SM ADAI, BN RASHID, Journal of Current Researches on Social Sciences, 2023

Corruption (Definition , Characteristics , Reasons , Features , and ways of combating it)

Slow cinema is a modern phenomenon conceptually. It is one of the most important contemporary features of the development of film art. Despite its roots extending back to previous cinematic schools, it is unique in its distinctive intellectual and visualaudio structures that tend towards slowness, simplicity, monotony, and calm in shaping the cinematic material it presents to the recipient, prompting them to contemplate and reflect on it, rather than receiving it passively. Thus, slow cinema becomes a revolutionary trend linked to philosophical structures broader than the world of film, attempting to resist the ideology of speed that dominates our contemporary lives. Based on this importance of slow cinema, the researcher definedthe topic o

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

The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then  proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme