The modern steer-by-wire (SBW) systems represent a revolutionary departure from traditional automotive designs, replacing mechanical linkages with electronic control mechanisms. However, the integration of such cutting-edge technologies is not without its challenges, and one critical aspect that demands thorough consideration is the presence of nonlinear dynamics and communication network time delays. Therefore, to handle the tracking error caused by the challenge of time delays and to overcome the parameter uncertainties and external perturbations, a robust fast finite-time composite controller (FFTCC) is proposed for improving the performance and safety of the SBW systems in the present article. By lumping the uncertainties, parameter var

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The tax exemption, whether wholly or partially, and for an unlimited duration of the investment or for a limited period of few years, is one of the encouraging things to the flow of foreign capital. And if necessary, impose tax on the profits of the invested capital, the promotion requires that not be discriminatory taxes or payments in the amount of money with the need to avoid double taxation. The tax exemption is granted by the government and the feature according to the law of a natural person or legal entity seeking from the government purports to achieve a set of political goals, economic and  social development. The reduction of taxes or grants partial exemption is one of the factors that encourage attract of direct foreign i

Groupwise non-rigid image alignment is a difficult non-linear optimization problem involving many parameters and often large datasets. Previous methods have explored various metrics and optimization strategies. Good results have been previously achieved with simple metrics, requiring complex optimization, often with many unintuitive parameters that require careful tuning for each dataset. In this chapter, the problem is restructured to use a simpler, iterative optimization algorithm, with very few free parameters. The warps are refined using an iterative Levenberg-Marquardt minimization to the mean, based on updating the locations of a small number of points and incorporating a stiffness constraint. This optimization approach is eff

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

The infrastructure is one of the basic components of the tourism industry in Iraq in general and in Najaf in particular, in spite of there are obstacles and problems that which are hindered the development of tourism in Iraq, some of them are related to the  tourism industry itself, some are related to the security and political situation, and some are related to poor management of tourism. However, the infrastructure is considered the cornerstone of the success of the tourism industry in Iraq and other countries, if it is available, it can be a potential indicator of success, and on the contrary, it is a hindrance to go forward. The aim of this research is to shed light on the availability of requirements for the s

The increased size of grayscale images or upscale plays a central role in various fields such as medicine, satellite imagery, and photography. This paper presents a technique for improving upscaling gray images using a new mixing wavelet generation by tensor product. The proposed technique employs a multi-resolution analysis provided by a new mixing wavelet transform algorithm to decompose the input image into different frequency components. After processing, the low-resolution input image is effectively transformed into a higher-resolution representation by adding a zeroes matrix. Discrete wavelets transform (Daubechies wavelet Haar) as a 2D matrix is used but is mixed using tensor product with another wavelet matrix’s size. MATLAB R2021