Gongcheng Kexue Yu Jishu/Advanced Engineering Science

Abstract : Cloud data storage is the cloud computing model that allows us to save information in an isolated location and can be retrieved or accessed through internet. It is widely accepted by many organizations as it provides cost effective, elasticity and scalable alternative to store large volumes of data. As the data is outsourced, it is necessary to have security mechanisms to keep outsourced data securely. Cloud data auditing technique enables cloud user to verify the reliability of outsourced data against cloud storage, without downloading the file from cloud. In this paper, we introduce the concept of user centric auditing scheme where users can control their own data. The proposed scheme also provides privacy preserving, i.e. the system prevents user’s data from leaking to TPA. In addition, we also describe how the system supports data dynamics. As per our observations, theoretical analysis and demonstration of security properties about its correctness, the proposed systems performance is efficient and secure..
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Abstract : High Efficiency Video Coding (HEVC) being the contemporary video coding standard aims to impart a much finer coding performance upon comparison to that of its antecedent. Different types of techniques have been evolved over the past few years in HEVC with the purpose of enhancing coding performance. An encouraging inclination of a distributed multimedia coding is thus required that could needed, that could ease the complete multimedia research community. Much of the evolution of video communication and processing has been administered in the direction of very high-quality media services via high-efficiency video coding (HEVC). In this work a method called, Ridge Regressive Bumble Bee Mating Optimized Deep Belief Network (RRBMO-DBN) is proposed to ensure both reliable and robust multimedia data communication. The designed RRBMO-DBN method uses different types of units for identifying optimal solution towards efficient multimedia communication. The entire process is built under the deep belief network involving one input unit, two hidden units and one output unit. To start with, the population of bumble bees is considered as input in the input unit. This is performed by applying Two-directional Derivative-based Representation and Gradient-based Evaluation model. Second rate distortion cost (RD cost) and energy consumption for every CU partitioning pattern are evaluated and population initialization is made accordingly. Followed by which the fitness function is evolved for each initialized bumble bees based on the fitness function results for every CU partitioning pattern using Ridge Regression function to select optimal CU partitioning pattern for efficient HEVC video encoding/decoding on multi-core DSP processor. With optimal results, better multimedia communication is said to be achieved in terms of bit rate, PSNR, bandwidth, latency and transmission rate. The presentation of the proposed RRBMO-DBN method is evaluated in bit rate, PSNR, bandwidth, latency and transmission rate using the short videos dataset. The proposed RRBMO-DBN method has good attributes that improves the performance of in terms of PSNR by 34%, transmission rate by 18% and bandwidth by 27% respectively..
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Abstract : Elastic Optical Network (EON) is a popular framework for interconnecting data centers, providing a spectrum tailored to bandwidth requirements. Verifying the high stage "Quality of Service (QoS)" for candidate requests following the fault is the main focus in the connection failure scenario. The resilience of a high-speed network is crucial because, as network sizes increase, so does the probability of node and link degradation. Thus, an adaptive method is required to forecast the link deterioration in EON. A unique approach employing hybrid heuristic implementation is suggested to achieve this goal. The required data is obtained and entered into the first stage of the connection failure detection model. The novel method is named as Atrous Spatial Pyramid Pooling – 1 Dimensional Convolution Neural Network with Attention mechanism (ASPP-1DCNN-AM), in which some of the hyper-parameters are tuned by proposing the hybrid algorithm as Iteration-aided Position of Beetle and Barnacles Mating (IPBBM). The model must choose the optimal routing in order to improve communication. Here, the optimal path is identified by using the IPBBM algorithm. Finally, the validation is done using divergent measurements and in contrast with traditional models. Hence, the designed system demonstrates that it achieves the higher detection results to make the data transmission effectively..
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Abstract : The Analytic Hierarchy Process (AHP) is a decision-making tool that can be used to select the best bridge type for a given project based on various factors such as economic, technical, and environmental considerations. In this case, the three bridge types considered are the PCI Girder Bridge, Composite Bridge, and Steel Truss Bridge. The AHP method involves breaking down the decision-making process into a hierarchy of criteria and sub-criteria and then assigning weights to each criterion based on its importance. The final decision is made by comparing the bridge type's weighted scores to determine the best overall choice. Usually, the AHP method is only used for one case for each questionnaire. Using the multiple options for technical and environmental conditions, conditions rent weighted scores are obtained for different cases using one questionnaire. The total possibilities of the alternatives are simulated to get the recommended bridge. This approach allows for systematically and objectively evaluating the various bridge types up to 240 bridge models, considering all relevant factors using the proposed formula..
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Abstract : Since G. Bird introduced Nickel electrodeposition coating in 1837, it has remained a focal point of research. Over the past few decades, attention has shifted towards its distinctive applications and properties in engineering. Electroplated nickel coatings offer numerous advantages over conventional electrolyte coatings, especially in terms of their excellent tribological properties, leading to widespread use in industries such as chemical, automotive, aerospace, and electrical. To further enhance these properties, researchers have incorporated second phase particles like SiC, ZrO2, B4C, TiO2, Al2O3, Si3N4, CeO2, between others, into the electrodeposition process. Studies have demonstrated that the addition of these particles leads to improvements in tribological characteristics. As industries continue to seek new coating materials with superior tribological properties for various applications, this article reviews the tribological advantages of different electrodeposited nickel and chromium (Ni-Cr) nano coatings, considering factors such as bath types and structure..
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