In this study, we present an operator splitting method (OSM) for the Cahn？Hilliard (CH) equation on a nonuniform mesh.

We consider the global existence and regularity of the solution to the stage-structured SIR system for rumor spreading. To obtain the local existence result of a weak solution to the system, we reduce the system to a single equation using the SIR structure and employ a fixed point argument with a Banach space and Volterra’s formula.

In this paper, we show that two compact CLAS schemes, Zhan et al.’s scheme and Chen-Chen’s scheme, are insecure against universal forgery attacks and type I attacks. Analyzing the design methodology and vulnerabilities against the attacks on the two compact CLAS schemes, we propose countermeasures to prevent the attacks.

Multivariate quadratic equation-based cryptographic algorithms are one of the promising post-quantum alternatives to current public-key cryptographic algorithms based on the discrete logarithm problem and the integer factorization problem. In this paper, we provide advanced security analysis of UOV, a well-known signature scheme based on the multivariate quadratic equations, when Vinegar values are reused in signing for efficiency.

This paper describes the mathematical structure of the ill-posed nonlinear inverse problem of low-dose dental cone-beam computed tomography (CBCT) and explains the advantages of a deep learning-based approach to the reconstruction of computed tomography images over conventional regularization methods.

This paper presents a fully automatic registration method of dental cone-beam computed tomography (CBCT) and face scan data. Difficulties in accurately merging facial scans and CBCT images arise from the different image acquisition methods and limited area of correspondence between the two facial surfaces.

In this work, we show that Wang et al.’s scheme is broken by key recovery attacks: anyone can recover the entire private keys of any users. We then propose a new secure CLS scheme and prove its unforgeability against type I and type II adversaries under the hardness assumption of the Elliptic Curve Diffie-Hellman problem.

In this work, we evaluate the post-quantum signature schemes in terms of various metrics, performance, signature/key sizes, energy consumption, resistance to implementation attacks and adaptability to Internet protocols. We then investigate their suitability for Internet of Things based on these metrics.

Commonly deep learning methods for enhancing the quality of medical images use unpaired dataset due to the impracticality of acquiring paired dataset through commercial imaging system. In this paper, we propose a supervised learning method to enhance the quality of ultrasound images.

In this paper, we present a unified spatio-temporal attention MixFormer framework for visual object tracking. Within the vision transformer framework, we design a cohesive network consisting of target template and search region feature extraction, cross-attention utilizing spatial and temporal information, and task-specific heads, all operating in an end-to-end manner.