Spectrum Focused Frequency Adversarial Attacks for Automatic Modulation Classification

Artificial intelligence (AI) technology has provided a potential solution for automatic modulation recognition (AMC). Unfortunately, AI-based AMC models are vulnerable to adversarial examples, which seriously threatens the efficient, secure and trusted application of AI in AMC. This issue has attracted the attention of researchers. Various studies on adversarial attacks and defenses evolve in a spiral. However, the existing adversarial attack methods are all designed in the time domain. They introduce more high-frequency components in the frequency domain, due to abrupt updates in the time domain. For this issue, from the perspective of frequency domain, we propose a spectrum focused frequency adversarial attacks (SFFAA) for AMC model, and further draw on the idea of meta-learning, propose a Meta-SFFAA algorithm to improve the transferability in the black-box attacks. Extensive experiments, qualitative and quantitative metrics demonstrate that the proposed algorithm can concentrate the adversarial energy on the spectrum where the signal is located, significantly improve the adversarial attack performance while maintaining the concealment in the frequency domain.Comment: 6 pages, 9 figure

Optical Nondestructive Controlled-NOT Gate without Using Entangled Photons

We present and experimentally demonstrate a novel optical nondestructive controlled-NOT gate without using entangled ancilla. With much fewer measurements compared with quantum process tomography, we get a good estimation of the gate fidelity. The result shows a great improvement compared with previous experiments. Moreover, we also show that quantum parallelism is achieved in our gate and the performance of the gate can not be reproduced by local operations and classical communications.Comment: 5 pages, 3 figures, Slight changes have been made, Journal-ref adde

The prediction of structural fractures in coal seams of the Kuba coalfield, China: an application for coalbed methane (CBM) recovery development

The structural fracture system in a coal reservoir enables coalbed methane (CBM) percolation and migration. It plays an important role in CBM exploration and exploitation (recovery) development. Nearly vertical strata with Mesozoic bituminous coal seams in the central part of the Kuba coalfield of the Xinjiang Province in China were studied using large-scale mapping of the structural fractures on the surface, and a using a technique for comparing and analyzing sections of the underground coal mine. This investigation verified that similar structural fractures are developed in the underground coal seams as those on the surface,  , and surrounding rocks represent the same tectonic layer. Meanwhile, a corresponding relationship between the characteristics of the development of fractures - including the growth directions and degree of development of fractures in coal seams and the surrounding rocks - was established. Based on this, the research presents a new method for predicting a pattern of fractures in coal seams and the coal structure, respectively. Finally, the study area was divided into zones with dense, moderate and un-developed fractures. The method should be applicable in various coal-and-gas engineering fields,  for example the prediction of fractured zones in coal seams,  the prediction of coal structure, and for projecting the well arrangement in the exploration and development of economic recovery of CBM.</p

1,3,5,7-Tetra­bromo­adamantane

In the pyramidal-shaped mol­ecule of the title compound, C10H12Br4, the four terminal Br—C bond distances are nearly identical, ranging from 1.964 (4) to 1.974 (4) Å. The Br⋯Br distance of 3.6553 (7) Å indicates van der Waals contacts between mol­ecules in the crystal structure