A Tamed Transformation Method (TTM) cryptosystem was proposed by T.T.Moh in 1999. We describe how the first implementation scheme of the TTM system can be defeated. The computational complexity of our attack is 2^{33} computations on the finite field with 2^8 elements.

We analyze the torus fixed loci of Mixed Spin P fields moduli, and deduce its localization formulas with explicit factors. An algorithm toward evaluating quintic's Gromov-Witten and Fan-Jarvis-Ruan-Witten invariants is derived.

We study how to characterize the families of paths between any two nodes s, t in a sensor network with holes. Two paths that can be deformed to one another through local changes are called homotopy equivalent. Two paths that pass around holes in different ways have different homotopy types. With a distributed algorithm we compute an embedding of the network in hyperbolic space by using Ricci flow such that paths of different homotopy types are mapped naturally to paths connecting s with different images of t. Greedy routing to a particular image is guaranteed with success to find a path with a given homotopy type. This leads to simple greedy routing algorithms that are resilient to both local link dynamics and large scale jamming attacks and improve load balancing over previous greedy routing algorithms.

We investigate so-called Laplace–Carleson embeddings for large exponents. In particular, we extend some results by Jacob, Partington, and Pott. We also discuss some related results for Sobolev– and Besov spaces, and mapping properties of the Fourier transform. These variants of the Hausdorff–Young theorem appear difficult to find in the literature. We conclude the paper with an example related to an open problem.

Non-line-of-sight (NLOS) imaging enables people to see a hidden scene based on multiple interaction information between the object and the carrier. There have been numerous studies focusing on the physical modeling of photon scattering, but few have explored the detection process, which also plays a vital role. In this paper, we put forward a novel, to the best of our knowledge, detection methodology for NLOS imaging based on time-sequential first photon (TSFP) data. We verify the method with both synthetic and experimental data, showing a dramatic reduction in acquisition time cost compared with traditional methods for the same reconstruction quality. This work may contribute to real-time and photon-starved NLOS imaging for practical applications.