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High throughput screening of rooting depth in rice using buried herbicide
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Abstract<p>Root research requires high throughput phenotyping methods that provide meaningful information on root depth if the full potential of the genomic revolution is to be translated into strategies that maximise the capture of water deep in soils by crops. A very simple, low cost method of assessing root depth of seedlings using a layer of herbicide (<styled-content style="fixed-case">TRIK</styled-content> or diuron) buried 25 or 30 cm deep in soil‐filled boxes of varying size is described that is suitable for screening hundreds or thousands of rice accessions in controlled environment conditions. Variation in cultivar sensitivity to the herbicide when injected into pots was detected but considered small in relation to the variation detected when the herbicide was buried. Using 32 rice cultivars previously characterised for root traits in rhizotron and hydroponic systems, 80% of variation in herbicide score at 35 days was explained by cultivar and herbicide score correlated strongly with rooting depth traits. Using 139 genotypes of the Bala × Azucena mapping population, heritability for herbicide symptoms reached 55% and quantitative trait loci were detected which match those previously reported in this population. In repeated experiments using different soils, the method did not always perform to its maximum potential (in terms of speed of symptom development or discrimination between cultivars). This was not due to degradation or reduced bio‐availability of the herbicide in the soil but is believed to be due to the soil water content and water release characteristics as it relates to plant water use. Therefore, when using this technique, thorough preliminary experiments to determine the best water application regime for the particular combination of soil and environmental conditions are required. The method should be applicable to seedling stage screening of rice and other crops.</p>
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Publication Date
Mon Jan 01 2018
Journal Name
International Journal Of Data Mining, Modelling And Management
Association rules mining using cuckoo search algorithm
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Association rules mining (ARM) is a fundamental and widely used data mining technique to achieve useful information about data. The traditional ARM algorithms are degrading computation efficiency by mining too many association rules which are not appropriate for a given user. Recent research in (ARM) is investigating the use of metaheuristic algorithms which are looking for only a subset of high-quality rules. In this paper, a modified discrete cuckoo search algorithm for association rules mining DCS-ARM is proposed for this purpose. The effectiveness of our algorithm is tested against a set of well-known transactional databases. Results indicate that the proposed algorithm outperforms the existing metaheuristic methods.

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Publication Date
Thu Jan 01 2015
Journal Name
International Journal Of Computer Science And Mobile Computing
Image Compression using Hierarchal Linear Polynomial Coding
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Publication Date
Sun Sep 24 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Human Recognition Using Ear Features: A Review
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Over the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric for the identification and recognition of humans due to its consistent shape and rich texture variation. The ear presents an attractive solution since it is visible, ear images are easily captured, and the ear structure remains relatively stable over time.  In this paper, a comprehensive review of prior research was conducted to establish the efficacy of utilizing ear features for individual identification through the employment of both manually-crafted features and deep-learning approaches. The objective of this model is to present the accuracy rate of person identification systems based on either manually-crafted features such as D

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Using Benford’s Law to detect Financial Fraud
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Fraud Includes acts involving the exercise of deception by multiple parties inside and outside companies in order to obtain economic benefits against the harm to those companies, as they are to commit fraud upon the availability of three factors which represented by the existence of opportunities, motivation, and rationalization. Fraud detecting require necessity of indications the possibility of its existence. Here, Benford’s law can play an important role in direct the light towards the possibility of the existence of financial fraud in the accounting records of the company, which provides the required effort and time for detect fraud and prevent it.

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Publication Date
Tue Dec 07 2021
Journal Name
2021 14th International Conference On Developments In Esystems Engineering (dese)
Object Detection and Distance Measurement Using AI
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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Detecting Textual Propaganda Using Machine Learning Techniques
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Social Networking has dominated the whole world by providing a platform of information dissemination. Usually people share information without knowing its truthfulness. Nowadays Social Networks are used for gaining influence in many fields like in elections, advertisements etc. It is not surprising that social media has become a weapon for manipulating sentiments by spreading disinformation.  Propaganda is one of the systematic and deliberate attempts used for influencing people for the political, religious gains. In this research paper, efforts were made to classify Propagandist text from Non-Propagandist text using supervised machine learning algorithms. Data was collected from the news sources from July 2018-August 2018. After annota

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Publication Date
Thu Oct 18 2018
Journal Name
Proceedings Of The Future Technologies Conference (ftc) 2018
Using Mouse Dynamics for Continuous User Authentication
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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Hiding Information Using different lighting Color images
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Publication Date
Mon Nov 01 2021
Journal Name
University Of Baghdad, College Of Education For Pure Sciences \ Ibn Al-haitham, Department Of Mathematics
SOME ALPHA-TOPOLOGICAL CONCEPTS USING GRAPH THEORY
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This dissertation depends on study of the topological structure in graph theory as well as introduce some concerning concepts, and generalization them into new topological spaces constructed using elements of graph. Thus, it is required presenting some theorems, propositions, and corollaries that are available in resources and proof which are not available. Moreover, studying some relationships between many concepts and examining their equivalence property like locally connectedness, convexity, intervals, and compactness. In addition, introducing the concepts of weaker separation axioms in α-topological spaces than the standard once like, α-feebly Hausdorff, α-feebly regular, and α-feebly normal and studying their properties. Furthermor

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Publication Date
Tue Sep 30 2008
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Dye Removal from Wastewater Using Iron Salts
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This investigation was carried out to study the treatment and recycling of wastewater in the cotton textile industry for an effluent containing three dyes: direct blue, sulphur black and vat yellow. The reuse of such effluent can only be made possible by appropriate treatment method such as chemical coagulation. Ferrous and ferric sulphate with and without calcium hydroxide were employed in this study as the chemical coagulants.
The results showed that the percentage removal of direct blue ranged between 91.4 and 94 , for sulphur black ranged between 98.7 and 99.5 while for vat yellow it was between 97 and 99.

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