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This study assessed the vulnerability of groundwater resources to the failure of the urban fuel distribution network under an earthquake. A case study of the Tehran, Iran, gas distribution network and the Tehran–Karaj Plain aquifer was conducted. To assess the seismic vulnerability of buried fuel pipelines in Tehran based on the fuel distribution network components, three possible earthquake scenarios were studied. To assess damage to the pipeline, a comprehensive model was developed using machine learning (ML). This model can assess and predict damage to a fuel pipeline and its type (i.e., leakage or full breakage). Moreover, aquifer contamination was assessed using the DRASTIC model. It was found that the ML-based pipeline seismic vulnerability assessment model had good performance in predicting seismic damage to the fuel distribution network, with a RMS error (RMSE) and a correlation coefficient (R) of 0.004 and 0.99, respectively. The results showed that the presented model had an acceptable efficiency in assessing the probability of seismic vulnerability of the buried pipeline and analyzing the pollution of the aquifer based on different earthquake scenarios. The developed groundwater seismic vulnerability assessment model can be used for further analysis in future research. Practical Applications: Earthquakes are one of the most important natural disasters, and have caused widespread financial, human, and environmental losses in different regions of the world, especially in seismic areas. The existence of faults and the possible deterioration of buried pipes makes earthquake crisis and its serious damage to humans and the environment more severe. One of the most important threats in this situation is the contamination of underground water with hydrocarbon substances due to leakage from the fuel transmission network. In this research, to evaluate the pollution of the aquifer due to the damage to the fuel transmission network, we developed a model using the machine learning method to analyze the vulnerability of the buried pipeline. The DRASTIC model also was used to evaluate aquifer pollution. To evaluate the presented model, the fuel transmission network and aquifer of Tehran, Iran, were studied. The results indicated acceptable performance of the proposed model for assessing the seismic vulnerability of groundwater. The presented model can be used for other areas. [ABSTRACT FROM AUTHOR]

The client’s choice of contractor at the project prequalification stage is critical as the selected contractor is responsible for the overall coordination of a project. Although a wide variety of criteria have been employed to develop models for contractor selection, one critical component of their capability – management performance – has historically been among the least addressed but, we argue, most critical elements in a useful selection model. Even in the cases when management performance is considered, it has typically focused only on objective outcome criteria of limited predictive power, such as contractor time and cost performance. This paper reports on the results of a study to develop a comprehensive contractor evaluation model that directly addresses the contractor management capabilities and practices as a critical additional element at the prequalification stage. Using a multi-step research process, including extensive literature review, analysis and synthesis of critical contractor management performance factors, development of an analytic network project (ANP) model, and subsequent case study and field validation, we identified a robust model that enhances the decision support tools for the client organization by creating databases for comparing multiple contractors with respect to management practices. In addition, the evaluation of this prequalification criterion permits the contractors to focus on their efforts to address the critical management practices to improve their project performance. [ABSTRACT FROM AUTHOR]

Successful performance measurement criteria cannot be limited to meeting just the three traditional criteria. Satisfaction is a subjective and critical measurement for the stakeholder performance, but it has rarely been used as a criterion for the performance measurement of project stakeholders. The purpose of this paper is to establish the client and customer satisfaction criteria as the two key stakeholders in construction project for the issue of performance measurement based on the reviewed data. The methodology of this study is based on comprehensive literature review of performance measurements for client and customer whereby the data were analyzed, using the metrics which are the aggregate number of each customer and client-satisfaction criteria occurring in previous study. From the metric analysis, the common factors for customer and client satisfaction were ranked. From the analysis, it can be concluded that expectation and perception are the two common critical satisfaction criteria for client and customer that must be considered where the satisfaction is required. [ABSTRACT FROM AUTHOR]

Background and Objective Diagnosis as the initial step of medical practice, is one of the most important parts of complicated clinical decision making which is usually accompanied with the degree of ambiguity and uncertainty. Since uncertainty is the inseparable nature of medicine, fuzzy logic methods have been used as one of the best methods to decrease this ambiguity. Recently, several kinds of literature have been published related to fuzzy logic methods in a wide range of medical aspects in terms of diagnosis. However, in this context there are a few review articles that have been published which belong to almost ten years ago. Hence, we conducted a systematic review to determine the contribution of utilizing fuzzy logic methods in disease diagnosis in different medical practices. Methods Eight scientific databases are selected as an appropriate database and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method was employed as the basis method for conducting this systematic and meta-analysis review. Regarding the main objective of this research, some inclusion and exclusion criteria were considered to limit our investigation. To achieve a structured meta-analysis, all eligible articles were classified based on authors, publication year, journals or conferences, applied fuzzy methods, main objectives of the research, problems and research gaps, tools utilized to model the fuzzy system, medical disciplines, sample sizes, the inputs and outputs of the system, findings, results and finally the impact of applied fuzzy methods to improve diagnosis. Then, we analyzed the results obtained from these classifications to indicate the effect of fuzzy methods in decreasing the complexity of diagnosis. Results Consequently, the result of this study approved the effectiveness of applying different fuzzy methods in diseases diagnosis process, presenting new insights for researchers about what kind of diseases which have been more focused. This will help to determine the diagnostic aspects of medical disciplines that are being neglected. Conclusions Overall, this systematic review provides an appropriate platform for further research by identifying the research needs in the domain of disease diagnosis. [ABSTRACT FROM AUTHOR]