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Technological Advances in Soil Penetration Resistance Measurement and Prediction Algorithms
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Soil compaction is one of the most harmful elements affecting soil structure, limiting plant growth and agricultural productivity. It is crucial to assess the degree of soil penetration resistance to discover solutions to the harmful consequences of compaction. In order to obtain the appropriate value, using soil cone penetration requires time and labor-intensive measurements. Currently, satellite technologies, electronic measurement control systems, and computer software help to measure soil penetration resistance quickly and easily within the precision agriculture applications approach. The quantitative relationships between soil properties and the factors affecting their diversity contribute to digital soil mapping. Digital soil maps use machine learning algorithms to determine the above relationship. Algorithms include multiple linear regression (MLR), k-nearest neighbors (KNN), support vector regression (SVR), cubist, random forest (RF), and artificial neural networks (ANN). Machine learning made it possible to predict soil penetration resistance from huge sets of environmental data obtained from onboard sensors on satellites and other sources to produce digital soil maps based on classification and slope, but whose output must be verified if they are to be trusted. This review presents soil penetration resistance measurement systems, new technological developments in measurement systems, and the contribution of precision agriculture techniques and machine learning algorithms to soil penetration resistance measurement and prediction.

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Publication Date
Sat Mar 11 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Measurement of Ferritin and Transforming Growth Factor-β1 Levels in Iraqi Women with Polycystic Ovary Syndrome.
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      Background: Polycystic ovary syndrome (PCOS) is common heterogeneous disorder syndrome in females, characterized by chronic oligoovulation, polycystic ovary, and hyperandrogenism. This study aimed to the association of ferritin and transforming growth factor- β1 (TGF-β1) levels with insulin resistance, cardiovascular and type 2 diabetes risks. Patients and methods: (61) Iraqi women with PCOS patients diagnosed according to the Rotterdam criteria, were subdivided according to their Body Mass Index (BMI) to: (20) lean women with normal BMI: (18-24), (17) overweight women with BMI: (25-29) and (25) obese women with BMI >30. For the the purpose of comparison, (20) healthy Iraqi women were enrolled as controls ma

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Publication Date
Wed Dec 30 2020
Journal Name
Al-kindy College Medical Journal
Measurement of plasma fibrinogen and D-dimer in a sample of Iraqi patients with solid malignant tumors
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Background: Multifactor affect the pathogenesis of thrombosis in solid malignancy; however, a significant role is attributed to the cancer cells ability to interact with and activate the host hemostatic system. [1] 

Hemostasis is highly correlated to tumor growth, angiogenesis and metastasis, modulation of these pathways reflects interesting and promising treatment options in the future. [1]

Most patients with cancer frequently suffer from chronic compensated DIC and have abnormal laboratory coagulation tests without clinical manifestations of thrombosis, which is a subclinical hypercoagulable state that can be detected by varying degrees of activation of blood clotting. The results of laboratory tests in th

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Publication Date
Mon Apr 23 2018
Journal Name
International Journal Of Quantum Information
Key rate estimation of measurement-device-independent quantum key distribution protocol in satellite-earth and intersatellite links
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In this work, an estimation of the key rate of measurement-device-independent quantum key distribution (MDI-QKD) protocol in free space was performed. The examined free space links included satellite-earth downlink, uplink and intersatellite link. Various attenuation effects were considered such as diffraction, atmosphere, turbulence and the efficiency of the detection system. Two cases were tested: asymptotic case with infinite number of decoy states and one-decoy state case. The estimated key rate showed the possibility of applying MDI-QKD in earth-satellite and intersatellite links, offering longer single link distance to be covered.

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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
Measurement of radionuclides in imported Coffee Consumed in Basra southern of Iraq and estimation of its annual effective dose
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Radioactive elements were identified in samples of imported coffee consumed in the province of Basra using gamma spectrometry SAM940TM. It is a scintillation detector of NaI(Tl) crystal and the dimensions of 2×2 inch. We have identified specific concentration As(Bq/kg) and annual effective dose D(Sv/y) for radioactive elements (_^40)K, (_^131)I, (_^134)Cs and (_^137)Cs. The estimated average effective dose for adults from coffee samples were found to be 0.037mSv/y, 88.434nSv/y, 46.909nSv/y, 27.212nSv/y for ((_^40)K,(_^131)I,(_^134)Cs,(_^137)Cs) respectively. The present results of the study revealed that the radioactivity was relatively low in the coffee and within the permissiblelimit.

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Intelligent Systems
Optimizing genetic prediction: Define-by-run DL approach in DNA sequencing
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Abstract: The utility of DNA sequencing in diagnosing and prognosis of diseases is vital for assessing the risk of genetic disorders, particularly for asymptomatic individuals with a genetic predisposition. Such diagnostic approaches are integral in guiding health and lifestyle decisions and preparing families with the necessary foreknowledge to anticipate potential genetic abnormalities. The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm to enhance the precision of genetic diagnostic tools. Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization

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Publication Date
Mon Mar 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of bubble size in Bubble columns using Artificial Neural Network
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In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A

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Publication Date
Wed Jul 13 2016
Journal Name
International Journal Of Mathematics Trends And Technology
Designed Algorithms for Compute the Tenser Product of Representation for the Special Linear Groups
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The main objective of this paper is to designed algorithms and implemented in the construction of the main program designated for the determination the tenser product of representation for the special linear group.

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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
A Study on the Accuracy of Prediction in Recommendation System Based on Similarity Measures
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Recommender Systems are tools to understand the huge amount of data available in the internet world. Collaborative filtering (CF) is one of the most knowledge discovery methods used positively in recommendation system. Memory collaborative filtering emphasizes on using facts about present users to predict new things for the target user. Similarity measures are the core operations in collaborative filtering and the prediction accuracy is mostly dependent on similarity calculations. In this study, a combination of weighted parameters and traditional similarity measures are conducted to calculate relationship among users over Movie Lens data set rating matrix. The advantages and disadvantages of each measure are spotted. From the study, a n

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Publication Date
Fri Nov 01 2019
Journal Name
Ecology, Environment And Conservation
Measurement of the concentration of lead in gasoline stations and in air battery factories and their effect of cytogenetic and hematological parameter in workers
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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
A Comparative Study of Single-Constraint Routing in Wireless Mesh Networks Using Different Dynamic Programming Algorithms
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Finding the shortest route in wireless mesh networks is an important aspect. Many techniques are used to solve this problem like dynamic programming, evolutionary algorithms, weighted-sum techniques, and others. In this paper, we use dynamic programming techniques to find the shortest path in wireless mesh networks due to their generality, reduction of complexity and facilitation of numerical computation, simplicity in incorporating constraints, and their onformity to the stochastic nature of some problems. The routing problem is a multi-objective optimization problem with some constraints such as path capacity and end-to-end delay. Single-constraint routing problems and solutions using Dijkstra, Bellman-Ford, and Floyd-Warshall algorith

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