A fast algorithm for feature extraction of hyperspectral images using the first order statistics

Multimedia Tools and Applications - A new supervised feature extraction method appropriate for small sample size situations is proposed in this work. The proposed method is based on the first-order...     

Well-conditioned configurations of fault-tolerant manipulators

Fault-tolerant motion of redundant manipulators can be obtained by joint velocity reconfiguration. For fault-tolerant manipulators, it is beneficial to determine the configurations that can tolerate the locked-joint failures with a minimum relative joint velocity jump, because the manipulator can rapidly reconfigure itself to tolerate the fault. This paper uses the properties of the condition numbers to introduce those optimal configurations for serial manipulators. The relationship between the manipulator’s locked-joint failures and the condition number of the Jacobian matrix is indicated by using a matrix perturbation methodology. Then, it is observed that the condition number provides an upper bound of the required relative joint velocity change for recovering the faults which leads to define the optimal fault-tolerant configuration from the minimization of the condition number. The optimization problem to obtain the minimum condition number is converted to three standard Eigen value optimization problems. A solution is for selected optimization problem is presented. Finally, in order to obtain the optimal fault-tolerant configuration, the proposed method is applied to a 4-DoF planar manipulator.     

Experimental characterization of the small strain shear modulus of soft clay stabilized with cement and nano-SiO2 using bender element tests

Bulletin of Engineering Geology and the Environment - The accurate and efficient modification of the static and dynamic properties of problematic soils is a primary concern in geotechnical...     

Improved physical stability of docosahexaenoic acid and eicosapentaenoic acid encapsulated using nanoliposome containing α‐tocopherol

This study aimed to develop a nanoliposomal formulation containing α‐tocopherol loaded with eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) and to characterise the formulation by its physical stability. For this purpose, different nanoliposomal formulations with dipalmitoyl phosphocholine were prepared using a modified thin‐film hydration method and evaluated by particle size, polydispersity index (PDI), transmission electron microscopy, differential scanning calorimetry and determining the encapsulation efficiencies of DHA and EPA. A physical stability study was conducted by investigating the change in the vesicle encapsulation efficiency, particle size, PDI and shape when stored at 4, 30 and 40 °C for 3 months. High encapsulation efficiency of DHA and EPA (89.1% ± 0.6% and 81.9% ± 1.4%) and appropriate particle size (82 ± 0.8 nm) were obtained for liposomes composed of α‐tocopherol. The optimum formulation was stable for 90 days when kept at 4 °C. This study demonstrated that α‐tocopherol had a protective effect on the physical stability of the nanoliposomes containing DHA and EPA.     

An improved cluster formation process in wireless sensor network to decrease energy consumption

Wireless sensor network has special features and many applications, which have attracted attention of many scientists. High energy consumption of these networks, as a drawback, can be reduced by a hierarchical routing algorithm. The proposed algorithm is based on the Low Energy Adaptive Clustering Hierarchy (LEACH) and Quadrant Cluster based LEACH (Q-LEACH) protocols. To reduce energy consumption and provide a more appropriate coverage, the network was divided into several regions and clusters were formed within each region. In selecting the cluster head (CH) in each round, the amount of residual energy and the distance from the center of each node were calculated by the base station (including the location and residual energy of each node) for all living nodes in each region. In this regard, the node with the largest value had the highest priority to be selected as the CH in each network region. The base station calculates the CH due to the lack of energy constraints and is also responsible for informing it throughout the network, which reduces the load consumption and tasks of nodes in the network. The information transfer steps in this protocol are similar to the LEACH protocol stages. To better evaluate the results, the proposed method was implemented with LEACH LEACH-SWDN, and Q-LEACH protocols using MATLAB software. The results showed better performance of the proposed method in network lifetime, first node death time, and the last node death time.

     

Prediction of heavy oil viscosity using a radial basis function neural network

Heavy oil and extra heavy oil resources comprise about 75% of petroleum resources. The most important characteristic of heavy oils is their viscosity. Consequently, to extract and prepare these kinds of crude oil for use, great emphasis should be put on viscosity. The present study highlights the application of intelligent model named radial basis function (RBF) network optimized by genetic algorithm for estimation of diluted heavy oil viscosity in presence on kerosene. The input parameters of model were temperature and mass fraction of kerosene. The output of model was viscosity of heavy oil. Genetic algorithm was utilized to optimize the tuning parameters of RBF model. The outcomes of this study showed that the proposed model is accurate in estimation of target data.     

A new synthetic metamodel methodology for liquid‐propellant engine's cooling system optimization

The present paper strives for optimization of the cooling system of a liquid‐propellant engine (LPE). To this end, the new synthetic metamodel methodology utilizing the design of experiment method and the response surface method was developed and implemented as two effective means of designing, analyzing, and optimizing. The input variables, constraints, objective functions, and their surfaces were identified. Hence, the design and development strategy of combustion chamber and nozzle was clarified, and 64 different experiments were carried out on the RD‐161 propulsion system, of which 47 experiments were approved and compatible with the problem constraints. This engine used all three modes of cooling: the radiation cooling, the regenerative cooling, and the film cooling. The response surface curves were drawn and the related objective function equations were obtained. The analysis of variance results indicate that the developed synthetic model is capable to predict the responses adequately within the limits of input parameters. The three‐dimensional response surface curves and contour plots have been developed to find out the combined effects of input parameters on responses. In addition, the precision of the models was assessed and the output was interpreted and analyzed, which showed high accuracy. Therefore, the desirability function analysis has been applied to LPE's cooling system for multiobjective optimization to maximize the total heat transfer and minimize the cooling system pressure loss simultaneously. Finally, confirmatory tests have been conducted with the optimum parametric conditions to validate the optimization techniques. In conclusion, this methodology optimizes the LPE's cooling system, a 2% increase in the total heat transfer, and a 38% decrease in the pressure loss of the cooling system. These values are considerably large for the LPE design.