Growth in Islamic Economy

A major proof viewed by the Islamic universe today is the proof of re-making and reorganizing the economy in such a way seen as similar to the motivation of Sharia’h work. Money-related new development is one of the topics that in a general sense is termed as a science that offers a technique to show the science of monetary angles. Nevertheless, the standard technique, which has been assembled, is being considered for dissatisfaction in dealing with the issues of the Ummah, for example, despair, backwardness in human resources (HR), and achievement in proper position and life, and even a matter of natural change. Sadly, those conditions are found overwhelmingly in the Muslim world, where they have essentially manifested and represented in Muslim life. Moreover, it seems that the uniqueness of the Muslim world has been challenging, that is, it is typically rich in asset but still weak and poor. As for the path, in Muslim society, there is an ignorance of the achievements of motivation. Thus, there is no possible norm to find the emergence of different methodologies within the Islamic structure, surprisingly in the area of ​​money-related to unforeseen development.

Nonlinear Stochastic Analysis of Machinery Health Dynamics

Condition based maintenance of machinery is being much talked about in the engineering sector of defense and commercial industry. A lot of expenditure is generally incurred on condition monitoring of machinery to avoid unexpected downtimes and failures vis-à-vis optimizing machinery operation. The concept is ever evolving due to technological advancements as well as with the emergence of unique nature of defects in complex systems. The features of machinery health extracted through modern condition monitoring technologies helps in diagnostics of current health; however, utilizing the current data for prediction of future machinery state i.e Prognostics is a challenging task. Prognostic is one of the key elements of modern maintenance philosophies. Effective prognostic, from the machinery data, leads towards operational reliability, reduced machinery downtime, cost savings, secondary/catastrophic failures etc. Machinery health prognosis follows a sequential methodology inclusive of various processes ranging from data acquisition till remaining useful life estimation. Every step depicts distinct statistical features, which are helpful in estimating present and future health state of a machine. Various methodologies have been adopted by the researchers in an effort to precisely forecast/predict machinery health. Research in this area, where stochastic models have been applied, revealed encouraging results. In this thesis, we have presented three nonlinear stochastic models with their application on bearing health prognosis. These include Markov Switching Auto Regressive Model with Time Varying Regime Probabilities, Threshold Auto Regressive Model and Structural Break Point Classifier Model. The results showed that the applied models can be effectively utilized for data driven machinery health prognosis.