Class consciousness represents its highest stage in the contemporary Marxist thought of Rosa Luxemburg and Antonio Gramsci, not just a reflection of reality, but rather a dialectical form through the reflection of consciousness on reality and its reproduction. The superiority over the infrastructure (historical materialism) promised the revolutionary class consciousness to be achieved spontaneously, and the seeds of a breakthrough are mass strikes, denying the role of the party to organize this awareness, limiting its role to the interconnection between classes, emphasizing the role of socialist democracy as a conscious vanguard for organizing spontaneity, struggle, and developing awareness during the revolutionary process and the leader

Brachytherapy treatment is primarily used for the certain handling kinds of cancerous tumors. Using radionuclides for the study of tumors has been studied for a very long time, but the introduction of mathematical models or radiobiological models has made treatment planning easy. Using mathematical models helps to compute the survival probabilities of irradiated tissues and cancer cells. With the expansion of using HDR-High dose rate Brachytherapy and LDR-low dose rate Brachytherapy for the treatment of cancer, it requires fractionated does treatment plan to irradiate the tumor. In this paper, authors have discussed dose calculation algorithms that are used in Brachytherapy treatment planning. Precise and less time-consuming calculations

Any software application can be divided into four distinct interconnected domains namely, problem domain, usage domain, development domain and system domain. A methodology for assistive technology software development is presented here that seeks to provide a framework for requirements elicitation studies together with their subsequent mapping implementing use-case driven object-oriented analysis for component based software architectures. Early feedback on user interface components effectiveness is adopted through process usability evaluation. A model is suggested that consists of the three environments; problem, conceptual, and representational environments or worlds. This model aims to emphasize on the relationship between the objects

 A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.

In this paper, we will provide a proposed method to estimate missing values for the Explanatory variables for Non-Parametric Multiple Regression Model and compare it with the Imputation Arithmetic mean Method, The basis of the idea of this method was based on how to employ the causal relationship between the variables in finding an efficient estimate of the missing value, we rely on the use of the Kernel estimate by Nadaraya – Watson Estimator , and on Least Squared Cross Validation (LSCV) to estimate the Bandwidth, and we use the simulation study to compare between the two methods.

In this paper, previous studies about Fuzzy regression had been presented. The fuzzy regression is a generalization of the traditional regression model that formulates a fuzzy environment's relationship to independent and dependent variables. All this can be introduced by non-parametric model, as well as a semi-parametric model. Moreover, results obtained from the previous studies and their conclusions were put forward in this context. So, we suggest a novel method of estimation via new weights instead of the old weights and introduce

Paper Type: Review article.

another suggestion based on artificial neural networks.

 In this paper, the human robotic leg which can be represented mathematically by single input-single output (SISO) nonlinear differential model with one degree of freedom, is analyzed and then a simple hybrid neural fuzzy controller is designed to improve the performance of this human robotic leg model. This controller consists from SISO fuzzy proportional derivative (FPD) controller with nine rules summing with single node neural integral derivative (NID) controller with nonlinear function. The Matlab simulation results for nonlinear robotic leg model with the suggested controller showed that the efficiency of this controller when compared with the results of the leg model that is controlled by PI+2D, PD+NID, and F