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We propose a weakly-coupled ultra-flattened chromatic dispersion few-mode photonic crystal fiber (FM-PCF) supporting 10 vector modes (HE11a, HE11b, TM01, HE21a, HE21b, TE01, HE31a, HE31b, EH11a, EH11b) which works over a large range of wavelength across the C+L band. We investigate the chromatic dispersion, minimum effective refractive index difference (minΔneff), confinement loss, bending loss and differential mode delay (DMD) of the proposed fiber under the influences of design parameters by using the finite element method (FEM). The circular holes in the first ring are replaced by elliptical holes to obtain flattened-chromatic dispersion. And an extra small rectangular defected hole is introduced in the fiber core order to achieve ultra-flattened chromatic dispersion and large minΔneff. The simulated results show that the designed weakly-coupled FM-PCF can obtain ultra-flattened (dispersion slope < 1.8 × 10−4 ns/km/nm2) and large minΔneff (> 1.6 × 10−4) in the wavelength range of 1520 nm to 1640 nm. And the proposed weakly-coupled FM-PCF also has ultra-low confinement loss (−9dB/km) and good bending resistance. In summary, the proposed weakly-coupled FM-PCF has the potential applications for large-capacity MDM communication systems.

This paper studies the mechanism and influencing factors of resonance overvoltage of EHV transmission lines caused by lightning. By analyzing the time domain steady state of the simplified resonance circuit, the physical mechanism of resonance is revealed. The characteristics of resonance transient process and overvoltage waveform are analyzed by using electromagnetic transient simulation. The main influencing factors of overvoltage amplitude are also studied. The results show that: 1) During uneven open-phase conditions, resonant circuit involving shunt inductors and line equivalent capacitor obtains energy from lightning strikes, which may lead to resonance. 2) the transient process of resonance can be divided into three stages, including lightning stage, lightning-resonance conversion stage and steady-state resonance stage, among which the voltage of the first two stages are higher; 3) the lightning strike time, lightning current parameters and subsequent lightning strike affect on the overvoltage amplitude, which leads to the random amplitude in overvoltage.

Unknown biases or perturbations in the INS/GNSS integrated navigation system may produce unforeseeable negative effects when the navigation states are estimated by using the Kalman filtering and its variants. To mitigate these undesirable effects in the INS/GNSS integrated navigation, a novel partially strong tracking extended consider Kalman filtering (PSTECKF) is proposed. In the presented PSTECKF algorithm, the biases are not estimated, but their covariance and co-covariance are incorporated into the state estimation covariance by using a nonlinear “consider” approach. Based on the above, the PSTECKF also partially introduces an adaptive fading factor into the predicted covariance of the states, which excludes the co-covariance between the states and biases, to compensate the nonlinear approximation errors and navigation system covariance uncertainties. Simulation results demonstrate the performance of the proposed PSTECKF for INS/GNSS integrated navigation is superior to that of the EKF and ECKF when the biases or perturbations happen in a navigation system.

The Internet of Things (IOT) is considered to be the third wave of the world information industry after the computer and the Internet. In order to realize the ubiquitous access to the IOT, the cellular network can only be fused with the wireless sensor network physical social systems. Based on this, the purpose of this paper is to extract the general functions that necessary but unrelated with the specific application in the cellular network and wireless sensor fusion technology. These general functions, including terminal registration and serial number assignment, terminal authentication management, connection management, terminal fault management, terminal state management and monitoring, congestion control, terminal dormancy and activation, and so on. Aiming at these general functions, the author gives an exploratory solution to provide a referable shared function module for the fusion of cellular network and wireless sensor networks physical social systems. It is of great significance to improve the development progress of the IOT, reduce the difficulty and cost of development.

Research on the optimization of Internet of Things wireless channel has received widespread attention. First, this paper analyzed the Internet of Things wireless channel, including multichannel analysis, Doppler effect analysis, MIMO channel model analysis, and channel correlation characteristics simulation. On this basis, a three-path channel neural network curve approximation model was established, and the CDF and PDF curves of Rayleigh and Rice fading channels were approximated and analyzed. The results showed that the neural network model basically conformed to the reality. According to the 3GPP2 standard, the time domain delay model of the FIR filter is optimized, and the design model has the characteristics of fast calculation speed and high precision. In addition, this paper also used the neural network to approximate the amplitude-frequency characteristics of the 64-order fading shaping filter and the 120-order interpolation filter. The simulation results met the requirements. Finally, based on the neural network MIMO channel model, a neural network model of additive white Gaussian noise channel under certain conditions was established. Based on the simulation data, the polarization antenna was optimized for path loss and different tilt angles, and the optimization could be performed at high speed while achieving the minimum error.

Text-based visual question answering (VQA) requires to read and understand text in an image to correctly answer a given question. However, most current methods simply add optical character recognition (OCR) tokens extracted from the image into the VQA model without considering contextual information of OCR tokens and mining the relationships between OCR tokens and scene objects. In this paper, we propose a novel text-centered method called RUArt (Reading, Understanding and Answering the Related Text) for text-based VQA. Taking an image and a question as input, RUArt first reads the image and obtains text and scene objects. Then, it understands the question, OCRed text and objects in the context of the scene, and further mines the relationships among them. Finally, it answers the related text for the given question through text semantic matching and reasoning. We evaluate our RUArt on two text-based VQA benchmarks (ST-VQA and TextVQA) and conduct extensive ablation studies for exploring the reasons behind RUArt’s effectiveness. Experimental results demonstrate that our method can effectively explore the contextual information of the text and mine the stable relationships between the text and objects. [ABSTRACT FROM AUTHOR]