This paper presents a fuzzy logic controller for a two-tank level control system, which is a process with a dead time. The fuzzy controller is a proportional-integral (PI-like) fuzzy controller which is suitable for steady state behavior of the system. Transient behavior of the system was improved without the need for a derivative action by suitable change in the rule base of the controller. Simulation results showed the step response of the two-tank level control system when this controller was used to control this plant and the effect of the dead time on the response of the system.

One of the important goals in the learning process is to be effective learning through the self-direction of the learner , because it has an impact on the effort of learners , it is better to be a learner responsible for learning and independent of the acquisition of knowledge ,

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Pleomorphic adenoma (PA) is the most frequent benign epithelial neoplasm of salivary glands, displaying a remarkable degree of morphological variety. The aim of the study is to illustrate the clinicopathological characteristics of PA with particular emphases on epithelial cell morphology and mesenchymal elements. Materials and Methods: A total of 132 PA collected between 2002 and 2017 were recruited from Al Shahid Ghazi Al Hariri Hospital and the Department of Oral Pathology, College of Dentistry, Baghdad University, Baghdad, Iraq, and analyzed for their demographic and histopathological features. All data were analyzed using descriptive statistics. A slightly higher incidence of PA was detected in females (52.3%) compared to male subject

Due to the high mobility and dynamic topology of the FANET network, maintaining communication links between UAVs is a challenging task. The topology of these networks is more dynamic than traditional mobile networks, which raises challenges for the routing protocol. The existing routing protocols for these networks partly fail to detect network topology changes. Few methods have recently been proposed to overcome this problem due to the rapid changes of network topology. We try to solve this problem by designing a new dynamic routing method for a group of UAVs using Hybrid SDN technology (SDN and a distributed routing protocol) with a highly dynamic topology. Comparison of the proposed method performance and two other algorithms is simula

Purpose: The research seeks to develop the implications of intellectual human capital, and social capital in business organizations, and will be accomplished on three levels, the first level (the level of description) to identify, diagnose and display content philosophical Strategic Human Resource Management at the thought of modern administrative represented by human capital and Ras social capital. The second level (level of analysis) and the analysis of the extent of the impact of alignment between human capital, and social capital in the organizational strength of the organizations. The third level (Level predict) the formulation of a plan to strengthen the organizational strength in business organizations and to develop speci

This paper deals with defining Burr-XII, and how to obtain its p.d.f., and CDF, since this distribution is one of failure distribution which is compound distribution from two failure models which are Gamma model and weibull model. Some equipment may have many important parts and the probability distributions representing which may be of different types, so found that Burr by its different compound formulas is the best model to be studied, and estimated its parameter to compute the mean time to failure rate. Here Burr-XII rather than other models is consider  because it is used to model a wide variety of phenomena including crop prices, household income, option market price distributions, risk and travel time. It has two shape-parame

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se