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The effects of big data, artificial intelligence, and business intelligence on e-learning and business performance: Evidence from Jordanian telecommunication firms
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This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big Data External and Internal, Innovative Usage, Indexing, and Sources Accuracy. In addition, Artificial intelligence positively affects business performance, including Data Accuracy, Data Transparency, Data Speed, and Creative Thinking and Learning. Moreover, business intelligence has a direct and positive impact on business performance, including Data Warehouse, Data Mining, Business Process Management, and Competitive Intelligence. In addition, the findings indicate that e-learning which represents system quality, information quality, and self-efficacy has a positive relationship on enhancing business performance. Interestingly, the present findings are inconsistent with those of previous studies showing the variables of interest which have no effect on e-learning and business performance. Taken together, the findings of this study suggest that firms should begin to apply processes related with applying e-learning and developing business performance. The novelty of the present study lies in highlighting the key dimensions of big data, artificial intelligence, and business intelligence when it comes to enhancing e-learning and business performance at Jordanian telecommunications industry.

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Publication Date
Wed Jan 08 2025
Journal Name
Interventional Cardiology
Intravascular Foreign Bodies Retrieval: Navigating Differences From Childhood to Adulthood
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Publication Date
Fri Mar 20 2009
Journal Name
Ijcsns International Journal Of Computer Science And Network Security
Pre-processing Importance for Extracting Contours from Noisy Echocardiographic Images
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Contours extraction from two dimensional echocardiographic images has been a challenge in digital image processing. This is essentially due to the heavy noise, poor quality of these images and some artifacts like papillary muscles, intra-cavity structures as chordate, and valves that can interfere with the endocardial border tracking. In this paper, we will present a technique to extract the contours of heart boundaries from a sequence of echocardiographic images, where it started with pre-processing to reduce noise and produce better image quality. By pre-processing the images, the unclear edges are avoided, and we can get an accurate detection of both heart boundary and movement of heart valves.

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Publication Date
Fri Feb 14 2020
Journal Name
Progress In Industrial Ecology, An International Journal
3D image reconstruction from its 2D projection - a simulation study
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A simulation study of using 2D tomography to reconstruction a 3D object is presented. The 2D Radon transform is used to create a 2D projection for each slice of the 3D object at different heights. The 2D back-projection and the Fourier slice theorem methods are used to reconstruction each 2D projection slice of the 3D object. The results showed the ability of the Fourier slice theorem method to reconstruct the general shape of the body with its internal structure, unlike the 2D Radon method, which was able to reconstruct the general shape of the body only because of the blurring artefact, Beside that the Fourier slice theorem could not remove all blurring artefact, therefore, this research, suggested the threshold technique to eliminate the

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Lactic Acid Bacteria (LAB) with Probiotic Potential from Dengke Naniura
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Dengke Naniura is a traditional food from Sumatera Utara, Indonesia, that is produced through fermenting process, and this food is believed to contain high probiotics. The objective of the current research is to determine the potential of LAB as a probiotic that has been obtained from Dengke Naniura. Dengke Naniura was traditionally prepared from Cyprinus carpio. Four LABs have been successfully isolated from Dengke Naniura, such as D7DA3, D7B3, D7DBF and D7DN3. Those four LAB isolates were identified as Lactobacillus sp. This result has been confirmed by the non-spore forming bacterium, non-motile, and Gram-positive. Also, it has been supported by biochemical test, for the example Voges Proskauer, catalase test, Methyl

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Publication Date
Sat Jun 01 2024
Journal Name
Ecological Engineering & Environmental Technology
Employing Phytoremediation Methods to Extract Heavy Metals from Polluted Soils
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The phytoremediation technique has become very efficient for treating soil contaminated with heavy metals. In this study, a pot experiment was conducted where the Dodonaea plant (known as hops) was grown, and soil previously contaminated with metals (Zn, Ni, Cd) was added at concentrations 100, 50, 0 mg·kg-1 for Ni and Zn, and at concentrations of 0, 5, 10 mg·kg-1 for cadmium. Irrigation was done within the limits of the field capacity of the soil. Cadmium, nickel and zinc was estimated in the soil to find out the capacity of plants to the absorption of heavy and contaminated metals by using bioconcentration factors (BCFs), bioaccumulation coefficient (BAC) and translocation factor (TF). Additionally, BCF values of both Ni and Zn were l

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Facial Emotion Recognition from Videos Using Deep Convolutional Neural Networks
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Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

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Publication Date
Sat Dec 31 2022
Journal Name
Al-kindy College Medical Journal
Pulmonary CT findings in Patients Recovered from COVID-19 Pneumonia
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Background: The COVID-19 infection is a more recent pandemic disease all over the world and studying the pulmonary findings on survivors of this disease has lately commenced.

Objective: We aimed to estimate the cumulative percentage of whole radiological resolution after 3 months from recovery and to define the residual chest CT findings and exploring the relevant affecting factors.

Subjects and Methods: Patients who had been previously diagnosed with COVID-19 pneumonia confirmed by RT-PCR test and had radiological evidence of pulmonary involvement by Chest CT during the acute illness were included in the present study. The radiol

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
5'-nucleoridase activity in sera from iraq children with leukemia
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Enzyme activity were studied in the sera of children with leukemia than healthy children, where 31 cases were studied, including 21 cases of patients with acute lymphatic leukemia

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Publication Date
Sat Apr 05 2025
Journal Name
2025 Ieee 4th International Conference On Computing And Machine Intelligence (icmi)
From Pixels to Diagnosis: AI-Powered CNN for Pneumonia Detection
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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The market value between the two dilemmas of profit distribution and retention: an analytical study in the Iraqi stock market
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Abstract:

             The distribution or retention of profits is the third decision among financial management decisions in terms of priority, whether at the level of theory or practice, as the issue of distribution or retention is multi-party in terms of influence and impact, as determining the optimal percentage for each component is still the subject of intellectual debate because these decisions are linked to the future of the organization and several considerations, The research focus on the nature of the policies followed by the Iraqi banking sector As the sample chosen by the intentional sampling method was represented by the Commercial Bank of

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