Interval methods for verified integration of initial value problems (IVPs) for ODEs have been used for more than 40 years. For many classes of IVPs, these methods have the ability to compute guaranteed error bounds for the flow of an ODE, where traditional methods provide only approximations to a solution. Overestimation, however, is a potential drawback of verified methods. For some problems, the computed error bounds become overly pessimistic, or integration even breaks down. The dependency problem and the wrapping effect are particular sources of overestimations in interval computations. Berz (see [1]) and his co-workers have developed Taylor model methods, which extend interval arithmetic with symbolic computations. The latter is an ef

This paper develops a fuzzy multi-objective model for solving aggregate production planning problems that contain multiple products and multiple periods in uncertain environments. We seek to minimize total production cost and total labor cost. We adopted a new method that utilizes a Zimmermans approach to determine the tolerance and aspiration levels. The actual performance of an industrial company was used to prove the feasibility of the proposed model. The proposed model shows that the method is useful, generalizable, and can be applied to APP problems with other parameters.

In the present study benzofuran based chalcones 1 (a, b) are synthesized by condensing aromatic aldehydes with 2-acetylbenzofuran in the presence suitable base. These chalcones are very useful precursors for the synthesis of pyrazoline, isoxazoline, pyrmidine, cyclohexenone and indazole derivatives. All these compounds are characterized by their melting points, FTIR and 1 HMNR (for some of them) spectral dat

The research aims to identify the obstacles facing the application of electronic management in our university libraries, including the central library of the University of Baghdad and the central library of Al-Mustansiriya University, the research sample, as they are among the main libraries that used electronic technologies in managing some of their work and in providing their services, and they have a website via the Internet. The research relied on the case study method to identify the obstacles by visiting the two libraries, interviewing their managers and employees responsible for the departments, and answering inquiries about the obstacles that prevent the application of electronic management in order to identify them and find appropr

One of the globalization results is (VAT) , so it is important to consider its        results and impact on the tax system.    

     The Iraqi economy having wittnisd an acute transition period , still in need for a better care in aim to back it, especialy from the tax system.

The research is concerned with the (VAT) and its details –And for five chapters all the problomes connect are displayed .But yet the new system does not comply with the modern development and this is one of the defects of (VAT) in Iraq.

The history of (VAT)was also studied mentiorned and studied.

     As a conclusion (VAT) is one of the m

Abstract

Leadership has now become a process for applying methods and techniques that make the Organization at the top of its competitive pyramid a greater market share. Leadership has become a focus for all leaders and managers، and leaders and managers are increasingly seeking to develop their skills and leadership skills. The research started with a clear problem of specific questions to ensure that the general objective of the research is to describe the characteristics of the leader and to clarify the dimensions of empowering the workers and to highlight the role of the leader in empowering the workers. The study examines the relation between the role of the leader in

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve