A newly flow injection-turbidimetric method characterized by it is speed and sensitivity has been developed for the determination of Amiloride in pure and pharmaceutical preparations. It is based on the formation of yellowish white precipitate for the Amiloride-phosphomolybidic acid ion pair in aqueous medium. Turbidity was measured by Ayah 6Sx1-T-1D solar cell CFI analyser via the attenuation of incident light from the surfaces precipitated particles at 0-180. The Chemical and physical parameters were investigated. Linear dynamic range for the attenuation of incident light versus Amiloride concentration was of 0.005-10 mmol.L-1, with the correlation coefficient (r) of 0.9986 , while the percentage linearity (r2%) was 99.71%. The L.O.

A newly flow injection-turbidimetric method characterized by it is speed and sensitivity has been developed for the determination of Amiloride in pure and pharmaceutical preparations. It is based on the formation of yellowish white precipitate for the Amiloride-phosphomolybidic acid ion pair in aqueous medium. Turbidity was measured by Ayah 6Sx1-T-1D solar cell CFI analyser via the attenuation of incident light from the surfaces precipitated particles at 0-180. The Chemical and physical parameters were investigated. Linear dynamic range for the attenuation of incident light versus Amiloride concentration was of 0.005-10 mmol.L-1, with the correlation coefficient (r) of 0.9986 , while the percentage linearity (r2%) was 99.71%. The L.O.

     Deep learning techniques allow us to achieve image segmentation with excellent accuracy and speed. However, challenges in several image classification areas, including medical imaging and materials science, are usually complicated as these complex models may have difficulty learning significant image features that would allow extension to newer datasets. In this study, an enhancing technique for object detection is proposed based on deep conventional neural networks by combining levelset and standard shape mask. First, a standard shape mask is created through the "probability" shape using the global transformation technique, then the image, the mask, and the probability map are used as the levelset input to apply the image segme

The author addresses the issue of the linguoculturological component in the process of teaching Russian to Arabic students, focuses on the peculiarities of the national character of students. The author also refers to the long-standing ties of Russian and Arab cultures, thus emphasizing the relevance of this aspect for the current state and situation of the Russian language in Arab countries.

Автор статьи обращается к вопросу лингвокультурологической составляющей в процессе преподавания русского языка арабским студентам, останавливается на особенностях национального хара

      Grammatical particles are so important in understanding a text and its meaning in linguistic context. This paper  " Grammatical Behavior and Uses of Negative and Prohibitive Particles in Semitic Languages: A Comparative Semitic Study"

      tackles  a very important topic in Semitic languages. Comparative studies in Semitic languages shed light on  phenomena in different languages that are related or have one common origin. No doubt, such studies have their own effects on language study in general especially when studying a specific phenomenon and explaining it by reliance on the one origin, or by investigating the various phases of its historical development.

Fingerprint recognition is one among oldest procedures of identification. An important step in automatic fingerprint matching is to mechanically and dependably extract features. The quality of the input fingerprint image has a major impact on the performance of a feature extraction algorithm. The target of this paper is to present a fingerprint recognition technique that utilizes local features for fingerprint representation and matching. The adopted local features have determined: (i) the energy of Haar wavelet subbands, (ii) the normalized of Haar wavelet subbands. Experiments have been made on three completely different sets of features which are used when partitioning the fingerprint into overlapped blocks. Experiments are conducted on

In this paper, point estimation for parameter ? of Maxwell-Boltzmann distribution has been investigated by using simulation technique, to estimate the parameter by two sections methods; the first section includes Non-Bayesian estimation methods, such as (Maximum Likelihood estimator method, and Moment estimator method), while the second section includes standard Bayesian estimation method, using two different priors (Inverse Chi-Square and Jeffrey) such as (standard Bayes estimator, and Bayes estimator based on Jeffrey's prior). Comparisons among these methods were made by employing mean square error measure. Simulation technique for different sample sizes has been used to compare between these methods.