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.

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.

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

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.

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.

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. 

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

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.

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.

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.

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．

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.

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.

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 21 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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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 % .

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.

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.

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.

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 clustering mechanism 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.

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.

Abstract:

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.

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

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.

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.

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.

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.

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％.