A Wireless Sensor Network Based Personnel Positioning Scheme in Coal Mines with Blind Areas

This paper proposes a novel personnel positioning scheme for a tunnel network with blind areas, which compared with most existing schemes offers both low-cost and high-precision. Based on the data models of tunnel networks, measurement networks and mobile miners, the global positioning method is divided into four steps: (1) calculate the real time personnel location in local areas using a location engine, and send it to the upper computer through the gateway; (2) correct any localization errors resulting from the underground tunnel environmental interference; (3) determine the global three-dimensional position by coordinate transformation; (4) estimate the personnel locations in the blind areas. A prototype system constructed to verify the positioning performance shows that the proposed positioning system has good reliability, scalability, and positioning performance. In particular, the static localization error of the positioning system is less than 2.4 m in the underground tunnel environment and the moving estimation error is below 4.5 m in the corridor environment. The system was operated continuously over three months without any failures

Research on the Deep Recognition of Urban Road Vehicle Flow Based on Deep Learning

At present, the recognition of vehicle flow is mainly achieved with an artificial statistical method or by intelligent recognition based on video. The artificial method requires a large amount of manpower and time, and the existing video-based vehicle flow recognition methods are only applicable to straight roads. Therefore, a deep recognition model (DERD) for urban road vehicle flow is proposed in this paper. Learning from the characteristic that the cosine distance between the feature vectors of the same target in different states is in a fixed range, we designed a deep feature network model (D-CNN) to extract the feature vectors of all vehicles in the traffic flow and to intelligently determine the real-time statistics of vehicle flow based on the change of distance between vectors. A detection and tracking model was built to ensure the stability of the feature vector extraction process and to obtain the behavior trajectory of the vehicle. Finally, we combined the behavior and the number of vehicle flows to achieve the deep recognition of vehicle flow. After testing with videos recorded in actual scenes, the experimental results showed that our method can intelligently achieve the deep recognition of urban road vehicle flow. Compared with the existing methods, our approach shows higher accuracy and faster real-time performance

A Novel Weak Signal Detection Method of Electromagnetic LWD Based on a Duffing Oscillator

The logging while drilling (LWD) electromagnetic weak signal detection model of a Duffing oscillator based on a one-dimensional nonlinear oscillator is established. The influences of noise on Duffing oscillator dynamic behavior of periodic driving force are discussed and evaluate the oscillator weak signal detection mechanism based on a phase change trajectory diagram. The improved Duffing oscillator is designed and applied to detect the electromagnetic logging signal resistivity at the drill bit using the time-scale transformation method. The simulation results show that the nonlinear dynamic characteristics of the Duffing oscillator are very noticeable, the Duffing circuit is very sensitive to detect the tested signal, and it has a reasonable level of immunity to noise. The smaller the amplitude of the tested signal, the more sensitive the circuit is to the signal, the better the antinoise system performance, and the lower the signal-to-noise ratio (SNR)

Organophosphorus catalytic reaction based on reduction of phosphine oxide

The special electronic configuration of phosphorus atoms endows organophosphorus reagents with unique chemical properties, which enable them to be used to catalyze various organic reactions, such as the Wittig reaction, Staudinger reaction, Appel reaction and Mitsunobu reaction. However, the catalytic process will be accompanied by the generation of large amounts of phosphine oxide waste, resulting in the reduction of atom utilization of the reaction, and it is difficult to separate the product. Therefore, it is essential to explore a greener and more sustainable organic synthesis route based on the catalytic cycle of phosphine oxide as a model. This paper summarizes the catalytic cycle and recycling of phosphorus with or without reducing agents and reviews the related developments in recent decades: from the addition of stoichiometric strong reducing agents, to the design of ring phosphines with specific structures, to the development of new energy inputs (electrochemistry), to the addition of a series of compounds to activate the P(V)O double bond, driving the catalytic cycle of phosphine oxide through chemical transformation. This review also points out the development potential of this field in the future, which will promote its development and progress in a greener direction

A Modified Micro-Macro Constitutive Model for Porous Rocks with Pressure-Sensitive Matrix by considering a New Hardening Law

This paper aims mainly at providing an incremental elastoplastic constitutive model for heterogeneous porous rock-like materials in the frame of micromechanics. The studied material is considered to be made up of randomly distributed spherical pores embedded in a pressure-sensitive solid matrix obeying Drucker–Prager yield function. The effective elastic properties of porous rocks are obtained by the use of Mori and Tanaka homogenization scheme, which are on function of the bulk and shear moduli of the solid matrix and of the value of porosity. For the macroscopic nonlinear phase, a limit analysis-based macroscopic criterion is adopted to derive the basic constitutive rule by considering an associated plastic flow rule. In order to capture the typical hardening effects of rocks, an originally proposed hardening function of the solid matrix is also taken into consideration, which is related on the accumulated equivalent plastic strain. In order to verify its accuracy, the proposed micro-macro constitutive model is implemented by a numerical procedure including elastic predictions and plastic corrections and compared to experimental results of triaxial compression tests of sandstone with different confining pressures. It is observed that the numerical simulation is in accord with the experimental data, indicating that the obtained model is able to predict the main mechanical behaviours of rock-like materials

Vegetation in Arid Areas of the Loess Plateau Showed More Sensitivity of Water-Use Efficiency to Seasonal Drought

Studying the impact of regional or seasonal drought on vegetation water-use efficiency (WUE) can identify an effective theoretical basis by which vegetation can cope with future climate change. Based on remote sensing data and climate grid data, in this study, we calculated the ecosystem WUE and standardized precipitation evapotranspiration index (SPEI), analyzed the temporal and spatial divergence of seasonal drought and WUE, and explored the relationship between WUE and seasonal drought in the Loess Plateau. The results indicate that from 2001 to 2019, the humidity in spring and summer on the Loess Plateau shows an increasing trend, and the aridity in fall also shows an increasing trend. Averaged over four seasons, WUE presents distribution characteristics of “high in the southeast and low in the northwest”, with the highest WUE in summer. However, the geological distribution of the sensitivity of WUE to seasonal drought was significantly different. Spring drought increased WUE, whereas summer drought led to a decrease in WUE. When fall drought was less severe, the WUE increased; WUE response to winter SPEI was negative, but the sensitivity did not change with variation of drought degree. The sensitivity of WUE to the magnitude of seasonal drought was affected by regional dry and wet conditions. A clear seasonal divergence was found in four climate regions, along with increased drought intensity, and the sensitivity of WUE to drought magnitude in arid areas was generally higher than that in semi-arid, semi-humid areas, or humid areas. With this study, we deeply explored how ecosystems deal with the water supply strategy of seasonal drought, which is of great significance in the understanding of the coupling relationship between the carbon–water cycle and climate change

Vegetation in Arid Areas of the Loess Plateau Showed More Sensitivity of Water-Use Efficiency to Seasonal Drought

Studying the impact of regional or seasonal drought on vegetation water-use efficiency (WUE) can identify an effective theoretical basis by which vegetation can cope with future climate change. Based on remote sensing data and climate grid data, in this study, we calculated the ecosystem WUE and standardized precipitation evapotranspiration index (SPEI), analyzed the temporal and spatial divergence of seasonal drought and WUE, and explored the relationship between WUE and seasonal drought in the Loess Plateau. The results indicate that from 2001 to 2019, the humidity in spring and summer on the Loess Plateau shows an increasing trend, and the aridity in fall also shows an increasing trend. Averaged over four seasons, WUE presents distribution characteristics of “high in the southeast and low in the northwest”, with the highest WUE in summer. However, the geological distribution of the sensitivity of WUE to seasonal drought was significantly different. Spring drought increased WUE, whereas summer drought led to a decrease in WUE. When fall drought was less severe, the WUE increased; WUE response to winter SPEI was negative, but the sensitivity did not change with variation of drought degree. The sensitivity of WUE to the magnitude of seasonal drought was affected by regional dry and wet conditions. A clear seasonal divergence was found in four climate regions, along with increased drought intensity, and the sensitivity of WUE to drought magnitude in arid areas was generally higher than that in semi-arid, semi-humid areas, or humid areas. With this study, we deeply explored how ecosystems deal with the water supply strategy of seasonal drought, which is of great significance in the understanding of the coupling relationship between the carbon–water cycle and climate change

Intelligent Reflecting Surface Assisted mmWave Integrated Sensing and Communication Systems

International audienceThis paper proposes an intelligent reflecting surface (IRS) assisted integrated sensing and communication (ISAC) system operating in the millimeter-wave band. Specifically, the ISAC system consists of a radar subsystem and a communication subsystem to detect multiple targets and communicate with the users simultaneously. The IRS is used to configure the radio propagation environment by changing the phase of the radio signal to enhance the communication transmission rate. In the proposed scheme, we first derive a closed-form solution for the radar signal covariance matrix to generate a radar beampattern in the angle of interest. Then, we jointly optimize the beamforming vector of the communication subsystem and the IRS phase shifts to enhance the communication transmission rate. To decouple the multiple variables to be optimized, the alternating optimization and quadratic transformation methods are applied to determine the communication beamforming vector and the IRS phase shifts. Specifically, we utilize the majorization minimization and the complex circle manifold methods to compute the IRS phase shifts. Simulation results verify the effectiveness of the proposed algorithm and demonstrate that an IRS can improve the performance of ISAC systems