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ESTIMATION OF GENE ACTION AND GENETIC PARAMETERS FOR SOME CHARACTERS OF YIELD AND ITS COMPONENTS IN SUMMER SQUASH (Cucurbita pepo L.) BY USING MEAN GENERATION ANALYSIS
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An experiment was carried out in the vegetables field of Horticulture Department / College of Agriculture / Baghdad University , for the three seasons : spring and Autumn of 2005 , and spring of 2007 , to study the type of gene action in some traits of yield and its components in summer squash crosses (4 x 3 = cross 1 , 3 x 7 = cross 2 , 3 x 4 = cross 3 , 3 x 5 = cross 4 , 5 x 1 = cross 5 , 5 x 2 = cross 6). The study followed generation mean analysis method which included to each cross (P1 , P2 , F1 , F2 , Bc1P1 , Bc1P2) , and those populations obtained by hybridization during the first and second seasons. Experimental comparison was performed in the second (Two crosses only) and third seasons , (four crosses) by using RCBD with three replications. Three parameters model with chi square test and six parameters model were used to estimate the type of gene effects , in breeding depression , components of genetic variance , mean degree of dominance , heritability and expected gain due to selection. The results showed that dominance and epistatic (additive x additive) and (dominance x dominance) effects were great importance than additive effects in most traits of all crosses. In breeding depression was important except for fruit weight . Broad-sense heritability was high in fruit weight , plant yields , and total yield (67.05 , 52.54 , 52.56) respectively for cross 1 , while it was low to moderate in some traits and crosses and narrow – sense heritability was high in fruit weight (40.82) for cross 6 and low in some traits to some crosses. Expected gain due to selection was low in plant yield and total yield for cross 4 and fruit weight for cross 6

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Publication Date
Tue Apr 01 2025
Journal Name
Natural And Engineering Sciences
Comparison of Some Soil Mineral’s Ability to Adsorb and Release Lead and Rates of its Removal From its Aqueous Solutions
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To study the comparative use of some soil minerals (zeolite, bentonite, phosphate rock, and limestone) in the adsorption and release of lead and its removal rates from its aqueous solutions using adsorption equations. Two laboratory experiments were carried out for the adsorption and release of lead. The adsorption experiment took 0.5 g of some of the above soil minerals. Lead was added as Pb (NO3)2 at levels of 3.0, 2.0, 1.5, 1.0, 0.5, and 0.0 mmol L-1 containing a concentration of 0.01M of calcium chloride. The experimental unit’s number was 72, the concentration of dissolved lead in the equilibrium solution was estimated and the amount of lead adsorbed was calculated. As for the lead release experiment, samples fo

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Publication Date
Thu Aug 01 2019
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Evaluation of routing protocol with multi-mobile sinks in WSNs using QoS and energy consumption parameters
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An efficient networks’ energy consumption and Quality of Services (QoS) are considered the most important issues, to evaluate the route quality of the designed routing protocol in Wireless Sensor Networks (WSNs). This study is presented an evaluation performance technique to evaluate two routing protocols: Secure for Mobile Sink Node location using Dynamic Routing Protocol (SMSNDRP) and routing protocol that used K-means algorithm to form Data Gathered Path (KM-DGP), on small and large network with Group of Mobile Sinks (GMSs). The propose technique is based on QoS and sensor nodes’ energy consumption parameters to assess route quality and networks’ energy usage. The evaluation technique is conducted on two routing protocols i

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Publication Date
Tue Aug 10 2021
Journal Name
Design Engineering
Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri
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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
Context and its influence in direction of reference by Abi Hussein Al Basri
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Context and its influence in direction of reference by Abi Hussein Al Basri

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
A noval SVR estimation of figarch modal and forecasting for white oil data in Iraq
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The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals

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Scopus
Publication Date
Fri Oct 07 2022
Journal Name
Texas Journal Of Engineering And Technology
Estimation of Pore Pressure and In-Situ Stresses for Halfaya Oil Field: A Case Study
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Publication Date
Wed Mar 23 2022
Journal Name
World Economics & Finance Bulletin (wefb)
ANALYSIS OF THE CAUSALITY RELATIONSHIP BETWEEN SPENDING ON HIGHER EDUCATION AND SOME ECONOMIC VARIABLES IN IRAQ FOR THE PERIOD 1990-2020
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Higher education is important because it creates and develops human capital and provides qualified human cadres, which requires restructuring government spending so that an increase in funding allocated to education is brought about. During the period 1990-2020, government spending was weak on educational institutions in Iraq, which led to a decline in The role of these institutions in the economic development of the country. The highest percentage of spending on higher education of GDP was 0.47% in 2007 and the lowest was 0.01% in 2005. The number of public universities reached 35, and the number of private universities and colleges reached 64 universities and private colleges in 2020. This was accompanied by an increase in the number of s

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Publication Date
Sat May 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Effect of adding different level of Bay laurel (Laurus nobilis L.) powder to diet on productive performance and some physiological traits for female Quail
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Abstract<p>This study was conducted at the Poultry Research Station, Animal Resources Research Department at the Agricultural Research Department / Ministry of Agriculture - Baghdad Abu Ghraib. To find the effect of adding different proportions of Bay Laurus powder on productive performance and some physiological characteristics of birds during the production stage as Eight Hundreds Female birds of quail were used at the age of 45 days, randomly deployed to 4 treatments with two replicates (100 birds / replicate ) each, and the bay laurel powder was added in the proportions 0.0, 0.5, 1.0, and 1.5% to the diets and for a period of 60 days divided into 4 periods of 15-day .The results indicated si</p> ... Show More
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Publication Date
Sat Jan 31 2026
Journal Name
International Journal Of Intelligent Engineering And Systems
Low-complexity Deep Learning for Joint Channel-type Identification and SNR Estimation in MIMO-OFDM Using CNN–BRNN with LUT Labels
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Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T

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Publication Date
Thu Mar 22 2018
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Assessment of medical solid waste generation rates for teaching hospitals in Baghdad city
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