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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
Tue Jan 01 2013
Journal Name
Thesis
User Authentication Based on Keystroke Dynamics Using Artificial Neural Networks
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Computer systems and networks are being used in almost every aspect of our daily life, the security threats to computers and networks have increased significantly. Usually, password-based user authentication is used to authenticate the legitimate user. However, this method has many gaps such as password sharing, brute force attack, dictionary attack and guessing. Keystroke dynamics is one of the famous and inexpensive behavioral biometric technologies, which authenticate a user based on the analysis of his/her typing rhythm. In this way, intrusion becomes more difficult because the password as well as the typing speed must match with the correct keystroke patterns. This thesis considers static keystroke dynamics as a transparent layer of t

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Publication Date
Mon Dec 24 2018
Journal Name
Civil Engineering Journal
Artificial Neural Network Model for the Prediction of Groundwater Quality
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The present article delves into the examination of groundwater quality, based on WQI, for drinking purposes in Baghdad City. Further, for carrying out the investigation, the data was collected from the Ministry of Water Resources of Baghdad, which represents water samples drawn from 114 wells in Al-Karkh and Al-Rusafa sides of Baghdad city. With the aim of further determining WQI, four water parameters such as (i) pH, (ii) Chloride (Cl), (iii) Sulfate (SO4), and (iv) Total dissolved solids (TDS), were taken into consideration. According to the computed WQI, the distribution of the groundwater samples, with respect to their quality classes such as excellent, good, poor, very poor and unfit for human drinking purpose, was found to be

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Publication Date
Sun Nov 26 2017
Journal Name
Journal Of Engineering
Compression Index and Compression Ratio Prediction by Artificial Neural Networks
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Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites

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Publication Date
Fri Aug 01 2008
Journal Name
2008 International Symposium On Information Technology
Generating pairwise combinatorial test set using artificial parameters and values
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Publication Date
Tue Dec 20 2022
Journal Name
International Journal Of Emerging Technologies In Learning (ijet)
Effect of Augmented Reality Technology on Spatial Intelligence among High School Students
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Spatial Intelligence is a mental ability to understand and solve real-world problems. These visual-spatial representations are fundamental in learning various "STEM" topics, like digital drawing, art presentations, creating graphical representations, 2D designs. Opportunity to interact with real and/or virtual objects. It is a good opportunity in applying new techniques such as the augmenter, which is able to clarify mathematical tables, concepts and generalizations greatly to the visualization, understanding and mastery of concepts mathematically. The purpose of the research is to investigate impact of using AR technology in developing spatial intelligence for secondary school students, Baghdad. The quasi-experimental design was us

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Proposition of New Ensemble Data-Intelligence Models for Surface Water Quality Prediction
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Publication Date
Wed Oct 01 2014
Journal Name
Iraqi Journal Of Science
Removal of chromium (III) ions from its aqueous solution on adsorbent surfaces: Charcoal, Attapulgite and Date Palm Leaflet Powder
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In the present work, a study is carried out to remove chromium (III) from aqueous solution by: activated charcoal, attapulgite and date palm leaflet powder (pinnae). The effect of various parameters such as contact time, and temperature has been studied. The isotherm equilibrium data were well fitted by Freundlich and Langmuir isotherm models. The adsorption capacity of chromium (III) that was observed by activated charcoal, attapulgite and date palm leaflet powder (pinnae) increased with the rise of temperature when the concentrations of Cr (III) were 600, 700 and 100mg/L respectively. The greatest adsorption capacity ofactivated charcoal, attapulgite and date palm leaflet powder (pinnae) at 10°C was 7.51, 5.39 and 0.77mg.gˉ¹ respective

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Publication Date
Thu Feb 16 1995
Journal Name
. مجلة العلوم الزراعية العراقية 26 (1), 84-87
Effect of GA3 and Pollen Extract on Fruit set and Seed Production of Date Palm Cvs. Zahdi and Khaustawi.‏
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Publication Date
Wed Dec 01 2021
Journal Name
Int. J. Agricult. Stat. Sci
THE EFFECT OF PUTRESCINE AND SPERMIDINE ON SOMATIC EMBRYOGENESIS AND REGENERATION OF DATE PALM (PHOENIX DACTYLIFERA L.) CV. BARHEE
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The present study was conducted to determine the effect of different concentrations of putrescine and spermidine at all stages of regeneration (callogenesis, somatic embryos multiplication, germination and rooting)) of date palm cultivar Barhee. Shoot tips were eradicated from 2-3 years old offshoots, surface sterilized and inoculated onto Murashiege and Skoog, 1962 (MS) medium supplemented with 20 mg/L 2,4-D and 3 mg/L N6-2-isopentyl adenine (2ip). Primary callus was obtained after 24 weeks on the nutrient medium. Calli were then transferred onto fresh MS medium containing 0.0, 50, 100 or 150 mg/L of putrescine or spermidine individually. Results were recorded after 12 weeks. A significant increase in embryonic callus fresh weights reached

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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Water Process Engineering
Removal kinetics of organic carbon from palm oil mill effluent by native duckweeds and its potential as a biofertilizer
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