Chemotherapy is one of the most efficient methods for treating cancer patients. Chemotherapy aims to eliminate cancer cells as thoroughly as possible. Delivering medications to patients’ bodies through various methods, either oral or intravenous is part of the chemotherapy process. Different cell-kill hypotheses take into account the interactions of the expansion of the tumor volume, external drugs, and the rate of their eradication. For the control of drug usage and tumor volume, a model based smooth super-twisting control (MBSSTC) is proposed in this paper. Firstly, three nonlinear cell-kill mathematical models are considered in this work, including the log-kill, Norton-Simon, and hypotheses subject to parametric uncertainties and exogenous perturbations. In accordance with clinical recommendations, the tumor volume follows a predefined trajectory after chemotherapy. Secondly, the MBSSTC is applied for the three cell-kill models to attain accurate trajectory tracking even in the presence of uncertainties and disturbances. Compared to conventional super-twisting control (STC), the non-smooth term is introduced in the proposed control to enhance the anti-disturbance capability. Finally, simulation comparisons are performed across the proposed MBSSTC, conventional STC, and proportional–integral (PI) control methods to show the effectiveness and merits of our designed control method.
Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreThe main problem of the current study concentrates on applying critical discourse analysis to examine textual, discoursal and social features of reduplication in some selected English newspaper headlines. The main aim of the current study is to analyze the linguistic features of reduplication by adopting Fairclough's three-dimensional model (2001). This study sets forth the following hypotheses: (1) English headline – newspapers comprise various textual, discoursal and social features ;(2)the model of analysis is best suited for the current study.To achieve the aims and verify the hypotheses, a critical discourse analysis approach is used represented by Fairclough's socio-cultural approach (2001).The present study has examined the use of
... Show MoreThe current study sheds light on the measurement and estimation of the radioactivity of radionuclides (238U, 226Ra, 232Th, and 40k) in natural waters of different regions of Nineveh Governorate in Iraq.15 samples were collected from different sources of natural waters, where gamma-ray spectroscopy was used using NaI)TI) sodium iodide detector to determine the concentration of radioactivity in the samples. According to the results, the radioactivity concentration in the tested water sample were ranged from 0.36 ± 0.04-1.57 ± 0.09with an average value of 0.69 ± 0.06 Bq/l for 238U, and 2.9 ± 0.02-0.88 ± 0.03 with an average value of 0.65 ± 0.03 Bq/l for 226Ra Bq/l
... Show MoreThe mixed-spin ferrimagnetic Ising system consists of two-dimensional sublattices A and B with spin values and respectively .By used the mean-field approximation MFA of Ising model to find magnetism( ).In order to determined the best stabile magnetism , Gibbs free energy employ a variational method based on the Bogoliubov inequality .The ground-state (Phase diagram) structure of our system can easily be determined at , we find six phases with different spins values depend on the effect of a single-ion anisotropies .these lead to determined the second , first orders transition ,and the tricritical points as well as the compensation phenomenon .
The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals
... Show MoreForecasting is one of the important topics in the analysis of time series, as the importance of forecasting in the economic field has emerged in order to achieve economic growth. Therefore, accurate forecasting of time series is one of the most important challenges that we seek to make the best decision, the aim of the research is to suggest employing hybrid models to predict daily crude oil prices. The hybrid model consists of integrating the linear component, which represents Box Jenkins models, and the non-linear component, which represents one of the methods of artificial intelligence, which is the artificial neural network (ANN), support vector regression (SVR) algorithm and it was shown that the proposed hybrid models in the predicti
... Show MoreThis paper presents a vibration suppression control design of cantilever beam using two piezoelectric patches. One patch was used as an actuator element, while the other was used as a sensor. The controller design was designed via the balance realization reduction method to elect the reduced order model that is most controllable and observable. the sliding mode observer was designed to estimate six states from the reduced order model but three states are only used in the control law. Estimating a number of states larger than that used is in order to increase the estimation accuracy. Moreover, the state estimation error is proved bounded. An optimal LQR controller is designed then using the estimated states with the slid
... Show MoreSome maps of the chaotic firefly algorithm were selected to select variables for data on blood diseases and blood vessels obtained from Nasiriyah General Hospital where the data were tested and tracking the distribution of Gamma and it was concluded that a Chebyshevmap method is more efficient than a Sinusoidal map method through mean square error criterion.
Laurylamine hydrochloride CH3(CH2)11 NH3 – Cl has been chosen from cationic surfactants to produce secondary oil using lab. model shown in fig. (1). The relationship between interfacial tension and (temperature, salinity and solution concentration) have been studied as shown in fig. (2, 3, 4) respectively. The optimum values of these three variables are taken (those values that give the lowest interfacial tension). Saturation, permeability and porosity are measured in the lab. The primary oil recovery was displaced by water injection until no more oil can be obtained, then laurylamine chloride is injected as a secondary oil recovery. The total oil recovery is 96.6% or 88.8% of the residual oil has been recovered by this technique as shown
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