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Estimation of mean photon number based on single photon detection of weak coherent pulses
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The demand for single photon sources in quantum key distribution (QKD) systems has necessitated the use of weak coherent pulses (WCPs) characterized by a Poissonian distribution. Ensuring security against eavesdropping attacks requires keeping the mean photon number (µ) small and known to legitimate partners. However, accurately determining µ poses challenges due to discrepancies between theoretical calculations and practical implementation. This paper introduces two experiments. The first experiment involves theoretical calculations of µ using several filters to generate the WCPs. The second experiment utilizes a variable attenuator to generate the WCPs, and the value of µ was estimated from the photons detected by the BB84 detection setup. The second experiment represents an accurate method for estimating the value of µ because of using single photon detectors with high timing resolution and low dark counts, in addition to using a Time-to-digital convertor with a bin size of 81 ps.                                                                                   

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
The effects of human error in the banking risks - Empirical study in a number of Iraqi private banks
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Abstract

This research aims to study human error effects in the banking risks in the private banks  through the measurement and testing of human error effect in every kind of banking risks types and stand on the most closely associated with the risks in order to focus on them and make appropriate processors have with respect to and increase the availability of skills and expertise required to carry out banking operations of error-free manner.

Find dealt with human error in terms of meaning and understandable, classifications and types, causes and consequences and its approaches and theories. Also addressed placed banking risks in terms of meaning and concept, species and entr

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The Impact of knowledge Workers in Organizational Excellence Field research in a number of the Iraqi industrial companies
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The Knowledge Workers is The Largest And Most Powerful Resource Of The Organizational Excellence it is A Precious  Treasure, Therefore Find Organizations at present is looking for them and seek to invest their ideas For achieving excellence, creativity and access to the excellence Organizational , As a result of their importance in terms of engagement and influence in the success or failure of the as an organizational Of The Research is Measuring The Correlation And  Impact Between Knowledge Workers And Organizational Excellence in Sample Of Companies Iraqi Industrial By Standing The Dimensions Of Knowledge Workers ( Characteristics , Skills , Roles , Competencies ) And

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Publication Date
Tue Jul 31 2012
Journal Name
Journal Of Babylon University/pure And Applied Sciences/
An Evaluation of the Effect of Bleaching Agent on Microhardness of a New Silorane-Based Restorative System and Methacrylate-Based Restorative Material
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Abstract Rasha Hameid Jehad Baghdad University Background: The high reactivity of hydrogen peroxide used in bleaching agents have raised important questions on their potential adverse effects on physical properties of restorative materials. The purpose of this in vitro study was to evaluate the effect of in-office bleaching agents on the microhardness of a new Silorane-based restorative material in comparison to methacrylate-based restorative material. Materials and method: Forty specimens of Filtek™ P90 (3M ESPE,USA) and Filtek™ Supreme XT (3M ESPE, USA) of (8mm diameter and 3m height) were prepared. All specimens were polished with Sof-Lex disks (3M ESPE, USA). All samples were rinsed and stored in incubator 37˚C for 24 ho

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Skull Stripping Based on the Segmentation Models
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Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor

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Publication Date
Fri Nov 11 2022
Journal Name
Al-mansour Journal
Text Cryptography Based on Three Different Keys
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Secure information transmission over the internet is becoming an important requirement in data communication. These days, authenticity, secrecy, and confidentiality are the most important concerns in securing data communication. For that reason, information hiding methods are used, such as Cryptography, Steganography and Watermarking methods, to secure data transmission, where cryptography method is used to encrypt the information in an unreadable form. At the same time, steganography covers the information within images, audio or video. Finally, watermarking is used to protect information from intruders. This paper proposed a new cryptography method by using thre

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Publication Date
Sat Jan 01 2011
Journal Name
Iraqi Journal Of Science
A CRYPTOGRAPHIC TECHNIQUE BASED ON AVL TREE
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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Engineering And Applied Sciences
New Data Security Method Based on Biometrics
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Merging biometrics with cryptography has become more familiar and a great scientific field was born for researchers. Biometrics adds distinctive property to the security systems, due biometrics is unique and individual features for every person. In this study, a new method is presented for ciphering data based on fingerprint features. This research is done by addressing plaintext message based on positions of extracted minutiae from fingerprint into a generated random text file regardless the size of data. The proposed method can be explained in three scenarios. In the first scenario the message was used inside random text directly at positions of minutiae in the second scenario the message was encrypted with a choosen word before ciphering

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Publication Date
Sat Aug 03 2024
Journal Name
Proceedings Of Ninth International Congress On Information And Communication Technology
Offline Signature Verification Based on Neural Network
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The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o

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Publication Date
Wed Jan 15 2025
Journal Name
International Journal Of Cloud Computing And Database Management
Deep video understanding based on language generation
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Vol. 6, Issue 1 (2025)

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Publication Date
Thu Aug 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Emotion Recognition System Based on Hybrid Techniques
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Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

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