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A three-stage learning algorithm for deep multilayer perceptron with effective weight initialisation based on sparse auto-encoder
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A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures and values of learning parameters are determined through cross-validation, and test datasets unseen in the cross-validation are used to evaluate the performance of the DMLP trained using the three-stage learning algorithm. Experimental results show that the proposed method is effective in combating overfitting in training deep neural networks.

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Publication Date
Thu Jan 01 2015
Journal Name
Journal Of Engineering
GNSS Baseline Configuration Based on First Order Design
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The quality of Global Navigation Satellite Systems (GNSS) networks are considerably influenced by the configuration of the observed baselines. Where, this study aims to find an optimal configuration for GNSS baselines in terms of the number and distribution  of baselines to improve the quality criteria of the GNSS networks. First order design problem (FOD) was applied in this research to optimize GNSS network baselines configuration, and based on sequential adjustment method to solve its objective functions.

FOD for optimum precision (FOD-p) was the proposed model which based on the design criteria of A-optimality and E-optimality. These design criteria were selected as objective functions of precision, whic

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Classification of fetal abnormalities based on CTG signal
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The fetal heart rate (FHR) signal processing based on Artificial Neural Networks (ANN),Fuzzy Logic (FL) and frequency domain Discrete Wavelet Transform(DWT) were analysis in order to perform automatic analysis using personal computers. Cardiotocography (CTG) is a primary biophysical method of fetal monitoring. The assessment of the printed CTG traces was based on the visual analysis of patterns that describing the variability of fetal heart rate signal. Fetal heart rate data of pregnant women with pregnancy between 38 and 40 weeks of gestation were studied. The first stage in the system was to convert the cardiotocograghy (CTG) tracing in to digital series so that the system can be analyzed ,while the second stage ,the FHR time series was t

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Publication Date
Wed Feb 05 2020
Journal Name
Journal Of Physical Education
The Effect of Group Investigation Model on Learning overhead and underarm Pass in Volleyball
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Volleyball is one of the sports that require physical and skill abilities thus many teaching models appeared to teach these abilities like group investigation model. The research aimed at identifying the effect of group investigation model on learning underarm and overhead passing in volleyball. The researchers hypothesized statistical differences between pre and posttests in learning underarm and overhead passing in volleyball as well as differences in posttests of controlling and experimental groups in learning underarm and overhead passing in volleyball. The researcher used the experimental method on (30) second year female students of physical education and sport sciences college/ university of Baghdad. Group investigation model was app

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Post COVID-19 Effect on Medical Staff and Doctors' Productivity Analysed by Machine Learning
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The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T

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Publication Date
Sun Jul 06 2014
Journal Name
Journal Of Educational And Psychological Researches
The influence of Online Training Courses on Iraqi EFL Instructors Teaching and Learning Process
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For over a decade, educational technology has been used sparingly in our schools and universities. Online training courses have been used since 2003 to fill the gaps in our learning system and to add extra program besides classroom learning. This paper aims to investigate the Iraqi EFL instructors’ participating in online training courses and its influence on the process of teaching and learning.

       The sample of present study consists of 30 instructors from University of Baghdad. The questionnaire of sixteen items was constructed. After ensuring validity and reliability of questionnaire, it was applied on March 2013 and the result shows that most of instructors improve their teaching methods b

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Publication Date
Thu Aug 01 2019
Journal Name
Nanomedicine: Nanotechnology, Biology And Medicine
Listeria innocua Dps as a nanoplatform for bioluminescence based photodynamic therapy utilizing Gaussia princeps luciferase and zinc protoporphyrin IX
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Publication Date
Sun Dec 01 2013
Journal Name
Baghdad Science Journal
The efficiency of Paecilomyce farinosus as biocontrol to larve stage on second ad sixith instar larve of Trogoderma granarium (Everts)
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The present study was conducted to determine the pathogenicity of Paecilomyces farinosus as biocontrol agents against Tragoderma granarium (khapra) under laboratory conditions with three concentrations ( 2.8 x 108 , 2.8 x 106 ,2.8 x104 spores/ ml). The laboratory results revealed that fungi showed it's higher pathogencity to larve stage on 2nd instar and 6th instar , although their capability differs according to the fungi concentrations this fungi caused higher mortality of 2nd larval instar 70% and 60% ,55% when it was used at concentrations 2 .8 x 106 ,2.8 x104 spores/ ml respectively. On the other hand on 6th larval instars 55% , 35% , 30% at concentrations ( 2.8 x 108 , 2.8 x 106 ,2.8 x104 spores/ ml) respectively, and the h

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Publication Date
Sun Jan 02 2011
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Relation-ships of neonatal septicemia with the mean serum levels of IL-8 and IL-1 in three large hospitals in Baghdad
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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
A New Green Approach of CFIA Technique for Direct Assay with a High Throughput of Sulfamethoxazole Drugs Using Condensation Reaction with NQS Agent
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A new design of manifold flow injection (FI) coupling with a merging zone technique was studied for sulfamethoxazole determination spectrophotometrically. The semiautomated FI method has many advantages such as being fast, simple, highly accurate, economical with high throughput . The suggested method based on the production of the orange- colored compound of SMZ with (NQS)1,2-Naphthoquinone-4-Sulphonic acid Sodium salt in alkaline media NaOH at λmax 496nm.The linearity range of sulfamethoxazole was  3-100  μg. mL-1, with (LOD) was 0.593 μg. mL-1 and the RSD% is about 1.25 and the recovery is 100.73%. All various physical and chemical parameters that have an effect on the stability and development of

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Publication Date
Sun Jul 01 2001
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
A COMPARATIVE STUDY OF ECOLOGICAL AND GENETICAL ADAPTATION OF THREE IRAQI FRESH WATER SNAILS IN RESPECT TO HEAVY METAL POLLUTION
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A comparative study was carried out on ecological and genetical adaptation of three Iraqi
freshwater snails, Physa acuta, Melanopsis buccinoidea and Melanoides tuberculata, in
respect to acute toxicity of heavy metals (Zn, Cd and Hg). Longevity are used as poisoning
tolerance criterion. LT 50 and LT 100 were determined for the studied snails at (0.5, 1, 5, and
10 ppm), for the three metals. Results indicated that Physa acuta had a higher tolerance than
Melanopsis buccinoidea and Melanoides tuberculata, which was the lower one. Previous
exposure to heavy metals in the original habitat was affecting on experimental tolerance and
no relationships of physical and chemical factors (total hardness, temperature, D. O. and

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