The development of electronic banking services, in order to facilitate the monetary transaction viz-a-viz banking system, requires the scientific and efficient management. The Automated Teller Machines (ATMs) which are mostly deployed in various banks branches, and are subject to direct supervision of branches authorities, will not get cash OPTIMALly injected. This mode of liquidity management, of ATMs will not only distort the brand name of banking system in a psedue competitive market, but it may lead to inefficient management of liquidity through the cash INJECTION more than the daily need of these machines. Hence in this paper an attempt is made to predict the OPTIMAL INJECTION of cash to ATMs of Sepah Bank by using the daily time series data of withdrawing money from them. For this purpose, we applied two econometric methods of ARMA modeling techniques. The results prima facie indicate that, despite existence of certain constraints on statistical data due to non operation of ATMs, impairment of Shetab Network, and delayed feeding of cash, the lower range of prediction error, is about 1%. Thus, we conclude that, to optimize the cash INJECTION process of ATMs, besides considering the human resources and required security measures, the application of above study is recommended.

In this paper, a novel risk-based, two-objective (technical and economical) OPTIMAL reactive power dispatch method in a wind-integrated power system is proposed which is more consistent with operational criteria.  The technical objective includes the minimization of the new voltage instability risk index. The economical objective includes cost minimization of reactive power generation and active power loss. The proposed voltage instability risk employs a hybrid possibilistic (Delphi-Fuzzy)-probabilistic approach that takes into consideration the operator’s experience, the wind speed and demand forecast uncertainties when quantifying the risk index. The decision variables are the reactive power resources of the system. To solve the problem, the modified multi-objective particle swarm optimization algorithm with sine and cosine acceleration coefficients is utilized. The method is implemented on the modified IEEE 30-bus system. The proposed method is compared with those in the previously published literature, and the results confirm that the proposed risk index is better at estimating the voltage instability risk of the system, especially in cases with severe impact and low probability. In addition, according to the simulation results compared to typical security-based planning, the proposed risk-based planning may increase the security and economy of the system due to better utilization of system resources.

Introduction: In different studies worldwide, gender ratios derived from ICSI (Assisted reproductive techniques) have been reported differently. Objective: Evaluation of neonatal gender in ICSI women referred to Mehr Infertility Research Center of Rasht. Materials and Methods: In this descriptive-analytical study, the cases of infertile women referred to Mehr Infertility Research Center in Rasht for ICSI were examined to determine the sex ratio of the neonates. Data were analyzed using SPSS 21 and descriptive and an alytical (Chi-square and independent t) tests. Results: The results showed that 52% of single-born neonates, 60% of multiple pregnancies (single sex) and 52. 5% of multiple pregnancy (two sexes) were male. Conclusion: The ratio of male in single and multiple pregnancies in ICSI was higher than female.

In this paper the problem of OPTIMAL multiple-burn INJECTION of a satellite into geostationary orbit using an upper stage with a limited thrust and restart capability, and comparison with sub-OPTIMAL case is considered. The goal is finding thrust vector angle, times of the engine firings and OPTIMAL duration of active phases of the upper stage so as to minimize fuel consumption and to meet the desired boundary conditions. The contribution of this research is developing an accurate and rapid convergence algorithm for solving multiple-burn trajectory for satellite INJECTION into geostationary orbit. To solve the multipoint boundary value problem, an improved indirect shooting method with high performance and modified Newton’s methodis presented and used for OPTIMAL solution. Moreover, the novel method presented for multi burn problem not only has very good accuracy, but also, it converges very fast to the desired end conditions. Various flight sequences with multiple burns are considered and the OPTIMAL trajectory with minimum fuel consumption criteria, for each flight sequence is derived. The verification and validation of the proposed algorithm is made via comparison with references. Finally, the results of OPTIMAL solutions are compared with the results of sub-OPTIMAL solution whose thrust direction is aligned to the velocity vector direction.

Objective Flexible Manufacturing Systems (FMS) are integrated workstations that utilize computer-controlled equipment components for production. These systems are managed by a central computer, which significantly enhances the efficiency and productivity of the production process. Accordingly, a case study is conducted on an FMS electrical manufacturing system with complex manufacturing processes, where automation on the production line is crucial. Selecting the OPTIMAL number of advanced equipment is a challenging and vital issue for managers aiming to boost productivity and efficiently fulfill customer orders. It is a hard-to-change model, and replacing equipment incurs substantial costs.   Methods This study employs the two-stage D-OPTIMAL method to optimize the combination of FMS elements and equipment. The D-OPTIMAL response level input is derived from discrete-event simulation results. Depending on the conditions, various FMS equipment is allocated to each process. Each simulation result for element combinations serves as input for the experimental design. Additionally, the response level (y) of experiments from various FMS indexes is calculated using a weighting method. To reduce the number of experiments and increase data accuracy in a case study with hard-to-change parameters, all combinations are categorized based on the number of automated and manual equipment. The two stages of the D-OPTIMAL design are defined as follows: In the first stage, all combinations within these categories are investigated. In the second stage, the optimized combination from the first stage is analyzed to determine the best configuration. Experiments in the top category from the first stage are simulated and further evaluated in the second stage of the D-OPTIMAL method.   Results In the first phase, all advanced production equipment and FMS elements were considered. After selecting the best-calculated “y” value, which was 147,133.09 in this category, another D-OPTIMAL design was optimized in the second phase to determine the best combination. This combination yielded a “y” value of 151,317.88, representing an improvement over the best category in the first phase of the D-OPTIMAL design. Consequently, the optimized combination from the first phase was further refined. The results from the developed D-OPTIMAL method and the second phase indicate that the OPTIMAL combination of equipment involves using automated and FMS equipment for approximately 92.8% of the total components. Finally, a list of recommended FMS equipment is provided, and its productivity is compared with the productivity at the current level and a higher degree of automation for this production line.   Conclusion In summary, the results of the experimental design show that using advanced production systems does not necessarily improve system efficiency, and determining OPTIMAL combinations requires accurate calculations.

In order to study the spatial structure of oriental beech (Fagus orientalis Lipsky) stand at OPTIMAL stage, this research was carried out in the Caspian forests of Iran. The studied site consisted of a natural stand located at Sangdeh district (Mers-e-se) with three hectare area. It is located between 1900 and1950 m.a.s.l. Six sample plots each with 0.36 ha area, were systematically selected and all trees (1244 stem) within the plots were measured and recorded. Using increment borer, the mean age of the stand was estimated as 137 years; the age difference of trees was 40 years. Results showed that the stand has a closed canopy cover and distribution of stem number per diameter class was more or less homogenous (Bell shape) with a semi even-aged structure. Using Ripley's K function, the distribution of trees within the stand was random.

Regarding the vast extension of information technology, communication systems and electronic instrumentation, the employment of phasor measurement units (PMUs) has been proposed for power system observability and wide-area protection. Nevertheless, the construction of communication channels and installation of PMU equipment are highly expensive and require optimizations. In this paper, first the constraints are proposed for the OPTIMAL PMU placement problem considering fault state observability of power system in presence of zero bus INJECTION, and afterwards the mathematical formulation is presented. For more realistic modeling of power network, line outages have been considered. Finally, the proposed method is implemented on standard IEEE 9, 14, and 30 bus networks, and the enhanced results are represented.

Background: Lumbar back pain is a common disease, which reduces life quality. Caudal epidural steroid INJECTION (CESI) is frequentlypreferred to relieve lumbar back pain. However, various major complications can be observed due to CESI. A new techniqueof needle angle should be improved to prevent complications such as intraosseous, intrathecal or intravascular INJECTION duringCESI. Objectives: Caudal epidural steroid INJECTION is one of the methods frequently used to treat chronic lumbar back pain. The currentstudy aimed at examining the anatomy of the sacral hiatus and determining the OPTIMAL angle of the needle for CESI. Methods: The current clinical trial was performed in Diyarbakı r Selahaddin Eyyü bi State Hospital from January to June in 2017. Thestudy included 150 adult patients (first group = 92 males (%61. 3), second group = 58 females (%38. 7) aged 18-78 years applied to theAlgology Polyclinic with ASA-PS classes I and II (the American Society of Anesthesiologists (ASA) physical status classification system). Measurements were taken during the CESI applied under ultrasonography (USG) guidance of the intercornual distance, the sacralspace, and the OPTIMAL needle entry angle. Results: The intercornual distance was significantly higher in group one (mean standard deviation (SD): 16. 6 2. 04) than grouptwo (mean SD: 15. 8 2. 51) (P < 0. 049). No difference was observed between group one (mean SD: 4. 49 0. 75) and group two(mean SD: 4. 45 0. 88) with respect to sacral space (P > 0. 79). The most appropriate entry angle for the needle in the applicationof CESI was mean 71. 04° in the whole patient group, as 71. 9° in group one and 69. 7° in group two. There was no significant differencebetween the genders in terms of themeanOPTIMAL angle (P> 0. 091). Also, nosignificant difference was observedamongthe patientsin terms of the demographic data (P > 0. 05). Conclusions: The results of the current study revealed that the OPTIMAL needle angle for CESI applied under USG guidance was71. 04° , different from traditional method and the INJECTION procedure could be safely made directly to the epidural space withoutchanging the angle after entry of the needle to the epidural space.

Production strategy from a hydrocarbon reservoir plays an important role in OPTIMAL field development in the sense of maximizing oil recovery and economic profits. To this end, self-adapting optimization algorithms are necessary due to the great number of variables and the excessive time required for exhaustive simulation runs. Thus, this paper utilizes genetic algorithm (GA), and the objective function is defined as net present value (NPV). After developing a suitable program code and coupling it with a commercial simulator, the accuracy of the code was ensured using a synthetic reservoir. Afterward, the program was applied to an Iranian southwest oil reservoir in order to attain the optimum scenario for primary and secondary production. Different hybrid water/gas INJECTION scenarios were studied, and the type of wells, the number of wells, well coordination/location, and the flow rate (production/INJECTION) of each well were optimized. The results from these scenarios were compared, and simultaneous water and gas (SWAG) INJECTION was found to have the highest overall profit representing an NPV of about 28. 1 billion dollars. The application of automated optimization procedures gives rise to the possibility of including additional decision variables with less time consumption, and thus pushing the scopes of optimization projects even further.