The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample sizes (50, 100, 200). A comparison between non-linear SVM and two standard classification methods was illustrated using various compared features. Our study has shown that the non-linear SVM method gives better results by checking: sensitivity, specificity, accuracy, and time-consuming. © 2024 Author(s).
The study aimed to effect of speed and die holes diameter in the machine on feed pellets quality. In this study was measured pellet direct measurement (%), pellet lengths (%), pellet durability (%) and pellet water absorption (%). Three die speeds 280, 300, and 320 rpm, three diameters of die holes in the machine 3, 4, and 5 mm, have been used. The results showed that increasing the pellet die speeds from 280 to 300 then to 320 rpm led to a significant decrease in direct measurement, pellet durability, and pellet water absorption was increased, whereas it did not significantly affect the pellet lengths. Increasing the die holes diameter from 3 to 4 then to 5 mm led to a significant de
Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin
... Show MoreThe free zone or the free economy cities are cities with classification and functional specificity, although the history of the concept of these areas has been It dates back to distant eras, but the intellectual and philosophical construction with the support of intellectual approaches, the most important of which is globalization contributed to its rapid spread globally and taking a variety of forms and models. With the diversity of its formulas and objectives countries have competed in adopting the establishment of these areas, meanwhile The influence of related trends affected the contemporary formation of these sites. Therefore ,the research was directed focus on the importance of adopting a set of common indicators (collection
... Show MoreSelf-criticism is that a person confronts himself with his mistakes in order to reform and develop them for the better, motivate them and inspire hope in them to push them forward and continue to give in this life. The Holy Qur’an teaches us, through the models it cited in its verses, that this is through repentance, a feeling of remorse, and a determination to leave mistakes, and quit disobedience and sins, etc., and all this is done through constructive criticism, and at the same time, one must realize his strengths. , in order to succeed in preserving it and employing it in the right path that pleases God, His Messenger, himself and his society. This has been explained through an introduction, two topics and a conclusion, and God is t
... Show MoreThe researcher highlighted in his research on an important subject that people need, which is the excuse of ignorance in Islamic law. , As the flag of light and ignorance of darkness. Then the researcher lameness of the reasons for research in this subject as it is one of the assets that should be practiced by the ruler and the judge and the mufti and the diligent and jurisprudent, but the public should identify the issues that ignore ignorance and issues that are not excused even if claimed ignorance.
Then the researcher concluded the most important results, and recommendations that he wanted to set scientific rules for students of science and Muslims in general, to follow the issues of legitimacy and learn its provisions and i
The power generation of solar photovoltaic (PV) technology is being implemented in every nation worldwide due to its environmentally clean characteristics. Therefore, PV technology is significantly growing in the present applications and usage of PV power systems. Despite the strength of the PV arrays in power systems, the arrays remain susceptible to certain faults. An effective supply requires economic returns, the security of the equipment and humans, precise fault identification, diagnosis, and interruption tools. Meanwhile, the faults in unidentified arc lead to serious fire hazards to commercial, residential, and utility-scale PV systems. To ensure secure and dependable distribution of electricity, the detection of such ha
... Show MoreBackground: Unlike normal EEG patterns, the epileptiform abnormal pattern is characterized by different mor phologies such as the high-frequency oscillations (HFOs) of ripples on spikes, spikes and waves, continuous and sporadic spikes, and ploy2 spikes. Several studies have reported that HFOs can be novel biomarkers in human epilepsy study. S) Method: To regenerate and investigate these patterns, we have proposed three large scale brain network models (BNM by linking the neural mass model (NMM) of Stefanescu-Jirsa 2D (S-J 2D) with our own structural con nectivity derived from the realistic biological data, so called, large-scale connectivity connectome. These models include multiple network connectivity of brain regions at different
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