The main object of this article is to study and introduce a subclass of meromorphic univalent functions with fixed second positive defined by q-differed operator. Coefficient bounds, distortion and Growth theorems, and various are the obtained results.
Background: clinically significant macular edema (CSME) is the commonest cause of visual loss in patients with diabetes mellitus and laser focal photocoagulation is the golden standard for treating it. Patients and Methods: A frequency doubled Nd: YAG laser was used to treat all eyes included in this study with diabetic maculopathy. Thirty eyes of three insulin dependent and twenty six non insulin dependent diabetic Iraqi patients were included. The study involved twenty six males, three females and followed for one year. Their ages were ranging between 36- 59 years, all of them from patients attending ophthalmic out-patient department in the medical city in the period between January 2005 and June 2006. Eyes divided in to two groups (fifte
... Show MoreA mathematical model was created to study the influences of Hall current and Joule heating with wall slip conditions on peristaltic motion of Rabinowitsch fluid model through a tapered symmetric channel with Permeable Walls. The governing equations are simplified under low Reynolds number and the long-wavelength approximations. The perturbation method is used to solve the momentum equation. The physiological phenomena are studied for a certain set of pertinent parameters. The effects offered here show that the presence of the hall parameter, coefficient of pseudo-plasticity, and Hartman number impact the flow of the fluid model. Additional, study reveals that a height in the Hall parameter and the velocity slip parameter incre
... Show MoreDifferent formula of bioagents (Rhizobium cicceri cp-93, Azospirillum sp.,
Pseudomonas fluorescence, Trichoderma harzianum ) used in this study as a
biofertilizer on wheat crop with two level of chemical fertilizer (0 and 12.5
kg/donm Dap) compared to 50kg/donm Dap (standard amount).the study carried out
in Iraq/Diyala –Alkhales during November 2014,results showed significant increase
in no. of spikes, no. of spikelet’s, length of spike ,Weight of 1000 seed and yield of
one m2 when adding (Rhizobium cicceri cp-93,Azospirillumsp+ Trichoderma
harzianum +12.5 kg/donm Dap) in comparison with the 50kg/donm Dap. Other
formulas recorded same results with the treatment 50kg/Donm Dap with not
significant differences
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for
The operator ψ has been introduced as an associated set-valued set function. Although it has importance for the study of minimal open sets as well as minimal I-open sets. As a result of this study, we introduce minimal I^*-open sets . In this study, several characterizations of minimal I^*-open sets are also investigated. This study also discusses the role of minimal I^*-open sets in the *-locally finite spaces. In an aspect of topological invariant, the homeomorphic images of minimal I^*-open set has been discussed here.
In this paper we study and design two feed forward neural networks. The first approach uses radial basis function network and second approach uses wavelet basis function network to approximate the mapping from the input to the output space. The trained networks are then used in an conjugate gradient algorithm to estimate the output. These neural networks are then applied to solve differential equation. Results of applying these algorithms to several examples are presented
The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).
The nuclear size radii, density distributions and elastic electron scattering charge form factors for Fluorine isotopes (17,19,20,24,26F) were studied using the radial wave functions (WF) of harmonic-oscillator (HO) potential and free mean field described by spherical Hankel functions (SHF) for the core and the valence parts, respectively for all aforementioned isotopes. The parameters for HO potential (size parameter ) and SHF were chosen to regenerate the available experimental size radii. It was found that using spherical Hankel functions in our work improved the calculated results quantities in comparison with empirical data.