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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
Thu Oct 31 2024
Journal Name
Iraqi Geological Journal
Artificial Neural Network Application to Permeability Prediction from Nuclear Magnetic Resonance Log
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Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is use

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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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Publication Date
Wed Nov 29 2023
Journal Name
International Journal Of Advances In Scientific Research And Engineering (ijasre), Issn:2454-8006, Doi: 10.31695/ijasre
Yolo Versions Architecture: Review
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Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed.  A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing

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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Advances In Scientific Research And Engineering
Yolo Versions Architecture: Review
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Deep learning techniques are used across a wide range of fields for several applications. In recent years, deep learning-based object detection from aerial or terrestrial photos has gained popularity as a study topic. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles andclassification probabilities for an image. In layman's terms, it is a technique for instantly identifying and rec

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Publication Date
Thu Jan 04 2024
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Achieving customer satisfaction by booking electronic flight tickets via the Internet of Things technology
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Abstract:

                The aim of this research is to highlight the importance of achieving customer satisfaction by using information technology and Internet networks in the process of purchasing flight tickets, and switching from the traditional method of purchasing and payment operations to the electronic method, to reduce the financial and non-financial risks associated with the traditional purchasing process, as well as saving time, effort and costs for the customer. The researcher used the deductive approach in linking the variables (achieving customer satisfaction and Internet of Things technology for booking electronic tickets)

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Publication Date
Sun Jun 02 2019
Journal Name
Journal Of The College Of Languages (jcl)
The Exploitation of Carmen Valero Garces' Theory in the Criticism of Literary Texts: Saleh al-Jafari's Arabic Translation of "Rubbayat al-Khayyam" as a: کاربست نظریه¬ی کارمن والرو گارسس در نقد ترجمه¬ی ادبی (مورد مطالعه: تعریب صالح الجعفری از رباعیات خیام)
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There is a mutual relationship between the form of a text and its meaning so as separating these two or devaluating the role of one of them leads to the absence of the value therein. Thus, a translation is important as to how it relates the details of a text. That is, the text has special features which go beyond form, and these set out its distinctiveness. Here, we tackle Saleh al-Jafari's Arabic translation of  "Rubbayat al-Khayyam" of Naysapour descriptively and analytically by depending on extracts from the original text. This translation is evaluated on the basis of Spanish critic Maria Carmen Valero Garces. Herein, we discuss the effectiveness of this theory in the criticism of literary texts. It has been concluded that al-Jaf

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Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
Development Binary Search Algorithm
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There are many methods of searching large amount of data to find one particular piece of information. Such as find name of person in record of mobile. Certain methods of organizing data make the search process more efficient the objective of these methods is to find the element with least cost (least time). Binary search algorithm is faster than sequential and other commonly used search algorithms. This research develops binary search algorithm by using new structure called Triple, structure in this structure data are represented as triple. It consists of three locations (1-Top, 2-Left, and 3-Right) Binary search algorithm divide the search interval in half, this process makes the maximum number of comparisons (Average case com

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Publication Date
Thu Jun 01 2017
Journal Name
International Journal Of Applied Engineering Research
A Proposed Method for Generating a Private Key Using Digital Color Image Features
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In this paper, the goal of proposed method is to protect data against different types of attacks by unauthorized parties. The basic idea of proposed method is generating a private key from a specific features of digital color image such as color (Red, Green and Blue); the generating process of private key from colors of digital color image performed via the computing process of color frequencies for blue color of an image then computing the maximum frequency of blue color, multiplying it by its number and adding process will performed to produce a generated key. After that the private key is generated, must be converting it into the binary representation form. The generated key is extracted from blue color of keyed image then we selects a c

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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
Proposing a General Formula for Evaluating the Parametric Cost Using MLR Method
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This research takes up address the practical side by taking case studies for construction projects that include the various Iraqi governorates, as it includes conducting a field survey to identify the impact of parametric costs on construction projects and compare them with what was reached during the analysis and the extent of their validity and accuracy, as well as adopting the approach of personal interviews to know the reality of the state of construction projects. The results showed, after comparing field data and its measurement in construction projects for the sectors (public and private), the correlation between the expected and actual cost change was (97.8%), and this means that the data can be adopted in the re

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Publication Date
Tue Sep 11 2018
Journal Name
Iraqi Journal Of Physics
Analytical study of high absorption region of the absorption edge of a-Si:H using nonlinear regression method
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This research is concerned with the re-analysis of optical data (the imaginary part of the dielectric function as a function of photon energy E) of a-Si:H films prepared by Jackson et al. and Ferlauto et al. through using nonlinear regression fitting we estimated the optical energy gap and the deviation from the Tauc model by considering the parameter of energy photon-dependence of the momentum matrix element of the p as a free parameter by assuming that density of states distribution to be a square root function. It is observed for films prepared by Jackson et al. that the value of the parameter p for the photon energy range is is close to the value assumed by the Cody model and the optical gap energy is which is also close to the value

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