Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a very high accuracy and is quite robust. ESGD-SVM is used to analyze the heart disease dataset downloaded from Harvard Dataverse. The entire analysis was performed using the program R version 4.3.
The use of ultraviolet rays is one of the methods of treating surface contamination of many foods especially pickles. however, there are some side effects to its use, especially in high percentage oil food products, it is necessary to determine the appropriate doses and time periods to avoid deterioration of its oil physicochemical characteristics. this study was conducted to see the effect of ultraviolet rays 15W on some chemical properties of olive oil when using it to preserve green olive pickles, treated for 5, 10 and 15 min daily. green olive fruits Iraqi variety (al-ashrasi), in season (2020-2021) were pickled using Spanish style, the best time period to pr
... Show MoreAnalysis of variance (ANOVA) is one of the most widely used methods in statistics to analyze the behavior of one variable compared to another. The data were collected from a sample size of 65 adult males who were nonsmokers, light smokers, or heavy smokers. The aim of this study is to analyze the effects of cigarette smoking on high-density lipoprotein cholesterol (HDL-C) level and determine whether smoking causes a reduction in this level, by using the completely randomized design (CRD) and Kruskal- Wallis method. The results showed that the assumptions of the one- way ANOVA are not satisfied, while, after transforming original data by using log transformation, they are satisfied. From the results, a significantly
... Show MoreThe present work describes guggul as a novel carrier for some anti-inflammatory drugs. Guggulusomes containing different concentration of guggul with aceclofenac were prepared by sonication method and characterized for vesicle shape, size, size-distribution, pH, viscosity, spread ability, homogeneity, and accelerated stability in-vitro drug permeation through mouse skin. The vesicles exhibited an entrapment efficiency of 93.2 ± 12%, vesicle size of 0.769 ± 3μm and a zeta potential of - 6.21mV. In vitro drug release was analyzed using Franz’s diffusion cells. The cumulative release of the guggulusomes gel (G2) was 75.8% in 18 hrs, which is greater than that all the gel formulation. The stability profile of prepare
... Show MoreSmishing is a cybercriminal attack targeting mobile Short Message Service (SMS) devices that contains a malicious link, phone number, or email. The attacker intends to use this message to steal the victim's sensitive information, such as passwords, bank account details, and credit cards. One method of combating smishing is to raise awareness and educate users about the various tactics used by SMS phishers. But even so, this method has been criticized for becoming inefficient because smishing tactics are continually evolving. A more promising anti-smishing method is to use machine learning. This paper introduces a number of machine learning algorithms that can be used for detecting smishing. Furthermore, the differences and simil
... Show MoreMachine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed
... Show MoreThis research a study model of linear regression problem of autocorrelation of random error is spread when a normal distribution as used in linear regression analysis for relationship between variables and through this relationship can predict the value of a variable with the values of other variables, and was comparing methods (method of least squares, method of the average un-weighted, Thiel method and Laplace method) using the mean square error (MSE) boxes and simulation and the study included fore sizes of samples (15, 30, 60, 100). The results showed that the least-squares method is best, applying the fore methods of buckwheat production data and the cultivated area of the provinces of Iraq for years (2010), (2011), (2012),
... Show MoreThe research aims to enhance the level of evaluation of the performance of banking transactions control policies and procedures. The research is based on the following hypothesis: efficient transactions control policies and procedures contribute enhancing financial reporting, by assessing non-application gap of those policies and procedures in a manner that helps to prevent, discover, and correct material misstatements. The researchers designed an examination list that includes the control policies and procedures related to the transactions, as a guide to the bank audit program prepared by the Federal Financial Supervision Bureau. The research methodology is
... Show MoreThis study investigated the applicability of iron oxide (Fe2O3) nanoparticles for the removal of cadmium metal from sewage water by using batch scale experiments. The iron oxide nanoparticles of 27.7nm were synthesized using a biological method and characterized by Atomic Force Microscope (AFM). The Box-Wilson design was used to conduct experiments with three parameters such as pH (2-6), time of adsorption (6-120min) and adsorbent dosage (5-25mg/L). The best conditions occurred at pH: 5.5; contact time: 95.8 min; and iron oxide nanoparticle dosage: 20.77 mg/L for maximum cadmium removal of (96.9%).