In this research, a mathematical model of tumor treatment by radiotherapy is studied and a new modification for the model is proposed as well as introducing the check for the suggested modification. Also the stability of the modified model is analyzed in the last section.

Activated carbon was Produced from coconut shell and was used for removing sulfate from industrial waste water in batch Processes. The influence of various parameter were studied such as pH (4.5 – 9.) , agitation time (0 – 120)min and adsorbent dose (2 – 10) gm.

The Langmuir and frandlich adsorption capacity models were been investigated where showed there are fitting with langmmuir model with squre regression value ( 0.76). The percent of removal of  sulfate (22% - 38%) at (PH=7) in the isotherm experiment increased  with adsorbent mass increasing. The maximum removal value of sulfate at  different pH experiments is (43%) at pH=7.

In this article, performing and deriving te probability density function for Rayleigh distribution is done by using ordinary least squares estimator method and Rank set estimator method. Then creating interval for scale parameter of Rayleigh distribution. Anew method using   is used for fuzzy scale parameter. After that creating the survival and hazard functions for two ranking functions are conducted to show which one is beast.

               Microalgae have been used widely in bioremediation processes to degrade or adsorb toxic dyes. Here, we evaluated the decolorization efficiency of Chlorella vulgaris and Nostoc paludosum against two toxic dyes, crystal violet (CV) and malachite green (MG). Furthermore, the effect of CV and MG dyes on the metabolic profiling of the studied algae has been investigated. The data showed that C. vulgaris was most efficient in decolorization of CV and MG: the highest percentage of decolorization was 93.55% in case of MG, while CV decolorization percentage was 62.98%. N. paludosum decolorized MG dye by 77.6%, and the decolorization percentage of CV was 35.1%. Metabolic profiling of

The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. T

The analysis of time series considers one of the mathematical and statistical methods in explanation of the nature phenomena and its manner in a specific time period.

Because the studying of time series can get by building, analysis the models and then forecasting gives the priority for the practicing in different fields, therefore the identification and selection of the model is of great importance in spite of its difficulties.

The selection of a standard methods has the ability for estimation the errors in the estimated the parameters for the model, and there will be a balance between the suitability and the simplicity of the model.

In the analysis of d

Simplification of new fashion design methods

Due to the availability of technology stemming from in-depth research in this sector and the drawbacks of other identifying methods, biometrics has drawn maximum attention and established itself as the most reliable alternative for recognition in recent years. Efforts are still being made to develop a user-friendly system that is up to par with security-system requirements and yields more reliable outcomes while safeguarding assets and ensuring privacy. Human age estimation and Gender identification are both challenging endeavours. Biomarkers and methods for determining biological age and gender have been extensively researched, and each has advantages and disadvantages. Facial-image-based positioning is crucial for many application

Thin films ZrO₂: MgO nanostructure have been synthesized by a radio frequency magnetron plasma sputtering technique at different ratios of MgO (0,6, 8 and  10)% percentage to be used as the gas sensor for nitrogen dioxide NO₂. The samples were investigated by X-ray diffraction (XRD), atomic force microscopy (AFM), scanning electron microscopy (SEM), energy-dispersive X-ray (EDX) and sensing properties were also investigated. The average particle size of all prepared samples was found lower than 33.22nm and the structure was a monoclinic phase. The distribution of grain size was found lower than36.3 nm and uninformed particles on the surface. Finally, the data of sensing properties have been discussed, where the