Using the Fuzzy Clustering and Principle Component Analysis for Assessing the Impact of Potential Evapotranspiration Calculation Method On the Modified RDI Index

The modified reconnaissance drought index (RDIe) which is a modified version of RDI is presented for assessing drought conditions with an emphasis on agricultural drought. The potential evapotranspiration (PET) and effective rainfall are required climatic variables to calculate RDIe. Although the FAO Penman–Monteith (FPM) equation is the reference method for determining the PET, due to the need for data of a large number of climatic variables it is difficult to use in areas with shortage climatic data. Therefore, in this research, using the fuzzy clustering (FC) and principle component analysis (PCA) methods, the influence of PET calculation methods including FPM (used as reference method), FAO Penman (FP), Hargreaves-Samani (HS), Blaney-Criddle (BC), Turc (Tu), Jensen-Haise (JH), Priestley–Taylor (PT) and FAO24 Radiation (Ra) methods on the RDIe (in 1, 3 and 12-month time scales) was assessed. In this study the climatic data series of 5 stations in Fars province, Iran from 1989 to 2018 was used. Based on the results of PCA model, in short-term time scales (1 and 3-month), the calculated RDIe values based on the HS method (at 100% of stations) and in long-term time scale (annual) based on the FP method (at 60% of stations) had the highest correlation with RDIe based on the FPM method. According to the results of FC method, in 1-month time scale, the values of RDIe using PT and HS methods (at 100% and 80% of selected stations, respectively), in 3-month time scale, the values of RDIe using PT, HS and Ra methods (at 100% of stations) and in annual time scale, the values of RDIe using FP method (at 60% of stations) had the highest similarities with the values of RDIe using FPM. Therefore, it is recommended to replace the FPM method with HS (in 1 and 3-month time scales) and FP (in 12-month time scales) methods in areas with minimum available meteorological data.

     

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.     

The Severn Barrage and other tidal energy options: Hydrodynamic and power output modeling

Details are given herein of the current main proposals for tidal energy provision from the Severn Estuary, in the UK, with particular emphasis being focused on the Severn Barrage project, as originally promoted by the Severn Tidal Power Group. In particular, emphasis has focused on assessing the potential hydro-environmental impacts and power outputs of a barrage across the estuary, with an unstructured grid, high resolution, model being developed and applied to the estuary to assess the implications of each of five shortlisted proposed schemes on the hydrodynamic, geomorphologic, flood risk and faecal indicator organism changes within the estuary. An outline is given of recent research on power refinements to the model to assess the options for power generation. The results show that the Severn Barrage has the potential to reduce the tidal currents in a highly dynamic estuary. This leads to the reduction of suspended sediment loads (particularly upstream of the barrage), an increase of light penetration within the water column and, potentially, an increase in the benthic bio-diversity and the level of aquatic life in the estuary. The results also show that the Severn Barrage will reduce markedly the risk of flooding upstream of the barrage and to a lesser extent downstream of the structure. In contrast the alternative options have far less impact on flood risk changes. In addition to the Severn Barrage some results are shown herein for a typical lagoon option, namely the Fleming Lagoon.     

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.     

Prediction and optimization of electrospinning parameters for polymethyl methacrylate nanofiber fabrication using response surface methodology and artificial neural networks

Since the fiber diameter determines the mechanical, electrical, and optical properties of electrospun nanofiber mats, the effect of material and process parameters on electrospun polymethyl methacrylate (PMMA) fiber diameter were studied. Accordingly, the prediction and optimization of input factors were performed using the response surface methodology (RSM) with the design of experiments technique and artificial neural networks (ANNs). A central composite design of RSM was employed to develop a mathematical model as well as to define the optimum condition. A three-layered feed-forward ANN model was designed and used for the prediction of the response factor, namely the PMMA fiber diameter (in nm). The parameters studied were polymer concentration (13–28 wt%), feed rate (1–5 mL/h), and tip-to-collector distance (10–23 cm). From the analysis of variance, the most significant factor that caused a remarkable impact on the experimental design response was identified. The predicted responses using the RSM and ANNs were compared in figures and tables. In general, the ANNs outperformed the RSM in terms of accuracy and prediction of obtained results.