Structural Characterization of Different Asphaltenes of Kuwaiti Origin

Asphaltenes obtained by precipitation from crude Kuwaiti oils have been analyzed by proton magnetic resonance (¹H-NMR), carbon-13 nuclear magnetic resonance (¹³C-NMR) and Infrared (IR) spectral techniques. The molecular weight and elemental analysis were also determined. These combined analytical data were used for the characterization of these Kuwaiti oils. The asphaltenes molecular weights range from approximately 4200-6500 with an H/C ratio of 0.91-1.1 with an average 45-71% aromatic carbons. The average side chain length was of 4-6 carbons. It can also be concluded that the asphaltenes under investigation contain 5-9 sets of condensed aromatic rings joined together by bridges of alkyl chains or other hetero atoms and the average number of each of these sets of condensed aromatic rings is nearly 7. There are a number of alicyclic rings and condensed alicyclic rings in asphaltene. The IR spectra showed main molecular groups including OH, NH, SH, C=O and aliphatic and aromatic C-H's.     

Harmonic and intermodulation performance in an R-LED series network

Analytical expressions are obtained for predicting the harmonic and intermodulation performance of R-LED series networks. These expressions are in terms of the ordinary Bessel functions with arguments depenedent on the modulation index.     

On ℤ2ℤ2[u]-additive codes

In this paper, a new class of additive codes which is referred to as ?₂ ?₂[u]-additive codes is introduced. This is a generalization towards another direction of recently introduced ?₂ ?₄-additive codes [J. Borges, C. Fernández-Córdoba, J. Pujol, J. Rif´a, and M. Villanueva, ?₂ ?₄-linear codes: Generator matrices and duality, Designs Codes Cryptogr. 54(2) (2010), pp. 167–179]. ?₂ ?₄-additive codes have shown to provide a promising class of codes with their algebraic structure and applications such as steganography. The standard generator matrices are established and by introducing orthogonality the parity-check matrices are also obtained. A MacWilliams-type identity that relates the weight enumerator of a code with its dual is proved. Furthermore, a Gray map that maps these codes to binary codes is defined and some examples of optimal codes which are the binary Gray images of ?₂ ?₂[u]-additive codes are presented.     

Cross level semantic similarity: an evaluation framework for universal measures of similarity

Semantic similarity has typically been measured across items of approximately similar sizes. As a result, similarity measures have largely ignored the fact that different types of linguistic item can potentially have similar or even identical meanings, and therefore are designed to compare only one type of linguistic item. Furthermore, nearly all current similarity benchmarks within NLP contain pairs of approximately the same size, such as word or sentence pairs, preventing the evaluation of methods that are capable of comparing different sized items. To address this, we introduce a new semantic evaluation called cross-level semantic similarity (CLSS), which measures the degree to which the meaning of a larger linguistic item, such as a paragraph, is captured by a smaller item, such as a sentence. Our pilot CLSS task was presented as part of SemEval-2014, which attracted 19 teams who submitted 38 systems. CLSS data contains a rich mixture of pairs, spanning from paragraphs to word senses to fully evaluate similarity measures that are capable of comparing items of any type. Furthermore, data sources were drawn from diverse corpora beyond just newswire, including domain-specific texts and social media. We describe the annotation process and its challenges, including a comparison with crowdsourcing, and identify the factors that make the dataset a rigorous assessment of a method’s quality. Furthermore, we examine in detail the systems participating in the SemEval task to identify the common factors associated with high performance and which aspects proved difficult to all systems. Our findings demonstrate that CLSS poses a significant challenge for similarity methods and provides clear directions for future work on universal similarity methods that can compare any pair of items.     

Random resampling algorithms for addressing the imbalanced dataset classes in insider threat detection

International Journal of Information Security - Cybersecurity threats can be perpetrated by insiders or outsiders. The threats that could be carried out by insiders are far more serious due to...     

Hybrid image steganography method using Lempel Ziv Welch and genetic algorithms for hiding confidential data

Multidimensional Systems and Signal Processing - Digital images are commonly used in steganography due to the popularity of digital image transfer and exchange through the Internet. However, the...     

Estimation of magnitude and time duration of temporary overvoltages using ANN in transmission lines during power system restoration

In most countries, the main step in the process of power system restoration, following a complete/partial blackout, is energization of primary restorative transmission lines. Artificial neural network (ANN) is employed for performing a nonlinear input–output mapping in this work, in order to estimate the temporary overvoltages (TOVs) due to transmission lines energization. In the proposed methodology, Levenberg–Marquardt second order method is used to train the multilayer perceptron. Proposed ANN is trained with equivalent circuit parameters of the network as input parameters, trained ANN has therefore satisfactory generalization capability. Both single and three-phase line energizations are analyzed. The simulated results for 39-bus New England test system, indicate that the proposed technique can estimate the peak values and duration of switching overvoltages with acceptable accuracy.     

An efficient hybrid approach based on PSO, ACO and k-means for cluster analysis

Clustering is a popular data analysis and data mining technique. A popular technique for clustering is based on k-means such that the data is partitioned into K clusters. However, the k-means algorithm highly depends on the initial state and converges to local optimum solution. This paper presents a new hybrid evolutionary algorithm to solve nonlinear partitional clustering problem. The proposed hybrid evolutionary algorithm is the combination of FAPSO (fuzzy adaptive particle swarm optimization), ACO (ant colony optimization) and k-means algorithms, called FAPSO-ACO–K, which can find better cluster partition. The performance of the proposed algorithm is evaluated through several benchmark data sets. The simulation results show that the performance of the proposed algorithm is better than other algorithms such as PSO, ACO, simulated annealing (SA), combination of PSO and SA (PSO–SA), combination of ACO and SA (ACO–SA), combination of PSO and ACO (PSO–ACO), genetic algorithm (GA), Tabu search (TS), honey bee mating optimization (HBMO) and k-means for partitional clustering problem.     

Calendar of Future Meetings Involving IWRA

ABSTRACT

Irrigation-water-delivery systems are designed and managed to receive water from a source and to distribute it among farmers in order to meet their agricultural requirements. High system performance can be achieved through rehabilitation of deteriorating and inadequate physical facilities and through improved system management. Various design decisions must be made in order to rehabilitate or develop irrigation-water-delivery systems, including those related to specification of the characteristics of hydraulic structures used to convey regulate, or divert water

This study develops and applies a response surface methodology (RSM) for achieving optimal design for hydraulic structures in irrigation-water-delivery systems in canal networks. This approach provides a means of understanding system behavior through developing a response surface in terms of a mathematical expression representing system performance as affected by design decisions. Design decisions include pipe diameters for diversion and regulating structures. Simulation of steady spatially varied flow was incorporated into the response surface methodology to determine high-performance low-cost solutions.

Objectives of adequacy, efficiency dependability, and equity of water delivery were considered in defining water delivery performance. Fuzzy membership functions were used to address subjectivity associated with interpreting expected values of performance measures associated with each of the prescribed objectives.

This study is an extension of a previous study by Alshaikh [1]. That study reported the application of RSM on a single canal case while herein RSM was used for the case of a canal network. Though, in general, RSMs for large-scale branched systems are computationally intensive, this proposed methodology overcomes this drawback. The approach constitutes a significant easy-to-use step forward in the development of comprehensive systems-scale techniques for the design of structural components of irrigation-water-delivery systems.     

Influence of processing condition and carbon nanotube on mechanical properties of injection molded multi‐walled carbon nanotube/poly(methyl methacrylate) nanocomposites

In this work, multi‐walled carbon nanotubes (MWCNT) and poly(methyl methacrylate) (PMMA) pellets were compounded via corotating twin‐screw extruder. The produced MWCNT/PMMA nanocomposite pellets were injection molded. The effect of MWCNT concentration, injection melt temperature and holding pressure on mechanical properties of the nanocomposites were investigated. To examine the mechanical properties of the MWCNT/PMMA nanocomposites, tensile test, charpy impact test, and Rockwell hardness are considered as the outputs. Design of experiments (DoE) is done by full factorial method. The morphology of the nanocomposites was performed using scanning electron microscopy (SEM). The results revealed when MWCNT concentration are increased from 0 to 1.5 wt %, tensile strength and elongation at break were reduced about 30 and 40%, respectively, but a slight increase in hardness was observed. In addition, highest impact strength belongs to the nanocomposite with 1 wt % MWCNT. This study also shows that processing condition significantly influence on mechanical behavior of the injection molded nanocomposite. In maximum holding pressure (100 bar), the nanocomposites show highest tensile strength, elongation, impact strength and hardness. According to findings, melt temperature has a trifle effect on elongation, but it has a remarkable influence on tensile strength. In the case of impact strength, higher melt temperature is favorable. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43738.