This paper considers indoor localization using multi-modal wireless signals including Wi-Fi, inertial measurement unit (IMU), and ultra-wideband (UWB). By formulating the localization as a multi-modal sequence regression problem, a multi-stream recurrent fusion method is proposed to combine the current hidden state of each modality in the context of recurrent neural networks while accounting for the modality uncertainty which is directly learned from its own immediate past states. The proposed method was evaluated on the large-scale SPAWC2021 multi-modal localization dataset and compared with a wide range of baseline methods including the trilateration method, traditional fingerprinting methods, and convolution network-based methods.
A simple, sensitive, and specific high-performance liquid chromatography method has been developed for the simultaneous quantification of the three major biologically active ingredients, gastrodin (GA), 4-hydroxybenzyl alcohol (HA), and 4-hydroxybenzaldehyde (HD), in Gastrodia elata Blume for the first time. The HPLC assay was performed on a reversed phase ODS column by using methanol-water-isopropyl alcohol (35:55:10, v:v:v) as mobile phase with a flow rate of 0.4mL/min. The detection wavelength was set at 270 nm. Regression equations revealed linear relationships (correlation coefficients: 0.9997–0.9999) between the peak area of each constituent (GA, HA, HD) and its concentration. The relative standard deviations of the retention times of three constituents range between 0.2∼0.5%. The recoveries for the three constituents ranged between 96.6∼98.5%. The GA, HA, HD contents measured 12.0 mg/g (2.53% RSD), 2.1 mg/g (2.04% RSD), and 0.13 mg/g (2.63% RSD), respectively, in the ethanol extracts of Gastrodia elata Blume.
The crystal structure, electronic properties of F, S, C, B and N doped SnO 2 were studied with the First-Principle Method. The theoretical results show that doping of non-metal elements did not change the structure of SnO 2 but result in slight lattice volume expansion. The dope of the non-metal elements of B, F, and S cause the Fermi level to shift upThe most obvious finding to emerge from the analysis is that F-doped SnO 2 has the lowest defect binding energy, stable crystal structure, and the easiest doping. The B, F, and S element doped SnO 2 can modulate the fermi level. The doping of the B and S elements introduced additional defect energy levels to appear within the forbidden band-gap，which improved the crystal conductivity. Analysis of the energy band structure of SnO 2 crystals doped with C and N elements shows that the Fermi level has crossed the impurity level. The Fermi level of F doped SnO 2 is inside the conduction band, and the doped crystal has metallicity. The optical properties of SnO 2 crystals doped with non-metallic elements were analyzed and calculated. The SnO 2 crystal doped with F element had the highest reflectivity in the infrared region, and the reflectance of the crystals doped with N, C, S, and B elements decreased sequentially. Based on this theoretical calculations, F doped SnO 2 is found to be the best photoelectric material for for preparing low-e thin film.
A novel method for determination of diphenylamine (DPA) and its nitrated derivatives, which are considered as characteristic components in smokeless powder and gunshot residues, is described. A tandem mass spectrometric method is established and mass spectrometer parameters optimized for each compound to obtain higher sensitivity. Under optimum conditions, quantitative analysis was carried out. The linear ranges are 5.0–200.0, 2.0–200.0 and 5.0–250.0 ng ml−1 and the detection limits are 1.0, 0.5 and 2.5 ng ml−1 for diphenylamine (DPA), N-NO-diphenylamine (N-NO-DPA) and 4-NO2-diphenylamine (4-NO2-DPA), respectively. Intra-assay and inter-assay precision and accuracy of analysis of these three samples were investigated. Based on the regression lines obtained above, smokeless samples were analyzed. It was found that there are 0.952% DPA, 0.384% N-NO-DPA and 0.128% 4-NO2-DPA in smokeless powder. Recovery tests showed that using cotton swabs, 80.3 ± 4.9% DPA, 79.6 ± 3.1% N-NO-DPA and 83.1 ± 5.4% 4-NO2-DPA could be recovered from human hands.
This paper presents a novel method of thickness measurement for microelectromechanical system (MEMS) structures using micro-Raman spectroscopy. When heating by a constant power laser, the local temperature rise of a microscale structure depends on the thickness and thermal characteristics of the structure. The thickness information can then be evaluated by the temperature induced Raman shift. Theoretical analysis and simulation of this method are performed. The small spot size of the laser in micro-Raman spectroscopy enables thickness measurement with a high spatial resolution. This measurement method is confirmed by measuring the thickness of a MEMS single-crystalline silicon (c-silicon) membrane. The measurement result also consists of that of scanning electron microscopy (SEM) for the same sample. It has the advantages of being a non-contact and nondestructive process, no preparation, and spatial mapping aspects. The proposed method is also feasible for materials with a temperature sensitive Raman signal.
In the list of addresses for the authors of this Communication, the country should read as Republic of China. The editors apologize for the error in the print version of their article.
A novel method, by using micro-Raman spectroscopy, is developed to measure the thickness of microelectromechanical system structures with high spatial resolution. When a microscale structure is heated by a laser, the temperature rise of the structure depends on the structure thickness and material properties. Therefore, the structure thickness can be measured using Raman shift, which is a function of temperature. Micro-Raman spectrometer is capable of measuring the thickness distribution of microscale structures with micron spatial resolution. This technique is evaluated by characterizing the thickness distribution of a single-crystal silicon (c-Si) membrane. The measured thickness distributions are verified by scanning electron microscope measurement.
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