Cloud storage provides scalable and low cost resources featuring economies of scale based on cross-user architecture. As the amount of data outsourced grows explosively, data deduplication, a technique that eliminates data redundancy, becomes essential. The most important cloud service is data storage. In order to protect the privacy of data owner, data are stored in cloud in an encrypted form. However, encrypted data introduce new challenges for cloud data deduplication, which becomes crucial for data storage. Traditional deduplication schemes cannot work on encrypted data. Existing solutions of encrypted data deduplication suffer from security weakness. This paper proposes a combined compressive sensing and video deduplication to maximize deduplication ratios. Our approach uses data deduplication to remove identical copies of the video. Our experimental results show significant storage savings, while providing strong level security
The seasonal behavior of the light curve for selected star SS UMI and EXDRA during outburst cycle is studied. This behavior describes maximum temperature of outburst in dwarf nova. The raw data has been mathematically modeled by fitting Gaussian function based on the full width of the half maximum and the maximum value of the Gaussian. The results of this modeling describe the value of temperature of the dwarf novae star system leading to identify the type of elements that each dwarf nova consisted of.
The objective of present study was to investigate the effect of using duplex volaticle oil of Rosmarinusoficinolis and Nigella sativain microbial quality, sensing and extending storage time of minced cold poultry meat. Duplex volaticle oil was added at 25, 50 and 75 mg/kg to minced poultry meat , these treatments were stored individually for (0 ,4 and 7) days at( 4-7) C0 . After making several microbial and sensing test. The following results were obtained:- The process of adding duplex volaticle oil of Rosmarinus officinolis and Nigella sativa to minced poultry meat led to significant reduced (P<0.01) in total arobic count, psychrophilic count and coliform bacteria during refrigerated storage periods. The results showed asignificant sens
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Abstract:
We can notice cluster data in social, health and behavioral sciences, so this type of data have a link between its observations and we can express these clusters through the relationship between measurements on units within the same group.
In this research, I estimate the reliability function of cluster function by using the seemingly unrelate
... Show MoreWithin the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo
... Show MoreST Alawi, NA Mustafa, Al-Mustansiriyah Journal of Science, 2013
The current research aimed to conducting two experiments to study the effect of coating hatching eggs with nano-titanium dioxide (nano-TiO2) and nano-silica dioxide (nano-SiO2) particles and their mixture with carboxymethyl cellulose (CMC) on the characteristics of hatching percentage, embryo growth inside the egg. The study was conducted in the Department of Animal Production, College of Agriculture, Tikrit University for the period from 19/3/2023 to 17/9/2024. It aimed to evaluate the coating of hatching eggs with Nano-TiO2 and Nano-SiO2 particles and their mixture with carboxymethyl cellulose CMC on the qualities of hatching percentage, embryo growth inside the egg, as well as trying to obtain the best and longest storage method for fert
... Show MoreThis study proposed using color components as artificial intelligence (AI) input to predict milk moisture and fat contents. In this sense, an adaptive neuro‐fuzzy inference system (ANFIS) was applied to milk processed by moderate electrical field‐based non‐thermal (NP) and conventional pasteurization (CP). The differences between predicted and experimental data were not significant (
Phase-change materials (PCMs) have a remarkable potential for use as efficient energy storage means. However, their poor response rates during energy storage and retrieval modes require the use of heat transfer enhancers to combat these limitations. This research marks the first attempt to explore the potential of dimple-shaped fins for the enhancement of PCM thermal response in a shell-and-tube casing. Fin arrays with different dimensions and diverse distribution patterns were designed and studied to assess the effect of modifying the fin geometric parameters and distribution patterns in various spatial zones of the physical domain. The results indicate that increasing the number of