The main goal of this paper is to introduce the higher derivatives multivalent harmonic function class, which is defined by the general linear operator. As a result, geometric properties such as coefficient estimation, convex combination, extreme point, distortion theorem and convolution property are obtained. Finally, we show that this class is invariant under the Bernandi-Libera-Livingston integral for harmonic functions.
Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca
... Show MoreBreast cancer is among the primary causes of death among Iraqi women and is a serious worldwide health concern. ALK or anaplastic lymphoma kinase, is connected to several cancers, including breast cancer.. The goal of this research was to assess the prevalence of anaplastic lymphoma kinase (ALK) with Alkaline phosphatise (ALP) and Lactate dehydrogenase (LDH) together as diagnostic markers. The study comprised 60 patients with metastatic breast cancer and 60 healthy volunteers. The blood levels of the enzymes (ALP), (LDH), and ALK in Iraqi breast cancer patients are compared to those of healthy controls. It was shown that compared to healthy people, patients had breast cancer noticeably greater levels of ALK, ALP, and NDH .These biomarkers m
... Show MoreThe logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables. The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.
... Show MoreThis research aims at answering many questions raised by the research problem concerning the view of the organizations under consideration for the concept of smart leadership and its most important dimensions, as well as the view of crisis management and its concept and most important methods through research objectives that define and clarify the smart leadership with its dimensions and methods of crisis management.
For the purpose of reaching the results of the research and testing the assumptions about the relationship between smart leadership and methods of crisis management, the researcher adopted a questionnaire, designed especially to be a criterion for the research, as the main tool for data coll
... Show MoreNowadays, Wheeled Mobile Robots (WMRs) have found many applications as industry, transportation, inspection, and other fields. Therefore, the trajectory tracking control of the nonholonomic wheeled mobile robots have an important problem. This work focus on the application of model-based on Fractional Order PIaDb (FOPID) controller for trajectory tracking problem. The control algorithm based on the errors in postures of mobile robot which feed to FOPID controller to generate correction signals that transport to torque for each driven wheel, and by means of dynamics model of mobile robot these torques used to compute the linear and angular speed to reach the desired pose. In this work a dynamics model of
... Show MoreThis paper presents a new algorithm in an important research field which is the semantic word similarity estimation. A new feature-based algorithm is proposed for measuring the word semantic similarity for the Arabic language. It is a highly systematic language where its words exhibit elegant and rigorous logic. The score of sematic similarity between two Arabic words is calculated as a function of their common and total taxonomical features. An Arabic knowledge source is employed for extracting the taxonomical features as a set of all concepts that subsumed the concepts containing the compared words. The previously developed Arabic word benchmark datasets are used for optimizing and evaluating the proposed algorithm. In this paper,
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