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Predicting Phosphorus and Potato Yield Using Active and Passive Sensors
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Applications of remote sensing are important in improving potato production through the broader adoption of precision agriculture. This technology could be useful in decreasing the potential contamination of soil and water due to the over-fertilization of agriculture crops. The objective of this study was to assess the utility of active sensors (Crop Circle™, Holland Scientific, Inc., Lincoln, NE, USA and GreenSeeker™, Trimble Navigation Limited, Sunnyvale, CA, USA) and passive sensors (multispectral imaging with Unmanned Arial Vehicles (UAVs)) to predict total potato yield and phosphorus (P) uptake. The experimental design was a randomized complete block with four replications and six P treatments, ranging from 0 to 280 kg P ha−1, as triple superphosphate (46% P2O5). Vegetation indices (VIs) and plant pigment levels were calculated at various time points during the potato growth cycle, correlated with total potato yields and P uptake by the stepwise fitting of multiple linear regression models. Data generated by Crop Circle™ and GreenSeeker™ had a low predictive value of potato yields, especially early in the season. Crop Circle™ performed better than GreenSeeker™ in predicting plant P uptake. In contrast, the passive sensor data provided good estimates of total yields early in the season but had a poor correlation with P uptake. The combined use of active and passive sensors presents an opportunity for better P management in potatoes.

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Study the Chemical Bonding of Heterometallic Trinuclear Cluster Containing Cobalt and Ruthenium: [(Cp*Co) (CpRu)2 (μ3-H) (μ-H)3] using QTAIM Approach
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The topological parameters of the metal-metal and metal-ligand bonding interactions in a trinuclear tetrahydrido cluster [(Cp*Co) (CpRu)2 (μ3-H) (μ-H)3]1 (Cp* = η5 -C5Me4Et), (Cp = η5 -C5Me5), was explored by using the Quantum Theory of Atoms-in-Molecules (QTAIM). The properties of bond critical points such as the bond delocalization indices δ (A, B), the electron density ρ(r), the local kinetic energy density G(r), the Laplacian of the electron density ∇2ρ(r), the local energy density H(r), the local potential energy density V(r) and ellipticity ε(r) are compared with data from earlier organometallic system studies. A comparison of the topological processes of different atom-atom interactions has become possible than

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Publication Date
Wed Jan 02 2019
Journal Name
Journal Of Educational And Psychological Researches
The Effect of Using the Oral Open-Ended Questions on Achievement and Developing Creative Thinking for Third-stage Arabic Department of Education College Students
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The problem of present study is determined by answering the following questions:                                                                   

1) What is the effect of using the oral open- ended questions on Students' achievement in the third-stage of Arabic department in the college of Education? 2) What is the effect of the oral open-ended questions on developing the creative thinking of students in

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Publication Date
Wed Dec 01 2010
Journal Name
Iraqi Journal Of Physics
Study of electron energy distribution function and transport parameters for CF4, Ar gases mixture discharge by using the solution of Boltzmann equation-Part II
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The Boltzmann transport equation is solved by using two- terms approximation for pure gases and mixtures. This method of solution is used to calculate the electron energy distribution function and electric transport parameters were evaluated in the range of E/N varying from . 172152110./510.VcmENVcm
The electron energy distribution function of CF4 gas is nearly Maxwellian at (1,2)Td, and when E/N increase the distribution function is non Maxwellian. Also, the mixtures are have different energy values depending on transport energy between electron and molecule through the collisions. Behavior of electrons transport parameters is nearly from the experimental results in references. The drift velocity of electron in carbon tetraflouride i

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Publication Date
Fri Dec 29 2023
Journal Name
International Journal Of Nanoscience
Detection of Silica in Rice Husks Using Laser-Induced Plasma and Studying the Effect of Laser Energy on the Parameters of the Produced Plasma
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This study aims to analyze the spectral properties of plasma produced from rice husk(Rh) using the laser breakdown spectroscopy (LIBS) method. The plasma generation process used the fundamental harmonic (1064 nm) of a Q-switched Nd:YAG laser. Yttrium aluminum garnet (YAG) is a man-made crystalline material. The laser fired pulses with a duration of 10 ns and a repetition rate of 6 Hz. Thus, the energy outputs achieved were 50–200 mJ at the wavelength of 1064 (nm). The silica content in the rice hulls was verified using an XRF measurement, which revealed the presence of silica in the rice hulls in a high percentage. Precise beam focusing was achieved by focusing the laser on the target material. This target material is placed with

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Publication Date
Thu Jun 15 2023
Journal Name
Journal Of Craniofacial Surgery
Evaluation of the Lingual Splitting Patterns and the Lateral Bone Cut Ends Following Mandibular Bilateral Sagittal Split Osteotomy Using Cone Beam Computed Tomography (CBCT)
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The bilateral sagittal split osteotomy (BSSO) is the most popular orthognathic procedure performed by maxillofacial surgeons to treat skeletal class II and class III and to correct mandibular asymmetries. The study aimed to evaluate the lingual splitting patterns and lateral bone cut end (LBCE) in bilateral sagittal split osteotomy (BSSO) and their relation with the ramal thickness and the presence of impacted third molars using cone beam computed tomography (CBCT). This prospective observational study included patients with mandibular prognathism who were treated with BSSO with or without Le Fort I osteotomy. Cone beam computed tomography was used to measure the ramal thickness preoperatively and to evaluate the LBCE, and the lingu

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Publication Date
Fri Sep 15 2017
Journal Name
Journal Of Baghdad College Of Dentistry
The Effect of Enamel Protective Agent on Shear and Tensile Bond Strength of Stainless Steel Brackets by Using Different Adhesive Agents (In Vitro Study)
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Background: Decalcification of surface enamel adjacent to fixed orthodontic appliances, in the form of white spot lesions, is a wide spread and familiar well-known side effect of orthodontic treatment. The present study was carried out to evaluate the effect of enamel protective agent (Clinpro white varnish) on shear and tensile bond strength of Dentaurum orthodontic stainless steel brackets by using 3M Unitek and Ormco as orthodontic adhesive agents. Materials and methods: Sixty-four extracted human upper first premolar teeth were selected and randomly divided into two groups with 32 teeth each, representing the shear and tensile bond strength testing groups. Then according to the type of bonding adhesive and the addition of Clinpro before

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Publication Date
Sat Mar 10 2012
Journal Name
الدنانير
Cryptography Using Artificial Neural Network
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Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.

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Publication Date
Tue Dec 27 2022
Journal Name
2022 3rd Information Technology To Enhance E-learning And Other Application (it-ela)
Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

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Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
Shadow Removal Using Segmentation Method
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Shadow detection and removal is an important task when dealing with color outdoor images. Shadows are generated by a local and relative absence of light. Shadows are, first of all, a local decrease in the amount of light that reaches a surface. Secondly, they are a local change in the amount of light rejected by a surface toward the observer. Most shadow detection and segmentation methods are based on image analysis. However, some factors will affect the detection result due to the complexity of the circumstances. In this paper a method of segmentation test present to detect shadows from an image and a function concept is used to remove the shadow from an image.

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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
Eye Detection using Helmholtz Principle
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            Eye Detection is used in many applications like pattern recognition, biometric, surveillance system and many other systems. In this paper, a new method is presented to detect and extract the overall shape of one eye from image depending on two principles Helmholtz & Gestalt. According to the principle of perception by Helmholz, any observed geometric shape is perceptually "meaningful" if its repetition number is very small in image with random distribution. To achieve this goal, Gestalt Principle states that humans see things either through grouping its similar elements or recognize patterns. In general, according to Gestalt Principle, humans see things through genera

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