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Green Innovation and its Impact in Reinforcing Sustainable Competitive Advantage: An Exploratory Study of Opinions of a Sample of Employees in the Karungi group in Kirkuk
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The development of the world, and in light of the intensity of competition highlighted the need to research and create a sustainable competitive advantage is sustained from an internal source in the company earned by the scarcity and difficulty of imitation by competitors, and this source is green innovation. In order to achieve the objective of the research, which is the diagnosis and analysis of the relationship between green innovation (in products, processes) and sustainable competitive advantage in the group of companies Kronji, was developed a default model of the research reflects the nature of the relationship and influence among its variables, the research adopted the questionnaire as a key tool for collecting data and information , Distributed to a sample of (94) workers tested using some statistical tools of data collected by the adoption of the program (SPSS.V.24). The research came to a number of conclusions, the most important one which is the green innovation , it linked and has a significant impact on sustainable competitive advantage, The biggest impact was on sustainable competitive advantage after green innovation in products, In view of the above, a number of proposals were presented, the most important of which is the need for the company's management to be concerned with green innovation through the establishment of green training courses to identify the importance of many concepts and standards that serve the environmental orientation, because the environmental trend has become a standard of achieving sustainable competitive advantage.  

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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Anomaly Detection Approach Based on Deep Neural Network and Dropout
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   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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Publication Date
Wed Oct 14 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Oral hygiene practices and self-perceived halitosis among dental students
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Background: Halitosis represents a common dental condition, although sufferers are often not conscious of it. It is common among humans around the world and is usually caused by an accumulation of bacteria in the mouth as a result of gum disease, food, or plaque. This study aimed to determine the prevalence of oral hygiene practices, smoking habits and halitosis among undergraduate dental students and correlate the oral hygiene practices, oral health conditions to the prevalence of self perceived oral malodor. Materials and Methods: Clinical examination of 250 dental students and a self-administered questionnaire were included in this study. A questionnaire was developed to assess the self-reported perception of oral breath, awareness of b

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Publication Date
Sat Jul 03 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Comparison between VG-levy and Kernel function estimation with application
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Publication Date
Thu Nov 01 2012
Journal Name
2012 International Conference On Advanced Computer Science Applications And Technologies (acsat)
Data Missing Solution Using Rough Set theory and Swarm Intelligence
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This paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estima

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Publication Date
Fri Jan 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Stamps extraction using local adaptive k- means and ISODATA algorithms
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<span>One of the main difficulties facing the certified documents documentary archiving system is checking the stamps system, but, that stamps may be contains complex background and surrounded by unwanted data. Therefore, the main objective of this paper is to isolate background and to remove noise that may be surrounded stamp. Our proposed method comprises of four phases, firstly, we apply k-means algorithm for clustering stamp image into a number of clusters and merged them using ISODATA algorithm. Secondly, we compute mean and standard deviation for each remaining cluster to isolate background cluster from stamp cluster. Thirdly, a region growing algorithm is applied to segment the image and then choosing the connected regi

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Publication Date
Sun Jun 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Carbonized Copolymers Nonwoven Nanofibers Composite: Surface Morphology and Fibers Orientation
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Carbonized nonwoven nanofibers composite were fabricated using the electrospinning method of a polymeric solution composite followed by heat treatment including stabilization and calcination steps. The spun polymeric solution was a binary polymer mixture/organic solvent. In this study, two types of polymers (Polymethylmethacrylate (PMMA) and Polyethylene glycol (PEG)) were used separately as a copolymer with the base polymer (Polyacrylonitrile (PAN)) to prepare a binary polymer mixture in a mixing ratio of 50:50. The prepared precursor solutions were used to prepare the precursor nanofibers composite (PAN: PMMA) and (PAN: PEG).  The fabricated precursors nonwoven fibers composite were stabilized and carbonized to produce carbon nonw

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Publication Date
Tue Oct 01 2013
Journal Name
Sensors And Actuators A: Physical
Enhanced energy harvesting using multiple piezoelectric elements: Theory and experiments
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Publication Date
Fri Feb 07 2020
Journal Name
Innovations In Pharmacy
Knowledge, Perception and Attitude Regarding Generic Medicines among Iraqi Physicians
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Objectives: The study aim was to explore the knowledge, perceptions, and attitudes of Iraqi physicians regarding generic and locally manufactured medicines. Methods: A total of 124 physicians were involved in this cross -sectional study. The convenience sample was collected from five public hospitals in Baghdad. A self-administered questionnaire was distributed and collected in-person. Fisher's Exact Test was used to measure the association between physician years of experience, gender and categorical (perception and knowledge) variables. Results: Most respondent answers regarding the knowledge of generic medicines were incorrect. Only up to one-third of the participants knew that generic medicines are therapeutically eq

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Publication Date
Fri Oct 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Novel Approximate Solutions for Nonlinear Initial and Boundary Value Problems
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This paper investigates an effective computational method (ECM) based on the standard polynomials used to solve some nonlinear initial and boundary value problems appeared in engineering and applied sciences. Moreover, the effective computational methods in this paper were improved by suitable orthogonal base functions, especially the Chebyshev, Bernoulli, and Laguerre polynomials, to obtain novel approximate solutions for some nonlinear problems. These base functions enable the nonlinear problem to be effectively converted into a nonlinear algebraic system of equations, which are then solved using Mathematica®12. The improved effective computational methods (I-ECMs) have been implemented to solve three applications involving nonli

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Publication Date
Sun Mar 02 2014
Journal Name
Baghdad Science Journal
On Strongly F – Regular Modules and Strongly Pure Intersection Property
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A submoduleA of amodule M is said to be strongly pure , if for each finite subset {ai} in A , (equivalently, for each a ?A) there exists ahomomorphism f : M ?A such that f(ai) = ai, ?i(f(a)=a).A module M is said to be strongly F–regular if each submodule of M is strongly pure .The main purpose of this paper is to develop the properties of strongly F–regular modules and study modules with the property that the intersection of any two strongly pure submodules is strongly pure .

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