A Decision-Tree Scheme for Responding to Uncertainties in Microgrid Protection Coordination

In addition to the dynamic nature of microgrids, uncertainty in the proper operation of protection system and communication links are other challenges affecting the protection coordination of these networks. Therefore, in this paper, a new protection coordination plan based on decision tree for considering uncertainties in the topology of microgrid, protection system, and communication links is presented. The proposed method allows the adaptive protection to make global decisions and adopt the best strategy to clear faults depending on considered uncertainties. Since circuit breakers are the most prone to failure equipment in the protection system due to fault-caused stress, this paper models uncertainty in the protection system with uncertainty in the performance of circuit breakers. In order to consider uncertainty in circuit breakers and communication links, their probability of correct operation are not considered fixed but variable, respectively, proportional to the fault current flowing through the circuit breakers and the latency of communication links. The proposed plan was tested on a sample microgrid in DIgSILENT Power Factory. Results prove that using the proposed method, adaptive protection can establish an optimal sequence of strategies so that with the failure of each strategy, the best backup strategy is replaced given the uncertainties.     

Quantum Henry gas solubility optimization algorithm for global optimization

Engineering with Computers - In this article, the lightweight design problems of Timoshenko composite beams with and without considering the uncertainties of input data (i.e., the geometry of beam,...     

Secure communication between UAVs using a method based on smart agents in unmanned aerial vehicles

The Journal of Supercomputing - Unmanned aerial vehicles (UAVs) can be deployed to monitor very large areas without the need for network infrastructure. UAVs communicate with each other during...     

Brain tissue segmentation based on spatial information fusion by Dempster-Shafer theory

As a result of noise and intensity non-uniformity,automatic segmentation of brain tissue in magnetic resonance imaging (MRI) is a challenging task.In this study a novel brain MRI segmentation approach is presented which employs Dempster-Shafer theory (DST) to perform information fusion.In the proposed method,fuzzy c-mean (FCM) is applied to separate features and then the outputs of FCM are interpreted as basic belief structures.The salient aspect of this paper is the interpretation of each FCM output as a belief structure with particular focal elements.The results of the proposed method are evaluated using Dice similarity and Accuracy indices.Qualitative and quantitative comparisons show that our method performs better and is more robust than the existing method.     

Synthesis of new optically active poly(amide‐imide)s containing EPICLON and L‐phenylalanine in the main chain by microwave irradiation and classical heating

EPICLON [3a,4,5,7a‐Tetrahydro‐7‐methyl‐5‐(tetrahydro‐2,5‐dioxo‐3‐furanyl)‐1,3‐isobenzofurandione] or [5‐(2,5‐dioxotetrahydrofurfuryl)‐3‐methyl‐3‐cyclohexyl‐1,2‐dicarboxylic acid anhydride] ( 1 ) was reacted with L ‐phenylalanine ( 2 ) in acetic acid, and the resulting amic acid was refluxed under a Dean‐Stark system with benzene, which produced diacid ( 3 ) in high yield. Compound ( 3 ) was converted to the diacid chloride ( 4 ) by reaction with oxalyl chloride in dry carbon tetrachloride. The polycondensation reaction of this diacid chloride ( 4 ) with several aromatic diamines such as 4,4′‐sulfonyldianiline ( 5a ), 4,4′‐diaminodiphenylmethane ( 5b ), 4,4′‐diaminodiphenylether ( 5c ), 1,4‐phenylenediamine ( 5d ), 1,3‐phenylenediamine ( 5e ), 2,4‐diaminotoluene ( 5f ), and 1,5‐diaminonaphthalene ( 5g ) was developed by using a domestic microwave oven in the presence of a small amount of a polar organic medium such as N‐methylpyrrolidone ( NMP ). The polymerization reactions were also performed under two different classical heating methods: low temperature solution polycondensation in the presence of trimethylsilyl chloride, and high temperature polymerization. A series of optically active poly(amide‐imide)s with moderate yield and inherent viscosity of 0.14–0.22 dL/g were obtained. All of the above polymers were fully characterized by IR, elemental analyses, and specific rotation. Some structural characterization and physical properties of this optically active poly(amide‐imide)s are reported. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 91: 3281–3291, 2004     

Simple and efficient motion estimation algorithm by continuum search

Motion estimation plays a vital role in reducing temporal correlation in video codecs but it requires high computational complexity. Different algorithms have tried to reduce this complexity. However these reduced-complexity routines are not as regular as the full search algorithm (FSA). Also, regularity of an algorithm is very important in order to have a hardware implementation of that algorithm even if it leads to more complexity burden. The goal of this paper is to develop an efficient and regular algorithm which mimics FSA by searching a small area exhaustively. Our proposed algorithm is designed based on two observations. The first observation is that the motion vector of a block falls within a specific rectangular area designated by the prediction vectors. The second observation is that in most cases, this rectangular area is smaller than one fourth of the FSA’s search area. Therefore, the search area of the proposed method is adaptively found for each block of a frame. To find the search area, the temporal and spatial correlations among motion vectors of blocks are exploited. Based on these correlations, a rectangular search area is determined and the best matching block in this area is selected. The proposed algorithm is similar to FSA in terms of regularity but requires less computational complexity due to its smaller search area. Also, the suggested algorithm is as simple as FSA in terms of implementation and is comparable with many of the existing fast search algorithms. Simulation results show the claimed performance and efficiency of the algorithm.     

Flame-Retardancy Improvement of Novel Styrene–Maleic Anhydride Based Copolymers

Brominated flame-retardants are one of the common and efficient compounds in producing flame retardant plastics and antimony trioxide is often used as a synergistic agent for halogenated flame-retardants. In this research, a new reactive flame retardant, maleated tetrabromobiphenol-A (MTBBA) crystals, has been introduced for the first time and its structure was fully characterized by high-field ¹H NMR and ¹³C NMR spectroscopy. The improvement in flame-retardancy effect of styrene–maleic anhydride copolymer by MTBBA and also their compounded samples with Sb₂O₃ was investigated as the main purpose in this work. Limiting oxygen indexes (LOI) for the neat terpolymers and the compounded samples were measured by flammability tests. Also thermal gravimetry analysis (TGA) and differential scanning calorimetry (DSC) were applied in order to study thermal behavior of the samples. The results of thermal analysis were used to observe the effect of insertion of this novel monomer into the copolymer chain in comparison with styrene–maleic anhydride copolymer.     

Extended distributed learning automata

In this paper, a new structure for cooperative learning automata called extended learning automata (eDLA) is introduced. Based on the new structure, an iterative randomized heuristic algorithm using sampling is proposed for finding an optimal subgraph in a stochastic edge-weighted graph. Stochastic graphs are graphs in which the weights of edges have an unknown probability distribution. The proposed algorithm uses an eDLA to find a policy that leads to a subgraph that satisfy some restrictions such as minimum or maximum weight (length). At each stage of the proposed algorithm, the eDLA determines which edges should be sampled. The proposed eDLA-based sampling method may reduce unnecessary samples and hence decrease the time required for finding an optimal subgraph. It is shown that the proposed method converges to an optimal solution, the probability of which can be made arbitrarily close to 1 by using a sufficiently small learning parameter. A new variance-aware threshold value is also proposed that can significantly improve the convergence rate of the proposed eDLA-based algorithm. It is further shown that our algorithm is competitive in terms of the quality of the solution.     

Simulation of Segregation to Free Surfaces in Cubic Oxides

Segregation of isovalent solute cations to (001) and (001) free surfaces in cubic metal oxides is investigated using atomistic computer simulations. Solute concentrations are represented by a mean-field approximation, and equilibrium distributions of solute are calculated by minimizing the free energy. Surface energy effects are found to dominate segregation behavior, even when in competition with misfit strain energy effects. Results are compared with a conventional Langmuir-McLean (LM) analysis. The two approaches are found to agree well in certain cases, but the LM treatment fails to reproduce important phenomena revealed using the free energy method (i.e., segregation to subsurface atomic layers).