This study aims to study argumentation in political debates by figuring out the logical fallacies employed in the debates of Clinton and Trump, the presidential nominees of the 2016 elections, and Biden and Trump, the leading contenders in the 2020 United States presidential election. The study attempts to answer the questions: (1) What relevance fallacies are adopted in the debate between Trump and Clinton? (2) What rhetorical devices are used to influence the audience and gain voters besides fallacies in the debates selected? The study analyses two texts from two arguments using Damer's (2009) taxonomy of relevance fallacy and rhetorical devices based on Perrine’s (1969) model of communication and interpersonal rhetoric to answe

The evaluation of subsurface formations as applied to oil well drilling started around 50 years ago. Generally, the curent review articule includes all methods for coring, logging, testing, and sampling. Also the methods for deciphering logs and laboratory tests that are relevant to assessing formations beneath the surface, including a look at the fluids they contain are discussed. Casing is occasionally set in order to more precisely evaluate the formations; as a result, this procedure is also taken into account while evaluating the formations. The petrophysics of reservoir rocks is the branch of science interested in studying chemical and physical properties of permeable media and the components of reservoir rocks which are associated

The paper proposes a methodology for predicting packet flow at the data plane in smart SDN based on the intelligent controller of spike neural networks(SNN). This methodology is applied to predict the subsequent step of the packet flow, consequently reducing the overcrowding that might happen. The centralized controller acts as a reactive controller for managing the clustering head process in the Software Defined Network data layer in the proposed model. The simulation results show the capability of Spike Neural Network controller in SDN control layer to improve the (QoS) in the whole network in terms of minimizing the packet loss ratio and increased the buffer utilization ratio.

     In this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets  namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant features from

In this paper two ranking functions are employed to treat the fuzzy multiple objective (FMO) programming model, then using two kinds of membership function, the first one is trapezoidal fuzzy (TF) ordinary membership function, the second one is trapezoidal fuzzy weighted membership function. When the objective function is fuzzy, then should transform and shrinkage the fuzzy model to traditional model, finally solving these models to know which one is better

This research was aimed to study the osmotic efficiency of the draw solutions and the factors affecting the performance of forward osmosis process : The draw solutions used were magnesium sulfate hydrate (MgSO₄.7H₂O) pojtassium chloride (KCL), calcium chloride (CaCl₂) and ammonium bicarbonate (NH₄HCO₃). It was found that water flux increases with increasing draw solution concentration, and feed solution flow rate and decreases with increasing draw solution flow rate and feed solution concentration. And also found that the efficiency of the draw solutions is in the following order:

CaCl₂> KCI > NH₄HCO₃> MgSO₄.7H

The increasing requirement and use of dental implant treatments has rendered dental implantology indispensable in dentistry. The aim of this study is to determine the optimum concentration of calcium silicate to be incorporated into a polyetherketoneketone (PEKK) matrix used as an implant material to enhance the bioactivity and mechanical properties of the composite compared with unmodified PEKK. In this study, different weight percentage (wt%) of micro-calcium silicate (m-CS) is incorporated into PEKK with ethanol as a binder. Subsequently, the mixture is dried in a forced convection oven at 120°C and poured into customized molds to fabricate a bioactive composite via compression molding (310°C, 15 MPa, and 20 min holding time