arXiv subjects

Shiyu Zhang

Publications and source records attributed to Shiyu Zhang.

54 records · Page 3Linked to original sources

arXiv2024

Fuzzy Logic Guided Reward Function Variation: An Oracle for Testing Reinforcement Learning Programs

Reinforcement Learning (RL) has gained significant attention across various domains. However, the increasing complexity of RL programs presents testing challenges, particularly the oracle problem: defining the correctness of the RL program. Conventional human oracles struggle to cope with the complexity, leading to inefficiencies and potential unreliability in RL testing. To alleviate this problem, we propose an automated oracle approach that leverages RL properties using fuzzy logic. Our oracle quantifies an agent's behavioral compliance with reward policies and analyzes its trend over training episodes. It labels an RL program as "Buggy" if the compliance trend violates expectations derived from RL characteristics. We evaluate our oracle on RL programs with varying complexities and compare it with human oracles. Results show that while human oracles perform well in simpler testing scenarios, our fuzzy oracle demonstrates superior performance in complex environments. The proposed approach shows promise in addressing the oracle problem for RL testing, particularly in complex cases where manual testing falls short. It offers a potential solution to improve the efficiency, reliability, and scalability of RL program testing. This research takes a step towards automated testing of RL programs and highlights the potential of fuzzy logic-based oracles in tackling the oracle problem.

cs.SE↗

arXiv2024

Regularizing property of the twisted conical Kähler-Ricci flow

In this paper, we show the regularity and uniqueness of the twisted conical Kähler-Ricci flow running from a positive closed current with zero Lelong number, which extends the regularizing property of the smooth twisted Kähler-Ricci flow, known as Guedj-Zeriahi's existence theorem and Di Nezza-Lu's uniqueness theorem, to the conical singularity case.

math.CV↗

arXiv2024

Distribution and Properties of Molecular Gas Toward the Monoceros OB1 Region

We perform a comprehensive CO study toward the Monoceros OB1 (Mon OB1) region based on the MWISP survey at an angular resolution of about $50''$. The high-sensitivity data, together with the high dynamic range, shows that molecular gas in the $\rm 8^{\circ}\times4^{\circ}$ region displays complicated hierarchical structures and various morphology (e.g., filamentary, cavity-like, shell-like, and other irregular structures). Based on Gaussian decomposition and clustering for $\mathrm{^{13}CO}$ data, a total of 263 $\mathrm{^{13}CO}$ structures are identified in the whole region, and 88% of raw data flux is recovered. The dense gas with relatively high column density from the integrated CO emission is mainly concentrated in the region where multiple $\rm ^{13}CO$ structures are overlapped. Combining the results of 32 large $\mathrm{^{13}CO}$ structures with distances from Gaia DR3, we estimate an average distance of $\rm 729^{+45}_{-45}~pc$ for the GMC complex. The total mass of the GMC Complex traced by $\mathrm{^{12}CO}$, $\mathrm{^{13}CO}$, and $\mathrm{C^{18}O}$ are $1.1\times10^5~M_\odot$, $4.3\times10^4~M_\odot$, and $8.4\times10^3~M_\odot$, respectively. The dense gas fraction shows a clear difference between Mon OB1 GMC East (12.4%) and Mon OB1 GMC West (3.3%). Our results show that the dense gas environment is closely linked to the nearby star-forming regions. On the other hand, star-forming activities have a great influence on the physical properties of the surrounding molecular gas (e.g., greater velocity dispersion, higher temperatures, and more complex velocity structures, etc.). We also discuss the distribution/kinematics of molecular gas associated with nearby star-forming activities.

astro-ph.GA↗

arXiv2024

The Multilayer Nature of Molecular Gas toward the Cygnus Region

We study the physical properties and 3D distribution of molecular clouds (MCs) toward the Cygnus region using the MWISP CO survey and Gaia DR3 data. Based on Gaussian decomposition and clustering for $\rm ^{13}CO$ lines, over 70% of the fluxes are recovered. With the identification result of $\rm ^{13}CO$ structures, two models are designed to measure the distances of the molecular gas in velocity crowding regions. The distances of more than 200 large $\rm ^{13}CO$ structures are obtained toward the 150 square degree region. Additionally, tens of the identified MC structures coincide well with masers and/or intense mid-IR emission. We find multiple gas layers toward the region: (1) the extensive gas structures composing the Cygnus Rift from 700 pc to 1 kpc across the whole region; (2) the $\sim$ 1.3 kpc gas layer mainly in the Cygnus X South region; and (3) the 1.5 kpc dense filament at the Cygnus X North region and many cometary clouds shaped by Cygnus OB2. We also note that the spatial distribution of YSO candidates is generally consistent with the molecular gas structures. The total molecular mass of the Cygnus region is estimated to be $\sim 2.7\times10^{6}~M_{\odot}$ assuming an X-factor ratio $X_{\rm CO} = 2 \times 10^{20} \rm cm^{-2} (K\cdot km\cdot s^{-1})^{-1}$. The foreground Cygnus Rift contributes $\sim$25% of the molecular mass in the whole region. Our work presents a new 3D view of the MCs' distribution toward the Cygnus X region, as well as the exact molecular gas mass distribution in the foreground Cygnus Rift.

astro-ph.GA↗

arXiv2024

Large-field CO (J=1-0) observations toward SNR G150.3+4.5

Aims. We aim to investigate the molecular environment of the supernova remnant (SNR) G150.3+4.5, and explore its association with ambient molecular clouds (MCs). Methods. We present large-field CO (J=1-0) molecular line observations toward SNR G150.3+4.5, using the 13.7 m millimeter telescope of the Purple Mountain Observatory. The observations have an angular resolution of $\sim 55 ''$. We analyzed the spatial distribution of MCs in relation to the SNR shell detected in previous Urumqi $λ$ 6 cm radio observations and examined the CO spectra for kinematics information. Results. We find that MCs at the velocity range of [-14, -2] km s$^{-1}$ are spatially distributed along the radio shell of the SNR. Line broadening and asymmetries are observed in the CO spectra of the clouds. Moreover, we find that the molecular clouds around the shell have systematic velocity gradients in the position-velocity (PV) diagrams. Both morphology alignment and gas kinematics suggest that the SNR is associated with the ambient MCs at $\sim$ 740 pc. Based on the CO gas distance, the dimension and the age of the SNR is estimated to be 40 pc $\times$ 33 pc and 3.8 $ \times 10^4$ years, respectively. The very high energy emission of 1LHAASO J0428+5531 toward the SNR may originate from the interaction between the SNR and the surrounding MCs.

astro-ph.GA↗

arXiv2023

Cloud-cloud collision in S235: triggered the formation of high-mass stars and young star clusters

We present the analysis of cloud-cloud collision (CCC) process in the Galactic molecular complex S235. Our new CO observations performed with the PMO-13.7m telescope reveal two molecular clouds, namely the S235-Main and the S235-ABC, with $\sim$ 4 km s$^{-1}$ velocity separation. The bridge feature, the possible colliding interface and the complementary distribution of the two clouds are significant observational signatures of cloud-cloud collision in S235. The most direct evidence of cloud-cloud collision process in S235 is that the S235-Main (in a distance of 1547$^{+44}_{-43}$ pc) and S235-ABC (1567$^{+33}_{-39}$ pc) meet at almost the same position (within 1$σ$ error range) at a supersonic relative speed. We identified ten $^{13}$CO clumps from PMO-13.7m observations, 22 dust cores from the archival SCUBA-2 data, and 550 YSOs from NIR-MIR data. 63$\%$ of total YSOs are clustering in seven MST groups (M1$-$M7). The tight association between the YSO groups (M1 $\&$ M7) and the bridge feature suggests that the CCC process triggers star formation there. The collisional impact subregion (the South) shows $3\sim5$ times higher CFE and SFE (average value of 12.3$\%$ and 10.6$\%$, respectively) than the non-collisional impact subregion (2.4$\%$ and 2.6$\%$, respectively), suggesting that the CCC process may have enhanced the CFE and SFE of the clouds compared to those without collision influence.

astro-ph.GA↗

arXiv2023

Explore the difficulty of words and its influential attributes based on the Wordle game

We adopt the distribution and expectation of guessing times in game Wordle as metrics to predict the difficulty of words and explore their influence factors. In order to predictthe difficulty distribution, we use Monte Carlo to simulate the guessing process of players and then narrow the gap between raw and actual distribution of guessing times for each word with Markov which generates the associativity of words. Afterwards, we take advantage of lasso regression to predict the deviation of guessing times expectation and quadratic programming to obtain the correction of the original distribution.To predict the difficulty levels, we first use hierarchical clustering to classify the difficulty levels based on the expectation of guessing times. Afterwards we downscale the variables of lexical attributes based on factor analysis. Significant factors include the number of neighboring words, letter similarity, sub-string similarity, and word frequency. Finally, we build the relationship between lexical attributes and difficulty levels through ordered logistic regression.

cs.CL↗

arXiv2023

See Your Heart: Psychological states Interpretation through Visual Creations

In psychoanalysis, generating interpretations to one's psychological state through visual creations is facing significant demands. The two main tasks of existing studies in the field of computer vision, sentiment/emotion classification and affective captioning, can hardly satisfy the requirement of psychological interpreting. To meet the demands for psychoanalysis, we introduce a challenging task, \textbf{V}isual \textbf{E}motion \textbf{I}nterpretation \textbf{T}ask (VEIT). VEIT requires AI to generate reasonable interpretations of creator's psychological state through visual creations. To support the task, we present a multimodal dataset termed SpyIn (\textbf{S}and\textbf{p}la\textbf{y} \textbf{In}terpretation Dataset), which is psychological theory supported and professional annotated. Dataset analysis illustrates that SpyIn is not only able to support VEIT, but also more challenging compared with other captioning datasets. Building on SpyIn, we conduct experiments of several image captioning method, and propose a visual-semantic combined model which obtains a SOTA result on SpyIn. The results indicate that VEIT is a more challenging task requiring scene graph information and psychological knowledge. Our work also show a promise for AI to analyze and explain inner world of humanity through visual creations.

cs.CV↗

arXiv2022

The Cassiopeia Filament: A Blown Spur of the Local Arm

We present wide-field and high-sensitivity CO(1-0) molecular line observations toward the Cassiopeia region, using the 13.7m millimeter telescope of the Purple Mountain Observatory (PMO). The CO observations reveal a large-scale highly filamentary molecular cloud within the Galactic region of 132\fdg0\,$\geq$\,$l$\,$\geq$\,122\fdg0 and -1\fdg0\,$\leq$\,$b$\,$\leq$\,3\fdg0 and the velocity range from approximately +1 to +4 km/s. The measured length of the large-scale filament, referred to as the Cassiopeia Filament, is about 390 pc. The observed properties of the Cassiopeia Filament, such as length, column density, and velocity gradient, are consistent with those synthetic large-scale filaments in the inter-arm regions. Based on its observed properties and location on the Galactic plane, we suggest that the Cassiopeia Filament is a spur of the Local arm, which is formed due to the galactic shear. The western end of the Cassiopeia Filament shows a giant arc-like molecular gas shell, which is extending in the velocity range from roughly -1 to +7 km/s. Finger-like structures, with systematic velocity gradients, are detected in the shell. The CO kinematics suggest that the large shell is expanding at a velocity of ~6.5 km/s. Both the shell and finger-like structures outline a giant bubble with a radius of ~16 pc, which is likely produced by stellar wind from the progenitor star of a supernova remnant. The observed spectral linewidths suggest that the whole Cassiopeia Filament was quiescent initially until its west part was blown by stellar wind and became supersonically turbulent.

astro-ph.GA↗

arXiv2022

Ensemble learning priors unfolding for scalable Snapshot Compressive Sensing

Snapshot compressive imaging (SCI) can record the 3D information by a 2D measurement and from this 2D measurement to reconstruct the original 3D information by reconstruction algorithm. As we can see, the reconstruction algorithm plays a vital role in SCI. Recently, deep learning algorithm show its outstanding ability, outperforming the traditional algorithm. Therefore, to improve deep learning algorithm reconstruction accuracy is an inevitable topic for SCI. Besides, deep learning algorithms are usually limited by scalability, and a well trained model in general can not be applied to new systems if lacking the new training process. To address these problems, we develop the ensemble learning priors to further improve the reconstruction accuracy and propose the scalable learning to empower deep learning the scalability just like the traditional algorithm. What's more, our algorithm has achieved the state-of-the-art results, outperforming existing algorithms. Extensive results on both simulation and real datasets demonstrate the superiority of our proposed algorithm. The code and models will be released to the public.

eess.IV↗

arXiv2022

CO(J = 1-0) Observations toward the Filamentary Cloud in the Galactic Region of $153.60^{\circ} \leqslant l \leqslant 156.50^{\circ}$ and $1.85^{\circ} \leqslant b \leqslant 3.50^{\circ}$

We present observations of $J$=1-0 transition lines of ${ }^{12} \mathrm{CO}$, ${ }^{13} \mathrm{CO}$, and $\mathrm{C}^{18} \mathrm{O}$ towards the Galactic region of $153.60^{\circ} \leqslant l \leqslant 156.50^{\circ}$ and $1.85^{\circ} \leqslant b \leqslant 3.50^{\circ}$, using the Purple Mountain Observatory (PMO) 13.7 m millimeter telescope. Based on the \tht data, one main filament and five sub-filaments are found together as a network structure in the velocity interval of $[-42.5, -30.0] \,\mathrm{km} \mathrm{\,s}^{-1}$. The kinematic distance of this molecular cloud (MC) is estimated to be $\sim4.5 \mathrm{\,kpc}$. The median length, width, excitation temperature, line mass of these filaments are $\sim49 \mathrm{\,pc}$, $\sim2.9 \mathrm{\,pc}$, $\sim8.9 \mathrm{\,K}$, and $\sim39 \,M_{\odot} \mathrm{pc}^{-1}$, respectively. The velocity structures along these filaments exhibit oscillatory patterns, which are likely caused by the fragmentation or accretion process along these filaments. The maximum accretion rate is estimated to be as high as $\sim700 \,M_{\odot} \mathrm{pc}^{-1}$. A total of $\sim162$ \tht clumps and $\sim 103$ young stellar objects (YSOs) are identified in this region. Most of the clumps are in gravitationally bound states. Three \hii regions (G154.359+2.606, SH2-211, SH2-212) are found to be located in the apexes of the filaments. Intense star forming activities are found along the entire filamentary cloud. The observed results may help us to better understand the link between filaments and massive star formation.

astro-ph.GA↗

arXiv2022

Geographic Spillover Effects of Prescription Drug Monitoring Programs (PDMPs)

Prescription Drug Monitoring Programs (PDMPs) seek to potentially reduce opioid misuse by restricting the sale of opioids in a state. We examine discontinuities along state borders, where one side may have a PDMP and the other side may not. We find that electronic PDMP implementation, whereby doctors and pharmacists can observe a patient's opioid purchase history, reduces a state's opioid sales but increases opioid sales in neighboring counties on the other side of the state border. We also find systematic differences in opioid sales and mortality between border counties and interior counties. These differences decrease when neighboring states both have ePDMPs, which is consistent with the hypothesis that individuals cross state lines to purchase opioids. Our work highlights the importance of understanding the opioid market as connected across counties or states, as we show that states are affected by the opioid policies of their neighbors.

econ.GN↗

arXiv2022

TENET: Transformer Encoding Network for Effective Temporal Flow on Motion Prediction

This technical report presents an effective method for motion prediction in autonomous driving. We develop a Transformer-based method for input encoding and trajectory prediction. Besides, we propose the Temporal Flow Header to enhance the trajectory encoding. In the end, an efficient K-means ensemble method is used. Using our Transformer network and ensemble method, we win the first place of Argoverse 2 Motion Forecasting Challenge with the state-of-the-art brier-minFDE score of 1.90.

cs.CV↗

arXiv2022

CO Emission Delineating the Interface between the Milky Way Nuclear Wind Cavity and the Gaseous Disk

Based on the MWISP survey, we study high-z CO emission toward the tangent points, in which the distances of the molecular clouds (MCs) are well determined. In the region of l=12-26 deg and |b|<5.1 deg, a total of 321 MCs with |z|> 110 pc are identified, of which nearly 30 extreme high-z MCs (EHMCs at |z|> 260 pc) are concentrated in a narrow region of R_GC=2.6-3.1 kpc. The EHMC concentrations, together with other high-z MCs at R_GC=2.3-2.6 kpc, constitute molecular crater-wall structures surrounding the edges of the HI voids that are physically associated with the Fermi bubbles. Intriguingly, some large high-z MCs, which lie in the crater walls above and below the Galactic plane, show cometary structures with the head toward the plane, favouring the scenario that the entrained molecular gas moves with the multi-phase flows from the plane to the high-z regions. We suggest that the Milky Way nuclear wind has a significant impact on the Galactic gaseous disk. The powerful nuclear wind at ~3-6 Myr ago is likely responsible for the observational features, (1) the enhanced CO gas lying in the edges of the HI voids, (2) the deficiency of atomic and molecular gas within R_GC<3 kpc, (3) the possible connection between the EHMC concentrations and the 3-kpc arm, and (4) the elongated high-z MCs with the tail pointing away from the Galactic plane.

astro-ph.GA↗

arXiv2021

DetectorNet: Transformer-enhanced Spatial Temporal Graph Neural Network for Traffic Prediction

Detectors with high coverage have direct and far-reaching benefits for road users in route planning and avoiding traffic congestion, but utilizing these data presents unique challenges including: the dynamic temporal correlation, and the dynamic spatial correlation caused by changes in road conditions. Although the existing work considers the significance of modeling with spatial-temporal correlation, what it has learned is still a static road network structure, which cannot reflect the dynamic changes of roads, and eventually loses much valuable potential information. To address these challenges, we propose DetectorNet enhanced by Transformer. Differs from previous studies, our model contains a Multi-view Temporal Attention module and a Dynamic Attention module, which focus on the long-distance and short-distance temporal correlation, and dynamic spatial correlation by dynamically updating the learned knowledge respectively, so as to make accurate prediction. In addition, the experimental results on two public datasets and the comparison results of four ablation experiments proves that the performance of DetectorNet is better than the eleven advanced baselines.

cs.CV↗

arXiv2021

Large-Scale Multiple Testing for Matrix-Valued Data under Double Dependency

High-dimensional inference based on matrix-valued data has drawn increasing attention in modern statistical research, yet not much progress has been made in large-scale multiple testing specifically designed for analysing such data sets. Motivated by this, we consider in this article an electroencephalography (EEG) experiment that produces matrix-valued data and presents a scope of developing novel matrix-valued data based multiple testing methods controlling false discoveries for hypotheses that are of importance in such an experiment. The row-column cross-dependency of observations appearing in a matrix form, referred to as double-dependency, is one of the main challenges in the development of such methods. We address it by assuming matrix normal distribution for the observations at each of the independent matrix data-points. This allows us to fully capture the underlying double-dependency informed through the row- and column-covariance matrices and develop methods that are potentially more powerful than the corresponding one (e.g., Fan and Han (2017)) obtained by vectorizing each data point and thus ignoring the double-dependency. We propose two methods to approximate the false discovery proportion with statistical accuracy. While one of these methods is a general approach under double-dependency, the other one provides more computational efficiency for higher dimensionality. Extensive numerical studies illustrate the superior performance of the proposed methods over the principal factor approximation method of Fan and Han (2017). The proposed methods have been further applied to the aforementioned EEG data.

stat.ME↗

arXiv2021

The OxyContin Reformulation Revisited: New Evidence From Improved Definitions of Markets and Substitutes

The opioid epidemic began with prescription pain relievers. In 2010 Purdue Pharma reformulated OxyContin to make it more difficult to abuse. OxyContin misuse fell dramatically, and concurrently heroin deaths began to rise. Previous research overlooked generic oxycodone and argued that the reformulation induced OxyContin users to switch directly to heroin. Using a novel and fine-grained source of all oxycodone sales from 2006-2014, we show that the reformulation led users to substitute from OxyContin to generic oxycodone, and the reformulation had no overall impact on opioid or heroin mortality. In fact, generic oxycodone, instead of OxyContin, was the driving factor in the transition to heroin. Finally, we show that by omitting generic oxycodone we recover the results of the literature. These findings highlight the important role generic oxycodone played in the opioid epidemic and the limited effectiveness of a partial supply-side intervention.

econ.GN↗

arXiv2018

Continuous Trajectory Planning Based on Learning Optimization in High Dimensional Input Space for Serial Manipulators

To continuously generate trajectories for serial manipulators with high dimensional degrees of freedom (DOF) in the dynamic environment, a real-time optimal trajectory generation method based on machine learning aiming at high dimensional inputs is presented in this paper. First, a learning optimization (LO) framework is established, and implementations with different sub-methods are discussed. Additionally, multiple criteria are defined to evaluate the performance of LO models. Furthermore, aiming at high dimensional inputs, a database generation method based on input space dimension-reducing mapping is proposed. At last, this method is validated on motion planning for haptic feedback manipulators (HFM) in virtual reality systems. Results show that the input space dimension-reducing method can significantly elevate the efficiency and quality of database generation and consequently improve the performance of the LO. Moreover, using this LO method, real-time trajectory generation with high dimensional inputs can be achieved, which lays a foundation for continuous trajectory planning for high-DOF-robots in complex environments.

cs.RO↗