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Artificial Intelligence Techniques to Identify Individuals through Palm Image Recognition
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Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep learning model was utilized to resize images and feature extraction. Finally, different ML classifiers have been tested for recognition based on the extracted features. The effectiveness of each classifier was assessed using various performance metrics. The results show that the proposed system works well, and all the methods achieved good results; however, the best results obtained were for the Support Vector Machine (SVM) with a linear kernel.

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Publication Date
Fri Oct 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Development of human resources and their role in achieving artificial intelligence A survey of the views of a sample of workers in the cement plant
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The research topic was chosen as a result of the importance of human resource in business organizations in general and the industrial process in particular. Without the human resource, business organizations cannot continue and achieve success and excellence, and the research problem has been diagnosed in the lack of sales of General Cement Company’s northern products, despite their distinctiveness, standing, and reputation in The market and its products with standard specifications, and through this problem, the following questions were raised:                                                    &nbs

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Publication Date
Thu Nov 01 2018
Journal Name
International Journal Of Advanced Research In Computer Engineering & Technology
Facial Emotion Recognition: A Survey
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Emotion could be expressed through unimodal social behaviour’s or bimodal or it could be expressed through multimodal. This survey describes the background of facial emotion recognition and surveys the emotion recognition using visual modality. Some publicly available datasets are covered for performance evaluation. A summary of some of the research efforts to classify emotion using visual modality for the last five years from 2013 to 2018 is given in a tabular form.

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Classification of Diseases in Oil Palm Leaves Using the GoogLeNet Model
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The general health of palm trees, encompassing the roots, stems, and leaves, significantly impacts palm oil production, therefore, meticulous attention is needed to achieve optimal yield. One of the challenges encountered in sustaining productive crops is the prevalence of pests and diseases afflicting oil palm plants. These diseases can detrimentally influence growth and development, leading to decreased productivity. Oil palm productivity is closely related to the conditions of its leaves, which play a vital role in photosynthesis. This research employed a comprehensive dataset of 1,230 images, consisting of 410 showing leaves, another 410 depicting bagworm infestations, and an additional 410 displaying caterpillar infestations. Furthe

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Publication Date
Tue Sep 19 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Palm Leaf as a Thermal Insulation Material
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This paper presents calculat,ion of thermal conductivity (K) of palm

leaf  experimentally  using  Lee s  disc  method   to  be  used  as   thermal

insulator. The therma l conducti vity is found to be equal to (k=0.03W/mK)

indicating  that  palm l eaf is a good thermal  insulator com pared to the other insulators. The effect of the thermal insulator   thickness  on temperature di lTt::rence,  heat   transfer    coefficient,   thermal     conductance,   thermal resistance,  thermal  insulation are in vestigated in this paper. It was  found that

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Publication Date
Wed Jul 11 2018
Journal Name
Iraqi Journal Of Agricultural Sciences
SYNTHESIS OF RAYON FROM DATE PALM FRONDS ‫
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The artificial silk (Rayon) was produced from the fronds of date palms which was taken from date palm trees (type Al-Zahdi) from the Iraqi gardens. Two main parts of the frond, namely leaves and stalks were used in this study to produce rayon. The palm fronds were converted into a powder of 90-180 micrometers. Major steps were used to produce rayon; delignification, bleaching and finally dissolution. Modified organosolv method which uses organic solvent method was applied to remove high lignin content. Three variables were studied in the delignification process: temperature, the ratio of ethanol to water and digestion time. The results showed that the best percent of lignin removal was (97%) which occured at; digestion time (80 minutes), te

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Publication Date
Sun Oct 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Intelligence framework dust forecasting using regression algorithms models
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<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

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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
Wed Jul 17 2019
Journal Name
Advances In Intelligent Systems And Computing
A New Arabic Dataset for Emotion Recognition
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In this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
The strengthening of strategic intelligence through an applied effective reality survey of strategic information systems An applied research in mobile companies in the Kurdistan Region
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Abstract

Purpose: The research attempts to Stand on the reality of the effective application of of strategic information systems in telecommunications companies in the Kurdistan Region, and what is the amount of the impact of such systems on promoting of Strategic Intelligence.

Design/Methodology/Approach: The Applied method has been used, In order to achieve the objectives of the research has been the development of a questionnaire prepared for this purpose and then distributed to (11) Company of Iraqi communications operating in Kurdistan Region companies, it has been used questionnaire to collect data in order to develop

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Publication Date
Sat Oct 29 2022
Journal Name
Current Trends In Geotechnical Engineering And Construction
Identify the Critical Risk Factors at the Tendering Phase in Iraq
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Risk factors can be considered unique in construction projects, especially in tendering phase. This research is directed to recognize and evaluate the importance of critical risk factors in the tendering phase related to Iraq’s construction project. As a rule, construction projects are impacted by risk factors throughout the project life cycle; without identifying and allocating these risk factors, the project cannot succeed. In this paper, the open and closed questionnaires are used to categorize the critical risk factors in tendering phase. Research aims to recognize the factors that influence the success of tendering phase, to determine the correct response to the risk’s factors in this research article, (IBM, SPSS, V23) package has

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