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jeasiq-2095
The role of corporate merger in achieving synergy (Analytical research in a sample of companies of the Iraqi Ministry of Industry and Minerals)
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The research aims to shed light on the recent experience in the Iraqi business environment, which is the experience of the merger. To evaluate a recent experience in an important sector of the Iraqi business sectors, namely the industrial sector to enable decision-makers to review that experience to judge the extent of its success and address some of the lapses that experience that by measuring synergies can be judged on the success of the merger experience or not. The research community is the governmental industrial sector. The research sample included six cases of merger (14) companies before the merger. The Holt method was used to predict the net sales and total cost values ​​before the merger as if it were not merged. The researcher reached a number of conclusions, the most important of which is that the merger achieved cost synergies for all cases of merger, and other conclusions were achieved synergistic net sales of part of the merger cases such as the General Company for Steel Industries and the General Company for Food Industries Companies that did not achieve consistency in net sales, as well as there are points of failure in the merger of the General Company for Electrical Industries, the General Company for Metallurgical Industries, the General Company for Design and Execution of Projects and the General Electronic Systems Company for not achieving synergies at the level of net sales

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Publication Date
Fri Jan 01 2016
Journal Name
Modern Applied Science
Hybrid Methodology for Image Segmentation Based on Active Contour Module and Alpha-Shape Theory
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The concept of the active contour model has been extensively utilized in the segmentation and analysis of images. This technology has been effectively employed in identifying the contours in object recognition, computer graphics and vision, biomedical processing of images that is normal images or medical images such as Magnetic Resonance Images (MRI), X-rays, plus Ultrasound imaging. Three colleagues, Kass, Witkin and Terzopoulos developed this energy, lessening “Active Contour Models” (equally identified as Snake) back in 1987. Being curved in nature, snakes are characterized in an image field and are capable of being set in motion by external and internal forces within image data and the curve itself in that order. The present s

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Publication Date
Mon Jul 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Solving Some Fractional Partial Differential Equations by Invariant Subspace and Double Sumudu Transform Methods
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      In this paper, several types of space-time fractional partial differential equations has been solved by using most of special double linear integral transform ”double  Sumudu ”. Also, we are going to argue the truth of these solutions by another analytically method “invariant subspace method”. All results are illustrative numerically and graphically.

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Publication Date
Tue Jun 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Between Partial Least Square Regression(PLSR) and Tree Regression by Using Simulation(RT).
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This research discussed, the process of comparison between the regression model of partial least squares and tree regression, where these models included two types of statistical methods represented by the first type "parameter statistics" of the partial least squares, which is adopted when the number of variables is greater than the number of observations and also when the number of observations larger than the number of variables, the second type is the "nonparametric statistic" represented by tree regression, which is the division of data in a hierarchical way. The regression models for the two models were estimated, and then the comparison between them, where the comparison between these methods was according to a Mean Square

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Publication Date
Sat Sep 21 2024
Journal Name
Asian Pacific Journal Of Cancer Prevention
Oncolytic Newcastle Disease Virus and Photodynamic Therapy as Dual Approach for Breast Cancer Treatment
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Objective: We hypothesized that attacking cancer cells by combining various modes of action can hinder them from taking the chance to evolve resistance to treatment. Incorporation of photodynamic therapy (PDT) with oncolytic virotherapy might be a promising dual approach to cancer treatment. Methods: NDV AMHA1 strain as virotherapy in integration with aminolaevulinic acid (ALA) using low power He-Ne laser as PDT in the existing work was examined against breast cancer cells derived from Iraqi cancer patients named (AMJ13). This combination was evaluated using Chou–Talalay analysis. Results: The results showed an increased killing rate when using both 0.01 and 0.1 Multiplicity of infection (MOI) of the virus when combined with a dose of 617

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Publication Date
Sun Jun 11 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Metal (II) Complexes with Tridentate N, N,O Ligand: Synthesis, Characterization and Biological Studies 
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 The preparation of some new coordination compounds for nikel (II), manganese (II), copper (II), cobalt (II)and mercury (II), with ligand obtained from Benzoinand2-amino pyridine.The ligand[6-(2-hydroxy-1,2-diphenylethylideneamino)pyridin-3-ylium)](L) was made from reactin ethanol with metal salts in (1:1)(metal : ligand)ratio.[MLCl] was the inclusive formula of the complexes where M= Mn(II),Co(II),Ni(II),Cu(II) and Hg(II). Metal analysis by electronic spectra, atomic absorption ,infrared spectra, 1H&13C-NMR(only ligand)spectral studies, magnetic moment and molar conductance measurements used to describe the compounds.The determinations indicated that the ligand coordinates with the metal (II) ion in neutral tridentate manner th

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Bayesian Tobit Quantile Regression Model Using Double Adaptive elastic net and Adaptive Ridge Regression
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     Recently Tobit  Quantile Regression(TQR) has emerged as an important tool in statistical analysis . in order to improve the parameter estimation in (TQR) we proposed Bayesian hierarchical model with double adaptive elastic net technique  and Bayesian hierarchical model with adaptive ridge regression technique .

 in double adaptive elastic net technique we assume  different penalization parameters  for penalization different regression coefficients in both parameters λ1and  λ, also in adaptive ridge regression technique we assume different  penalization parameters for penalization different regression coefficients i

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Publication Date
Tue Jan 31 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
Survey on intrusion detection system based on analysis concept drift: Status and future directions
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Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor

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Publication Date
Sun Dec 03 2017
Journal Name
Baghdad Science Journal
Network Self-Fault Management Based on Multi-Intelligent Agents and Windows Management Instrumentation (WMI)
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This paper proposed a new method for network self-fault management (NSFM) based on two technologies: intelligent agent to automate fault management tasks, and Windows Management Instrumentations (WMI) to identify the fault faster when resources are independent (different type of devices). The proposed network self-fault management reduced the load of network traffic by reducing the request and response between the server and client, which achieves less downtime for each node in state of fault occurring in the client. The performance of the proposed system is measured by three measures: efficiency, availability, and reliability. A high efficiency average is obtained depending on the faults occurred in the system which reaches to

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Publication Date
Thu Feb 09 2023
Journal Name
Artificial Intelligence Review
Community detection model for dynamic networks based on hidden Markov model and evolutionary algorithm
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Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction
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Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

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