Modelling and Simulation of Cognitive Electronic Attack under the Condition of System of systems Combat

From the height of system-of-systems combat and operational perspective, the operations of cognitive electronic warfare (CEW) was analysed, and its main process and links were described. Secondly, the jamming effectiveness evaluation (JEE) model of cognitive electronic attack (CEA) operations was established based on the interference side, in which the change of threat degree was used as the measure index of jamming effectiveness. Then, based on the Q-learning model, an intelligent countermeasure strategy generation (ICSG) model was established, and the main steps in the model were given. Finally, on the basis the JEE model and the ICSG model, the simulation experiment was carried out for CEA operations. The result showed that combining the JEE model with the ICSG model can express the main process of the operations of CEW, as well as proved the validity of these models

Prediction of xylanase optimal temperature by support vector regression

Background: Support vector machine (SVM), a novel powerful machine learning technology, was used to develop the non-linear quantitative structure-property relationship (QSPR) model of the G/11 xylanase based on the amino acid composition. The uniform design (UD) method was applied to optimize the running parameters of SVM for the first time. Results: Results showed that the predicted optimum temperature of leave-one-out (LOO) cross-validation fitted the experimental optimum temperature very well, when the running parameter C, \u190, and \u3b3 was 50, 0.001 and 1.5, respectively. The average root-mean-square errors (RMSE) of the LOO cross-validation were 9.53\ubaC, while the RMSE of the back propagation neural network (BPNN), was 11.55\ubaC. The predictive ability of SVM is a minor improvement over BPNN, but it is superior to the reported method based on stepwise regression. Two experimental examples proved the validation of the model for predicting the optimal temperature of xylanase. Conclusion: The results indicated that UD might be an effective method to optimize the parameters of SVM, which could be used as an alternative powerful modeling tool for QSPR studies of xylanase

Design and Simulation of Small Space Parallel Parking Fuzzy Controller

Based on the nonlinearity and time-variation of automatic parking path tracking control system, we use fuzzy control theories and methods to explore the control rules to improve fuzzy controllers and design an automobile steering controller. Then we build the simulation experiment platform of an automobile in Simulink to simulate the reversing settings of parallel parking. This paper adopts the Mamdani control rules; the membership function is the Gauss function. This paper verifies the fuzzy controller's kinematic model and the advantages of fuzzy control rules. Simulation results show that the design of the controller allows the automobile to stop into the parking space smaller than the space obtained by planning path, and automatic parking becomes possible in the parking plot. The control system is characterized by small tracking error, fast response and high reliability

Expression and non-chromatographic purification of 1,3-propanediol oxidoreductase in Escherichia coli

The gene dhaT from Klebsiella pneumoniae encodes 1,3-propanediol oxidoreductase (PDOR). Thermally responsive elastin-like polypeptides (ELPs) was used as a fusion tag to purify the proteins (PDOR). The ELP gene was attached to dhaT and ligated into the pET-22b vector. Different NaCl concentrations were employed to decrease the transition temperature (Tt) which was diminished as salt concentration increased. The optimal final concentration of NaCl was 1 M and the corresponding Tt was 39.5\ubaC. Enzymatic assays were determined via every step for purification of fusion PDOR. PDOR showed good stability during the purification process, the specific activity in the first and second round of inverse transition cycling (ITC) was 276.1 \ub1 13.3 and 213.3 \ub1 10.8 U/mg, respectively. The ELPs fusion PDOR was superior to histidine tagged PDOR in both yield and activity after the purification

Codon optimization of 1,3-propanediol oxidoreductase expression in Escherichia coli and enzymatic properties

The gene dhaT from Klebsiella pneumoniae encoding 1,3-propanediol oxidoreductase (PDOR) was de novo synthesized by splicing overlap extension polymerase chain reaction (SOE-PCR) primarily according to Escherichia coli's codon usage, as well as mRNA secondary structure. After optimization, Codon Adaptation Index (CAI) value was improved from 0.75 to 0.83, meanwhile energy of mRNA secondary structure was increased from -400.1 to -86.8 kcal/mol. This synthetic DNA was under control by phage T7 promoter in the expression vector pET-15b and transformed into the E. coli BL21 (DE3) strain. Inducers such as isopropyl \u3b2-D-thiogalactoside (IPTG) and lactose were compared by activity at different inducing time. The activity of PDOR after codon optimized was 385.4 \ub1 3.6 U/mL, which was almost 5-fold higher than wild type (82.3 \ub1 1.5 U/ml) under the flask culture at 25\ub0C for 10 hrs. Then his-tagged enzyme was separated by using Ni-IDA column. The favorite environment for enzyme activity was at 5\ub0C and pH 10.0, PDOR showed a certainly stability in potassium carbonate buffer for 2 hrs at diverse temperatures, enzyme activity was significantly improved by Mn2+

Software-Defined Virtual Synchronous Condenser

Synchronous condensers (SCs) play important roles in integrating wind energy into relatively weak power grids. However, the design of SCs usually depends on specific application requirements and may not be adaptive enough to the frequently-changing grid conditions caused by the transition from conventional to renewable power generation. This paper devises a software-defined virtual synchronous condenser (SDViSC) method to address the challenges. Our contributions are fourfold: 1) design of a virtual synchronous condenser (ViSC) to enable full converter wind turbines to provide built-in SC functionalities; 2) engineering SDViSCs to transfer hardware-based ViSC controllers into software services, where a Tustin transformation-based software-defined control algorithm guarantees accurate tracking of fast dynamics under limited communication bandwidth; 3) a software-defined networking-enhanced SDViSC communication scheme to allow enhanced communication reliability and reduced communication bandwidth occupation; and 4) Prototype of SDViSC on our real-time, cyber-in-the-loop digital twin of large-wind-farm in an RTDS environment. Extensive test results validate the excellent performance of SDViSC to support reliable and resilient operations of wind farms under various physical and cyber conditions

Real-time monitoring for road-base quality with the aid of buried piezoelectric sensors

The road-base usually deteriorate during service time due to factors such as cyclical traffic loads and road-base fouling. Currently the monitoring method for road-base quality is quite limited. This paper proposes a real-time Monitoring method for Road-Base Quality (MRBQ) based on a soil dynamic model and piezoelectric sensors buried in road-base. The soil dynamic model was extended with a piezoelectric equation to calculate the voltage in the road-base generated by a moving traffic load. Then, a model test was conducted to measure the output voltage of the piezoelectric sensors buried in the road-base. Finally, the road-base modulus was back-calculated through the soil dynamic model with the measured voltage. The back-calculated modulus was compared with the modulus measured by resonance column test (RCT) to validate this method. The unique relationship between the peak voltage and the road-base modulus at various depths was identified for different traffic load amplitudes and speeds, and the feasibility and accuracy of the MRBQ was demonstrated. This study reveals that the sensitivity of the piezoelectric sensors can reach 2 V/MPa, and the error to measure the road-base modulus is less than 20%. The proposed MRBQ demonstrates a good application potential in health monitoring of transportation facilities

Surface deformation law of mining under thick loose layer and thin bedrock: taking the southern Shandong Mining Area as an example

The surface subsidence in the thick loose layer and thin bedrock mining area in the east of China has the characteristics of large subsidence value, wide movement range and long settling time. Taking a coal mine in Southern Shandong Mining Area as an example,this paper discusses the variation rules of coal seam mining surface deformation parameters under different loose layer and bedrock thickness ratio conditions, on the basis of field measurements, using FLAC3D, and establishes a surface deformation calculation model for coal seam mining under the conditions of different loose layer bedrock thickness ratios (0.25−5.00), studies the characteristics of surface deformation, analyzed the influence of ratio of loose layer thickness to bedrock thickness on the parameters of probability integral method, and quantitatively analyzed and discussed the conditions of thick loose layer and thin bedrock from the perspective of mining subsidence. Research shows: ①Under the same mining thickness conditions,when the ratio of loose layer thickness to bedrock thickness increases, the surface deformation amount obviously increases first and then decrease, when the ratio reaches a certain limit, the ground surface deformation tends to be stabilized; ②The subsidence coefficient, the horizontal movement coefficient and the tangent of the main influence angle all increase first and then decreases, and the inflection point is 1.75,1.25 and 1.25, respectively; ③The proportion of loose bed thickness in the average mining depth has great influence on the angle of draw and boundary angle. The boundary angle and the angle of draw gradually decrease with the increase of the ratio. Based on the above research, it is proposed that the ratio of 1.25−1.75 is the critical value for the condition of thick loose bedding and thin bedrock, which provides a theoretical basis and technical reference for the prediction of surface deformation and the prevention and control of mining subsidence disasters in typical thick loose layer thin bedrock mining areas in eastern China