Transformer-Based Detection for Highly Mobile Coded OFDM Systems.

This paper is concerned with mobile coded orthogonal frequency division multiplexing (OFDM) systems. In the high-speed railway wireless communication system, an equalizer or detector should be used to mitigate the intercarrier interference (ICI) and deliver the soft message to the decoder with the soft demapper. In this paper, a Transformer-based detector/demapper is proposed to improve the error performance of the mobile coded OFDM system. The soft modulated symbol probabilities are computed by the Transformer network, and are then used to calculate the mutual information to allocate the code rate. Then, the network computes the codeword soft bit probabilities, which are delivered to the classical belief propagation (BP) decoder. For comparison, a deep neural network (DNN)-based system is also presented. Numerical results show that the Transformer-based coded OFDM system outperforms both the DNN-based and the conventional system.

Adaptive Binarization of QR Code Images for FastAutomatic Sorting in Warehouse Systems.

As the fundamental element of the Internet of Things, the QR code has become increasingly crucial for connecting online and offline services. Concerning e-commerce and logistics, we mainly focus on how to identify QR codes quickly and accurately. An adaptive binarization approach is proposed to solve the problem of uneven illumination in warehouse automatic sorting systems. Guided by cognitive modeling, we adaptively select the block window of the QR code for robust binarization under uneven illumination. The proposed method can eliminate the impact of uneven illumination of QR codes effectively whilst meeting the real-time needs in the automatic warehouse sorting. Experimental results have demonstrated the superiority of the proposed approach when benchmarked with several state-of-the-art methods.

Quantitative method for analysis of tobacco-specific N-nitrosamines in mainstream cigarette smoke by using heart-cutting two-dimensional liquid chromatography with tandem mass spectrometry.

A heart-cutting two dimensional liquid chromatography coupled with tandem mass spectrometry method was developed for the analysis of tobacco-specific N-nitrosamines (TSNAs) at low concentration level in Virginia-type cigarette smoke. A strong cation exchange column was utilized for the first dimensional separation, which effectively removed acidic and neutral components in the smoke, followed by a reversed phase liquid chromatography coupled with tandem mass spectrometric analysis. To capture components of the TSNAs in the effluent on the trapping column, a compensating pump was applied for online dilution and pH adjustment during the period of the TSNAs fraction transferring and enrichment. Highly sensitive determination of the TSNAs in mainstream cigarette smoke was achieved by isotope deuterated internal standards under the multiple reaction monitoring mode. Compared with traditional methodologies, the method was almost no matrix interference. Limits of quantity for the TSNAs were within 0.027-0.094 ng/mL, and the results showed good reproducibility and accuracy. Finally, the new method was applied for analysis of the Kentucky reference cigarettes and the results agreed well with joint experiments of Cooperation Centre for Scientific Research Relative to Tobacco.

[Analysis of alkaline CuO degradation products of acid detergent fiber from tobacco leaves by using liquid chromatography].

The acid detergent fiber (ADF) from tobacco leaves was obtained by treating the sample with petroleum ether-ethanol (6:4, v/v), 30 g/L sodium dodecylsulfate and 0.5 mol/L sulphuric acid containing 20 g/L hexadecyl trimethyl ammonium bromide successively. The ADF was degraded by the alkaline CuO oxidation procedure. In this work, six samples of ADF degradation products from tobacco leaves were prepared. The samples were analyzed by using gradient liquid chromatography (LC) where an Ultimate XB C18 column was used as stationary phase, with a mixture of methanol and water as mobile phase, at a column temperature of 35 °C and a flow rate of 0.8 mL/min. Dual wavelengths of 280 nm and 320 nm were chosen for the detection. It was found that there were four characteristic peaks for the ADF degradation products. By taking these peaks as research object, the optimum time for the degradation was found to be 5 h and the sample solution could be kept stable within 7 days. The established method may provide a new approach for the studies of the differences between lignin composition in different tobacco leaves and the relationship between lignin content and the smoking quality of tobacco leaves.

A novel fully automated on-line coupled liquid chromatography-gas chromatography technique used for the determination of organochlorine pesticide residues in tobacco and tobacco products.

In this study, a novel fully automated on-line coupled liquid chromatography-gas chromatography (LC-GC) technique was reported and applied for the determination of organochlorine pesticide residues (OCPs) in tobacco and tobacco products. Using a switching valve to isolate the capillary pre-column and the analytical column during the solvent evaporation period, the LC solvent can be completely removed and prevented from reaching the GC column and the detector. The established method was used to determinate the OCPs in tobacco samples. By using Florisil SPE column and employing GPC technique, polarity impurities and large molecule impurities were removed. A dynamic range 1-100ng/mL was achieved with detection limits from 1.5 to 3.3µg/kg. The method exhibited good repeatability and recoveries. This technology may provide an alternative way for trace analysis of complex samples.