The Application of Vague Language in International Business Negotiations from a Cross-cultural Perspective

in the environment of economic globalization, business negotiation becomes more and more frequent than ever. International business negotiation has a significant role in international business trade. There are many factors that can affect the negotiation, including language, culture, negotiators, and negotiation strategies. Language as an important tool plays a great role in the negotiation strategies. It is commonly held that precise language should be used in business negotiations in order to avoid misunderstanding. However, people ignore the fact that language itself is vague in essence. Negotiators unavoidably use vague language in business negotiations, for vague language can be used as a kind of politeness strategy. Appropriate use of vague language will make the negotiation go smoothly, and avoid the conflict of business negotiation so as to achieve the purpose of cooperation

Radio-frequency spectroscopy of weakly bound molecules in spin-orbit coupled atomic Fermi gases

We investigate theoretically radio-frequency spectroscopy of weakly bound molecules in an ultracold spin-orbit-coupled atomic Fermi gas. We consider two cases with either equal Rashba and Dresselhaus coupling or pure Rashba coupling. The former system has been realized very recently at Shanxi University [Wang et al., arXiv:1204.1887] and MIT [Cheuk et al., arXiv:1205.3483]. We predict realistic radio-frequency signals for revealing the unique properties of anisotropic molecules formed by spin-orbit coupling.Comment: 11 pages, 7 figure

Deep Learning Based on Orthogonal Approximate Message Passing for CP-Free OFDM

Channel estimation and signal detection are very challenging for an orthogonal frequency division multiplexing (OFDM) system without cyclic prefix (CP). In this article, deep learning based on orthogonal approximate message passing (DL-OAMP) is used to address these problems. The DL-OAMP receiver includes a channel estimation neural network (CE-Net) and a signal detection neural network based on OAMP, called OAMP-Net. The CE-Net is initialized by the least square channel estimation algorithm and refined by minimum mean-squared error (MMSE) neural network. The OAMP-Net is established by unfolding the iterative OAMP algorithm and adding some trainable parameters to improve the detection performance. The DL-OAMP receiver is with low complexity and can estimate time-varying channels with only a single training. Simulation results demonstrate that the bit-error rate (BER) of the proposed scheme is lower than those of competitive algorithms for high-order modulation.Comment: 5 pages, 4 figures, updated manuscript, International Conference on Acoustics, Speech and Signal Processing (ICASSP 2019). arXiv admin note: substantial text overlap with arXiv:1903.0476

Simulation analysis of underwater structure based on local cylindrical acoustic holography

The local cylindrical acoustic holography technology is introduced, and its application in identifying and locating the column is introduced. The implementation algorithm of local cylindrical holographic reconstruction is given. In engineering operations, columnar sound sources such as electric motors, water pipes, and underwater structures are common noise sources in engineering. Therefore, this paper is of great significance for the location identification and control of such sound sources. The simulation results show that the proposed local cylindrical acoustic holography algorithm is useful to identify the noise source and reconstruct the sound field correctly