Abstract: This study aims to investigate the effects of solvents of various polarities on the electronic absorption and fluorescence spectra of RhB and Rh6G. The singlet‐state excited dipole moments (me) and ground state dipole moments (mg) were estimated from the equations of Bakshiev -Kawski and Chamma‐ Viallet using the variation of Stokes shift along with the solvent’s dielectric constant (e) and refractive indexes (n). The observed singlet‐state excited dipole moments were found to be larger than the ground‐state ones. Moreover, the obtained fluorescence quantum yield values were influenced by the environment of the fluorescing molecule. Consequently, the concentration of the dye solution, excited singlet state absorption and

     The proton, neutron and matter density distributions, the corresponding size radii and elastic electron scattering form factors of one-proton⁸B and two-proton ¹⁷Ne halo nuclei are calculated. The theoretical technique used to fulfill calculations is by assuming that both nuclei under study are composed of two main parts; the first is the compact core and the second is the unstable halo part. The single-particle radial wavefunctions of harmonic-oscillator (HO) and Woods-Saxon (WS) potentials are used to study core and halo parts, respectively. And other approach is studied by using HO potential for both core and halo parts, but using two HO size parameters for both supposed parts. The long ta

We are used Bayes estimators for unknown scale parameter  when shape Parameter  is known of Erlang distribution. Assuming different informative priors for unknown scale  parameter. We derived The posterior density with posterior mean and posterior variance using different informative priors for unknown scale parameter  which are the inverse exponential distribution, the inverse chi-square distribution, the inverse Gamma distribution, and the standard Levy distribution as prior. And we derived Bayes estimators based on the general entropy loss function (GELF) is used the Simulation method to obtain the results. we generated different cases for the parameters of the Erlang model, for different sample sizes. The estimates have been comp

The stress – strength model is one of the models that are used to compute reliability. In this paper, we derived mathematical formulas for the reliability of the stress – strength model that follows Rayleigh Pareto (Rayl. – Par) distribution. Here, the model has a single component, where strength Y is subjected to a stress X, represented by moment, reliability function, restricted behavior, and ordering statistics. Some estimation methods were used, which are the maximum likelihood, ordinary least squares, and two shrinkage methods, in addition to a newly suggested method for weighting the contraction. The performance of these estimates was studied empirically by using simulation experimentation that could give more varieties for d

Cloud Computing is a mass platform to serve high volume data from multi-devices and numerous technologies. Cloud tenants have a high demand to access their data faster without any disruptions. Therefore, cloud providers are struggling to ensure every individual data is secured and always accessible. Hence, an appropriate replication strategy capable of selecting essential data is required in cloud replication environments as the solution. This paper proposed a Crucial File Selection Strategy (CFSS) to address poor response time in a cloud replication environment. A cloud simulator called CloudSim is used to conduct the necessary experiments, and results are presented to evidence the enhancement on replication performance. The obtained an

 The aim of this paper, is to discuss several high performance training algorithms fall into two main categories. The first category uses heuristic techniques, which were developed from an analysis of the performance of the standard gradient descent algorithm. The second category of fast algorithms uses standard numerical optimization techniques such as: quasi-Newton . Other aim is to solve the drawbacks related with these training algorithms and propose an efficient training algorithm for FFNN

Iraq is one of the Arabian area countries, which considered from the drier areas
on the earth, though it has two main rivers that pass through(Tigris and Euphrates);
it suffers the same problem as them (drought), only the rivers' nearby regions make
use of their water for (domestic, agricultural, and industrial purposes(.
One of the usable solutions is to utilize the groundwater (especially in the desert
regions). Using the Remote Sensing and geographic information system is a rapid
and coast effective techniques, they provide information of large and inaccessible
area within short span for assessing, monitoring, and management of groundwater
resources. In this study, an adaptive algorithm based on Canny edge dete

      As smartphones incorporate location data, there is a growing concern about location  privacy as smartphone technologies advance. Using a remote server, the mobile applications are able to capture the current location coordinates at any time and store them. The client awards authorization to an outsider. The outsider can gain admittance to area information on the worker by JSON Web Token (JWT). Protection is giving cover to clients, access control, and secure information stockpiling. Encryption guarantees the security of the location area on the remote server using the Rivest Shamir Adleman (RSA) algorithm. This paper introduced two utilizations of cell phones (tokens, and location). The principal application can give area inf

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]).

Solid waste is a major issue in today's world. Which can be a contributing factor to pollution and the spread of vector-borne diseases. Because of its complicated nonlinear processes, this problem is difficult to model and optimize using traditional methods. In this study, a mathematical model was developed to optimize the cost of solid waste recycling and management. In the optimization phase, the salp swarm algorithm (SSA) is utilized to determine the level of discarded solid waste and reclaimed solid waste. An optimization technique SSA is a new method of finding the ideal solution for a mathematical relationship based on leaders and followers. It takes a lot of random solutions, as well as their outward or inward fluctuations, t