Abstracts:Pipes with in poor condition in water distribution systems cause significant operational problems and water losses. Therefore, it is important to evaluate the technical performance of these pipes. In this study, the evaluation of technical performance of the individual water pipes by Analytic Hierarchy Process (AHP) according to various main-factors such physical, environmental and operational and sub-factors is aimed. The weight coefficients for the physical, environmental and operational main factors were calculated as, 0.43, 0.14 and 0.43, respectively. Physical Factor Score (PFS), Environmental Factor Score (EFS) and Operational Factor Score (EFS) were calculated to define the technical evaluation score of the water pipes. Finally, the Performance Evaluation Score (PES) was calculated using the weights and scores of the PFS, EFS and OFS and applied for 17 individual water pipes selected for testing the technical performance. It was determined that the structural condition and performance of ACP and PVC pipes was bad and the risk of damage was high. It is considered that the AHP model developed may be an important tool in the technical evaluation of pipes for water supply utilities.

Abstracts:Super-resolution is designed to construct a high-resolution version of a low-resolution for more information. Super-resolution can help doctors to get a more accurate diagnosis. In this paper, we propose a novel super-resolution method utilizing minimum error regression selection. In the training step, we partition the patches into multiple clusters through jointly learning multiple regression models. Then we train a random forest model based on the patches of multiple clusters. During the reconstruction step, we use trained random forest model to select the most suitable regression model for the reconstruction of each low-resolution patch. Several medical images are applied to test the proposed method. We compare both the objective parameters and the visual effect to other state-of-the-art example-based methods. Experiment results show that the proposed method has better performance.