In order to increase the side-mode suppression ratio of FBGs ( Fiber Bragg Gratings) with high reflectivity and reduce the insertion loss caused by preparation of high reflectivity gratings using femtosecondlaser pulses, we present a processing method based on a combination of a half-wave plate and a Glan prism, anapodized fiber grating with high reflectivity, high side mode suppression ratio, and low insertion loss.By inputting the apodization function model to the host computer, the stepper motor speed can be precisely adjusted in real time, and the half-wave plate position can be mechanically rotated to realize the laser energy distribution along the fiber direction as an apodization function. Finally an apodized fiber grating with adjustable parameters is obtained. The experiment shows that the apodized grating of this method can reach 70% reflectance at 1 550 nm, the side-mode suppression ratio is 20 dB with a full width at half maximum of 0. 35 nm. And the temperature and strain sensing characteristics is tested. The temperature sensitivity is
1. 529*10^-2nm / K, and the strain sensitivity is 1. 61 nm / N. This high-reflectance apodized fiber gratings can be expected to be applied in high-power narrow-linewidth fiber lasers and high-speed accurate sensing demodulation system.

With more and more photovoltaic renewable energy integrated into the power system, the traditional deterministic power flow can not accurately describe the actual operation state of the power system. We present a probabilistic power flow analysis method which combines semi invariant method, Copula theory and Gaussian mixture approximation method. This method overcomes the shortcoming that the existing series expansion method can not approximate the multimodal probability distribution. The mixture of Gaussian, non Gaussian and discrete probability distributions of input bus power is considered. Without using any series expansion method, the probability distributions of multi-mode bus voltage and line power flow with these correlated inputs are obtained accurately. Multi input correlation is considered. The performance of this method is verified in IEEE14 and IEEE57 bus system. Experimental results show that the multi-modal distribution of the expected random variables is accurately established, and the running time of the proposed method is reduced by 76% compared to the Gram-Charlier method.

Aiming at cases of setup and measurement about static work point in experiment circuit, instructive process is provided based on the schematic system structure by soft of Multisim 10 for speeding up the efficiency of knowledge studying. The Multisim soft is easy to learn and use. Students are induced to research the principle of the working circuit actively by parameter adjusting so as to train students to think independently. The results show that students' abilities of analyzing are trained through the process of virtual simulation. The foundation of experiment is built. Student's ability of problem handing is promoted by such a process.

Aiming at the control problem of time-delay in fractional order systems, the Smith predictor fractional order PI(Proportion Integral) control scheme is introduced for a time-delayed systems in case of no eliminating the time-delayed part. Taking into account the stability of the fractional order systems with time-delayed, the Smith predictor control can effective overcome the time delay for fractional order systems. The simple rules of parameter tuning of fractional order PI controller are given, which have certain practical application value. The influence of the order for fractional order system on the system convergence time is analyzed. The numerical simulation results has verified the effectiveness and feasibility of the conclusion.

Gradient distribution exists widely in biological materials. Gradient materials can withstand large forces and thermal shocks and are widely used in high-temperature and high-pressure environments. It is very difficult to make gradient materials by traditional technology. 3D printing technology and experimental equipment for gradient distribution materials including gradient modeling, control systems and printing machinery are designed. Based on the image gray changes, a modeling method for material composition gradient is established. Based on the motion controller, a 6-axis linkage system including X,Y,Z three-dimensional spatial position axes and U,V, and W material extrusion axes is designed. It has functions such as motion trajectory planning and continuous interpolation. Software and hardware of the control system are developed to achieve coordinated control of material proportioning and three-dimensional motion. A 3D Printing mechanism is constructed using piston extrusion, dynamic mixing, and a linear 3D platform design. The developed experimental equipment is used to perform gradient distribution printing experiments using different color materials, and the feasibility of the developed experimental equipment to print gradient distribution materials is verified.

Sowing depth has an important impact on the performance of no-till seeder, it is one of the key factors to ensure the rapid germination. However, the consistency of sowing depth is easily affected by the complex environment of no tillage. The Flex sensor was installed on the inner surface of the gauge wheel at 120° intervals to monitor the pressure exerted by the seeding row unit against ground. The pneumatic spring is used as a down force generator, and its intelligent regulation model is established by Mamdani fuzzy algorithm, which can realize the control of the pressure exerted by the seeding row unit aganst ground and ensure the proper seeding depth.
The working process is simulated based on Simulink, The results show that Mamdani fuzzy model has a good following performace of the pressure change against ground. meet the demand of sowing depth regulation.Experiment results in the field show that, when the working speed is 9 km / h, The control error of the system is 40% lower than that of the passive control, the performance of sowing depth was improved.

In order to solve the problems of noise interference and complex circuit in the process of ECG(Electrocardiograph) signal acquisition, a low cost high precision ECG acquisition circuit is designed. AD8232is used to collect and amplify ECG signals. By using 100 Hz low-pass filter, 0. 05 Hz high-pass filter and 50 Hznotch circuit, the interference attenuation of low frequency and high frequency is 60 dB(tenfold), and the noiseattenuation of 50 Hz is 41. 08 dB. It can effectively filter out the doped common mode interference,myoelectric interference, baseline drift, power frequency interference, etc. , and improve the acquisition accuracy of singlelead EGC. This circuit can be used in home medical monitoring and portable wearable ECG monitoring equipment.

In order to solve the problems of high data density, short response time and the need to identify clusters of arbitrary shapes which are unique to the observed data of marine Argo buoy profiles that need real-time analysis and processing, this paper proposes a low-complexity clustering method which can effectively process data set in a single scan. The algorithm DBIRCH(Density-Based Balanced Iterative Reducing and Clustering Using Hierarchies), by using the new parameter density threshold correction factor, dynamically updates the constraint coefficient subspace threshold which restricts the growth of CF(Clustering Feature) tree. It combines the idea of density correlation to establish CF tree in different neighborhoods and merges several times. Finally,the core CF tree sub-nodes are used as the output of clustering results, which avoids the excessive dependence ofBIRCH (Balanced Iterative Reducing and Clustering Using Hierarchies) algorithm on parameters and can deal with arbitrary shape clusters. It improves the robustness of data processing, the timeliness of processing Argo profile monitoring data and the overall throughput speed of the algorithm. In order to measure the comprehensive performance of the algorithm, real-time monitoring data sets of Argo buoy profiles are used to make multi-group comparative experiments on the algorithm according to different parameters. And different evaluation indexes are used to evaluate the algorithm comprehensively in terms of running time and clustering accuracy. From a global point of view, the algorithm has the best comprehensive clustering performance among three different algorithms:DBSCAN ( Density-Based Spatial Clustering of Applications with Noise ), BIRCH and DBIRCH. The experimental results show that among the three algorithms, birch algorithm has the fastest operation speed, but the lowest accuracy; DBSCAN algorithm has better clustering performance than birch algorithm, but the operation speed is the slowest; the improved dbirch algorithm is slightly lower than birch algorithm, but the clustering accuracy is the highest.

In order to improve the search ability of traditional teaching-learning optimization algorithm, the corresponding quantum version of the algorithm is proposed by integrating principle of quantum computing. In proposed method, two learning mechanisms, teacher self-study and student learning from teacher, are used to search the global optimal solution. The individual uses qubits coding, and the search process is performed on the Bloch sphere. The individual is updated by the rotation of the qubits about axis, and then is decoded into the Bloch spherical coordinates of the qubits. Because the proposed method extends the search of each dimension in the common teaching-learning algorithm to the Bloch sphere, the search process can be more refined, thus enhancing the traversal effect on the solution space. The experimental results show that the optimization ability of this method is not only better than that of common teaching-learning-based optimization algorithm, but also better than that of other classical swarm intelligence optimization algorithms. The results show that the combination of some mechanisms of quantum computing and intelligent optimization can improve its optimization performance.

The leakage acoustic signal of oil and gas pipeline contains large amount of noise. The common denoising algorithms such as wavelet transform, empirical mode decomposition and variable mode decomposition are studied. According to the characteristics of the leakage acoustic signal, referring to the idea of Wavelet-EMD(Wavelet-Empirical Mode Decomposition) algorithm, combining the improved wavelet threshold denoising and variable mode decomposition, a VMD-Wavelet (Variable Mode Decomposition-Wavelet) algorithm is proposed.Four typical signals with noise are used to verify that VMD-wavelet joint denoising algorithm is superior to other common denoising algorithms in output SNR (Signal Noise Ratio) and minimum mean square error. Finally, the VMD-Wavelet algorithm is applied to the actual pipeline leakage acoustic signal denoising. It is found that the VMD-Wavelet algorithm can achieve a high signal-to-noise ratio and a small mean square error for the pipeline leakage acoustic signal under strong background noise.

At present, the opacity of big data interaction and the unreasonable access form of data files lead to the problems of long storage delay and poor security in big data storage. We propose a dynamic secure storage technology of unstructured big data based on block chain. The multi-user rule scheduling model is constructed, the independent row vector and n-order matrix are generated by using the stored data packet, and the storage algorithm is designed based on the probability of column dissatisfaction rank. The public and private keys of block chain asymmetric encryption technology is used to realize transparent and complete data interaction and record the secondary information and data access forms. The distributed file system is introduced, which is effectively combined with Mongo DB non-relational database, and the unstructured big data can be stored safely.The simulation results show that the proposed method has an ideal storage rate, and ensures the integrity of big data. It is effective and practical.

In order to improve the operation parameters and optimize the communication performance of the current communication system, the principle and control simulation experiment method of digital communication system based on Matlab is proposed. The simulation model of digital communication system is constructed, and the basic characteristics of its operation are analyzed. The simulation program of digital communication system is divided into three parts: simulation modeling, experiment and analysis. According to the design interface of communication toolbox in Matlab software, the simulation experiment of Matlab is divided into time flow simulation experiment based on Simulink platform and data flow simulation experiment based on Matlab workspace. The bit error rate of digital signal baseband in transmission process is selected as an example to carry out data flow simulation experiment, and the adaptive antenna research is taken as an example to carry out time flow simulation experiment. The experimental results show that the Matlab tool can adjust the system parameters flexibly in the simulation test of digital communication system, so as to optimize the system operation effect.

To solve the problem of false negative examples and zero loss, the transformer network structure is used to extract the entity description information in the knowledge base. The self attention mechanism with constraints is used to find the representation subspace that can best express the entity meaning to enhance the entity representation ability. The idea of counter generated network is introduced to generate negative samples,which improves the knowledge representation ability. In the construction of the knowledge map of public computer course, this method clearly describes the internal relationship between the knowledge points of the course, which is of great significance for guiding the curriculum setting and schedule arrangement and guiding students to learn.

In order to solve the problem of scientific and technological report evaluation, the index selection and index weight of the competitiveness evaluation index system is proposed. It gives the evaluation formula of the competitiveness evaluation index system of scientific and technological report. According to the designed competitiveness evaluation formula model, combined with the design of the competitiveness evaluation system of scientific and technological report, the competitiveness of scientific and technological report of Jilin Province is realized using computer. The evaluation example proves that the evaluation system can realize the automatic evaluation of a single scientific report or a comparative evaluation of multiple scientific and technological reports,which provides a certain reference value for scientific research project management.

In order to effectively improve the quality and efficiency of video editing in online courses, the practicability of the multimedia production software Edius 6. 5 series is analyzed, and a nonlinear editing technology based on EDIUS6. 5 technology is proposed. Through experiments on the actual course editing and production process, it is pointed out The application methods and skills of non-linear editing technology based on EDIUS6. 5 technology are presented, which provides a good reference value and reference significance for the production of online courses.

In order to improve the precision of remote sensing image for crop prediction and the efficiency of agricultural planting, combined with the innovation and entrepreneurship training program of Jilin University, an experimental project of crop classification algorithm based on satellite remote sensing image is designed. Taking the high-resolution satellite image of Harbin agricultural demonstration base captured by sentinel-2 on July 30, 2018 as the experimental data, the characteristics of rice, soybean, corn and sorghum in the image are extracted and classified by using the maximum likelihood method, support vector machine method and neural network method in different spectral bands ( including red band) , and then the crop classification map is obtained, the statistical results are compared with the real parameters, and then the classification accuracy and reliability of different algorithms are compared. The experimental results show that the neural network method has the highest accuracy and the strongest reliability, and is suitable for nationwide promotion.