A new interval type-2 fuzzy approach for analyzing and monitoring the performance of megaprojects based on earned value analysis (with a case study)

Neural Computing and Applications - Major factors of project success include using tools of performance measurements and feedbacks. Earned value management (EVM) is a unique issue within...     

Simulation of Shrinkage Porosity Formation During Alloy Solidification

Metallurgical and Materials Transactions A - Porosity due to solidification shrinkage is a troublesome defect in metal casting. It results in low yields and increased costs in production and limits...     

An efficient image retrieval based on an integration of HSV,RLBP, and CENTRIST features using ensemble classifier learning

Multimedia Tools and Applications - Recently, we have been witnessing a tremendous rise in digital image quantities, which in return calls for an adjustment and management system to fulfill...     

On braced trapezoidal corrugated steel shear panels: An experimental and numerical study

In this study, a new system consisting of a combination of braces and steel infill panels called the braced corrugated steel shear panel (BCSSP) is presented. To obtain the hysteretic behavior of the proposed system, the quasi-static cyclic performances of two experimental specimens were first evaluated. The finite element modeling method was then verified based on the obtained experimental results. Additional numerical evaluations were carried out to investigate the effects of different parameters on the system. Subsequently, a relationship was established to estimate the buckling shear strength of the system without considering residual stresses. The results obtained from the parametric study indicate that the corrugated steel shear panel (CSSP) with the specifications of a = 30 mm, t = 2 mm, and θ = 90° had the highest energy dissipation capacity and ultimate strength while the CSSP with the specifications of a = 30 mm, t = 2 mm, and θ = 30° had the highest initial stiffness. It can thus be concluded that the latter CSSP has the best structural performance and that increasing the number of corrugations, corrugation angle, and plate thickness and decreasing the sub-panel width generally enhance the performance of CSSPs in terms of the stability of their hysteretic behaviors.     

Single and multi‐objective optimization for the performance enhancement of lead–acid battery cell

Electric energy storage systems are used considerably in industries and daily applications. The demand for batteries with high energy content has increased because of their use in hybrid vehicles. Lead–acid batteries have wide applications because of their advantages such as high safety factor and low cost of production. The major shortcoming of lead–acid batteries is low energy content and high dimension and weight. Nowadays, a common method to increase the energy content of lead–acid battery is the experimental method with trial and error, which is time consuming and expensive. In this paper, non‐isothermal one‐dimensional numerical simulation of lead–acid battery with finite volume method is performed. In addition, a cell with higher energy content and lower thickness is designed by using particle swarm optimization algorithm based on developed simulation code. The results of single objective optimization show that an optimal battery that has 27.6% higher energy can be made with the same cell dimension. The results also show that an optimum cell battery can be obtained with a decrease of 24% in thickness while keeping the energy the same. Moreover, a multi‐objective optimization algorithm is utilized to find Pareto optimal solutions while considering the energy content and thickness objectives simultaneously. Copyright © 2016 John Wiley & Sons, Ltd.     

Screening of the Antioxidant and Enzyme Inhibition Potentials of Portuguese <Emphasis Type="Italic">Pimpinella anisum</Emphasis> L. Seeds by GC-MS

The results of GC-MS analysis are used to characterise the bioactive compounds in the infusion. The obtained results of the current research clearly revealed that the phenols, flavonoids and monomeric anthocyanins are abundant and a high-antioxidant activity of Pimpinella anisum L. infusions was detected. As expected, the studied plant’s infusion showed a stronger activity against free radicals than the enzymes that are attributed to generation of various chronic diseases. Among the characterised compounds, the fatty acids were detected with the highest quantity with 47.68% followed by triterpenoids and sterols, with 15.56 and 7.29%, respectively. Fatty acids (linoleic, oleic and palmitic acids), triterpenoids (lupeol, β-Amyrin and betulinic acids (BAs)) as well as sterols (β-sitosterol and stigmasterol) were detected as the main bioactive compounds in the studied infusion. In the current research, these compounds were detected to have substantial impacts on revealing of the potential health benefits of P. anisum L. seeds.     

Brittleness of rock and stability assessment in hard rock tunneling

Brittleness is a characteristic of many geomaterials in which the pre-existing heterogeneities among the mechanical and geometrical properties of the constituent materials, (e.g. grains cementing materials and voids) and loading conditions promote non-homogeneous distribution of the stresses inside the failing mass and eventually along the potential failure plane. This study relates the brittleness of failing hard rocks and tunnels to a strain-dependent brittleness index (I_B) which characterizes the entire failure process of rock (pre- to post-peak), and accounts for the involved mechanisms in inducing inelastic strains (damage) inside the failing rock. The strain-dependent brittleness of rock dictates the mobilized strength around underground excavations, affects their short- and long-term stability, and determines the shape of breakout (failed or inelastic) zone. The ground-support pressure interaction mechanism is also affected by rock brittleness. Brittleness of rock is a time- (loading rate) and size- (geometry) dependent property.     

Multi-walled carbon nanotube-supported Ni@Pd core–shell electrocatalyst for direct formate fuel cells

Journal of Applied Electrochemistry - In the present work, Ni@Pd core–shell nanoparticles are successfully deposited on multi-walled carbon nanotubes as support and investigated their...     

Spatial Based Pilot Allocation (SBPA) in Crowded Massive MIMO Systems

Nowadays, the internet of things (IoT) has gained significant research attention. It is becoming critically imperative to protect IoT devices against cyberattacks with the phenomenal intensification. The malicious users or attackers might take control of the devices and serious things will be at stake apart from privacy violation. Therefore, it is important to identify and prevent novel attacks in the IoT context. This paper proposes a novel attack detection system by interlinking the development and operations framework. This proposed detection model includes two stages such as proposed feature extraction and classification. The preliminary phase is feature extraction, the data from every application are processed by integrating the statistical and higher-order statistical features together with the extant features. Based on these extracted features the classification process is evolved for this, an optimized deep convolutional neural network (DCNN) model is utilized. Besides, the count of filters and filter size in the convolution layer, as well as the activation function, are optimized using a new modified algorithm of the innovative gunner (MAIG), which is the enhanced version of the AIG algorithm. Finally, the proposed work is compared and proved over other traditional works concerning positive and negative measures as well. The experimental outcomes show that the proposed MAIG algorithm for application 1 under the GAF-GYT attack achieves higher accuracy of 64.52, 2.38 and 3.76% when compared over the methods like DCNN, AIG and FAE-GWO-DBN, respectively.