HM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023

 In this paper, we propose a method using continuous wavelets to study the multivariate fractional Brownian motion through the deviations of the transformed random process to find an efficient estimate of Hurst exponent using eigenvalue regression of the covariance matrix. The results of simulations experiments shown that the performance of the proposed estimator was efficient in bias but the variance get increase as signal change from short to long memory the MASE increase relatively. The estimation process was made by calculating the eigenvalues for the variance-covariance matrix of Meyer’s continuous wavelet details coefficients.

                   The Iraqi sports journalism has paid great attention to sports events through press coverage of all its forms and arts, especially the coverage of the World Cup of football which is one of the most watched events in the world. Thousands of journals are preparing for the immediate coverage of such event which is a daunting task in itself. Newspapers have devoted a wider space to this great event in its pages as well as the weakly sports newspapers work on issuing a daily special issue. The importance of this research sheds light on the coverage of major events such as World Cup in Iraqi newspapers. The topic is new

The conception and experimental assessment of a removable friction-based shear connector (FBSC) for precast steel-concrete composite bridges is presented. The FBSC uses pre-tensioned high-strength steel bolts that pass through countersunk holes drilled on the top flange of the steel beam. Pre-tensioning of the bolts provides the FBSC with significant frictional resistance that essentially prevents relative slip displacement of the concrete slab with respect to the steel beam under service loading. The countersunk holes are grouted to prevent sudden slip of the FBSC when friction resistance is exceeded. Moreover, the FBSC promotes accelerated bridge construction by fully exploiting prefabrication, does not raise issues relevant to precast co

Simulated annealing (SA) has been an effective means that can address difficulties related to optimization problems. is now a common discipline for research with several productive applications such as production planning. Due to the fact that aggregate production planning (APP) is one of the most considerable problems in production planning, in this paper, we present multi-objective linear programming model for APP and optimized by . During the course of optimizing for the APP problem, it uncovered that the capability of was inadequate and its performance was substandard, particularly for a sizable controlled problem with many decision variables and plenty of constraints. Since this algorithm works sequentially then the current state wi

This paper presents a robust control method for the trajectory control of the robotic manipulator. The standard Computed Torque Control (CTC) is an important method in the robotic control systems but its not robust to system uncertainty and external disturbance. The proposed method overcome the system uncertainty and external disturbance problems. In this paper, a robustification term has been added to the standard CTC. The stability of the proposed control method is approved by the Lyapunov stability theorem.  The performance of the presented controller is tested by MATLAB-Simulink environment and is compared with different control methods to illustrate its robustness and performance.

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a