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AI-Driven Cybersecurity, Big Data, and Business Intelligence: Impacts on Strategic Flexibility and Entrepreneurship in Iraqi ISPs
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This research aims to explore the status effects of the Sudden, and gradual of AI-Driven Cyber Security (AIDC), Big data analytics and Business Intelligence (BI) The strategic flexibility (SF) and entrepreneurship (ENT) on Iraqi internet services providers ISPs. The work fills an important lacunae in what the advanced dimensions of technology have with regard to its influencing both SF and ENT outcomes in developing economy context, where empirical evidences are scant. A cross-sectional survey based on a quantitative research methodology was conducted on 113 professionals in Iraqi telecommunication sector. A partial least squares structural equation modeling (PLS-SEM) approach was adopted to examine 10 hypotheses concerning the relationships between technology capabilities and SF and ENT. The results reveal the in-depth direct influences of AIDC, BDAC and BI on the SF and ENT factors. SF is found to be an important mediating factor that significantly strengthens the influence of technological competence on ENT outcomes. This indicates two paths (direct and indirect) to reach SF and ENT, facilitated by AT. The present study also extends the literature by adding further empirical evidence from Iraq which indicates that integrating AIDC, BDAC and BI has a synergetic impact on SF but also on ENT. The findings apply only to the Iraqi context in geographical terms. The results show that spending on these technologies are strategic spending rather than operational expenditure. “Institutions should structure responses that are flexible to fit in with people and things, in order to harness the maximum benefit from technology.” These capabilities may be viewed as bases of competitive advantage (CA). This study is first of its kind in Iraq which examines the synergistic effect of AIDC, BDAC and BI on OSC and ENT performance where insight into developing economy perspective becomes present.

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Publication Date
Tue Jan 01 2019
Journal Name
Advances In Materials Physics And Chemistry
The Role of Cooling Condition on the Superconducting Properties of Tl<sub>2-x</sub>Hg<sub>x</sub>Sr<sub>2</sub>Ca<sub>2</sub>Cu<sub>3</sub>O<sub>10+δ</sub> System
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Publication Date
Sun Jan 01 2017
Journal Name
International Journal Of Economic Research
Credit derivatives: Do they matter to avoid credit exposure? (Some evidences from the US market)
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Credit derivatives (CDs) have been increasingly acknowledged as an important requirement to hedge and transfer credit risk CR. Nonetheless, they have been extensively criticized for destabilizing the whole economic system bringing about the latest subprime credit crisis. The study’s main aim is to investigate the reason for the use of (CDs), whether it is used for hedging or trade purpose, for four of the US international financial institutions that had made it through the 2007 crisis to resume functioning post-crisis. This will be for three different and critical periods, namely the pre, during and after crisis periods (Q1, 2000-Q1, 2014). Adopting the SUR technique, the investigation of the factors that influence the net position of (CD

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Scopus
Publication Date
Wed Jun 01 2022
Journal Name
Journal Of The College Of Languages (jcl)
The Linguistic Characteristics In The Morphology ( Nominal Suffixes ) Of a Number Of ( Khoryat or Hoyrat ) Printed By The Poet Kamal Mustafa Daquqli: Kemal Mustafa Dakuk ̕ lunun Basılmayan Bazı Hoyratlarında Şekil Bilgisi Özelliklerin ( İsim Durum Ekleri )
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The present study, entitled “ linguistic characteristics (the morphology - nominal suffixes ) of a number of (Quriyat or koyrat ) by the poet Kamal Mustafa Daquqli, aims at studying and making a comparison between  Turkmen dialect written and spoken forms that show many of the hidden language structures. Similarly, the study sheds light on the poet as one of the most prominent literary figures in Turkmenistan literature.

Turkman Quriyat is one of Turkman blank verse significant forms. Apart from (songs and Quriyat) and until the 19th C., folk poetry has been stalled for a long time but reclaimed its literary high position in the middle of the 20th C.

The study introduction briefly discusses Tu

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Publication Date
Wed Oct 11 2023
Journal Name
Journal Of Educational And Psychological Researches
The Degree to which Arabic Language Teachers at the Secondary Stage Possess the Teaching Competencies Necessary to Develop the Literary Appreciation Skills of Their Students from the Point of View of Educational Leaders in Bisha Governorate
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This study aims to identify the degree of Arabic language teachers at the secondary stage possessing the teaching competencies necessary to develop the skills of literary savor among their students from the perception of educational leaders in Bisha Province. To achieve the objectives of the study, the descriptive approach was used by adopting a comprehensive survey method. The study sample consisted of (48) school principals and Arabic language supervisors in Bisha Province who supervise the teaching of Arabic language at the secondary level in Bisha Province. The necessary data was collected using a questionnaire. The results of the study revealed that the evaluation of the study sample for the degree to which Arabic language teachers

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Publication Date
Thu Jan 02 2020
Journal Name
Journal Of The College Of Languages (jcl)
Principles of modeling a dictionary article in the «Dictionary of the Russian Folklore: lexicon epics» (M.A. Bobunova, A.T. Khro: Принципы моделирования словарной статьи В «словаре языка русского фольклора: Лексика былины» (М. А. Бобунова, А. Т. Хроленко)
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The article describes the basic principles of modeling a dictionary article in the “Dictionary of the Language of Russian Folklore Lexicon epics” (M. A. Bobunova, A. T. Khrolenko). Among such principles are the principle of linguocentrism (representation of universal cognitions in strict observance of the traditions of lexicographic science), the principle of anthropocentrism (language learning as a means of human consciousness / subconsciousness), the principle of expansionism (attracting material from various knowledge bases), the principle of explanatory ("explanatory moment"), and fractal principle (synergistic potential of the presented material: nonlinearity and self-similarity; hierarchical organizati

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Publication Date
Sun Jul 05 2026
Journal Name
Iraoi Journal Of Statistical Sciences
حول تقليص تقدير المركبات الرئيسة مع التطبيق
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This research deals with a shrinking method concerned with the principal components similar to that one which used in the multiple regression “Least Absolute Shrinkage and Selection: LASS”. The goal here is to make an uncorrelated linear combinations from only a subset of explanatory variables that may have a multicollinearity problem instead taking the whole number say, (K) of them. This shrinkage will force some coefficients to equal zero, after making some restriction on them by some "tuning parameter" say, (t) which balances the bias and variance amount from side, and doesn't exceed the acceptable percent explained variance of these components. This had been shown by MSE criterion in the regression case and the percent explained

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Publication Date
Thu May 05 2016
Journal Name
Global Journal Of Engineering Science And Researches
EVALUATE THE RATE OF CONTAMINATION SOILS BY COPPER USING NEURAL NETWORK TECHNIQUE
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The aim of this paper is to design suitable neural network (ANN) as an alternative accurate tool to evaluate concentration of Copper in contaminated soils. First, sixteen (4x4) soil samples were harvested from a phytoremediated contaminated site located in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Copper. The performance of the ANN technique was compared with the traditional laboratory inspecting using the training and test data sets. The results of this study show that the ANN technique trained on experimental measurements can be successfully applied to the rapid est

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Intelligent Systems
An online COVID-19 self-assessment framework supported by IoMT technology
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Abstract<p>As COVID-19 pandemic continued to propagate, millions of lives are currently at risk especially elderly, people with chronic conditions and pregnant women. Iraq is one of the countries affected by the COVID-19 pandemic. Currently, in Iraq, there is a need for a self-assessment tool to be available in hand for people with COVID-19 concerns. Such a tool would guide people, after an automated assessment, to the right decision such as seeking medical advice, self-isolate, or testing for COVID-19. This study proposes an online COVID-19 self-assessment tool supported by the internet of medical things (IoMT) technology as a means to fight this pandemic and mitigate the burden on our nation</p> ... Show More
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Publication Date
Thu Nov 19 2020
Journal Name
Indonesian Journal Of Chemistry
Determination of Eugenol in Personal-Care Products by Dispersive Liquid-Liquid Microextraction Followed by Spectrophotometry Using &lt;i&gt;p&lt;/i&gt;-Amino-&lt;i&gt;N,N&lt;/i&gt;-dimethylaniline as a Derivatizing Agent
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Two simple methods for the determination of eugenol were developed. The first depends on the oxidative coupling of eugenol with p-amino-N,N-dimethylaniline (PADA) in the presence of K3[Fe(CN)6]. A linear regression calibration plot for eugenol was constructed at 600 nm, within a concentration range of 0.25-2.50 μg.mL–1 and a correlation coefficient (r) value of 0.9988. The limits of detection (LOD) and quantitation (LOQ) were 0.086 and 0.284 μg.mL–1, respectively. The second method is based on the dispersive liquid-liquid microextraction of the derivatized oxidative coupling product of eugenol with PADA. Under the optimized extraction procedure, the extracted colored product was determined spectrophotometrically at 618 nm. A l

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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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