A quantitative and simulation model for managing sudden supply delay with fuzzy demand and safety stock

In this paper, a recovery model is developed for managing sudden supply delays that affect retailers’ economic order quantity model. For this, a mathematical model is developed that considers fuzzy demand and safety stock, and generates a recovery plan for a finite future period immediately after a sudden supply delay. An efficient heuristic solution is developed that generates the recovery plan after a sudden supply delay. An experiment with scenario-based analysis is conducted to test our heuristic and to analyse the results. To assess the quality and consistency of solutions, the performance of the proposed heuristic is compared with the performance of the generalised reduced gradient method, which is widely applied in constrained mathematical programming. A simulation model is also designed to bring the recovery model closer to real-world processes. Several numerical examples are presented and a sensitivity analysis is performed to demonstrate the effects of various parameters on the performance of the heuristic method. The results show that safety stock plays an important role in recovery from sudden supply delays, and there is a trade-off between backorder and lost sales costs in the recovery plan. With the help of the proposed model, supply chain decision-makers can make accurate and prompt decision regarding recovery plans in case of sudden supply delay.     

Gamma-ray shielding properties of zinc oxide soda lime silica glasses

In the present work, the gamma ray shielding properties of zinc oxide soda lime silica, (ZnO)_x(SLS)_1?x glasses with 0 ≥ x ≥ 50 wt% have been investigated. By using WinXCom computer software, the mass attenuation coefficient (µ/ρ) and half value layer (HVL) for total photon interaction in the energy range of 1 keV–100 GeV were calculated. Furthermore and by Geometric Progression method exposure buildup factor values were calculated for incident photon energy 0.015–15 MeV up to penetration depths of 40 mfp (mean free path). The addition of zinc oxide (ZnO) into soda lime silica (SLS) glass resulted in an increase the mass attenuation coefficient and decreases both the half value layer and exposure buildup factor. The obtained results of the selected glass series have been compared, in terms of mass attenuation coefficient, half value layer and exposure buildup factor with some common shielding materials. The shielding effectiveness of the selected glasses is found comparable to that of common ones; which indicates that the SLS glasses with suitable ZnO content may be developed as gamma ray shielding materials.     

A game theoretic-based distributed detection method for VM-to-hypervisor attacks in cloud environment

Cloud computing is a pool of scalable virtual resources serving a large number of users who pay fees depending on the extent of utilized service. From payment perspective, cloud is like electricity and water as people who use more of this shared pool should pay larger fees. Cloud computing involves a diverse set of technologies including networking, virtualization and transaction scheduling. Thus, it is vulnerable to a wide range of security threats. Some of the most important security issues threatening the cloud computing systems originate from virtualization technology, as it constitutes the main body and basis of these systems. The most important virtualization-based security threats include VM side channel, VM escape and rootkit attacks. The previous works on the subject of virtualization security rely on hardware approaches such as the use of firewalls, which are expensive, the use of schedulers to control the side channels along with noise injection, which impose high overhead, or the use of agents to collect information and send them back to a central intrusion detection system, which itself can become the target of attacker. In the method presented in this paper, a group of mobile agents act as the sensors of invalid actions in the cloud environment. They start a noncooperative game with the suspected attacker and then calculate the Nash equilibrium value and utility so as to differentiate an attack from legitimate requests and determine the severity of attack and its point of origin. The simulation results show that this method can detect the attacks with 86% accuracy. The use of mobile agents and their trainability feature has led to reduced system overhead and accelerated detection process.     

Automating identification of services and their variability for product lines using NSGA-II

Architecture-level business services are identified based on business processes; and likewise, in service-oriented product lines, identifying the domain architecture-level business services and their variability is preferred to be based on business processes and their variability. Identification of business services for a product line satisfying a set of given design metrics (such as cohesion and coupling) is extremely difficult for a domain architect, since there are many product configurations for which the services must be proper at the same time. This means that the identified services must have proper values for n metrics in m different configurations at the same time. The problem becomes more serious when there are high degrees of variability and complexity embedded in the business processes that are the basis for service identification.We contribute to solve the multi-objective optimization problem of identifying business services for a product line by partitioning the graph of a business process variability model utilizing Non-dominated Sorting Genetic Algorithm-II. The service specification is achieved based on the results of the partitioning. The variability of the services is then determined in terms of mandatory and optional services as well as variability relationships, which are all represented in a Service Variability Model. The method was empirically evaluated through experimentation, and showed proper levels of reusability and variability. Furthermore, the resulting models were fully consistent.     

Low temperature functional analysis of bitumen modified with composite of nano-SiO2 and styrene butadiene styrene polymer

Most parts of Iran have completely different climates in different seasons of year. In other words, in summer it is very warm and in winter it becomes very cold. Achieving modified bitumen that could function adequately in both high and low temperature has always been under attention of researchers. One of bitumen modifiers is styrene butadiene styrene polymer. Because bitumen modified by styrene butadiene styrene does not show expected field function in both high and low temperatures, largely due to phase separation of bitumen and polymer, in the present study it has been tried to analyze the low-temperature function of bitumen modified by combining nano-SiO₂ and styrene butadiene styrene polymer. The study reveals that adding nano-SiO₂ by 3% and 4% of bitumen weight to the double combination of bitumen and styrene butadiene styrene polymer has improved its function in low temperature. This study has innovation as it deals with the analysis of low temperature function of nano-SiO₂ and SBS in modification of bitumen for the first time in the world.     

Numerical simulation of hydrogen production by gasification of large biomass particles in high temperature fluidized bed reactor

Biomass as a renewable fuel compared to fossil fuels usually contains high moisture content and volatile release. Hydrogen production by large particle biomass gasification is a promising technology for utilizing high moisture content biomass particle in the high temperature fluidized bed reactor. In the present work, simulation of large particles biomass gasification investigated at high temperature by using the discrete phase model (DPM). Combustible gases with homogeneous gas phase reactions, drying process with a heterogeneous reaction, primary and secondary pyrolysis with independent parallel-reaction by using two-competing-rate model to control a high and low temperature were used. During the thermochemical process of biomass, gaseous products containing of H₂, H₂O, CH₄, CO and CO₂ was obtained. The effects of concentration, mole and mass fraction and hydrodynamics effects on gaseous production during gasification were studied. The results showed that hydrodynamic effect of hot bed is different from cold bed. Concentration and molar fraction of CO and H₂ production by continually and stably state and small amount of CO₂, H₂O, and CH₄ was obtained. The hydrodynamic of bed plays the significant role on the rate of gaseous products.     

Inverse radiation-conduction estimation of temperature-dependent emissivity using a combined method of genetic algorithmand conjugate gradient

The solution of an inverse, conduction-radiation problem in a two-dimensional rectangle is analyzed to determine the temperature-dependent emissivity at the boundary. The medium is gray, absorbing, emitting and isotropically scattering. The bounding surfaces are assumed to be opaque and diffuse. The inverse problem is solved by minimizing the performance function, which is expressed by the sum of square residuals between estimated and exact heat fluxes, using a combined method of genetic algorithm and conjugate gradient. The emissivity is assumed to be represented as a function of boundary temperature with unknown variables. Therefore, the inverse problem is treated by the estimation of these variables. Finally, four examples are presented to show the accuracy of the algorithm. The effect of the measurement errors on the accuracy of the inverse analysis is also investigated. Results show the algorithm can estimate the unknown emissivity when the measurement errors are neglected. Also it is found that increasing the measurement error decreases the accuracy of estimation of temperature-dependent emissivity.     

Desulfurization From Model of Gasoline by Extraction With Synthesized [BF4]−- and [PF6]−-based Ionic Liquids

Abstract

The authors report that 1-octyl-3-methylimidazolium tetrafluoroborate, [OMIM][BF₄], and 1-butyl-3-methylimidazolium hexafluorophosphate, [BMIM][PF₆], ionic liquids were synthesized and tested for their capability to desulfurization from model of gasoline. The results show that the aromatic sulfur compounds with higher π-electron density were favorably adsorbed. The results also show that [BF₄]^?-based ionic liquid displays higher extraction efficiencies than [PF₆]^?-based ionic liquid. Thus, it was shown that the extractive ability of the imidazolium ionic liquids was dominated by the structure of cation and anion. It is also found that the sizes of ionic liquids are important factors affecting the absorption capacity for aromatic sulfur compounds.