Background: Lung cancer is a common disease for patients over the age of 50 years, especially males due to smoking habits. This study aimed to compare the modulation complexity score (MCS) for the advanced treatment planning techniques which the intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT). Materials and Methods: Thirty patients who had non-small lung cancerous tumors on their left side participated in this study. The range ages were 68 to 98 years, the heights were between 151 and 182cm and they having weights from 46 to 79 kg. For Each patient will create two plans dial using two different techniques, which will be Intensity Modulated Radiation Therapy (IMRT) and Volumetric Modulated Arc Therapy

The study presents the modification of the Broyden-Flecher-Goldfarb-Shanno (BFGS) update (H-Version) based on the determinant property of inverse of Hessian matrix (second derivative of the objective function), via updating of the vector s ( the difference between the next solution and the current solution), such that the determinant of the next inverse of Hessian matrix is equal to the determinant of the current inverse of Hessian matrix at every iteration. Moreover, the sequence of inverse of Hessian matrix generated by the method would never  approach a near-singular matrix, such that the program would never break before the minimum value of the objective function is obtained. Moreover, the new modification of BFGS update (H-vers

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

In recent years, the positioning applications of Internet-of-Things (IoT) based systems have grown increasingly popular, and are found to be useful in tracking the daily activities of children, the elderly and vehicle tracking. It can be argued that the data obtained from GPS based systems may contain error, hence taking these factors into account, the proposed method for this study is based on the application of IoT-based positioning and the replacement of using IoT instead of GPS.  This cannot, however, be a reason for not using the GPS, and in order to enhance the reliability, a parallel combination of the modern system and traditional methods simultaneously can be applied. Although GPS signals can only be accessed in open spaces, GP

Dynamic machine foundations can be considered as a necessary component of the industrial infrastructure. Design of the dynamic equipment foundations has, however, traditionally been grounded on a rule of thumb that is inaccurate and rigid to use at the discretion of the engineers. The conventional rule of thumb, which includes minimum weight ratios and resonance avoidance criteria, has been used singularly with two poles, which can be either conservatively designed systems that are too heavy, or systems that are going to experience too much vibration and fatigue. This paper presents a novel, analytical framework for the reinterpretation of traditional design practices, using a physics-based approach, and results in a single, unified overall