In this paper, we propose a sampling algorithm based on state-of-the-art statistical machine learning techniques to obtain conditional nonlinear optimal perturbations (CNOPs), which is different from traditional (dete...
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In this paper, a diffuse-interface lattice Boltzmann method (DI-LBM) is developed for fluid-particle interaction problems. In this method, the sharp interface between the fluid and solid is replaced by a thin but nonz...
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A novel class of stabilized multiple-relaxation implicit-explicit Runge–Kutta methods is proposed for solving nonlinear Gross–Pitaevskii equations. The methods conserve the mass and the energy simultaneously in the ...
A novel class of stabilized multiple-relaxation implicit-explicit Runge–Kutta methods is proposed for solving nonlinear Gross–Pitaevskii equations. The methods conserve the mass and the energy simultaneously in the discrete sense, and achieve arbitrarily high-order accuracy in the temporal direction. Additionally, there are several highlights in this study. Firstly, this is the first attempt to apply the stabilization approach to develop relaxation-type schemes, which effectively avoids the blow-up of the relaxation parameters due to the nonlinearity and stiffness of the problems. Secondly, the governing equations that determine the relaxation parameters are newly designed to conserve the original invariants, which can be extended to conserve more invariants of other physical models. Thirdly, the schemes are linearly implicit after obtaining the relaxation parameters, and thus are easy to implement. Several numerical experiments are carried out to confirm the effectiveness and theoretical results of the proposed methods.
Static analysis is often impeded by malware obfuscation techniques,such as encryption and packing,whereas dynamic analysis tends to be more resistant to obfuscation by leveraging concrete execution ***,malware can emp...
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Static analysis is often impeded by malware obfuscation techniques,such as encryption and packing,whereas dynamic analysis tends to be more resistant to obfuscation by leveraging concrete execution ***,malware can employ evasive techniques to detect the analysis environment and alter its behavior *** known evasive techniques can be explicitly dismantled,the challenge lies in generically dismantling evasions without full knowledge of their conditions or implementations,such as logic bombs that rely on uncertain conditions,let alone unsupported evasive techniques,which contain evasions without corresponding dismantling strategies and those leveraging unknown *** this paper,we present Antitoxin,a prototype for automatically exploring evasive *** utilizes multi-path exploration guided by taint analysis and probability calculations to effectively dismantle evasive *** probabilities of branch execution are derived from dynamic coverage,while taint analysis helps identify paths associated with evasive techniques that rely on uncertain ***,Antitoxin prioritizes branches with lower execution probabilities and those influenced by taint analysis for multi-path *** is achieved through forced execution,which forcefully sets the outcomes of branches on selected ***,Antitoxin employs active anti-evasion countermeasures to dismantle known evasive techniques,thereby reducing exploration ***,Antitoxin provides valuable insights into sensitive behaviors,facilitating deeper manual *** experiments on a set of highly evasive samples demonstrate that Antitoxin can effectively dismantle evasive techniques in a generic *** probability calculations guide the multi-path exploration of evasions without requiring prior knowledge of their conditions or implementations,enabling the dismantling of unsupported techniques such as C2 and signific
We utilize the weak convergence method to establish the Freidlin-Wentzell large deviations principle (LDP) for stochastic delay differential equations (SDDEs) with super-linearly growing coefficients, which covers a l...
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Predicting whether there are defects in code changes submitted by developers is called just-in-time software defect prediction (JIT-SDP). Unfortunately, JIT-SDP usually suffers from the class imbalance problem, which ...
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Point cloud completion, as the upstream procedure of 3D recognition and segmentation, has become an essential part of many tasks such as navigation and scene understanding. While various point cloud completion models ...
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Token dropping is a recently-proposed strategy to speed up the pretraining of masked language models, such as BERT, by skipping the computation of a subset of the input tokens at several middle layers. It can effectiv...
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Equilibrium states are natural dynamical analogs of Gibbs states in thermodynamic formalism. This paper is devoted to the study of their computability in the sense of Computable Analysis. We show that the unique equil...
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Objective: The current models of estimating vascular age (VA) primarily rely on the regression label expressed with chronological age (CA), which does not account individual differences in vascular aging (IDVA) that a...
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