bluuebunny/crossref_metadata_2025 huggingface dataset:
LPHN2 inhibits vascular permeability by differential control of endothelial cell adhesion
Authors: Camillo Chiara , Facchinello Nicola , Villari Giulia , Mana Giulia , Gioelli Noemi , Sandri Chiara , Astone Matteo , Tortarolo Dora , Clapero Fabiana , Gays Dafne , Oberkersch Roxana E. , Arese Marco , Tamagnone Luca , Valdembri Donatella , Santoro Massimo M. , Serini Guido
Published: September 2021

Dynamic modulation of endothelial cell-to-cell and cell–to–extracellular matrix (ECM) adhesion is essential for blood vessel patterning and functioning. Yet the molecular mechanisms involved in this process have not been completely deciphered. We identify the adhesion G protein–coupled receptor (ADGR) Latrophilin 2 (LPHN2) as a novel determinant of endothelial cell (EC) adhesion and barrier function. In cultured ECs, endogenous LPHN2 localizes at ECM contacts, signals through cAMP/Rap1, and inhibits focal adhesion (FA) formation and nuclear localization of YAP/TAZ transcriptional regulators, while promoting tight junction (TJ) assembly. ECs also express an endogenous LPHN2 ligand, fibronectin leucine-rich transmembrane 2 (FLRT2), that prevents ECM-elicited EC behaviors in an LPHN2-dependent manner. Vascular ECs of lphn2a knock-out zebrafish embryos become abnormally stretched, display a hyperactive YAP/TAZ pathway, and lack proper intercellular TJs. Consistently, blood vessels are hyperpermeable, and intravascularly injected cancer cells extravasate more easily in lphn2a null animals. Thus, LPHN2 ligands, such as FLRT2, may be therapeutically exploited to interfere with cancer metastatic dissemination.
A Modified Online Intelligent Method to Calibrate Radar and Camera Sensors for Data Fusing
Authors: Xu Guobin , Li Dongdong , Chen Xiangyang , Li Qiankun , Yin Jun
Published: September 2021

This paper introduces a modified online intelligent calibration method to calibrate radar and camera sensors in traffic scenarios. Radar and camera sensor calibration is to construct a one-to-one mapping between the radar coordinate system and the image pixel coordinate system. Based on the currently widely used artificial intelligence method (deep neural networks), camera can accurately recognize the target type. For the research and application of radar sensor and camera sensor fusion, the most important thing is to synchronize the sensor sampling time of the radar and the camera and space calibration. This paper emphasizes on spatial calibration. At present, the common calibration methods are the calibration method based on the internal and external parameters of the camera, the four-point calibration method, and the neural network calibration method. However, these three calibration methods have significant advantages and disadvantages. In the field of transportation, the disadvantages are even more prominent. This paper proposes a modified online intelligent calibration method for the application field of radar and camera sensors in traffic scenarios. We have proved through simulation experiments that this method is less time-consuming and manual operation while ensuring high-precision calibration performance.
Fast Arbitrary Shaped Scene Text Detection via Text Discriminator
Authors: Zeng Chengbin , Song Chunli
Published: September 2021

Robust scene text detection is one of the difficult and significant challenges in the computer vision community. Most previous methods detect arbitrary-shaped text using complicated post-processing steps. In this paper, we propose a trainable fast arbitrary-shaped text detection network by using the text discriminator, sharing visual information among the two complementary tasks. Specifically, we extend PSENet [1] by adding a text discriminator to fuse multiple predictions for each text instance, rather than using complicated post-processing steps which are time consuming. The text discriminator shares visual information with text detection network, and thus can achieve much faster detection speed compared with PSENet, while maintaining a similar accuracy reported in PSENet. Furthermore, our text discriminator can reduce the false alarms effectively. Experiments on ICDAR 2017 MLT, ICDAR 2015, and ICDAR 2019 ART datasets demonstrate that the proposed approach can achieve nearly realtime detection speed while keeping state-of-the-art detection accuracy.
Facial Expression Recognition Based on Transfer Learning and SVM
Authors: Yang Lei , Zhang Haiqing , Li Daiwei , Xiao Fei , Yang Shanglin
Published: September 2021

The facial expression datasets always have a problem: data with small amount or large amounts of data but also with large noisy. Both problems will affect the facial expression recognition accuracy of the model. A transfer learning method for facial expression recognition is proposed by combining the Convolutional Neural Network (CNN) and Support Vector Machine (SVM). SVM have good performance on small data sets and CNN based on transfer learning have better ability of feature extraction for large noisy data set. This method reduces the training time of model and increase the facial expression recognition accuracy. The experimental results show that the accuracy of the proposed method on the CK+ and FER2013 data sets has reached 99.6% and 68.1%.
An Interval Reliability Demand Prediction Method Combined with XGBoost and D-S Evidence Theory in Film Preparation Period
Authors: Tang Zhongjun , Ni Lang
Published: September 2021

The lack of historical sales data and word-of-mouth information in the film preparation period, the few available variables and the uncertainty in the prediction process lead to the difficulty in predicting the total box office demand of films. To solve this problem, this paper constructed and verified the prediction method of interval reliability demand in the film preparation period, which combined XGBoost algorithm and D-S evidence theory. Firstly, the total box office interval was effectively divided according to the sample data of the training set, and XGBoost was used to complete the calculation of the reliability function value of the evidence variables. Then, the D-S evidence theory was used for information fusion to obtain the results of box office interval reliability fusion. Finally, the box office attribution was judged by the interval reliability, so as to realize the interval reliability demand prediction in the preparatory period. The validity of the proposed method was verified by selecting the data of Chinese films from 2017 to 2019, and it was compared with the classical predictive classification algorithm. The results showed that the method has higher prediction accuracy and better generalization ability.
Ship Short-Term Trajectory Prediction Based on RNN
Authors: Zhu Feixiang
Published: September 2021

In the application of ship supervision, ship collision avoidance, maritime search and rescue, the trajectory prediction of the target ship is a key issue. Given the ship navigation trajectory is easily affected by wind and waves, in order to improve the accuracy and efficiency of prediction, a ship short-term trajectory prediction method combining with Automatic Identification System (AIS) data and deep learning is proposed. Based on the preprocessing of AIS data, a recurrent neural network (RNN) model is constructed to achieve the accurate prediction of ship position information is realized. Through the real ship AIS trajectory data experiment, the results show that the method is practical and effective. Compared with the traditional backpropagation (BP) neural network processing method, it has certain advantages in prediction accuracy.
Network Traffic Anomaly Detection Method Based on CAE and LSTM
Authors: Guo Shuai , Liu Yao , Su Yang
Published: September 2021

This paper constructs a deep learning method for detecting network traffic anomalies to enhance the secure transmission of data in networks due to the complex, diverse and numerous types of anomalous traffic in current networks. The method combines multiple convolutional auto-encoders (Multi-CAE) with a long short-term memory network. The convolutional auto-encoders are obtained by combining stacked auto-encoders with convolutional layers, which can not only reduce feature loss but also effectively extract the spatial structure of samples. The use of Multi-CAE greatly improves the feature extraction capability, and combined with the long short-term memory network to extract temporal features, the effective features extracted in this paper are more comprehensive and less losses compared to the models used in other researches. A comparison of the loss values in the training of CAE (Convolutional Auto-Encoders) and SAE (Stacked Auto-Encoders) in the experiments shows that the loss values of CAE are about one-tenth lower than those of SAE, and the method consisting of Multi-CAE and LSTM for the USTC- TFC2016 dataset was trained with accuracy values up to 99.98%, and the precision, recall and f1-score parameters were also above 99%, outperforming other studies.
Study on Preprocessing Method of TCM Prescription Data in Data Mining
Authors: Zhang S Z , Yu Y R , Shen M Z
Published: September 2021

Traditional Chinese medicine (TCM) prescriptions have been developed for thousands of years. Data forms are diverse, content is discrete and missing, and there are many uncertainties due to cultural and regional differences. Therefore, it has brought some difficulties to the mining of TCM prescriptions. Data based on the 3108 prescriptions for the treatment of typhoid fever, for example, is given priority to with data cleaning and data transformation of data preprocessing, prescriptions combined with multiple functions, expounds the unqualified prescriptions data cleansing, drug name normalization, dose for solving the problems of the unification, the data structured method, make the processed data can be effectively mining, It provides a strong support for exploring the compatibility law of prescription and the development of new drugs.
A Novel Multi-objective Lion Swarm Intelligent Optimization Based on Cloud Model for Manufacturing Scheduling Problem
Authors: Dong Shengwei , Jiang Mingyan
Published: September 2021

With the continuous upgrading of industrial manufacturing, various artificial intelligence technologies have gradually been applied to the field of industrial production, including swarm intelligence optimization algorithms. Aiming at the flow shop scheduling problem (FSP) and job shop scheduling problem (JSP) in industrial production, which are NP-hard problems, we use a multi-objective optimization method to solve them. We proposed a novel multi-objective optimization named multi-objective lion swarm optimization based on cloud model mutation (CMOLSO). This new optimization algorithm, which is based on the Lion Swarm Optimization (LSO), introduces the concept of cloud model and cloud generator algorithm. The introduction of the cloud model mechanism can expand the search range of CMOLSO in high-dimensional multi-objective problems, make it avoid falling into local extremes, and improve its optimization accuracy. Compared with the traditional multi-objective optimization, the new algorithm CMOLSO achieves better performance, and it can effectively solve the scheduling problems in practice.
Image Super Resolution Reconstruction Algorithm Based on Convolution Neural Network
Authors: Zhao Feng , Hu Zhifeng
Published: September 2021

Aiming at the characteristics of large amount of remote sensing image data, large terrain fluctuations and wide coverage, this paper proposes a method for super-resolution reconstruction of remote sensing image. This method combines dense network and deep back projection network to form dense projection. The unit forms a deep dense projection network, which solves the problems of insufficient texture, loss of image details and training difficulty in the super-resolution reconstruction of remote sensing image. The experimental results show that on multiple remote sensing image datasets, compared other traditional methods, the PSNR and SSIM are significantly improved, and reconstructed remote sensing image texture signs and details are more abundant.
Incremental Attribute Reduction Based on Knowledge Granularity under Incomplete Data
Authors: Zhong Qiangqiang , Wang Lei , Yang Wen , Liu Chao
Published: September 2021

Traditional attribute reductions can’t be directly applied to miss attribute values and dynamic changes data. Therefore, how to dynamically update attribute reductions efficiently when incomplete data changes dynamically is great research value. For the change of the object, using matrix’s simple and clear characteristics, the paper focus on the incremental attribute reduction algorithm in matrix form of knowledge granularity. Firstly, the knowledge granularity is obtained by matrix which uses to measure the uncertainty of the system, then calculating the attribute importance, and using the attribute importance to devise a static algorithm, and then analyzing incremental matrix form when the object increases. The comparative experiments show that the incremental algorithm can effectively and efficiently update the result of attribute reduction as the object changes.
Heuristic Attribute Reduction Based on Neighborhood Knowledge Granularity
Authors: Yang Wen , Wang Lei , Liu Chao , Zhong Qiangqiang
Published: September 2021

The classical attribute reduction algorithm is not suitable for the neighborhood decision information system of numerical attribute. Since any feature subset in real feature space can be approximated by neighborhood information particles, the concept of knowledge granularity is extended to neighborhood rough set from the perspective of the granularity computation. In this paper, knowledge granularity, attribute importance and heuristic algorithm based on the granularity of knowledge in neighborhood rough set are studied from the point of view of neighborhood relation matrix. The feasibility of heuristic algorithm is analyzed on UCI data sets. Experiments achieve better classification accuracy and lower attribute reduction results than the existing algorithms.
Computation of Differential in Strong Product Network of Paths via Recursive Iteration
Authors: Chen Yuanmei , Ren Haizhen , Zhang Lei , Zhao Yang
Published: September 2021

The set differential can be attributed to some influence maximization problems, which are widely used. For example, it is a basic algorithm problem of information diffusion in social networks. In 2004, Lewis et al. extended this concept to the graph, defined the differential of graph. The present article mainly studies the differential in strong product network of paths. Using the basic block recursive iterative method, we obtain closed form formulas for the differential on the strong product network of paths. The method used here is also effective for the differentials in square graphs.
Gated Fusion of Infrared and Visible Light Images Based on CNN
Authors: Liu Dong , Yang Huihua , Wang Lemeng , Shao Yuying , Peng Peng
Published: September 2021

As a new research direction, fusion image technology has attracted more and more attention in many fields. Among them, infrared image and visible image, the two kinds of multimodal data have strong complementarity, the fusion image of the two modes contains not only the radiation information of infrared image, but also the texture detail information of visible image. In this paper, a convolutional neural network-based encoding-fusing-decoding network model structure is used. In the encoding stage, Dense Block, which has the advantage of feature extraction, was adapted to extract the image features. In the fusion stage, four fusion methods were compared and analyzed, and the gated fusion was selected as the main method of fusion layer. In the decoding stage, RDB (Residual Dense Blocks) was used to restore the fused features to the fused image. The fusion image based on this method is sensitive to temperature characteristics and has a better performance in image quality. The fused image has a high contrast, a relatively smooth fusion effect, and the overall visual effect is more natural.
Sliding Mode Variable Structure Chaos Control for Propulsion Motor of Deep Sea Robot
Authors: Meng Junhong
Published: September 2021

As the deepwater robot’s dynamic thruster system, the brushless thruster system’s performance will influence the whole system reliability, stabilization, safety. The brushless thruster system will appear chaotic phenomena when its system structure and parameter match badly. The phenomena will lead the deepwater robot out of control, even involved by ocean wave. Aiming the chaos phenomenon of propulsion motor of deepwater robot, this paper proposes the application of sliding mode variable structure control theory to chaos control. The sliding mode variable structure chaotic control of brushless propulsion motor for deep-sea robot is designed, and the controller is designed. The feasibility and effectiveness of the chaotic control are simulated, analyzed and verified. The research result proves that, the gradation sliding mode variable structure using in control of the deepwater robot thruster motor chaotic motion are feasible and effective, i.e. the thruster motor can research the stabilization state from chaotic state and the procedure of control is related to the controller structure, parameter, and control time. And for the example system, the exponent gradation sliding mode variable stature control effect is the better.
Research on Optimization Control Strategy of Vehicle-Road-Grid Charging and Exchanging Based on User Demand Guidance
Authors: Zhang Yuanxing , Li Bin , Cao Boyuan , Li Taoyong , Huang Xingde , Yang Xingang
Published: September 2021

Considering the time-space uncertainty of electric vehicle charging and changing demand, the uneven distribution and random diversity of charging stations, the big data cloud network is used to realize the real-time information interaction between charging and changing power station and electric vehicle. Based on the user demand orientation, an intelligent charging and changing optimization control strategy of “Vehicle-Road-Grid” integrating cloud vehicle operation data is proposed. Under the discrete electric vehicle charging demand, this strategy quickly organizes the supply information around the discrete point. On the basis of the minimum energy consumption between the electric vehicle charging request point and the supply point, considering the multi-dimensional factors such as the optimal interests of the electric vehicle users, the shortest waiting time for charging and changing, and the shortest driving distance for charging and changing, the multi-objective optimal configuration strategy is realized. The simulation results show that the strategy can stably select the charging and swapping scheme that best meets the actual needs of users, effectively improve the charging and swapping service experience of users, and enhance the adhesion and participation of users.
Research on the Method of Reusing Injection Process Knowledge Based on CBR
Authors: Chen Haowei , Zhan Hongfei , Wang Rui , Yu Junhe
Published: September 2021

The injection molding process is the most critical factor affecting the quality and efficiency of injection molded products. The traditional process setting mainly relies on the operator’s limited experience and simple calculation formulas to make repeated “Try”, which has the problems of long cycle, high cost, and difficulty in guaranteeing product quality. To this end, this article takes the injection molding process as the research object, and proposes a CBR-based injection process knowledge reusing method. This method models the historical cases of injection molding from seven dimensions to form an injection case library. Through the weighted calculation of the similarity algorithm, the parameters, context and auxiliary knowledge of the case with the highest similarity are pushed to the staff to provide references for the staff to determine the corresponding process parameters and improve work efficiency.
Optimal Design of Remanufacturing Process for Injection Molding Machine Parts
Authors: Chen Chong , Zhan Hongfei , Wang Rui , Yu Junhe
Published: September 2021

The remanufacturing process of an injection molding machine is a key link that affects the remanufacturing process of an injection molding machine. Uncertainties such as damage form and degree of damage will increase the difficulty of remanufacturing repair process technology and process parameter selection. To this end, this article is based on the failure characteristics of injection molding machine parts, first establishes the failure feature fault tree extraction model of used parts, and uses damage to describe the failure characteristics such as wear, fracture and corrosion. This paper establishes a mathematical model of damage, and then uses Fuzzy comprehensive evaluation method is used to establish a quantitative scoring table for the failure characteristics of waste parts of injection molding machines. Afterwards, a directed graph is used to indicate the priority relationship between the failure feature processing elements, and finally the genetic-neural network algorithm is used to optimize the remanufacturing process route in combination with the remanufacturing time and cost to realize the optimized design of the remanufacturing process of the injection molding machine parts.
Research on the Evolutionary Development Method of Software Service Based on Trusted Agent
Authors: Gao Tilei , Yang Ming , Jia Xiaohui , Zhang Tao
Published: September 2021

The factors that affect the trustworthiness of complex software system include not only the trustworthiness of subsystem services, but also the selection and construction process of subsystem services. According to the selection and construction process of sub services, this paper has proposed the concept of trusted agent. The trusted agent contains the key modules such as trustworthiness measurement and selection of software services, which can filter external software services and send the screened high-quality results to the system, so as to optimize the construction process of complex system. The method of software system construction based on trusted agent not only ensures the trustworthiness of the construction process, but also reduces the degree of manual participation, and improves the efficiency and automation of the software system construction process.
Research on Test Method of Power Sensor Battery Considering the Influence of Air Flow
Authors: Zhou Wen , Jiang Yi , Zhang Jing , Yu Chunlai , Zhu Hao
Published: September 2021

The reliability of sensor is an important index to determine the outdoor operation efficiency of power sensor, and the reliability detection of power sensor is an important means to ensure the reliability of network equipment. Based on the analysis of the thermal characteristics and thermal behavior of the battery, this paper studies the current detection methods of the low-temperature battery of the power sensor, and proposes a reliability test method of the power sensor considering the influence of outdoor airflow. Through multi-physical field simulation and analysis, the key parameters of relevant experiments are obtained, and the key test parameters are given.
Research on the Control Method of Short-term Transmission and Distribution Price Level
Authors: Zhang Xuejun
Published: September 2021

In order to ensure the orderly competition in the power market, through a variety of measures to reduce the electricity cost of enterprises and users, and improve the service quality of power enterprises, this paper puts forward the research on the control method of the total level of short-term transmission and distribution price. Combined with the principle of “three sets and five big”, the power grid marketing system is established, the main responsibilities of customer service center are assigned, and the main factors affecting pricing are extracted by bird swarm algorithm. Combining the rate of return on investment with the price cap regulation mode, a growth type short-term total level regulation mode of transmission and distribution electricity price is constructed. Simulation results show that the proposed control method has high accuracy in forecasting electricity demand and can give full play to the role of market price regulation.
Simulation Design of Spot Welding of Body Structure and Transfer Robot Workstation
Authors: Gao Jun , Han Chang , Liu Yicai
Published: September 2021

Application of virtual simulation technology to manufacturing industry today can shorten the development cycle, reduce costs and improve the design accuracy. This paper takes the spot welding workstation of auto body structure as the research object. Firstly, the production demand of spot welding of auto body structure is analyzed, the structure and production characteristics of spot welding robot workstation are analyzed, and the appropriate equipment is selected for the layout of spot welding robot workstation. Secondly, the work path of the robot is planned reasonably, and the planning of the robot trajectory can facilitate the writing of program instructions later. In the design process, three-dimensional modelling software is used to model some components in the workstation. Finally, through the use of simulation software, the welding path optimization and off-line programming of the whole spot welding robot workstation are simulated. The results show that the designed robot workstation can meet the use requirements.
Research on Parallel Operation Characteristics of High-pressure Pumps Applied in Coal Mine Hydraulics permeability improvement
Authors: Shen Kai , Xiong Wei , Ba Quanbin , Liao Yin , He Lipeng
Published: September 2021

Nowadays, plunger high-pressure water pumps applied in large-scale mine are mostly used in coal mine hydraulics to increase permeability, and it is difficult to transport objections underground. Besides, the permeability improvement is affected during overhaul too. Therefore, multiple small high-pressure water pumps operating in parallel can be used to solve the problems mentioned above instead of large high-pressure water pumps. Moreover, the operating principle of the plunger high-pressure pump determines the specific flow fluctuation characteristics during its operation, and similar flow fluctuations also exist during the operating of parallel pump sets. The transmission model and AMESim hydraulic simulation model of single, parallel plunger pumps are established, taking the BQW-22/50 high-pressure water pump as an example. The operating characteristics of a single plunger pump and a parallel pump group are analyzed in this paper. The results are obtained as follows: the instantaneous discharge flow curve of a single plunger pump conforms to a sine function; the flow of the parallel pump set is the superposition of the flow of multiple plunger pumps; the instantaneous discharge flow curve changes under the influence of the phase deviation angle between the pumps; when parallel pump sets are running, there is an optimal phase deflection angle between the pumps, which minimizes the flow fluctuation of the pump sets; when four high-pressure water pumps are operated in parallel, the optimal phase deflection angle between the pumps is π/12 or π/4.
Simulation of shock test for an AUV propulsion motor based on DDAM
Authors: Liu Lei , Zhao Zengwu , Wei Juan , Li Xiaobei , Yuan Liwei
Published: September 2021

The paper studies the simulation of shock test for a propulsion motor equipped on an AUV. According to DDAM, the modal parameters are calculated using finite element analysis. Then the input spectrum of impacting acceleration is given based on modal analysis. The response after shocking is analyzed at last. Distribution of the stress in different directions are given, showing that the shock resistance performance of the propulsion motor satisfied the shock test.
Research on Human-Machine Interface Design of Smart Refrigerator Based on Conjoint Analysis
Authors: Yang Jing , OuYang Wumin , Chen Yuqi
Published: September 2021

The purpose is to study the design method of the smart refrigerator man-machine interface. The method adopts conjoint analysis, starting from the human-machine interface of the smart refrigerator, and splitting and orthogonally reorganizing the main components and element types of the interface, allowing users to score the virtual experiment scheme and statistical data, and calculate the utility value of each element and type, analyzes the user preference in the smart refrigerator man-machine interface, and then draws the design principles of the smart refrigerator man-machine interface, and generates the final interface design plan. This paper concluded that through the conjoint analysis method, multi-factor data could be statistically analyzed. Therefore, enable designers to better understand the user preference for the smart refrigerator man-machine interface, improve user experience and user viscosity, and providing ideas for similar interface design in the future.
Research on Calibrating Device of Daily Clock Time Difference Testers Based on DDS Cascade Technology
Authors: Yan Ming , Zhang Shengnan , Yin Fucheng , Yang Ming , Li Nuo
Published: September 2021

According to the specific requirements in the national verification regulations of JJG488-2018 “Instantaneous Daily Clock Time Difference Testers”, this paper has developed a calibration device for an instantaneous daily rate measuring instrument. Under the premise of not using FPGA, CPLD, DSP and complex algorithms, the device adopts DDS chip cascade technology and energy conversion principle to ensure that the maximum allowable error of the daily difference is 0.001s/d. Therefore, the device is not only suitable for personnel in the field of measurement to calibrate instantaneous daily clock time difference testers, but also can be used as a general-purpose measuring instrument with frequency measurement functions such as high-resolution frequency synthesizer calibration frequency meters.
Research and design of a multifunctional intelligent walking stick
Authors: Chen Yan , Meng Chaoying , Li Yunlong , Sun Taokai , Wang Shangyu
Published: September 2021

This paper designed a multifunctional intelligent walking stick for the elderly. The mechanical structure of the walking stick is provided with a hook, auxiliary mechanism for standing up, an anti-tripping mechanism, a small table board and telescopic adjustment. The auxiliary mechanism for standing up can make it easier for the user to stand up. The anti-tripping mechanism makes it safer for the elderly to walk without tripping. The retractable adjustment can meet the needs of people with different heights. The walking stick is also equipped with intelligent elements, such as lighting lamp, automatic time alarm, fall alarm system, manual alarm system, GPS positioning and MP3 music functions. When the elderly feels unwell, they can press the alarm switch, and the alarm bell will turn on, which can attract passers-by and improve the chance of rescue. When the fall alarm system is turned on, if the user falls, the alarm bell will ring, At the same time, the GPS positioning module will send the crutch position to the intelligent terminal to remind the guardian in time. Compared with the traditional crutches, the crutch has many functions and it is more convenient to use and safer.
PID Parameter Tuning for Buck Controllers Based on an Improved Differential Evolution Algorithm
Authors: Zhao YJ , Qiu QX , Zhao X
Published: September 2021

With the wide application of Buck converters, it is of great significance to select the optimal PID controller parameters to ensure the dynamic and steady-state performance of the Buck converters. On this basis, a PID parameter tuning method based on an improved differential evolution algorithm is proposed. Also, a crossover approach with population generation across orders of magnitude, elastic boundary absorption, and retention of some combined features is put forward. In addition, an adaptive mutation factor, and a cost function that suppresses overshoot and is sensitive to the tuning time are designed. The results of 10 tests show that the differential evolution algorithm fails in the case of parameters in a range cross orders of magnitude, while the algorithm proposed in this paper enables a better combination of PID parameters selected in terms of speed and stability, with a wide search space and stable convergence results.
New type solar energy micro-polluted water purification technology and device
Authors: Huang Yaqin , Rong Lishan , Yu Feng , Chen Ziqian , Shi Ling , Wang Xinyue , Gong Wei
Published: September 2021

The “new micro-polluted water purification device” is mainly used to deal with the micro-pollution of some water bodies. The purpose is to purify micro-polluted water through this device to provide necessary domestic water for human life. This project designed a simple, economical and environmentally friendly sewage treatment system in order to solve the water problem in water-scarce regions such as Africa. By simulating the process of natural water cycle, using solar energy as the power source, the micro-polluted water is purified into potable water. And store it in a water tank. The device flexibly utilizes clean energy such as heat energy and wind energy to meet the demand for water extraction in different situations. The device realizes the purification treatment of micro-polluted water body under the condition of low cost and low energy consumption.
Research on the influence of bottom expanding and filling on bolt sliding instability and supporting effect
Authors: Wang Jinrui , Nan Hua , Wang Shuai
Published: September 2021

Aiming at the problems of soft coal roadway, such as low hardness, fracture development, poor bonding ability between anchoring agent and surrounding rock of borehole, weak shear resistance, which easily lead to resin bolt sliding instability in coal roadway. To effectively support soft coal roadway, the method of bottom expanding and filling is adopted. This method expands the hole at the bottom of the borehole and replaces the soft coal with high-strength material to achieve the same position modification of the soft coal body at the bottom of the borehole and improve the anchoring performance of bolt support. Through laboratory tests and numerical simulations, the sliding instability of the bottom reamed bolt is evaluated. the results show that, with the increase of the reaming times, the anchoring force changes in direct proportion to the reaming times, except single of the reaming times, the anchoring force increases fast under quintuple of the reaming times, and increases slowly over quintuple of the reaming times, so it is considered that quintuple reaming is the most appropriate.
Energy Saving Application of Variable Speed Auxiliary Pump Plus Hydro Turbine in Circulating Cooling Water System
Authors: Wang Peng , Luo Xingqi , Chen Senlin , Cai Qingsen , Lu Jinling
Published: September 2021

The circulating cooling water system (CCWS) is a common industrial auxiliary system, and water pumps need to consume much energy to transport cooling water to distributed heat exchangers. Previous studies show that a pump network configuration with constant speed auxiliary pump plus hydro turbine (CSAP-T) plays a significant role in energy conservation. However, given the fluctuations in the production load and cooling water supply temperature, the flow demand of heat exchangers for cooling water varies. Under different working conditions, the CSAP-T scheme cannot supply the minimum cooling water flow required by all heat exchangers at the same time, thereby wasting energy. Therefore, this paper proposes a new fluid machinery network configuration called variable speed auxiliary pump plus hydro turbine (VSAP-T) and establishes a mathematical model of the total output power of the fluid machinery network in CCWS to minimize network energy consumption. To illustrate the effectiveness of the VSAP-T scheme, a real system is used as the research object, and both CSAP-T and VSAP-T schemes are used to optimize the system. When the working conditions are changed, the total output power of the system fluid machinery network can be conserved by 30% to 50%.
Application of ground laser scanner in surveying and mapping field
Authors: Hu Chang’an , Hu Song , Kong Linghui , Liu Junbo
Published: September 2021

With the continuous development of measurement demand, the market of single point measurement mode is shrinking, 3D measurement is more and more appearing in the field of surveying and mapping, ground laser scanner as a portable 3D measurement tool, its use is more and more important. This paper takes substation measurement, cadastral measurement, facade measurement and oil tank measurement as typical cases, and introduces the case of oil tank measurement in detail.
Optimization of stereo calibration parameters for the binocular camera based on improved Beetle Antennae Search algorithm
Authors: Wang Zhaoran , Chen Guochu , Tan Lisi
Published: September 2021

For binocular cameras, aiming at the low precision of traditional stereo calibration methods for binocular cameras, a Beetle Antennae Search (BAS) algorithm based on binocular parallel polar line constraint was proposed to improve the calibration accuracy. The internal parameter matrix and distortion parameter matrix of the left and right cameras of the binocular camera were first calculated by using the MATLAB calibration toolbox. Then the stereo calibration parameter matrix of the binocular camera was calculated. Then, using the binocular parallel polar line constraint based on the BAS algorithm establishes the objective function by taking the difference and average values of the vertical coordinates of each checkerboard corner in the left and right images after stereo correction as the objective. The stereo calibration parameters of the binocular camera are further optimized. The results show that the BAS algorithm based on binocular parallel pole constraint is stable, reliable and fast in convergence, which can realize the optimization of stereo calibration parameters of the binocular camera.
Research and Design of Data Acquisition and Monitoring System for Intelligent Production Line of Prefabricated Building Components
Authors: Chen YaJuan , Zhou FuLiang
Published: September 2021

In order to solve the intelligent production and management level of assembly parts and components production line, a data acquisition and monitoring system scheme is designed to collect key parameters in the product production process, such as vibration strength (amplitude) information, concrete weight information, temperature information, humidity information, energy and other data. The scheme can realize the functions of on-site data display and processing, dynamic monitoring of equipment status and so on.
Magnetic Circuit Model of Magnetic Valve Controllable Reactor Considering Magnetic Flux Leakage Effect
Authors: Dong Liwei , Tian Mingxing , Zhang Huiying
Published: September 2021

The magnetic circuit model of the magnetic saturation characteristic magnetoresistance of the magnetically controlled shunt reactor (MCSR) nonlinear core is proposed by using the magnetic field division method, combining with the geometric parameters and working principle of the prototype. The magnetic circuit structure and working characteristics are analyzed. The calculation formula of the magnetic potential node of the magnetically controlled shunt reactor is derived by improving the node analysis method, and the simulation calculation and analysis of the working current of the magnetic control reactor under no-load and different DC bias are carried out. The conclusion shows that the accuracy of the magnetic circuit model can meet the needs of engineering, and the modeling method has the characteristics of clear principle, simple modeling, accurate model and engineering applicability, which can provide guidance for designers.
Matching Underwater Sonar Images by the Learned Descriptor Based on Style Transfer Method
Authors: Zhou Xiaoteng , Yu Changli , Yuan Xin , Luo Citong
Published: September 2021

This paper proposes a method that combines the style transfer technique and the learned descriptor to enhance the matching performances of underwater sonar images. In the field of underwater vision, sonar is currently the most effective long-distance detection sensor, it has excellent performances in map building and target search tasks. However, the traditional image matching algorithms are all developed based on optical images. In order to solve this contradiction, the style transfer method is used to convert the sonar images into optical styles, and at the same time, the learned descriptor with excellent expressiveness for sonar images matching is introduced. Experiments show that this method significantly enhances the matching quality of sonar images. In addition, it also provides new ideas for the preprocessing of underwater sonar images by using the style transfer approach.
Trajectory Clustering Of Segmented Field Operations Logistics Process
Authors: Zhang B.S. , Xiang Z.Q. , Zhang H. , Liu R.
Published: September 2021

It has become a new research direction to use process mining technology to mine and analyze all kinds of data generated during shipbuilding. The classification of hull segments into different clusters according to some properties in advance can make the excavation results more specific. In this paper, the process examples in ship construction are divided into different clusters based on the cohesive hierarchical clustering algorithm. Firstly, this paper introduces the advantages and disadvantages of several main clustering algorithms, selects the clustering algorithm most suitable for segmented outfield logistics, establishes the mathematical model of segmented outfield logistics process trajectory clustering, and defines the appropriate feature vectors. Euclidean distance, Hamming distance, Jekard distance and cosine distance were used to calculate the similarity distance between process instances, and the concepts of chain, single chain and group average were added to select the appropriate similarity distance between clusters. An evaluation method of clustering results based on coutour coefficient is introducedwhich can effectively evaluate the clustering results of the logistics process trajectory during segmented remote operations. Finally, the feasibility and effectiveness of the proposed algorithm are verified by experiments.
Analysis on water hammer protection of FPSO ballast water system
Authors: Li xiu , Yang hao jie , Dou pei lin , Zhao shi fa
Published: September 2021

In practical engineering, the protection of FPSO water hammer is very important. Through simulation analysis, the relevant data are obtained to provide reference for relevant engineering practice. A general-purpose FPSO ballast water pipe network system was established by aft impulse software, and water hammer simulation calculation and analysis were carried out to find out the maximum pressure position of water hammer phenomenon. According to the water hammer generation mechanism, the simulation research was carried out by two-stage valve closing and adding surge tank into the pipeline. It was found that water hammer was easily caused by quick closing valve; the protection method of two-stage valve closing and installation of surge tank has a very objective protective effect, which provides a reference for related projects.
Judgment and correction of lost speed Keyphasor pulse of rotating machinery
Authors: Qihe Liu
Published: September 2021

The order analysis of vibration signal of rotating machinery depends on the speed Keyphasor signal, and the Keyphasor pulse will be lost in actual measurement. In order to calculate the rotational speed accurately, a method to judge whether the Keyphasor pulse is lost is given, and a method to recover the lost pulse based on cubic spline interpolation is proposed. The simulation based on LabVIEW shows that the method given in this paper can well judge and recover the lost Keyphase pulse.
Study & Improvement of Occupant Out-of-position Injuries Under Pre-crash Braking Condition
Authors: Yang Jialin , Li Mengqi , Zhu Haitao
Published: September 2021

Although the impact strength can be reduced by AEB and other active safety technologies, the occupants may move forward under braking condition and reduce the protection space of the restraint system. The out-of-position displacement and injuries of occupants under braking conditions are studied by sled tests. The injury characteristics of the out-of-position occupant are obtained. By orthogonal tests, the influence of out-of-position on the injury of different body regions are analysed. MADYMO active human body simulation model is established, and the characteristics of the occupant forward displacement under different braking waveforms are studied by single variable method. By using the active seatbelt, the occupant’s forward displacement is restrained. With the use of Central Composite Design (CCD) method, the response surface model of the occupant’s neck displacement relative to the pretension force and pretension time of the active seatbelt is established. The effects of pretension force and pretension time on out-of-position displacement are studied, and the optimal design is carried out to obtain the parameter combination.
Crowdsourcing Innovation
Authors: Dahlander Linus , Piezunka Henning
Published: September 2021

Crowdsourcing—a form of collaboration across organizational boundaries—provides access to knowledge beyond an organization’s local knowledge base. There are four basic steps to crowdsourcing: (a) define a problem, (b) broadcast the problem to an audience of potential solvers, (c) take actions to attract solutions, and (d) select from the set of submitted ideas. To successfully innovate via crowdsourcing, organizations must complete all these steps. Each step requires an organization to make various decisions. For example, organizations need to decide whether its selection is made internally. Organizations must take into account interdependencies among these four steps. For example, the choice between qualitative and quantitative selection mechanisms affects how widely organizations should broadcast a problem and how many solutions they should attract. Organizations must make many decisions, and they must take into account the many interdependencies in each key step.
Italy: The Military in Politics
Authors: Labanca Nicola
Published: September 2021

The Italian case is virtually nonexistent in almost all the best general works on military intervention in politics, but understanding the Italian case could add much to the academic debate as the debate seems to be again investigating the role of the military in established democracies.

The most important key to understanding the story of Italian civil–military relations is not military professionalism. Rather, a specific feature of these cases could lay in the reduced strength of the different players (the military, the civilians). These widespread and common weaknesses end up being a continuity along all Italian history: the first years of Risorgimento and Liberal Italy, fascism, the advent of the Republic and democracy after the end of World War II, and even in the post-Cold War decades. Because of this continuity, the work of historians could be most useful for political scientists. What is interesting is that whether the Italian military was strong or weak, it almost always managed to have its demands met by influencing, penetrating, and conditioning the political system. Almost always, the military did not need to intervene directly. And this is another reason to better understand this case without the influence of old, biased national stereotypes and as studied by Italian scholars but ignored in its subtleties by international scholarship.