Saliency motivated pulse coupled neural network for underwater laser image segmentation

The detection range of underwater laser imaging technology achieves 4—6 times of detection range of conventional camera in intervening water medium, which makes it very promising in oceanic research, deep sea exploration and robotic works. However, the special features in underwater laser images, such as speckle noise and non-uniform illumination, bring great difficulty for image segmentation. In this paper, a novel saliency motivated pulse coupled neural network(SM-PCNN) is proposed for underwater laser image segmentation. The pixel saliency is used as external stimulus of neurons. For improvement of convergence speed to optimal segmentation, a gradient descent method based on maximum two-dimensional Renyi entropy criterion is utilized to determine the dynamic threshold. On the basis of region contrast in each iteration step, the real object regions are effectively distinguished,and the robustness against speckle noise and non-uniform illumination is improved by region selection. The proposed method is compared with four other state-of-the-art methods which are watershed, fuzzy C-means, meanshift and normalized cut methods. Experimental results demonstrate the superiority of our proposed method to allow more accurate segmentation and higher robustness.     

The coordination mechanism of supply chain finance based on tripartite game theory

Supply chain finance (SCF) is concerned because of its service efficiency for the real economy. Beside the bank, some enterprises have provided the SCF service. E-commerce platform firms develop small and micro loan system in China. A given small enterprise can apply for a loan through its platform. Based on the latest SCF developments and the relevant literature, this study focuses on the coordination mechanism of SCF. We construct a game theory model including supplier, retailer and financial service provider to analyze the decision making of them. We find the optimal solution to the supplier, retailer and financial service provider.     

Causality of future and spot grain prices between China and the US: Evidence from soybean and corn markets against the surging import pressure

As the boom of the world grain market phases out, the challenge for Chinese government has gradually moved from retarding grain exports to restraining imports. This study tries to examine the causalities of soybean and corn price movement among the United States (US) future market, Chinese domestic future market and Chinese spot markets. We find that the daily prices of all these three types of grains belong to I(1) series, and there are long-run integrations. Also Chinese soybean future prices adjust more quickly than its spot prices, while Chinese corn future prices adjust slower. This paper finds that the soybean price movement originates from the US future market, then passes through Chinese future market, and finally reaches Chinese spot market, while the corn price movement starts in Chinese spot market, then spreads to the future markets in both China and the US. Finally, this paper also provides some policy implications on how to release the pressure from the grain imports.     

Investigation of the capabilities of yield functions on describing the deformation behavior of 5754O aluminum alloy sheet under combined loading paths

The combined loading tests of 5754O aluminum alloy sheet are used to verify the yield function. Three yield functions are implemented into the commercial finite element model (FEM) code ABAQUS as a user material subroutine UMAT for the FEM simulation of the combined loading tests. The comparison of the simulating and experimental results shows that the modified Yld2000-2d yield function can describe the mechanical behavior of 5754O aluminum alloy sheet under combined loading paths reasonably while other three yield functions do not. The performance of the modified Yld2000-2d yield function on describing the mechanical behavior under combined loading paths is analyzed in detail. It is concluded that the modified Yld2000-2d yield function can be adopted to describe the deformation behavior of 5754O aluminum alloy sheet for industrial applications.     

Imprecise reliability assessment for heavy numerical control machine tools against small sample size problem

Small sample size problem is one of the main problems that heavy numerical control (NC) machine tools encounter in their reliability assessment. In order to deal with the small sample size problem, many indirect reliability data such as reliability data of similar products, expert opinion, and engineers’ experience are used in reliability assessment. However, the existing mathematical theories cannot simultaneously process the above reliability data of multiple types, and thus imprecise probability theory is introduced. Imprecise probability theory can simultaneously process multiple reliability data by quantifying multiple uncertainties (stochastic uncertainty, fuzzy uncertainty, epistemic uncertainty, etc.) together. Although imprecise probability theory has so many advantages, the existing natural extension models are complex and the computation result is imprecise. Therefore, they need some improvement for the better application of reliability engineering. This paper proposes an improved imprecise reliability assessment method by introducing empirical probability distributions to natural extension model, and the improved natural extension model is applied to the reliability assessment of heavy NC machine tool spindle to illustrate its effectiveness.     

Study of tunnel thruster performance and flow by quasi-steady Reynolds-averaged Navier-Stokes simulation

A numerical approach based on the solution of the Reynolds-averaged Navier-Stokes(RANS) equations using the shear-stress transport(SST) turbulence model has been employed to investigate the hydrodynamic performance and flow of tunnel thrusters.The flow passages between adjacent blades are discretized with prismatic cells so that the boundary layer flow is resolved down to the viscous sub-layer.The hydrodynamic performances predicted by the quasi-steady approach agree well with the experimental data for three impellers covering a range of blade area and pitch.Through analysis of the flow field,the reason why the hub of impeller also contributes to thrust which can amount to 40%—60% of the impeller thrust,and the mechanism of the impeller inducing an axial force on the hull are elucidated.     

Serum levels of RBP4 might not be determined by diabetes mellitus but by kidney function and renal replacement therapy

It has been reported that retinol-binding protein 4(RBP4) is associated to adiposity,insulin resistance,and type 2 diabetes.Meanwhile,circulating RBP4 levels are also affected by renal function.The aim of the present study is to investigate whether serum levels of RBP4 are primarily associated with different stages of chronic kidney disease(CKD) or type 2 diabetes,if there is more potential relevance between RBP4 and renal replacement therapy.The serum levels of RBP4 were assessed by commercial competitive enzyme-linked immunosorbent assay(ELISA)kit in 212 patients with the CKD stages 1—5 and in 24 healthy controls,while its correlation with clinical and metabolic parameters was analyzed.The serum level of RBP4 had a strong correlation with estimated glomerular filtration rate(e GFR)(P 0.001).Stratified by e GFR and treatment,no more differences in RBP4 serum concentration were detected between type 2 diabetic and non-diabetic subjects [CKD stages 1—5,non-dialysis(ND),hemodialysis(HD) and peritoneal dialysis(PD);P 0.05 for all].The elevation of RBP4 become higher in HD than in PD and ND in CKD5 patients(P = 0.008 and P = 0.04,respectively),while there was no significant difference between PD and ND groups.Multivariate linear regression analysis demonstrated three independent predictors of e GFR(β =-0.676,P 0.001),C-reactive protein(CRP)(β =-0.573,P 0.001) and creatine(β = 0.509,P = 0.024) in the study population.The study results demonstrated that the serum level of RBP4 was negatively related to the e GFR,whether diabetes mellitus(DM) affected the blood concentration of RBP4 or not.And the serum level of RBP4 exhibited significant difference in different renal replacement therapies.     

A new hybrid reliability index definition and its application to the structure buckling reliability analysis of supercavitating projectiles

As structure buckling problems easily arise when supercavitating projectiles operate with high underwater velocity, it is necessary to perform structure buckling reliability analysis. Now it is widely known that probabilistic and non-probabilistic uncertain information exists in engineering analysis. Based on reliability comprehensive index of multi-ellipsoid convex set, probabilistic uncertain information is added and transferred into non-probabilistic interval variable. The hybrid reliability is calculated by a combined method of modified limit step length iteration algorithm(MLSLIA) and Monte-Carlo method. The results of engineering examples show that the convergence of MLSLIA is better than that of limit step length iteration algorithm(LSLIA). Structure buckling hybrid reliability increases with the increase of ratio of base diameter to cavitator diameter, and decreases with the increase of initial launch velocity. Also the changes of uncertain degree of projectile velocity and cavitator drag coefficient affect structure buckling hybrid reliability index obviously. Therefore, uncertain degree of projectile velocity and cavitator drag coefficient should be controlled in project for high structure buckling reliability.     

Research of order allocation model based on cloud and hybrid genetic algorithm under ecommerce environment

For massive order allocation problem of the third party logistics (TPL) in ecommerce, this paper proposes a general order allocation model based on cloud architecture and hybrid genetic algorithm (GA), implementing cloud deployable MapReduce (MR) code to parallelize allocation process, using heuristic rule to fix illegal chromosome during encoding process and adopting mixed integer programming (MIP) as fitness function to guarantee rationality of chromosome fitness. The simulation experiment shows that in mass processing of orders, the model performance in a multi-server cluster environment is remarkable superior to that in stand-alone environment. This model can be directly applied to cloud based logistics information platform (LIP) in near future, implementing fast auto-allocation for massive concurrent orders, with great application value.     

Simultaneous localization and mapping of autonomous underwater vehicle using looking forward sonar

A method of underwater simultaneous localization and mapping (SLAM) based on on-board looking forward sonar is proposed. The real-time data flow is obtained to form the underwater acoustic images and these images are pre-processed and positions of objects are extracted for SLAM. Extended Kalman filter (EKF) is selected as the kernel approach to enable the underwater vehicle to construct a feature map, and the EKF can locate the underwater vehicle through the map. In order to improve the association efficiency, a novel association method based on ant colony algorithm is introduced. Results obtained on simulation data and real acoustic vision data in tank are displayed and discussed. The proposed method maintains better association efficiency and reduces navigation error, and is effective and feasible.