Synthesis and characterization of new thermally stable poly(ester‐imide)s derived from 2,2′‐bis(4‐trimellitimidophenoxy)biphenyl and 2,2′‐bis(4‐trimellitimidophenoxy)‐1,1′‐binaphthyl and various aromatic dihydroxy compounds

A series of new alternating aromatic poly(ester‐imide)s were prepared by the polycondensation of the preformed imide ring‐containing diacids, 2,2′‐bis(4‐trimellitimidophenoxy)biphenyl (2a) and 2,2′‐bis(4‐trimellitimidophenoxy)‐1,1′‐binaphthyl (2b) with various aromatic dihydroxy compounds in the presence of pyridine and lithium chloride. A model compound (3) was also prepared by the reaction of 2b with phenol, its synthesis permitting an optimization of polymerization conditions. Poly(ester‐imides) were fully characterized by FTIR, UV‐vis and NMR spectroscopy. Both biphenylene‐ and binaphthylene‐based poly(ester‐imide)s exhibited excellent solubility in common organic solvents such as tetrahydrofuran, m‐cresol, pyridine and dichloromethane. However, binaphthylene‐based poly(ester‐imide)s were more soluble than those of biphenylene‐based polymers in highly polar organic solvents, including N‐methyl‐2‐pyrrolidone, N,N‐dimethylacetamide, N,N‐dimethylformamide and dimethyl sulfoxide. From differential scanning calorimetry thermograms, the polymers showed glass‐transition temperatures between 261 and 315 °C. Thermal behaviour of the polymers obtained was characterized by thermogravimetric analysis, and the 10 % weight loss temperatures of the poly(ester‐imide)s was in the range 449–491 °C in nitrogen. Furthermore, crystallinity of the polymers was estimated by means of wide‐angle X‐ray diffraction. The resultant poly(ester‐imide)s exhibited nearly an amorphous nature, except poly(ester‐imide)s derived from hydroquinone and 4,4′‐dihydroxybiphenyl. In general, polymers containing binaphthyl units showed higher thermal stability but lower crystallinity than polymers containing biphenyl units. Copyright © 2005 Society of Chemical Industry     

基于不同爆轰产物的格尼速度估算新方法（英）

A new method for prediction of Gurney velocity of explosives is introduced in which energy output is correlated with the heat of detonation, the number of moles of gaseous products of detonation per gram of explosive and the average molecular weight of gaseous products. It is assumed that the CHNO explosive reacts to form products composed of N2 , CO, H2O, CO2, H2,O2 and C（s） as determined by the oxygen balance of the unreacted compound. Good agreement is obtained between measured and calculated values of Gurney velocity as compared to previous correlations which assumed the reaction products to consist of N2 , H2O, CO2 and either C（s） or O2.     

Reconstruction of reflectance spectra using weighted principal component analysis

The weighted principal component analysis technique is employed for reconstruction of reflectance spectra of surface colors from the related tristimulus values. A dynamic eigenvector subspace based on applying certain weights to reflectance data of Munsell color chips has been formed for each particular sample and the color difference value between the target, and Munsell dataset is chosen as a criterion for determination of weighting factors. Implementation of this method enables one to increase the influence of samples which are closer to target on extracted principal eigenvectors and subsequently diminish the effect of those samples which benefit from higher amount of color difference. The performance of the suggested method is evaluated in spectral reflectance reconstruction of three different collections of colored samples by the use of the first three Munsell bases. The resulting spectra show considerable improvements in terms of root mean square error between the actual and reconstructed reflectance curves as well as CIELAB color difference under illuminant A in comparison to those obtained from the standard PCA method. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 360–371, 2008     

Genetic algorithm hybridized with multilayer perceptron to have an economical slope stability design

The present work aimed to evaluate and optimize the design of an artificial neural network (ANN) combined with an optimization algorithm of genetic algorithm (GA) for the calculation of slope stability safety factors (SF) in a pure cohesive slope. To make datasets of training and testing for the developed predictive models, 630 finite element limit equilibrium (FELE) analyses were performed. Similar to many artificial intelligence-based solutions, the database was involved in 189 testing datasets (e.g., 30% of the entire database) and 441 training datasets; for example, a range of 70% of the total database. Moreover, variables of multilayer perceptron (MLP) algorithm (for example, number of nodes in any hidden layer) and the algorithm of GA like population size was optimized by utilizing a series of trial and error process. The parameters in input, which were used in the analysis, consist of slope angle (β), setback distance ratio (b/B), applied stresses on the slope (F_y) and undrained shear strength of the cohesive soil (C_u) where the output was taken SF. The obtained network outputs for both datasets from MLP and GA-MLP models are evaluated according to many statistical indices. A total of 72 MLP trial and error (e.g., parameter study) the optimal architecture of 4 × 8 × 1 were determined for the MLP structure. Both proposed techniques result in a proper performance; however, according to the statistical indices, the GA–MLP model can somewhat accomplish the least mean square error (MSE) when compared to MLP. In an optimized GA–MLP network, coefficient of determination (R²) and root mean square error (RMSE) values of (0.975, and 0.097) and (0.969, and 0.107) were found, respectively, to both of the normalized training and testing datasets.

     

Nonlinear evolutionary swarm intelligence of grasshopper optimization algorithm and gray wolf optimization for weight adjustment of neural network

Engineering with Computers - The advent of new data-mining techniques and, more recently, swarm-based optimization algorithms have antiquated traditional models in the field of energy performance...     

Ignite-GPU: a GPU-enabled in-memory computing architecture on clusters

The Journal of Supercomputing - During recent years, big data explosion and the increase in main memory capacity, on the one hand, and the need for faster data processing, on the other hand, have...     

A firefly algorithm for power management in wireless sensor networks (WSNs)

The Journal of Supercomputing - In wireless sensor networks (WSNs), designing a stable, low-power routing protocol is a major challenge because successive changes in links or breakdowns destabilize...     

Optimal pixel aspect ratio for enhanced 3D TV visualization

In multiview 3D TV, a pair of corresponding pixels in adjacent 2D views contributes to the reconstruction of voxels (3D pixels) in the 3D scene. We analyze this reconstruction process and determine the optimal pixel aspect ratio based on which the estimated object position can be improved given specific imaging or viewing configurations and constraints. By applying mathematical modeling, we deduce the optimal solutions for two general stereo configurations: parallel and with vergence. We theoretically show that for a given total resolution a finer horizontal resolution, compared to the usual uniform pixel distribution, in general, provides a better 3D visual experience for both configurations. The optimal value may vary depending on different configuration parameter values. We validate our theoretical results by conducting subjective studies using a set of simulated non-square discretized red–blue stereo pairs and show that human observers indeed have a better 3D viewing experience with an optimized vs. a non-optimized representation of 3D-models.     

Multiobjective invasive weed optimization: Application to analysis of Pareto improvement models in electricity markets

This paper presents a proposal for multiobjective Invasive Weed Optimization (IWO) based on nondominated sorting of the solutions. IWO is an ecologically inspired stochastic optimization algorithm which has shown successful results for global optimization. In the present work, performance of the proposed nondominated sorting IWO (NSIWO) algorithm is evaluated through a number of well-known benchmarks for multiobjective optimization. The simulation results of the test problems show that this algorithm is comparable with other multiobjective evolutionary algorithms and is also capable of finding better spread of solutions in some cases. Next, the proposed algorithm is employed to study the Pareto improvement model in two complex electricity markets. First, the Pareto improvement solution set is obtained for a three-player oligopolistic electricity market with a nonlinear demand function. Then, the IEEE 30-bus power system with transmission constraints is considered, and the Pareto improvement solutions are found for the model with deterministic cost functions. In addition, NSIWO algorithm is used to analyze this system with stochastic cost data in a risk management problem which maximizes the expected total profit but minimizes the profit risk in the market.