peng, Long, Guo, Jiaming, Di, Xin, Liao, Bohao, Du, Zhibo, Xia, Peize, Pei, Renjing, Wang, Yang, Cao, Yang, Zha, Zhengjun, Han, Bingnan, Yu, Hongyuan, Wu, Zhuoyuan, Wan, Cheng, Liu, Yuqing, Yu, Haodong, Li, Jizhe, Huang, Zhijuan, Huang, Yuan, Zou, Yajun, Guan, Xianyu, Jia, Qi, Zhang, Heng, Yin, Xuanwu, Zuo, Kunlong, Moon, Hyeon-Cheol, Jeong, Tae-hyun, Yang, Yoonmo, Kim, Jae-Gon, Jeong, Jinwoo, and Kim, Sunjei
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Computer Science - Computer Vision and Pattern Recognition ,Electrical Engineering and Systems Science - Image and Video Processing - Abstract
This paper introduces a novel benchmark as part of the AIS 2024 Real-Time Image Super-Resolution (RTSR) Challenge, which aims to upscale compressed images from 540p to 4K resolution (4x factor) in real-time on commercial GPUs. For this, we use a diverse test set containing a variety of 4K images ranging from digital art to gaming and photography. The images are compressed using the modern AVIF codec, instead of JPEG. All the proposed methods improve PSNR fidelity over Lanczos interpolation, and process images under 10ms. Out of the 160 participants, 25 teams submitted their code and models. The solutions present novel designs tailored for memory-efficiency and runtime on edge devices. This survey describes the best solutions for real-time SR of compressed high-resolution images., Comment: CVPR 2024, AI for Streaming (AIS) Workshop
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- 2024
20. Pegasus-v1 Technical Report
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Jung, Raehyuk, Go, Hyojun, Yi, Jaehyuk, Jang, Jiho, Kim, Daniel, Suh, Jay, Lee, Aiden, Han, Cooper, Lee, Jae, Kim, Jeff, Kim, Jin-Young, Kim, Junwan, Park, Kyle, Lee, Lucas, Ha, Mars, Seo, Minjoon, Jo, Abraham, Park, Ed, Kianinejad, Hassan, Kim, SJ, Moon, Tony, Jeong, Wade, Popescu, Andrei, Kim, Esther, Yoon, EK, Heo, Genie, Choi, Henry, Kang, Jenna, Han, Kevin, Seo, Noah, Nguyen, Sunny, Won, Ryan, Park, Yeonhoo, Giuliani, Anthony, Chung, Dave, Yoon, Hans, Le, James, Ahn, Jenny, Lee, June, Saini, Maninder, Sanders, Meredith, Lee, Soyoung, Kim, Sue, and Couture, Travis
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Computer Science - Multimedia ,Computer Science - Artificial Intelligence ,Computer Science - Computation and Language ,Computer Science - Computer Vision and Pattern Recognition - Abstract
This technical report introduces Pegasus-1, a multimodal language model specialized in video content understanding and interaction through natural language. Pegasus-1 is designed to address the unique challenges posed by video data, such as interpreting spatiotemporal information, to offer nuanced video content comprehension across various lengths. This technical report overviews Pegasus-1's architecture, training strategies, and its performance in benchmarks on video conversation, zero-shot video question answering, and video summarization. We also explore qualitative characteristics of Pegasus-1 , demonstrating its capabilities as well as its limitations, in order to provide readers a balanced view of its current state and its future direction.
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- 2024
21. AAM-VDT: Vehicle Digital Twin for Tele-Operations in Advanced Air Mobility
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Nguyen, Tuan Anh, Kwag, Taeho, Pham, Vinh, Nguyen, Viet Nghia, Hyun, Jeongseok, Jang, Minseok, and Lee, Jae-Woo
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Electrical Engineering and Systems Science - Systems and Control ,Computer Science - Emerging Technologies ,Computer Science - Human-Computer Interaction ,Computer Science - Robotics - Abstract
This study advanced tele-operations in Advanced Air Mobility (AAM) through the creation of a Vehicle Digital Twin (VDT) system for eVTOL aircraft, tailored to enhance remote control safety and efficiency, especially for Beyond Visual Line of Sight (BVLOS) operations. By synergizing digital twin technology with immersive Virtual Reality (VR) interfaces, we notably elevate situational awareness and control precision for remote operators. Our VDT framework integrates immersive tele-operation with a high-fidelity aerodynamic database, essential for authentically simulating flight dynamics and control tactics. At the heart of our methodology lies an eVTOL's high-fidelity digital replica, placed within a simulated reality that accurately reflects physical laws, enabling operators to manage the aircraft via a master-slave dynamic, substantially outperforming traditional 2D interfaces. The architecture of the designed system ensures seamless interaction between the operator, the digital twin, and the actual aircraft, facilitating exact, instantaneous feedback. Experimental assessments, involving propulsion data gathering, simulation database fidelity verification, and tele-operation testing, verify the system's capability in precise control command transmission and maintaining the digital-physical eVTOL synchronization. Our findings underscore the VDT system's potential in augmenting AAM efficiency and safety, paving the way for broader digital twin application in autonomous aerial vehicles.
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- 2024
22. MonoPatchNeRF: Improving Neural Radiance Fields with Patch-based Monocular Guidance
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Wu, Yuqun, Lee, Jae Yong, Zou, Chuhang, Wang, Shenlong, and Hoiem, Derek
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Computer Science - Computer Vision and Pattern Recognition - Abstract
The latest regularized Neural Radiance Field (NeRF) approaches produce poor geometry and view extrapolation for large scale sparse view scenes, such as ETH3D. Density-based approaches tend to be under-constrained, while surface-based approaches tend to miss details. In this paper, we take a density-based approach, sampling patches instead of individual rays to better incorporate monocular depth and normal estimates and patch-based photometric consistency constraints between training views and sampled virtual views. Loosely constraining densities based on estimated depth aligned to sparse points further improves geometric accuracy. While maintaining similar view synthesis quality, our approach significantly improves geometric accuracy on the ETH3D benchmark, e.g. increasing the F1@2cm score by 4x-8x compared to other regularized density-based approaches, with much lower training and inference time than other approaches.
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- 2024
23. Towards a classification of $1$-homogeneous distance-regular graphs with positive intersection number $a_1$
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Koolen, Jack H., Abdullah, Mamoon, Gebremichel, Brhane, and Lee, Jae-Ho
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Mathematics - Combinatorics ,05E30, 05C50 - Abstract
Let $\Gamma$ be a graph with diameter at least two. Then $\Gamma$ is said to be $1$-homogeneous (in the sense of Nomura) whenever for every pair of adjacent vertices $x$ and $y$ in $\Gamma$, the distance partition of the vertex set of $\Gamma$ with respect to both $x$ and $y$ is equitable, and the parameters corresponding to equitable partitions are independent of the choice of $x$ and $y$. Assume $\Gamma$ is $1$-homogeneous distance-regular with intersection number $a_1>0$ and $D\geqslant 5$. Define $b=b_1/(\theta_1+1)$, where $b_1$ is the intersection number and $\theta_1$ is the second largest eigenvalue of $\Gamma$. We show that if intersection number $c_2\geqslant 2$, then $b\geqslant 1$ and one of the following (i)--(vi) holds: (i) $\Gamma$ is a regular near $2D$-gon, (ii) $\Gamma$ is a Johnson graph $J(2D,D)$, (iii) $\Gamma$ is a halved $\ell$-cube where $\ell \in \{2D,2D+1\}$, (iv) $\Gamma$ is a folded Johnson graph $\bar{J}(4D,2D)$, (v) $\Gamma$ is a folded halved $(4D)$-cube, (vi) the valency of $\Gamma$ is bounded by a function of $b$. Using this result, we characterize $1$-homogeneous graphs with classical parameters and $a_1>0$, as well as tight distance-regular graphs., Comment: 19 pages
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- 2024
24. Comparative Analysis of Single and Combined Antipyretics Using Patient-Generated Health Data: Retrospective Observational Study
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Park, Yu Rang, Kim, Hyery, Park, Ji Ae, Ahn, Sang Hyun, Chang, Seyun, Shin, Jae Won, Kim, Myeongchan, and Lee, Jae-Ho
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Information technology ,T58.5-58.64 ,Public aspects of medicine ,RA1-1270 - Abstract
BackgroundFever is one of the most common symptoms in children and is the physiological response of the human immune system to external pathogens. However, effectiveness studies of single and combined antipyretic therapy are relatively few due to lack of data. In this study, we used large-scale patient-generated health data from mobile apps to compare antipyretic affects between single and combination antipyretics. ObjectiveWe aimed to establish combination patterns of antipyretics and compare antipyretic affects between single and combination antipyretics using large-scale patient-generated health data from mobile apps. MethodsThis study was conducted using medical records of feverish children from July 2015 to June 2017 using the Fever Coach mobile app. In total, 3,584,748 temperature records and 1,076,002 antipyretic records of 104,337 children were analyzed. Antipyretic efficacy was measured by the mean difference in the area under the temperature change curve from baseline for 6 hours, 8 hours, 10 hours, and 12 hours after antipyretic administration in children with a body temperature of ≥38.0 ℃ between single and combination groups. ResultsThe single antipyretic and combination groups comprised 152,017 and 54,842 cases, respectively. Acetaminophen was the most commonly used single agent (60,929/152,017, 40.08%), and acetaminophen plus dexibuprofen was the most common combination (28,065/54,842, 51.17%). We observed inappropriate use, including triple combination (1205/206,859, 0.58%) and use under 38 ℃ (11,361/206,859, 5.50%). Combination antipyretic use increased with temperature; 23.82% (33,379/140,160) of cases were given a combination treatment when 38 ℃ ≤ temperature < 39 ℃, while 41.40% (1517/3664) were given a combination treatment when 40 ℃ ≤ temperature. The absolute value of the area under the curve at each hour was significantly higher in the single group than in the combination group; this trend was consistently observed, regardless of the type of antipyretics. In particular, the delta fever during the first 6 hours between the two groups showed the highest difference. The combination showed the lowest delta fever among all cases. ConclusionsAntipyretics combination patterns were analyzed using large-scale data. Approximately 75% of febrile cases used single antipyretics, mostly acetaminophen, but combination usage became more frequent as temperature increased. However, combination antipyretics did not show definite advantages over single antipyretics in defervescence, regardless of the combination. Single antipyretics are effective in reducing fever and relieving discomfort in febrile children.
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- 2021
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25. Is the RSGC4 (Alicante 8) cluster a real star cluster?: Peculiar radial velocities of red supergiant stars
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Chun, Sang-Hyun, Myeong, GyuChul, Lee, Jae-Joon, and Oh, Heeyoung
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Astrophysics - Astrophysics of Galaxies - Abstract
Young massive star clusters, like the six red supergiant clusters in the Scutum complex, provide valuable insights into star-formation and galaxy structures. We investigated the high-resolution near-infrared spectra of 60 RSG candidates in these clusters using the Immersion Grating Infrared Spectrograph. Among the candidates in RSGC4, we found significant scattering in radial velocity ($-64$ km/s to $115$ km/s), unlike other clusters with velocities of $\sim$100 km/s. Most candidates in RSGC4 have $Q_{GK_s}$ values larger than 1.7, suggesting that they could be early AGB stars. Four candidates in RSGC4 exhibit infrared excess and distinct absorption features absent in other candidates. Two of these stars exhibit absorption lines resembling those of D-type symbiotic stars, showing radial velocity changes in multi-epoch observations. Analysis of relative proper motions revealed no runaway/walkaway stars in RSGC4. The dynamic properties of RSGC4 and RSGC1 differ from the disk-like motions of other clusters: RSGC4 has low normalized horizontal action $J_\mathrm{hor}=J_\mathrm{\phi}/J_\mathrm{tot}$ and vertical action $J_\mathrm{ver}=(J_\mathrm{z}-J_\mathrm{R})/J_\mathrm{tot}$ values and high eccentricities, while RSGC1 has vertical motions with high $J_\mathrm{ver}$ values and inclinations. We propose that RSGC4 may not be a genuine star cluster but rather a composite of RSGs and AGBs distributed along the line of sight at similar distances, possibly originating from various environments. Our results suggest a complex and hierarchical secular evolution of star clusters in the Scutum complex, emphasizing the importance of considering factors beyond density crowding when identifying star clusters in the bulge regions., Comment: 22 pages, 9 figures, 2 tables, accepted for publication in AJ
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- 2024
26. XB-MAML: Learning Expandable Basis Parameters for Effective Meta-Learning with Wide Task Coverage
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Lee, Jae-Jun and Yoon, Sung Whan
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Computer Science - Machine Learning - Abstract
Meta-learning, which pursues an effective initialization model, has emerged as a promising approach to handling unseen tasks. However, a limitation remains to be evident when a meta-learner tries to encompass a wide range of task distribution, e.g., learning across distinctive datasets or domains. Recently, a group of works has attempted to employ multiple model initializations to cover widely-ranging tasks, but they are limited in adaptively expanding initializations. We introduce XB-MAML, which learns expandable basis parameters, where they are linearly combined to form an effective initialization to a given task. XB-MAML observes the discrepancy between the vector space spanned by the basis and fine-tuned parameters to decide whether to expand the basis. Our method surpasses the existing works in the multi-domain meta-learning benchmarks and opens up new chances of meta-learning for obtaining the diverse inductive bias that can be combined to stretch toward the effective initialization for diverse unseen tasks., Comment: In Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 2024, Valencia, Spain
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- 2024
27. Structure-Preserving Operator Learning: Modeling the Collision Operator of Kinetic Equations
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Lee, Jae Yong, Schotthöfer, Steffen, Xiao, Tianbai, Krumscheid, Sebastian, and Frank, Martin
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Mathematics - Numerical Analysis - Abstract
This work explores the application of deep operator learning principles to a problem in statistical physics. Specifically, we consider the linear kinetic equation, consisting of a differential advection operator and an integral collision operator, which is a powerful yet expensive mathematical model for interacting particle systems with ample applications, e.g., in radiation transport. We investigate the capabilities of the Deep Operator network (DeepONet) approach to modelling the high dimensional collision operator of the linear kinetic equation. This integral operator has crucial analytical structures that a surrogate model, e.g., a DeepONet, needs to preserve to enable meaningful physical simulation. We propose several DeepONet modifications to encapsulate essential structural properties of this integral operator in a DeepONet model. To be precise, we adapt the architecture of the trunk-net so the DeepONet has the same collision invariants as the theoretical kinetic collision operator, thus preserving conserved quantities, e.g., mass, of the modeled many-particle system. Further, we propose an entropy-inspired data-sampling method tailored to train the modified DeepONet surrogates without requiring an excessive expensive simulation-based data generation., Comment: 12 pages, 8 figures
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- 2024
28. Tunable incommensurability and spontaneous symmetry breaking in the reconstructed moir\'e-of-moir\'e lattices
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Park, Daesung, Park, Changwon, Ko, Eunjung, Yananose, Kunihiro, Engelke, Rebecca, Zhang, Xi, Davydov, Konstantin, Green, Matthew, Park, Sang Hwa, Lee, Jae Heon, Watanabe, Kenji, Taniguchi, Takashi, Yang, Sang Mo, Wang, Ke, Kim, Philip, Son, Young-Woo, and Yoo, Hyobin
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Condensed Matter - Materials Science - Abstract
Imposing incommensurable periodicity on the periodic atomic lattice can lead to complex structural phases consisting of locally periodic structure bounded by topological defects. Twisted trilayer graphene (TTG) is an ideal material platform to study the interplay between different atomic periodicities, which can be tuned by twist angles between the layers, leading to moir\'e-of-moir\'e lattices. Interlayer and intralayer interactions between two interfaces in TTG transform this moir\'e-of-moir\'e lattice into an intricate network of domain structures at small twist angles, which can harbor exotic electronic behaviors. Here we report a complete structural phase diagram of TTG with atomic scale lattice reconstruction. Using transmission electron microscopy combined with a new interatomic potential simulation, we show that a cornucopia of large-scale moir\'e lattices, ranging from triangular, kagome, and a corner-shared hexagram-shaped domain pattern, are present. For small twist angles below 0.1{\deg}, all domains are bounded by a network of two-dimensional domain wall lattices. In particular, in the limit of small twist angles, the competition between interlayer stacking energy and the formation of discommensurate domain walls leads to unique spontaneous symmetry breaking structures with nematic orders, suggesting the pivotal role of long-range interactions across entire layers. The diverse tessellation of distinct domains, whose topological network can be tuned by the adjustment of the twist angles, establishes TTG as a platform for exploring the interplay between emerging quantum properties and controllable nontrivial lattices.
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- 2024
29. Hands-Free VR
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Fernandez, Jorge Askur Vazquez, Lee, Jae Joong, Vacca, Santiago Andrés Serrano, Magana, Alejandra, Benes, Bedrich, and Popescu, Voicu
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Computer Science - Human-Computer Interaction ,Computer Science - Artificial Intelligence ,Computer Science - Computation and Language - Abstract
The paper introduces Hands-Free VR, a voice-based natural-language interface for VR. The user gives a command using their voice, the speech audio data is converted to text using a speech-to-text deep learning model that is fine-tuned for robustness to word phonetic similarity and to spoken English accents, and the text is mapped to an executable VR command using a large language model that is robust to natural language diversity. Hands-Free VR was evaluated in a controlled within-subjects study (N = 22) that asked participants to find specific objects and to place them in various configurations. In the control condition participants used a conventional VR user interface to grab, carry, and position the objects using the handheld controllers. In the experimental condition participants used Hands-Free VR. The results confirm that: (1) Hands-Free VR is robust to spoken English accents, as for 20 of our participants English was not their first language, and to word phonetic similarity, correctly transcribing the voice command 96.71% of the time; (2) Hands-Free VR is robust to natural language diversity, correctly mapping the transcribed command to an executable command in 97.83% of the time; (3) Hands-Free VR had a significant efficiency advantage over the conventional VR interface in terms of task completion time, total viewpoint translation, total view direction rotation, and total left and right hand translations; (4) Hands-Free VR received high user preference ratings in terms of ease of use, intuitiveness, ergonomics, reliability, and desirability.
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- 2024
30. Mesoscopic Stacking Reconfigurations in Stacked van der Waals Film
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Heo, Yoon Seong, Kim, Tae Wan, Lee, Wooseok, Choi, Jungseok, Park, Soyeon, Yeom, Dong-Il, and Lee, Jae-Ung
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Condensed Matter - Materials Science - Abstract
Mesoscopic-scale stacking reconfigurations are investigated when van der Waals films are stacked. We have developed a method to visualize complicated stacking structures and mechanical distortions simultaneously in stacked atom-thick films using Raman spectroscopy. In the rigid limit, we found that the distortions originate from the transfer process, which can be understood through thin film mechanics with a large elastic property mismatch. In contrast, with atomic corrugations, the in-plane strain fields are more closely correlated with the stacking configuration, highlighting the impact of atomic reconstructions on the mesoscopic scale. We discovered that the grain boundaries don`t have a significant effect while the cracks are causing inhomogeneous strain in stacked polycrystalline films. This result contributes to understanding the local variation of emerging properties from moir\'e structures and advancing the reliability of stacked vdW material fabrication., Comment: 38 pages, 23 figures
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- 2024
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31. Any-Precision LLM: Low-Cost Deployment of Multiple, Different-Sized LLMs
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Park, Yeonhong, Hyun, Jake, Cho, SangLyul, Sim, Bonggeun, and Lee, Jae W.
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Computer Science - Machine Learning - Abstract
Recently, considerable efforts have been directed towards compressing Large Language Models (LLMs), which showcase groundbreaking capabilities across diverse applications but entail significant deployment costs due to their large sizes. Meanwhile, much less attention has been given to mitigating the costs associated with deploying multiple LLMs of varying sizes despite its practical significance. Thus, this paper introduces \emph{any-precision LLM}, extending the concept of any-precision DNN to LLMs. Addressing challenges in any-precision LLM, we propose a lightweight method for any-precision quantization of LLMs, leveraging a post-training quantization framework, and develop a specialized software engine for its efficient serving. As a result, our solution significantly reduces the high costs of deploying multiple, different-sized LLMs by overlaying LLMs quantized to varying bit-widths, such as 3, 4, ..., $n$ bits, into a memory footprint comparable to a single $n$-bit LLM. All the supported LLMs with varying bit-widths demonstrate state-of-the-art model quality and inference throughput, proving itself to be a compelling option for deployment of multiple, different-sized LLMs. Our code is open-sourced and available online., Comment: To appear at ICML 2024. Code is available at https://github.com/SNU-ARC/any-precision-llm
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- 2024
32. Learning time-dependent PDE via graph neural networks and deep operator network for robust accuracy on irregular grids
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Cho, Sung Woong, Lee, Jae Yong, and Hwang, Hyung Ju
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Computer Science - Machine Learning ,Mathematics - Numerical Analysis ,65D17, 68U07 - Abstract
Scientific computing using deep learning has seen significant advancements in recent years. There has been growing interest in models that learn the operator from the parameters of a partial differential equation (PDE) to the corresponding solutions. Deep Operator Network (DeepONet) and Fourier Neural operator, among other models, have been designed with structures suitable for handling functions as inputs and outputs, enabling real-time predictions as surrogate models for solution operators. There has also been significant progress in the research on surrogate models based on graph neural networks (GNNs), specifically targeting the dynamics in time-dependent PDEs. In this paper, we propose GraphDeepONet, an autoregressive model based on GNNs, to effectively adapt DeepONet, which is well-known for successful operator learning. GraphDeepONet exhibits robust accuracy in predicting solutions compared to existing GNN-based PDE solver models. It maintains consistent performance even on irregular grids, leveraging the advantages inherited from DeepONet and enabling predictions on arbitrary grids. Additionally, unlike traditional DeepONet and its variants, GraphDeepONet enables time extrapolation for time-dependent PDE solutions. We also provide theoretical analysis of the universal approximation capability of GraphDeepONet in approximating continuous operators across arbitrary time intervals., Comment: 25 pages, 11 figures
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- 2024
33. Higgs Boson Precision Analysis of the Full LHC Run 1 and Run 2 Data
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Heo, Yongtae, Jung, Dong-Won, and Lee, Jae Sik
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High Energy Physics - Phenomenology ,High Energy Physics - Experiment - Abstract
We perform global fits of the Higgs boson couplings to the full Higgs datasets collected at the LHC with the integrated luminosities per experiment of approximately 5/fb at 7 TeV, 20/fb at 8 TeV, and up to 139/fb at 13 TeV. Our combined analysis based on the experimental signal strengths used in this work and the theoretical ones elaborated for our analysis reliably reproduce the results in the literature. We reveal that the LHC Higgs precision data are no longer best described by the SM Higgs boson taking account of extensive and comprehensive CP-conserving and CP-violating scenarios found in several well-motivated models beyond the SM. Especially, in most of the fits considered in this work, we observe that the best-fitted values of the normalized Yukawa couplings are about $2\sigma$ below the corresponding SM ones with the $1\sigma$ errors of 3%-5%. On the other hand, the gauge-Higgs couplings are consistent with the SM with the $1\sigma$ errors of 2%-3%. Incidentally, the reduced Yukawa couplings help to explain the excess of the $H\to Z\gamma$ signal strength of $2.2\pm 0.7$ recently reported by the ATLAS and CMS collaborations., Comment: 44 pages, 14 figures, 23 tables; To appear in PRD, $H \to Z\gamma$ considered more rigorously: a few typos removed
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- 2024
34. Region-Based Representations Revisited
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Shlapentokh-Rothman, Michal, Blume, Ansel, Xiao, Yao, Wu, Yuqun, T V, Sethuraman, Tao, Heyi, Lee, Jae Yong, Torres, Wilfredo, Wang, Yu-Xiong, and Hoiem, Derek
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Computer Science - Computer Vision and Pattern Recognition - Abstract
We investigate whether region-based representations are effective for recognition. Regions were once a mainstay in recognition approaches, but pixel and patch-based features are now used almost exclusively. We show that recent class-agnostic segmenters like SAM can be effectively combined with strong unsupervised representations like DINOv2 and used for a wide variety of tasks, including semantic segmentation, object-based image retrieval, and multi-image analysis. Once the masks and features are extracted, these representations, even with linear decoders, enable competitive performance, making them well suited to applications that require custom queries. The compactness of the representation also makes it well-suited to video analysis and other problems requiring inference across many images., Comment: CVPR 2024 Camera Ready; website: https://regionreps.web.illinois.edu/
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- 2024
35. Motion-induced error reduction for high-speed dynamic digital fringe projection system
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Jeon, Sanghoon, Lee, Hyo-Geon, Lee, Jae-Sung, Kang, Bo-Min, Jeon, Byung-Wook, Yoon, Jun Young, and Hyun, Jae-Sang
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Computer Science - Computer Vision and Pattern Recognition ,Electrical Engineering and Systems Science - Systems and Control - Abstract
In phase-shifting profilometry (PSP), any motion during the acquisition of fringe patterns can introduce errors because it assumes both the object and measurement system are stationary. Therefore, we propose a method to pixel-wise reduce the errors when the measurement system is in motion due to a motorized linear stage. The proposed method introduces motion-induced error reduction algorithm, which leverages the motor's encoder and pinhole model of the camera and projector. 3D shape measurement is possible with only three fringe patterns by applying geometric constraints of the digital fringe projection system. We address the mismatch problem due to the motion-induced camera pixel disparities and reduce phase-shift errors. These processes are easy to implement and require low computational cost. Experimental results demonstrate that the presented method effectively reduces the errors even in non-uniform motion., Comment: 9 pages, 7 figures
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- 2024
36. A parameter-free approach for solving SOS-convex semi-algebraic fractional programs
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Yang, Chengmiao, Jiao, Liguo, and Lee, Jae Hyoung
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Mathematics - Optimization and Control ,90C32, 90C22, 90C23 - Abstract
In this paper, we study a class of nonsmooth fractional programs {\rm (FP, for short)} with SOS-convex semi-algebraic functions. Under suitable assumptions, we derive a strong duality result between the problem (FP) and its semidefinite programming (SDP) relaxations. Remarkably, we extract an optimal solution of the problem (FP) by solving one and only one associated SDP problem. Numerical examples are also given., Comment: 22 pages
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- 2024
37. Stereo-Matching Knowledge Distilled Monocular Depth Estimation Filtered by Multiple Disparity Consistency
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Ka, Woonghyun, Lee, Jae Young, Choi, Jaehyun, and Kim, Junmo
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Computer Science - Computer Vision and Pattern Recognition - Abstract
In stereo-matching knowledge distillation methods of the self-supervised monocular depth estimation, the stereo-matching network's knowledge is distilled into a monocular depth network through pseudo-depth maps. In these methods, the learning-based stereo-confidence network is generally utilized to identify errors in the pseudo-depth maps to prevent transferring the errors. However, the learning-based stereo-confidence networks should be trained with ground truth (GT), which is not feasible in a self-supervised setting. In this paper, we propose a method to identify and filter errors in the pseudo-depth map using multiple disparity maps by checking their consistency without the need for GT and a training process. Experimental results show that the proposed method outperforms the previous methods and works well on various configurations by filtering out erroneous areas where the stereo-matching is vulnerable, especially such as textureless regions, occlusion boundaries, and reflective surfaces., Comment: ICASSP 2024. The first two authors are equally contributed
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- 2024
38. Modeling Stereo-Confidence Out of the End-to-End Stereo-Matching Network via Disparity Plane Sweep
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Lee, Jae Young, Ka, Woonghyun, Choi, Jaehyun, and Kim, Junmo
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Computer Science - Computer Vision and Pattern Recognition - Abstract
We propose a novel stereo-confidence that can be measured externally to various stereo-matching networks, offering an alternative input modality choice of the cost volume for learning-based approaches, especially in safety-critical systems. Grounded in the foundational concepts of disparity definition and the disparity plane sweep, the proposed stereo-confidence method is built upon the idea that any shift in a stereo-image pair should be updated in a corresponding amount shift in the disparity map. Based on this idea, the proposed stereo-confidence method can be summarized in three folds. 1) Using the disparity plane sweep, multiple disparity maps can be obtained and treated as a 3-D volume (predicted disparity volume), like the cost volume is constructed. 2) One of these disparity maps serves as an anchor, allowing us to define a desirable (or ideal) disparity profile at every spatial point. 3) By comparing the desirable and predicted disparity profiles, we can quantify the level of matching ambiguity between left and right images for confidence measurement. Extensive experimental results using various stereo-matching networks and datasets demonstrate that the proposed stereo-confidence method not only shows competitive performance on its own but also consistent performance improvements when it is used as an input modality for learning-based stereo-confidence methods., Comment: AAAI 2024. The first two authors contributed equally
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- 2024
39. Universal Time-Series Representation Learning: A Survey
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Trirat, Patara, Shin, Yooju, Kang, Junhyeok, Nam, Youngeun, Na, Jihye, Bae, Minyoung, Kim, Joeun, Kim, Byunghyun, and Lee, Jae-Gil
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence - Abstract
Time-series data exists in every corner of real-world systems and services, ranging from satellites in the sky to wearable devices on human bodies. Learning representations by extracting and inferring valuable information from these time series is crucial for understanding the complex dynamics of particular phenomena and enabling informed decisions. With the learned representations, we can perform numerous downstream analyses more effectively. Among several approaches, deep learning has demonstrated remarkable performance in extracting hidden patterns and features from time-series data without manual feature engineering. This survey first presents a novel taxonomy based on three fundamental elements in designing state-of-the-art universal representation learning methods for time series. According to the proposed taxonomy, we comprehensively review existing studies and discuss their intuitions and insights into how these methods enhance the quality of learned representations. Finally, as a guideline for future studies, we summarize commonly used experimental setups and datasets and discuss several promising research directions. An up-to-date corresponding resource is available at https://github.com/itouchz/awesome-deep-time-series-representations., Comment: 41 pages, 7 figures
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- 2024
40. A JWST Survey of the Supernova Remnant Cassiopeia A
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Milisavljevic, Dan, Temim, Tea, De Looze, Ilse, Dickinson, Danielle, Laming, J. Martin, Fesen, Robert, Raymond, John C., Arendt, Richard G., Vink, Jacco, Posselt, Bettina, Pavlov, George G., Fox, Ori D., Pinarski, Ethan, Subrayan, Bhagya, Schmidt, Judy, Blair, William P., Rest, Armin, Patnaude, Daniel, Koo, Bon-Chul, Rho, Jeonghee, Orlando, Salvatore, Janka, Hans-Thomas, Andrews, Moira, Barlow, Michael J., Burrows, Adam, Chevalier, Roger, Clayton, Geoffrey, Fransson, Claes, Fryer, Christopher, Gomez, Haley L., Kirchschlager, Florian, Lee, Jae-Joon, Matsuura, Mikako, Niculescu-Duvaz, Maria, Pierel, Justin D. R., Plucinsky, Paul P., Priestley, Felix D., Ravi, Aravind P., Sartorio, Nina S., Schmidt, Franziska, Shahbandeh, Melissa, Slane, Patrick, Smith, Nathan, Weil, Kathryn, Wesson, Roger, and Wheeler, J. Craig
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Astrophysics - High Energy Astrophysical Phenomena - Abstract
We present initial results from a JWST survey of the youngest Galactic core-collapse supernova remnant Cassiopeia A (Cas A), made up of NIRCam and MIRI imaging mosaics that map emission from the main shell, interior, and surrounding circumstellar/interstellar material (CSM/ISM). We also present four exploratory positions of MIRI/MRS IFU spectroscopy that sample ejecta, CSM, and associated dust from representative shocked and unshocked regions. Surprising discoveries include: 1) a web-like network of unshocked ejecta filaments resolved to 0.01 pc scales exhibiting an overall morphology consistent with turbulent mixing of cool, low-entropy matter from the progenitor's oxygen layer with hot, high-entropy matter heated by neutrino interactions and radioactivity, 2) a thick sheet of dust-dominated emission from shocked CSM seen in projection toward the remnant's interior pockmarked with small (approximately one arcsecond) round holes formed by knots of high-velocity ejecta that have pierced through the CSM and driven expanding tangential shocks, 3) dozens of light echoes with angular sizes between 0.1 arcsecond to 1 arcminute reflecting previously unseen fine-scale structure in the ISM. NIRCam observations place new upper limits on infrared emission from the neutron star in Cas A's center and tightly constrain scenarios involving a possible fallback disk. These JWST survey data and initial findings help address unresolved questions about massive star explosions that have broad implications for the formation and evolution of stellar populations, the metal and dust enrichment of galaxies, and the origin of compact remnant objects., Comment: 27 pages, 10 figures, now published in ApJL
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- 2024
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41. Prediction of Prolonged Length of Hospital Stay After Cancer Surgery Using Machine Learning on Electronic Health Records: Retrospective Cross-sectional Study
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Jo, Yong-Yeon, Han, JaiHong, Park, Hyun Woo, Jung, Hyojung, Lee, Jae Dong, Jung, Jipmin, Cha, Hyo Soung, Sohn, Dae Kyung, and Hwangbo, Yul
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Computer applications to medicine. Medical informatics ,R858-859.7 - Abstract
BackgroundPostoperative length of stay is a key indicator in the management of medical resources and an indirect predictor of the incidence of surgical complications and the degree of recovery of the patient after cancer surgery. Recently, machine learning has been used to predict complex medical outcomes, such as prolonged length of hospital stay, using extensive medical information. ObjectiveThe objective of this study was to develop a prediction model for prolonged length of stay after cancer surgery using a machine learning approach. MethodsIn our retrospective study, electronic health records (EHRs) from 42,751 patients who underwent primary surgery for 17 types of cancer between January 1, 2000, and December 31, 2017, were sourced from a single cancer center. The EHRs included numerous variables such as surgical factors, cancer factors, underlying diseases, functional laboratory assessments, general assessments, medications, and social factors. To predict prolonged length of stay after cancer surgery, we employed extreme gradient boosting classifier, multilayer perceptron, and logistic regression models. Prolonged postoperative length of stay for cancer was defined as bed-days of the group of patients who accounted for the top 50% of the distribution of bed-days by cancer type. ResultsIn the prediction of prolonged length of stay after cancer surgery, extreme gradient boosting classifier models demonstrated excellent performance for kidney and bladder cancer surgeries (area under the receiver operating characteristic curve [AUC] >0.85). A moderate performance (AUC 0.70-0.85) was observed for stomach, breast, colon, thyroid, prostate, cervix uteri, corpus uteri, and oral cancers. For stomach, breast, colon, thyroid, and lung cancers, with more than 4000 cases each, the extreme gradient boosting classifier model showed slightly better performance than the logistic regression model, although the logistic regression model also performed adequately. We identified risk variables for the prediction of prolonged postoperative length of stay for each type of cancer, and the importance of the variables differed depending on the cancer type. After we added operative time to the models trained on preoperative factors, the models generally outperformed the corresponding models using only preoperative variables. ConclusionsA machine learning approach using EHRs may improve the prediction of prolonged length of hospital stay after primary cancer surgery. This algorithm may help to provide a more effective allocation of medical resources in cancer surgery.
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- 2021
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42. Lifelog Data-Based Prediction Model of Digital Health Care App Customer Churn: Retrospective Observational Study
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Kwon, Hongwook, Kim, Ho Heon, An, Jaeil, Lee, Jae-Ho, and Park, Yu Rang
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Computer applications to medicine. Medical informatics ,R858-859.7 ,Public aspects of medicine ,RA1-1270 - Abstract
BackgroundCustomer churn is the rate at which customers stop doing business with an entity. In the field of digital health care, user churn prediction is important not only in terms of company revenue but also for improving the health of users. Churn prediction has been previously studied, but most studies applied time-invariant model structures and used structured data. However, additional unstructured data have become available; therefore, it has become essential to process daily time-series log data for churn predictions. ObjectiveWe aimed to apply a recurrent neural network structure to accept time-series patterns using lifelog data and text message data to predict the churn of digital health care users. MethodsThis study was based on the use data of a digital health care app that provides interactive messages with human coaches regarding food, exercise, and weight logs. Among the users in Korea who enrolled between January 1, 2017 and January 1, 2019, we defined churn users according to the following criteria: users who received a refund before the paid program ended and users who received a refund 7 days after the trial period. We used long short-term memory with a masking layer to receive sequence data with different lengths. We also performed topic modeling to vectorize text messages. To interpret the contributions of each variable to model predictions, we used integrated gradients, which is an attribution method. ResultsA total of 1868 eligible users were included in this study. The final performance of churn prediction was an F1 score of 0.89; that score decreased by 0.12 when the data of the final week were excluded (F1 score 0.77). Additionally, when text data were included, the mean predicted performance increased by approximately 0.085 at every time point. Steps per day had the largest contribution (0.1085). Among the topic variables, poor habits (eg, drinking alcohol, overeating, and late-night eating) showed the largest contribution (0.0875). ConclusionsThe model with a recurrent neural network architecture that used log data and message data demonstrated high performance for churn classification. Additionally, the analysis of the contribution of the variables is expected to help identify signs of user churn in advance and improve the adherence in digital health care.
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- 2021
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43. Factors Associated with and Impact of Open Conversion in Laparoscopic and Robotic Minor Liver Resections: An International Multicenter Study of 10,541 Patients
- Author
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Saleh, Mansour, Pascual, Franco, Ghallab, Mohammed, Wu, Andrew G. R., Chin, Ken-Min, Ratti, Francesca, Giglio, Mariano Cesare, Garatti, Marco, Nghia, Phan Phuoc, Kato, Yutaro, Lim, Chetana, Herman, Paulo, Coelho, Fabricio Ferreira, Schmelzle, Moritz, Pratschke, Johann, Aghayan, Davit L., Liu, Qiu, Marino, Marco V., Belli, Andrea, Chiow, Adrian K. H., Sucandy, Iswanto, Ivanecz, Arpad, Di Benedetto, Fabrizio, Choi, Sung Hoon, Lee, Jae Hoon, Park, James O., Prieto, Mikel, Guzman, Yoelimar, Fondevila, Constantino, Efanov, Mikhail, Rotellar, Fernando, Choi, Gi-Hong, Robles-Campos, Ricardo, Kadam, Prashant, Sutcliffe, Robert P., Troisi, Roberto I., Tang, Chung Ngai, Chong, Charing C., D’Hondt, Mathieu, Dalla Valle, Bernardo, Ruzzenente, Andrea, Kingham, T. Peter, Scatton, Olivier, Liu, Rong, Mejia, Alejandro, Mishima, Kohei, Wakabayashi, Go, Lopez-Ben, Santiago, Wang, Xiaoying, Ferrero, Alessandro, Ettorre, Giuseppe Maria, Vivarelli, Marco, Mazzaferro, Vincenzo, Giuliante, Felice, Yong, Chee Chien, Yin, Mengqiu, Monden, Kazuteru, Geller, David, Chen, Kuo-Hsin, Sugioka, Atsushi, Edwin, Bjørn, Cheung, Tan-To, Long, Tran Cong Duy, Abu Hilal, Mohammad, Aldrighetti, Luca, Soubrane, Olivier, Fuks, David, Han, Ho-Seong, Cherqui, Daniel, and Goh, Brian K. P.
- Published
- 2024
- Full Text
- View/download PDF
44. Accessing of Viable Bacteria Captured by Antimicrobial Filters in a Metropolitan Subway of South Korea
- Author
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Ko, Sangwon, Park, Ki Hoon, Lee, Jae-Young, and Kim, Young Bong
- Published
- 2024
- Full Text
- View/download PDF
45. Differences in the prevalence of NAFLD, MAFLD, and MASLD according to changes in the nomenclature in a health check-up using MRI-derived proton density fat fraction
- Author
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Park, Hee Jun, Lee, Sunyoung, and Lee, Jae Seung
- Published
- 2024
- Full Text
- View/download PDF
46. Improvement of sleep disorders through the adenosine A receptor agonist effect of Phlomoides umbrosa Turczaninow root extract in pentobarbital-induced ICR mice
- Author
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Oh, Joo-Hyun, Han, Yoon-Young, Kim, Eun-Bi, Jo, Ha-Neul, Lee, Jae-Sun, Kim, Bo-Mi, Kim, Ji-Min, Lee, Young-Seob, Lee, Dae Young, Kim, Kwan-Woo, Lee, Inil, Lee, Yong-Wook, Park, Chan-Sung, and Kim, Dae-Ok
- Published
- 2024
- Full Text
- View/download PDF
47. The Hupo Basin, a neotectonic piggyback basin on the eastern Korean margin
- Author
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Lee, Jae-Hyuk and Kim, Gi-Bom
- Published
- 2024
- Full Text
- View/download PDF
48. Assessing the Brain Death/Death by Neurologic Criteria Determination Process in Korea: Insights from 10-Year Noncompleted Donation Data
- Author
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Koh, Seungyon, Park, Sungju, Lee, Mijin, Kim, Hanki, Lee, Won Jung, Lee, Jae-Myeong, and Choi, Jun Young
- Published
- 2024
- Full Text
- View/download PDF
49. In planta production of human-derived RANKL
- Author
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Lee, Jae-Ho, Geem, Kyoung Rok, Chen, Zhihao, Jeong, Jujin, Park, Sang-Wook, and Lee, Dong Wook
- Published
- 2024
- Full Text
- View/download PDF
50. Development of wet-type ten-path ultrasonic flowmeters to validate their performance at two national metrology institutes
- Author
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Park, Jungkyu, Chun, Sejong, Yoon, Byung-Ro, Kim, Joohyun, and Lee, Jae-Yong
- Published
- 2024
- Full Text
- View/download PDF
Catalog
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