A newly developed analytical method characterized by its speed and sensitivity for
the determination of cadmium (II) in aqueous solution in three randomly chosen
samples from river water at different locations via turbidimetric measurement by
Ayah 6SX1-T-2D Solar - CFI analyser. The method is based on the formation of
yellowish white precipitate for the complex Cd3[Fe(CN)6]2 by direct reaction of the
cadmium (II) with potassium hexacyano ferrate (III) in aqueous medium. Turbidity
was measured via the reflection of incident light that collides on the surfaces
precipitated particles at 0-180o. Chemical and physical parameters were investigated.
Linear dynamic of cadmium (II) is ranged from 0.05-12 mmol.L-1, with correlation
coefficient r = 0.9951. The limit of detection 25.29 ng/ sample from the step wise
dilution for the minimum concentration in the linear dynamic range of the
calibration graph with RSD % lower than 1.5% for 8 mmol.L-1 (n=5) concentration
of cadmium (II). The method was applied successfully for the determination of
cadmium (II) in three river samples. A comparison was made between the proposed
method of analysis with the classical method (HANNA instrument for turbidity
measurement) using the standard additions method via the use of ANOVAtreatments.
It was noticed that there is a significant difference at α=0.05 between the
two methods at level < 0.05 was obtained. On that basis the new method can be
accepted as an alternative analytical method.
This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).
Many fuzzy clustering are based on within-cluster scatter with a compactness measure , but in this paper explaining new fuzzy clustering method which depend on within-cluster scatter with a compactness measure and between-cluster scatter with a separation measure called the fuzzy compactness and separation (FCS). The fuzzy linear discriminant analysis (FLDA) based on within-cluster scatter matrix and between-cluster scatter matrix . Then two fuzzy scattering matrices in the objective function assure the compactness between data elements and cluster centers .To test the optimal number of clusters using validation clustering method is discuss .After that an illustrate example are applied.
Lattakia city faces many problems related to the mismanagement of solid waste, as the disposal process is limited to the random Al-Bassa landfill without treatment. Therefore, solid waste management poses a special challenge to decision-makers by choosing the appropriate tool that supports strategic decisions in choosing municipal solid waste treatment methods and evaluating their management systems. As the human is primarily responsible for the formation of waste, this study aims to measure the degree of environmental awareness in the Lattakia Governorate from the point of view of the research sample members and to discuss the effect of the studied variables (place of residence, educational level, gender, age, and professional status) o
... Show More
(1)
