Degree constrained minimum spanning tree problem: a learning automata approach

Degree-constrained minimum spanning tree problem is an NP-hard bicriteria combinatorial optimization problem seeking for the minimum weight spanning tree subject to an additional degree constraint on graph vertices. Due to the NP-hardness of the problem, heuristics are more promising approaches to find a near optimal solution in a reasonable time. This paper proposes a decentralized learning automata-based heuristic called LACT for approximating the DCMST problem. LACT is an iterative algorithm, and at each iteration a degree-constrained spanning tree is randomly constructed. Each vertex selects one of its incident edges and rewards it if its weight is not greater than the minimum weight seen so far and penalizes it otherwise. Therefore, the vertices learn how to locally connect them to the degree-constrained spanning tree through the minimum weight edge subject to the degree constraint. Based on the martingale theorem, the convergence of the proposed algorithm to the optimal solution is proved. Several simulation experiments are performed to examine the performance of the proposed algorithm on well-known Euclidean and non-Euclidean hard-to-solve problem instances. The obtained results are compared with those of best-known algorithms in terms of the solution quality and running time. From the results, it is observed that the proposed algorithm significantly outperforms the existing method.     

Numerical analysis of restitution coefficient,rotational speed and particle size effects on the hydrodynamics of particles in a rotating drum

Hydrodynamic behavior of two dimensional horizontal rotating drum was studied by using finite volume method and granular kinetic theory. In this work, the effects of the different parameters such as rotation speed, restitution coefficient and particle size on the hydrodynamic and especially on the granular temperature of particles were investigated. At first, the results of present work were verified with previous experimental results. Packing limit of 0.6 and restitution coefficient of 0.95 with Gidaspow inter-phase momentum coefficient showed the good agreement with experimental works. It is found that by increasing the restitution coefficient, the granular temperature at different depth of bed increased and affected the hydrodynamic behavior of the bed. Also, particle size and rotation speed directly changed the granular temperature. Moreover, augmentation of the rotation speed leads to increasing the repose angle which caused better mixing of bed, granular temperature rising and consequently particle velocity alteration in the bed.     

Developed split window method to retrieve land surface temperature from HYTES thermal hyperspectral images using genetic algorithm

This article aims to establish a new method to retrieve land surface temperature (LST) from hyperspectral thermal emission spectrometer (HYTES) data with split window (SW) algorithm. First, the optimal bands of HYTES sensor were selected with the genetic algorithm and then were used in the SW algorithm. In the SW algorithm, its coefficients were obtained based on several subranges of atmospheric column water vapours (CWVs) and view zenith angle (VZA) under various land surface conditions, in order to remove the atmospheric effect and improve the retrieval accuracy. Results showed that the root-mean-square error (RMSE) varies for different CWV and VZA, and with the increasing CWV and VZA, the RMSE value also increases. The emissivity, CWV, and VZA were also obtained for pixels. The sensitive analysis of LST retrieval to instrument noise and uncertainty of pixel emissivity and water vapour demonstrated the good performance of the proposed algorithm. Finally, the new algorithm was applied to HYTES sensor data, and the LST was validated using LST product of HYTES sensor obtained by NASA. The results showed that the RMSE of the LST retrieval with the proposed algorithm and the LST product of sensor for data 1 and data 2 is 1.3 K and 1.6 K, respectively.     

Uncertainty handling in convolutional neural networks

Neural Computing and Applications - The performance of convolutional neural networks is degraded by noisy data, especially in the test phase. To address this challenge, a new convolutional neural...     

LATOC: an enhanced load balancing algorithm based on hybrid AHP-TOPSIS and OPSO algorithms in cloud computing

Providing required level of service quality in cloud computing is one of the most significant cloud computing challenges because of software and hardware complexities, different features of tasks and computing resources and also, lack of appropriate distribution of tasks in cloud computing environments. The recent research in this field show that lack of smart prioritization and ordering of tasks in scheduling (as an NP-hard problem) has been very effective and resulted in lack of load balancing, response time increase, total execution time increase and also, average resource use decrease. In line with this, the proposed method of this research called LATOC considered first the key criteria of an input task like required processing unit, data length of task and execution time. Then, it addressed task prioritization in separate queues using the technique for order preference by similarity to ideal solution (TOPSIS) and analytic hierarchy process (AHP) in figure of a hybrid intelligent algorithm (AHP-TOPSIS). Each ordered task in separate priority queues was placed based on its priority level, and then, to assign each task from each priority queue to virtual machines, optimized particle swarm optimization was used. Many simulations based on various scenarios in Cloudsim simulator show that smart assignment of prioritized tasks by LATOC resulted in improvement of important cloud computing parameters such as total execution time and average resource use comparing similar methods.

     

Effects of sintering temperature on morphology and mechanical characteristics of 3D printed porous titanium used as dental implant

Porous titanium samples were manufactured using the 3D printing and sintering method in order to determine the effects of final sintering temperature on morphology and mechanical properties. Cylindrical samples were printed and split into groups according to a final sintering temperature (FST). Irregular geometry samples were also printed and split into groups according to their FST. The cylindrical samples were used to determine part shrinkage, in compressive tests to provide stress-strain data, in microCT scans to provide internal morphology data and for optical microscopy to determine surface morphology. All of the samples were used in microhardness testing to establish the hardness. Below 1100 °C FST, shrinkage was in the region of 20% but increased to approximately 30% by a FST of 1300 °C. Porosity varied from a maximum of approximately 65% at the surface to the region of 30% internally. Between 97 and 99% of the internal porosity is interconnected. Average pore size varied between 24 μm at the surface and 19 μm internally. Sample hardness increased to in excess of 300 HV0.05 with increasing FST while samples with an FST of below 1250 °C produced an elastic–brittle stress/strain curve and samples above this displayed elastic–plastic behaviour. Yield strength increased significantly through the range of sintering temperatures while the Young's modulus remained fairly consistent.     

Electrocatalytic oxygen reduction on single-walled carbon nanotubes supported Pt alloys nanoparticles in acidic and alkaline conditions

The objective of this study is to improve the catalytic activity of platinum by alloying with transition metal (Pd) in gas diffusion electrodes (GDEs) by oxygen reduction reaction (ORR) at cathode site and comparison of the acidic and alkaline electrolytes. The high porosity of single-walled carbon nanotubes (SWCNTs) facilitates diffusion of the reactant and facilitates interaction with the Pt surface. It is also evident that SWCNTs enhance the stability of the electrocatalyst. Functionalized SWCNTs are used as a means to facilitate the uniform deposition of Pt on the SWCNT surface. The structure of SWCNTs is nearly perfect, even after functionalization, while other types of CNTs contain a significant concentration of structural defects in their walls. So catalysts supported on SWCNTs are studied in this research. The electrocatalytic properties of ORR were evaluated by cyclic voltammetry, polarization experiments, and chronoamperometry. The morphology and elemental composition of Pt alloys were characterized by X-ray diffraction (XRD) analysis and inductively coupled plasma atomic emission spectroscopy (ICP-AES) system. The catalytic activities of the bimetallic catalysts in GDEs have been shown to be not only dependent on the composition, but also on the nature of the electrolytes. The GDEs have shown a transition from the slow ORR kinetics in alkaline electrolyte to the fast ORR kinetics in the acidic electrolyte. The results also show that introduction of Pd as transition metal in the Pt alloys provides fast ORR kinetics in both acidic and alkaline electrolytes. The performance of GDEs with Pt–Pd alloy surfaces towards the ORR as a function of the alloy’s overall composition and their behavior in acidic electrolyte was also studied. These results show that the alloy’s overall composition and also the nature of the electrolytes have a large effect on the performance of GDEs for ORR.     

Copolymer of acrylonitrile/acrylic acid solid surface film dendrigrafted with citric acid

BACKGROUND: The aim of the present work was to improve the properties of acrylic polymer, which is a major fibre‐forming polymer. Acrylonitrile/acrylic acid copolymer, P(AN/AA), was chosen for this purpose and it was intended to study the condition for the formation of hydroxyl groups through the formation of hyperbranched polymers. RESULTS: The synthesis of a dendritic polymer of citric acid (CA) in the solid phase on a P(AN/AA) core is described. The product was analysed using the elemental analysis technique and ¹H NMR. Dendritic molecules were grown by a reaction between the carboxylic acid of acrylic acid and hydroxyl group of CA activated by dicyclohexylcarbodiimide. Products were analysed using Fourier transform infrared and NMR spectroscopy. CONCLUSION: The formation of CA dendrigraft on P(AN/AA) films in a heterogeneous system is possible. The percentage conversion of the copolymer reaction with CA was calculated based on the NMR results. The percentage conversion showed a gradual reduction with an increase in step numbers. The contact angle of water on the films was affected by the percentage conversion of the reactions. A calculation scheme is presented to show that the low degree of conversion leads to an increase in hydrophobic groups. Copyright © 2008 Society of Chemical Industry