Cloud computing offers a new way of service provision by rearranging various resources over the Internet. The most important and popular cloud service is data storage. In order to preserve the privacy of data holders, data are often stored in cloud in an encrypted form. However, encrypted data introduce new challenges for cloud data deduplication, which becomes crucial for big data storage and processing in the cloud. Traditional deduplication schemes cannot work on encrypted data. Among these data, digital videos are fairly huge in terms of storage cost and size; and techniques that can help the legal aspects of video owner such as copyright protection and reducing the cloud storage cost and size are always desired. This paper focuses on video copyright protection and deduplication. A video copyright and deduplication scheme in cloud storage environments using the H.264 compression algorithm and SHA-512 hashing technique is proposed. This paper proposes a combined copyright production and deduplication based on video content to authenticate and to verify the integrity of the compressed H.264 video. The design of the proposed scheme consists of two modules. First, a H.264 compression algorithm is applied on the given video by the user. Second, a unique signature in different time interval of the compressed video is generated by the user in such a way that the CSP can use it to compare the user’s video against other videos without compromising the security of the user’s video. To avoid any attacker to gain access to the hash signature during uploading to the cloud, the hash signature is encrypted with the user password. Some experimental results are provided, showing the effectiveness of our proposed copyright protection and deduplication system.
An experiment was carried out to study the effect of soil organic carbon (SOC) and soil texture on the distance of the wetting front, cumulative water infiltration (I), infiltration rate (IR), saturated water conductivity (Ks), and water holding capacity (WHC). Three levels ( 0, 10, 20, and 30 g OC kg-1 ) from organic carbon (OC) were mixed with different soil materials sandy, loam, and clay texture soils. Field capacity (FC) and permanent wilting point (PWP) were estimated. Soil materials were placed in transparent plastic columns(12 cm soil column ), and water infiltration(I) was measured as a function of time, the distance of the wetting front and Ks. Results showed that advance we
To study the response of the celery plant to nitrogen fertilization and spray with salicylic acid in the leaves content of nutrients, the research was conducted in one of the fields of the Department of Horticulture and Gardening Engineering / College of Agriculture / University of Baghdad within the 2019-2018 season. The research was carried out as a global experiment and with the design of complete randomized sectors (RCBD) and with three replicates, the first factor included the addition of nitrogen with three levels and its symbol (N) (N1 control), (N2) g / m2 18 ), (N3) 37 g / m2 and the second factor spraying acid salicylic is denoted by
This study was conducted to identify the impact of germination in the ratio Almaah of Chemical Constituents of Homs and in the organoleptic properties of the Biskt plant it and compare the results with the treatment control (seeds Almnepth) Adhrt results for a significant increase in the percentage of crude protein with the progress of the process of germination, reaching 24.5% in percentage of crude protein with the progress of the germination process Krbu hydrate college during the germination period, reaching 59.2% in the fourth day
Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables
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The research aims to measure, assess and evaluate the efficiency of the directorates of Anbar Municipalities by using the Data Envelopment Analysis method (DEA). This is because the municipality sector is consider an important sector and has a direct contact with the citizen’s life. Provides essential services to citizens. The researcher used a case study method, and the sources of information collection based on data were monthly reports, the research population is represented by the Directorate of Anbar Municipalities, and the research sample consists of 7 municipalities which are different in terms of category and size of different types. The most important conclusion reached by the research i
... Show MoreThis paper is dealing with non-polynomial spline functions "generalized spline" to find the approximate solution of linear Volterra integro-differential equations of the second kind and extension of this work to solve system of linear Volterra integro-differential equations. The performance of generalized spline functions are illustrated in test examples
Abstract:Two-dimensional crystal has been achieved and controlled with the aid of DC electric field applied between two electrodes at 5 millimeters separating distance between them. Sol-gel method has been used to prepared nanosilica particle which used in this work as well as TiO2 nanopaowder. The assembly of the silica particles is due to the interaction between the electrical force, the particles dipole, and the interaction between the particles themselves. When a DC voltage is applied, the particles accumulated and crystallized on the surface between the electrodes. The Light diffraction demonstrates that the hexagonal crystal is always oriented with one axis along the direction of the field. The particles disassemble when the field is
... Show MoreTwo-dimensional crystal has been achieved and controlled
with the aid of DC electric field applied between two electrodes at 5
millimeters separating distance between them. Sol-gel method has
been used to prepared nanosilica particle which used in this work as
well as TiO2 nanopaowder. The assembly of the silica particles is
due to the interaction between the electrical force, the particles
dipole, and the interaction between the particles themselves. When a
DC voltage is applied, the particles accumulated and crystallized on
the surface between the electrodes. The Light diffraction
demonstrates that the hexagonal crystal is always oriented with one
axis along the direction of the field. The particles disass
The research aims to know the impact of science, technology, engineering, and mathematics education on both creative thinking and mathematical achievement. To achieve it, the two researchers followed the quasi-experimental approach with an experimental design for two groups, one experimental and the other a control. The research sample consisted of (32) female students from the fourth scientific grade in Al-Intisar Preparatory School for Girls/ AlRasafa, First Directorate. The sample was chosen intentionally and was divided into two groups: a control group studying by the traditional method, their number (16), and an experimental group that applied the STEM approach, their number also (16). There was parity between the two research groups i
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