arXiv subjects

Zhihao Chen

Publications and source records attributed to Zhihao Chen.

86 records · Page 5Linked to original sources

arXiv2022

Evolution of A Peculiar Type Ibn Supernova SN 2019wep

We present a high-cadence short term photometric and spectroscopic monitoring campaign of a type Ibn SN 2019wep, which is one of the rare SN Ibn after SNe 2010al and 2019uo to display signatures of flash ionization (\ion{He}{2}, \ion{C}{3}, \ion{N}{3}). We compare the decline rates and rise time of SN 2019wep with other SNe Ibn and fast transients. The post-peak decline in all bands (0.1 mag d$^{-1}$) are consistent with SNe Ibn but less than the fast transients. On the other hand, the $Δ$m$_{15}$ values are slightly lower than the average values for SNe Ibn but consistent with the fast transients. The rise time is typically shorter than SNe Ibn but longer than fast transients. SN 2019wep lies at the fainter end of SNe Ibn but possesses an average luminosity amongst the fast transients sample. The peculiar color evolution places it between SNe Ib and the most extreme SNe Ibn. The bolometric light curve modelling shows resemblance with SN 2019uo with ejecta masses consistent with SNe Ib. SN 2019wep belongs to the "P cygni" sub-class of SNe Ibn and shows faster evolution in line velocities as compared to the "emission" sub-class. The post-maximum spectra show close resemblance with ASASSN-15ed hinting it to be of SN Ib nature. The low \ion{He}{1} CSM velocities and residual H$α$ further justifies it and gives evidence of an intermittent progenitor between WR and LBV star.

astro-ph.HE↗

arXiv2022

Feature Transformation for Cross-domain Few-shot Remote Sensing Scene Classification

Effectively classifying remote sensing scenes is still a challenge due to the increasing spatial resolution of remote imaging and large variances between remote sensing images. Existing research has greatly improved the performance of remote sensing scene classification (RSSC). However, these methods are not applicable to cross-domain few-shot problems where target domain is with very limited training samples available and has a different data distribution from source domain. To improve the model's applicability, we propose the feature-wise transformation module (FTM) in this paper. FTM transfers the feature distribution learned on source domain to that of target domain by a very simple affine operation with negligible additional parameters. Moreover, FTM can be effectively learned on target domain in the case of few training data available and is agnostic to specific network structures. Experiments on RSSC and land-cover mapping tasks verified its capability to handle cross-domain few-shot problems. By comparison with directly finetuning, FTM achieves better performance and possesses better transferability and fine-grained discriminability. \textit{Code will be publicly available.}

cs.CV↗

arXiv2021

Effect of density control in partially observable asymmetric-exit evacuation under guidance: Strategic suggestion under time delay

To enhance the evacuation efficiency in partially observable asymmetric-exit evacuation under guidance, a general framework of the dynamic guiding assistant system is presented to investigate the effect of density control. In this framework, several evacuation assistants are established to observe the partial information of pedestrians' location and adjust the guiding signals of the dynamic guiding assistant systems. A simple on-off-based density control algorithm is proposed for the evacuation assistants according to the delayed data of the observed information (i.e., pedestrian densities in the observed regions near the corresponding exits). This paper provides strategic suggestions on how to set the observed region and the target density by involving a force-driven cellular automaton model. It is observed that the proposed density control algorithm can control (positively affect) the global distribution of the pedestrians' locations and suppress arching phenomena in the evacuation process even using the observed partial information under time delays. By imposing a moderate target density, the dynamic guiding assistant system also suppresses the triggers of collisions around the exits and avoids inefficiently separating the pedestrians. To enhance evacuation efficiency, we reveal an interesting fact without loss of generality that we only need to observe the pedestrians' location from a small region near the exit instead of a large region when the time delay of the observed information is slight enough. Our numerical findings are expected to provide new insights into designing computer-aided guiding strategies in real evacuations.

physics.soc-ph↗

arXiv2021

Minute-cadence Observations of the LAMOST Fields with the TMTS: I. Methodology of Detecting Short-period Variables and Results from the first-year Survey

Tsinghua University-Ma Huateng Telescopes for Survey (TMTS), located at Xinglong Station of NAOC, has a field of view upto 18 deg^2. The TMTS has started to monitor the LAMOST sky areas since 2020, with the uninterrupted observations lasting for about 6 hours on average for each sky area and a cadence of about 1 minute. Here we introduce the data analysis and preliminary scientific results for the first-year observations, which covered 188 LAMOST plates ( about 1970 deg^2). These observations have generated over 4.9 million uninterrupted light curves, with at least 100 epochs for each of them. These light curves correspond to 4.26 million Gaia-DR2 sources, among which 285 thousand sources are found to have multi-epoch spectra from the LAMOST. By analysing these light curves with the Lomb-Scargle periodograms, we identify more than 3700 periodic variable star candidates with periods below 7.5 hours, primarily consisting of eclipsing binaries and Delta Scuti stars. Those short-period binaries will provide important constraints on theories of binary evolution and possible sources for space gravitational wave experiments in the future. Moreover, we also identified 42 flare stars by searching rapidly-evolving signals in the light curves. The densely-sampled light curves from the TMTS allow us to better quantify the shapes and durations for these flares.

astro-ph.IM↗

arXiv2021

Deep Learning methods for automatic evaluation of delayed enhancement-MRI. The results of the EMIDEC challenge

A key factor for assessing the state of the heart after myocardial infarction (MI) is to measure whether the myocardium segment is viable after reperfusion or revascularization therapy. Delayed enhancement-MRI or DE-MRI, which is performed several minutes after injection of the contrast agent, provides high contrast between viable and nonviable myocardium and is therefore a method of choice to evaluate the extent of MI. To automatically assess myocardial status, the results of the EMIDEC challenge that focused on this task are presented in this paper. The challenge's main objectives were twofold. First, to evaluate if deep learning methods can distinguish between normal and pathological cases. Second, to automatically calculate the extent of myocardial infarction. The publicly available database consists of 150 exams divided into 50 cases with normal MRI after injection of a contrast agent and 100 cases with myocardial infarction (and then with a hyperenhanced area on DE-MRI), whatever their inclusion in the cardiac emergency department. Along with MRI, clinical characteristics are also provided. The obtained results issued from several works show that the automatic classification of an exam is a reachable task (the best method providing an accuracy of 0.92), and the automatic segmentation of the myocardium is possible. However, the segmentation of the diseased area needs to be improved, mainly due to the small size of these areas and the lack of contrast with the surrounding structures.

eess.IV↗

arXiv2021

Physics-informed generative neural network: an application to troposphere temperature prediction

The troposphere is one of the atmospheric layers where most weather phenomena occur. Temperature variations in the troposphere, especially at 500 hPa, a typical level of the middle troposphere, are significant indicators of future weather changes. Numerical weather prediction is effective for temperature prediction, but its computational complexity hinders a timely response. This paper proposes a novel temperature prediction approach in framework ofphysics-informed deep learning. The new model, called PGnet, builds upon a generative neural network with a mask matrix. The mask is designed to distinguish the low-quality predicted regions generated by the first physical stage. The generative neural network takes the mask as prior for the second-stage refined predictions. A mask-loss and a jump pattern strategy are developed to train the generative neural network without accumulating errors during making time-series predictions. Experiments on ERA5 demonstrate that PGnet can generate more refined temperature predictions than the state-of-the-art.

cs.LG↗

arXiv2021

Triple-cooperative Video Shadow Detection

Shadow detection in a single image has received significant research interest in recent years. However, much fewer works have been explored in shadow detection over dynamic scenes. The bottleneck is the lack of a well-established dataset with high-quality annotations for video shadow detection. In this work, we collect a new video shadow detection dataset, which contains 120 videos with 11, 685 frames, covering 60 object categories, varying lengths, and different motion/lighting conditions. All the frames are annotated with a high-quality pixel-level shadow mask. To the best of our knowledge, this is the first learning-oriented dataset for video shadow detection. Furthermore, we develop a new baseline model, named triple-cooperative video shadow detection network (TVSD-Net). It utilizes triple parallel networks in a cooperative manner to learn discriminative representations at intra-video and inter-video levels. Within the network, a dual gated co-attention module is proposed to constrain features from neighboring frames in the same video, while an auxiliary similarity loss is introduced to mine semantic information between different videos. Finally, we conduct a comprehensive study on ViSha, evaluating 12 state-of-the-art models (including single image shadow detectors, video object segmentation, and saliency detection methods). Experiments demonstrate that our model outperforms SOTA competitors.

cs.CV↗

arXiv2021

The Peculiar Transient AT2018cow: A Possible Origin of A Type Ibn/IIn Supernova

We present our photometric and spectroscopic observations on the peculiar transient AT2018cow. The multi-band photometry covers from peak to $\sim$70 days and the spectroscopy ranges from 5 to $\sim$50 days. The rapid rise ($t_{\mathrm{r}}$$\lesssim$2.9 days), high luminosity ($M_{V,\mathrm{peak}}\sim-$20.8 mag) and fast decline after peak make AT2018cow stand out of any other optical transients. While we find that its light curves show high resemblance to those of type Ibn supernovae. Moreover, the spectral energy distribution remains high temperature of $\sim$14,000 K after $\sim$15 days since discovery. The spectra are featureless in the first 10 days, while some broad emission lines due to H, He, C and O emerge later, with velocity declining from $\sim$14,000 km s$^{-1}$ to $\sim$3000 km s$^{-1}$ at the end of our observations. Narrow and weak He I emission lines emerge in the spectra at $t>$20 days since discovery. These emission lines are reminiscent of the features seen in interacting supernovae like type Ibn and IIn subclasses. We fit the bolometric light curves with a model of circumstellar interaction (CSI) and radioactive decay (RD) of \Ni and find a good fit with ejecta mass $M_{\mathrm{ej}}\sim$3.16 M$_{\odot}$, circumstellar material mass $M_{\mathrm{CSM}}\sim$0.04 M$_{\odot}$, and ejected \Ni mass $M_{^{56}\mathrm{Ni}}\sim$0.23 M$_{\odot}$. The CSM shell might be formed in an eruptive mass ejection of the progenitor star. Furthermore, host environment of AT2018cow implies connection of AT2018cow with massive stars. Combining observational properties and the light curve fitting results, we conclude that AT2018cow might be a peculiar interacting supernova originated from a massive star.

astro-ph.HE↗

arXiv2020

Can Helium-detonation Model Explain the Observed Diversity of Type Ia Supernovae?

We study a sample of 16 Type Ia supernovae (SNe Ia) having both spectroscopic and photometric observations within 2 $-$ 3 days after the first light. The early $B-V$ colors of such a sample tends to show a continuous distribution. For objects with normal ejecta velocity (NV), the C~II $λ$6580 feature is always visible in the early spectra while it is absent or very weak in the high-velocity (HV) counterpart. Moreover, the velocities of the detached high-velocity features (HVFs) of Ca~II NIR triplet (CaIR3) above the photosphere are found to be much higher in HV objects than in NV objects, with typical values exceeding 30,000 km~s$^{-1}$ at 2 $-$ 3 days. We further analyze the relation between %velocities of Si~II~$λ$6355 at maximum, $v_{\rm Si,max}$, the velocity shift of late-time [Fe~II] lines ($v_{\rm [Fe~II]}$) and host galaxy mass. We find that all HV objects have redshifted $v_{\rm [Fe~II]}$ while NV objects have both blue- and redshifted $v_{\rm [Fe~II]}$. It is interesting to point out that the objects with redshifted $v_{\rm [Fe~II]}$ are all located in massive galaxies, implying that HV and a portion of NV objects may have similar progenitor metallicities and explosion mechanisms. We propose that, with a geometric/projected effect, the He-detonation model may account for the similarity in birthplace environment and the differences seen in some SNe Ia, including $B-V$ colors, C~II feature, CaIR3 HVFs at early time and $v_{\rm [Fe~II]}$ in the nebular phase. Nevertheless, some features predicted by He-detonation simulation, such as the rapidly decreasing light curve, deviate from the observations, and some NV objects with blueshifted nebular $v_{\rm [Fe~II]}$ may involve other explosion mechanisms.

astro-ph.SR↗

arXiv2019

Effects of Blur and Deblurring to Visual Object Tracking

Intuitively, motion blur may hurt the performance of visual object tracking. However, we lack quantitative evaluation of tracker robustness to different levels of motion blur. Meanwhile, while image deblurring methods can produce visually clearer videos for pleasing human eyes, it is unknown whether visual object tracking can benefit from image deblurring or not. In this paper, we address these two problems by constructing a Blurred Video Tracking benchmark, which contains a variety of videos with different levels of motion blurs, as well as ground truth tracking results for evaluating trackers. We extensively evaluate 23 trackers on this benchmark and observe several new interesting results. Specifically, we find that light blur may improve the performance of many trackers, but heavy blur always hurts the tracking performance. We also find that image deblurring may help to improve tracking performance on heavily blurred videos but hurt the performance on lightly blurred videos. According to these observations, we propose a new GAN based scheme to improve the tracker robustness to motion blurs. In this scheme, a finetuned discriminator is used as an adaptive assessor to selectively deblur frames during the tracking process. We use this scheme to successfully improve the accuracy and robustness of 6 trackers.

cs.CV↗

arXiv2019

Observations of Type Ia Supernova 2014J for Nearly 900 Days and Constraints on Its Progenitor System

We present extensive ground-based and $Hubble~Space~Telescope$ ($HST$) photometry of the highly reddened, very nearby type Ia supernova (SN Ia) 2014J in M82, covering the phases from 9 days before to about 900 days after the $B$-band maximum. SN 2014J is similar to other normal SNe Ia near the maximum light, but it shows flux excess in the $B$ band in the early nebular phase. This excess flux emission can be due to light scattering by some structures of circumstellar materials located at a few 10$^{17}$ cm, consistent with a single degenerate progenitor system or a double degenerate progenitor system with mass outflows in the final evolution or magnetically driven winds around the binary system. At t$\sim$+300 to $\sim$+500 days past the $B$-band maximum, the light curve of SN 2014J shows a faster decline relative to the $^{56}$Ni decay. Such a feature can be attributed to the significant weakening of the emission features around [Fe III] $λ$4700 and [Fe II] $λ$5200 rather than the positron escape as previously suggested. Analysis of the $HST$ images taken at t$>$600 days confirms that the luminosity of SN 2014J maintains a flat evolution at the very late phase. Fitting the late-time pseudo-bolometric light curve with radioactive decay of $^{56}$Ni, $^{57}$Ni and $^{55}$Fe isotopes, we obtain the mass ratio $^{57}$Ni/$^{56}$Ni as $0.035 \pm 0.011$, which is consistent with the corresponding value predicted from the 2D and 3D delayed-detonation models. Combined with early-time analysis, we propose that delayed-detonation through single degenerate scenario is most likely favored for SN 2014J.

astro-ph.SR↗

arXiv2019

Data-Driven Online Optimization for Enhancing Power System Oscillation Damping

This paper reports an initial work on power system oscillation damping improvement using a data-driven online optimization method. An online oscillation damping optimization mod-el is proposed and formulated in a form solvable by the data-driven method. Key issues in the online optimization procedures, including the damping sensitivity identification method, its compatibility with the dispatch plans, as well as other practical issues in real large-scale system are discussed. Simulation results based on the 2-area 4-machine system, and the NETS-NYPS 68-bus system verify the feasibility and efficiency of the proposed method. The results also show the capability of the proposed method to bridge the gap between online data analysis and complex optimization for power system dynamics.

math.OC↗

arXiv2018

Seeing Double: ASASSN-18bt Exhibits a Two-Component Rise in the Early-Time K2 Light Curve

On 2018 Feb. 4.41, the All-Sky Automated Survey for SuperNovae (ASAS-SN) discovered ASASSN-18bt in the K2 Campaign 16 field. With a redshift of z=0.01098 and a peak apparent magnitude of B_{max}=14.31, ASASSN-18bt is the nearest and brightest SNe Ia yet observed by the Kepler spacecraft. Here we present the discovery of ASASSN-18bt, the K2 light curve, and pre-discovery data from ASAS-SN and the Asteroid Terrestrial-impact Last Alert System (ATLAS). The K2 early-time light curve has an unprecedented 30-minute cadence and photometric precision for an SN~Ia light curve, and it unambiguously shows a ~4 day nearly linear phase followed by a steeper rise. Thus, ASASSN-18bt joins a growing list of SNe Ia whose early light curves are not well described by a single power law. We show that a double-power-law model fits the data reasonably well, hinting that two physical processes must be responsible for the observed rise. However, we find that current models of the interaction with a non-degenerate companion predict an abrupt rise and cannot adequately explain the initial, slower linear phase. Instead, we find that existing, published models with shallow 56Ni are able to span the observed behavior and, with tuning, may be able to reproduce the ASASSN-18bt light curve. Regardless, more theoretical work is needed to satisfactorily model this and other early-time SNe~Ia light curves. Finally, we use Swift X-ray non-detections to constrain the presence of circumstellar material (CSM) at much larger distances and lower densities than possible with the optical light curve. For a constant density CSM these non-detections constrain rho<4.5 * 10^5 cm^-3 at a radius of 4 *10^15 cm from the progenitor star. Assuming a wind-like environment, we place mass-loss limits of Mdot< 8 * 10^-6 M_sun yr^-1 for v_w=100 km s^-1, ruling out some symbiotic progenitor systems.

astro-ph.HE↗

arXiv2014

A Smart Cushion for Real-Time Heart Rate Monitoring

This paper presents a smart cushion for real time heart rate monitoring. The cushion comprises of an integrated micro-bending fiber sensor, which records the BCG (Ballistocardiogram) signal without direct skin-electrode contact, and an optical transceiver that does signal amplification, digitization, and pre-filtering. To remove the artifacts and extract heart rate from BCG signal, a computationally efficient heart rate detection algorithm is developed. The system doesn't require any pre-training and is highly responsive with the outputs updated every 3 sec and initial response within first 10 sec. Tests conducted on human subjects show the detected heart rate closely matches the one from a commercial SpO2 device.

cs.OH↗