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A true random number generator based on the photon arrival time registered in a coincidence window between two single-photon counting modules
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True random number generators are essential components for communications to be conconfidentially secured. In this paper a new method is proposed to generate random sequences of numbers based on the difference of the arrival times of photons detected in a coincidence window between two single-photon counting modules

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Publication Date
Wed Apr 25 2018
Journal Name
Oriental Journal Of Chemistry
Diagnosis, Structure, and In vitro Antimicrobial and Antifungal Evaluation of some Amino benzoic acids, derived Ligand Schiff base and their Mixed Complexes with Cu(II), Hg(II), Mn(II), Ni(II) and Co(II)
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Publication Date
Thu Dec 01 2022
Journal Name
Iraqi Journal Of Physics
Detection of Physical and Chemical Parameters Using Water Indices (NDWI, MNDWI, NDMI, WRI, and AWEI) for Al-Abbasia River in Al-Najaf Al-Ashraf Governorate Using Remote Sensing and Geographic Information System (GIS) Techniques
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The purpose of this study was to find out the connection between the water parameters that were examined in the laboratory and the water index acquired from the examination of the satellite image of the study area. This was accomplished by analysing the Landsat-8 satellite picture results as well as the geographic information system (GIS). The primary goal of this study is to develop a model for the chemical and physical characteristics of the Al-Abbasia River in Al-Najaf Al-Ashraf Governorate. The water parameters employed in this investigation are as follows: (PH, EC, TDS, TSS, Na, Mg, K, SO4, Cl, and NO3). To collect the samples, ten sampling locations were identified, and the satellite image was obtained on the

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Retrieving Encrypted Images Using Convolution Neural Network and Fully Homomorphic Encryption
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A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

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Publication Date
Thu Dec 31 2020
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
STUDY THE INHIBITION ACTIVITY OF PURIFIED BACTERIOCIN FROM LOCAL ISOLATION Lactococcuslactis ssp. lactisagainst SOME PATHOGENIC BACTERIAL SPECIES ISOLATED FROM CLINICAL SAMPLES: دراسة الفعالية التثبيطية للبكتريوسين المنقى من العزلة المحلية Lactococcuslactis ssp. Lactis تجاه بعض البكتريا الممرضة المعزولة من عينات سريرية
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This study aimed to study the inhibition activity of purified bacteriocin produced from the local isolation Lactococcuslactis ssp. lactis against pathogenic bacteria species isolated from clinical samples in some hospitals Baghdad city. Screening of L. lactis ssp. Lactis and isolated from the intestines fish and raw milk was performed in well diffusion method. The results showed that L. lactis ssp. lactis (Lc4) was the most efficient isolate in producing the bacteriocin as well observed inhibitory activity the increased that companied with the concentration, the concentration of the twice filtrate was better in obtaining higher inhibition diameters compared to the one-fold concentration. The concentrate

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Publication Date
Mon Aug 19 2024
Journal Name
Journal Of Metastable And Nanocrystalline Materials
The Structural, Magnetic, and Electrochemical Properties of Composite PAni/Co<sub>0.2</sub>Mn<sub>0.8</sub>Fe<sub>2</sub>O<sub>4</sub>
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The current work concerns preparing cobalt manganese ferrite (Co0.2Mn0.8Fe2O4) and decorating it with polyaniline (PAni) for supercapacitor applications. The X-ray diffraction findings (XRD) manifested a broad peak of PAni and a cubic structure of cobalt manganese ferrite with crystal sizes between 21 nm. The pictures were taken with a field emission scanning electron microscope (FE-SEM), which evidenced that the PAni has nanofibers (NFs) structures, grain size 33 – 55 nm, according to the method of preparation, where the hydrothermal method was used. The magnetic measurements (VSM) that were conducted at room temperature showed that the samples had definite magnetic properties. Additionally, it was noted that the saturation magnetizatio

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Publication Date
Fri Aug 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Sub–Nyquist Frequency Efficient Audio Compression
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This paper presents the application of a framework of fast and efficient compressive sampling based on the concept of random sampling of sparse Audio signal. It provides four important features. (i) It is universal with a variety of sparse signals. (ii) The number of measurements required for exact reconstruction is nearly optimal and much less then the sampling frequency and below the Nyquist frequency. (iii) It has very low complexity and fast computation. (iv) It is developed on the provable mathematical model from which we are able to quantify trade-offs among streaming capability, computation/memory requirement and quality of reconstruction of the audio signal. Compressed sensing CS is an attractive compression scheme due to its uni

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Publication Date
Thu Nov 01 2018
Journal Name
2018 1st Annual International Conference On Information And Sciences (aicis)
Speech Emotion Recognition Using Minimum Extracted Features
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Recognizing speech emotions is an important subject in pattern recognition. This work is about studying the effect of extracting the minimum possible number of features on the speech emotion recognition (SER) system. In this paper, three experiments performed to reach the best way that gives good accuracy. The first one extracting only three features: zero crossing rate (ZCR), mean, and standard deviation (SD) from emotional speech samples, the second one extracting only the first 12 Mel frequency cepstral coefficient (MFCC) features, and the last experiment applying feature fusion between the mentioned features. In all experiments, the features are classified using five types of classification techniques, which are the Random Forest (RF),

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Simplified Novel Approach for Accurate Employee Churn Categorization using MCDM, De-Pareto Principle Approach, and Machine Learning
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Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
Total Global Dominator Coloring of Trees and Unicyclic Graphs
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          A total global dominator coloring of a graph  is a proper vertex coloring of  with respect to which every vertex  in  dominates a color class, not containing  and does not dominate another color class. The minimum number of colors required in such a coloring of  is called the total global dominator chromatic number, denoted by . In this paper, the total global dominator chromatic number of trees and unicyclic graphs are explored.

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Publication Date
Sun Jan 05 2025
Journal Name
Science Journal Of University Of Zakho
DETECTION AND RECOGNITION OF IRAQI LICENSE PLATES USING CONVOLUTIONAL NEURAL NETWORKS
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Due to the large population of motorway users in the country of Iraq, various approaches have been adopted to manage queues such as implementation of traffic lights, avoidance of illegal parking, amongst others. However, defaulters are recorded daily, hence the need to develop a mean of identifying these defaulters and bring them to book. This article discusses the development of an approach of recognizing Iraqi licence plates such that defaulters of queue management systems are identified. Multiple agencies worldwide have quickly and widely adopted the recognition of a vehicle license plate technology to expand their ability in investigative and security matters. License plate helps detect the vehicle's information automatically ra

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