Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

Freedom of opinion is one of the freedoms that constitutions and laws have guaranteed to protect and is exercised through the media. However, this freedom must be exercised within certain limits, which include respecting a person’s right to preserve his privacy, image and reputation. Just as the media has the freedom to exercise its right to publish and express its opinion with complete frankness, it is in return obligated to respect the rights of others and avoid defaming them and violating their privacy. If the media does this, the injured party has the right to demand compensation for the damage he has suffered as a result.

Most of the water pollutants with dyes are leftovers from industries, including textiles, wool and others. There are many ways to remove dyes such as sorption, oxidation, coagulation, filtration, and biodegradation, Chlorination, ozonation, chemical precipitation, adsorption, electrochemical processes, membrane approaches, and biological treatment are among the most widely used technologies for removing colors from wastewater. Dyes are divided into two types: natural dyes and synthetic dyes.

In the present study, advanced oxidation process / heterogeneous photocatalytic process (UV/TiO₂/Fenton) system was investigated to the treatment of oily wastewater. The present study was conducted to evaluate the effect of hydrogen peroxide concentration H₂O₂, initial amount of the iron catalyst Fe⁺², pH, temperature, amount of TiO₂ and the concentration of oil in the wastewater.  The removal efficiency for the system UV/TiO₂/Fenton at optimal conditions and dosage (H₂O₂ = 400mg/L, Fe⁺² = 40mg/L, pH=5, temperature =30^oC, TiO₂=75mg/L) for 1000mg/L load was found to be 77%.

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The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in

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The activity of Adhatoda vasica crude plants extracts against B.thuringiensis bacteria was determined by MIC test and sensitivity test which showed no response of this type of bacteria against extracts .The interference between the effect of hot and cold aqueous extracts and Bacillus thuringiensis bacteria for controlling the population of fig moth when males and females released before treatment under control condithion was gave a highly percentage of larval mortality which reached to 100% in (B.t. + hot aqueous extract ) and 97.3% in (B.t + coldaqueous extract ) after two weeks of treatment when concentration of 50% of aqueous extracts and 5×10?1of Bacillus thuringiensis bacteria but when the insect (males & females) released after

This research a study model of linear regression problem of autocorrelation of random error is spread when a normal distribution as used in linear regression analysis for relationship between variables and through this relationship can predict the value of a variable with the values of other variables, and was comparing methods (method of least squares, method of the average un-weighted, Thiel method and Laplace method) using the mean square error (MSE) boxes and simulation and the study included fore sizes of samples (15, 30, 60, 100). The results showed that the least-squares method is best, applying the fore methods of buckwheat production data and the cultivated area of the provinces of Iraq for years (2010), (2011), (2012),