Nano-sized carbon hollow spheres for abatement of ethylene

In this paper, the ethylene adsorption capacities of the nano-sized carbon hollow spheres (CNB) and active carbon (AC), the Pd (PdCl₂) impregnated CNB or AC (Pd/CNB, Pd/AC) and heat treatment under various conditions, were studied at different ethylene concentrations from 64 to 1060 ppm. The results indicated that AC had a good ethylene adsorption capacity at high ethylene concentration. Pd impregnation decreased the ethylene adsorption capacity of AC. Heat treatment and H₂ activation could increase the ethylene adsorption capacity, but also lowered than AC itself. CNB had lower ethylene adsorption capacity than AC, but heat treatment and H₂ activation could increase its ethylene adsorption capacity markedly. With activating condition from heat treatment in N₂ at 300 °C to activation in H₂/N₂ at 100 °C, to activation in H₂ at 200 °C, and to activation in H₂ at 300 °C, the ethylene adsorption capacity of Pd/CNB was increased regularly. At low ethylene concentration, viz., 64 ppm, the ethylene adsorption quantities (q _a) by Pd/CNB activated in H₂ at 200 or 300 °C were higher than any other adsorbents. So, activated in H₂ atmosphere at higher than 100 °C, Pd/CNB is particularly advantaged for adsorbing low concentration of ethylene. Amongst all the adsorbents used, Pd/CNB activated in H₂ atmosphere at 300 °C for 2 h has the highest ethylene adsorption capacity at lower concentration than 125 ppm. In addition, all the CNB, Pd/CNB, AC, and Pd/AC samples can be easily regenerated in airflow for more than 3 h.     

Feature Selection for Detecting ICMPv6-Based DDoS Attacks Using Binary Flower Pollination Algorithm

Internet Protocol version 6 (IPv6) is the latest version of IP that goal to host 3.4 × 10³⁸ unique IP addresses of devices in the network. IPv6 has introduced new features like Neighbour Discovery Protocol (NDP) and Address Auto-configuration Scheme. IPv6 needed several protocols like the Address Auto-configuration Scheme and Internet Control Message Protocol (ICMPv6). IPv6 is vulnerable to numerous attacks like Denial of Service (DoS) and Distributed Denial of Service (DDoS) which is one of the most dangerous attacks executed through ICMPv6 messages that impose security and financial implications. Therefore, an Intrusion Detection System (IDS) is a monitoring system of the security of a network that detects suspicious activities and deals with a massive amount of data comprised of repetitive and inappropriate features which affect the detection rate. A feature selection (FS) technique helps to reduce the computation time and complexity by selecting the optimum subset of features. This paper proposes a method for detecting DDoS flooding attacks (FA) based on ICMPv6 messages using a Binary Flower Pollination Algorithm (BFPA-FA). The proposed method (BFPA-FA) employs FS technology with a support vector machine (SVM) to identify the most relevant, influential features. Moreover, The ICMPv6-DDoS dataset was used to demonstrate the effectiveness of the proposed method through different attack scenarios. The results show that the proposed method BFPA-FA achieved the best accuracy rate (97.96%) for the ICMPv6 DDoS detection with a reduced number of features (9) to half the total (19) features. The proven proposed method BFPA-FA is effective in the ICMPv6 DDoS attacks via IDS.     

Corrigendum to “A model to control environmental performance of project execution process based on greenhouse gas emissions using earned value management” [Int. J. Proj. Manag. 36 (3) (April 2018) 397-413]

Abstract was revised as follows:In response to recent climate change, which is believed to be attributed to the release of greenhouse gas (GHG) emissions, many countries are placing CO₂ abatement programs such as carbon tax and cap-and-trade. Projects do have a significant share in GHGs and therefore their environmental performance, like their schedule and cost performance, should be monitored and controlled. Although many large projects would pass an environmental assessment in the project evaluation phase, the issue of environmental performance monitoring during the project execution phase has not been addressed in project management methodologies. The objective of this paper is to develop a model to estimate project GHG emissions, and to measure project GHG performance using the developed metrics, which can be used at any point in time over the life of a project. A comprehensive study is conducted to collect information on GHG emission factors of various project activity data (such as material use, energy and fuel consumption, transportation, etc.), and a user form interface is developed to calculate the total GHG of an activity. Also, a breakdown structure is proposed which supports managing all the project GHG accounts. The monitoring and control model is formulated based on the logic used in earned value management (EVM) methodology. The proposed model is then implemented to a work package of a real construction project. The results present the project initial GHG plan and show that the model is able to calculate project GHG variance by the reporting date and predict project final GHG based on a project GHG performance index. The method presented in this paper is general and can be applied to any type of projects in an organization that aims to reduce its carbon footprint. The same structure can be applied to monitor and control any other environmental impact associated with project execution process.     

Toward prediction of surface tension of branched n-alkanes using ANN technique

This study features the application of artificial neural network for prediction of surface tension of branched alkanes. Surface and interfacial tensions of alkanes show a specific interaction between adjacent molecules of the higher n-alkanes which results in an anisotropic dispersion force component of the surface energy. The surface tension of branched alkanes was studied for temperatures between 283.15 and 448.15 K. Two intelligent models named multilayer perceptron model (MLP) and radial basis function (RBF) model were developed and the accuracy of two models was examined by different graphical and statistical methods. Results showed that the both models are accurate and effective in prediction of surface tension of branched alkanes. However, the results were compared with experimental data and it was found that the estimated surface tension by multi-layer perceptron neural network is more accurate than radial basis function network.     

A globally convergent BFGS method for pseudo-monotone variational inequality problems

In this paper, we propose a globally convergent BFGS method to solve Variational Inequality Problems (VIPs). In fact, a globalization technique on the basis of the hyperplane projection method is applied to the BFGS method. The technique, which is independent of any merit function, is applicable for pseudo-monotone problems. The proposed method applies the BFGS direction and tries to reduce the distance of iterates to the solution set. This property, called Fejer monotonicity of iterates with respect to the solution set, is the basis of the convergence analysis. The method applied to pseudo-monotone VIP is globally convergent in the sense that subproblems always have unique solutions, and the sequence of iterates converges to a solution to the problem without any regularity assumption. Finally, some numerical simulations are included to evaluate the efficiency of the proposed algorithm.     

Experimental Investigation of Interference Between Adjacent Footings on Layered Cohesionless Soil

Soil Mechanics and Foundation Engineering - In this study, an experimental investigation of the interference effect of two closely spaced strip footings resting on the surface of a layered sand...     

Effects of ibuprofen on airway vascular response to cotton smoke injury

We studied the effects of ibuprofen on bronchial blood flow and myocardial function after inhalation injury. Sheep (n = 12) were chronically instrumented with cardiovascular and pulmonary catheters. After 5 days of recovery period, baseline data were collected and the sheep were divided into two groups. Group S (n = 6) were insufflated with 48 breaths of cotton smoke; while group I (n = 6) were pretreated with ibuprofen (12mg/kg bolus followed by 3 mg/kg/h continuous infusion for 24 h) and challenged with the same dose of smoke. All the animals were studied for 24h. Bronchial blood flow increased significantly in both groups throughout the experimental period; while stroke volume as well as right and left ventricular stroke work indices of both groups were significantly decreased (group I worse than group S) in the second half of the experimental period. These data suggest that vasodilatory prostaglandins do not play a major role in the bronchial vascular response to smoke inhalation injury and myocardial depression seen post injury is worse in animals treated with ibuprofen.     

Identifying the period of a step change in high‐yield processes

Quality control charts have proven to be very effective in detecting out‐of‐control states. When a signal is detected a search begins to identify and eliminate the source(s) of the signal. A critical issue that keeps the mind of the process engineer busy at this point is determining the time when the process first changed. Knowing when the process first changed can assist process engineers to focus efforts effectively on eliminating the source(s) of the signal. The time when a change in the process takes place is referred to as the change point. This paper provides an estimator for a period of time in which a step change in the process non‐conformity proportion in high‐yield processes occurs. In such processes, the number of items until the occurrence of the first non‐conforming item can be modeled by a geometric distribution. The performance of the proposed model is investigated through several numerical examples. The results indicate that the proposed estimator provides a reasonable estimate for the period when the step change occurred at the process non‐conformity level. Copyright © 2009 John Wiley & Sons, Ltd.     

A special finite element for the analysis of the singularity in a bimaterial containing a crack perpendicular to the interface

It is shown that the singularity of stresses near the tip of crack in an elastic bi-material can be obtained by using degenerate triangular elements, the shape functions of which are derived from those classical isoparametric elements. A four node triangular element is tested on two different samples. The results obtained are compared with those which exist already in bibliography.     

Epithelial Layer Estimation Using Curvatures and Textural Features for Dysplastic Tissue Detection

Boundary effect in digital pathology is a phenomenon where the tissue shapes of biopsy samples get distorted during the sampling process. The morphological pattern of an epithelial layer is greatly affected. Theoretically, the shape deformation model can normalise the distortions, but it needs a 2D image. Curvatures theory, on the other hand, is not yet tested on digital pathology images. Therefore, this work proposed a curvature detection to reduce the boundary effects and estimates the epithelial layer. The boundary effect on the tissue surfaces is normalised using the frequency of a curve deviates from being a straight line. The epithelial layer’s depth is estimated from the tissue edges and the connected nucleolus only. Then, the textural and spatial features along the estimated layer are used for dysplastic tissue detection. The proposed method achieved better performance compared to the whole tissue regions in terms of detecting dysplastic tissue. The result shows a leap of kappa points from fair to a substantial agreement with the expert’s ground truth classification. The improved results demonstrate that curvatures have been effective in reducing the boundary effects on the epithelial layer of tissue. Thus, quantifying and classifying the morphological patterns for dysplasia can be automated. The textural and spatial features on the detected epithelial layer can capture the changes in tissue.