Rehabilitation robots are widely recognized as vital for restoring motor function in patients with lower-limb impairments. A Modified Fractional-Order Proportional-Integral-Derivative (MFOPID) controller is proposed to improve trajectory tracking of a 2-DoF Lower Limb Rehabilitation Exoskeleton Robot (LLRER). The classical FOPID is augmented with a modified control formulation by which steady-state error is reduced and the transient response is sharpened. Controller gains and fractional orders were tuned offline using a hybrid metaheuristic Improved Elk Herd Optimization hybridized with Grey Wolf and Multi-Verse Optimization algorithms (IElk-GM) so that exploration and exploitation are balanced. Superiority over the classical FOPID

The main objective of this paper is to designed algorithms and implemented in the construction of the main program designated for the determination the tenser product of representation for the special linear group.

 To expedite the learning process, a group of algorithms known as parallel machine learning algorithmscan be executed simultaneously on several computers or processors. As data grows in both size andcomplexity, and as businesses seek efficient ways to mine that data for insights, algorithms like thesewill become increasingly crucial. Data parallelism, model parallelism, and hybrid techniques are justsome of the methods described in this article for speeding up machine learning algorithms. We alsocover the benefits and threats associated with parallel machine learning, such as data splitting,communication, and scalability. We compare how well various methods perform on a variety ofmachine learning tasks and datasets, and we talk abo

This research has been devoted to the objective and important issue which is the legal protection of the printing form of the newspaper in the Iraqi press.

As this issue constitutes the integrated unit of the printing format in addition to achieving legal protection for the illustrative image used in the press. Such matter, on both level the integrated unit of the printing format and the legal protection, is out of reach of study due to the comprehension of the subject is concerned.

Although there is a justification for dealing with both of them together as the explanatory image is one of the foundations on which the printing format of the newspaper is built. This case generates, at least, the same legal subject that appe

This study emphasizes the infinite-boundary integro-differential equation. To examine the approximate solution of the problem, two modified optimization algorithms are proposed based on generalized Laguerre functions. In the first technique, the proposed method is applied to the original problem by approximating the solution using the truncated generalized Laguerre polynomial of the unknown function, optimizing coefficients through error minimization, and transforming the integro-differential equation into an algebraic equation. In contrast, the second approach incorporates a penalty term into the objective function to effectively enforce boundary and integral constraints. This technique reduces the original problem to a mathematical optimi

Data generated from modern applications and the internet in healthcare is extensive and rapidly expanding. Therefore, one of the significant success factors for any application is understanding and extracting meaningful information using digital analytics tools. These tools will positively impact the application's performance and handle the challenges that can be faced to create highly consistent, logical, and information-rich summaries. This paper contains three main objectives: First, it provides several analytics methodologies that help to analyze datasets and extract useful information from them as preprocessing steps in any classification model to determine the dataset characteristics. Also, this paper provides a comparative st

The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

The study aimed at knowing the financial consumer about the available protection from financial and banking services, presenting, and examining the evidence of some indicators indicating the reality of financial inclusion in the Iraqi banking system. Therefore, the study sought to know the extent of the level of protection available to the financial consumer as a result of its use of financial and banking services by the Iraqi banking system, and what It is the reality of financial inclusion in the banking system by measuring some financial and banking indicators. The study relies on the two (analytical) and (descriptive) approaches based on the questionnaire form and the data issued by the Central Bank of Iraq (2017-2020). Watch

      In this study, the CR-39 detector technique was used, to estimate the uranium concentration from the soil in midland refineries Company (Doura refine (, Baghdad, Iraq. Uranium concentrations in soil samples have been measured using solid state nuclear track detector type CR-39.  Nine soil samples were collected from different areas within the Doura refinery and other soil samples were collected form Abu Tayara Street and ALshortaa District outside the refinery for comparison. The results showed variable values for uranium concentrations. The average value of uranium concentration was found to be 0.37 ppm in doura refinery. For areas outside the refinery, the concentration of uranium was 0.008 ppm. Thes