Cloud computing provides huge amount of area for storage of the data, but with an increase of number of users and size of their data, cloud storage environment faces earnest problem such as saving storage space, managing this large data, security and privacy of data. To save space in cloud storage one of the important methods is data deduplication, it is one of the compression technique that allows only one copy of the data to be saved and eliminate the extra copies. To offer security and privacy of the sensitive data while supporting the deduplication, In this work attacks that exploit the hybrid cloud deduplication have been identified, allowing an attacker to gain access to the files of other users based on very small hash signatures of

The use of credit cards for online purchases has significantly increased in recent years, but it has also led to an increase in fraudulent activities that cost businesses and consumers billions of dollars annually. Detecting fraudulent transactions is crucial for protecting customers and maintaining the financial system's integrity. However, the number of fraudulent transactions is less than legitimate transactions, which can result in a data imbalance that affects classification performance and bias in the model evaluation results. This paper focuses on processing imbalanced data by proposing a new weighted oversampling method, wADASMO, to generate minor-class data (i.e., fraudulent transactions). The proposed method is based on th

The goal of the research is to identify the effectiveness of using a proposed strategy according to the Fraunhofer model of knowledge management in mathematics achievement for second-grade female students in middle and high schools affiliated with the General Directorate of Education in Baghdad / Al-Karkh II. The objective was to prove the following null hypothesis: "The average scores of the experimental group who will study with the proposed strategy according to the Fraunhofer model and the scores of the control group students who will study in the usual way in the mathematics achievement test are not statistically significant different at the significance level (0.05)." The General Directorate of Education of Baghdad / Al-Karkh

يؤدي عرض معلومات مضللة او محرفة ضمن القوائم المالية والتي تعد أهم مصادر المعلومات الموثوقة التي يُعول عليها لاتخاذ القرارات السليمة الى عدم قدرتها على عكس نتيجة النشاط والمركز المالي لها او اعمال الوحدة الاقتصادية لتلك الفترات الزمنية بصورة صادقة وعادلة نتيجة لنوعية المعلومات المفصح عنها في القوائم المالية لذلك زاد الاهتمام بتطوير الممارسات المحاسبية لتتضمن افصاحات كافية بغرض اعطائهم صورة صادقة وعادلة

 

    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.

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New complexes of Al(III) such as [Al (Ura) (Phen) (OH2) Cl ] Cl. 2H2O, [Al(Ura)2(OA)(OH2)Cl].H2O and [Al(Ura)3Cl3]H2O type, where (Ura)=Uracil, (Phen)= 1,10-Phenanthroline monohydrate and (OA)= Oxalic acid dihydrate, were prepared. The elemental microanalysis, FT.IR, electronic spectra, and magnetic susceptibility as well as the conductivity measurements are characterized. For isolated three complexes for six coordinated of Al(III) are proposed with molecular formulas that depend on the nature of (Ura), (Phen) and (OA) present. The suggested molecular structure into all complexes for aluminum ion is octahedral geometries .The antibacterial efficacy was examined from metal salt (AlCl3), ligands and metal complexes into the pathogenic bacteri

Cocrystallization is an emerging approach for improving physico-chemical characteristics of an active pharmaceutical ingredient (API) for instance dissolution rate, solubility, stability in addition to mechanical properties without affecting their therapeutic activity. It is of great importance when other approaches like salt or polymorph formation do not encounter the estimated targets. In this review article, an outline of pharmaceutical cocrystals will be presented, with highlighting on factors affecting cocrystallization which include ∆pKa, donors and acceptors hydrogen bonds, molecular recognition point, synthon forming functional groups flexibility, dicarboxylic acid coformers carbon chain length and solvent effe