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The impact of fun in the workplace In achieving internal marketing (Applied research)
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    The research aims to study the impact of the dimensions of fun in the workplace in achieving internal marketing And knowing the type of relationships That link the dimensions of fun in the workplace With each other, None of the researchers mentioned (to the researcher's knowledge) the link between fun in the workplace and internal marketing From this point of view the main objective is determined, which is to study the effect of fun in the workplace in internal marketing, The research was conducted at Al Salam Public Company for Communications and Information Technology The research community was represented by (308) employees of the aforementioned company , Where a random sample was selected that included (116) employees representing (37.6%) of the total community, The questionnaire was the main tool in collecting data and information As it was distributed randomly to company employees  through assistance of human resources Manager with a view Data processing Many statistical methods were used most notably, standard deviation ,SMA ,Pearson Correlation Coefficient And structural equations model, The most prominent results of the research The existence of a significant correlation and positive relationship between fun in the workplace and internal marketing for the employees of the General Salam Company, also Fun in the workplace have significant and positive effect in the internal marketing of the employees of the aforementioned company , The current research is considered a general review of the concept of fun in the workplace And its impact on achieving internal marketing

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Advanced Intelligent Data Hiding Using Video Stego and Convolutional Neural Networks
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Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
An Efficient Image Encryption Using a Dynamic, Nonlinear and Secret Diffusion Scheme
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The growing use of tele

This paper presents a new secret diffusion scheme called Round Key Permutation (RKP) based on the nonlinear, dynamic and pseudorandom permutation for encrypting images by block, since images are considered particular data because of their size and their information, which are two-dimensional nature and characterized by high redundancy and strong correlation. Firstly, the permutation table is calculated according to the master key and sub-keys. Secondly, scrambling pixels for each block to be encrypted will be done according the permutation table. Thereafter the AES encryption algorithm is used in the proposed cryptosystem by replacing the linear permutation of ShiftRows step with the nonlinear and secret pe

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Publication Date
Sun Dec 01 2013
Journal Name
Baghdad Science Journal
Notes on Approximately Pure Submodules
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Let R be a commutative ring with identity 1 and M be a unitary left R-module. A submodule N of an R-module M is said to be approximately pure submodule of an R-module, if for each ideal I of R. The main purpose of this paper is to study the properties of the following concepts: approximately pure essentialsubmodules, approximately pure closedsubmodules and relative approximately pure complement submodules. We prove that: when an R-module M is an approximately purely extending modules and N be Ap-puresubmodulein M, if M has the Ap-pure intersection property then N is Ap purely extending.

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Publication Date
Tue Jun 01 2021
Journal Name
Periodicals Of Engineering And Natural Sciences
Steganography using dual tree complex wavelet transform with LSB indicator technique
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Image steganography is undoubtedly significant in the field of secure multimedia communication. The undetectability and high payload capacity are two of the important characteristics of any form of steganography. In this paper, the level of image security is improved by combining the steganography and cryptography techniques in order to produce the secured image. The proposed method depends on using LSBs as an indicator for hiding encrypted bits in dual tree complex wavelet coefficient DT-CWT. The cover image is divided into non overlapping blocks of size (3*3). After that, a Key is produced by extracting the center pixel (pc) from each block to encrypt each character in the secret text. The cover image is converted using DT-CWT, then the p

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Scopus (6)
Crossref (5)
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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
F-Compact operator on probabilistic Hilbert space
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This paper deals with the F-compact operator defined on probabilistic Hilbert space and gives some of its main properties.

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Modern Mathematical Sciences
Coupled Laplace-Decomposition Method for Solving Klein- Gordon Equation
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In this paper, we consider a new approach to solve type of partial differential equation by using coupled Laplace transformation with decomposition method to find the exact solution for non–linear non–homogenous equation with initial conditions. The reliability for suggested approach illustrated by solving model equations such as second order linear and nonlinear Klein–Gordon equation. The application results show the efficiency and ability for suggested approach.

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Data Classification using Quantum Neural Network
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In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

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Publication Date
Sun Dec 07 2008
Journal Name
Baghdad Science Journal
Some Results on Reduced Rings
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The main purpose of this paper is to study some results concerning reduced ring with another concepts as semiprime ring ,prime ring,essential ideal ,derivations and homomorphism ,we give some results a bout that.

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Publication Date
Sun Jun 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Zinc Element Traces to Inhibit Scale Formation on Cooling Tower and Air Cooler Systems
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Calcium carbonate is predominantly present in aqueous systems, which is
commonly used in industrial processes. It has inverse solubility characteristics
resulting in the deposition of scale on heat transfer surface. This paper focuses on
developing methods for inhibition of calcium carbonate scale formation in cooling
tower and air cooler system where scaling can cause serious problems, ZnCl 2 and ZnI
2 has been investigated as scale inhibitor on AISI 316 and 304. ZnCl 2 were more
effective than ZnI 2 in both systems, and AISI 316 show more receptivity to the
chlorides salt compared to AISI 304. The inhibitors were more effective in cooling
tower than air cooler system. AISI 316 show more constant inhibition effic

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Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Fuzzy Wavenet (FWN) classifier for medical images
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    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

&n

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