Methods of estimating statistical distribution have attracted many researchers when it comes to fitting a specific distribution to data. However, when the data belong to more than one component, a popular distribution cannot be fitted to such data. To tackle this issue, mixture models are fitted by choosing the correct number of components that represent the data. This can be obvious in lifetime processes that are involved in a wide range of engineering applications as well as biological systems. In this paper, we introduce an application of estimating a finite mixture of Inverse Rayleigh distribution by the use of the Bayesian framework when considering the model as Markov chain Monte Carlo (MCMC). We employed the Gibbs sampler and

Polyaniline membranes of aniline were produced using an electrochemical method in a cell consisting of two poles. The effect of the vaccination was observed on the color of membranes of polyaniline, where analysis as of blue to olive green paints. The sanction of PANI was done by FT-IR and Raman techniques. The crystallinity of the models was studied by X-ray diffraction technique. The different electronic transitions of the PANI were determined by UV-VIS spectroscopy. The electrical conductivity of the manufactured samples was measured by using the four-probe technique at room temperature. Morphological studies have been determined by Atomic force microscopy (AFM). The structural studies have been measured by (SEM).

Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

نُفذت تجربة حقلية في أحد الحقول التي تقع على خط عرض 1333 59.93 شمالاً، وخط طول 37.913744" شرقاً، وعلى ارتفاع 31 م فوق مستوى سطح البحر خلال الموسم الخريفي لسنة 2018م لمعرفة تأثير نظم الحراثة المختلفة في إنتاجية الماء ونمو وحاصل الحنطة تحت التسوية الليزرية للارض ، استعملت في التجربة ثلاث معاملات المعاملة الأولى: الآت الحراثة وبمستويين هما المحراث المطرحي (T)، والمحراث الحفار (T2). إمَّا المعاملة الثانية نسبة انحدار تسوية سطح

Zinc Oxide thin film of 2 μm thickness has been grown on glass substrate by pulsed laser deposition technique at substrate temperature of 500 oC under the vacuum pressure of 8×10-2 mbar. The optical properties concerning the absorption, and transmission spectra were studied for the prepared thin film. From the transmission spectra, the optical gap and linear refractive index of the ZnO thin film was determined. The structure of the ZnO thin film was tested with X-Ray diffraction and it was formed to be a polycrystalline with many peaks.

The effect of solution heat treatment on the mechanical properties of Aluminum-Copper alloy. (2024-T3) by the rolling process is investigated. The solution heat treatment was implemented by heating the sheets to 480 C° and quenching them by water; then forming by rolling for many passes. And then natural aging is done for one month. Mechanical properties (tensile strength and hardness) are evaluated and the results are compared with the metal without treatment during the rolling process. ANSYS analysis is used to show the stresses distribution in the sheet during the rolling process.  It has been seen that good mechanical properties are evident in the alloy without heat treatment due to the strain hardening and also the mechanical

In this paper a new idea was introduced which is finding a new distribution from other distributions using mixing parameters; w_i  where  0 < w_i < 1 ­and . Therefore we can get many mixture distributions with a number of parameters. In this paper I introduced the idea of a mixture Weibull distribution which is produced from mixing two Weibull distributions; the first with two parameters, the scale parameter , and the shape parameter,  and the second also has the scale parameter , and the shape parameter,  in addition to the location parameter, . These two distributions were mixed using a new parameter which is the mixing parameter w which represents the proportion