No abstract

Industrial control systems are increasingly used for control and monitoring of important infrastructure. Machine learning algorithms have the ability to discover patterns in large amounts of data and to create diagnosis models based on these patterns. Since modelling a large amount of unlabeled data is costly and time-consuming, the automated machine learning methods have the ability to detect anomalies in industrial control systems effectively. In this paper, first, twenty-four machine learning algorithms are evaluated for anomaly detection in gas distribution control network. Then dimensionality reduction algorithms are used to improve the accuracy of anomaly detection. Finally, by using an evolutionary based optimization for training a neural network, a new algorithm for prediction of anomalies in the SCADA system with high accuracy is proposed. The experimental results show that the proposed algorithm has the ability to detect the anomalies in the gas distribution control network with 97.5% accuracy.

Wide area monitoring system requires the integration of an advanced technology that provides real time synchronized phase angle measurements at all their measurement points. The phasor measurement units are the most advanced devices to achieve that. The objective of this work is first, to find the optimal placement of a minimum number of PMUs in some standardized IEEE systems. Next, the same method was applied to the Algerian 63 bus system. Two cases are taken into consideration: the minimum number of PMUs without considering the ZIB, then, considering the ZIB. The simulations are carried out using MATLAB/SIMULINK.

Comparison of several kinds of English-PersianStatistical Machine Translation systems is reported in this paper. A large parallel corpus containing about 6 million tokens on each side has been developed for training the proposed SMT system. In development of the parallel corpus, a noisy filtering system based on MaxEnt classifier bas been innovated to distinguish between correct and incorrect sentence pairs. By using the generated parallel corpus, a variety of SMT systems on English to Persian languages has been developed. Several variations on SMT, such as hybrid MT or statistical post editing MT has been proposed in this paper. The whole systems were tested on two different types of test set, one extracted randomly from parallel corpus and the other containing formal English sentences extracted from English learning book. The results shows hybrid system of SMT augmented by a rule based detection of English phrasal verb and Persian compound verb improves the baseline significantly. Also, state-of-the-art results on English-Persian translation are obtained by Verb-aware SMT with respect to BLEU measure.

So far arrayed waveguide grating (AWG) multi/demultiplexers have been fabricated based on uniform arrayed waveguide grating, having very sharp passband. Consequently they are sensitive to wavelength fluctuations of the laser sources. In this paper by optimizing the lengths algorithm, nonuniform A W G has been designed with flat passband.