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The use of image analysis to study the effect of moisture content on the physical properties of grains
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Abstract<p>Designing machines and equipment for post-harvest operations of agricultural products requires information about their physical properties. The aim of the work was to evaluate the possibility of introducing a new approach to predict the moisture content in bean and corn seeds based on measuring their dimensions using image analysis using artificial neural networks (ANN). Experimental tests were carried out at three levels of wet basis moisture content of seeds: 9, 13 and 17%. The analysis of the results showed a direct relationship between the wet basis moisture content and the main dimensions of the seeds. Based on the statistical analysis of the seed material, it was shown that the characteristics examined have a normal or close to normal distribution, and the seed material used in the investigation is representative. Furthermore, the use of artificial neural networks to predict the wet basis moisture content of seeds based on changes in their dimensions has an efficiency of 82%. The results obtained from the method used in this work are very promising for predicting the moisture content.</p>
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Publication Date
Sun Feb 10 2019
Journal Name
Journal Of The College Of Education For Women
The Effect of Using Reciprocal Teaching on Improving College Students' Achievement in Reading Comprehension
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Reciprocal Teaching is an interactive method that is used to improve reading comprehension. Using this teaching strategy, teachers and students take turns leading discussions regarding sections of text using the four strategies: predicting, questioning, clarifying and summarizing. This study is an attempt to investigate the effect of using reciprocal teaching on improving female college students' achievement in reading comprehension. To fulfill the aim of the study, the researcher has adopted two null hypotheses: first, there is no significant difference between the achievement of students' who practice the reciprocal teaching technique and that of students who do not practice it. Second, there is no statistically significant difference

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Publication Date
Tue Jan 31 2012
Journal Name
British Journal Of Nutrition
Zinc modifies the effect of phyto-oestrogens on osteoblast and osteoclast differentiation in vitro
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Osteoblast and osteoclast activity is disrupted in post-menopausal osteoporosis. Thus, to fully address this imbalance, therapies should reduce bone resorption and promote bone formation. Dietary factors such as phyto-oestrogens and Zn have beneficial effects on osteoblast and osteoclast activity. However, the effect of combinations of these factors has not been widely studied. We therefore examined the effect of coumestrol, daidzein and genistein in the presence or absence of zinc sulphate (Zn) on osteoclast and osteoblast activity. Osteoclast differentiation and bone resorption were significantly reduced by coumestrol (10- 7 m), daidzein (10- 5 m) and genistein (10- 7 m); and this direct anti-osteoclastic action was unaffected by Zn (10-

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Publication Date
Sat Dec 01 2018
Journal Name
Results In Physics
Radioactivity effect on the shape of even-even nuclei for uranium and thorium series
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The purpose of present work is to study the relationship of the deformed shape of the nucleus with the radioactivity of nuclei for (Uranium-238 and Thorium-232) series. To achieve our purposes we have been calculated the quadruple deformation parameter (β2) and the eccentricity (e) and compare the radioactive series with the change of the and (e) as indicator for the changing in the nucleus shape with the radioactivity. To obtain the value of quadruple deformation parameter (β2), the adopted value of quadruple transition probability B (E2; 0+ → 2+) was calculated from Global Best fit equation. While the eccentricity (e) was calculated from the values of the minor and major ellipsoid axis’s (a & b). From the results, it is obvi

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Publication Date
Fri Dec 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Effect of speed and die holes diameter in the machine on feed pellets quality
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Abstract<p>The study aimed to effect of speed and die holes diameter in the machine on feed pellets quality. In this study was measured pellet direct measurement (%), pellet lengths (%), pellet durability (%) and pellet water absorption (%). Three die speeds 280, 300, and 320 rpm, three diameters of die holes in the machine 3, 4, and 5 mm, have been used. The results showed that increasing the pellet die speeds from 280 to 300 then to 320 rpm led to a significant decrease in direct measurement, pellet durability, and pellet water absorption was increased, whereas it did not significantly affect the pellet lengths. Increasing the die holes diameter from 3 to 4 then to 5 mm led to a significant de</p> ... Show More
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Publication Date
Thu Mar 12 2020
Journal Name
Al-khwarizmi Engineering Journal
Optimization the Effect of Electrode Material Change on EDM Process Performance Using Taguchi Method
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Electrical Discharge Machining (EDM) is a widespread Nontraditional Machining (NTM) processes for manufacturing of a complicated geometry or very hard metals parts that are difficult to machine by traditional machining operations. Electrical discharge machining is a material removal (MR) process characterized by using electrical discharge erosion. This paper discusses the optimal parameters of EDM on high-speed steel (HSS) AISI M2 as a workpiece using copper and brass as an electrode. The input parameters used for experimental work are current (10, 24 and 42 A), pulse on time (100, 150 and 200 µs), and pulse off time (4, 12 and 25 µs) that have effect on the material removal rate (MRR), electrode wear rate (EWR) and wear ratio (WR). A

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Publication Date
Sun Aug 17 2025
Journal Name
Journal Of Baghdad College Of Dentistry
The effect of tooth shape ratio on mandibular incisors arrangement in Iraqi adult subjects
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Background: This study aimed to assess the effect of tooth shape ratio on mandibular incisor arrangement. Materials and methods: The sample included dental casts of some dental students and orthodontic patients having Class I dental and skeletal patterns with normal occlusion and severe crowding. The sample was divided into two groups according to the severity of crowding into: group I had Class I normal occlusion with mild or no crowded mandibular dentition and group II had Class I malocclusion with severe crowded mandibular dentition. Each group comprising of 40 subjects (20 males and 20 females). The mesio-distal and facio-lingual crown diameters were measured manually for each cast using modified vernier caliper gauge. Descriptive sta

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Publication Date
Wed Dec 29 2021
Journal Name
Anatolian Congresses 8th International Applied Sciences Congress
The Effect of Twin-Row Silage Maize Harvesting on Single Row Silage Machine Performance
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In this study, the harvest of maize silage with the cross double row sowing method were tested with a single row disc silage machine in two different PTO applications (540 and 540E min-1) and at two different working speeds v1, v2 (1.8 and 2.5 km h-1). The possibilities of harvesting with a single row machine were revealed, and performance characteristics such as hourly fuel consumption, field-product fuel consumption and PTO power consumption were determined in the trials. The best results in terms of hourly fuel consumption and PTO power consumption were determined in the 540E PTO application and V1 working speed. When the fuel consumption of the field-product is evaluated, it is obtained with V2 working speed and 540E PTO application. As

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
An Observation and Analysis the role of Convolutional Neural Network towards Lung Cancer Prediction
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Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

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Publication Date
Thu Mar 01 2012
Journal Name
Journal Of Magnetism And Magnetic Materials
Structural analysis, magnetic and electrical properties of samarium substituted lithium–nickel mixed ferrites
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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Determining the Mobility of some Essential Elements in Saffron (Crocus sativus L.) by the Neutron Activation Analysis
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The main purpose of this investigation is to evaluate the concentrations of six essential metals (Na+, Mg2+, K+, Ca2+, Fe2+ and Zn2+) in saffron and a farm soil using the neutron activation analysis (NAA) as a nuclear spectrometry method. The stratified random sampling method was used here. The NAA results showed the well uptake of Mg2+, K+, Ca2+, Fe2+, and Zn2+ in saffron, which is lower than the toxicity range. Based on the contamination factor and geoaccumulation index, soil contamination levels were determined uncontaminated by Zn, moderately contaminated by Na+ and Fe2+, and strongly contamin

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