The deliberation and exchanged of power is a matter of political importance For the Iraqi political system after 2003, The deliberation of power and its democratic transition and electoral integrity Is a good indicator of political stability and progress In the Iraqi parliamentary political system , The transfer of authority in terms of adopting the deliberative approach represents a structural and institutional dimension of the political process , it led the power to become Authority of the Foundation Exercised in accordance with the Constitution and the law not real power , And lead to the recognition of the existence of an official parliamentary opposition and its right to take political power later through the ballot box Makes the pr

Abstract: In accordance with contemporary Western thinking, power is an organized force with a high ability to achieve stability and social security because it possesses tools based on rational organization, which helps it to control the behavior of the individual and society and prevent them from practicing the processes of exclusion and discrimination against others in pursuit of their interests and needs. Vision The philosophers and thinkers of the theory of social contract can consolidate it, which changed the form and nature of power from the traditional heritage to the constructionWhich has contributed to the development and development of civil society - Western political, and despite the success of this experiment, especially aft

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Debate is a teaching strategy in nursing education that enhances students' critical thinking. Although debate can be an effective teaching strategy, it is not without limitations. This article discusses the advantages and disadvantages of debate as a teaching strategy in nursing. Also, evaluating debates and choosing topics are highlighted. [ J Contin Educ Nurs . 2021;52(6):263–265.]

Wireless sensor applications are susceptible to energy constraints. Most of the energy is consumed in communication between wireless nodes. Clustering and data aggregation are the two widely used strategies for reducing energy usage and increasing the lifetime of wireless sensor networks. In target tracking applications, large amount of redundant data is produced regularly. Hence, deployment of effective data aggregation schemes is vital to eliminate data redundancy. This work aims to conduct a comparative study of various research approaches that employ clustering techniques for efficiently aggregating data in target tracking applications as selection of an appropriate clustering algorithm may reflect positive results in the data aggregati

Millions of lives might be saved if stained tissues could be detected quickly. Image classification algorithms may be used to detect the shape of cancerous cells, which is crucial in determining the severity of the disease. With the rapid advancement of digital technology, digital images now play a critical role in the current day, with rapid applications in the medical and visualization fields. Tissue segmentation in whole-slide photographs is a crucial task in digital pathology, as it is necessary for fast and accurate computer-aided diagnoses. When a tissue picture is stained with eosin and hematoxylin, precise tissue segmentation is especially important for a successful diagnosis. This kind of staining aids pathologists in disti

The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

This paper presents a proposed neural network algorithm to solve the shortest path problem (SPP) for communication routing. The solution extends the traditional recurrent Hopfield architecture introducing the optimal routing for any request by choosing single and multi link path node-to-node traffic to minimize the loss. This suggested neural network algorithm implemented by using 20-nodes network example. The result shows that a clear convergence can be achieved by 95% valid convergence (about 361 optimal routes from 380-pairs). Additionally computation performance is also mentioned at the expense of slightly worse results.