Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning algorithms implementation in the recurrent stroke prediction models. This research aims to investigate and compare the performance of machine learning algorithms using recurrent stroke clinical public datasets. In this study, Artificial Neural Network (ANN), Support Vector Machine (SVM) and Bayesian Rule List (BRL) are used and compared their performance in the domain of recurrent stroke prediction model. The result of the empirical experiments shows that ANN scores the highest accuracy at 80.00%, follows by BRL with 75.91% and SVM with 60.45%.
The estimation of the parameters of Two Parameters Gamma Distribution in case of missing data has been made by using two important methods: the Maximum Likelihood Method and the Shrinkage Method. The former one consists of three methods to solve the MLE non-linear equation by which the estimators of the maximum likelihood can be obtained: Newton-Raphson, Thom and Sinha methods. Thom and Sinha methods are developed by the researcher to be suitable in case of missing data. Furthermore, the Bowman, Shenton and Lam Method, which depends on the Three Parameters Gamma Distribution to get the maximum likelihood estimators, has been developed. A comparison has been made between the methods in the experimental aspect to find the best meth
... Show MoreSorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.
ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data
... Show MoreConcentrated research topic in the study of variables key to the work of offices of inspectors Amyin ، a (re- design function، and performance Organisational ) and took this message to know the nature of the relationship and the impact of the dimensions of the re- design function as a variable interpretative through its dimensions، is ( the diversity of skill، selecting the task ، the importance of task، autonomy، feedback )، and performance Organisational variable responsive through two dimensions are ( effectiveness ، efficiency )، and in order to test the research hypotheses were absorbed variables in the form of a questionnaire and were questionnaire primary means of gatheri
... Show MoreImprovisation is that spontaneous automatic achievement which is formed by a new cognition that is not based on something prior to it or a previous cognition. It is instantaneous. Whereas in art, improvisation also inters in all types of applied and performance arts as a foundation for launching and initiating it in music, painting, cinema, television and theater. In order to study the improvisation of the actor, the researcher put forward a theoretical study that included two sections. The first section is (the improvisation concept) and the second section is (improvisation in the show). The researcher, in the research procedures, took an intentional sample that was represented by the theatrical show (Rehearsal in Hell Play) and after t
... Show MoreThe concept of deficit in public budget becomes a chronic economic phenomenon in most of the world, whether the advanced countries or developing countries. Despite the difference in the visions of the economic schools to accept or reject the deficit in public budget but the opinion that prevailed is the necessity of the state to reduce the public spending which led to a continuous deficits in the public budget which consequently increased the government borrowing ,increase income taxes and wealth, consequently this weakened the in motivation in private investment which contributed to the increase of in factionary stagnation , so that governments have to cover the lack of local funding sources which become difficult to be eq
... Show MoreThe current research seeks to achieve several objectives, including knowing the extent of the audit directorate of the Ministry of Construction, Housing and General Municipalities of the International Standard (ISO19011:2018) regarding determining the efficiency and evaluation of auditors and diagnosing the gap between requirements and application and knowing the reasons for not applying some of the items in the standard, starting from the problem, The field raised the following question (Does the audit directorate determine the efficiency and evaluation of auditors according to the standard ISO19011:2018?), and the importance of research lies in determining the return that can be achieved by the directorate through its application of stand
... Show MoreThe study aims to measure the level of academic stress in the e-learning environment in three areas, students and their dealing with classmates, dealing with the professor and technical skills, and the nature and content of the curriculum among graduate students in the College of Education at King Khalid University during COVID-19 pandemic. This study was descriptive in nature (survey, comparative). The sample consisted of (512) male and female graduate students in the master's and doctoral programs. The Academic Stress Scale in the E-learning Environment designed by Amer (2021) was used. The results indicated a high level of academic stress among graduate students in the e-learning environment. The study also found that there were stati
... Show MoreIn the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A
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