In many of the studies concerning Accelerated life testing (ALT), the log linear function between life and stress which is just a simple re-parameterization of the original parameter of the life distribution is used to obtain the estimates of original parameters but from the statistical point of view, it is preferable to work with the original parameters instead of developing inferences for the parameters of the log-linear link function. In this paper the geometric process is used for the analysis of accelerated life testing under constant stress for Pareto Distribution. Assuming that the lifetimes under increasing stress levels form a geometric process, estimates of the parameters are obtained by using the maximum likelihood method for complete data. In addition, asymptotic interval estimates of the parameters of the distribution using Fisher information matrix are also obtained. The statistical properties of the parameters and the confidence intervals are illustrated by a Simulation study.

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Women of all over the world suffer from a common cancer, named Cervical cancer. Cervical cancer cells grow slowly at the cervix. This cancer can be avoided if it is recognized and handled in its first stage. Now it is a key challenge for Medical experts to identify such cancer before it develops extremely. Nowadays, data mining models are popularly used to extract hidden patterns from huge medical dataset. This paper introduces data mining techinques for classification and finding associations in order to detect Cervical cancer at early stage. After preprocessing, the dataset was tested on Decision Tree, Random Forest, Logistic Model Tree and Artificial Neural Network. These methods achieve considerable success in case of both K-fold cross validations and randomly split dataset. Association rules has been established for detecting comparatively riskier factors which are more responsible for cancer development. The proposed methodology can help Medical experts to conduct their research on Cervical cancer.

Aluminum wire mat reinforced polyester composite has been studied as an alternative structural material. The physical and mechanical properties of the composite such as tensile strength, flexural strength, water absorption, hardness illustrated the competency of the developed composite. It was found that percent water absorption is very low for the resultant studied composite. However, water absorption increased very slowly when metal mat layers were increased. Furthermore, mechanical strength of the composite was increased as mechanical properties: tensile strength, flexural strength, hardness and stiffness of this composite increased with the increase in the number of metal mat layer in the composite. This study suggested the use of this composite as an unbeaten alternative structural material to conventional materials.