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Content Based Image Retrieval Based on Feature Fusion and Support Vector Machine
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Publication Date
Thu Apr 21 2016
Journal Name
Iraqi Journal Of Agricultural Sciences
EFFECT OF SHEEP MANURE EXTRACT ON THE GROWTH AND NUTRIENTS CONTENT OF TOMATO SEEDLINGS
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The experiment was conducted under shading (with the aid of Saran) condition on a nursery managed by the Baghdad Mayoralty during the season of 2014-2015 to study the effect of composed sheep manure extract on the growth and leaf nutrients content of tomato seedlings var. Wijdan. The experiment was composed of 6 treatments included the extract of sheep manure by hot (425C)and lmbient(205C) temperature water .The extract was diluted to the half by water and foliar applied to seedlings (multible application) or to the soil . Treatments also included the application of NPK chemical fertilizers as recommended and a control treatment through applying distilled water as foliar .The experiment was designed according to the randomized compl

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Publication Date
Sat Mar 04 2023
Journal Name
Baghdad Science Journal
Nordhaus-Gaddum Type Relations on Open Support Independence Number of Some Path Related Graphs Under Addition and Multiplication
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In this paper, Nordhaus-Gaddum type relations on open support independence number of some derived graphs of path related graphs under addition and multiplication are studied.

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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
Perceived organizational support and impact on high performance Analytical research in the colleges of the University of Baghdad
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     The research tagged (Perceived Organizational Support in High Performance) deals with identifying the extent of the impact of perceived organizational support as an explanatory variable on high performance as a response variable for the purpose of reaching appropriate mechanisms that enable colleges of the University of Baghdad to exploit the perceived organizational support in achieving the required high performance and pursuit of its goals. The researcher relied on the descriptive and analytical approach in carrying out the research. An intentional sample was selected and reached (70) persons from the higher leadership of the colleges represented by (deans, assistants deans, heads of departments) that r

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Effect of Design Parameters and Support Conditions on Natural Frequency of Pipe Excited by a Turbulent Internal Flow
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In this study, the effect of design parameters such as pipe diameter, pipe wall thickness, pipe material and the effect of fluid velocity on the natural frequency of fluid-structure interaction in straight pipe conveying fully developed turbulent flow were investigate numerically,analytically and experimentally. Also the effect of support conditions, simply-simply and clamped-clamped was investigated. Experimentally, pipe vibrations were characterized by accelerometer mounted on the pipe wall. The natural frequencies of vibration were analyzed by using Fast Fourier Transformer (FFT). Five test sections of two different pipe diameters of 76.2
mm and 50.8 mm with two pipe thicknesses of 3.7 mm and 2.4 mm and two pipe materials,stainles

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Publication Date
Thu Jun 20 2019
Journal Name
Baghdad Science Journal
A Comparative Analysis of the Zernike Moments for Single Object Retrieval
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Zernike Moments has been popularly used in many shape-based image retrieval studies due to its powerful shape representation. However its strength and weaknesses have not been clearly highlighted in the previous studies. Thus, its powerful shape representation could not be fully utilized. In this paper, a method to fully capture the shape representation properties of Zernike Moments is implemented and tested on a single object for binary and grey level images. The proposed method works by determining the boundary of the shape object and then resizing the object shape to the boundary of the image. Three case studies were made. Case 1 is the Zernike Moments implementation on the original shape object image. In Case 2, the centroid of the s

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Publication Date
Fri Sep 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Document retrieval using term term frequency inverse sentence frequency weighting scheme
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The need for an efficient method to find the furthermost appropriate document corresponding to a particular search query has become crucial due to the exponential development in the number of papers that are now readily available to us on the web. The vector space model (VSM) a perfect model used in “information retrieval”, represents these words as a vector in space and gives them weights via a popular weighting method known as term frequency inverse document frequency (TF-IDF). In this research, work has been proposed to retrieve the most relevant document focused on representing documents and queries as vectors comprising average term term frequency inverse sentence frequency (TF-ISF) weights instead of representing them as v

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Detection of Suicidal Ideation on Twitter using Machine Learning & Ensemble Approaches
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Suicidal ideation is one of the most severe mental health issues faced by people all over the world. There are various risk factors involved that can lead to suicide. The most common & critical risk factors among them are depression, anxiety, social isolation and hopelessness. Early detection of these risk factors can help in preventing or reducing the number of suicides. Online social networking platforms like Twitter, Redditt and Facebook are becoming a new way for the people to express themselves freely without worrying about social stigma. This paper presents a methodology and experimentation using social media as a tool to analyse the suicidal ideation in a better way, thus helping in preventing the chances of being the victim o

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Publication Date
Wed Feb 01 2023
Journal Name
Journal Of Engineering
An Empirical Investigation on Snort NIDS versus Supervised Machine Learning Classifiers
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With the vast usage of network services, Security became an important issue for all network types. Various techniques emerged to grant network security; among them is Network Intrusion Detection System (NIDS). Many extant NIDSs actively work against various intrusions, but there are still a number of performance issues including high false alarm rates, and numerous undetected attacks. To keep up with these attacks, some of the academic researchers turned towards machine learning (ML) techniques to create software that automatically predict intrusive and abnormal traffic, another approach is to utilize ML algorithms in enhancing Traditional NIDSs which is a more feasible solution since they are widely spread. To upgrade t

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Publication Date
Tue Feb 17 2026
Journal Name
Journal Of Engineering
Design and Implementation of ICT-Based Recycle-Rewarding System for Green Environment
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Publication Date
Sat Jan 14 2023
Journal Name
Cogent Engineering
C. B interrupt duty reduction based controlling TRV and symmetrical breaking current
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