bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of chronic dietary grape seed extract supplementation on aortic stiffness and hemodynamic responses in obese/overweight males during submaximal exercise
Authors: Dillon Katherine , Shariffi Brian , Gillum Trevor , Boyer William , Sullivan Sean , Kim Jong‐Kyung
Published: April 2021

We investigated the effect of chronic grape seed extract (GSE) on blood pressure and aortic stiffness (AoS) among overweight and obese males. Systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), heart rate (HR), stroke volume (SV), cardiac output (Q), total vascular conductance (TVC), and AoS were measured during two submaximal cycling exercises (40% and 60% VO2max), after 7 consecutive days of GSE or placebo (PL) ingestion with one week washout period. Compared with PL, GSE supplementation significantly decreased MAP at rest (85 ± 3 mmHg vs. 82 ± 3 mmHg), 40% (102 ± 3 mmHg vs. 99 ± 3 mmHg), and 60% workloads (109 ± 3 mmHg vs. 107 ± 3 mmHg) (P = 0.001, ES = 0.2). AoS was significantly reduced (13.0 ± 1.9 AU vs. 10.2 ± 1.0 AU) at rest (P = 0.002, ES = 0.6). Q was decreased at rest and across all workloads, but there were no significant differences (7.5 ± 0.4 L/min vs. 7.1 ± 0.4 L/min; 20.4 ± 1.2 L/min vs. 19.6 ± 0.9 L/min; 26.3 ± 1.1 L/min vs. 25.5 ± 1.6 L/min, respectively). GSE had no effect on HR, TVC, and SV. Our study indicates that chronic supplementation with GSE reduces arterial pressure at rest and during exercise primarily via the substantial reduction in AoS. Thus, GSE can be a dietary supplement to treat augmented blood pressure responses in obese and overweight males at rest and during exercise.

Trial registration: ClinicalTrials.gov identifier: NCT04465110.
Numerical analysis of motional mode coupling of sympathetically cooled two-ion crystals*
Authors: Du Li-Jun , Meng Yan-Song , He Yu-Ling , Xie Jun
Published: April 2021

A two-ion pair in a linear Paul trap is extensively used in the research of the simplest quantum-logic system; however, there are few quantitative and comprehensive studies on the motional mode coupling of two-ion systems yet. This study proposes a method to investigate the motional mode coupling of sympathetically cooled two-ion crystals by quantifying three-dimensional (3D) secular spectra of trapped ions using molecular dynamics simulations. The 3D resonance peaks of the 40Ca+–27Al+ pair obtained by using this method were in good agreement with the 3D in- and out-of-phase modes predicted by the mode coupling theory for two ions in equilibrium and the frequency matching errors were lower than 2%. The obtained and predicted amplitudes of these modes were also qualitatively similar. It was observed that the strength of the sympathetic interaction of the 40Ca+–27Al+ pair was primarily determined by its axial in-phase coupling. In addition, the frequencies and amplitudes of the ion pair’s resonance modes (in all dimensions) were sensitive to the relative masses of the ion pair, and a decrease in the mass mismatch enhanced the sympathetic cooling rates. The sympathetic interactions of the 40Ca+–27Al+ pair were slightly weaker than those of the 24Mg+–27Al+ pair, but significantly stronger than those of 9Be+–27Al+. However, the Doppler cooling limit temperature of 40Ca+ is comparable to that of 9Be+ but lower than approximately half of that of 24Mg+. Furthermore, laser cooling systems for 40Ca+ are more reliable than those for 24Mg+ and 9Be+. Therefore, 40Ca+ is probably the best laser-cooled ion for sympathetic cooling and quantum-logic operations of 27Al+ and has particularly more notable comprehensive advantages in the development of high reliability, compact, and transportable 27Al+ optical clocks. This methodology may be extended to multi-ion systems, and it will greatly aid efforts to control the dynamic behaviors of sympathetic cooling as well as the development of low-heating-rate quantum logic clocks.
A new method for measuring complex relative permittivity of dielectric material by reflection method
Authors: Qin Yao , Wei Bin , Liu Shuo , Li Mingxing , Cai Chengxin , Hou Tiangang
Published: April 2021

In this paper, a new lossless free space method for measuring the complex relative permittivity of dielectric material by reflection method is presented. When this method is used to measure the complex relative permittivity of dielectric material, there is no multi-value problem. The measurement system used in this method consists of a horn lens antenna and a vector network analyzer(VNA). In this paper, HFSS microwave simulation software is used to simulate the complex relative permittivity measurement method proposed in this paper. The simulation results show that this method can accurately measure the complex relative permittivity of dielectric material.
Numerical simulation study of free space method for measuring sample permittivity
Authors: Qin Yao , Liu Shuo , Wei Bin , Li Mingxing , Cai Chengxin , Hou Tiangang
Published: April 2021

The composition and performance of the material can be expressed by the permittivity. The paper introduces the measurement principle of free space method and TRL calibration principle, the calculation formula of the sample permittivity is theoretically analysed, a horn lens antenna is designed to simulate the emission of plane waves, and numerical simulation software is used for simulation and optimization. In the working frequency range, the voltage standing wave ratio of the antenna is less than 1.49, and the maximum gain is 21.8dB. A free space measurement system is established in the software to measure the sample permittivity with different thicknesses, and compare the calculated value with the actual value. The results show that the root mean square error of the real part is less than 5.3%, and the root mean square error of the imaginary part is less than 1.3%. The correctness and applicability of the formula for calculating the permittivity are also proved.
Optimal economic dispatch of microgrid based on chaos map adaptive annealing particle swarm optimization algorithm
Authors: Dai Xufan , Lu Kui , Song Dan , Zhu Zheng , Zhang Yongle
Published: April 2021

This paper adds chaos optimization based on adaptive annealing particle swarm optimization algorithm, which improves the global convergence ability and makes up for the shortcomings of traditional PSO algorithm, which is easy to fall into local optimization in addition, this paper adds simulated annealing operator, improving the diversity of better population. In addition, the micro source of microgrid is modeled, and the constraints of the model are set. The fitness of the optimized algorithm is compared with the traditional algorithm, and the objective function involved in microgrid dispatching is taken as the application layer. Finally, through data analysis, the effectiveness of the optimization algorithm for microgrid optimal economic dispatching is confirmed.
The research on notch filtering and spectral filling for RFI suppression
Authors: He Yinguang , Gao Fei , Gong Ziyi , Dang Hongxing , Tan Xiaomin
Published: April 2021

Radio frequency interference (RFI) suppression has become an essential step in synthetic aperture radar (SAR) imaging processing. In this paper, a spectral filling filtering method for RFI suppression referred to notch filter is derived and analysed. The derivation results show the reason for the “residual terms” after suppression processing in frequency domain and the influence of the “residual terms”. And a conclusion is drawn: the essence of interference suppression based on spectral filling filter is the dynamic change process of “residual terms”. Since they cannot be completely eliminated in theory, they will affect the image quality after interference suppression, but the effect of spectral filling method is better than that of the notch filter method. The conclusion is verified by the simulation experiment.
Torque ripple minimization for PMSM considering harmonic magnet flux phase
Authors: Guo Honghao , Cao Rui , Lin Xinxin
Published: April 2021

Due to the existence of cogging torque, magnet flux harmonics and inverter dead time, permanent magnet synchronous motor (PMSM) has torque ripple during operation, which limits its application in high-precision situations. Stator current optimization is an easy-to-apply and accurate torque ripple suppression approach. However, existing methods fail to consider the effect of magenet flux phase angle on optimal current calculation. In this paper, a torque ripple minimization method considering harmonic magnet flux phase is presented, which uses torque waveform of an electric angular period as the optimization object. By deducing the electromagnetic torque model considering harmonic magnet flux, the torque is expressed as a dense sequence. Based on this, the objective function including torque ripple and losses minimization is constructed and optimized by genetic algorithm (GA) to obtain the optimal harmonic current. Experiment results show that the proposed approach can calculate the optimal harmonic current accurately and suppress the torque ripple effectively.
Research on live detection technology of cable joint defects based on high-speed light sensing and pressure wave method
Authors: Zhaoguo Wu , Weisheng He , Haibing Zhang , Bangfei Deng , Qian Wang , Hong Xiang , Zhaoguo Wu
Published: April 2021

With the widespread application of stable high-voltage power cables, cable failures have gradually become the main source of major accidents in the process of power transmission. The most easily damaged part is the cable joint. Since the cable joints are made on site, it is easy to introduce high-voltage cable defects and cause insulation failures. Therefore, the defect detection of high-voltage voltage joints is particularly important. In order to promote the process of urbanization, ensure people’s life quality and personal safety, the popularization of high-voltage cables is an inevitable trend. However, difficulties will be encountered in the detection of cable joint faults. To improve the detection efficiency, relatively extensive research has been carried out on the detection of high-voltage cable joints at home and abroad. Based on the high-speed light sensing and pressure wave method, the online detection method of cable joint defects proposed in this paper has accurate, fast, convenient and non-contact online detection features.
Analysis of Practical Application of PLC Technology in Electric Automation
Authors: Zhao Guohua , Zheng Hui
Published: April 2021

With the continuous development of science and technology, PLC technology has been applied in many industries. This also includes electrical automation control, which can better maintain the accuracy and stability of electrical automation control, and its development prospects are very broad. This article summarizes the application significance and advantages of PC technology in electrical automation control based on previous work experience. The author discusses the practical application of PLC technology in electrical automation from six aspects: air conditioning, coal mining, numerical control, transportation, power systems, and lathe electrical control systems.
Risk Assessment of Power Systems Considering CVaR
Authors: Yu Jin , Wang Xingang , Yu Zhongping , Xi Dongsheng , Chen Mengdi
Published: April 2021

In view of the randomness of component fault and load, considering the deficiency of traditional single reliability index, this paper introduces the Conditional Value-at-risk method based on Monte Carlo simulation, and constructs the probability model of risk assessment considering the forced outage rate of unit and line. In order to quantify uncertainty caused by random factors, the value-at-risk and conditional value-at-risk of power system security was proposed and used as a grid security index in the model combined with reliability index, which can accurately describe secure operation level in power system under different operation parameters, and reflect the severity of the accident and weakness and the grid, for further research on safe operation of power system to offer reference and decision-making basis.
A single-winding BSRMWR direct instantaneous torque control and direct levitation force control method
Authors: Xiang Yu , Yang Yan , Liu Chengzi , Liu Zeyuan
Published: April 2021

The stator and rotor of the bearingless switched reluctance motor are both double salient pole structures, when the traditional current chopping control method is used, the torque and levitation force of the motor will have large fluctuations. To solve this problem, this paper studies a direct instantaneous torque control and direct levitation force control (DITC&DFC) method suitable for single-winding bearingless switched reluctance motors. This method takes the instantaneous torque and the instantaneous levitation force of the motor as the directly controlled object, eliminates the current loop, and simplifies the control algorithm while suppressing the fluctuation of the motor torque and levitation force. A 12/8-pole singlewinding bearingless switched reluctance motor with wide rotor teeth drive system is constructed, the Matlab/Simulink system simulation verifies the effectiveness and feasibility of the method.
Soft Start Strategy of Power Electronic Transformer based on Energy Feedback
Authors: Yu Jimin , Nie Chuanjie , Xiong Fei
Published: April 2021

There are a large number of capacitors in power electronic transformer (PET). If PET is started by conventional closed-loop control directly to establish DC capacitor voltage, the over-current that may lead to device damage may be caused. To solve this problem, a soft start strategy of PET based on energy feedback is proposed. In this strategy, the DC capacity of the low voltage side is moderately overcharged at first, and then part of the energy is fed back to the high voltage side to make the voltage of the high voltage DC side reach the reference value. Finally, the CHB is allowed to enter the closed-loop control, thus completely eliminating the impulse current of the AC side. This method avoids the complex parameter design process, and completely relies on the theoretical model rather than experience to guide the design of the process of soft start. Simulation results verify the feasibility and effectiveness of the proposed method.
Research on current harmonic suppression of PMSM based on mathematical morphology
Authors: Cheng Zhihua , Kan Kun
Published: April 2021

Due to the existence of power converter dead time, flux harmonics and other nonlinear factors, the motor phase current contains a large number of high-order harmonics, so the electromagnetic torque generated by the interaction of current and flux also contains various orders of harmonics. In order to eliminate current harmonics, mathematical morphology filter is proposed to suppress current harmonics. However, the single-scale morphological filtering has shortcomings in preserving information details. In order to make up for the deficiency of the traditional single-scale morphological filtering in preserving information details, a weighted multi-scale mathematical morphology method is proposed to suppress the current harmonics.
New feed-forward control strategy of single-phase grid-connected inverter
Authors: Cao Ziheng , Zhou Shaoping , Wu Di
Published: April 2021

Traditional proportional feed-forward strategy can well restrain harmonic disturbance from grid background, but in the weak grid, positive feedback channel and grid-connected current inner-loop are coupling with each other by grid impedance, and robustness is substantially decreased. According to the above situation, a kind of new feed-forward control strategy is proposed, and adding more resonant link on positive feedback channel of point of common coupling voltage to change full pass characteristics of positive feedback channel which only make positive feedback channel have feedback effect on the frequency of main grid background harmonics. Inverter can both have great robustness and harmonic suppression ability in weak grid. In the end, the effectiveness and correctness of proposed control strategy is verified by the simulation model of single-phase grid-connected inverter.
Development of integrated spectral sun-photometer based on embedded Linux OS
Authors: Zhaoyang Qi , Fengying Sun , Jianyu Li , Wenyue Zhu , Wenqing Xu , Gang Xu , Yao Huang
Published: April 2021

Accurate detection of solar irradiance has important application value for theoretical research on climate change and atmospheric analysis, so this paper proposes the integrated spectral sun-photometer to enrich methods of obtaining the solar irradiance and entire atmospheric transmittance. With the ARM microprocessor as central processing unit and Linux OS as the software platform, the two-dimensional turntable and grating spectrometer are combined to construct sun-photometer which can measure continuous wavebands. This article advances the solution scheme to realize data transmission between microcontroller and turntable through CANopen communication. Meanwhile, the spectrometer based on USB communication protocol is used to obtain spectrum from visible to near-infrared band. In addition, both the multiple task operating system Linux and application framework Qt are employed to design friendly user-interface and display real-time process images, which would simplify and integrate the solar radiometer. After Langley calibration is used to calculate the constants to achieve calibration of instrument in spectral band, measured data of the radiometer and results of the DTF solar radiometer are compared and analysed, which confirms the reliability of integrated sun-photometer.
Differential evolution algorithm based on entropy weight method to determine the weight to optimize the configuration of wind, solar, and diesel microgrid
Authors: Xing Yongchen , Duan Qing , Zhang Guobao , Ma Chunyan , Liu Wen Long
Published: April 2021

In order to enhance the stable operation of the multi-energy complementary microgrid for wind, solar, and diesel storage, reduce operating costs, and solve the problems of large randomness, low accuracy, and slow convergence of traditional microgrid optimization multi-objective decision-making, a differential evolution based on the entropy weight method to determine the weight is proposed. Firstly, we establish a microgrid integrated energy model from the perspectives of system operation stability, economy and environmental protection; combined with the Pareto optimal solution set, multi-objectives are weighted according to the entropy weight method, and the multi-objective optimization problem is transformed into single-objective optimization The problem is to avoid artificial setting of weight factors; the calculation example shows that this method is more economical and reasonable in optimization results, and provides an economic, reliable and environmentally friendly microgrid configuration strategy for users to increase power capacity.
Research on Information Coding of Smart Substation Facing “Two Networks Convergence”
Authors: Chen Pan , Xiao ZhiHong , Yan Peili , Feng Teng , Wang Xiaoming , Wang Liang
Published: April 2021

With the popularization and application of “Internet of Things” technologies such as equipment online monitoring and intelligent inspection in the field of substation operation and maintenance, the number of subsystems in smart substations has increased rapidly, and the types of information and the amount of information have shown explosive growth. However, due to disorder and irregular expression, the potential value of a large amount of information is difficult to be effectively used. This paper proposes a “system code-device code-information code” information coding technology that serves the operation and maintenance of information equipment to make information orderly and standardized. This technology lays the foundation for quickly and accurately finding the required information, fully mining and effectively using the value of information, strengthening information fusion between subsystems, and realizing digital management and control of substation equipment information.
Research on Aging and Burning Performance of AC 380V ZR-YJV Cable Insulation sheat
Authors: Chen Minjiang , Liu Yang , Jiang Lingao , Huang Zhidong , Liu Yang
Published: April 2021

Carrying out research on the aging and burning performance of cable insulation sheath is an important means to prevent cable fires. The thermal aging test box, cone calorimeter and synchronous thermal analyzer were used to study the effect of thermal aging on the combustion performance of AC 380V ZR-YJV cable insulation sheath. The results show that in the early stage of thermal aging of the cable, the ignition time of the YJV cable insulation sheath material gradually increases; compared with unaged cables, the ignition time of cables being aged for 15 days has increased from 8 seconds to 57 seconds while the initial peak value of the heat release rate of the cable decreased from 123 kW/m2 to 22 kW/m2. A large amount of easily decomposable additives in the early stage of thermal volatilized from aging cable sheath may be responsible for the reduction trend of the ignition and fire occurrence of the cable insulation sheath. And for the condition of the aging time increasing, the ignition time decreases from 57s to 32s, and the heat release rate will increase from 22 kW/m2 to 85 kW/m2 in which the ignition and fire trend of the cable insulation sheath increase.
Research of Coal Mining Safety Evaluation on Roughset-Svm
Authors: Zhao Zhen
Published: April 2021

Through the impact of fully mechanized coal mining face security personnel, equipment, operating environment and the analysis of geological environment, the establishment of a fully mechanized coal mining face safety evaluation index system is presented based on rough sets - Support Vector Machine fully mechanized coal mining face Safety assessment model. Model application method of rough set evaluation index system of attributes, eliminate redundant attributes, thus reducing the input of SVM learning sample dimension. On this basis, the use of SVM regression nonlinear characteristics was evaluated, and the final example shows the applicability of this model.
Learning BiLSTM-based Embeddings for Relation Prediction in Temporal Knowledge Graph
Authors: Ma Sixia , Li Aiping , Zhao Xiaojuan , Song Yichen
Published: April 2021

At present, as the knowledge graph continues to increase, problems such as incomplete information in the graph also emerge, mainly reflected in the lack of links between entities [1], and the current commonly solution is to learn their representations that can represent more semantic information for the entities and relations in the graph. This article focuses on the temporal knowledge graph (TKG), consistent with the goal in the static knowledge graph, this paper tries to propose a better representation learning method to solve the link prediction problem. According to the time information in the temporal knowledge graph, the paper constructs a bag of words about time, uses the bag of words model to decompose the time in the temporal knowledge graph into sequences, and learns its semantic information together with relations and entities. The embeddings obtained in this way can learn more semantic information. In addition, proving the effectiveness of the model through experiments on the currently commonly used temporal knowledge graphs.
An exponential smoothing channel estimation method for MIMO-OFDM system
Authors: Yan Guo , Sheng Su
Published: April 2021

In order to solve the problem of inaccurate channel estimation of least square (LS) algorithm for multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system under time-varying channel, a novel channel estimation method using exponential smoothing algorithm (ESA) is proposed in this paper. Based on LS estimation algorithm and ESA theory, the proposed method fully exploits the variation law of time-varying channel, adopts the predicted results of the previous time to predict the estimation value of the current time by iterative computations, and utilizes the low-pass character of the ESA equivalent filter to reduce the random disturbance. Therefore, the additive white Gaussian noise (AWGN) existing in LS algorithm is effectively suppressed and the estimation accuracy is further improved. Simulation results show that, compared with the traditional channel estimation approaches, the proposed method can provide high estimation accuracy with low computational complexity, especially under time-varying channel and low SNR conditions..
Research on the method of multi-station integrated data center module location based on fuzzy analytic hierarchy process
Authors: Chen Zhuo Lin , Yin Yuan , Lin Xiao Ning , Sen Li Yang
Published: April 2021

Internet data center module(IDC) is an important part of the multi-station integrated substation, and its site selection will be an important basis for the site selection and construction of the multi-station integrated substation. In order to be useful to the practical engineering, the fuzzy analytic hierarchy method is proposed to analyze the location of IDC. There are six factors influenced in total which land price, policy environment, the annual average temperature, industrial electricity, network environment and peer development. FAHP has been adopted for calculating and sequencing priority membership value for every single factor thoroughly. According to the factor, different priority location has been chosen. Finally, based on the fuzzy analytic hierarchy process, the paper proves the effectiveness and convenience of the site selection method, through analysis of the three regions.
Research and Realization of Grouping Collection Algorithm of Infrared Cage Heating Circuit for Spacecraft Vacuum Thermal Test
Authors: Dong Hao , Xie Jihui , Liu Yang , Shen Bin
Published: April 2021

In the process of spacecraft thermal test, the infrared cage is mainly used to simulate the heat flow outside the space. In the design, the infrared cage is divided into several heating zones corresponding to the spacecraft. The heating strip of the infrared cage is divided into heating circuits, the heating circuits are grouped and collected, and the infrared cage heating node table is defined as an important basis for controlling the infrared cage. At present, there is a single method of grouping and gathering heating circuits, which is mostly limited by manual adjustment based on experience and lack of automation. In order to solve the shortcomings of the existing technology, this paper adopts the genetic algorithm hybrid BFD based on reinforcement learning to group and collect the heating circuits, and optimize the design results according to the constraints. The user interaction interface is designed to facilitate the user to do further analysis. Thereby improving the level of business automation, optimizing working procedures and reducing costs.
Research on Person Reidentification Method Fusing Direction Information in Multi-camera Pedestrian Tracking Problem
Authors: Liu Junliang , Shi Xiangbin
Published: April 2021

In multi-camera pedestrian tracking, pedestrian apparent features are usually used to solve the problem of cross-camera reidentification. In order to make the pedestrian apparent features robust to the directional changes of pedestrians in different cameras. In this paper, a pedestrian feature extraction method combining directional features is proposed by using deep network Resnet 50. Pedestrian feature extraction network is trained by adding pedestrian direction information. in order to improve the performance of person reidentification model, BNblock structure is added in the design, a batch normalization (BN) layer is added after the feature to get the normalized feature. It can make the triplet loss converge with the convergence of the ID loss, thereby improving the performance of the model. The proposed method was verified on DukeMTMC and Market-1501 data sets, and the results show that the pedestrian appearance features combined with direction information proposed by the pedestrian reidentification algorithm can significantly improve the reidentification accuracy. By adding BNblock into the network structure, the accuracy can be further improved.
Electromagnetic analysis for complex satellite targets using time-frequency representations
Authors: Sun Xumin , Guan Yongsheng
Published: April 2021

An analytical method for electromagnetic scattering characteristics of complex satellite targets by using multilevel fast multipole algorithm (MLFMA) and short-time fourier transformation (STFT) is proposed in this paper. By constructing different electromagnetic models of satellite target with multi-scale structures and coatings, the aspect and polarization characteristics of radar cross section (RCS) and time-frequency representation (TFR) are studied. To validate the influence of the multi-scale structure and coating, the full-polarization RCS at specific angles, RCS statistical characteristics and TFR correlation are simulated and compared. It is concluded that the multi-scale structures and coating materials should be sufficiently considered to calculate the accurate scattering characteristics.
Research and Improvement of Multi-granularity Method for Pedestrian Tracing System
Authors: Ni Ruixuan
Published: April 2021

In the field of video surveillance, with the continuous development of the Internet and artificial intelligence, the related technology for single device has been very mature, but how to accurately realize pedestrian tracing under cross-devices is still an active research field. In this paper, a multi-granularity pedestrian traceability method is proposed, which is based on the attribute extraction of pedestrian image and the person re-identification algorithm based on attention mechanism retrieves the same pedestrian image cross a lot of devices. The results show that the video surveillance system has good performance, which reduces the occurrence of tracking loss, and the track is visualized at the platform.
Research on Optimization Algorithm of auto-encoding neural network applied to rolling bearing fault diagnosis
Authors: Shi Shi , Tong Qingbin
Published: April 2021

Real time, fast and batch processing of vibration signals has become a future development trend in the field of fault diagnosis, but data dimensionality disasters may arise. In view of the long running time of deep learning in the case of large samples, the gradient descent method and its variant algorithms are introduced for the loss function optimization problem, and the approximate optimal solution is solved in an iterative manner. The gradient descent method is used to minimize the loss function, and the research is carried out on the basis of MATLAB program implementation. The gradient descent method and its variant algorithm are applied to the rolling bearing fault diagnosis model for analysis. By comparing the algorithm’s convergence speed, loss value and accuracy of the rolling bearing fault diagnosis model, a relatively good optimization algorithm suitable for the rolling bearing fault diagnosis model is determined.
Channel Power Allocation Optimization Based on Water-filling Algorithm in 5G
Authors: Wei Song , Zheng Zige , Wu Chenwei
Published: April 2021

Since entering the information age, the popularity of mobile communication has become higher and higher, and people’s requirements for communication quality are also increasing, but the channel resources that people can control are limited. This paper proposes an optimization algorithm for channel resource allocation based on water-filling algorithm. Some improvements have been made on the basis of the original water-filling algorithm. The sgn function is used to optimize the transmit interference temperature limit (Sk), so that the screening result is not completely dependent on Sk, which improves the flexibility of channel screening and effectively optimizes the capacity of the communication network.
Research on Penetration Path Planning Method on Near Sea Bottom Based on the Sonar Detection Blind Zone
Authors: Yong-qi Gao , Peng Wang , Wei-qiang Ma
Published: April 2021

To improve the survivability and penetration probability of unmanned undersea vehicle(UUV) on near sea bottom combat missions, the factors leading to sonar detection blind zone are analyzed, and the detection blind zone produced by underwater terrain obscuration is mainly studied. A detection range calculation method based on DEM and acoustic ray is proposed, and the simulation study of the near sea bottom penetration path planning is carried out by using terrain blind zone and invasive weed optimization algorithm. Simulation results show the effectiveness of the proposed algorithm. This method can be applied to path planning of the UUV on near sea bottom penetration, which helps to improve Combat effectiveness and Operational effectiveness of UUV.
Design of Three Variable Camera Lens Control Circuit Based on C8051F311
Authors: Zeng Ziqiang , Wang Yuhan
Published: April 2021

A three variable lens control circuit based on C8051F311 is designed to solve some problems at the scene such as low precision or difficult quality control. In this system, the C8051F311 is used as the control, first a PWM signal is output, then the PWM signal through a RC filter circuit, finally through a signal processing circuit composed of comparator chip TL064 and amplifier IC TDA2030A to control the brushless DC motor, based on above all, the control of the lens is realized. At the same time, the circuit parameters are designed by using Multisim to simulate the circuit. The practice shows that the system has simple structure, convenient speed regulation and stable operation.
The early prediction of AD evolution based on Trusted-LGBM
Authors: Hao Pan , Li Jiyun
Published: April 2021

In order to achieve the purpose of early diagnosis of Alzheimer’s disease, this study uses machine learning technology to process 14,659 original data from the public data set ADNI. First use the KNN algorithm to fill in the null value. Then a feature transformation method is proposed to transform regression problems into classification problems. Then this study calculates the trust level of each sample based on the feature correlation and the weight of null value, and proposes an improved LightGBM algorithm-Trusted-LGBM. Finally, the prediction results of the Trusted-LGBM algorithm are compared with SVM, XGBoost, and the unimproved LightGBM algorithm. The experimental results show that the Trusted-LGBM algorithm proposed by this research has a higher Fl-score (0.784) and AUC (0.91). It can be seen that the method proposed in this study can more effectively support the early diagnosis of Alzheimer’s disease.
Software-based online self-testing using bounded model checking for 3D network-on-chips
Authors: Ji Pengfei , Zhang Ying , Jiang Jianhui
Published: April 2021

Online testing has become essential for the reliable operations of manycore systems using three-dimension (3D) network-on-chip (NoC) fabric. This paper presents a software-based online self-testing solution using bounded model checking (BMC) for 3D NoCs. The proposed method implements BMC on the extended finite state machine of the 3D NoC and extracts leading sequences to triggerinternal functions. Next, it detects structural defects in each function activated by the leader sequence using constrained ATPG. Finally, it effectively organizes packets to test the 3D NoC and reduce test cost. Experimental results demonstrate that the proposed method achieves high fault coverage online with extremely lower test cost and outperforms existing methods.
Discussion on The Data Extraction Strategy Of FAQ System Based On Chat Records
Authors: Li Jia , Chen Xin
Published: April 2021

Q&A data based on chat records have one characteristic: customers ask, service answers. There is a large amount of knowledge between the questions and answers of customer service. By optimizing the Q&A extraction algorithm to extract knowledge, a very excellent Q&A library can be constructed, thus the accuracy of FAQ system is greatly improved. By analyzing the existing data, this paper cnosiders the extraction strategy of question answering from machine learning and non-machine learning respectively. Then We compares their performance from three aspects of precision, recall and Fl-score according to their different characteristics. In order to ensure the best classification performance, grid search and K-fold crossover are also used to test the optimized classifier performance. After selecting the optimal data extraction strategy, We developed a FAQ system use this strategy, the system results show that the performance is reliable.
Research on Movie Recommendation Algorithm Based on Stack De-noising Auto-encoder
Authors: Wang Lihong , Song Xiaoming , Cong Wanjuan
Published: April 2021

Focused on the problems that the randomness of the noise-adding operation in the de-noising auto-encoder (DAE), and the data matrix does not consider the impact of trusted users on the deep preferences of target users, this paper proposes a recommendation algorithm based on stack de-noising auto-encoder (SDAE) which integrates the preferences of trusted users. Firstly, the score vector is used as the input of the auto-encoder, and the mask vector is designed to train the potential preference of the target user. Secondly, the deep preference of the target user and the trusted user is obtained by the weighted fusion of the features of the two hidden layers of the auto-encoder. Thirdly, in order to reduce the impact of noise on the prediction accuracy, the cascaded auto-encoder model is constructed and trained according to the greedy training method layer by layer training. Finally, SDAE model is compared with other models on different data sets. The experimental results show that SDAE model has better recommendation performance.
Load-balanced routing algorithm for Network-on-Chip employing fair arbiter
Authors: Liu Lu , Yang Yanfei , Lei Qianqian , Wang Huhu , Lixun Song
Published: April 2021

Balanced load is one of the most important performance metrics for on-chip communication. To design flexible, adaptive load-balanced routing algorithms, an arbiter that alternated the priority order fairly is employed. With fair arbiter to decide the routing path for network-on-chip, balanced load can result in performance improvement in speed and capacity for both congestion-oblivious and congestion-aware routing schemes.
A deep learning model S-Darknet suitable for small target detection
Authors: Yang Miao , Shi Xiangbin
Published: April 2021

In order to solve the problem of low accuracy of small target detection in target detection, a small target detection model S-Darknet is proposed. The algorithm is designed based on the Darknet-53 network. First, a new backbone network is proposed, which fully extracts the feature of small objects and adapts to multi-scale detection. Then, in order to enhance the feature information of the target after the fusion, a feature enhancement module is added before each upsampling. Finally, the proposed algorithm was verified on the VOC2007, VOC2012 data sets and the actual data sets of railway freight locks. Experimental results show that this method has high detection accuracy under the premise of ensuring real-time performance.
Research on injection speed control algorithm of oral anesthesia booster based on dynamic pressure detection
Authors: Li Jingdong
Published: April 2021

Oral anesthesia booster is an automatic injection system that replaces manual precise injection and solves the problem of abnormal pain caused by traditional oral anesthesia injection. Through the analysis of the system composition and model, it is determined that the pressure at the output end of the motor collected by the system in real time mainly reflects the load torque of the motor, so as to obtain the dynamic pressure detection method. According to the results of comparison with the high and low pressure thresholds, the oral anesthesia booster is controlled to select an appropriate injection speed mode. In addition, the pressure detection process is described, and the dynamic characteristics of the system are simulated and analyzed, which proves that the speed response of the system is timely after the dynamic pressure changes. The system can automatically alarm for obstruction or leakage according to the monitoring results, remind the doctor to correct the pressure and needle insertion position applied to the handle, so as to maintain the most rational needle insertion position and pressure, reduce the patient’s pain, and improve the comfort of treatment.
Research on 3D global path planning technology for UUV based on fusion algorithm
Authors: Hu Zhiyuan , Wang Zheng , Yin Yang
Published: April 2021

Aiming at the global path planning problem of unmanned underwater vehicle (UUV) in three-dimensional environment, a fusion algorithm named PACO based on particle swarm optimization (PSO) and ant colony optimization (ACO) is proposed. In order to meet the needs of three-dimensional path planning, the grid method is used to model the actual marine environmental data. Besides, PSO and ACO are optimized respectively. Taking the path length as the measurement index, the simulation is realized by using MATLAB. The simulation results show that the initial path search ability of the fusion algorithm is significantly improved, and the effectiveness of the algorithm is verified.
Application of parameter estimation in Logistic model
Authors: Zhao Jing , Wu Gang , Zhang Fan , Zhang Xuan , Wang Haitao , Cao Xinyu
Published: April 2021

Firstly, Logistic model and parameter estimation are simply introduced. Secondly, we make some analysis and summary of various methods of solving Logistic model estimation, which have been put forward by scholars in recent years. These methods include: using Logistic model’s integral form, linearization, optimization method, numerical method, grey system dynamic model, population model to solve the modeling parameter identification method. What’s more, the practical applications of Logistic model are introduced such as the application in the process of urbanization.
Research on Computer Intelligent Proofreading System of Improved English Phrase Translation Model
Authors: Zheng Hairong
Published: April 2021

When carrying out English translation based on phrases and sentence patterns, the contextual coherence of phrases and sentence patterns is relatively poor, which will directly affect the effect of English translation. In the process of designing and improving the English translation computer intelligent proofreading system, we need to study the specific modules of the system design. At the same time, we need to improve the design level of the English translation computer intelligent proofreading system based on the improved phrase translation model. Only in this way can it be ensured that vocabulary can be proofread when translating English, and the translation effect can be improved. This is also the main goal to realize the design of an intelligent proofreading system for English translation. In the process of analyzing and researching the proofreading system, we need to analyze and compare the accuracy of the design system and proofread the incoherent context in the English translation results in time. This can give full play to the advantages of the intelligent angle system with high accuracy and contextual coherence.
Research on operation characteristics of UHV converter valve hall based on intelligent image processing and 3D modeling technology
Authors: Shiling Zhang
Published: April 2021

There are many power equipments in the UHV valve hall, including the converter transformer, converter valve tower, all kinds of bushing, tubular bus. The operation condition monitoring of the above main equipment mainly includes electrical performance parameter measurement, oil and gas insulation medium performance parameter measurement and other means. This paper mainly introduces a monitoring method for the operation status of converter valve hall from the perspective of image processing technology. The technology mainly includes: 1) the application of intelligent image processing technology to identify and classify the database of infrared thermal imager and ultraviolet imager; 2) the real-time on-line measurement for the insulation distance of typical fittings through Kalman filter technology, including the measurement of the hottest temperature The insulation distance between partial discharge point and zero potential grounding point; 3) the electric field simulation model of typical main equipment in valve hall is established based on three-dimensional modeling technology of finite element method, and the surface electric field distribution of key main equipment fittings is obtained. Combined with the image database information, insulation distance information and typical main equipment electric field distribution information, the operation state parameters are effectively obtained, and the intelligent algorithm is applied to automatically evaluate its operation state, discover the latent fault and locate the positive fault, so as to provide effective data support and the protection strategy for the main equipment operation and maintenance.
Data Processing and Analysis Flow of Internet of Things System
Authors: He XiaoPing
Published: April 2021

The data processing and analysis flow of Internet of things system is the basic process of system design ideas and methods. It includes a series of operations such as requirement analysis, software function design, algorithm and method of implementation, overall structure design, module design, coding and debugging, program linking and testing, compilation and submission of the system. Data processing and analysis process can meet the needs of the system, and solve the problem of the main content of the process. This paper discusses the basic mechanism, principle, type and application of data processing of Internet of things, discusses the composition and elements of data analysis system of Internet of things, and explains the construction process and analysis process and steps of data processing of Internet of things.
Poor University Students Management System Based on Web
Authors: Zhou Tuo , Liu Defang
Published: April 2021

Combining with the actual work of the poverty aid management in F University, this paper analyzes the work flow of the poverty aid management in University, designs and develops the Poor University Students Management System. The system uses web architecture mode, JSP programming technology and SQL Server database management technology. The system is composed of four modules: system management module, institute management module, class management module and student management module. It realizes the functions of poor students’ information collection, poor students’ application, students’ information query and poverty level audit. It improves the efficiency of poor students’ management and realizes the networking, automation and informatization of poor students’ management.
Optimal Dispatching of Microgrid Based on Improved Particle Swarm Optimization
Authors: Zhou Fengdao , Bian Siyu , Wang Dan
Published: April 2021

In order to enable the microgrid to meet the system load demand while performing economically optimal operation scheduling, this paper establishes an island-type microgrid model, which is optimized by using an improved immune particle swarm algorithm, and the inertia weight and learning the two parameters of the factor are improved. On the basis of the immune particle swarm algorithm, a power exponential function operator is added to the inertia weight to improve the search ability of the algorithm, in order to reduce the computing time, the dynamically adjusted learning factor is introduced to optimize the immune particle swarm algorithm the local search ability is stronger. Two examples are selected to verify the algorithm, the results prove that the method has better global convergence and local search capabilities and the convergence speed has been improved.