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Automatic Identification of Ear Patterns Based on Convolutional Neural Network
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Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in an image, possesses the unique characteristic that no two individuals share the same ear patterns. Consequently, our research proposes a system for individual identification based on ear traits, comprising three main stages: (1) pre-processing to extract the ear pattern (region of interest) from input images, (2) feature extraction, and (3) classification. Convolutional Neural Network (CNN) is employed for the feature extraction and classification tasks. The system remains invariant to scaling, brightness, and rotation. Experimental results demonstrate that the proposed system achieved an accuracy of 99.86% for all datasets.

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Publication Date
Fri Feb 04 2022
Journal Name
Neuroquantology
Detecting Damaged Buildings on Post-Hurricane Satellite Imagery based on Transfer Learning
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In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

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Publication Date
Fri Dec 20 2019
Journal Name
Iet Circuits, Devices & Systems
Multi‐bit error control coding with limited correction for high‐performance and energy‐efficient network on chip
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In the presence of deep submicron noise, providing reliable and energy‐efficient network on‐chip operation is becoming a challenging objective. In this study, the authors propose a hybrid automatic repeat request (HARQ)‐based coding scheme that simultaneously reduces the crosstalk induced bus delay and provides multi‐bit error protection while achieving high‐energy savings. This is achieved by calculating two‐dimensional parities and duplicating all the bits, which provide single error correction and six errors detection. The error correction reduces the performance degradation caused by retransmissions, which when combined with voltage swing reduction, due to its high error detection, high‐energy savings are achieved. The res

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Publication Date
Wed Jan 01 2020
Journal Name
Annals Of Tropical Medicine And Public Health
EFFECT OF EUCALYPTUS AND MYRTUS EXTRACTS IDENTIFICATION BY GAS CHROMATOGRAPHY-MASS SPECTROMETRY ON SOME SPECIES OF CANDIDA AS A MODEL OF MEDICAL PLANTS
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Publication Date
Wed Jun 10 2020
Journal Name
Annals Of Tropical Medicine & Public Health
EFFECT OF EUCALYPTUS AND MYRTUS EXTRACTS IDENTIFICATION BY GAS CHROMATOGRAPHY-MASS SPECTROMETRY ON SOME SPECIES OF CANDIDA AS A MODEL OF MEDICAL PLANTS
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The study showed that all extracts (aqueous, ethanolic and acetonic) of the leaves of Eucalyptus and Myrtus plants had a inhibitory effect on the growth of all types of yeasts studied, acetone extract recorded the highest inhibition of yeastat 100ppm concentration,The inhibition was 35mm, 34mm, 24mm and 20mm for Candida parapsilosis, Candida glabrata, Candida tropicalis and Candida albicans respectively, The experiments above showed the least significant differences at 0.05 level.The results ofE. Cammldulensis ethanolic tincture analysis has shown the presence of 44 biologically active substances. The main Eucalyptus leaves component was: 2-Bicyclo (2-2.1) heptanol (12.37%), Ledol (8.23%),1,2,4- Benzenetriol (8.45%) and that contain spathul

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Publication Date
Sun Mar 03 2013
Journal Name
Baghdad Science Journal
Synthesis and Identification of Some New Derivative of Trimethoprim and Paracetemol Drugs
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In this research two series of the new derivatives of Trimethoprim and paracetamol drugs have been prepared which known as a high medicinal effectiveness. Series (A) is including the interaction of diazonium salt of trimethoprim and coupling with some substituted phenol compounds (2-amino phenol, 3-ethyl phenol, 1-naphthol, 2-nitro phenol, Salbutamol). Series (B) is including the interaction coupling alkali solution of paracetamol with diazonium salt of some substituted aniline compounds (Benzedine, 2, 3-di chloro aniline, Trimethoprim, Anilinium chloride, 2-nitro- 4-chloro aniline).Chemical structures of all synthesized compounds were confirmed by UV-visible and FTIR spectroscopy.

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Publication Date
Wed Mar 16 2016
Journal Name
World Journal Of Pharmaceutical Research
Identification of some species of wireworm Agriotes spp.(Coleoptera: Elateridae) in Baghdad
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Publication Date
Sun Jan 01 2017
Journal Name
World Journal Of Pharmaceutical Research
IDENTIFICATION OF SOME SPECIES OF WIREWORM AGRIOTES SPP. (COLEOPTERA: ELATERIDAE) IN BAGHDAD
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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of The Mechanical Behavior Of Materials
Identification of the main causes of risks in engineering procurement construction projects
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Abstract<p>Many risks have adverse consequences for construction projects’ objectives such as quality, schedule, and cost. As engineering procurement construction (EPC) contracts gradually become one of the most common types used in implementing major large-scale construction projects, identifying common risk types and analyzing their root causes is important for developing measures to decrease and eliminate future risks in these types of contracts. The information about the main causes of risks was collected <italic>via</italic> well-structured questionnaires addressed to construction sector professionals and preparing lists of main potential risks in EPC/construction projects throu</p> ... Show More
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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Performance of Case-Based Reasoning Retrieval Using Classification Based on Associations versus Jcolibri and FreeCBR: A Further Validation Study
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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
Classification of Rural Road Network in Al-Najaf Governorate
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This study has dealt with, the issue of classification of rural road network , in addition to prepare a suggested for the classification for this network in Iraq , this classification account , the specifications and characteristics of rural roads, population, and the range taking of settlements , then this classification was applied on the rural road network in the Najaf province there are four categories of classification ,the first is major arterial rural roads divided into two major arterial and minor arterial roads , while the second category collected roads which was divided into minor arterial roads and main collected roads. The third category was represented by Local Roads , it has been divided into paved roads and unpaved, the f

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