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

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

order to increase the level of security, as this system encrypts the secret image before sending it through the internet to the recipient (by the Blowfish method). As The Blowfish method is known for its efficient security; nevertheless, the encrypting time is long. In this research we try to apply the smoothing filter on the secret image which decreases its size and consequently the encrypting and decrypting time are decreased. The secret image is hidden after encrypting it into another image called the cover image, by the use of one of these two methods" Two-LSB" or" Hiding most bits in blue pixels". Eventually we compare the results of the two methods to determine which one is better to be used according to the PSNR measurs

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

Traditionally, style is defined as the expressive, emotive or aesthetic emphasis added linguistically to the discourse with its meaning is the same. In the current study, however, style is defined as the linguistic choice that the language users can make for specific purposes.

    This study, thus, aims at analyzing political Arabic and English speeches to find out whether there are differences of style between English and Arabic and whether the choices the language users make  can show any traits of their psychological status.

    To fulfill the above aims, the study hypothesizes that English and Arabic  speeches can be analyzed stylistically and that there are stylistic difference

The construction process of reception containing rebuild educated new gloss within the context of real-time knowledge with previous experience and learning environment, accounting for all of the real experiences and information beside Education backbones structural climate (olive 0.2002: p. 212 .) Based on two basic principles - : I: - The natural science that we do know from our experiences, we can not say for sure Bhakaigah realism and clearly, but built by creative minds of certain interpretations be applicable in light of our expectations. Other: - The knowledge built effectively active learner who adapts new knowledge with the conceptual framework has, since everyone has a conceptual framework can break at any time and replaced by a ne