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Analyzing the behavior of different classification algorithms in diabetes prediction
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<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the curve (AUC), accuracy, receiver operating characteristic (ROC) curve, f-measure, and recall. Experimental results show that random forest is better than any other classifier in predicting diabetes with a 90.75% accuracy rate.</span>

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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Educational And Psychological Researches
Analyzing the content of the chemistry textbook for the third intermediate grade according to the skills of knowledge economy
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The current research aims to identify the extent to which cognitive economics skills are included in the content of the chemistry textbook for the third intermediate grade, and the research sample was represented in the chemistry textbook for the third intermediate grade. A list of knowledge economy skills was prepared (6) main skills (basic skills, communication skills, thinking skills, work skills Group, information-gathering skill, behavioral skills (and (20) sub-skills) (reading, writing, operations, computer skills and employability, oral expression and written communication, dialogue, persuasion, influence and arousal, analysis, problem-solving, decision-making, suggestions and hypotheses and employing them. Controlling, directing

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Publication Date
Mon Jul 01 2024
Journal Name
Journal Of Engineering
Efficient Intrusion Detection Through the Fusion of AI Algorithms and Feature Selection Methods
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With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi

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Publication Date
Mon Jan 01 2018
Journal Name
Rehabend
Prediction of impact force-time history in sandy soils
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Publication Date
Wed Jan 01 2020
Journal Name
Annals Of Tropical Medicine And Public Health
The extent of UMOD gene polymorphism and its level in type 2 diabetes patients
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Publication Date
Mon Dec 20 2021
Journal Name
Natural Volatiles & Essential Oils
Therapeutic Effects of Allicin against the Diabetes Mellitus Induced by Streptozotocin in Male Rats
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This study aimed to see how allicin (45mg/kg BW) affected diabetic Mellitus in male rats (DM). Forty male rats were utilized, and they were split into four groups at random for 42 days. T2 was treated with 45 mg/kg B.W of allicin dissolved in 1 ml of D.W daily and injected with a single dose of sodium citrate buffer (0.5ml Intra-Peritoneal IP), DM was induced in T1 and T2 by injection of a single dose of streptozotocin 50 mg/kg B.W IP, T1 was assigned as a positive control, T3 received 45 mg/kg B.W. of allicin dissolved in 1 ml D.W. every day, and a single dose of sodium citrate buffer was injected (0.5ml IP). When diabetic rats treated with allicin in T2 were compared to diabetic rats in T1, the findings indicated a significant increase (P

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Publication Date
Sun Sep 06 2015
Journal Name
Baghdad Science Journal
The effect of obesity and Insulin Resistance on Liver Enzymes in Type2 Diabetes Mellitus
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Diabetes mellitus (DM) has been defined as a clinical syndrome that is characterized by abnormal carbohydrate metabolism. The chronic hyperglycemia of diabetes is associated with long term damage, dysfunction, and failure of different organs, especially the liver .This study was conducted to assess the effect obesity and insulin resistance on liver enzymes in diabetic Iraqi patients.A comparative study of (90) Iraqi adults divided to three subgroup(30) obese ,(30) nonobese diabetic patients and(30)person had used as control. The analysis included Liver enzyme ALP,ALT,AST,GGT ,Fasting Plasma Glucose (FBG) , Lipid Profile , Hemoglobin A1C , insulin and homeostasis model assessment of insulin resistance (HOMA IR) were measured. Subjects

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Publication Date
Mon Jun 22 2020
Journal Name
Baghdad Science Journal
Using Evolving Algorithms to Cryptanalysis Nonlinear Cryptosystems
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            In this paper, new method have been investigated using evolving algorithms (EA's) to cryptanalysis one of the nonlinear stream cipher cryptosystems which depends on the Linear Feedback Shift Register (LFSR) unit by using cipher text-only attack. Genetic Algorithm (GA) and Ant Colony Optimization (ACO) which are used for attacking one of the nonlinear cryptosystems called "shrinking generator" using different lengths of cipher text and different lengths of combined LFSRs. GA and ACO proved their good performance in finding the initial values of the combined LFSRs. This work can be considered as a warning for a stream cipher designer to avoid the weak points, which may be f

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Publication Date
Fri Aug 23 2024
Journal Name
Aro-the Scientific Journal Of Koya University
Graphical User Authentication Algorithms Based on Recognition
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In cyber security, the most crucial subject in information security is user authentication. Robust text-based password methods may offer a certain level of protection. Strong passwords are hard to remember, though, so people who use them frequently write them on paper or store them in file for computer .Numerous of computer systems, networks, and Internet-based environments have experimented with using graphical authentication techniques for user authentication in recent years. The two main characteristics of all graphical passwords are their security and usability. Regretfully, none of these methods could adequately address both of these factors concurrently. The ISO usability standards and associated characteristics for graphical

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Publication Date
Sun Jan 10 2016
Journal Name
British Journal Of Applied Science &amp; Technology
The Effect of Classification Methods on Facial Emotion Recognition ‎Accuracy
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The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

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Publication Date
Sun Sep 04 2011
Journal Name
Baghdad Science Journal
The Prediction of the Electromagnetic Properties and the ?(E2/M1) of 110-116Cd-Isotopes in IBM Model
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The Nuclear structure of 110-116Cd isotopes was studied theoretically in the framework of the interacting boson model of IBM-l and IBM-2. The properties of the lowest mixed symmetry states such as the 1+, 2+ and 3+ levels produced by the IBM-2 model in the vibrational-limit U(5) of Cd - isotopes are studied in details. This analysis shows that the character of mixed symmetry of 2+ is shared between and states in 110-114Cd – isotopes, the large shar goes to s, while in isotope, the state is declared as a mixed symmetry state without sharing. This identification is confirmed by the percentage of F-spin contribution. The electromagnetic properties of E2 and Ml operators were investigated and the results were analyzed. Various

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