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The potential of nonparametric model in foundation bearing capacity prediction
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Publication Date
Mon Nov 01 2021
Journal Name
Energy Reports
Global solar radiation prediction over North Dakota using air temperature: Development of novel hybrid intelligence model
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Publication Date
Sat Dec 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
The Cluster Analysis by Using Nonparametric Cubic B-Spline Modeling for Longitudinal Data
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Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.

In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.

The longitudinal balanced data profile was compiled into subgroup

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Engineering
Finite Element Analysis of Raft Foundation under Coupled Moment
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Due to wind wave actions, ships impacts, high-speed vehicles and others resources of loading, structures such as high buildings rise bridge and electric transmission towers undergo significant coupled moment loads. In this study, the effect of increasing the value of coupled moment and increasing the rigidity of raft footing on the horizontal deflection by using 3-D finite element using ABAQUS program. The results showed that the increasing the coupled moment value leads to an increase in lateral deflection and increase in the rotational angle (α◦). The rotational angle increases from (0.014, 0.15 to 0.19) at coupled moment (120 kN.m), (0.29, 0.31 and 0.49) at coupled moment (240 kN.m) and (0.57, 0.63 and 1.03) at cou

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Publication Date
Tue May 16 2023
Journal Name
Journal Of Engineering
AXIAL FAN BEARING SYSTEM VIBRATION ANALYSIS
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Rotating fan shaft system was investigated experimentally and theoretically to study its dynamic performance. The type of oil used for the bearing was taken in consideration during the experimental program .Three types of oil were used, SAE 40, SAE 50 and degraded oil. During the experiments, the fan blades stagger angle was changed through angles (20˚, 30˚, 40˚, and 50˚). The shaft rotational speed also changed in the range of (0-3000 rpm). All these parameters have investigated for two cases (balanced and unbalanced fan). The performance parameters of the fan were found experimentally by measuring the fan, volume flow rate, Reynolds and Strouhal numbers, efficiency and pressure head. Analytical part was also represented to prepare

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Revolution In Science And Humanity
Nonparametric Estimation of Failure Periods for Log Normal Distribution Using Bootstra
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A non-parametric kernel method with Bootstrap technology was used to estimate the confidence intervals of the system failure function of the log-normal distribution trace data. These are the times of failure of the machines of the spinning department of the weaving company in Wasit Governorate. Estimating the failure function in a parametric way represented by the method of the maximum likelihood estimator (MLE). The comparison between the parametric and non-parametric methods was done by using the average of Squares Error (MES) criterion. It has been noted the efficiency of the nonparametric methods based on Bootstrap compared to the parametric method. It was also noted that the curve estimation is more realistic and appropriate for the re

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Publication Date
Mon Mar 23 2020
Journal Name
Journal Of Engineering
Effect of Embedment on Generated Bending Moment in Raft Foundation under Seismic Load
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This research shows the experimental results of the bending moment in a flexible and rigid raft foundation rested on dense sandy soil with different embedded depth throughout 24 tests. A physical model of dimensions (200mm*200mm) and (320) mm in height was constructed with raft foundation of (10) mm thickness for flexible raft and (23) mm for rigid raft made of reinforced concrete. To imitate the seismic excitation shaking table skill was applied, the shaker was adjusted to three frequencies equal to (1Hz,2Hz, and 3Hz) and displacement magnitude of (13) mm, the foundation was located at four different embedment depths (0,0.25B = 50mm,0.5B = 100mm, and B = 200mm), where B is the raft width. Generally, the maximum bending

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Publication Date
Tue Jan 24 2023
Journal Name
Journal Of Research In Medical And Dental Science
The Wound Healing Potential of Iraqi Origanum majorana L n-Hexane and Ethyl Acetate Fractions in a Rat Model of Excisional Wound Repair: Pre-Clinical Test
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Origanum majorana (Majorana hortensis), an evergreen herbaceous plant belonging to the Lamiaceae family, has been well known for being used for gastrointestinal, cardiac, respiratory, rheumatologic and many other illnesses, but in wounds management hasn’t been qualified scientifically yet. The goal of the study was to evaluate the wound healing properties of sterols in n-hexane and phenols in ethyl acetate extract fractions of the Iraqi Origanum majorana L aerial parts by contrasting their wound healing abilities with those of commercially available MEBO ointment in a rat excised wound repair model. At various periods, the size of the wounds was measured and skin tissue samples were taken for histopathology. When compared to positive and

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Publication Date
Tue Dec 30 2008
Journal Name
Al-kindy College Medical Journal
Evaluation of the Potential Role of Serum Selenium in Diabetic Patients
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Background: The altered status of some essential trace elements observed in diabetes could have deleterious influences on the health of the diabetics. Objectives: To estimate and study the potential role of serum Selenium in type 1, type 2 diabetics and healthy subjects; and its relation with lipid profile and glycemic index. Methods: A case control designed study was carried out at the National Diabetes Center (NDC) / Al-Mustansiria University; on a total of 94 participants formed of 32 type 1 diabetics, 32 type 2 diabetics and 30 healthy control participants. Data collected about age, sex and BMI; also, blood samples examined for FPG, HbA1C, serum total cholesterol, HDL cholesterol, non-HDL cholesterol, serum triglyceride and sera were

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
COMPARISON OF SOME NONPARAMETRIC METHODS TO DETERMINE THE NUMBER OF RADIATION DOSES FOR BREAST CANCER PATIENTS
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Radiation therapy plays an important role in improving breast cancer cases, in order to obtain an appropriateestimate of radiation doses number given to the patient after tumor removal; some methods of nonparametric regression werecompared. The Kernel method was used by Nadaraya-Watson estimator to find the estimation regression function forsmoothing data based on the smoothing parameter h according to the Normal scale method (NSM), Least Squared CrossValidation method (LSCV) and Golden Rate Method (GRM). These methods were compared by simulation for samples ofthree sizes, the method (NSM) proved to be the best according to average of Mean Squares Error criterion and the method(LSCV) proved to be the best according to Average of Mean Absolu

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Scopus
Publication Date
Fri Mar 01 2024
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
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 c

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