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.

A Factorial Study for separation anxiety in students, of Baghdad City

The textbook is the primary means of creativity and thinking, which has a major role in the development of the readership and mental abilities of the student. It is the basic tool in education in Iraq for the teacher and the student, which cannot be dispensed in any educational program. The current study aimed at the book of the biology of the sixth grade of science in Iraq (comparative study). It was compared to the book of biology for the twelve grade in the Kingdom of Jordan to identify the ratio of similarity and differences between them, in addition, to identify the weaknesses in the Iraq curriculum and developing appropriate solutions and suggestions to address them. The sample was represented with books of biology (six-science cla

            Human Interactive Proofs (HIPs) are automatic inverse Turing tests, which are intended to differentiate between people and malicious computer programs. The mission of making good HIP system is a challenging issue, since the resultant HIP must be secure against attacks and in the same time it must be practical for humans. Text-based HIPs is one of the most popular HIPs types. It exploits the capability of humans to recite text images more than Optical Character Recognition (OCR), but the current text-based HIPs are not well-matched with rapid development of computer vision techniques, since they are either vey simply passed or very hard to resolve, thus this motivate that

Recently, all over the world mechanism of cloud computing is widely acceptable and used by most of the enterprise businesses in order increase their productivity. However there are still some concerns about the security provided by the cloud environment are raises. Thus in this our research project, we are discussing over the cloud computing paradigm evolvement for the large business applications like CRM as well as introducing the new framework for the secure cloud computing using the method of IT auditing. In this case our approach is basically directed towards the establishment of the cloud computing framework for the CRM applications with the use of checklists by following the data flow of the CRM application and its lifecycle. Those ch

This paper proposes a self organizing fuzzy controller as an enhancement level of the fuzzy controller. The adjustment mechanism provides explicit adaptation to tune and update the position of the output membership functions of the fuzzy controller. Simulation results show that this controller is capable of controlling a non-linear time varying system so that the performance of the system improves so as to reach the desired state in a less number of samples.

Background: Nursing interventions tailored to the smoking triggers in patients with non-communicable chronic diseases are essential. However, these interventions are scant due to the nature of factors associated with smoking cessation and the poor understanding of the effect of nurse-led intervention in Iraq.Purpose: This study aimed to determine the dominant smoking triggers and examine the effects of a tailored nursing intervention on smoking behavior in patients with non-communicable chronic diseases.Methods: Convenience samples of 128 patients with non-communicable chronic diseases, male and female patients, who were 18-70 years old, were recruited in this quasi-experimental, randomized comparative trial in the outpatient clinic

Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has