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A power MOSFET with P-base Schottky diode and built-in channel diode is proposed and numerically investigated in this article. The P-base Schottky diode formed by the P-base Schottky contact is in reverse series with the P-base/N-drift junction diode. Besides, by coupling the gate of the dummy MOSFET to the source, a built-in channel diode is introduced, which provides a unipolar reverse conduction current path and drastically reduces the gate-to-drain charge. When the proposed MOSFET serves as the freewheeling diode, the reverse-biased P-base Schottky diode inactivates the P-base/N-drift junction diode, so that the reverse current will be carried out by the built-in channel diode. As a result, in comparison with the planar gate power MOSFET, the reverse recovery charge and the gate-to-drain charge could be reduced by 96.9 % and 75.4%, respectively.

Metal oxide field-effect transistors (FETs) have potential applications in display, flexible electronic device. Here, we will report the advance of our OLED display, metal oxide FETs, and application in beyond display. We have paid more attention to the stability improvement, interface trap of MO-TFT, and application in CMOS circuit, artificial synapse and gas sensor.

This paper proposes a limited discrete operation points control strategy for series hybrid electric tracked-vehicle. First, to optimize the control parameters of rule-based energy management strategy, particle swarm optimization algorithm is employed. the optimization results were applied to determine the optimal switch strategy between operation points of the engine. Second, a dynamic adaptive strategy is also proposed to achieve the coordinated control of the engine-generator set. Finally, with combination of above parts, a detailed energy management strategy and coordinated control system was proposed. The results demonstrate that the discrete operation points control strategy combined with coordinated control strategy can improve the electricity power supply performance, decrease the fluctuations of the system and stabilize the bus voltage and guarantee robust control performance.

Eco-environmental quality is one of the important contents affecting urban human settlement environment. Remote sensing technology can quickly evaluate the quality of the ecological environment and provide scientific basis for urban ecological environment protection and governance. In this study, remote sensing ecological index (RSEI) and Sentinel 2A remote sensing data were used to comprehensively evaluate the ecological environment of Kunming in 2020. At the same time, based on remote sensing and GIS software platforms, normalized vegetation index, humidity index, surface temperature and bare soil index were extracted from remote sensing images to represent the four ecological elements of greenness, humidity, dryness, and heat. After standardizing the data, the principal component analysis method was coupled to establish the remote sensing ecological index. The results show that the change of ecological environment quality is mainly related to the rapid economic development in Kunming, the change of vegetation coverage caused by human activities, the gradual change of lake area and the change of land use structure caused by urban expansion.

Machine learning algorithms, such as Support Vector Machine (SVM) and Deep Neural Network (DNN), have gained a lot of interest recently. When training a machine learning algorithm, randomly shuffling all the training data can improve the testing accuracy and boost the convergence rate. Nevertheless, realizing training data random shuffling in a real system is not straightforward due to the slow random accesses in hard disk drives (HDDs). Common random shuffling implementations assume that HDD is used as storage, so they sacrifice the random degree of shuffling to reduce random storage accesses. Different from conventional HDD, emerging solid-state drive (SSD) based storage devices, such as Intel Optane SSD, offer fast random accesses. In this paper, we explore the opportunities to take advantage of the fast random access property in SSD to perform full-range random shuffling without taking up precious CPU memory and study the interplay between different shuffling methods and various types of storage devices. We use a lightweight implementation of random shuffling (LIRS) as an example of the SSD-aware shuffling method to conduct performance analysis. Evaluations show that, compared to conventional shuffling methods, LIRS can improve convergence rate and reduce the total training time of SVM and DNN by 67.1% and 33.9% on average.

In this paper, a novel neural network based compressed sensing (CS) receiver for chaotic ultra-wideband (UWB) communication system is proposed. Chaotic UWB system receiver based on CS has been proved to be feasible and can greatly reduce the sampling rate. However, the measurement signal in CS is not optimized according to the received chaotic signals. Thanks to the learning capability of neural network with deep learning algorithm, the proposed receiver is able to intelligently optimize the measurement signal in CS and discover the underlying mapping between the input and output signals. Numerical experiments demonstrate that the proposed scheme can effectively enhance the bit error rate (BER) performance than the conventional one. Moreover, we propose a simple and practical statistical adjustment method for the proposed receiver. Numerical experiments also show that the method can further improve the BER performance.

This paper investigates the impact of relay selection on cognitive radio non-orthogonal multiple access (CR-NOMA) based satellite-ground cooperation network. By analyzing the signal-to-interference-plus-noise ratio (SINR) at the User 1, we propose a two-stage relay selection scheme, and derive the exact outage probability expression and the progressive probability expression of the primary user. Finally, theoretical simulations are used to verify the correctness of the deduced results and the impact of related variables on system performance.

In this paper, a design method of extended state observer (ESO)-based sliding mode control is proposed for underwater vehicle manipulator systems (UVMSs) with prescribed performance. First, the system model is reformulated by lumping the unknown uncertainties and disturbances into a total disturbance. Then, an ESO is developed to estimate the total disturbance. Based on ESO, the prescribed performance is defined to limit upper bounds of tracking error and then a sliding mode controller is proposed to ensure that all the signals are ultimately uniformly bounded (UUB). Moreover, the tracking errors can converge to the neighborhood of zero in finite-time and satisfy the prescribed performances. Finally, simulation results are presented to show the effectiveness of the proposed controller.

Aiming at the problem that the precision of gaze information data extraction is not high in the process of pilot's; flight, this paper puts forward the research on the fusion of the data of the landing point of sight and the target information, and feeds back the information through human-computer interaction to obtain the accurate target information. First, the non wearable eye tracker is used to track the line of sight, estimate the fixation point, obtain the fixation point coordinates, and match with the position coordinates of the instrument panel to get the dial where the fixation point is. Then, data fusion is carried out between the instrument panel where the fixation point is located and the flight parameters to obtain the information displayed on the instrument panel. Finally, the fixation information of the instrument panel is used as the input data to support the identification of the pilot's intention. Secondly, data fusion is carried out between the pilot's attention information and reaction time information, and a large amount of data is used as the input data. Machine learning is adopted Methods after information fusion, the decision- making of pilots was predicted.

Board burning is a comprehensive failure caused by a variety of factors. Typically, board burning can be divided into two modes: overheating and voltage breakdown. It is necessary to analyze the root cause according to the observation and the circuit design of burned areas. In the failure analysis, first step is to determine the position of ignition, which is the necessary step for further analysis of board burning. In this paper, some characterizations were introduced to determine the position of ignition. Finally, some burning cases were studied, and the failure mechanism was discussed.

In this paper, we propose a novel robust downlink beamforming (BF) design for satellite-terrestrial integrated networks. Under a realistic assumption that the angular information of eavesdroppers is not perfectly known, we establish an optimization framework for hybrid BF at the terrestrial base station and digital BF at the satellite to maximize the secrecy-energy efficiency of the system, while satisfying the quality-of-service constraints of both earth station and cellular user. Since the formulated optimization problem is mathematically intractable, we present an iterative algorithm based on the Charnes-Cooper approach to optimize the BF weight vectors. The effectiveness and superiority of the proposed robust hybrid BF scheme are validated via computer simulations.

The modified group runs (MGR) scheme has a superior performance to the Shewhart and synthetic control schemes, particularly in identifying small and moderate mean shifts in a process. Recently, the MGR scheme was studied using the average number of observations to signal (ANOS) criterion, under the scenario where the process parameters are unknown (Case-U). However, a setback of this study is that the exact shift size must be specified prior to the implementation of this scheme as this is required by the ANOS criterion. In most of the scenarios, practitioners do not have a good knowledge of the exact shift size. To tackle this issue, we propose the use of the expected average number of observations to signal (EANOS) criterion in evaluating the performance of the Case-U MGR scheme. We also proposed the optimal design of the MGR scheme with Case-U based on minimizing out-of-control (OOC) EANOS. Finally, we present an example of application and demonstrate that the proposed procedure eases the implementation of the MGR scheme with Case-U as it minimizes the risk of misspecifying the shift size.

In this paper, we propose a novel zero-forcing (ZF)- based beamforming (BF) scheme for a wireless powered cognitive satellite-terrestrial network (CSTN) operated in the millimeter wave band. Assuming that the satellite and base station are equipped with multiple antennas, we aim at maximizing the sum rate of the CSTN while satisfying the signal-to-interference-plus-noise- ratio requirements for both the information receivers (IRs) and earth stations, the energy harvesting requirements of the energy receivers (ERs), and the secrecy constraints at the ERs. Since the resulting optimization problem is mathematically intractable, we propose a novel multi-beam-based ZF BF scheme to generate beamforming vectors to serve the IRs and ERs. Specifically, the original nonconvex problem is decomposed into two independent subproblems. The first subproblem, which features beam orthogonality constraints, leads to closed form solutions for the beamforming vectors. The second subproblem, aiming at finding the optimal power allocation, is solved via the S-procedure. Finally, the effectiveness of the proposed scheme is demonstrated by simulation results.

In this paper, an inverter composed of semi-floating gate (SFG) transistor and a load resistor was analyzed. Varying threshold voltage $(V_{\mathrm {th}})$ during switching was observed. This dynamic $V_{\mathrm {th}}$ behavior of SFG device is because of the special device structure of SFG transistors. Based on the $V_{\mathrm {th}}$ -programmable behavior of the SFG transistor, a SFG-based GaN high electron mobility transistor was proposed and enhancement-mode was realized with writing-0 into the transistor during every switching operation by simulation.

According to the requirement of stability and safety of power grid and the high-speed construction of power information network, the standardized management mechanism for power grid emergencies based on typical case base updating strategy is proposed. Based on the classification and the level of emergency, the emergency information reporting process is improved. With the design of a standard case framework including basic attributes, feature attributes, processing patterns and evaluation attributes, the case matching mechanism and the case update mechanism is proposed, and the application of H-law algorithm is greatly improves the efficiency of case matching. Typical case base has the advantages of high hit rate and easy expansion, which can be applied in the field of power emergency management.

The electrical degradation behavior in metal oxide thin film transistor (TFT) under negative bias-illumination stress (NBIS) is one of the biggest obstacles for its applications in flat panel display. In order to solve this issue, Sr and N are doped in In 2 O 3 thin film and significantly improve the NBIS stability of In 2 O 3 TFT. In addition, the doping of N can also reduce the degradation in electrical performance caused by Sr doping. The XPS of SrInON thin film is tested to prove the reduction of the oxygen vacancy.

Aiming at the collision avoidance problem of large ships at sea, this paper studies a collision avoidance method that can take into account the difficulty of steering of large ships and the large inertia of motion. According to the KT equation of the ship, its kinematic model is established, and the ship hazard model is established on the basis of fully considering the maneuverability of the ship. The geometrical collision avoidance method is used to quantitatively calculate the ship's speed reduction range or steering range, and the decision is given in conjunction with COLREGS (Convention on the International Regulations for Preventing Collisions at Sea). The experimental results show that this method can solve the collision avoidance problem of large ships in open water area and has high accuracy and reliability.

Event extraction is an important research topic for information extraction. The event extraction technique extracts events of interest from the unstructured information and presents them to the user in a structured manner. Digital Library Promotion Project launched by National Library of China collects public cultural event news released by Chinese public libraries, and this paper presents the method of collecting events from cultural domain news text and propose an approach to discover cultural event automatically. To distinguish cultural news from noisy data and identify the event types, we established a cultural keywords dictionary. For event argument recognition, we adopted pattern matching method. Experimental result valid the method, and a F1 score of 86.43% on average is achieved with cultural event news from 319 Chinese public libraries.

A low-power integrated controllable high-voltage start-up current source for an off-line switched-model power supply chip is presented. The proposed structure features a thick gate oxide MOSFET which is controlled by a voltage sensor. In the supply voltage range of 100-400 V, the sensor can output a steady high voltage. The optimized total area is 0.025 mm$^{2}$, less than 1 % of a 12 W SPMS chip. Under a 100 V supply voltage, the initial charging time and recharging time are 0.12 s and 0.08 s, with the load of a 10 $\mu$ F capacitor in parallel with $\mathrm{a}20 \mathrm{k}\Omega$ resistor, respectively.

This paper proposes a beamforming (BF) scheme with non-orthogonal multiple access (NOMA) for a cognitive satellite-terrestrial network (CSTN), where the satellite network shares the radio frequency bandwidth with the terrestrial network. By assuming that the satellite adopts multicast technology to serve several satellite terminals (STs), while the base station (BS) employs the combination of BF and NOMA to significantly enhance the spectrum efficiency, we aim at maximizing the sumrate of the considered CSTN under the constraints of per-antenna power budget and the quality of service (QoS) requirements for desired cellular users (CUs) and STs. Then, based on the S-procedure and Taylor approximation approach, we present a method to convert the nonconvex problem to a solvable one with linear constraints, and obtain the optimal BF weight vectors through iterative procedure. Finally, numerical results demonstrate the validity and superiority of our proposed scheme.

This paper investigates the secure transmission in satellite communication systems, where a geostationary orbit (GEO) satellite serves an earth station while multiple eavesdroppers attempt to intercept the confidential message. Assuming that only the imperfect channel state information (CSI) of the wiretap channels are available, we propose a secure beamforming scheme to maximize the secrecy energy efficiency (SEE) of the earth station while satisfying the signal-noise-ratio (SNR) requirement at earth station, the secrecy constraints at eavesdroppers, and per-antenna power constraints at satellite antenna feeds. Since the formulated optimization problem is mathematically intractable, we propose a two-stage beamforming scheme to convert the original nonconvex problem into a solvable one and obtain the beamforming weight vectors. Numerical results are finally provided to verify the effectiveness of our proposed scheme.

In this paper, we propose a joint optimization design for a non-orthogonal multiple access (NOMA)-based satellite-terrestrial integrated network (STIN), where a satellite multicast communication network shares the millimeter wave spectrum with a cellular network employing NOMA technology. By assuming that the satellite uses multibeam antenna array and the base station employs uniform planar array, we first formulate a constrained optimization problem to maximize the sum rate of the STIN while satisfying the constraint of per-antenna transmit power and quality-of-service requirements of both satellite and cellular users. Since the formulated optimization problem is NP-hard and mathematically intractable, we develop a novel user pairing scheme so that more than two users can be grouped in a cluster to exploit the NOMA technique. Based on the user clustering, we further propose to transform the non-convex problem into an equivalent convex one, and present an iterative penalty function-based beamforming (BF) scheme to obtain the BF weight vectors and power coefficients with fast convergence. Simulation results confirm the effectiveness and superiority of the proposed approach in comparison with the existing works.

This paper proposes a beamforming (BF) scheme based on multi-objective optimization (MOO) for a cognitive satellite-terrestrial network (CSTN), where the eavesdroppers (Eves) attempt to intercept the private message conveyed to an intended user. By considering that the maximization of achievable secrecy rate (ASR) and the minimization of transmit power can not be achieved simultanesouly, we adopt artificial noise (AN) and apply the weighted Tchebycheff approach to formulate a multi-object optimization problem. Then, by introducing several auxiliary variables, applying semidefinite programming (SDP) and means of Taylor approximation, the original nonconvex MOO problem is transformed into a convex one with a series of linear constraints, and the BF weight vector and AN vector can be obtained. Finally, simulation results are given to illustrate the tradeoff between the conflicting objectives and the superiority of the proposed algorithm in comparison with the commonly used schemes.