The logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis .                                                

The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result.    &nbs

  Weibull distribution is considered as one of the most widely  distribution applied in real life, Its similar to normal distribution in the way of applications, it's also considered as one of the distributions that can applied in many fields such as industrial engineering to represent replaced and manufacturing time ,weather forecasting, and other scientific uses in reliability studies and survival function in medical and communication engineering fields.

   In this paper, The scale parameter has been estimated for weibull distribution using Bayesian method based on Jeffery prior information as a first method , then enhanced by improving Jeffery prior information and then used as a se

Background: Due to the variations in tooth anatomy and size among different populations, this study aimed to compare the mesiodistal width of primary second molars in Iraqi children with the mesiodistal width of stainless-steel crowns from different companies. Materials and Methods: This cross-sectional study was conducted on 220 intact maxillary and mandibular primary second molars selected from boys and girls’ Iraqi children aged 8-9 years collected from different primary schools in Baghdad city. The mesiodistal dimensions of the selected teeth and the available maxillary and mandibular stainless-steel crowns from three different companies were measured by using a 3-D scanner, and then the whole measurements were calculated usin

International law is no longer suffering from violations alone. It is confronting a deeper crisis of credibility: a widening belief that rules that still exist on paper no longer bind the most powerful states in practice.

With the continuous downscaling of semiconductor processes, the growing power density and thermal issues in multicore processors become more and more challenging, thus reliable dynamic thermal management (DTM) is required to prevent severe challenges in system performance. The accuracy of the thermal profile, delivered to the DTM manager, plays a critical role in the efficiency and reliability of DTM, different sources of noise and variations in deep submicron (DSM) technologies severely affecting the thermal data that can lead to significant degradation of DTM performance. In this article, we propose a novel fault-tolerance scheme exploiting approximate computing to mitigate the DSM effects on DTM efficiency. Approximate computing in hardw

A confluence of forces has brought journalism and journalism education to a precipice. The rise of fascism, the advance of digital technology, and the erosion of the economic foundation of news media are disrupting journalism and mass communication (JMC) around the world. Combined with the increasingly globalized nature of journalism and media, these forces are posing extraordinary challenges to and opportunities for journalism and media education. This essay outlines 10 core principles to guide and reinvigorate international JMC education. We offer a concluding principle for JMC education as a foundation for the general education of college students.

To ensure fault tolerance and distributed management, distributed protocols are employed as one of the major architectural concepts underlying the Internet. However, inefficiency, instability and fragility could be potentially overcome with the help of the novel networking architecture called software-defined networking (SDN). The main property of this architecture is the separation of the control and data planes. To reduce congestion and thus improve latency and throughput, there must be homogeneous distribution of the traffic load over the different network paths. This paper presents a smart flow steering agent (SFSA) for data flow routing based on current network conditions. To enhance throughput and minimize latency, the SFSA distrib

According to the importance of the conveyor systems in various industrial and service lines, it is very desirable to make these systems as efficient as possible in their work. In this paper, the speed of a conveyor belt (which is in our study a part of an integrated training robotic system) is controlled using one of the artificial intelligence methods, which is the Artificial Neural Network (ANN). A visions sensor will be responsible for gathering information about the status of the conveyor belt and parts over it, where, according to this information, an intelligent decision about the belt speed will be taken by the ANN controller. ANN will control the alteration in speed in a way that gives the optimized energy efficiency through