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Application of Probit Analysis in Studying the Allelopathy Phenomenon
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   Probit analysis is a type of regression used to analyze the relationship between a stimulus and the quantal response. Allelopathy refers to direct or indirect negative or positive effects of one plant on another through the release of chemical compounds into the environment. This study was carried out to apply probit analysis in investigating the allelopathic effects of the leaves aqueous extracts of apple of Sodom [Calotropis procera (Aiton) W.T.] on the inhibition of seed germination of African rattlebox (Crotalaria saltiana Andr.). A laboratory experiments were carried out at the Faculty of Agricultural Sciences, University of Gezira, Sudan in season 2014/15. Ten concentrations (2.3, 4.6, 7.0, 9.3, 11.6, 13.9, 16.2, 18.5, 20.8 and 23.2 g/l) leaves aqueous extract of apple of Sodom were prepared from the stock solution (50 g / l). A control with sterilized-distilled water was included for comparison. Treatments were arranged in completely randomized design with four replicates. The seeds were examined for inhibition (%) in germination at three days after initial germination. Collected data were transformed using Abbott’s formula and subjected to probit analysis procedure (P £ 0.5). The results showed that the leaves aqueous extract of apple of Sadom had allelopathic effects on seed germination of African rattlebox and there was direct positive relationship between concentration (g/l) and inhibition (%). Also, the data indicated that plotting of corrected inhibition (%) against concentration (%) formed a sigmoid curve. Probit analysis transformed the sigmoid concentration-response curve to a straight line. Hence, the LC25 (2.16 g/l), LC50 (8.55 g/l) and LC75 (33.88 g/l) were accurately estimated. It was concluded that probit analysis is appropriate procedure in studying the allelopathy phenomenon.

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Publication Date
Wed Mar 23 2022
Journal Name
World Economics & Finance Bulletin (wefb)
ANALYSIS OF THE CAUSALITY RELATIONSHIP BETWEEN SPENDING ON HIGHER EDUCATION AND SOME ECONOMIC VARIABLES IN IRAQ FOR THE PERIOD 1990-2020
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Higher education is important because it creates and develops human capital and provides qualified human cadres, which requires restructuring government spending so that an increase in funding allocated to education is brought about. During the period 1990-2020, government spending was weak on educational institutions in Iraq, which led to a decline in The role of these institutions in the economic development of the country. The highest percentage of spending on higher education of GDP was 0.47% in 2007 and the lowest was 0.01% in 2005. The number of public universities reached 35, and the number of private universities and colleges reached 64 universities and private colleges in 2020. This was accompanied by an increase in the number of s

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Publication Date
Thu Jun 27 2019
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
MICROFACIES ANALYSIS AND BASIN DEVELOPMENT OF THE CENOMANIAN - EARLY TURONIAN SEQUENCE IN THE RAFAI, NOOR AND HALFAYA OIL FIELDS, SOUTHEASTERN IRAQ
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    The stratigraphic sequence of Cenomanian-Early Turonian is composed of Ahmadi, Rumaila, and Mishrif formations in the Rifai, Noor and Halfaya Oil Fields within the Mesopotamian Zone of Iraq, which is bounded at top and bottom by unconformity surfaces. The microfacies analysis of the study wells assisted the recognition of five main environments (open marine, basinal, shallow open marine, Rudist biostrome, and lagoon); these microfacies were indicative of a normal lateral change facies from shallow water facies to deeper water and open marine sediments.

 

    Ahmadi Formation (Early Cenomanian) is characterized by open marine sediments during the transgressive conditions, and would be

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Publication Date
Mon Jan 31 2022
Journal Name
Iraqi Journal Of Science
Evaluation of Water Quality for Greater Zab River by Principal Component Analysis/ Factor Analysis
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This study was conducted to determining the variable effects on water quality of Greater Zab River in Erbil province, Iraq, using multivariate statistical analysis. Seventeen variables were monitored in four sampling sites during one year (from May 2012 to April 2013). The dataset were treated using principal component analysis (PCA)/ factor analysis (FA), cluster analysis (CA) to the most important factors affecting water quality, sources of pollution and suitability of water for drinking consumption and irrigation. Six factors were identified as responsible for the data structure explaining 73.5% of the total variance in the dataset and are conditionally named, hydrochemical from weathering, mineral salts and domestic wastes. CA showed

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Publication Date
Sun Oct 30 2022
Journal Name
Iraqi Journal Of Science
An Internet of Things Botnet Detection Model Using Regression Analysis and Linear Discrimination Analysis
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The Internet of Things (IoT) has become a hot area of research in recent years due to the significant advancements in the semiconductor industry, wireless communication technologies, and the realization of its ability in numerous applications such as smart homes, health care, control systems, and military. Furthermore, IoT devices inefficient security has led to an increase cybersecurity risks such as IoT botnets, which have become a serious threat. To counter this threat there is a need to develop a model for detecting IoT botnets.

This paper's contribution is to formulate the IoT botnet detection problem and introduce multiple linear regression (MLR) for modelling IoT botnet features with discriminating capability and alleviatin

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Publication Date
Mon Mar 29 2021
Journal Name
Journal Of Engineering
Effluent quality assessment of sewage treatment plant using principal component analysis and cluster analysis
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Sewage water is a mixture of water and solids added to water for various uses, so it needs to be treated to meet local or global standards for environmentally friendly waste production. The present study aimed to analyze the new Maaymyrh sewage treatment plant's quality parameters statistically at Hilla city. The plant is designed to serve 500,000 populations, and it is operating on a biological treatment method (Activated Sludge Process) with an average wastewater inflow of 107,000m3/day. Wastewater data were collected daily by the Mayoralty of Hilla from November 2019 to June 2020 from the influent and effluent in the (STP) new in Maaymyrh for five water quality standards, such as (BOD5), (COD), (TSS), (TP)

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Publication Date
Tue Apr 20 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Parametric Models in Survival Analysis for Lung Cancer Patients
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    The aim of this study is to estimate the survival function for the data of lung cancer patients, using parametric methods (Weibull, Gumbel, exponential and log-logistic).

Comparisons between the proposed estimation method have been performed using statistical indicator Akaike information Criterion, Akaike information criterion corrected and Bayesian information Criterion, concluding that the survival function for the lung cancer by using Gumbel distribution model is the best. The expected values of the survival function of all estimation methods that are proposed in this study have been decreasing gradually with increasing failure times for lung cancer patients, which means that there is an opposite relationshi

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Publication Date
Thu Jun 01 2023
Journal Name
Iraqi Journal Of Physics
Geomorphological Analysis Methodologies for Houran Valley Basin in Iraq
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Extracting, studying and interpreting the morphological database of a basin is a basic building block for building a correct geomorphological understanding of this basin. In this work, Arc GIS 10.8 software and SRTM DEM satellite images were used. The principle of data integration was adopted by extracting the quantitative values of the morphometric characteristics that are affected by the geomorphological condition of the studied basin, then eliciting an optimal conception of the geomorphological condition of the basin from the meanings and connotations of these combined transactions. Hypsometric integration was extracted for each region in the basin separately with the value of integration of the plot curve for the relative heights of

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Publication Date
Sat Jun 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
NONPARAMETRIC And Semiparametric Bayesian Estimators in survival function analysis
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 Most statistical research generally relies on the study of the behaviour of different phenomena during specific time periods and the use of the results of these studies in the development of appropriate recommendations and decision-making and for the purpose of statistical inference on the parameters of the statistical distribution of life times in  The technical staff of most of the manufacturers in the research units of these companies deals with censored data, the main objective of the study of survival is the need to provide information that is the basis for decision making and must clarify the problem and then the goals and limitations of this study and that  It may have different possibilities to perform the

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Publication Date
Sun Dec 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Oil Sector in Iraq (Reality and Prospects) Economic Analysis
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   The oil sector in Iraq suffered from several difficulties led to the decline and reduction of oil production and the deterioration of refineries and transport pipeline status in addition to the weakness of the technology side and the prevalence of financial and administrative corruption besides the high costs of rehabilitation of the oil sector and also administrative and institutional problems still ongoing. 

 In spite of Iraq's possession of vast oil wealth allows him to play an important role in the international energy market، he is still under the level. The production of oil doesn'<

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Publication Date
Mon Jan 27 2020
Journal Name
Iraqi Journal Of Science
Sentiment Analysis in Social Media using Machine Learning Techniques
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Over the last period, social media achieved a widespread use worldwide where the statistics indicate that more than three billion people are on social media, leading to large quantities of data online. To analyze these large quantities of data, a special classification method known as sentiment analysis, is used. This paper presents a new sentiment analysis system based on machine learning techniques, which aims to create a process to extract the polarity from social media texts. By using machine learning techniques, sentiment analysis achieved a great success around the world. This paper investigates this topic and proposes a sentiment analysis system built on Bayesian Rough Decision Tree (BRDT) algorithm. The experimental results show

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Scopus (28)
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