With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

The real and imaginary part of complex dielectric constant for InAs(001) by adsorption of oxsagen atoms has been calculated, using numerical analysis method (non-linear least square fitting). As a result a mathematical model built-up and the final result show a fairly good agreement with other genuine published works.

The available experimental data of proton electronic stopping power for Polyethylene, Mylar, Kapton and Polystyrene are compared with Mathematica, SRIM2013, PSTAR and libdEdx programs or databases.  The comparison involves sketching out both experimental and databases data for each polymer to discuss the agreement. Further, we use statistical means via standard deviation resulting from the mean normalized difference to describe the precise agreement among the databases and the experimental data. We found that there is not a specific one database can describe the experimental data for certain material at given proton energy.

In this paper, a method for data encryption was proposed using two secret keys, where the first one is a matrix of XOR's and NOT's gates (XN key), whereas the second key is a binary matrix (KEYB) key. XN and KEYB are (m*n) matrices where m is equal to n. Furthermore this paper proposed a strategy to generate secret keys (KEYBs) using the concept of the LFSR method (Linear Feedback Shift Registers) depending on a secret start point (third secret key s-key). The proposed method will be named as X.K.N. (X.K.N) is a type of symmetric encryption and it will deal with the data as a set of blocks in its preprocessing and then encrypt the binary data in a case of stream cipher.

Transforming the common normal distribution through the generated Kummer Beta model to the Kummer Beta Generalized Normal Distribution (KBGND) had been achieved. Then, estimating the distribution parameters and hazard function using the MLE method, and improving these estimations by employing the genetic algorithm. Simulation is used by assuming a number of models and different sample sizes. The main finding was that the common maximum likelihood (MLE) method is the best in estimating the parameters of the Kummer Beta Generalized Normal Distribution (KBGND) compared to the common maximum likelihood according to Mean Squares Error (MSE) and Mean squares Error Integral (IMSE) criteria in estimating the hazard function. While the pr

Chelating agents were used in a chelation therapy to detoxify heavy metals and toxins and convert them to an inactive form which was excreted out of the body. Nickel is one of these toxic heavy metal when presented in a high values over its allowable limit. This work studies the complexation of some amino acid (Glycine, Histidine, and Arginine) with nickel (II) ion and compare the result with complexation of EDTA (the synthesized amino acid) used in the chelation therapy. Our experiment were performed in a phosphate buffer of PH (7.2) and in a different temperature (283, 288,293, 298, 303)K . The results show a high tendency for these amino acid to nickel ion with an equilibrium constant in arrange of [KNi(II)-EDTA(17.2×108) > KNi(II