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Compression Index and Compression Ratio Prediction by Artificial Neural Networks
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Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites in Baghdad city were used. 70% of these results were used to train the prediction ANN models and the rest were equally divided to test and validate the ANN models. The performance of the developed models was examined using the correlation coefficient R. The final models have demonstrated that the ANN has capability for acceptable prediction of compression index and compression ratio. Two equations were proposed to estimate compression index using the connecting weights algorithm, and good agreements with test results were achieved.

 

 

 

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Publication Date
Sun Jan 14 2018
Journal Name
Journal Of Engineering
A Nonlinear MIMO-PID Neural Controller Design for Vehicle Lateral Dynamics model based on Modified Elman Neural Network
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This paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation resul

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Publication Date
Tue Jun 12 2018
Journal Name
Indian Journal Of Natural Sciences
Effect of Pomegranate Seed Oil on Glycemic Index in Diabetic Rabbits
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This study aimed to investigate the effect of oral administration of pomegranate seed oil on diabetic in male rabbits. A total of 32 adult male rabbits.6 months old weighting 1-2kg were divided in to four equal groups. G- Control (negative) Rabbits were received olive oil, G2- (control positive) Rabbits were received (30 mg/kg B.W/daily of the Pomegranate seed oil orally and daily for 45 day. G3-Rabbits were received (150mg/kg of Alloxan injected Intraperitonealy, G4-Rabbits were received the same dose orally of the Pomegranate seed oil four 45 days. There is significant increase (Insulin, Insulin resistance) and decreased glucose in group received Pomegranate seed oil (G4) as compared with G3 (diabetic group). On conclusion, the administra

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Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
The effect of different flooding ratio on Al-Shuwaija marsh
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In this research, the effect of changing the flood level of Al-Shuwaija marsh was studied using the geographic information systems, specifically the QGIS program, and the STRM digital elevation model with a spatial analysis accuracy of 28 meters, was used to study the marsh. The hydraulic factors that characterize the marsh and affecting on the flooding such as the ranks of the water channels feeding the marsh and the degree of slope and flat areas in it are studied. The area of immersion water, the mean depth, and the accumulated water volume are calculated for each immersion level, thereby, this study finds the safe immersion level for this marsh was determined.

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Publication Date
Wed Sep 01 2021
Journal Name
Journal Of Engineering
Spike neural network as a controller in SDN network
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The paper proposes a methodology for predicting packet flow at the data plane in smart SDN based on the intelligent controller of spike neural networks(SNN). This methodology is applied to predict the subsequent step of the packet flow, consequently reducing the overcrowding that might happen. The centralized controller acts as a reactive controller for managing the clustering head process in the Software Defined Network data layer in the proposed model. The simulation results show the capability of Spike Neural Network controller in SDN control layer to improve the (QoS) in the whole network in terms of minimizing the packet loss ratio and increased the buffer utilization ratio.

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Publication Date
Fri Jul 24 2020
Journal Name
Al-kindy College Medical Journal
Serum Ferritin and Body Mass Index in Chronic Telogen Effluvium among women attending the main dermatological outpatient clinics in BaghdadSerum Ferritin and Body Mass Index in Chronic Telogen Effluvium among women attending the main dermatological
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Background: Hair loss is a common distressing disease and challenging problem for many dermatologist. Telogen effluvium is the most common hair loss disease in which nutritional deficiencies may precipitate the disease through their effect on hair structure and growth.

Study Aim : Validating role of serum ferritin level and body mass index in Chronic Telogen Effluvium and analyzing association between these factors with socioeconomic, demographic, gynecological factors and weight loss effect. Establishing a nutritional preventive advice to improve treatment successfulness and decrease the disease occurrence.

             

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
In vitro isolation and expansion of neural stem cells NSCs
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   Neural stem cells (NSCs) are progenitor cells which have the ability to self‑renewal and potential for differentiating into neurons, oligodendrocytes, and astrocytes. The in vitro isolation, culturing, identification, cryopreservation were investigated to produce neural stem cells in culture as successful sources for further studies before using it for clinical trials. In this study, mouse bone marrow was the source of neural stem cells. The results of morphological study and immunocytochemistry of isolated cells showed that NSCs can be produced successfully and maintaining their self‑renewal and successfully forming neurosphere for multiple passages. The spheres preserved their morphology in culture and cryopreserved t

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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Anomaly Detection Approach Based on Deep Neural Network and Dropout
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   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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Publication Date
Tue Feb 12 2019
Journal Name
Iraqi Journal Of Physics
Calculated the diffuse and direct parts of global solar radiation in Baghdad city for the period (1983-2005) depending on clearness index by applying the two world models of Liu -Jordan
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In this paper solar radiation was studied over a region of Baghdad (Latitude 33.3o and longitude 44.4o). The two parts of global solar radiation: diffuse and direct solar radiation were estimated depending on the clearance index of measured data (Average Monthly mean global solar radiation). Metrological data of measured (average monthly mean diffuse and direct solar radiation) were used to comparison the results and show the agreement between them. Results are determined by applying Liu and Jordan two models (1960). Excel 2007program is used in calculation, graphics and comparison the results.

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Publication Date
Mon Feb 18 2019
Journal Name
Iraqi Journal Of Physics
Drought assessment in Iraq using analysis of Standardized precipitation index (SPI)
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The Present study investigated the drought in Iraq, by using the rainfall data which obtained from 39 meteorological stations for the past 30 years (1980-2010). The drought coefficient calculated on basis of the standard precipitation index (SPI) and then characteristics of drought magnitude, duration and intensity were analyzed. The correlation and regression between magnitude and duration of drought were obtained according the (SPI) index. The result shows that drought magnitude values were greater in the northeast region of Iraq. 

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Publication Date
Mon Jul 01 2024
Journal Name
Journal Of Biomedical Sciences
Effect of Age and Body Mass Index on some Physiological Parameters in Women with Thyroid Disorders
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Age and BMI may be used to diagnosis of thyroid autoimmune disease. One hundred Iraqi women with age ranged from 18 to 60 years participate in this research, 50 of them were hypothyroidism patients, 30 were hyperthyroidism patients and the other 20 were euthyroidism served as controls. Blood samples were collected from the studied subjects to determine thyroid profile [free triiodothyronine (FT3), free tetraiodothyronine (FT4) and thyroid stimulating hormone (TSH)], thyroid antibodies [anti-thyroid peroxidase (anti-TPO), anti-thyroglobulin (anti-Tg), and anti-thyroid stimulating hormone receptor (anti-TSHR)], and levels of vitamin D (vit D), calcium (Ca), and phosphorus (P) using different analysis techniques. When the effect of age

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