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 these files. More specifically, an attacker who knows the hash signature of a file can convince the storage service that he/she owns that file, hence the server lets the attacker to download the entire file. To overcome such attacks,the hash signature is encrypted with the user password. As a proof of concept a prototype of the proposed authorized deduplicate is implemented and conducted the test bed experiments using the prototype. Performance measurements indicate that the proposed Deduplication system incurs minimal overhead in the context of uploading, bandwidth compared to native deduplication.
The purpose of this interview study was to explore teachers’ perceptions of Response to Intervention (RtI) implementation in their school. Particularly, the study explored teachers’ knowledge of RtI, teachers’ perceptions of RtI their intervention/instruction in school, and teachers’ suggestions of RtI implementation in their school. The study design was a qualitative interview in nature and data were collected from face-to-face interviews with four teachers in one school. The findings revealed that RtI means to identify students’ problems; the positive teachers’ perceptions of their implementation included: (a) students who demonstrate progress through RtI are those who receive private education services, (b) progress monito
... Show MoreTo damp the low-frequency oscillations which occurred due to the disturbances in the electrical power system, the generators are equipped with Power System Stabilizer (PSS) that provide supplementary feedback stabilizing signals. The low-frequency oscillations in power system are classified as local mode oscillations, intra-area mode oscillation, and interarea mode oscillations. A suitable PSS model was selected considering the low frequencies oscillation in the inter-area mode based on conventional PSS and Fuzzy Logic Controller. Two types of (FIS) Mamdani and suggeno were considered in this paper. The software of the methods was executed using MATLAB R2015a package.
Abstract:
The research seeks to identify the role of the International Assurance Standard (3402) in the auditor's procedures, as the importance of the research stems from providing assurance services for control tools through reports that are prepared according to this standard, which contribute to strengthening audit procedures through a proposed assurance program. Many conclusions were reached, the most important of which The assurance operations are considered among the operations with a special assignme
... Show MoreThe aim of the research is to present and discuss the subject of the budgeting estimates and how to activate the role of the Federal board of supreme audit in examining these estimates through reference to Articles 6 and 10 of the Federal board of supreme Law, which did not restrict Federal board of supreme in Preventive control on examination process for planning which is prepared from the government units, as the result of a large amount of government units Provisions and the weakness of estimates in most of its items, which rely on personal assessment and not based on scientific and logical basis of the estimate, which leads to the emergence of a deficit is not true in the general budget and this seems clear in most Iraq
... Show MoreThe current study aims to compare between the assessments of the Rush model’s parameters to the missing and completed data in various ways of processing the missing data. To achieve the aim of the present study, the researcher followed the following steps: preparing Philip Carter test for the spatial capacity which consists of (20) items on a group of (250) sixth scientific stage students in the directorates of Baghdad Education at Al–Rusafa (1st, 2nd and 3rd) for the academic year (2018-2019). Then, the researcher relied on a single-parameter model to analyze the data. The researcher used Bilog-mg3 model to check the hypotheses, data and match them with the model. In addition
... Show MoreA frequently used approach for denoising is the shrinkage of coefficients of the noisy signal representation in a transform domain. This paper proposes an algorithm based on hybrid transform (stationary wavelet transform proceeding by slantlet transform); The slantlet transform is applied to the approximation subband of the stationary wavelet transform. BlockShrink thresholding technique is applied to the hybrid transform coefficients. This technique can decide the optimal block size and thresholding for every wavelet subband by risk estimate (SURE). The proposed algorithm was executed by using MATLAB R2010aminimizing Stein’s unbiased with natural images contaminated by white Gaussian noise. Numerical results show that our algorithm co
... Show MoreEmotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In
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Regression testing is a crucial phase in the software development lifecycle that makes sure that new changes/updates in the software system don’t introduce defects or don’t affect adversely the existing functionalities. However, as the software systems grow in complexity, the number of test cases in regression suite can become large which results into more testing time and resource consumption. In addition, the presence of redundant and faulty test cases may affect the efficiency of the regression testing process. Therefore, this paper presents a new Hybrid Framework to Exclude Similar & Faulty Test Cases in Regression Testing (ETCPM) that utilizes automated code analysis techniques and historical test execution data to
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