2024 volumne 45卷 Issue  02
ZHANG Zhen 1 , WANG Xiaojie 1 , JIN Zhihua 1 , MA Jijun
Abstract: In order to improve the detection speed of road traffic signs, an improved model based on lightweight YOLOv5 was proposed. Firstly, Ghost convolution and depthwise convolution were used to build a new Bottleneck, which could reduce the amount of computation and parameters. Then the BiFPN structure was introduced, which could enhance the feature fusion ability. CIoU loss function was replaced by SIoU loss function, which focused on the angle information of ground true box and prediction one, so that it would improve the detection accuracy. Secondly, the TT100K dataset was optimized, and 24 categories of traffic sign pictures and labels with more than 200 were screened out. Finally, the experiment achieved 84% accuracy, 81. 2% recall and 85. 4% mAP@ 0. 5. Compared with the original YOLOv5 model, the number of parameters was reduced by 29. 0%, the amount of computation was reduced by 29. 4%, but the mAP@ 0. 5 was only reduced by 0. 1 percentages, and the detection frame rate was improved by 34 frames/ s. Using the improved model for detection, the detection speed could be significantly improved, could basically achieve the goal of compression model on the basis of maintaining the detection accuracy.
FAN Wenbing, ZHANG Lulu
Abstract: Aiming at the problem that KCF tracking algorithm might decrease the tracking performance or even tracks unsuccessfully in the occlusion scene, an anti-occlusion model adaptation image tracking algorithm was proposed by combining KCF and KF prediction. Firstly, considering the lack of occlusion evaluation in the traditional KCF target tracking algorithm, the peak sidelobe rate of the response map was introduced to judge the occlusion of the image target, and the occlusion types were divided into partial occlusion and severe occlusion. Then different model update strategies were adopted according to the severity of occlusion. When the target was not occluded or occluded partially, instead of using a fixed learning rate to update the model in the traditional KCF tracking algorithm, the target appearance model was updated by adjusting the model learning rate adaptively to avoid tracking drift. When the target was severely occluded, stopped updating the KCF model. Finally, the state space and position output models of Kalman filter were constructed by applying the motion information before severe occlusion. The Kalman filter prediction algorithm was designed to predict the moving target trajectory and estimate the target position in the occlusion scene,so as to solve the problem of target tracking failure in occlusion scenes. The OTB2013 standard dataset was utilized to conduct extensive experiments, the results demonstrated that the distance accuracy of the proposed hybrid tracking algorithm KCF-KF was 0. 796, and the overlap success rate was 0. 692. Compared with the other traditional tracking algorithms, the tracking accuracy and success rate of the hybrid algorithm were better, and the hybrid algorithm could achieve better tracking performance when encountering the target occlusion challenges and solve the occlusion interference in the tracking process effectively.
GAO Yufei, MA Zixing, XU Jing, ZHAO Guohua, SHI Lei
Abstract: For medical image segmentation tasks such as glioma image segmentation with dense prediction, both local and global dependencies were indispensable. To address the problems that convolutional neural networks lacked the ability to establish global dependencies and the self-attention mechanism had insufficient ability to capture local details, a convolutional and deformable attention-based method for glioma image segmentation was proposed. A serial combination module of convolution and deformable attention Transformer was designed, in which convolution was used to extract local features and the immediately following deformable attention. Transformer was used to capture global dependencies to the establishment of local and global dependencies at different resolutions. As a hybrid CNN-Transformer architecture, the method could achieve accurate brain glioma image segmentation without any pretraining. Experiments showed that the average dice score and the average 95% Hausdorff distance on the BraTS2020 glioma image segmentation dataset were 83. 56% and 11. 30 mm, respectively, achieving comparable segmentation accuracy compared with other methods, while reducing the computational overhead by at least 50% and effectively improving the efficiency of glioma image segmentation.
LI Wenju1, JI Qianqian1, SHA Liye2, CHU Wanghui1, CUI Liu1
Abstract: Aiming at the shortage of distance feature and local geometric structure information in feature extraction, a point cloud classification and segmentation network based on graph walk and graph attention was proposed. Firstly, a guided graph walk algorithm was used to supplement additional geometric information and remote feature information to the whole feature of point cloud. Secondly, the graph attention mechanism was embedded to make the model on the key areas of the point cloud and improve the feature extraction ability of the network. Finally, distance features were extracted from the initial point cloud and embedded into the network as initial residuals to avoid oversmoothing. Point cloud classification experiments were carried out on ModelNet40 dataset and ScanObjectNN dataset, and point cloud component segmentation and point cloud semantic segmentation experiments were carried out on ShapeNetPart dataset and Toronto-3D dataset, respectively. The experiment results showed that, compared with the benchmark network DGCNN, classification accuracy increased by 1. 3 percentages and 5. 6 percentages, respectively; The segmentation accuracy was improved by 1. 2 percentages and 33. 1 percentages respectively. Through the robust analysis on ModelNet40-C dataset, it was proved that the proposed network had strong robustness.
CHEN Yan1,2, LAI Yubin1, XIAO Ao1, LIAO Yuxiang1, CHEN Ningjiang1
Abstract: In response to the issues of limited annotated data, insufficient fusion between modalities, and information redundancy in multimodal sentiment analysis, a multimodal sentiment analysis model called CLIP-CA-MSA based on contrastive language-image pretraining(CLIP) and cross-attention mechanism was proposed in this study. This model employed models such as BERT which was pre-trained by CLIP, and PIFT to extract feature vectors from videos and textual content. Subsequently, a cross-attention mechanism was applied to facilitate interaction between image feature vectors and text feature vectors, enhancing information exchange across different modalities. Finally, the uncertainty loss was utilized to compute the fused features, and the ultimate sentiment classification results were generated from the outputs. The experimental results showed that the model could increase accuracyrate by 5 percentage points to 14 percentage points and the F1 value by 3 percentage point to 12 percentage point over other multimodal models, which verifieed the superiority of the model in this study. And uses of ablation experiments to verified the validity of each module of the model. This model could effectively utilize the complementarity and correlation of multimodal data, and utilize uncertainty loss to improve the robustness and generalization ability of the model.
JI Ke1,2, ZHANG Xiu1,2, MA Kun1,2, SUN Runyuan1,2, CHEN Zhenxiang1,2, WU Jun3
Abstract: Text matching is an important task in the field of natural language processing, which can be used in many scenarios, such as information retrieval, machine translation, dialogue systems, etc. Topic matching is a broader matching ba<x>sed on text matching, judging whether the main thing described by two paragraphs of text is the same. Nowadays, the existing text matching technology is developing in the direction of refined matching of text semantics, and the topic matching effect is poor, which cannot meet the needs of users in practical applications. Therefore, a topic matching algorithm ba<x>sed on multi-feature fusion of key entities and text abstracts is proposed, which integrates key entities and text summary features to better understand the deep semantic information of natural language, and improves the interaction of text semantic features through the cross-attention mechanism to improve the effect of text topic matching. We conducted comparative experiments on real data from Sohu, and the results show that the performance of the algorithm is better than the popular deep learning text matching algorithm.
WANG Hairong, XU Xi, WANG Tong, JING Boxiang
Abstract: In order to solve the problems in studies of multimodal named entity recognition, such as the lack of text feature semantics, the lack of visual feature semantics, and the difficulty of graphic feature fusion, a series of multimodal named entity recognition methods were proposed. Firstly, the overall framework of multi modal named entity recognition methods and common technologies in each part were examined, and classified into BilSTM-based MNER method and Transformer based MNER method. Furthermore, according to the model structure, it was further divided into four model structures, including pre-fusion model, post-fusion model, Transformer single-task model and Transformer multi-task model. Then, experiments were carried out on two data sets of Twitter-2015 and Twitter2017 for these two types of methods respectively. The experimental results showed that multi-feature cooperative representation could enhance the semantics of each modal feature. In addition, multi-task learning could promote modal feature fusion or result fusion, so as to improve the accuracy of MNER. Finally, in the future research of MNER, it was suggested to focus on enhancing modal semantics through multi-feature cooperative representation, and promoting model feature fusion or result fusion by multi-task learning.
HU Hongchao 1 , ZHANG Shuaipu 2 , CHENG Guozhen 3 , HE Weizhen 3
Abstract: In addressing the inefficiencies and limitations in proactive defense against Regular Expression Denial of Service (ReDoS) attacks in cloud-native environments, we have developed a defense method based on Moving Target Defense (MTD) technology. Initially, we analyzed the behaviors of both attackers and defenders within microservice applications characteristic of cloud-native environments. Subsequently, leveraging Kubernetes, we designed an MTD-based defense system. This system incorporates dynamic and static multi-dimensional microservice weight indices based on topology information and request arrival rates, as well as service efficiency judgment indices based on queue theory. It also includes a method for selecting the timing of key microservice rotations to guide the selection and rotation timings of critical microservices. Finally, we introduced a multi-dimensional MTD heterogeneous rotation algorithm, grounded in heterogeneity and service efficiency, and conducted simulations using Python. Experimental results indicate that our proposed algorithm reduces defense latency by approximately 50% compared to dynamic scaling and that defense costs stabilize after the initial defense against an attack, preventing continuous growth.
YU Kunjie, WANG Siyu, YANG Duo, FU Hanwen, LIAO Yuefeng
Abstract: In order to reduce the equivalent hydrogen consumption of the hybrid system and delay the aging of the fuel cell, an Energy management strategy (EMS) was proposed based on multi-objective optimization and road condition classification. Firstly, the electrical model of the fuel cell and lithium battery hybrid system power was constructed, and the equivalent hydrogen consumption model and fuel cell aging model were introduced. Then, a rulebased multi-mode EMS was designed; on this basis, in order to further reduce the equivalent hydrogen consumption of the system and prolong its service life, the multi-objective beluga whale optimization algorithm (MOBWO) was proposed to optimize the control parameters. Furthermore, in order to make the designed EMS suitable for different road conditions, a real-time classification method of driving road conditions based on long short-term memory ( LSTM) network was proposed, aiming to switch the control parameters of EMS according to the classification results to achieve the optimal effect. Finally, the proposed algorithm was analyzed on the simulation platform. The results showed that the hydrogen consumption of the hybrid system with the proposed method was reduced by 2. 3% and the aging degree of the fuel cell was reduced by 1. 02% compared with the rule-based method,The proposed EMS could effectively reduce the equivalent hydrogen consumption of the hybrid system and delay the aging of the fuel cell.
ZHANG Wenyu, MA Keke, GUO Zhenhai, ZHAO Jing, QIU Wenzhi
Abstract: In order to improve the multi-step prediction of wind speed, a hybrid prediction model based on data signal decomposition and grey wolf optimization algorithm was proposed to optimize extreme learning machine. Firstly, the original wind speed time series was decomposed into several intrinsic mode functions and a residual sequence using the complete ensemble empirical mode decomposition with adaptive noise, and the partial autocorrelation function model input. Then, the model was built and the prediction was made on the decomposition subsequence. An extreme learning machine neural network with multi-input-multi-output strategy was constructed, and grey wolf algorithm was used to solve the weight and bias of the optimal hidden layer. Finally, the subsequence was reconstructed and the final prediction result was obtained. Simulation experiments were conducted using multiple sets of measured data with a time resolution of 15 minutes. The root mean square errors of the proposed model in the three wind farms were 0. 859, 0. 925, and 0. 927, respectively, which were lower than other comparative models, verifying the effectiveness of the model in predicting wind speed in the next four hours,i. e. 16 steps prediction.
LUO Peng, CHEN Guanghao, YANG Donghong, GUO Lei
Abstract: To solve the problem that the output voltage of the new energy power generation device varied greatly and it was difficult to realize energy storage, a novel single-switch coupled buck-boost converter based on PI controller and feed-forward control was presented. The voltage gain could be adjusted by the turns ratio of the coupled inductor, and the voltage stress on the power switch was suppressed by the passive clamped circuit with recycled leakage inductor energy. Compared with traditional buck-boost converter, the proposed converter had the advantages of wider voltage conversion ratio, continuous input current, and low voltage stress on power switch. Combing PI controller with feedforward control strategy, superior input transient response of the converter during the whole input voltage range is obtained. The operating principles and steady-state characteristics of proposed converter were analyzed and derived in detail, respectively, and the performances were compared with other single-tube buck-boost converters. The small-signal model was derived, and the correctness of PI parameter design was verified by bode diagram. The design process of PI controller combined with feedforward control strategy was analyzed. Finally, an experimental prototype with a rated power of 100 W, 20 V to 60 V input, and 48 V output was built to verify the performance of the proposed converter in boost mode and buck mode, and the feasibility of PI controller combined with feed-forward control strategy. The measured maximum efficiencies with the boost and buck modes were 97. 08% and 97. 10%, respectively.
ZHENG Yuanxun, KONG Meng, WANG Boli, WANG Changzhu, CHEN Jing
Abstract: In order to study the effect of bridge pre-camber on the comfort of continuous rigid bridge, a number of continuous rigid bridges with main span diameters between 110 m and 200 m were used as research objects. Firstly, the time domain model of the pavement was established using the filtered white noise method, and the levelness of the new bridge deck was simulated by superimposing it with the formed bridge alignment set according to the cosine curve. Secondly, MATLAB / Simlink was used to build the vehicle-road system model. The root means square (RMS) acceleration value was used to evaluate the traffic comfort of the bridge side span and middle span deck. The maximum transient vibration value (MTVV) was used as the evaluation index of the driving comfort in the short time at the peak of the side span. Finally, the influence of the span diameter and design speed on the RMS value of the side and middle spans of the bridge with the empirical method of setting the pre-arch according to the cosine curve was analyzed. The influence of the pre-arch value on the MTVV value at 3L / 8 of the side span were analyzed. The results showed that the RMS values were less than 0. 315 m / s 2 at the side span and mid-span, indicating that the empirical method of setting the pre-arch of the bridge according to the cosine curve did not affect the traffic comfort at the mid-span. The MTVV value at the side span 3L / 8 was greater than 0. 345 m / s 2 in a short period of time, which mean that the peak of the side span was slightly uncomfortable in a short period of time. In order to improve the traffic comfort within the side span, measures were proposed to optimize the bridge deck alignment at 3L / 8 and the top of the side pier based on the leveling layer construction.
LIU Mingjian, ZHU Yunhe, ZHANG Sijia, SUN Hua
Abstract: The existing autonomous intersection control strategies lack foresight and are prone to deadlock, resulting in low execution efficiency of the control system. To address this issue, a vehicle road collaborative autonomous intersection control strategy based on maximum clique theory is designed. Firstly, the spatiotemporal trajectory of vehicles was modeled, and the conflict matrix describing the driving conflict relationship between vehicles was constructed. Secondly, the conflict matrix was transformed into a conflict relation graph. Through three established solution stages, the complement of the maximum clique in the conflict relation graph was solved as the set of accepted vehicle reservation requests, which could ensure more successful vehicle reservation requests passing through the intersection within each batch processing cycle and could improve the efficiency of intersection passage while ensuring the safety of vehicle driving at the intersection. Simulation results showed that compared with the first come first served control strategy, traffic signal control strategy, and Tabu-based control strategy, the average waiting time was reduced by 40%, 17%, and 8%, and the number of vehicles passing through the intersection per unit time was increased by 30%, 18%, and 9%, respectively. This proved the effectiveness of the strategy, which not only could improved the throughput of the intersection but also could effectively reduce the average waiting time of vehicles.
JIN Libing, WANG Zhenhao, WU Tian, XIE Zhiheng, ZHOU Pin
Abstract: In view of the damage to the durability of concrete structures caused by the coupled effects of loading and sulfate attack in coastal and saline soil environments, a numerical model for the sulfate ion diffusion in compressed concrete was proposed. Firstly, based on Fick′s second law, a theoretical diffusion model of sulfate ions in concrete under loading was established by considering the relationship between stress and concrete porosity. Secondly, a three-phase mesoscopic convex polygonal stochastic aggregate model of concrete containing cement mortar, interfacial transition zone, and natural aggregate was established by a self-programmed program, which enabled the mesoscopic simulation of sulfate ions diffusion in compressed concrete. Finally, the validity of the theoretical and mesoscopic models was verified by comparative analysis with the experiment results of full immersion of compressed concrete in a sulfate solution. Then the ion diffusion and damage process of compressed concrete specimens with different water-cement ratios in sulfate solutions of different concentrations were numerically analyzed. The findings indicate that the sulfate ion concentration at the same depth gradually decreased as the compressive stress level increased. The effects of sulfate concentration and the water-cement ratio on sulfate ion diffusion were more evident than with compressive stress. The extent to which compressive stress inhibited ion diffusion was influenced more by the water-cement ratio than by the sulfate concentration. Reducing the water-to-cement ratio appropriately made the compressed concrete more resistant to the sulfate attack.
Pre-publication
Bi Ying,Xue Bing,Zhang Mengjie
Abstract: As an evolutionary computation (EC) technique, Genetic programming (GP) has been widely applied to image analysis in recent decades. However, there was no comprehensive and systematic literature review in this area. To provide guidelines for the state-of-the-art research, this paper presented a survey of the literature in recent years on GP for image analysis, including feature extraction, image classification, edge detection, and image segmentation. In addition, this paper summarised the current issues and challenges, such as computationally expensive, generalisation ability and transfer learning, on GP forimage analysis, and pointd out promising research directions for future work.
Wang Wen1,Hu Haoliang1,He Shitang1,Pan Yong2,Zhang Caihong3
Abstract: In view of the current situation that the traditional methane sensor technology is difficult to imple-ment the field detection and monitor on methane gas, a novel room-temperature SAW methane gas sensor coa-ted with cryptophane-A sensing interface is proposed by utilizing the supermolecular compound cryptophane-A’ s specific clathration to methane molecules. The sensor was composed of differential resonator-oscillators with excellent frequency stability, a supra-molecular CrypA coated along the acoustic propagation path, and a frequency acquisition module. The supramolecular CrypA was synthesized from vanillyl alcohol using a three-step method and deposited onto the surface of the sensing resonators via dropping method. Fast response and excellent repeatability were observed in gas sensing experiment, and the estimated detection limit and meas-ured sensitivity in gas dynamic range of 0 . 2% ~5% was evaluated as ~0 . 05 % and ~184 Hz/%, respec-tively. The measured results indicated the SAW sensor was promising for under-mine methane gas detection and monitor.
Li Yanyan 1,Yang Haotian 2,Zeng Yufan 3
Abstract: Urban capital structure was a complex?problem affected by multi-factors and multi-objective particle.This paper attempt ed to explore a scientific and appropriate d algorithm to construct the optimal capital structure model under the influence of multi-objective and multi-factors to analyze the situation of urban capital structure.First, the data in history could find the relationship among features of the data in history by using the regression characteristics of random forest. Then, the multi-objective particle swarm optimization algorithm was used to find values of the features that achieve the best results according to the existing relationship features. Then finding the most correlate data from the historical data based on the best eigenvalues of these effects. Therefore, the cities and the years with relatively better capital structure allocations are analyzed. We could play a good role in the reference and development of each city by continuously learning these superior structural configurations
Huang Yuda; Wang Yanran; Niu Sijie;
Abstract: In order to improve the super-resolution reconstruction quality of single image,an improved learning based super-resolution approach was proposed in this paper. To tackle the problem of low details of semi-coupled dictionary learning super-resolution algorithm , the paper presented learning strategy where detail constraint factor and semi-coupled dictionary learning were performed in turn. In reconstruction stage,detail constraint factor was designed by the gradient in both horizontal and vertical direction .Combined with semi-coupled dictionary learning ,detail constraint factor was used to further improve the super-resolution reconstruction quality. In order to improve the contribution of detail constraint factor on preserving boundary information,the adaptive regular parameter was explored via the approximate Laplacian distribution of edge difference .Compared with the semi coupled dictionary learning super-resolution algorithm,the peak signal-to-noise ratio of this method was increased by 1.5% on average . Experiments demonstrated that the proposed method could achieve better reconstruction effect in both subjective and objective evaluation and improve the quality of super-resolution.
Wang Jianming; Qiu Qinyu; He Xunchao
Abstract: By means of EDEM-FLUENT simulation and VOF(Volume of Fluid) method and Euler-Lagrangian model, a mixture model of discrete solid, continuous liquid and gas phase was constructed to simulate the three-phase flow with solid-liquid-gas in a stirring tank. The effect of the moving state of solid particles in stirring tank and free liquid level were explored. The gas-liquid continuous phase modeling based on VOF method using FLUENT software could capture gas-liquid interface well and the model was closer to the actual working condition. Based on the Discrete Element Method(DEM), the discrete element modeling of solid particles was established and its position information in the tank was simulated intuitively by the joint simulation of the two software. The dispersion of solid particles was consistent with the results obtained by Euler method.
Zhao Shufang, Dong Xiaoyu
Abstract: The language model based on neural network LSTM structure, the LSTM structure used in the hidden layer unit, the structure unit comprises a memory unit which can store the information for a long time, which has a good memory function for the historical information. But the LSTM in the current input information state9 does not affect the final output information of the output gate, get less historical information. To solve the above problems, this paper puts forward based on improved LSTM  (long short-term memory) modeling method of network model. The model increases the connection from the current input gate to the output gate, and simultaneously combines the oblivious gate and the input gate into a single update. The door keeper input and forgotten past and present memory consolidation, can choose to forget before the accumulation of information, the improved LSTM model can learn the long history of information, solve the drawback of the LSTM method is morerobust. This paper uses the neural network languag LSTM model based on the inproved model on TIMIT data sets show that the axxuracy of test. The results illustrate that the improved LSTM identification error rate is 5
% lower than the standard LSTM identification error rate. 
Jiang Yang1,Guo Jiankun 1,Wang Xiaomou 2,Hou Chaoqun 3
Abstract:  In the field of engineering construction, foundations were often placed adjacent to slopes. In the present research work, the evaluation of the maximum bearing capacity of slope foundations lacked a sufficientrate method. A bilateral asymmetry slip failure model for ground foundation adjacent to slope was develthe strength of soil on the side of flat ground was reduced and this is characterized by a mobilization factor. Base on limit equilibrium method and superposition principle, three bearing capacity factors were ex-pressed. The upper bound bearing capacity for ground foundation adjacent to slope was deduced based on limitanalysis approach. Centrifugal model tests were used to verify the theoretical analysis results; and thetion and failure characteristics of these foundations were studied. In addition the influence of variousuch as the contact conditions of the foundation, the location of the foundation, and the height of slope on themaximum bearing capacity of these foundation

Han Chuang, Wu Lili
Abstract: For the modeling and control of proton exchange membrane fuel cells, the empirical model and mechanism model based on polarization curve and parameter dimension are summarized, the electrochemical steady-state model and dynamic model based on electrochemical reaction, temperature, pressure and other factors are analyzed, and the intelligent method model based on neural network identification, swarm intelligence algorithm and support vector machine is introduced.The existing intelligent control strategies of proton exchange membrane fuel cells are summarized. Finally, it is pointed out that it will be a development direction of modeling to optimize the model parameters and environmental parameters of proton exchange membrane fuel cells by using swarm intelligence algorithm. The generalized Hamilton theory can also be tried to be used in the modeling of proton exchange membrane fuel cells.At the same time, the intelligent control strategy combining the new algorithm will become the research trend of proton exchange membrane fuel cell control.
CHEN Deliang,DONG Huina,ZHANG Rui
Abstract: Molybdenum disulfide ( MoS2 ) with a typical layered structure easily forms few-layered MoS2 nanosheets,and has a wealth of optical,electrical and catalytic performance with wide application potentials in areas such as photo-electrical and energy conversion. The preparation of few-layered MoS2 nanocrystals and MoS2-based nanocomposites using molybdenum-containing chemicals as starting materials by wet-chemical and vapor-deposition methods are the cutting-edge focuses of recent research. However,the synthesis of MoS2 nanocrystals from chemical reagents with a long route is not low-carbon and environment friendly. Molybdenite is a typical layered mineral and composed of layered MoS2 units. The amount of molybdenite in China is huge and it is a green and low-carbon way to prepare few-layered MoS2 nanomaterials via the intercalation-exfoliation strategy using the purified molybdenite as the direct raw materials.
Zhou Junjie, Wang Pu, Zhou Jinfang
Abstract: The analysis was held with the 125MW axial flow steam turbine impulse stage blade.The three-dimensional numerical simulation and optimization were conducted by using the commercial software ANSYS CFX.The results showed that the pressure distribution of blade surface reduced,and the radial secondary flow loses was controlled effectively,with optimizing the structure geometric parameters such as ellipticity of the leading edge and trailing edge,relative pitch,inter-stage ratio,and so on.Isentropic efficiency increased by 0.43%,the total pressure loss coefficiency decreased about 0.005.After the optimization,the aerodynamic performance of the blade increased,and the energy loss in the blade decreased and the efficiency of steam turbine increased.
Zhang Heng, Wang Heshan
Abstract: To improve the adaptability of echo state network (ESN),an optimization method based on mutual information (MI) and Just-In-Time (JIT) learning was proposed in this paper to optimize the input scaling and the output layer of ESN.The method was named as MI-JIT optimization method and the obtained new network was MI-JIT-ESN.The optimization method mainly consists of two parts.Firstly,the scaling parameters of multiple inputs were adjusted on the basis of MI between the network inputs and outputs.Secondly,based on JIT learning,a partial model of output layer was established.The new partial model could make the regression results more accurate.Further,a multi-input multi-output MI-JIT-ESN model was developed for the fed-batch penicillin fermentation process.The experimental results showed that the obtained MI-JIT-ESN model performed well,and that it had better adaptability than ESN model without optimization and other neural network models.
Li Yifeng, Mao Xiaobo, Yang Yihang, Zhu Feng
Abstract: In order to prevent the serious safety problem caused by the dry pot burning and stove explosion and firing,an anti-overheating system was designed.The system of infrared temperature sensor MLX90614 on the bottom of the pot was used to realize the non-contact real-time temperature monitoring.The real-time temperature data was collected and processed by the STM32 microcontroller and SMBus.When the temperature of the bottom of the boiler was beyond the normal heating range,the temperature monitoring module could send a voice alarm.When the threshold value of the dry burning temperature was reached,the gas circuit could be cut off by the control circuit serially connected in the thermocouple temperature detection circuit.Experimental results showed that the proposed system could cut off the gas path once the preset temperature reached and prevent the dry pot burning effectively.
Shi Chunyan1,Fan Bingbing1,Li Yaya1,Hu Yongbao1,Zhang Rui2
Abstract: In this work,graphene oxide (GO) was prepared by an improved Hummers method.Zirconia/graphene composites (ZrO2/rGO) were rapidly synthesized by hydrothermal method with Zr(OH)4/rGO as precursor prepared by ultrasound-stirred-coprecipitation.The adsorption capacity of Zr (OH) 4/rGO and ZrO2/rGO composites decreased with the increase of pH value and increased with the increase of phosphate concentration and the solution temperature.The maximum adsorption capacities of Zr (OH)4/rGO and ZrO2/rGO composites were 81.84 mg/g and 63.58 mg/g respectively at pH 2.0.The adsorption kinetics of these two adsorbents accorded with the pseudo-second-order model and isothermal adsorption complied with the Langmuir isotherm equation.The results of its recycling properties showed the adsorption capacity decreased for the Zr (OH) 4/rGO samples,while ZrO2/rGO samples were almost the same as the initial adsorption performance.
JIAO Liu-cheng,YAO Tao
Abstract: In view of the speed control problem of the linear permanent magnet synchronous motor ( L.PMSM) ,which is viewed as an energy-transformation device,from the viewpoint of energy shaping,applying port-con-trolled Hamultonian with dissipation and passivty-based control theory , the port-controlled Hamltonan modelof LPMSM is deduced. Based on the Hamiltonian structure,the desired Hamiltonian function of the closed-loop system is given, and the speed controller is designed by using the method of interconnection and dampingassignment. In the design,the Hamiltonian function is used directly as the storage function,and the systemcan achieve the required performance and bring more definite physical meaning on the condition of satisfyingpassivity. The simulation results show that the closed-loop control system can respond quickly to changes inload resistance and has good robustness.
Maling1,Jiang Huiqin1,Liu Yumin2
Abstract: In order to meet the practical requirements of automatic application and renewal of driver’s license,a high speed system for automatic recognition of driver’s licenser was designed and implemented.The hardware was designed to capture the image of the driver’s license that contained the smallest identifiable features.Because of the complex background such as the shadow line and so on in the driver’s license images,the existing recognition algorithms had the low recognition accuracy,universality and robustness problems.This paper first solved the segmentation difficulties for uneven illumination,noise,tilt and shadow line character by combined adaptive binarization and morphological processing.Then,the Blob analysis was used to extract the important local features of the driver’s license,and the recognition accuracy was further improved by using the prior information and the correlation matching algorithm.The experimental results showed that not only the false recognition rate was 0,but also the practical products was developed,and the better social effects were achieved.
Li Cailin, Chen Wenhe, Wang Jiangmei, Tian Pengyan, Yao Jili
Abstract: Cliff and steep slope are important landscape elements of topographic map, and these elements play a very important role in the construction of the ecological environment and prevention of geological disasters, etc. However, it is unfavorable to observe and process data because of vegetation occlusion on cliff. In this paper, we present a cliff vegetation filtration method based on the principle of surface orthographic projection. Firstly, transform the original three dimensional point cloud of cliff to the spatial cartesian coordinate system, whose xy plane is the cliff face and z-axis is perpendicular to the direction of the cliff surface. Then the grid on the xy plane is divided to establish local grid Digital Terrain Model ( DTM) by fitting surface, and the vegeta-tion points can be extracted through setting a reasonable distance threshold. Finally, after inverse projection transformation, cliff rocky points preserved are mapped to the original spatial coordinate system. The experi-mental analysis using actual cliff point cloud data shows that the cliff point cloud vegetation filtering method based on the surface orthographic projection is feasible and effective.
Sun Xiaoyan, Zhu Lixia, Chen Yang
Abstract: Interactive evolutionary algorithms with user preference implicitly extracted from interactions of user are more powerful in alleviating user fatigue and improving the exploration in personalized search or recommendation. However, the uncertainties existing in user interactions and preferences have not been considered in the previous research, which will greatly impact the reliability of the extracted preference model, as well as the effective exploration of the evolution with that model. Therefore, an interactive genetic algorithm with probabilistic conditional preference networks (PCP-nets)is proposed , in which, the uncertainties are further figured out according to the interactions, and a PCP-net is designed to depict user preference model with higher accuracy by involving those uncertainties. First, the interaction time is adopted to mathematically describe the relationship between the interactions and user preference, and the reliability of the interaction time is further defined to reflect the interactive uncertainty.The preference function with evaluation uncertainty is established with the reliability of interaction time. Second, the preference weights on each interacted object are assigned on the basis of preference function and reliability. With these weights, the PCP-nets are designed and updated by involving the uncertainties into the preference model to improve the approximation. Third, a more accurate fitness function is delivered to assign fitness for the individuals. Last, the proposed algorithm is applied to a personalized book search and its superiority in exploration and feasibility is experimentally demonstrated.
Mao Xiaobo, Zhang Qun,Liang Jing, Liu Yanhong
Abstract: In this paper,a new algorithm of license plate recognition in the hazy weather was designed.Firstly,defogging operation was introduced for license plate image in the environment of hazy by using improved dark channel prior.Then after the pretreatment,positioning,segmentation and extraction,coarse grid characteristic matrix is obtained.Finally,radial basis function (RBF) neural network,which was optimized by particle swarm algorithm in advance,was used to identify the character.The experiment results showed that the improved algorithm not only had a good effect on haze removal,but also reduced the duration of defogging,which effectively improve the license plate recognition speed and accuracy in fog and haze weather.
Liang Jing1,Liu Rui1,Qu Boyang2,Yue Caitong1
Abstract: Based on the characterisities of large-scale problems, lager-scale optimization were grossly analyzed. This paper  introduced some methods for lager-scale problems.The methods included the initialization method, decomposition strategy, updating strategy and so on. This paper mainly focued on the search strategy, update strategy, mutation strategy and cooperative coevolution. Meanwhile, the characteristics of lager-scale optimization algorithm testing function set and evaluation method were listed. Finally, the future research directions were given.
Liu Qian; Feng Yanhong; Chen Yingying;
Abstract: Moth-flame optimization algorithm ( MFO) has some drawbacks in solving optimization problems ,such as low precision and high possibility of being trapped in local optimum. A modified MFO algorithm based on chaotic initialization and Gaussian mutation is proposed .Firstly, the cube chaotic map is used to initialize the moth population ,which makes the moth more evenly distributed in the search space. Then, Gaussian mutation is adopted to disturb a few poor individuals to enhance the ability of escaping the local optimum .Finally ,Archimedes curve is introduced to expand the search scope and strength the exploration ability in the unknown field .A series of experiments are carried out on CEC14 test function set and 2l extensible Benchmark functions .Compared with standard moth-flame optimization algorithm,genetic algorithm,artificial bee colony algorithm ,particle swarm algorithm,differential evolution algorithm,flower pollination algorithm, and butterfly optimization algorithm ,the results demonstrate that the proposed algorithm is strengthened in obtaining solutions with better quality and convergence.
Zhao Huadong, Jiangnan, Lei Chaofan
Abstract: Commercial automayic guided vehicles (AGV) usually used chain transmission mechanism power transmission, and the fixed structure of the wheel could be considered as cantilever structure. Therefore, the problem of wheels "tilting" and start-stop "shocking" easily occurs, which limited the accurate movement of the AGV during frequent and rapid acceleration or deceleration. In this paper, AGV designed by a company was taken as an example. Though repeated tests and numerical simulations, the structure and force analysis were used to find out the reasons for this phenomeno. The larger stress was caused by the "L"-shaped suspension mechanism, which magnified the contact gaps of each component; the uses of the chain transmission mechanism could make it easy for the AGV to form gaps between the sprocket and the chain when the AGV started, stopped, moved forward, backward frequently. Then a new drive unit structure was put forward from the engineering point of view, which could solves the above problems, at the same time-greatly could reduced the stress in the mechanism, could improve the transmission precision, and could provide a more practical and optimized driving structure for the design of AGV.
WAN Ya-zhen,LIU Ya-nan,CHEN Di
Abstract: PTA supported catalyst was prepared by dip roasting method for the synthesis of 2-(4’ -ethyl benzoyl) benzoic acid (BEA) from phthalic anhydride and ethyl benzene as raw materials and chlorobenzene as solvent.The experimental results showed that when the load of PTA was 30%(mass fraction) and the roasting temperature was 300℃, the catalytic activity of PTA was more than doubled with SiO2 as the carrier.The effects of XRD on loading capacity and NH3-TPD on calcination temperature were analyzed. Ft-ir and BET were used to characterize PTA/SiO2 catalysts.The reuse performance of PTA/SiO2 catalyst was investigated, and the results showed that the original catalytic activity of PTA/SiO2 was still maintained after repeated use.
LIU Zhenghua1, WANG Jing2,DU Haiying’1,2
Abstract: In order to solve the problem that electrospinning process is hard to control,FEA tool softwareCOMSOL Multiphysics was used to simulate the the electric field orientation within the electrospinning. Basedon the vector maps and contour lines, the electric fields distribution was analyzed. Which includes single-nee-dle electrospinning device,electrospinning device with circle and orparallel auxiliary electrodes. Experimentwith parallel auxiliary electrodes was conducted,and the deposition area with the ellipse shape matched thesimulation result.
Liu Guangrui; Zhou Wenbo; Tian Xin; Guo Kefu
Abstract: BP neural network for effectively fusioning the information obtained by arc sensor and ultrasonic sensor and information of welding parameters such as welding current,welding speed,welding groove and so on was used to obtain the prediction model of weld penetration depth.Simulation results showed that:the prediction model of weld penetration depth could measure the weld penetration quickly,accurately and in real time.For the precise control of weld penetration,parameters self-tuning fuzzy PID controller was desing,which combined with the advantages of traditional PID controller and fuzzy controller.Smulation results showed that compared with traditional PID controller,parameters self-tuning fuzzy PID controller had a significant advantage in the performance of the system.
Li Haibin1,Ke Shengwang2,Shen Yanjun2
Abstract: With the increasing of highway extension projects and widely use of sheet piles in railway construction,the mechanical behavior of extension embankment was analyzed through simulating different kinds of pile and load of different positions.Then the optimal pile kind and the most unfavorable load position were proposed.Through continuous observing of settlement in sheet pile section and CFG pile section,the optimal adaptability of sheet pile was showed in extension projects.The analysis results showed that the effect on settlement of PTC pile,CFG pile and cement mixing pile was gradually decreased.The PTC pile and CFG pile should be firstly selected from the options of controlling settlement.The most unfavorable load position was in new embankment and its quality was the key control point in construction.The effect on decreasing differential settlement was appeared in process of semi-rigid base construction,and it would be even obvious in pavement construction.The sheet pile was an effective supplement to traditional soft soil treatment methods.It had better adaptability and foreground in highway extension projects.
Liu Yanhong, Zhao Jinglong
Abstract: A high-order non-singular terminal sliding mode control strategy is proposed to address the issue of achieving maximum wind energy capture in permanent magnet direct drive wind power generation systems. Based on the nonlinear model of the permanent magnet direct drive wind power generation system, a maximum power point tracking method based on optimal torque tracking is proposed, Applying high-order non-singular terminal sliding mode control to the design of torque controller and current controller for permanent magnet synchronous generator (PMSG), achieving fast tracking and stable control of the maximum power point of the permanent magnet direct drive wind power generation system without wind speed sensors. Simulation results verify the effectiveness of the proposed control scheme
Wei Ran
Abstract: Impact effects on carbon emissions intensity by population, per capita GDP, and main types of energy in China were evaluated with the fixed effect model based on LSDV estimation with reasons of the results of Likelihood Ratio Test and Hausman Test. The traditional model of STIRPAT was improved by adding Carbon Emission Intensity and Energy Consumption Variables, which included consumptions of coal, coke, crude oil, gasoline, kerosene, diesel oil, fuel oil, and natural gas, except population and per capita GDP. The results show that consumptions of different types of energy have different impacts on carbon emissions intensity from 2004 to 2016 in China. Five variables of energy consumption, which were corresponding to coal, coke, gasoline, diesel oil, and natural gas, had played positive effects on carbon emission intensity from the data of China Statistical Yearbook and China Energy Statistical Yearbook of 200 5 to 201 7. Other variables of crude oil consumption, fuel oil consumption, and kerosene consumption took opposite impact on carbon emission intensity. Moreover, change of population had the most significant favorable influence on carbon emission intensity in all studied variables. Unfortunately, per capita GDP and coal consumption contributed to the increasing of carbon emission intensity in China in the studied period.
Dong Chee-hwa1,Wang Guoyin2,Yongxi3,Shi Xiaoyu2,Li Qingliang4
Abstract: Principal Component Analysis (PCA) is a well known model for dimensionality reduction in data mining,it transforms the original variables into a few comprehensive indices.In this paper,we study the principle of PCA,the distributed architecture of Spark and PCA algorithm of distributed matrix from spark’s ML-lib,then improved the design and present a new algorithm named SNPCA (Spark’s Normalized Principal Component Analysis),this SNPCA algorithm computes principal components together with data normalization process.We carried out benchmarking on multicore CPUs and the results demonstrate the effectiveness of SNPCA.
Mao Xiaobo, Hao Xiangdong, Liang Jing
Abstract: In view of the problem of object deviation when occlusions occur during the target tracking, a new algorithm using Mean Shift with ELM is proposed. According to the formal information of the object’ s loca-tion, current possible location was predicted by ELM, the iteration was started from the possible location in-stead of formal location, and the object’ s real center is calculated by mean shift algorithm. The simulation re-sults show that proposed algorithm can track precisely target occluded, operation time and number of iteration are reduced so that efficiency and robustness are improved.
Sheng Zunrong1,Xue Bing1,Liu Zhouming1,Wei Xinli2
Abstract: A direct-contact method of zeolite adsorption liquid water was adopted to enhance heat and mass transfer rate within adsorption heat transformer.Hot water was recycled to generate superheated steam directly,and then saturated zeolite would be regenerated by drying gas.The reactor with was filled spherical zeolite with same mass and different diameters.The mass of steam generated by small particle packed bed was 64.89% higher than that generated by big particle packed bed.The maximum steam temperature and gross temperature life had increased by about 37C.Experiments of two kinds of packed types in double layer reactor (finecoarse bed and coarse-fine bed) have shown that small particle played a more effective role for the heating of steam and packed bed;the mean maximum temperature of the steam at the top of fine-coarse bed is 37.23% higher than that of coarse-fine bed and the lasting time of the maximum temperature is decreased by 14.25%.The steam generation rate of fine-coarse bed was 16.18% higher than that of coarse-fine bed,which is more efficient in steam generation.In regeneration process,drying time of upper reactor was 25.03% shorter than coarse-fine bed.It concluded that fine-coarse bed was more effective for zeolite regeneration.
Cao Ben, Yuan Zhong, Yu Liu Hong
Abstract: During heating process of sintering furnace,the model parameters were easy to change,and traditional PID control was difficult to achieve the desired control effect.This paper used particle swarm optimization algorithm to identify the mathematical model of sintering furnace,for sintering furnace with high inertia,time-variation and strong time delay etc,a method of supervision and control based on RBF neural network,which combined PID control with neural network control.When temperature or parameters changed greatly,PID control played a major role.neural network played a regulatory role and compensated the shortage of PID control.The simulation results of MATLAB software showed that this method could improve the control precision of sintering furnace,which had a certain practicality.
Deng Jicai, Geng Yanan
Abstract: In order to improve the detection rate of the acoustic magnetic EAS system,and enhance the antiinterference performance,the paper studied a new label detection algorithm that was the combination of the improved artificial fish swarm algorithm (IAFSA) and the support vector machine (SVM).An improved scheme was proposed after analyzing the strengths and weaknesses of the traditional AFSA and SVM.The experimentalresults showed that the IASFA had the faster rate of convergence and the higher accuracy than AFSA,the genetic algorithm and the particle swarm algorithm;The IASFA-SVM had the higher detection rate,the longer detective distance and the lower rate of false than the traditional magnetic label detection algorithm,and the IASFA-SVM also could meet the requirements of real-time detection.
LIU Zhi-fang ,LIU Xin-hong,HUANG Ya-lei,MA Teng
Abstract: The effects of nano-ZR02 powder on the properties, composition and structure of Al-Si composite Al203-C were studied by using plate corundum aggregate and fine powder, Al powder, Si powder, graphite and nano-Zro2 powder as raw materials and phenolic resin as binder.The results show that the introduction of nano-ZRO2 powder has little effect on the strength of the sample at room temperature and high temperature, but it is beneficial to improve the molding density and oxidation resistance of the sample, and can significantly improve the thermal shock resistance of the sample.The reason for the increase of sample density is that the nano-cobalt oxide has a good filling effect and helps sintering.Nano-zro2 can promote the reaction of Al and Si to generate more non-oxide whiskers, and form a cross-linked network structure in the sample, and the toughening of nano-powder and the phase transition toughening of ZrO2 are conducive to improving the thermal shock resistance of the sample.
Ding Guoqiang1Zhang Duo1Xiong Ming1Zhou Weidong2
Abstract: In order to improve the precision requirement about the attitude control of the strap-down inertial navigation system,the high order moment matching UKF (Higher-order Moment Matching UKF,HoMMUKF) algorithm was proposed,that is to estimate the SINS’ attitude parameters of based on its quaternion error model.In the recursive calculation process,for accurately approximating computational purposes,it uses high order moment matching method to calculate the average skewness value and peak value of the predicted sampling points set and their weights of the system state parameters in the view of the probability distribution.Making use of attitude quaternion method,then onlinear quaternion error model was constructed,in which model the systemnoise vector depends on system state vector,meanwhile construct its measure equation whose measurement noise vector depends on quaternion measurement vector by pseudo observation vector method was constructed,the weighted average of estimated quaternion with Lagrangian operator was calculated,the system noise variance calculation with the system noise separation algorithm was carried out,and finallyconstruct the SINS’ attitude estimation HoMM-UKF algorithms simulation on SINS attitude experiment platform was designed.It can be seen that HoMM-UKF algorithm’s calculation accuracy is higher than others and has better numerical stability,comparison of the UKF,and CDKF algorithms,and so the HoMM-UKF algorithm’s feasibility and calculation accuracy is verified.
Xiao Junming, Zhou Qian, Qu Boyang, Wei Xuehui
Abstract: The energy supply of power system is very important to modern society, and the scientific and effective solution to the problem of environmental economic dispatch of power system is the guarantee of energy supply. The multi-objective evolutionary algorithm has unique advantages in solving the problem of environmental economic dispatch of power system. This paper presses In chronological order, the multi-objective evolutionary algorithm is first introduced, and then the application of the multi-objective evolutionary algorithm in the power system environmental economic dispatching problem is discussed. The direction of development is prospected.
ZHU Yazhong,LI Shunyi,LUO Yimeng ,MA Hongye,WANG Yan
Abstract: Self-made biological fillers embedded with Pseudomonas putida were used as biofilter packing materials for treating toluene.The effects of inlet loading rate (ILR) and empty bed residence time (EBRT) were evaluated.Changes in micro-organisms before and after the shut down period and its effect on biofilter performance were investigated.Results indicated that,no need for hanging film,activities of micro-organisms were high,capacity to eliminate toluene was strong.Optimal EBRT was 74.2 s,and removal efficiency ranged from 49.3 to 97.3 %;maximum elimination capacity,16.97 g · (m3 · h)-1 was occurred at ILR of 22.11 g · (m3 · h)-1.The recovery time needed for achieving constant state,after biofilter shut down for 3 d,7 d and 30 d,were 5,21 and 45 h,respectively.Microbial counts after recovery were significantly higher than the 30d shut-down period,and lower layer had the highest microbial population.
Hu Xiaobing, Xie Zhenfang, Xie Ji, Xie Lili, Zhu Zhigang
Abstract: Micro/Nano-particles of CuO were prepared with hexamethylenetetramine template. The composi-tion and morphology of the product were characterized by SEM and X-ray diffraction. The synthetic powder was prepared as sensitive membrane, and its gas sensitivity was studied with a static gas distribution method. The results indicated that the uniform copper oxide powders was synthesized at the 110℃, and the molar ratio be-tween copper nitrate and hexamethylenetetramine was 1∶45. The spindle structure was around 1~2 μm, and was composed of 100 nm nanoplates. The sensor had better selectivity with CH3 COCH3 and H2 S. Copper ox-ide showed good selectivity to hydrogen sulfide and its sensitivity had a certain degree of improvement after fur-ther doping 0. 25% ~1. 25% noble metal catalyst Pt.
JIANG Jian-dong1 ,ZHANG Hao-jie1 ,WANG Jing2
Abstract: To further improve the accuracy of power load forecasting,on the basis of the analysis of affectingfactors of power load, a combination prediction model based on HHT is proposed. This model uses EMD algo-rithm to decompose the original load sequence. Thus, a stationary sequence of different frequencies,which ismore predictable than the original load sequence,can be obtained. Based on the components of different fre-quencies,according to the characteristics of the different frequency of subsequence ,the RBF neural network ,BP neural network and time series model are selected to forecast while considering the influence of temperatureon the load. Then,a new combined model can be achieved. The experiment shows that the proposed modelcan effectively improve the accuracy of load forecasting.
Ding Chang, Fu Yantang, Wu Xuehong, Gong Yi
Abstract: FLUENT software was adopted to simulate the sloshing process of liquid in container under the sudden braking condition based on VOF (volume of fluid) model.The pressure variation of front and back head was compared,which showed that the sloshing liquid mainly had a greater impact on the front head.Baffles could effectively weaken the sloshing in the container,reduce the impact on the head and improve the container safety.The liquid impact on front head was studied in the condition of different filling ratio for different baffle arrangement(all down,all up,up and downinterlaced,left and right interlaced) of five same arc baffles.Results show that the arrangement style of left and fight interlaced 、all down could reduce impact load on front head for low filling ratio,however the arrangement style of up and downinterlaced all up had poor anti-wave effect.The anti-wave effect of the arrangement style of left and right interlaced became poorer and poorer with the increment of filling ratio.Compared with other arrangement style,the arrangement style of all down had better anti-wave effect.
LIU Min-shan,XU Wei-feng ,JIN Zun-long,WANG Yong-qing,WANG Dan
Abstract: A numerical simulation of trisection-ellipse heat exchangers with helical baffles is carried out, andthe helix angles are 15° and 20° respectively , and we studied the impact of triangle leakage between continu-ously overlapped and adjacent baffles on heat transfer and resistance performance of heat exchangers.Throughthe comparative analysis about the simulation results of existing triangle leakage and that of blocking trianglearea without leakage , the results show :triangle leakage makes a more serious short circuit flow for the shell-si-ded fluid;Triangle leakage makes heat transfer coefficient,shell-sided pressure drop and comprehensive per-formance of heat exchanger reduce. When triangle leakage is blocked,heat transfer coefficient increases by8.5% ~ 11% , shell-sided pressure drop increases marginally , comprehensive performance increases by 8.1 %~11 . 1 % .
FANGShuqi1,2,HELiping1,ZHANGLonglong1,CHANGChun1,2,BAI Jing1,2,CHENJunying1,
Abstract: The effects of processing variables,such as screw speed,initial moisture content and the length ofthe straw plug pipe of extrusion process on the dewatering rate,handling capacity ,output per kW h etc.were experimentally studied using a low CR screw straw extruder. And the response surface optimization exper-imental results showed the extruder can run efficiently , stably and continuously with considerate dewateringrate , handling capacity and output per kW ·h under the conditions that moisture content is 85% ,screw speed50.8 r/min,length of the straw plug pipe is 26.91 mm.
Deng Shaohong 1,Li Ling 1Guibin 2
Abstract: First, according to the theory of space crowdsourcing, the concept of equivalent task representative points is proposed, and the relationship between the original task pricing law and task density, membership density, member average credibility and nearest neighbor reach distance is studied. On this basis, from the perspectives of the contractor, the platform and the contractor, According to the four steps of completing the task, a task pricing model based on multi-objective programming , a member dynamic grab order model, a task allocation model and a task completion probability prediction model are respectively established. Furthermore, the TOPSIS method is used to calculate the comprehensive evaluation index of different pricing schemes, and then choose the optimal task pricing scheme by the ranking result of the comprehensive evaluation index. Finally, the optimized scheme is compared with the original scheme. Under the condition that the total cost of the contractor is as low as possible, the platform task completion rate, the average individual member income and the unit reputation value conversion rewards are significantly improved, that is, the crowdsourcing performance are improved. The result verifies the feasibility and effectiveness of the model and provides reference for the task pricing of the crowdsourcing platform
Li Jingli, He Pengwei, Qiu Zaisen, Li Yuanbo, Guo Liying
Abstract: Impulse charactersitic of grounding devices was the important factor of lightning withstand level and lightning trip-out rate of transmission line.Based on HIFREQ program and FFTSES program in grounding power system analysis software CDEGS,this paper presented a grounding system impulse characteristic modeling considered soil frequency-dependence,especially,the Visacro-Alipio soil frequency-dependence formula has been introduced.The impact of the soil frequency-dependence on the effective length of the grounding device in different initial soil resistivity and different impulse current waveform was analyzed.The calculating results showed that when considering soil frequency-dependence,the impulse effective length would be shorter,especially for the grounding devices buried in high resistivity soil.
FENG Dong-qing ,XING Kai-li
Abstract: Focusing on the target tracking problem in resource-constrained wireless sensor networks,a novelenergy-balanced optimal distributed clustering mechanism is adopted by introducing an energy-balanced indexbased on the standard deviation of residual energv of nodes. Then . it is transformed into a multi-obijective con-strained optimization problem,and a binary particle swarm optimization algorithm is employed to solve thisproblem. Simulation results in Matlab environment show that the energy-balanced optimal distributed clusteringmechanism guarantees energy balance and tracking accuracy comparing with the clustering mechanisms respec-tively based on the energy consumption and the extended Kalman filter,and that it improves the network life-time of nearly 2-fold ,effectively prolonging the network lifetime.
Wang Dongshu, Tan Dapei, Wei Xiaoqin
Abstract: Based on the characteristic of face orientation,position and the light background in face recognition,a new method of face orientation recognition based on development network is proposed.The characteristic of human’s eye was very prominent,so the position of eyes was chosen as the face orientation feature vector.And the deveiopment network model was used to recognize human’s face orientation in the different light background images.The result showed that this method could effectively solve the difficult problem of face orientation recognition under varying illumination conditions by comparing with the test results of other methods,which was fast,stable and effective.The recognition rate was as high as 100%.
Zhang Zhonghui, Liu Gushuai, Xiong Jianfeng, Liu Xiaowan, Xu Gaochao
Abstract: The distribution of charging and battery swap station has always been one of the key problems for the development of electric vehicle.A site location of charging and battery swap station could be represented by a network with traffic flow,the distance from the power source,parcel load,and city block position respectively.Spectral clustering methodology was used to reveal the internal connectivity structure of such a network.First of all,it adopted the min-max standardized method in dimensionless to establish a sample space matrix S.Then,the normalized Laplacian was achived according to the similarity between matrix W and matrix D.The former two and three feature vector of Laplace matrix were mapped to the 2d and 3d space to observe parcel partition.Finally methodology goes beyond the standard k-means algorithm by instead representing the complete network substructure as a dendrogram and verifies its correctness by analyzing the voltage sags.We include the results of our methodology for a real distribution network in Jiangxi province.Example shows that our methodology has certain rationality and it could be helpful for distribution network planning.
Chen Tiejun, Cai Jinshou, Guo Li
Abstract: Aiming at the defect that wavelet analysis cannot make full use of the unique geometric features of the data itself when dealing with multi-dimensional graphics, the second generation of curvelet transform (SGCT) method is used to process face images, and the image with the largest standard deviation is selected. Scale layer coefficients are used to complete the feature extraction of face images, and combined with data dimensionality reduction based on bidirectional two-dimensional principal component analysis (B2DPCA), a hybrid voting mechanism-based extreme learning machine (voting Extreme learning machine, VELM) face recognition algorithm. By comparing with the classification results of other algorithms, it is proved that the algorithm has a higher recognition accuracy.
Dai Pinqiang1,Song Lairui2,Cui Zhixiang3,Wang Qianting3
Abstract: Chitosan ( CS)/poly ( vinyl alcohol) ( PVA) composite fibers were fabricated by electrospinning in this study. The influences of material formulation and formed time on the viscosity,electrical conductivity and the morphology, average diameter, diameter distribution of CS/PVA composite fiber were investigated. The re-sults showed that, the introduction of CS could increase the viscosity,electrical conductivity of CS/PVA blend solution. And the viscosity of blend solution decreased with the increase of formed time. In addition, the more CS content was, the smaller diameter of CS/PVA composite fiber would be. The fiber-forming capacity of CS/PVA blend solution decreased dramatically as the solution formed time increased.
MU Xiaomin , SHI Guangqiang,LIU Ying , YANG Shouyi
Abstract: To solve the problem of contract-based cooperative spectrum sharing between multiple primary usersand multiple secondary users,we put forward a contract design method based on statistical theory to maximizethe total utility of primary users. Firstly,the primary users make full use of the accepting contract statisticalinformation of secondary users to design a reasonable contract. Then,the primary users according to the statis-tical expected utility to obtain the optimization problem of maximizing theirs total expected utilities. Further-more,we simplify the problem in theory and exploit the genetic algorithm to derive the sub-optimal solution.The simulation results and analysis show the contract design method can solve the problem of contract-basedcooperative spectrum sharing successfully.Compared with the DMA-UI,the approach we formulated can makeprimary users obtain a higher utility, and further improve the primary users’energy efficiency and spectrumefficiency.
CHEN Deliang,DONG Huina,ZHANG Rui
Abstract: Molybdenum disulfide ( MoS2 ) with a typical layered structure easily forms few-layered MoS2 nanosheets,and has a wealth of optical,electrical and catalytic performance with wide application potentials in areas such as photo-electrical and energy conversion. The preparation of few-layered MoS2 nanocrystals and MoS2-based nanocomposites using molybdenum-containing chemicals as starting materials by wet-chemical and vapor-deposition methods are the cutting-edge focuses of recent research. However,the synthesis of MoS2 nanocrystals from chemical reagents with a long route is not low-carbon and environment friendly. Molybdenite is a typical layered mineral and composed of layered MoS2 units. The amount of molybdenite in China is huge and it is a green and low-carbon way to prepare few-layered MoS2 nanomaterials via the intercalation-exfoliation strategy using the purified molybdenite as the direct raw materials.
RONG Xian1,2 ,SONG Peng1,ZHANG Jian-xin’,LIU Ping1,2
Abstract: Based on the quasi-static test study of seismic performance of HRB500 reinforced concrete piers ,influence law about steel strength ,the spacing,the axial compression ratio on seismic behavior was obtainedaccording to the analysis of its failure characteristics, hysteresis curves,skeleton curves,stiffness degradationunder low eyclic loads. The results show that increasing steel strength can improve components’ bearing ca-pacity and deformation capacity obviously , stirrup ratio can not influence members’ bearing capacity and de-formation capacity ,axial compression ratio can improve components’bearing capacity , but on the other hand,it is useless to improve components’deformation capacity.
Zhao Shujun, Duan Shaoli, Zhang Xiaofang, Li Lei, Liu Xiaomin
Abstract: The calibration method of the zoom camera is studied. The self-calibration method based on the two vanishing points is used to calibrate the general parameters of the zoom camera under two fixed focal lengths. By comparing with Zhang Zhengyou’s calibration method and the results of the machine vision software Halcon calibration, the results are verified. The feasibility and robustness of this method are verified. In order to better reflect the zoom characteristics of the zoom camera, a thick lens model that can more accurately describe the zoom camera is established. The author performs SIFT feature matching on the zoom image, and according to the matching point pair The linear equations are established, and the least square method is used to estimate the zoom center of the zoom image. In addition, the optical center displacement between different focal lengths is also calculated. The experimental results show that there is an obvious gap between the optical center displacement and the focal length, which shows that The thick lens model is more suitable for describing the zoom lens of the camera.
Li Yifeng, Mao Xiaobo, Yang Yihang, Zhu Feng
Abstract: In order to prevent the serious safety problem caused by the dry pot burning and stove explosion and firing,an anti-overheating system was designed.The system of infrared temperature sensor MLX90614 on the bottom of the pot was used to realize the non-contact real-time temperature monitoring.The real-time temperature data was collected and processed by the STM32 microcontroller and SMBus.When the temperature of the bottom of the boiler was beyond the normal heating range,the temperature monitoring module could send a voice alarm.When the threshold value of the dry burning temperature was reached,the gas circuit could be cut off by the control circuit serially connected in the thermocouple temperature detection circuit.Experimental results showed that the proposed system could cut off the gas path once the preset temperature reached and prevent the dry pot burning effectively.
Han Chuang, Wu Lili
Abstract: For the modeling and control of proton exchange membrane fuel cells, the empirical model and mechanism model based on polarization curve and parameter dimension are summarized, the electrochemical steady-state model and dynamic model based on electrochemical reaction, temperature, pressure and other factors are analyzed, and the intelligent method model based on neural network identification, swarm intelligence algorithm and support vector machine is introduced.The existing intelligent control strategies of proton exchange membrane fuel cells are summarized. Finally, it is pointed out that it will be a development direction of modeling to optimize the model parameters and environmental parameters of proton exchange membrane fuel cells by using swarm intelligence algorithm. The generalized Hamilton theory can also be tried to be used in the modeling of proton exchange membrane fuel cells.At the same time, the intelligent control strategy combining the new algorithm will become the research trend of proton exchange membrane fuel cell control.
Li Lingjun, Jin Bingma, Yanli Han, Jie Hao, Wang body
Abstract: The method of extracting degradation features was proposed based on MEMD and MMSE to solve the problem that non-stationarity of fault signals of roller bearing and degradation condition, which was characteristic of non-ststionarity and hard to recognize. The character of MEMD was adopted to catch different scales of signals effectively during the process of multiscalization,  which made complexity of different degradation condition distinguished better than other methods. Firstly, multichannel signals corresponding to various degradation condition of roller bearing were decomposed adaptively using MEMD, then, the reconstructed signals by multiscale IMF was dealt with MSE analysis. The results showed that the proposed method could efficiently evaluate the degradation trend of roller bearing by handing the experimental signals.
Li Guang1, Zhang Heng2, Wang Jie2, Zhu Xiaodong2, Yue Caitong2
Abstract: Warning technology of drilling engineering was the key technolog of drilling safety protection. Through the monitoring of real-time well site drilling process parameters, huge amounts of drilling data mining and intelligent learning, abnormal state modeling and optimization, abnormal state modeling and optimization, abnormal characteristics of the early warning model online judging process, achieved the goal of oil drilling abnormal state arly warning, and prevention of drilling engineering accidents. This paper reviewed the development course of early warning technology, introduced the drilling engieering warning technology architecture, and also introduced the early warning teachnology in detail and compared their characteristics, finally depicted the development of future early warning system for drilling engineering.
Liu Ke 1;Gong Dunwei 2
Abstract: In the human-computer interaction system based on fingertip, the position of fingertip center is very important. By solving the multi-objective optimization model for the fingertip localization, several fingertip center positions can be obtained. The fingertip pixels distribute around the fingertip centers, so the optimal solution components of this optimization model have the above distribution law. Using the estimation of distribution algorithm with the distribution law to solve this optimization model, can obtain accurate results. This paper discusses the estimation of distribution algorithm for the fingertip localization. It proposes that the decision variable dimension, population size, maximum sampling variance, and minimum sampling variance are the main parameters of this estimation of distribution algorithm. The experimental results show that each main parameter has its best value; when their values are their best values, the fingertip center positions obtained by the proposed method excel the results of the existing methods.
Zhao Fengxia , Jin Shaobo , Li Jifeng
Abstract: A method of considering tolerance principle for three dimensional tolerance analysis was put forward. Based on small displacement torsor (SDT) theory and modal interval arithmetic, the tolerance models of size tolerance and geometrical tolerance of the feature of size apply independent principle, envelope requirement, maximum material requirement, least material requirement or reciprocity requirement, were established respectively. By using the space vector to represent 3D dimension chain, a mathematical model is built to calculate the closed loop tolerance based on space vector loop stack principle. The application of the proposed method is illustrated through presenting an example, the tolerance analysis steps are given, and the availability of the proposed method was proved successfully.
Dong Chee-hwa1,Wang Guoyin2,Yongxi3,Shi Xiaoyu2,Li Qingliang4
Abstract: Principal Component Analysis (PCA) is a well known model for dimensionality reduction in data mining,it transforms the original variables into a few comprehensive indices.In this paper,we study the principle of PCA,the distributed architecture of Spark and PCA algorithm of distributed matrix from spark’s ML-lib,then improved the design and present a new algorithm named SNPCA (Spark’s Normalized Principal Component Analysis),this SNPCA algorithm computes principal components together with data normalization process.We carried out benchmarking on multicore CPUs and the results demonstrate the effectiveness of SNPCA.
ZHANG Chunjiang1,2,TAN Kay Chen2,GAO Liang1, wU qing3
Abstract:  In order for effective application of Multi-Objective Evolutionary Algorithm based on Decomposition(MOEA/D) in engineering optimization,normalization of the range of objective values is needed. A self-a-daptive s constrained Differential Evolution ( gDE) algorithm is proposed to obtain the minimum and maximumvalues of each objective on the Pareto Front ( PF). After normalization,MOEA/D can then be effectively ap-plied. In addition ,the self-adaptive s constraint method is combined with MOEA/D for constraint handling. Abenchmark problem and a weld bean design problem are used to evaluate the performance of the algorithm a-gainst two other normalization methods. One main advantage of the proposed method is the selective concen-trated optimization on some regions on the Pareto front which allows handling of problems where regions of Pa-reto front are difficult to be optimized.
WANG Qinghai1,ZHAO Fengxia2,Ll Jifeng2,JIN Shaobo2
Abstract: In order to solve the problems,such as low efficiency,poor real-time performance and so on,in on-line detection of glass fiber fabric,a new method of fabric defect detection based on Blob analysis is proposed. Firstly,the image is smoothed by using mean filter,and the noises and the fabric textures are weakened. Then,the Otsu algorithm is used to find the best threshold to segment the image into Blob and background pixels. The shape of the Blob region is adjusted by using morphological processing. Finally,the connectivity analysis and feature extraction of the image are carried out. The number and size of the defects are obtained by using the least square fitting of the Blob region. Experimental results show that the method is simple,reliable and robust.
Shen Chao1,Yu Peng1,Yang Jianzhong1,Zhang Dongwei2,Wei Xinli2
Abstract: Based on the cooling characteristics of the electric vehicle drive motor, a novel cooling structure the circumferential multi spiral structure, was proposed. The three dimensional numerical model of fluid flow and heat transfer in the shell was established. The flow field and temperature field of different water cooling schemes were calculated based on CFD technology. The numerical results showed that the temperature uniformity and cooling performance of Circumferential "Z" structure is better than the circumferential multi spiral structure; and the circumferential "Z" structure was suitable for the cooling of 135KW electric vehicle drive motor under the condition of inlet water temperature was 65ºC, with the optimal water flow rate 9.8L/min. However, the circumferential multi spiral structure could be used for higher power density of the motor cooling for the better performance of pressure resistance. The research provided a theoretical basis for cooling design and optimization of the small size and high power density motor.   
Cheng Shi 1,Wang Rui 2,Wu Guohua 3,Guo Yinan 4,Malembo 5,Shi Yuhui 6
Abstract: The core idea of swarmintelligence (swarmintelligence) is that several simple individuals form a group, through cooperation, competition, interaction and learning mechanisms to show advanced and complex functions, in the absence of local information and models, still able to complete the solution of complex problems.The solution process is to initialize the variable randomly, and calculate the output value of the objective function after iterative solution.Swarm intelligent optimization algorithm is not dependent on gradient information, and it is not continuous and derivable to solve problems, which makes it suitable for both continuous numerical optimization and discrete combinational optimization.At the same time, the potential parallelism and distributed characteristics of swarm intelligence optimization algorithm make it have significant advantages in dealing with big data.
Cong Pei-LIANG 1,2, LIU Jian-fei 1,2, ZHAO Zhi-qiang 1,2, Chen Muan-Fa 1,2
Abstract: Aiming at the application of epoxy asphalt in concrete bridge pavement, epoxy asphalt was prepared. The effects of different resin content on viscosity, high and low temperature properties of epoxy asphalt bond, mechanical properties, low temperature crack resistance and high temperature stability of epoxy asphalt mixture were studied.The results show that the addition of epoxy resin can improve the road performance and mechanical properties of asphalt mixture. With the increase of the addition amount, the curing reaction process of epoxy asphalt is accelerated, the high temperature performance and fatigue resistance are enhanced, the stiffness modulus is increased, the creep rate is decreased, the low temperature crack resistance is decreased, and the fatigue resistance and high temperature stability of asphalt mixture are improved.By comprehensive analysis,30% is the best dosage of epoxy resin.
Li Jingli, He Pengwei, Qiu Zaisen, Li Yuanbo, Guo Liying
Abstract: Impulse charactersitic of grounding devices was the important factor of lightning withstand level and lightning trip-out rate of transmission line.Based on HIFREQ program and FFTSES program in grounding power system analysis software CDEGS,this paper presented a grounding system impulse characteristic modeling considered soil frequency-dependence,especially,the Visacro-Alipio soil frequency-dependence formula has been introduced.The impact of the soil frequency-dependence on the effective length of the grounding device in different initial soil resistivity and different impulse current waveform was analyzed.The calculating results showed that when considering soil frequency-dependence,the impulse effective length would be shorter,especially for the grounding devices buried in high resistivity soil.
Sun Xiaoyan, Zhu Lixia, Chen Yang
Abstract: Interactive evolutionary algorithms with user preference implicitly extracted from interactions of user are more powerful in alleviating user fatigue and improving the exploration in personalized search or recommendation. However, the uncertainties existing in user interactions and preferences have not been considered in the previous research, which will greatly impact the reliability of the extracted preference model, as well as the effective exploration of the evolution with that model. Therefore, an interactive genetic algorithm with probabilistic conditional preference networks (PCP-nets)is proposed , in which, the uncertainties are further figured out according to the interactions, and a PCP-net is designed to depict user preference model with higher accuracy by involving those uncertainties. First, the interaction time is adopted to mathematically describe the relationship between the interactions and user preference, and the reliability of the interaction time is further defined to reflect the interactive uncertainty.The preference function with evaluation uncertainty is established with the reliability of interaction time. Second, the preference weights on each interacted object are assigned on the basis of preference function and reliability. With these weights, the PCP-nets are designed and updated by involving the uncertainties into the preference model to improve the approximation. Third, a more accurate fitness function is delivered to assign fitness for the individuals. Last, the proposed algorithm is applied to a personalized book search and its superiority in exploration and feasibility is experimentally demonstrated.
ZHENG Yuan-xun ,YANG Pei-bing
Abstract: In order to study the influence of asphalt pavement temperature on pavement deflection, a finite element coupling model of asphalt pavement was established considering the temperature sensitivity of road material parameters.Based on the numerical model, the variation of pavement deflection under FWD dynamic loading under different temperature conditions and the influence of temperature on the maximum deflection of asphalt pavement with different thickness are analyzed.At the same time, the influence of asphalt pavement structure and material parameters on the dynamic bending temperature correction coefficient is analyzed. Finally, the dynamic bending temperature correction coefficient of asphalt pavement is studied based on the coupling model and compared with the test results.The results show that the pavement thickness and base modulus have great influence on the temperature correction coefficient. The temperature correction coefficient of asphalt pavement deflection established based on the finite element model is in good agreement with the temperature correction coefficient established through the experimental research, and can be used as an effective supplement to the experimental research.
Liang Jing1,Liu Rui1,Qu Boyang2,Yue Caitong1
Abstract: Based on the characterisities of large-scale problems, lager-scale optimization were grossly analyzed. This paper  introduced some methods for lager-scale problems.The methods included the initialization method, decomposition strategy, updating strategy and so on. This paper mainly focued on the search strategy, update strategy, mutation strategy and cooperative coevolution. Meanwhile, the characteristics of lager-scale optimization algorithm testing function set and evaluation method were listed. Finally, the future research directions were given.
JIANG Jian-dong1 ,ZHANG Hao-jie1 ,WANG Jing2
Abstract: To further improve the accuracy of power load forecasting,on the basis of the analysis of affectingfactors of power load, a combination prediction model based on HHT is proposed. This model uses EMD algo-rithm to decompose the original load sequence. Thus, a stationary sequence of different frequencies,which ismore predictable than the original load sequence,can be obtained. Based on the components of different fre-quencies,according to the characteristics of the different frequency of subsequence ,the RBF neural network ,BP neural network and time series model are selected to forecast while considering the influence of temperatureon the load. Then,a new combined model can be achieved. The experiment shows that the proposed modelcan effectively improve the accuracy of load forecasting.
FANGShuqi1,2,HELiping1,ZHANGLonglong1,CHANGChun1,2,BAI Jing1,2,CHENJunying1,
Abstract: The effects of processing variables,such as screw speed,initial moisture content and the length ofthe straw plug pipe of extrusion process on the dewatering rate,handling capacity ,output per kW h etc.were experimentally studied using a low CR screw straw extruder. And the response surface optimization exper-imental results showed the extruder can run efficiently , stably and continuously with considerate dewateringrate , handling capacity and output per kW ·h under the conditions that moisture content is 85% ,screw speed50.8 r/min,length of the straw plug pipe is 26.91 mm.
Liu Guangrui; Zhou Wenbo; Tian Xin; Guo Kefu
Abstract: BP neural network for effectively fusioning the information obtained by arc sensor and ultrasonic sensor and information of welding parameters such as welding current,welding speed,welding groove and so on was used to obtain the prediction model of weld penetration depth.Simulation results showed that:the prediction model of weld penetration depth could measure the weld penetration quickly,accurately and in real time.For the precise control of weld penetration,parameters self-tuning fuzzy PID controller was desing,which combined with the advantages of traditional PID controller and fuzzy controller.Smulation results showed that compared with traditional PID controller,parameters self-tuning fuzzy PID controller had a significant advantage in the performance of the system.
Zhang Heng, Wang Heshan
Abstract: To improve the adaptability of echo state network (ESN),an optimization method based on mutual information (MI) and Just-In-Time (JIT) learning was proposed in this paper to optimize the input scaling and the output layer of ESN.The method was named as MI-JIT optimization method and the obtained new network was MI-JIT-ESN.The optimization method mainly consists of two parts.Firstly,the scaling parameters of multiple inputs were adjusted on the basis of MI between the network inputs and outputs.Secondly,based on JIT learning,a partial model of output layer was established.The new partial model could make the regression results more accurate.Further,a multi-input multi-output MI-JIT-ESN model was developed for the fed-batch penicillin fermentation process.The experimental results showed that the obtained MI-JIT-ESN model performed well,and that it had better adaptability than ESN model without optimization and other neural network models.
Liu Yanping Wei Hanghang, Li Qian
Abstract: The surface morphology and the different mechanical properties between crystalline region and amorphous region of the stereocomplex crystal were studied in this paper. The same mass ratio of Poly (L-lactic acid) (PLLA) and poly (D-lactic acid) (PDLA) stereocomplex was prepared by solution blending. Differential Scanning Calorimetry, Polarizing Microscope, Atomic Force Microscopy, Confocal Laser Scanning Microscope and Nano Indentation Tester were used to list the surface morpholigy of PLA stereocomplex crystal and the diversification of mechanical properties. The result showed  that a high degree of stereo-tacticity of PLLA/PDLA blend could be achieved from the mass ratio of 1/1 for sample.The research also showed that obviously depression phenomenon on the surface of crystal was formed due to the contraction of the molecular chain. Furthermore, the hardness and modulus of crystalline region were improved compared to the amorphous region.
WANG Peng1 , FAN Lei1,2,CUI Can1
Abstract: In order to research the effects of coefficient of thermal expansion ( CTE) on the PCC pavement de-sign,some efforts have been done. According to the PCC pavement design standard in our country ,the influ-ence of CTE on the temperature stress is analyzed , and the M-E design method is used to analyses the influ-ence of CTE on transverse joint faulting. The conclusion is drawn that CTE has a great impact on the designingof pavement thickness especially on the joint load transfer and the warping of slab corner. So introducing theparameter of CTE to the PCC pavement design is of great significance.
Wang Dongshu, Tan Dapei, Wei Xiaoqin
Abstract: Based on the characteristic of face orientation,position and the light background in face recognition,a new method of face orientation recognition based on development network is proposed.The characteristic of human’s eye was very prominent,so the position of eyes was chosen as the face orientation feature vector.And the deveiopment network model was used to recognize human’s face orientation in the different light background images.The result showed that this method could effectively solve the difficult problem of face orientation recognition under varying illumination conditions by comparing with the test results of other methods,which was fast,stable and effective.The recognition rate was as high as 100%.
Shi Chunyan1,Fan Bingbing1,Li Yaya1,Hu Yongbao1,Zhang Rui2
Abstract: In this work,graphene oxide (GO) was prepared by an improved Hummers method.Zirconia/graphene composites (ZrO2/rGO) were rapidly synthesized by hydrothermal method with Zr(OH)4/rGO as precursor prepared by ultrasound-stirred-coprecipitation.The adsorption capacity of Zr (OH) 4/rGO and ZrO2/rGO composites decreased with the increase of pH value and increased with the increase of phosphate concentration and the solution temperature.The maximum adsorption capacities of Zr (OH)4/rGO and ZrO2/rGO composites were 81.84 mg/g and 63.58 mg/g respectively at pH 2.0.The adsorption kinetics of these two adsorbents accorded with the pseudo-second-order model and isothermal adsorption complied with the Langmuir isotherm equation.The results of its recycling properties showed the adsorption capacity decreased for the Zr (OH) 4/rGO samples,while ZrO2/rGO samples were almost the same as the initial adsorption performance.
Zhang Yang; Si Guangya; Wang Yanzheng
Abstract: In this paper, the system function analysis was carried out based on the capability demand of the joint operation for Cyberspace War Situation Visualization System(CWSVS). Then, a distributed system architecture based on HLA was constructed based on the capability perspective, service perspective and operational perspective, and the scenario generating architecture and real-time running architecture were designed. The component-based rapid and customizable situation driven technology and the map-based multi-layered dynamic fusion visualization technology were taken as the key technology examples. At last, the cyberspace Offensive and defensive operations against the C4ISR system was given as an typical example, and the utility of the system was demonstrated
Mao Xiaobo, Zhang Qun,Liang Jing, Liu Yanhong
Abstract: In this paper,a new algorithm of license plate recognition in the hazy weather was designed.Firstly,defogging operation was introduced for license plate image in the environment of hazy by using improved dark channel prior.Then after the pretreatment,positioning,segmentation and extraction,coarse grid characteristic matrix is obtained.Finally,radial basis function (RBF) neural network,which was optimized by particle swarm algorithm in advance,was used to identify the character.The experiment results showed that the improved algorithm not only had a good effect on haze removal,but also reduced the duration of defogging,which effectively improve the license plate recognition speed and accuracy in fog and haze weather.
JIAO Liu-cheng,YAO Tao
Abstract: In view of the speed control problem of the linear permanent magnet synchronous motor ( L.PMSM) ,which is viewed as an energy-transformation device,from the viewpoint of energy shaping,applying port-con-trolled Hamultonian with dissipation and passivty-based control theory , the port-controlled Hamltonan modelof LPMSM is deduced. Based on the Hamiltonian structure,the desired Hamiltonian function of the closed-loop system is given, and the speed controller is designed by using the method of interconnection and dampingassignment. In the design,the Hamiltonian function is used directly as the storage function,and the systemcan achieve the required performance and bring more definite physical meaning on the condition of satisfyingpassivity. The simulation results show that the closed-loop control system can respond quickly to changes inload resistance and has good robustness.
Maling1,Jiang Huiqin1,Liu Yumin2
Abstract: In order to meet the practical requirements of automatic application and renewal of driver’s license,a high speed system for automatic recognition of driver’s licenser was designed and implemented.The hardware was designed to capture the image of the driver’s license that contained the smallest identifiable features.Because of the complex background such as the shadow line and so on in the driver’s license images,the existing recognition algorithms had the low recognition accuracy,universality and robustness problems.This paper first solved the segmentation difficulties for uneven illumination,noise,tilt and shadow line character by combined adaptive binarization and morphological processing.Then,the Blob analysis was used to extract the important local features of the driver’s license,and the recognition accuracy was further improved by using the prior information and the correlation matching algorithm.The experimental results showed that not only the false recognition rate was 0,but also the practical products was developed,and the better social effects were achieved.
Cao Ben, Yuan Zhong, Yu Liu Hong
Abstract: During heating process of sintering furnace,the model parameters were easy to change,and traditional PID control was difficult to achieve the desired control effect.This paper used particle swarm optimization algorithm to identify the mathematical model of sintering furnace,for sintering furnace with high inertia,time-variation and strong time delay etc,a method of supervision and control based on RBF neural network,which combined PID control with neural network control.When temperature or parameters changed greatly,PID control played a major role.neural network played a regulatory role and compensated the shortage of PID control.The simulation results of MATLAB software showed that this method could improve the control precision of sintering furnace,which had a certain practicality.
Zhou Junjie, Wang Pu, Zhou Jinfang
Abstract: The analysis was held with the 125MW axial flow steam turbine impulse stage blade.The three-dimensional numerical simulation and optimization were conducted by using the commercial software ANSYS CFX.The results showed that the pressure distribution of blade surface reduced,and the radial secondary flow loses was controlled effectively,with optimizing the structure geometric parameters such as ellipticity of the leading edge and trailing edge,relative pitch,inter-stage ratio,and so on.Isentropic efficiency increased by 0.43%,the total pressure loss coefficiency decreased about 0.005.After the optimization,the aerodynamic performance of the blade increased,and the energy loss in the blade decreased and the efficiency of steam turbine increased.
Dai Pinqiang1,Song Lairui2,Cui Zhixiang3,Wang Qianting3
Abstract: Chitosan ( CS)/poly ( vinyl alcohol) ( PVA) composite fibers were fabricated by electrospinning in this study. The influences of material formulation and formed time on the viscosity,electrical conductivity and the morphology, average diameter, diameter distribution of CS/PVA composite fiber were investigated. The re-sults showed that, the introduction of CS could increase the viscosity,electrical conductivity of CS/PVA blend solution. And the viscosity of blend solution decreased with the increase of formed time. In addition, the more CS content was, the smaller diameter of CS/PVA composite fiber would be. The fiber-forming capacity of CS/PVA blend solution decreased dramatically as the solution formed time increased.
Wang Wen1,Hu Haoliang1,He Shitang1,Pan Yong2,Zhang Caihong3
Abstract: In view of the current situation that the traditional methane sensor technology is difficult to imple-ment the field detection and monitor on methane gas, a novel room-temperature SAW methane gas sensor coa-ted with cryptophane-A sensing interface is proposed by utilizing the supermolecular compound cryptophane-A’ s specific clathration to methane molecules. The sensor was composed of differential resonator-oscillators with excellent frequency stability, a supra-molecular CrypA coated along the acoustic propagation path, and a frequency acquisition module. The supramolecular CrypA was synthesized from vanillyl alcohol using a three-step method and deposited onto the surface of the sensing resonators via dropping method. Fast response and excellent repeatability were observed in gas sensing experiment, and the estimated detection limit and meas-ured sensitivity in gas dynamic range of 0 . 2% ~5% was evaluated as ~0 . 05 % and ~184 Hz/%, respec-tively. The measured results indicated the SAW sensor was promising for under-mine methane gas detection and monitor.
WANG Wei-shu1, SHAGN GUAN Shan-shan1,LU Tong1 ,YANG Zhi-feng2 ,ZHENG Chun-xiong1,CHEN Gang1
Abstract: Based on FLUENT6.3 software,the simulation and analysis were applied to the optimization designof splitters in Selective Catalytic Reduction ( SCR ) denitrification system for a 600MW coal-fired boiler. Theresults show that because of variable cross-section and deflection in flue,flow field in the system appears non-uniform severely when there is no splitters. The velocity difference on two sides of the section at AlG lowerreaches is up to 15 m/s,the velocity deviations in the reactor inlet is 31.25% , and the flow field is poor intail flue,which affects the operation of downstream equipments.Reasonable splitters can improve flow field influe effectively. After equipping the transition pipe of the inlet with two group of longitudinal splitters, the ve-locity deviations in section at AIG lower reaches is reduced to 15% and in the reactor inlet is reduced to 13% .Splitters in elbow is equipped with an extension for guiding,which have a good effect on homogenization of thedownstream flow field.
LIU Min-shan,XU Wei-feng ,JIN Zun-long,WANG Yong-qing,WANG Dan
Abstract: A numerical simulation of trisection-ellipse heat exchangers with helical baffles is carried out, andthe helix angles are 15° and 20° respectively , and we studied the impact of triangle leakage between continu-ously overlapped and adjacent baffles on heat transfer and resistance performance of heat exchangers.Throughthe comparative analysis about the simulation results of existing triangle leakage and that of blocking trianglearea without leakage , the results show :triangle leakage makes a more serious short circuit flow for the shell-si-ded fluid;Triangle leakage makes heat transfer coefficient,shell-sided pressure drop and comprehensive per-formance of heat exchanger reduce. When triangle leakage is blocked,heat transfer coefficient increases by8.5% ~ 11% , shell-sided pressure drop increases marginally , comprehensive performance increases by 8.1 %~11 . 1 % .
Bi Ying,Xue Bing,Zhang Mengjie
Abstract: As an evolutionary computation (EC) technique, Genetic programming (GP) has been widely applied to image analysis in recent decades. However, there was no comprehensive and systematic literature review in this area. To provide guidelines for the state-of-the-art research, this paper presented a survey of the literature in recent years on GP for image analysis, including feature extraction, image classification, edge detection, and image segmentation. In addition, this paper summarised the current issues and challenges, such as computationally expensive, generalisation ability and transfer learning, on GP forimage analysis, and pointd out promising research directions for future work.
Sheng Zunrong1,Xue Bing1,Liu Zhouming1,Wei Xinli2
Abstract: A direct-contact method of zeolite adsorption liquid water was adopted to enhance heat and mass transfer rate within adsorption heat transformer.Hot water was recycled to generate superheated steam directly,and then saturated zeolite would be regenerated by drying gas.The reactor with was filled spherical zeolite with same mass and different diameters.The mass of steam generated by small particle packed bed was 64.89% higher than that generated by big particle packed bed.The maximum steam temperature and gross temperature life had increased by about 37C.Experiments of two kinds of packed types in double layer reactor (finecoarse bed and coarse-fine bed) have shown that small particle played a more effective role for the heating of steam and packed bed;the mean maximum temperature of the steam at the top of fine-coarse bed is 37.23% higher than that of coarse-fine bed and the lasting time of the maximum temperature is decreased by 14.25%.The steam generation rate of fine-coarse bed was 16.18% higher than that of coarse-fine bed,which is more efficient in steam generation.In regeneration process,drying time of upper reactor was 25.03% shorter than coarse-fine bed.It concluded that fine-coarse bed was more effective for zeolite regeneration.
ZHAO Guosheng1,NIU Zhenzhen1,LIU Yongguang2, SUN Chaoliang2
Abstract: In view of the disadvantages of the traditional Fuy C-means clustering algorithm, the author pro-poses an adaptive FCM algorithm. This algorithm is based on two clustering results evaluation index of withinthe class distance MIA and between the class distance MDC. The ratio of MDC and MIA,defined as l, is anadaptive function to determine the clustering number c of FCM algorithm. At the same time,according to thefuzy decision method,we use the objective function and partition entropy of FCM algorithm together to deter-mine the value of optimal fuzzy weighted m. ’This algorithm not only overcomes the FCM algorithm disadvan-tage of not being able to determine the clustering number automatically and fuzzy weighted index needs to begiven by experience,but also the clustering result is optimal. Finally,the correctness and effectiveness of thealgorithm were proved through example analysis.
Li Haibin1,Ke Shengwang2,Shen Yanjun2
Abstract: With the increasing of highway extension projects and widely use of sheet piles in railway construction,the mechanical behavior of extension embankment was analyzed through simulating different kinds of pile and load of different positions.Then the optimal pile kind and the most unfavorable load position were proposed.Through continuous observing of settlement in sheet pile section and CFG pile section,the optimal adaptability of sheet pile was showed in extension projects.The analysis results showed that the effect on settlement of PTC pile,CFG pile and cement mixing pile was gradually decreased.The PTC pile and CFG pile should be firstly selected from the options of controlling settlement.The most unfavorable load position was in new embankment and its quality was the key control point in construction.The effect on decreasing differential settlement was appeared in process of semi-rigid base construction,and it would be even obvious in pavement construction.The sheet pile was an effective supplement to traditional soft soil treatment methods.It had better adaptability and foreground in highway extension projects.
Mao Xiaobo, Hao Xiangdong, Liang Jing
Abstract: In view of the problem of object deviation when occlusions occur during the target tracking, a new algorithm using Mean Shift with ELM is proposed. According to the formal information of the object’ s loca-tion, current possible location was predicted by ELM, the iteration was started from the possible location in-stead of formal location, and the object’ s real center is calculated by mean shift algorithm. The simulation re-sults show that proposed algorithm can track precisely target occluded, operation time and number of iteration are reduced so that efficiency and robustness are improved.
Hu Xiaobing, Xie Zhenfang, Xie Ji, Xie Lili, Zhu Zhigang
Abstract: Micro/Nano-particles of CuO were prepared with hexamethylenetetramine template. The composi-tion and morphology of the product were characterized by SEM and X-ray diffraction. The synthetic powder was prepared as sensitive membrane, and its gas sensitivity was studied with a static gas distribution method. The results indicated that the uniform copper oxide powders was synthesized at the 110℃, and the molar ratio be-tween copper nitrate and hexamethylenetetramine was 1∶45. The spindle structure was around 1~2 μm, and was composed of 100 nm nanoplates. The sensor had better selectivity with CH3 COCH3 and H2 S. Copper ox-ide showed good selectivity to hydrogen sulfide and its sensitivity had a certain degree of improvement after fur-ther doping 0. 25% ~1. 25% noble metal catalyst Pt.
Zhang Zhonghui, Liu Gushuai, Xiong Jianfeng, Liu Xiaowan, Xu Gaochao
Abstract: The distribution of charging and battery swap station has always been one of the key problems for the development of electric vehicle.A site location of charging and battery swap station could be represented by a network with traffic flow,the distance from the power source,parcel load,and city block position respectively.Spectral clustering methodology was used to reveal the internal connectivity structure of such a network.First of all,it adopted the min-max standardized method in dimensionless to establish a sample space matrix S.Then,the normalized Laplacian was achived according to the similarity between matrix W and matrix D.The former two and three feature vector of Laplace matrix were mapped to the 2d and 3d space to observe parcel partition.Finally methodology goes beyond the standard k-means algorithm by instead representing the complete network substructure as a dendrogram and verifies its correctness by analyzing the voltage sags.We include the results of our methodology for a real distribution network in Jiangxi province.Example shows that our methodology has certain rationality and it could be helpful for distribution network planning.
Jiang Yuewen, Qian Jiaqi
Abstract: In response to the current construction status of specialized transmission projects, optimization methods are adopted to select the main electrical equipment of the transmission project, such as high-voltage circuit breakers, transmission lines, transformers, etc. An optimization model is established that considers one-time investment, annual operation and maintenance costs, and power outage losses. The optimization model is used to select the most cost-effective investment plan from a large number of electrical equipment that meet the technical parameter requirements. This plan takes into account both economy and reliability, To minimize the annual comprehensive operating cost, an ant colony algorithm was used to solve the problem. In response to the slow optimization speed of the algorithm, an improved neighborhood ant "benchmark" learning algorithm was used for optimization. Finally, the effectiveness of the model and algorithm was demonstrated through calculation and analysis of a residential dedicated transmission project example
MU Xiaomin , SHI Guangqiang,LIU Ying , YANG Shouyi
Abstract: To solve the problem of contract-based cooperative spectrum sharing between multiple primary usersand multiple secondary users,we put forward a contract design method based on statistical theory to maximizethe total utility of primary users. Firstly,the primary users make full use of the accepting contract statisticalinformation of secondary users to design a reasonable contract. Then,the primary users according to the statis-tical expected utility to obtain the optimization problem of maximizing theirs total expected utilities. Further-more,we simplify the problem in theory and exploit the genetic algorithm to derive the sub-optimal solution.The simulation results and analysis show the contract design method can solve the problem of contract-basedcooperative spectrum sharing successfully.Compared with the DMA-UI,the approach we formulated can makeprimary users obtain a higher utility, and further improve the primary users’energy efficiency and spectrumefficiency.
Ding Chang, Fu Yantang, Wu Xuehong, Gong Yi
Abstract: FLUENT software was adopted to simulate the sloshing process of liquid in container under the sudden braking condition based on VOF (volume of fluid) model.The pressure variation of front and back head was compared,which showed that the sloshing liquid mainly had a greater impact on the front head.Baffles could effectively weaken the sloshing in the container,reduce the impact on the head and improve the container safety.The liquid impact on front head was studied in the condition of different filling ratio for different baffle arrangement(all down,all up,up and downinterlaced,left and right interlaced) of five same arc baffles.Results show that the arrangement style of left and fight interlaced 、all down could reduce impact load on front head for low filling ratio,however the arrangement style of up and downinterlaced all up had poor anti-wave effect.The anti-wave effect of the arrangement style of left and right interlaced became poorer and poorer with the increment of filling ratio.Compared with other arrangement style,the arrangement style of all down had better anti-wave effect.
CHEN Xiaopan1 ,QU Jiantao1,2,ZHAO Yameng2, WANG Peng1, 2 , CHEN Yulin1
Abstract: When dealing with massive terrain data ,the advantage of hardware performance can’t be fully uti-lized. This has become a bottleneck,which restricts the speed of massive terrain tiles rendering. This paperanalyzes the key factors that affect large-scale terrain rendering speed,and proposes a parallel algorithm formassive terrain data processing. The algorithm adopts double buffer queues and divides large scale terrain ren-dering into two parallel processing which includes data processing and rendering. The two buffer queues areresponsible for data reading and writing operations in turn. The loading priority of terrain tiles is consideredand tasks are allocated based on the priority. The experimental results show that this approach improves thespeed of rendering massive terrain tiles greatly.
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Bimonthly(Started in 1980)
Administrated by:
The Education Department of Henan Province
Sponsored by: Zhengzhou University
Edited & Published by:
Editorial Board of Journal of Zhengzhou University( Engineering Sciences)
E-mail: gxb@zzu.edu.cn
Website: http://.zzu.edu.cn
Address: No.100 Science Avenue,100,
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Telephone: (0371)67781276 67781277
Chief Editor: LI Yanyan
Executive Chief Editor: XIANG Sa
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Distributed by: Office of Postal Distribution of Henan Proince
Distributed Abroad by: Publishing Trading Corporation,P.O.B.782, Beijing100011, China
Publication Scope: Public Publication
Periodicity:Bimonthly
Founded in:1980
Code of Domestic Distribution: 36-232
Code of Overseas Distribution: BM2642
ISSN:1671-6833
CN:41-1339/T
CODEN:ZDXGAN
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