arXiv subjects

Pengcheng Zhao

Publications and source records attributed to Pengcheng Zhao.

31 records · Page 2Linked to original sources

arXiv2024

QTG-VQA: Question-Type-Guided Architectural for VideoQA Systems

In the domain of video question answering (VideoQA), the impact of question types on VQA systems, despite its critical importance, has been relatively under-explored to date. However, the richness of question types directly determines the range of concepts a model needs to learn, thereby affecting the upper limit of its learning capability. This paper focuses on exploring the significance of different question types for VQA systems and their impact on performance, revealing a series of issues such as insufficient learning and model degradation due to uneven distribution of question types. Particularly, considering the significant variation in dependency on temporal information across different question types, and given that the representation of such information coincidentally represents a principal challenge and difficulty for VideoQA as opposed to ImageQA. To address these challenges, we propose QTG-VQA, a novel architecture that incorporates question-type-guided attention and adaptive learning mechanism. Specifically, as to temporal-type questions, we design Masking Frame Modeling technique to enhance temporal modeling, aimed at encouraging the model to grasp richer visual-language relationships and manage more intricate temporal dependencies. Furthermore, a novel evaluation metric tailored to question types is introduced. Experimental results confirm the effectiveness of our approach.

cs.CV↗

arXiv2024

WeatherReal: A Benchmark Based on In-Situ Observations for Evaluating Weather Models

In recent years, AI-based weather forecasting models have matched or even outperformed numerical weather prediction systems. However, most of these models have been trained and evaluated on reanalysis datasets like ERA5. These datasets, being products of numerical models, often diverge substantially from actual observations in some crucial variables like near-surface temperature, wind, precipitation and clouds - parameters that hold significant public interest. To address this divergence, we introduce WeatherReal, a novel benchmark dataset for weather forecasting, derived from global near-surface in-situ observations. WeatherReal also features a publicly accessible quality control and evaluation framework. This paper details the sources and processing methodologies underlying the dataset, and further illustrates the advantage of in-situ observations in capturing hyper-local and extreme weather through comparative analyses and case studies. Using WeatherReal, we evaluated several data-driven models and compared them with leading numerical models. Our work aims to advance the AI-based weather forecasting research towards a more application-focused and operation-ready approach.

physics.ao-ph↗

arXiv2024

Anomalous Raman Response in 2D Magnetic FeTe under Uniaxial Strain: Tetragonal and Hexagonal Polymorphs

Two-dimensional (2D) Fe-chalcogenides have emerged with rich structures, magnetisms and superconductivities, which sparked the growing research interests in the torturous transition mechanism and tunable properties for their potential applications in nanoelectronics. Uniaxial strain can produce a lattice distortion to study symmetry breaking induced exotic properties in 2D magnets. Herein, the anomalous Raman spectrum of 2D tetragonal (t-) and hexagonal (h-) FeTe were systematically investigated via uniaxial strain engineering strategy. We found that both t- and h-FeTe keep the structural stability under different uniaxial tensile or compressive strain up to +/- 0.4%. Intriguingly, the lattice vibrations along both in-plane and out-of-plane directions exceptionally hardened (softened) under tensile (compressive) strain, distinguished from the behaviors of many conventional 2D systems. Furthermore, the difference in thickness-dependent strain effect can be well explained by their structural discrepancy between two polymorphs of FeTe. Our results could provide a unique platform to elaborate the vibrational properties of many novel 2D materials.

cond-mat.mtrl-sci↗

arXiv2023

Momentum space oscillation properties of vortex states collision

A qualitative calculation and discussion of two vortex states collisions are given in the scalar $ϕ^4$ model. Three kinds of vortex states -- Bessel, general monochromatic, and Laguerre-Gaussian vortex states -- are considered. It is found that the total final momentum distribution in collision of physical vortex states displays general topological structures, which depend on the initial vortex states' topological charges, which are proportional to the orbital angular momenta. This peculiar matching provides a novel observable, the topological number of momentum distribution, and it may represent a new fascinating research direction in particle physics. We also find that the situation when the angular momenta of the two colliding Laguerre-Gaussian states combine to zero can be recognized by the total final momentum distribution close to the collision axis. Both features can be used to measure the orbital angular momentum of vortex states.

hep-ph↗

arXiv2023

Spinal nerve segmentation method and dataset construction in endoscopic surgical scenarios

Endoscopic surgery is currently an important treatment method in the field of spinal surgery and avoiding damage to the spinal nerves through video guidance is a key challenge. This paper presents the first real-time segmentation method for spinal nerves in endoscopic surgery, which provides crucial navigational information for surgeons. A finely annotated segmentation dataset of approximately 10,000 consec-utive frames recorded during surgery is constructed for the first time for this field, addressing the problem of semantic segmentation. Based on this dataset, we propose FUnet (Frame-Unet), which achieves state-of-the-art performance by utilizing inter-frame information and self-attention mechanisms. We also conduct extended exper-iments on a similar polyp endoscopy video dataset and show that the model has good generalization ability with advantageous performance. The dataset and code of this work are presented at: https://github.com/zzzzzzpc/FUnet .

cs.CV↗

arXiv2022

$Z_n$ symmetry in the vortex muon decay

Polarization of a vortex state fermion has rich structure due to the nontrivial momentum distribution of wave function. This larger freedom provides an unique opportunity to prepare fermions in exotic polarized states, which do not exist for plane-wave state fermions. Based on the so called spin-orbit state which was studied both theoretically and experimentally, we put forward a peculiar vortex muon whose polarization exhibits $Z_n$ symmetry and study its decay. We investigate the azimuthal distribution of the emitted electrons and find that it exhibits the same symmetry ($Z_n$) as the initial state.

hep-ph↗

arXiv2021

Svar: A Tiny C++ Header Brings Unified Interface for Multiple programming Languages

There are numerous types of programming languages developed in the last decades, and most of them provide interface to call C++ or C for high efficiency implementation. The motivation of Svar is to design an efficient, light-weighted and general middle-ware for multiple languages, meanwhile, brings the dynamism features from script language to C++ in a straightforward way. Firstly, a Svar class with JSON like data structure is designed to hold everything exists in C++, including basic values, functions or user defined classes and objects. Secondly, arguments are auto cast to and from Svar efficiently with compile time pointers, references and shared\_ptr detection. Thirdly, classes and functions are binded with string names to support reflection, this means all functions and classes in a shared library can be exported to a Svar object, which also calls a Svar module. The Svar modules can be accessed by different languages and this paper demonstrates how to import and use a Svar module in Python and Node.js. Moreover, the Svar modules or even a python module can also be imported by C++ at runtime, which makes C++ easier to compile and use since headers are not required anymore. We compare the performance of Svar with two state-of-the-art binding tool for Python and Node.js, and the result demonstrates that Svar is efficient, elegant and general. The core of this project is one single tiny modern C++ header with less than 5000 lines code without extra dependency. To help developers using Svar, all the source codes related are public available on http://github.com/zdzhaoyong/Svar, including documentations and benchmarks.

cs.PL↗

arXiv2020

Spatial Mode Correction of Single Photons using Machine Learning

Spatial modes of light constitute valuable resources for a variety of quantum technologies ranging from quantum communication and quantum imaging to remote sensing. Nevertheless, their vulnerabilities to phase distortions, induced by random media, impose significant limitations on the realistic implementation of numerous quantum-photonic technologies. Unfortunately, this problem is exacerbated at the single-photon level. Over the last two decades, this challenging problem has been tackled through conventional schemes that utilize optical nonlinearities, quantum correlations, and adaptive optics. In this article, we exploit the self-learning and self-evolving features of artificial neural networks to correct the complex spatial profile of distorted Laguerre-Gaussian modes at the single-photon level. Furthermore, we demonstrate the possibility of boosting the performance of an optical communication protocol through the spatial mode correction of single photons using machine learning. Our results have important implications for real-time turbulence correction of structured photons and single-photon images.

quant-ph↗

arXiv2020

Safe, Optimal, Real-time Trajectory Planning with a Parallel Constrained Bernstein Algorithm

To move through the world, mobile robots typically use a receding-horizon strategy, wherein they execute an old plan while computing a new plan to incorporate new sensor information. A plan should be dynamically feasible, meaning it obeys constraints like the robot's dynamics and obstacle avoidance; it should have liveness, meaning the robot does not stop to plan so frequently that it cannot accomplish tasks; and it should be optimal, meaning that the robot tries to satisfy a user-specified cost function such as reaching a goal location as quickly as possible. Reachability-based Trajectory Design (RTD) is a planning method that can generate provably dynamically-feasible plans. However, RTD solves a nonlinear polynmial optimization program at each planning iteration, preventing optimality guarantees; furthermore, RTD can struggle with liveness because the robot must brake to a stop when the solver finds local minima or cannot find a feasible solution. This paper proposes RTD*, which certifiably finds the globally optimal plan (if such a plan exists) at each planning iteration. This method is enabled by a novel Parallelized Constrained Bernstein Algorithm (PCBA), which is a branch-and-bound method for polynomial optimization. The contributions of this paper are: the implementation of PCBA; proofs of bounds on the time and memory usage of PCBA; a comparison of PCBA to state of the art solvers; and the demonstration of PCBA/RTD* on a mobile robot. RTD* outperforms RTD in terms of optimality and liveness for real-time planning in a variety of environments with randomly-placed obstacles.

math.OC↗

arXiv2019

Leveraging the Template and Anchor Framework for Safe, Online Robotic Gait Design

Online control design using a high-fidelity, full-order model for a bipedal robot can be challenging due to the size of the state space of the model. A commonly adopted solution to overcome this challenge is to approximate the full-order model (anchor) with a simplified, reduced-order model (template), while performing control synthesis. Unfortunately it is challenging to make formal guarantees about the safety of an anchor model using a controller designed in an online fashion using a template model. To address this problem, this paper proposes a method to generate safety-preserving controllers for anchor models by performing reachability analysis on template models while bounding the modeling error. This paper describes how this reachable set can be incorporated into a Model Predictive Control framework to select controllers that result in safe walking on the anchor model in an online fashion. The method is illustrated on a 5-link RABBIT model, and is shown to allow the robot to walk safely while utilizing controllers designed in an online fashion.

cs.RO↗

arXiv2018

Optimal Control for Nonlinear Hybrid Systems via Convex Relaxations

This paper considers the optimal control for hybrid systems whose trajectories transition between distinct subsystems when state-dependent constraints are satisfied. Though this class of systems is useful while modeling a variety of physical systems undergoing contact, the construction of a numerical method for their optimal control has proven challenging due to the combinatorial nature of the state-dependent switching and the potential discontinuities that arise during switches. This paper constructs a convex relaxation-based approach to solve this optimal control problem. Our approach begins by formulating the problem in the space of relaxed controls, which gives rise to a linear program whose solution is proven to compute the globally optimal controller. This conceptual program is solved by constructing a sequence of semidefinite programs whose solutions are proven to converge from below to the true solution of the original optimal control problem. Finally, a method to synthesize the optimal controller is developed. Using an array of examples, the performance of the proposed method is validated on problems with known solutions and also compared to a commercial solver.

math.OC↗

arXiv2017

Control Synthesis for Nonlinear Optimal Control via Convex Relaxations

This paper addresses the problem of control synthesis for nonlinear optimal control problems in the presence of state and input constraints. The presented approach relies upon transforming the given problem into an infinite-dimensional linear program over the space of measures. To generate approximations to this infinite-dimensional program, a sequence of Semi-Definite Programs (SDP)s is formulated in the instance of polynomial cost and dynamics with semi-algebraic state and bounded input constraints. A method to extract a polynomial control function from each SDP is also given. This paper proves that the controller synthesized from each of these SDPs generates a sequence of values that converge from below to the value of the optimal control of the original optimal control problem. In contrast to existing approaches, the presented method does not assume that the optimal control is continuous while still proving that the sequence of approximations is optimal. Moreover, the sequence of controllers that are synthesized using the presented approach are proven to converge to the true optimal control. The performance of the presented method is demonstrated on three examples.

math.OC↗

arXiv2016

Recovery rate affects the effective epidemic threshold with synchronous updating

Accurate identification of effective epidemic threshold is essential for understanding epidemic dynamics on complex networks. The existing studies on the effective epidemic threshold of the susceptible-infected-removed (SIR) model generally assume that all infected nodes immediately recover after the infection process, which more or less does not conform to the realistic situation of disease. In this paper, we systematically study the effect of arbitrary recovery rate on the SIR spreading dynamics on complex networks. We derive the theoretical effective epidemic threshold and final outbreak size based on the edge-based compartmental theory. To validate the proposed theoretical predictions, extensive numerical experiments are implemented by using asynchronous and synchronous updating methods. When asynchronous updating method is used in simulations, recovery rate does not affect the final state of spreading dynamics. But with synchronous updating, we find that the effective epidemic threshold decreases with recovery rate, and final outbreak size increases with recovery rate. A good agreement between the theoretical predictions and numerical results are observed on both synthetic and real-world networks. Our results extend the existing theoretical studies, and help us to understand the phase transition with arbitrary recovery rate.

physics.soc-ph↗