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Synchrosqueezing transform (SST) has been used to address the problems in many diverse disciplines. However, the calculated instantaneous frequency (CIF) precision by SST decreases with the increase in time-sample interval and actual instantaneous frequency. This will lead to an incorrect time–frequency distribution. To eliminate the impact of the time-sample interval and to enhance the CIF precision and SST resolution, we propose an adaptive time-resampled high-resolution SST, in which the time-resampled interval of the time–frequency spectrum for instantaneous frequency calculation is adapted to the highest frequency in its effective frequency band and the desired CIF precision. A synthetic signal example shows that the adaptive time-resampled high-resolution SST can eliminate the impact of the time-sample interval and achieve correct and desired high-resolution time–frequency distribution. A real 3-D seismic data application demonstrates that the proposed approach is a good potential technique for high-precision signal processing and interpretation.

The Hilbert transform (HT) has been widely used in seismic data processing and interpretation. However, HT results exhibit lower noise robustness and resolution. This paper extends HT by introducing three orders greater than or equal to 0 and the sign function in frequency domain and propose an extended Hilbert transform (EHT) which has many advantages over the HT—particularly noise robustness, resolution, and a variety of applications. The output of EHT depends on the choice of the three orders and the sign function. Analysis of synthetic cosine signal and hypothetical channel model shows that EHT helps to retain the desired characteristics of HT while overcoming its shortcomings and exhibits better noise robustness and higher resolution than HT. Analysis of real 3‐D seismic data application demonstrates that EHT shows a very desirable ability to capture subtle geologic features and can be well used for seismic attributes and other fields involving digital data processing.

Although deep convolutional neural networks have made breakthroughs in the accuracy and speed of single-image super-resolution, there are still many unsolved problems: firstly, How to refine the texture problem when performing super-resolution processing at a larger magnification ratio. Secondly, the existing convolutional neural network image super-resolution algorithms are prone to overfitting and insufficient convergence of the loss function. Aiming at two problems, an image super-resolution method based on generative adversarial network is proposed. The feature map is spatially transformed on the network to solve the problem of refined texture, combined with CycleGAN and SRGAN, the network structure is improved and the loss function is optimized, and the SRCICGAN algorithm is proposed to restore the four times down-sampled image to solve the loss function problem. The experiment is compared with the latest six methods on three data sets. The PSNR and SSIM indicators are 1.92% and 5.49% higher in the Flickr2K data set, respectively, and better visual effects can be obtained in terms of detailed texture.

In order to solve the problems of long time-consuming, low accuracy and high energy consumption in detecting the state of health (SOH) of retired power batteries, a rapid prediction method of SOH based on electrochemical impedance spectroscopy (EIS) is proposed. This method realizes the rapid estimation of the SOH of retired power batteries through the mathematical model established by the constant phase element parameters in the constructed electrochemical impedance spectroscopy equivalent circuit model and the battery SOC and SOH. The verification experiment results show that using this method can greatly reduce the test time, save energy, and achieve rapid estimation of the unknown state of charge and health of the battery, and the prediction error is less than 2%.

The load characteristic model based on demand response and the load optimization control method in three different scenarios are studied in this paper. Firstly, by decoupling rigid load and flexible load, according to different degree that flexible load participates in demand response, considering the influence of different control variables, three types of load characteristics models of electricity price load, direct control load and interruptible load are constructed. Secondly, based on the established the load characteristic model proposes a reasonable load control strategy optimization control method under the condition of different practical power supply gap constraints. Finally, through three cases of scenarios, we explored the control variables are direct control load and interruptible load control, the objective function is when the deviation between the actual load reduction amount and the power supply gap is the smallest, and the constraint condition considers the demand response contract. The feasibility of the constructed model and the optimization method is verified, which provides a reference for the promotion of user-side demand response in China.

Analysis of flight safety risk coupling plays an important role to prevent flight accidents. In this paper, a topological analysis based on fuzzy network theory is presented to reveal the complex coupling relationship of interrelated risks in flight safety system. The connotation of flight safety risk coupling is presented, and the integration research of fuzzy sets and complex network is introduced. Based on extracting the key flight accident causation factors, the model to analyze flight safety risk coupling is constructed. Finally, the key risk factors and important interactions are gained by analyzing the structural properties of flight safety risk network. The conclusion is that the proposed method based on fuzzy sets and complex network is helpful to reveal the coupling mechanism of flight safety risk factors, and the network theory-based analysis serves as a powerful complement to classical flight safety risk analysis.

Safety Management Performance of Air Traffic Control is affected by many factors. Via questionnaire statistics analysis and Exploratory Factor Analysis (EFA) to optimize items and extract factors, the authors confirm five main effective factors at last, including work initiative, communication and exchange, team cohesion, system completeness and leadership management, and all of them have passed the reliability test and validity test so as to enhance the level of safety management of Air Traffic Control.

The purpose of this paper is to analyze the current financial employee participation scheme in Ecuador. Private companies, according to the law, have to pay fifteen percent of their profits to employees. In some companies this procedure represents a minimum benefit to employees. However, in the Ecuadorian oil industry this matter is relevant and mentioned in the hiring process as the most important part of employees' compensation. Using references and data from different industries in the Ecuadorian market, this paper provides an analysis of this scheme as a mechanism of recognition and motivation for employees in private oil companies established in the country.