Reserve estimation of an open pit mine under price uncertainty by real option approach

Reserve estimation is a key to find the correct NPV in a mining project. The most important factor in reserve estimation is the metal price. Metal price fluctuations in recent years were exaggerated, and imposed a high degree of uncertainty to the re-serve estimation, and in consequence to the whole mine planning procedure. Real option approach is an efficient method of deci-sion making in the uncertain conditions. This approach has been used for evaluation of defined natural resources projects until now. This study considering the metal price uncertainty used real option approach to prepare a methodology for reserve estimation in open pit mines. This study was done on a copper cylindrical deposit, but the achieved methodology can be adjusted for all kinds of deposits. This methodology was comprehensively described through the examples in such a manner that can be used by the mine planners.     

MC-MLAS: Multi-channel Minimum Latency Aggregation Scheduling in Wireless Sensor Networks

Data aggregation is a key, yet time-consuming functionality in wireless sensor networks (WSNs). Multi-channel design is a promising technique to alleviate interference as a primary reason for long latency of TDMA aggregation scheduling. Indeed, it provides more potential of parallel transmissions over different frequency channels, thus minimizing time latency. In this paper, we focus on designing a multi-channel minimum latency aggregation scheduling protocol, named MC-MLAS, using a new joint approach for tree construction, channel assignment, and transmission scheduling. To our best knowledge, this is the first work in the literature which combines orthogonal channels and partially overlapping channels to consider the total latency involved in data aggregation. Extensive simulations verify the superiority of MC-MLAS in WSNs.     

A mechanistic approach to evaluate the potential of the debonding distress in asphalt pavements

The debonding distress in asphalt pavement structures is a critical problem that affects the performance of asphalt concrete pavements. It occurs at the layer interface due to the poor bond quality between adjacent asphalt concrete layers and/or when stresses at the layer interface exceed the strengths of the material at the interface. The debonding of the adjacent layers, especially the top surface layer of an asphalt pavement, is a contributing factor to the premature cracking of pavements. Hence, the debonding distress can lead to a reduction in the life of the pavement. This paper presents an analytical and experimental framework to evaluate the potential for debonding at the layer interface of asphalt concrete pavements. Computational analysis was performed to determine the critical stress and strain states in layered asphalt pavements under moving vehicle loads using the Layered ViscoElastic pavement analysis for Critical Distresses (LVECD) computer program developed at North Carolina State University. This computational analysis enables a greater understanding of the critical stress that is involved in debonding and the ways that such stress is affected by pavement design parameters and environmental conditions. In addition, a prediction model was developed that can determine the shear bond strength at the interface of asphalt concrete layers with different tack coat materials at various temperatures, loading rates and normal confining stresses. The systematic and mechanistic framework developed in this study employs the maximum shear ratio concept as a shear failure criterion and provides a tool to evaluate the effects of various loading, environmental and pavement factors on the debonding potential of asphalt pavements. The overall advantages of the mechanistic framework and approach using the LVECD analysis tool will help lead to better understanding of the debonding mechanism, proper selection of the tack coats, and economic benefit in highway pavement maintenance and rehabilitation costs.     

UML-CI: A reference model for profiling critical infrastructure systems

The study of critical infrastructure systems organization and behavior has drawn great attention in the recent years. This is in part due to their great influence on the ordinary life of every citizen. In this paper, we study critical infrastructures’ characteristics and propose a reference model based on the Unified Modeling Language (UML). This reference model attempts to provide suitable means for the task of modeling an infrastructure system through offering five major metamodels. We introduce each of these metamodels and explain how it is possible to integrate them into a unique representation to characterize various aspects of an infrastructure system. Based on the metamodels of UML-CI, infrastructure system knowledge bases can be built to aid the process of infrastructure system modeling, profiling, and management.     

Nano levels detection of beryllium by a novel beryllium PVC-based membrane sensor based on 2,3,5,6,8,9-hexahydro-1,4,7,10-benzotetra oxacyclododecine-12-carbaldehyde-12-(2,4-dinitrophenyl)hy

A novel poly(vinyl chloride)-based 2,3,5,6,8,9-hexahydro-1,4,7,10-benzotetra oxacyclododecine-12-carbaldehyde-12-(2,4-dinitrophenyl)hy (PBC) with sodium tetraphenyl borate (NaTPB) as an anion excluder, benzyl acetate (BA), acetophenon (AP) and o-nitrophenyloctyl ether (NPOE) as plasticizing solvent mediators was prepared and investigated as a beryllium selective sensor. The best performance was observed with the membrane having the PVC–NaTPB–NPOE–PBC composition 30%:3%:62%:5%, which worked well over a very wide concentration range (1.0×10⁻⁷ M to 1.0×10⁻¹ M). The sensor exhibits a Nernstian slope of 29.9 mV per decade of Be²⁺ activity. The detection limit of the sensor is 7.0×10⁻⁸ M (630 ppt). The proposed electrode shows excellent discriminating ability toward Be²⁺ ion with regard to alkali, alkaline earth, transition and heavy metal ions. It was successfully applied to the determination of beryllium in a mineral sample.     

Control of Variation by Reward Probability.

Two bar-press experiments with rats tested the rule that reducing expectation of reward increases the variation from which reward selects. Experiment 1 used a discrete-trial random-interval schedule, with trials signaled by light or sound. One signal always ended with reward; the other signal ended with reward less often. The 2 signals were randomly mixed. Bar-press duration (how long the bar was held down) varied more during the signal with the lower probability of reward. Experiment 2 closely resembled Experiment 1 but used a random-ratio schedule rather than a random-interval schedule. Again, bar-press duration varied more during the signal with the lower probability of reward. The results support the rule--the first well-controlled comparisons to do so. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Preparation and characterization of foamed polyurethane/silicone rubber/graphite nanocomposite as radio frequency wave absorbing material: The role of interfacial compatibilization

A novel method for the preparation of radio frequency (RF) wave absorber polyurethane foam (PU) has been developed by impregnation of PU foam in n-hexane solution of room temperature vulcanizing (RTV) silicone rubber (SR) hybridized with graphite nanosheets (GNs) called doping solution. Extent of the GNs dispersion was optimized by the incorporation of a specific type of bifunctional compatibilizer. Insulator to conductive transition threshold as well as electromagnetic wave absorption characteristics of the fabricated nanocomposites was shown to be dependent upon the compatibilizer functionality. All PU/SR/GN nanocomposites generated from bifunctional compatibilizer exhibited higher electrical conductivity with enhanced permittivity implying enhanced formation of conductive networks by GN platelets. Permittivity of the PU/SR/GN nanocomposite based on bifunctional compatibilizer showed to be higher than uncompatibilized counterpart. Electromagnetic reflection loss behavior of the PU/SR/GN nanocomposites exhibited a non-linear correlation with the electrical conductivity. Although all PU/SR/GN prepared nanocomposites exhibited electromagnetic wave reflection loss behavior, but this revealed to be affected by the GN level as well as the size and dispersion state of the graphite nanosheets.     

Using Fuzzy Cost‐Based FMEA,GRA and Profitability Theory for Minimizing Failures at a Healthcare Diagnosis Service

This paper proposes an integrated approach to identify, evaluate and improve the potential failures in a service setting. This integrated approach combines Fuzzy cost‐based service‐specific FMEA (FCS‐FMEA), Grey Relational Analysis (GRA) and profitability theory for better prioritization of the service failures by considering cost as an important issue and using the profitability theory in a way that the corrective actions costs are taken into account. Considering profitability with FCS‐FMEA and GRA reduces the losses caused by failure occurrence. Besides, a maximization linear mathematical problem is used to select the best mix of failures to be repaired. We apply our approach to an academic example concerning the potential failures diagnosis of the Internal Medicine service of a hospital located in Seoul, Korea. We applied our approach and solved the associated maximization problem by a commercial solver, producing an optimal solution which indicates the most convenient mix of failures to be repaired by considering available budget. Copyright © 2013 John Wiley & Sons, Ltd.     

An energy‐efficient utility‐based distributed data routing scheme for heterogenous sensor networks

A utility‐based distributed data routing algorithm is proposed and evaluated for heterogeneous wireless sensor networks. It is energy efficient and is based on a game‐theoretic heuristic load‐balancing approach. It runs on a hierarchical graph arranged as a tree with parents and children. Sensor nodes are considered heterogeneous in terms of their generated traffic, residual energy and data transmission rate and the bandwidth they provide to their children for communication. The proposed method generates a data routing tree in which child nodes are joined to parent nodes in an energy‐efficient way. The principles of the Stackelberg game, in which parents as leaders and children as followers, are used to support the distributive nature of sensor networks. In this context, parents behave cooperatively and help other parents to adjust their loads, while children act selfishly. Simulation results indicate the proposed method can produce on average more load‐balanced trees, resulting in over 30% longer network lifetime compared with the cumulative algorithm proposed in the literature. Copyright © 2014 John Wiley & Sons, Ltd.     

Application of mesoporous magnetic carbon composite for reactive dyes removal: Process optimization using response surface methodology

Discharging the effluents of textile wastewaters into potable water resources can endanger the ecosystem, due to their reactivity, toxicity, and chemical stability. In this research, the application of powder activated carbon modified with magnetite nanoparticles (PAC-MNPs) as an adsorbent for removal of reactive dyes (Reactive black 5 (RB5) and reactive red 120 (RR120)) was studied in a batch system. The adsorption performance was evaluated as a function of temperature, contact time and different adsorbent and adsorbate concentrations. The levels of factors were statistically optimized using Box-Behnken Design (BBD) from the response surface methodology (RSM) to maximize the efficiency of the system. The adsorption process of both dyes was fit with the pseudo-second order kinetic and Langmuir isotherm models. The identified optimum conditions of adsorption were 38.7 °C, 46.3 min, 0.8 g/L and 102 mg/L for temperature, contact time, adsorbent dose, and initial dyes concentration, respectively. According to the Langmuir isotherm, the maximum sorption capacities of 175.4 and 172.4 mg/g were obtained for RB5 and RR120, respectively. Thermodynamics studies indicated that the adsorption process of the reactive dyes was spontaneous, feasible, and endothermic. After five cycles, the adsorption efficiency was around 84 and 83% for RB5 and RR120, respectively. A high value of desorption was achieved, suggesting that the PAC-MNPs have a good potential in regeneration and reusability, and also can be effectively utilized in industrial applications. PAC-MNPs also show a good anti-interference potential for removal of reactive dyes in dye-industry wastewaters.