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In this article, a new class of weighted exponential distribution called Entropy-Based Exponential weighted distribution (EBEWD) is proposed. The main idea of the new lifetime distribution is in using the Shannon entropy measure as a weighted function. The mathematical properties of the EBEWD, such as reliability measures, moment measures, variability measures, shapes measures, entropy measures and Fisher’s information, were derived. The unknown parameters of the proposed distribution were estimated using the maximum likelihood estimation method. The efficiency and flexibility of the EBEWD were examined numerically and then by a real-life data application. The results revealed that the EBEWD outperforms some existing distributions in terms of their test statistics.

This article proposes a new estimation method to fit the structural regression model when the variables are subject to errors. The new estimation method is the extension of theWald estimation method and involves iterative process. Several Monte Carlo simulation experiments were used to study the performance of the proposed estimators. The results were compared with the classical Wald estimation method in terms of its root mean square error (RMSE). In addition, an application for examining the relationships between Jordan's national gross domestic product (GDP) and its human development index (HDI) was presented. Numerical results showed that the GDP and HDI have a strong positive and significant correlation. Moreover, the proposed procedures with different subgroup sizes (r =3 and r =4) gave more accurate estimators than the classical estimation methods in fitting the relationships between GDP and HDI. [ABSTRACT FROM AUTHOR]

In environmental and many other areas, the main focus of survey is to measure elements using an efficient and cost-effective sampling technique. One way to reach that is by using Ranked set sampling (RSS). RSS is an alternative sampling technique that can be advantageous when measuring the variable of interest is either costly or time-consuming but ranking small sets of units according to the character under investigation by eye or other methods not requiring actual quantifications. The purpose of this article is to introduce a new modification of RSS to estimate the mean of the target population. This proposed technique is a double-stage approach that combines median RSS (MRSS) and MiniMax RSS (MMRSS). The performance of the empirical mean and variance estimators based on the proposed technique are compared with their counterparts in Double RSS (DRSS), Extreme RSS (ERSS), Double Extreme RSS (DERSS), MMRSS, RSS, and simple random sampling (SRS) via Monte Carlo simulation. Simulation results revealed that this new modification is almost always more efficient than their counterparts using MMRSS and SRS, while it is more efficient than RSS in many cases especially when the distribution is asymmetric. [ABSTRACT FROM AUTHOR]

In this paper, truncated lifetime testing is considered, and new single acceptance sampling plans (SASP) are proposed assuming that the lifetime distribution is the q-Weibull distribution of a product. Assuming a finite population size (limited population size, N); the inspection process for a single sampling plan is ASP(n,p) begins by choosing a simple random sample from a given lot, then based on pre-assigned quality standards, the manager will decide to reject the lot if some items fail to meet the pre-assigned quality standards. Since the population is limited; then this experiment meets the hypergeometric distribution assumptions. The hypergeometric theory is applied to compute the probability of acceptance, and the procedure is used to compute the minimum sample size and the operating characteristics of the sampling plans. Also, a real data analysis is given to illustrate the applicability of the proposed plan in the industry. [ABSTRACT FROM AUTHOR]

The research is aimed at evaluating the process of urbanization and it's spatio-temporal impacts on albedo and the changing climate of the Punjab. Climate change in urban areas has become a public focal point, as urban development in our present-day environment is one of the most critical aspects of human activities. The shift in the reflective properties of the surface is one of the particular climatic consequences of urbanization which most researchers have overlooked (Albedo). Changes in urbanized land surface properties resulted in a global, regional, and local change s in biochemical cycles and environment. This analysis aims to identify the urban land use of the 1990-2018 study area (decadal) and evaluate Albedo and Climatic Variables' trends over the selected region. This study will provide a complete code of classification in Google Earth Engine for researchers. In Google Earth Engine, the classification technique was utilized to detect urban areas and barren land cover types by applying coding over four images of 1990, 2000, 2010, and 2018 of Punjab Province. The Albedo maps were created in the same way for the years 2000 and 2018. Climatic maps were created from 1990 to 2018 by applying the Inverse Distance Weighted method in a GIS system. There has been an apparent increase in the urban area of Punjab Province from 1990 to 2018. The urban area has increased from 1183.5342 km2 to 8396.4618 km2 during the study period. Results from climatic maps showed hotspots in the areas that have undergone urbanization. Overall, the accuracy of the classification images was 81-88 percent, which was foremost to achieve the objectives of the research. [ABSTRACT FROM AUTHOR]