This paper presents a robust algorithm for the assessment of risk priority for medical equipment based on the calculation of static and dynamic risk factors and Kohnen Self Organization Maps (SOM). Four risk parameters have been calculated for 345 medical devices in two general hospitals in Baghdad. Static risk factor components (equipment function and physical risk) and dynamics risk components (maintenance requirements and risk points) have been calculated. These risk components are used as an input to the unsupervised Kohonen self organization maps. The accuracy of the network was found to be equal to 98% for the proposed system. We conclude that the proposed model gives fast and accurate assessment for risk priority and it works as p

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In this paper, the goal of proposed method is to protect data against different types of attacks by unauthorized parties. The basic idea of proposed method is generating a private key from a specific features of digital color image such as color (Red, Green and Blue); the generating process of private key from colors of digital color image performed via the computing process of color frequencies for blue color of an image then computing the maximum frequency of blue color, multiplying it by its number and adding process will performed to produce a generated key. After that the private key is generated, must be converting it into the binary representation form. The generated key is extracted from blue color of keyed image then we selects a c

The choice of binary Pseudonoise (PN) sequences with specific properties, having long period high complexity, randomness, minimum cross and auto- correlation which are essential for some communication systems. In this research a nonlinear PN generator is introduced . It consists of a combination of basic components like Linear Feedback Shift Register (LFSR), ?-element which is a type of RxR crossbar switches. The period and complexity of a sequence which are generated by the proposed generator are computed and the randomness properties of these sequences are measured by well-known randomness tests.

Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security

          The subject of marketing culture and mental image is one of the important topics in the field of management. There is no study that combines these two variables. The research is important because of the increasing importance of the subject. The future direction of the company in question will support the company's economic and marketing responsibilities. And reflect the company's mental image, as a culture that contributes to changing the reality of the organization investigated by polling the views of a sample of managers in the General Company for Vegetable Oil Industry, which (30) out of the (65) individual, and There are two hypotheses of research: There is a significant

Mixed ligand complexes of bivalent metal ions, viz; M= Fe(II),Co(II),Ni(II),Cu(II), Zn(II), Cd (II), and Hg(II) of the composition Na2[M (Amox)(Sac)3] in 1:1:3 molar ratio, (where Amox = Amoxicillin tryhydrate (C16H19N3O5S.H2O) and Sac = Saccharine(C7H5NO3S) have been synthesized and characterized by repeated melting point determination, Solubility, Molar conductivity, determination the percentage of the metal in the complexes by flame(AAS), FT-IR, magnetic susceptibility measurements and electronic spectral data. The ligands and their metal complexes have been screened for their biological activity against selected microbial strains (gram +ve) and (gram -ve).

Mixed ligand complexes of bivalent metal ions, viz; M= Fe(II),Co(II),Ni(II),Cu(II), Zn(II), Cd (II), and Hg(II) of the composition Na2[M (Amox)(Sac)3] in 1:1:3 molar ratio, (where Amox = Amoxicillin tryhydrate (C16H19N3O5S.H2O) and Sac = Saccharine(C7H5NO3S) have been synthesized and characterized by repeated melting point determination, Solubility, Molar conductivity, determination the percentage of the metal in the complexes by flame(AAS), FT-IR, magnetic susceptibility measurements and electronic spectral data. The ligands and their metal complexes have been screened for their biological activity against selected microbial strains (gram +ve) and (gram -ve).

The ligand 2-[1-(1H-indol-3-yl)ethylimino) methyl]naphthalene-1-ol, derived from 1-hydroxy-2-naphthaldehyde and 2-(1H-indol-3-yl)ethylamine, was used to produce a new sequence of metal ions complexes. Thus ligand reactions with NiCl₂.6H₂O, PdCl₂, FeCl_3.6H₂O and H₂PtCl₆.6H₂O were sequentially made to collect mono-nuclear Ni(II), Pd(II), Fe (III), and Pt(IV). (IR or FTIR), Ultraviolet Reflective (UV–visible), Mass Spectra analysis, Bohr-magnetic (B.M.), metal content, chloride content and molar conductivity have been the defining features of the composites. The Fe(III) and Pt(IV) complexes have octahedral geometries, while the Ni(II) complex has tetra