Generating Z‐number based on OWA weights using maximum entropy

In the application of Z‐number, how to generate Z‐number is a significant and open issue. In this paper, we proposed a method of generating Z‐number based on the OWA weights using maximum entropy considering the attitude (preference) of the decision maker. Some numerical examples are used to illustrate the effectiveness of the proposed method. Results show that the attitude (preference) of the decision maker can give an optimal possibility distribution of the reliability for Z‐number using maximum entropy.     

Optimal multi-dimensional vector bin packing using simulated evolution

The use of the evolutionary heuristic simulated evolution for the optimization of the multi-dimensional vector bin packing problem, which is encountered in several industrial applications, is described. These applications range from production planning and steel fabrication to assignment of virtual machines (VMs) onto physical hosts at cloud-based data centers. The dimensions of VMs can include demands of CPU, memory, bandwidth, disk space etc. The generalized goodness functions that aid traversing the search space in an intelligent manner are designed to cater to the multidimensional nature of items (VMs). The efficiency of heuristics is tested by considering phase transition in the generation of difficult test cases. The quality of the heuristics is judged by determining how close the solution is to the estimated lower bound. A new implementation of a tighter lower bound is proposed. Experiments show that superior quality results are obtained by employing the proposed strategy.     

Direction of arrival estimation using adaptive directional time-frequency distributions

Time-frequency distributions (TFDs) allow direction of arrival (DOA) estimation algorithms to be used in scenarios when the total number of sources are more than the number of sensors. The performance of such time–frequency (t–f) based DOA estimation algorithms depends on the resolution of the underlying TFD as a higher resolution TFD leads to better separation of sources in the t–f domain. This paper presents a novel DOA estimation algorithm that uses the adaptive directional t–f distribution (ADTFD) for the analysis of close signal components. The ADTFD optimizes the direction of kernel at each point in the t–f domain to obtain a clear t–f representation, which is then exploited for DOA estimation. Moreover, the proposed methodology can also be applied for DOA estimation of sparse signals. Experimental results indicate that the proposed DOA algorithm based on the ADTFD outperforms other fixed and adaptive kernel based DOA algorithms.     

Metal concentrations in a shallow groundwater aquifer underneath petrochemical complex

Duplicate groundwater samples were collected from 104 monitoring wells (piezometers) from shallow aquifers underneath an industrial city in the Eastern Province of Saudi Arabia. Concentrations of Al, As, Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, Pb, Ti, V, Zn, Ca, Mg, K, Na, Cl, SO₄, alkalinity, salinity, total dissolved salts, and pH were determined in these samples. Analysis of variance showed significantly (p < 0.05) wide variations in the concentrations of the above parameters. The contour maps of metal concentrations indicated that these variations were related to important landmarks in the study area. The results of correlation analyses suggest that geographical as well as chemical factors may influence metal distribution in the groundwater samples. To investigate the geographical effects, the analytical data were normalized (element/Cl ratios were calculated) for chemical variability. As expected, contour mapping of the ratio data of element/Cl of Na, Ca, Mg, K, SO₄, alkalinity, salinity, total dissolved salts, and Sr vary in a relatively small range and did not show a particular geographical trend. The groundwater sample from the industrial-dust area contained higher ratios between concentrations of Cl and Co, Cr, Cu, Fe, Mn, Mo, Ni, Pb, and Zn. These observations clearly suggest an extraneous contamination source, probably industrial dust, in the area. Another geographical area where metal (As, Cd, Cu, Mo, Ni, Ti,and V)/Cl ratios were found to be large was in the vicinity of an oil-refinery. Groundwater samples collected from the vicinity of a fertilizer plant and green-belt area contained relatively higher ratios of Al, Cd, Cr, Co, and Ni. The results of this study suggest that leachate from the industrial dust, leakage from the oil refinery and fertilizer plant, and drainage of irrigation water are some of the important pollution sources in the industrial city.     

A fuzzy Bayesian belief network for safety assessment of oil and gas pipelines

Safety assessment of oil and gas (O&G) pipelines is necessary to prevent unwanted events that may cause catastrophic accidents and heavy financial losses. This study develops a safety assessment model for O&G pipeline failure by incorporating fuzzy logic into Bayesian belief network. Proposed fuzzy Bayesian belief network (FBBN) model explicitly represents dependencies of events, updating probabilities and representation of uncertain knowledge (such as randomness, vagueness and ignorance). The study highlights the utility of FBBN in safety analysis of O&G pipeline because of its flexible structure, allowing it to fit a wide variety of accident scenarios. The sensitivity analysis of the proposed model indicates that construction defect, overload, mechanical damage, bad installation and quality of worker are the most significant causes for the O&G pipeline failures. The research results can help owners of transmission and distribution pipeline companies and professionals to prepare preventive safety measures and allocate proper resources.     

Condition Assessment of Buried Pipes Using Hierarchical Evidential Reasoning Model

Effective inspection and monitoring practices for the condition assessment of pipes ensure better decision(s) for repair or replacement before they fail. Pipe deterioration is a physical manifestation of the aging process in which many factors can contribute to structural failure. Various technologies/ techniques have been developed during the last few years to inspect/monitor piping systems, but how to intelligently interpret the collected data remains a challenge. In this paper, a new approach based on hierarchical evidential reasoning is proposed. This approach uses Dempster–Shafer (D-S) theory to make inferences for condition assessment of buried pipes. A hierarchical evidential reasoning model can help combine different distress indicators (bodies of evidence) at different hierarchical levels using D-S rule of combination. The proposed hierarchical evidential reasoning method is demonstrated with an example of condition assessment for a large diameter pipe. Information from multiple sources is fused to obtain a more reliable assessment of pipe deterioration.     

Synergistic antifungal effects of thyme essential oil and Lactobacillus plantarum cell‐free supernatant against Penicillium spp. and in situ effects

This study evaluates the synergistic antifungal effects between thyme essential oils and Lactobacillus plantarum cell‐free supernatant (LCFS) against Penicillium spp. and in situ antifungal activity in rice grains. Thyme essential oil and LCFS showed remarkable antifungal activities against Penicillium spp. with the minimum inhibitory concentration (MIC) of 40 and 80 µL/mL, respectively. The analysis of fractional inhibitory concentration (FIC) index showed the antifungal synergism between thyme essential oil and LCFS against Penicillium spp. with FIC index of 0.5. This synergism also resulted in fourfold reduction in their MICs when applied in combination. The antifungal modes of action were characterized by observing the changes in cell membrane permeability and degradation of fungal cell wall. The combination of thyme essential oil and LCFS (2 × MIC of each) showed remarkable in situ antifungal effect and completely inhibit the growth of Penicillium in rice seeds. The results suggested the possible applications of the observed synergism on actual crops.

Practical applications

Essential oils are used as preservative in food industry and high concentration of essential oil is associated with negative organoleptic characteristics. This study presented a novel approach for synergistic antifungal effects by using the combination of thyme essential oil and Lactobacillus plantarum cell‐free supernatant (LCFS) against Penicillium spp. and systematic evaluation of the antifungal effect by using fractional inhibitory concentration (FIC) index method. This approach will be a role model for future research on synergism and overcome the major drawbacks of using live bacteria and the negative effects arising from antimicrobial activities of essential oils.     

Inspection and maintenance of oil & gas pipelines: a review of policies

Oil and gas (O&G) pipelines are expensive assets that cross through both the ecologically sensitive and densely populated urban areas. The pipeline failure may have potentially significant consequences for both the natural and human environments. In order to maintain the integrity of O&G pipelines, inspection and maintenance processes should be governed by efficient policies. The objective of this paper is to conduct a state-of-the-art review of maintenance policies of O&G pipelines to investigate their advantages, limitations, and associated implementation issues. Maintenance policies can be categorised into corrective, preventive, predictive and proactive. Corrective maintenance policies (1940s) were based on the ‘repair when broke’ philosophy. Economic considerations shifted practice towards preventive maintenance (1970s to 1990s); later with improved inspection techniques and environmental regulations, predictive and proactive or risk-based maintenance (RBM) policies were developed. This review explicates different methodologies for RBM and related issues, e.g. uncertainties and variability, conservative assumptions, etc. Uncertainties associated with investigation and prediction of defects have been more frequently reported in the literature so far. Moreover, existing studies primarily focused on reducing the likelihood and cost of failure, whereas consideration of environmental factors in overall risk has been a relatively less addressed issue.     

Quality of Processed Cheddar Cheese as a Function of Emulsifying Salt Replaced by κ-Carrageenan

Hydrocolloids act as stabilizer and thickening agents, thus able to replace emulsifying salts. The present study was planned to use к-carrageenan in the production of processed cheddar cheese and to explore its effect on physico-chemical and textural properties of processed cheddar cheeses. Different concentration of ?-carrageenan were used with gradual decrease in salt contents along with natural cheese, fat, and water to prepare processed cheddar cheese. The prepared samples were analyzed for physico-chemical and sensory attributes at storage interval of 45 days during and after 90 days. With the increase in hydrocolloid concentration, stiffer product was obtained and meltability of the samples decreased than control. Processed cheddar cheese samples having 0.15% к-carrageenan with 2% emulsifying salt (1.34% sodium citrate and 0.66% disodium phosphates) were found more acceptable in terms of physico-chemical and sensory attributes, but all sensory attributes got fewer score with the passage of storage time.