In this study, a low-cost biosorbent, dead mushroom biomass (DMB) granules, was used for investigating the optimum conditions of Pb(II), Cu(II), and Ni(II) biosorption from aqueous solutions. Various physicochemical parameters, such as initial metal ion concentration, equilibrium time, pH value, agitation speed, particles diameter, and adsorbent dosage, were studied. Five mathematical models describing the biosorption equilibrium and isotherm constants were tested to find the maximum uptake capacities: Langmuir, Freundlich, Redlich-Peterson, Sips, and Khan models. The best fit to the Pb(II) and Ni(II) biosorption results was obtained by Langmuir model with maximum uptake capacities of 44.67 and 29.17 mg/g for these two ions, respectively, w

The massive distribution and development in the digital images field with friendly software, that leads to produce unauthorized use. Therefore the digital watermarking as image authentication has been developed for those issues. In this paper, we presented a method depending on the embedding stage and extraction stag. Our development is made by combining Discrete Wavelet Transform (DWT) with Discrete Cosine Transform (DCT) depending on the fact that combined the two transforms will reduce the drawbacks that appears during the recovered watermark or the watermarked image quality of each other, that results in effective rounding method, this is achieved by changing the wavelets coefficients of selected DWT sub bands (HL or HH), followed by

Information security in data storage and transmission is increasingly important. On the other hand, images are used in many procedures. Therefore, preventing unauthorized access to image data is crucial by encrypting images to protect sensitive data or privacy. The methods and algorithms for masking or encoding images vary from simple spatial-domain methods to frequency-domain methods, which are the most complex and reliable. In this paper, a new cryptographic system based on the random key generator hybridization methodology by taking advantage of the properties of Discrete Cosine Transform (DCT) to generate an indefinite set of random keys and taking advantage of the low-frequency region coefficients after the DCT stage to pass them to

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Azo ligand 11-(4-methoxyphenyl azo)-6-oxo-5,6-dihydro-benzo[4,5] imidazo[1,2-c] quinazoline-9-carboixylic acid was derived from 4-methoxyaniline and 6-oxo-5,6-dihydro-benzo[4,5]imidazo[1,2-c]quinazoline-9-carboxylic acid. The presence of azo dye was identified by elemental analysis and spectroscopic methods (FT-IR and UV-Vis). The compounds formed have been identified by using atomic absorption in flame, FT.IR, UV-Vis spectrometry magnetic susceptibility and conductivity. In order to evaluate the antibacterial efficiency of ligand and its complexes used in this study three species of bacteria were also examined. Ligand and its complexes showed good bacterial efficiencies. From the obtained data, an octahedral geometry was proposed for all p

 

    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

&n

Speech is associated with all early term grammar - somewhat - talking about the beginnings of the emergence of grammar, its foundation, and the truth is that this period has remained obscure, what came of them was a novels dealt with a facilitator beginnings as, and this means that what was of grammatical terms in the period of the first generation of grammarians do not constitute in itself, but the initial harbingers of serious way as in the science, and the real beginning of the term grammar mature as orally were at Hebron and Sibawayh evident in the book, then the efforts of the grammarians available until after the term of grammar arrived to what it is .
In this area is (actor) a grammatical terminology, which won at the ancient s

     In the present work, the possibility of treating many types of radioactive sources was examined practically. Six types of sealed radioactive sources were selected: ¹³⁷Cs, ¹³³Ba, ⁹⁰Sr, ¹⁵²Eu, ²²⁶Ra, and ²⁴¹Am. The sources were exposed to a neutron flux emitted from ²⁴¹Am/Be source for 33 days. The results showed a measurable reduction of activity for ²²⁶Ra, ²⁴¹Am, and ¹⁵²Eu, while the other radionuclides, ¹³⁷Cs, ¹³³Ba, and ⁹⁰Sr, showed less response to neutron incineration.

Biomarkers to detect Alzheimer’s disease (AD) would enable patients to gain access to appropriate services and may facilitate the development of new therapies. Given the large numbers of people affected by AD, there is a need for a low-cost, easy to use method to detect AD patients. Potentially, the electroencephalogram (EEG) can play a valuable role in this, but at present no single EEG biomarker is robust enough for use in practice. This study aims to provide a methodological framework for the development of robust EEG biomarkers to detect AD with a clinically acceptable performance by exploiting the combined strengths of key biomarkers. A large number of existing and novel EEG biomarkers associated with slowing of EEG, reductio