Analysis of lifetime datasets has always been the burning need of a variety of fields to study system reliability. The Pareto-Raleigh (PR) distribution is considered to be a potential candidate
to model lifetime datasets. Recently, the uniformly minimum variance unbiased estimators, maximum likelihood estimators, percentile estimators, least squares estimators and weighted
least squares estimators for the parameters of the PR distribution with known scale parameter and unknown shape parameter. These methods don’t have the capacity to model the uncertainty
associated with the parameters of interest. In this paper, both of the scale and shape parameters of the PR distribution are assumed unknown and are evaluated in Bayesian estimation that has the potential to accommodate the uncertainty appearing in the parameters. The entire estimation procedure is exemplified using real datasets and the posterior summaries are presented. The behavior of different combinations of parametric values is evaluated in terms of relative bias, mean square errors (MSE) and with of confidence and credible intervals for increasing sample sizes by Markov Chain simulations. The comparison of the classical and Bayesian estimation methods is made using different model selection criteria. The analysis of read dataset is also presented for illustration.

Poverty was one of the biggest social problems in the twentieth century and continues to be in present century. Very few would deny that human miseries amidst the plenty, especially when they can be unraveled through collective actions, should not be related. Poverty encompasses low levels of health and education, poor access to clean water and sanitation, inadequate physical security, lack of voice, insufficient capacity and opportunity improve one’s life. In the present research, while reviewing the concepts of poverty, various approaches to poverty and its related issues such as education, health, housing and etc. are considered. Finally, measuring poverty from different researchers’ views and their critical perspectives are discussed.

Abstract
Poverty is a condition in which a person or community lacks the fundamentals for having a minimum standard of well-being and life. These fundamentals may be material resources such as food, safe drinking water and shelter or they may include social resources like access to information, education, health care, social status and political power, or the opportunity to develop meaningful connections with other people in society. Poverty amid plenty is the world\'s greatest challenge and eradicating poverty is an ethical, social, political and economic imperative of humankind. To eliminate or reduce poverty it should be measured. The aim of measuring poverty is usually to make economic status comparisons between two or more groups. The present research examined the measures of poverty and then consequences and different aspects of poverty were regarded. Finally poverty reduction and critiques of the poverty measure were described.

The four sources of Islamic knowledge and wisdom of the Koran is the consensus of the Quran and Sunnah and the consensus of the original sources and secondary sources of Islamic law are the reason. The research-based marketing management resources can be based on Islamic values. If you do marketing in the context of Islamic law, has always faced criticism for unethical issues in this critical area of marketing activities. In this article we can say that marketing ethics, a growing role to play in improving the activities of marketing executives. The model is also designed on the basis of market values will be introduced.

More personal software is our permanent goal. This means that more people should be concerned with cryptography. We think that the encoding of cryptographic algorithms important step in it.
In this paper, our choice is encoding operation “Point addition and Point doubling” on an Eliptic curve, over finite field Fp (E(FP))- where p is odd prime, in order to intensify interest in ECC-Elipse curve cryptography.

The present paper highlights aspects upon the stage reached by some possible trends of development of tourism in the Danube Delta, established in different studies and researches, as well as suggestions in successfully reaching them in order to eliminate dysfunction. Agritourism, as an economic activity has gained its recognition and importance in the national economy because of the social role it plays due to the natural resources potential and also to the species biodiversity that are to be found in our country\'s waters. In some isolated areas, such as the Danube Delta and the Danube Plain, fishing and agritourism are the main activities that provide jobs and income sources for local populations.

The article is devoted to the history of the establishment and operation of institutions of higher education for minorities that existed in 1920-1930s.: the Communist University for the Toilers of the East, the Communist University of the Toilers of China and the Communist University of National Minorities of the West. The reasons and prerequisites of their appearance, distinctive features are analyzed. The aims and objectives, structure, curriculum, student and faculty dates of the universities are considered. This article uses historical documents, not previously introduced to the scientific revolution.

Data clustering is the process of partitioning data objects into a number of clusters. Clustering is one of the most important tasks in data mining. K-means (KM) clustering algorithm is an iterative and well known distance based clustering method. KM is a hard competitive learning algorithm that has two main drawbacks. KM is sensitive to cluster centers initialization, and is easily trapped in local optima. Fuzzy K-means (FKM) clustering solves the problem of initialization in KM but it also easily converges at local optima. In this paper, we proposed a new clustering algorithm called ICAFKM based on Imperialist Competitive Algorithm (ICA) and FKM algorithm which combined the advantageous aspects of ICA and FKM. ICA is a new global search algorithm that introduced for dealing with different optimization tasks. ICA has shown great performance in both convergence rate and better global optimal achievement. Our proposed ICAFKM algorithm helps the FKM to escape from local optimal and has high convergence speed. We compared the proposed ICAFKM with PSOFKM (Particle Swarm Optimization Algorithm and FKM) algorithm and reported experimental results on well-known data sets demonstrate the high efficiency of the ICAFKM algorithm.