In this present paper, an experimental study of some plasma characteristics in dielectric barrier discharge (DBD) system using several variables, such as different frequencies and using two different electrodes metals(aluminium (Al) and copper (Cu)), is represented. The discharge plasma was produced by an AC power supply source of 6 and 7 kHz frequencies for the nitrogen gas spectrum and for two different electrodes metals(Al and Cu). Optical emission spectrometer was used to study plasma properties (such as electron temperature ( ), electron number density ( ), Debye length ( ), and plasma frequency ( )). In addition, images were analysed for the plasma emission intensity at atmospheric air pressure.
In this paper we give many connections between essentially quasi-Dedekind (quasi-
Dedekind) modules and other modules such that Baer modules, retractable modules,
essentially retractable modules, compressible modules and essentially compressible
modules where an R-module M is called essentially quasi-Dedekind (resp. quasi-
Dedekind) if, Hom(M N ,M ) 0 for all N ≤e M (resp. N ≤ M). Equivalently, a
module M is essentially quasi-Dedekind (resp. quasi-Dedekind) if, for each
f End (M) R , Kerf ≤ e M implies f = 0 (resp. f 0 implies ker f 0 ).
Throughout this paper R represents commutative ring with identity and M is a unitary left R-module. The purpose of this paper is to investigate some new results (up to our knowledge) on the concept of weak essential submodules which introduced by Muna A. Ahmed, where a submodule N of an R-module M is called weak essential, if N ? P ? (0) for each nonzero semiprime submodule P of M. In this paper we rewrite this definition in another formula. Some new definitions are introduced and various properties of weak essential submodules are considered.
The definition of semi-preopen sets were first introduced by "Andrijevic" as were is defined by :Let (X , ï´ ) be a topological space, and let A ⊆, then Ais called semi-preopen set if ⊆∘ . In this paper, we study the properties of semi-preopen sets but by another definition which is equivalent to the first definition and we also study the relationships among it and (open, α-open, preopen and semi-p-open )sets.
A class of hyperrings known as divisible hyperrings will be studied in this paper. It will be presented as each element in this hyperring is a divisible element. Also shows the relationship between the Jacobsen Radical, and the set of invertible elements and gets some results, and linked these results with the divisible hyperring. After going through the concept of divisible hypermodule that presented 2017, later in 2022, the concept of the divisible hyperring will be related to the concept of division hyperring, where each division hyperring is divisible and the converse is achieved under conditions that will be explained in the theorem 3.14. At the end of this paper, it will be clear that the goal of this paper is to study the concept
... Show MoreThe definition of semi-preopen sets were first introduced by "Andrijevic" as were is defined by :Let (X , ï´ ) be a topological space, and let A ⊆, then A is called semi-preopen set if ⊆∘ . In this paper, we study the properties of semi-preopen sets but by another definition which is equivalent to the first definition and we also study the relationships among it and (open, α-open, preopen and semi-p-open )sets.
The structure of this paper includes an introduction to the definition of the nano topological space, which was defined by M. L. Thivagar, who defined the lower approximation of G and the upper approximation of G, as well as defined the boundary region of G and some other important definitions that were mentioned in this paper with giving some theories on this subject. Some examples of defining nano perfect mappings are presented along with some basic theories. Also, some basic definitions were presented that form the focus of this paper, including the definition of nano pseudometrizable space, the definition of nano compactly generated space, and the definition of completely nano para-compact. In this paper, we presented images of nan
... Show MoreA numerical computation for determination transmission coefficient and resonant tunneling energies of multibarriers heterostructure has been investigated. Also, we have considered GaN/Al0.3Ga0.7N superlattice system to estimate the probability of resonance at specific energy values, which are less than the potential barrier height. The transmission coefficient is determined by using the transfer matrix method and accordingly the resonant energies are obtained from the T(E) relation. The effects of both well width and number of barriers (N) are observed and discussed. The numbers of resonant tunneling peaks are generally increasing and they become sharper with the increasing of N. The resonant tunneling levels are sh
... Show MoreA numerical computation for determination transmission coefficient and resonant tunneling energies of multibarriers heterostructure has been investigated. Also, we have considered GaN/Al0.3Ga0.7N superlattice system to estimate the probability of resonance at specific energy values, which are less than the potential barrier height. The transmission coefficient is determined by using the transfer matrix method and accordingly the resonant energies are obtained from the T(E) relation. The effects of both well width and number of barriers (N) are observed and discussed. The numbers of resonant tunneling peaks are generally increasing and they become sharper with the increasing of N. The resonant tunneling levels are shifted inside the well by
... Show MoreThese days, it is crucial to discern between different types of human behavior, and artificial intelligence techniques play a big part in that. The characteristics of the feedforward artificial neural network (FANN) algorithm and the genetic algorithm have been combined to create an important working mechanism that aids in this field. The proposed system can be used for essential tasks in life, such as analysis, automation, control, recognition, and other tasks. Crossover and mutation are the two primary mechanisms used by the genetic algorithm in the proposed system to replace the back propagation process in ANN. While the feedforward artificial neural network technique is focused on input processing, this should be based on the proce
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