Islamic Azad University

About: Islamic Azad University is a education organization based out in Tehran, Iran. It is known for research contribution in the topics: Population & Catalysis. The organization has 83635 authors who have published 113437 publications receiving 1275049 citations. The organization is also known as: Azad University.

Optimization of neural networks for precipitation analysis in a humid region to detect drought and wet year alarms

Abstract: In this study, annual precipitation was forecast by coding in MATLAB software environment based on a non-linear autoregressive neural network (NARNN), non-linear input–output (NIO) and NARNN with exogenous input (NARNNX). Historical precipitation data (27 precipitation gauge stations located in Gilan, Iran) were used as two 21 year sets from 1968 to 1988 and from 1989 to 2009 for calibration and testing of the networks, respectively. Results showed that the accuracy of the NARNNX was better than that of the NARNN and NIO, based on r values. However, performance of the networks was not satisfactory because the number of neurons in the hidden layer and the roles of training, validation and testing phases were lacking flexibility and change. Optimization of the number of neurons in the hidden layer and the determination of the best role among the different phases led to improvement of network accuracy. The r values were <0.73 only for five stations in the optimized NARNN and <0.74 only for those stations with optimized NIO.

Cloud computing security threats and responses

Abstract: Cloud computing is one of today's most exciting technologies due to its ability to reduce costs associated with computing while increasing flexibility and scalability for computer processes. During the past few years, cloud computing has grown from being a promising business idea to one of the fastest growing parts of the IT industry. IT organizations have expresses concern about critical issues (such as security) that exist with the widespread implementation of cloud computing. These types of concerns originate from the fact that data is stored remotely from the customer's location; in fact, it can be stored at any location. Security, in particular, is one of the most argued-about issues in the cloud computing field; several enterprises look at cloud computing warily due to projected security risks. The risks of compromised security and privacy may be lower overall, however, with cloud computing than they would be if the data were to be stored on individual machines instead of in a so — called "cloud" (the network of computers used for remote storage and maintenance). Comparison of the benefits and risks of cloud computing with those of the status quo are necessary for a full evaluation of the viability of cloud computing. Consequently, some issues arise that clients need to consider as they contemplate moving to cloud computing for their businesses. In this paper I summarize reliability, availability, and security issues for cloud computing (RAS issues), and propose feasible and available solutions for some of them.

Optimisation of demand response in electric power systems, a review

Abstract: Demand response programs offer efficient solutions for many power system problems, such as high generation cost, high demand’s peak to average ratio, high emissions, reliability issues and congestion in generation, transmission and distribution systems. Their main function is to assist power systems during peak demand hours and also during contingencies. They are a subcategory of the family of demand side management (DSM) strategies. DR programs are classified into two broad categories; price-based DR programs and incentive-based DR programs. In order to exploit their full potential, DR programs must be implemented optimally. Such a problem, which here is referred to as “DR optimisation problem”, is a hot research topic and has been frequently researched in the literature. This paper aims to review different research works on DR optimisation problems. Based on the conducted review, some directions for future research are proposed.

Hydrophilic Multitemplate Molecularly Imprinted Biopolymers Based on a Green Synthesis Strategy for Determination of B-Family Vitamins.

Abstract: A novel green synthesis strategy was proposed for preparation of multitemplate molecularly imprinted biopolymers (mt-MIBP) in aqueous media with less consumption of organic solvents, which were subsequently used as sorbents of ultrasound-assisted dispersive solid-phase extraction (d-SPE) for simultaneous recognition and efficient separation of B-family vitamins in juice samples, followed by high performance liquid chromatography (HPLC) determination. The obtained mt-MIBP was fully characterized by SEM, FT-IR, TEM, and BET. It offered high binding capacity, good selectivity, and fast dynamics toward all the templates. Involved parameters in the d-SPE efficiency such as mt-MIBP mass, sonication time, and eluting/washing solvents' types and volumes were concurrently investigated by central composite design with rapidity and reliability. Under the optimum conditions, the developed mt-MIBP-d-SPE-HPLC method exhibited wide linear range, low limits of detection and quantification (LOQs) within 1.2-5.5 μg L-1 and 4.0-18.4 μg L-1, respectively, and appropriate repeatability (relative standard deviation values below 4.2%, n = 4). The high selectivity of this method makes it suitable for successful monitoring of vitamins in juice samples with satisfactory recoveries of 75.8-92.7%, 81.1-92.5%, and 84.7-93.8% for vitamins riboflavin (B2), nicotinamide (B3), and pyridoxine (B6), respectively. The present study implied highly promising perspectives of water-compatible eco-friendly mt-MIBP for highly effective multiresidue analysis in complicated matrixes.