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Abstract-One of the main drawbacks of Orthogonal Frequency Division Multiplexing (OFDM) are the large fluctuations of its power envelope. In this letter, a novel and efficient scheme based on Multilayer Perceptron (MLP) Neural Networks (NN) is proposed. The NN synthesizes the Active Constellation Expansion -(ACE) technique which is able to drastically reduce envelope fluctuations. This is achieved with much lower complexity, faster convergence, and better performance compared to previously available methods.

Perceptual hashing is conventionally used for content identification and authentication. It has applications in database content search, watermarking and image retrieval. Most countermeasures proposed in the literature generally focus on the feature extraction stage to get robust features to authenticate the image, but few studies address the perceptual hashing security achieved by a cryptographic module. When a cryptographic module is employed [1], additional information must be sent to adjust the quantization step. In the perceptual hashing field, we believe that a perceptual hashing system must be robust, secure and generate a final perceptual hash of fixed length. This kind of system should send only the final perceptual hash to the receiver via a secure channel without sending any additional information that would increase the storage space cost and decrease the security. For all of these reasons, in this paper, we propose a theoretical analysis of full perceptual hashing systems that use a quantization module followed by a crypto-compression module. The proposed theoretical analysis is based on a study of the behavior of the extracted features in response to content-preserving/content-changing manipulations that are modeled by Gaussian noise. We then introduce a proposed perceptual hashing scheme based on this theoretical analysis. Finally, several experiments are conducted to validate our approach, by applying Gaussian noise, JPEG compression and low-pass filtering.

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Perceptual image hashing maps an image to a fixed length binary string based on the image's appearance to the human eye, and has applications in image indexing, authentication, and watermarking. In this paper, we analyze the robustness of perceptual signatures generated by the known SHA1 hash function in the DWT domain. This is achieved by generation signatures from the coefficients of the subband LL after a DWT transformation. Experiments on large-scale database show that the proposed method is efficient, robust against common contentpreserving manipulations.

Abstract:Improving data availability in mobile ad hoc networks is very important issue since the ultimate goal of using these networks, is to provide information access to mobile nodes. Make data available in such environment where bandwidth, battery power and memory size are limited, is very difficult issueIn this paper we propose tow data replication methods for improving the availability of data. These methods executed under two main phases. In the first phase we create the primary replicas, and in the second phase we redistribute these replicas dynamically. The first method creates the primary replicas for each new data created in the network or received from fixed network. The second method creates the primary replicas only for the important data. The simulation experiments show that the data availability is improved and the traffic is reduced.