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Nowadays, the issue of service quality for service-provider organizations specifically banks is of considerable importance. The service-provider organizations (specifically governmental banks) are aware from the necessity of getting satisfaction of customer and assessing quality of services. In this research, we evaluate and analyze the gap of expected and current service quality. In fact, the gap between customer´s expectations of bank services and customers perceptions is assessed based on the hierarchical service quality model (HSQM), which has been introduced by Brady and Cronin in 2001. To do this, customers of Keshavarzi Bank are given as statistical population and a sample with 384 people is extracted from Tehran Keshavarzi Banks using Krejcie-Morgan Table and Cochran formula. The results show that just in two dimensions of HSQM namely «waiting time» and «valence», there is no significant difference between expectations and perceptions, but there are gaps among expectations and perceptions in the other dimensions.

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Comparison of Back stepping method optimized via particle swarm optimization algorithm and LQR method for hovering control of a quadrotor is presented in this paper. Quadrotor is not a stable dynamical system and development of high performance controllers for it is important. First the dynamic model of a quadrotor is introduced and state-space equations are presented in order to simulate the dynamic model. Then two Back stepping and LQR controllers are designed to control Euler angles and height of the quadrotor. In order to optimize back stepping controller, its parameters are determined using particle swarm optimization algorithm to minimize cost function considered for LQR controller. Also commands to the motors are calculated and plotted to show the feasibility of the controller. To obtain better comparison, the cost function is calculated for different weighting matrices of Q and R for two controllers and the results are compared. The results show that Back stepping controller has more ability to minimize the cost function in comparison to LQR and the cost function in Back stepping has less values for several choices of weighting matrices.

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Adsorption simulation of vancomycin antibiotic is done using molecular dynamics. The simulation results show the adsorption behavior of vancomycin on a functionalized biosensor. Regarding the importance of vancomycin, its molecular function is simulated using multiscale discipline. Adsorption to a single assembly monolayer is considered according to vancomycin’s in-vivo function. A selected biosensor is a non-symmetrically functionalized microcantilever which undergoes deformation as a result of changes in surface tension regarding functionalized surface. Multiscale simulations implemented to calculate microcantilever deformation. Molecular models in a vacuum and aquatic media are taken into account. Energy parameters related to surface tension is studied versus the distance of target molecules to the surface of the biosensor. To calculate the distance between receptor molecules in single assembly monolayer, an algorithm is proposed based on experimental results.
 

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In recent decades, due to the high cost of running a water supply network, designers have been trying to design networks with the least cost and maximum reliability. Networks that are able to provide good services in the face of demand changes or failure of the pipeline. Several indexes for reliability measurements were introduced and used as one of the objective functions along with cost in water distribution systems design problem. One of the issues that has been highlighted in recent years is which of these indicators are more successful in measuring the reliability of a water supply network. In this study, six famous reliability indicator entitled Minimum surplus head (MSH), total surplus head (TSH), resilience index (RI), network resilience index (NRI) and modified resilience index (MRI), entropy reliability indicator (ERI) and a new presented reliability indicator entitled Ratio of surplus head (MSH) described and used as one of the objective functions of a water distribution system design optimization problem. For this purpose, a multi-objective differential evolution algorithm has been developed in Matlab software and linked to the Epanet as the hydraulic solver. The generated algorithm applied on two different sample networks with different nature (gravitational feeding and feeding with pumping stations). To analysis of real hydraulic and mechanical reliability of obtained networks in optimization processes, a large number of abnormal operating conditions such as water demand uncertainty or pipes burst scenarios have been generated and applied on obtained Pareto Fronts of each optimization process. Then, the percentage of scenarios that each network could not satisfy the design’s constraints or failed in response to them has been calculated. The over demand’s scenarios were sampled using the general normal distribution method. The percentage of scenarios that each answer (water network in Pareto Front) cannot satisfy the design constraint has been measured and called Hydraulic Failure Percentage (HFP). Also, for modeling the abnormal mechanical conditions, lot of scenarios were produced with broken pipes. In each of these scenarios, there is a possibility of one to ten different pipes break. The locations of burst pipes are selected randomly. The percentage of scenarios that each case cannot satisfy the design constraint has been measured and called Mechanical Failure Percentage (MFP). These scenarios would remain constant for all of members of Pareto Fronts. The lower value of HFP and MFP demonstrate the greater ability of the network to deal with changes in nodal demand and the pipe bursts respectively. For deeper analysis, the conditions of failing (Not satisfying the constraints) divides into three sub-state as flowing: State A: Pressure of all nodes is more than the minimum acceptable pressure in all time. State B: Pressure of all nodes is more than 95% of the minimum acceptable pressure in all time. State C: Pressure of 95% of nodes is more than the minimum acceptable pressure in all time. The results of calculations summarized and have been shown in the diagrams. Results show that MSH and RI are the best indicators for optimal design of water supply networks without pumping station and include it.

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Given the varying water demand for various hours of the day from different seasons, the pressure of the water distribution network (WDN) will vary at different times. In the event of a decrease in demand, the network pressure increases, and the excess pressure leads to increase the leakage from old connections and small fractures. One of the ways to reduce leakage is the network pressure management and reduce excess pressure, which it can be achieved by the pressure reducing valves.‏ But the question is, how many pressure reducing valves and at which points of the water network should be installed. In the first part of this study, the optimal location of the pressure reducing valves (PRV's) was found by the combination of the binary genetic optimization algorithm (GA) and real differential evolution (DE) optimization algorithm. For this purpose, the GA proposes the potential locations (pipes) for the valve installation to the DE algorithm, and it attempts to eliminate surplus head in the WDN by making changes in the Hazen-William coefficient of proposed pipes and creating a head loss on the pipes. These changes should be in such a way that the WDN's constraints like the minimum allowable pressure to be respected. The related hybrid algorithm was coded in MATLAB software and connected to the Epanet software as a hydraulic solver. After determining the hydraulic model of the water network and the number of PRVs by the designer, the proposed code determines the optimal installation location of the PRVs in order to the reduction of network background leakage. In the next part of the study, after determining the optimal location of the PRVs, the optimal set-point of each PRVs has been determined. To this end, a single objective differential evolution algorithm is used. The design variable of the optimization algorithm is the outlet pressure of the installed PRVs and the permissible pressure ratio on both sides of PRVs considered as a new network constraint alongside the minimum allowable pressure. The objective function of this optimization problem is minimizing of WDN's background leakage. After validating of presented codes, they applied on a local WDN in the north of IRAN, Guilan, entitled Mehr Water Network. The covered area of this network is 144 acres and its daily average demand is 366 m3 per hour. The altitude difference of Mehr WDS is about 4 meters and it has 371 pipes with the length of 33 kilometers, 366 junctions, one reservoir and a pump station with 3 pumps. Results show that installing two pressure reducing valves in determined locations and control them with DE optimization algorithm can reduce the surplus head and background water leakage from 21.9% to 12.3% (about 41.3%) On a full day. It is noteworthy that this method can be used in Supervisory control and data acquisition (SCADA) in order to pressure management of WDNs and leakage reduction. A calibrated hydraulic model of WDN, current state of valves and pumps and demand multiplier (obtained from installed flow meters or estimated demand profile) are required as the input of the optimization code to determine the optimum output pressure (set-point) of PRVs in SCADA telecontrol system.