Global development in terms of increased attention to environmental protection and the finite nature of fossil resources have accelerated the use of renewable energies. Renewable energy portfolio standard (RPS), is a government policy to promote the use of renewable energy in the energy consumption basket.  The RPS stipulates the minimum amount of renewable energy that each electricity supplier should produce.  This policy has been widely studied in different countries, but so far no such studies have been undertaken in Iran. This study introduces the experience of countries that have been successful in their RPS policies.  We then use linear programming techniques to study an RPS policy that requires regional power supply companies to produce at least 10 percent of their electricity from renewable energy sources. We focus on identifying the optimal combination of different renewable energy sources to meet the RPS.  The results indicate the maximum production of electricity from renewable sources is about 13/65559 TWh.  The optimal ratio of each renewable energy source is respectively 4.29, 9.19, 8.5, 30.9, 19.337 and 30.34 percent for solar energy, biomass, geothermal, wind, hydroelectric and tidal energy.

In this paper, a dynamical model-based SMC (Sliding Mode Control) is proposed for trajectory tracking of a 3-RPS (Revolute, Prismatic, Spherical) parallel manipulator. With ignoring small inertial effects of all legs and joints compared with those of the end-effector of 3-RPS, the dynamical model of the manipulator is developed based on Lagrange method. By removing the unknown Lagrange multipliers, the distribution matrix of control input vector disappears from the dynamical equations. Therefore, the calculation of the aforementioned matrix is not required for modeling the manipulator. It in trun results in decreased mathematical manipulation and low computational burden. As a robust nonlinear control technique, a SMC system is designed for the tracking of the 3-RPS manipulator. According to Lyapunov’s direct method, the asymptotic stability and the convergence of 3-RPS manipulator to the desired reference trajectories are proved. Based on computer simulations, the robust performance of the proposed SMC system is evaluated with respect to FL (feedback linearization) method. The proposed model and control algorithms can be extended to different kinds of holonomic and non-holonomic constrained parallel manipulators.

In this paper, quadratic convex relaxation (QCR) is used to relax AC optimal power flow (AC-OPF) used for reactive power scheduling (RPS) of the power system. The objective function is system active power loss minimization to optimally determine the tap position of tap-changers, the reactive power output of generating units, synchronous condensers, shunt capacitor banks, and reactors. The nonlinear and non-convex terms due to trigonometric functions cause the problem to be non-convex which results in trapping in local minimum or even not converging in large size power systems. Therefore, in this paper, the nonlinear terms and trigonometric function are relaxed by linear and quadratic functions. Furthermore, the product of two variables and multi-variables are relaxed by McCormick bilinear and multi-linear expressions, converting the AC-OPF of RPS to quadratic constraint programming (QCP) optimization problem. The proposed RPS method is studied based on IEEE RTS 24-bus test system. The results show the accuracy of the proposed (QCR) method to relax the AC-OPF optimization problem of RPS.

To study the mechanical and thermal parameters effective on quality and quantity of olive oil towards an extraction of highly pure oil, the velocity in rps of crushing rollers, at two levels of 6 and 12 (rps) along with the temperature of the mixing unit at three levels of 30, 45 and 60°C were taken into account. Data, obtaind through a factorial experiment of Randomized Complete Block Design (RCBD) were analytically evaluated and compared. A comparison of means as based on Duncan Multirange test was indicative of the fact that: acid and peroxide level of oil increases with an incrase in temperature at the mixing unit, meaning a decrease in the quality of olive oil. Increase in temperature of mixing unit also leads to an increase in moisture content of pumice leading to a decrease in the quantity of oil extracted. An increase in temperature of the mixing unit from 30 to 45°c was followed by an increase in oil content of pumice and leading to an increase in extracted oil. A further increase in temperature of the mixing unit from 45 to 60°C did increase oil content in pumice, but this increase was accompanied by a decrease in total quantity of oil extracted. The least acidity figure was obtained for a roller crusher speed of 12 rps at 30°C. As for peroxide content to be the least there were no significant differences observed among the treatments of 12×30, 12×60 and 6 (rps)×45°C, but the least peroxide content was observed for the treatment 12 rps × 30°C. This led to the conclution that the most suitable velocity of crusher rollers along with the most proper temperature of the mixing unit for an extraction of optimum quantity high quality olive oil would be 12 rps and 30°C respectively. These are the figures finally recommended for efficient quality olive oil extraction

Design of new feature extraction methods out of the speech signal and combination of their obtained information are the most effective approaches to improve the performance of automatic speech recognition (ASR) system. Recent researches have been shown that the speech signal contains nonlinear and chaotic properties, but the effects of these properties were not used in the continuous ASR systems. Reconstructed phase space (RPS) is an appropriate domain to exhibit nonlinear properties of a chaotic signal. Therefore, in this paper a new method is proposed to utilize the RPS-based features (LLRPS). These features will be computed using similarity scores between the embedded speech signal in the RPS and a set of predefined phoneme manifolds. Then, TMLP-based neural network estimates phoneme posterior probability over the LLRPS features. This network includes some useful properties such as extracting dynamic information and output combination methods. Experimental results using Farsdat speech database show that nonlinear combination of the speech recognition outputs including traditional MFCC features and LLRPS features, leading to improvement of 3.94% and 4.02% in the accuracy of frame and phoneme recognition, respectively.

Cereal yellow dwarf viruses are among the most destructive cereal viruses worldwide. In this study, subcellular localizations of silencing suppressor proteins ( P0) from two cereal yellow dwarf viruses, Cereal yellow dwarf virus-RPV (CYDV-RPV) and Cereal yellow dwarf virus-RPS (CYDV-RPS), were examined via confocal microscopy. To do so, P0 genes were synthesized by polymerase chain reaction (PCR) and were cloned through Gateway cloning system. Agrobacterium. tumefaciens clones harboring GFP:P0 constructs were infiltrated into Nicotiana benthamiana plants. Transient expression of P0 proteins with N-terminal GPF fusion enabled us to examine their subcellular localizations in plant cells, 24 hours post infiltration. Results showed that both proteins are nuclear-cytoplasmic but different tendencies were observed in their localizations. In other words, P0 of CYDV-RPS was more nuclear oriented than P0 of CYDV-RPV. In the Western blot analysis using GFP polyclonal antibody only GFP:P0 proteins but no free GFP, were detected indicating that localizations were related to GFP:P0 proteins.

Recent researches show that nonlinear and chaotic behavior of the speech signal can be studied in the reconstructed phase space (RPS). Delay embedding theorem is a useful tool to study embedded speech trajectories in the RPS. Characteristics of the speech trajectories have rarely used in the practical speech recognition systems. Therefore, in this paper, a new feature extraction (FE) method is proposed based on parameters of vector AR (VAR) analysis over the speech trajectories. In this method, using filter and reflection matrices obtained from applying VAR analysis on static and dynamic information of the speech trajectory in the RPS, a high-dimensional feature vector can be achieved. Then, different transformation methods are utilized to attain final feature vectors with appropriate dimension. Results of discrete and continuous phoneme recognition over FARSDAT speech corpus show that the efficiency of the proposed FE method is better than other time-domain-based FE methods such as LPC and LPREF.

Many methods for automatic heartbeat classification have been applied and reported in literature, but relatively little number of them concerned with patient independent classification because of the less significant results compared to patient dependent ones. In this work, Reconstructed Phase Space (RPS) theory is used to classify five heartbeat types (Normal, PVC, LBBB, RBBB and PB). In the first and second method, RPS is modeled by the Gaussian mixture model (GMM) and bins, respectively and then classified by classic Bayesian classifier. In the third method, RPS is directly used to train predictor time-delayed neural networks (TDNN) and classified based on minimum prediction error. All three methods highly outperform the results reported before for patient independent heartbeat classification. The best result is achieved using GMM-Bayes method with 92.5% accuracy for patient independent classification.

A reward and penalty scheme (RPS) is used for setting up the service quality which exposes the distribution companies to financial benefits caused by demand for the reliability of customers. In this paper, an algorithm for the optimal switch number and placement in distribution networks in the presence of RPS is presented. The primary objective is reliability improvement and minimization of the cost of sectionalizing switches (SS) and tie switches (TS) for a given regulatory period considering acceptable financial risk. In this algorithm, the uncertainty in the reliability is appeared as financial risk. A genetic algorithm is adopted to solve the optimization problem. The number and location of SS and TS is found while financial incentives of RPS, capital investment and annual operation and maintenance costs are considered. The performance of the proposed approach is assessed and illustrated on a real distribution network. The results show the efficiency of the proposed algorithm.

Intensive culture of  rainbow trout is usually conducted in a variety of culture systems. The objective of this study, was to compare the performance of fish growth and welfare in a new design of elliptic ponds with circular flow; Foster-locas ponds (FLPs) and raceway ponds (RPs) under field conditions. The experiment was designed in two treatments with three repeats. For this purpose, three FLPs and three RPs were constructed. Each pond was randomly stocked by rainbow trout fish with initial average weight of approximately 40±5 g. Stocking density was 120 fish/m3 during study. Fish fed commercial diet (Chineh Company). Feeding operation conducted according to the manual by consideration of water temperature and fish weight at amount of 1.3 percent of biomass. Based on results, the fish survival rate in FLPs and RPs were  high (98.05% and 97.39% respectively). No significant difference in growth parameters were observed between RPs and FLPs, but fish growth rate in FLP was higher than RP (P> 0.05). Mean water quality factors (dissolved oxygen and PH) were favorite in FLP for culture of  rainbow trout and don,t have significant difference with those in RP (P> 0.05). The results confirmed when water quality is maintained in safe level ranges, FLPs can be used as a substitute of RP for intense rainbow trout culture.