Methodologies for reducing the design-space dimensionality in shape optimization have been recently developed based on unsupervised machine learning methods. These methods provide reduced representations of design space, capable maintaining a certain degree original variability. Nevertheless, they usually do not allow to use directly parameterization method, representing limitation their widesp...

In this paper, we introduce a new setting for graph embedding, which considers embedding communities instead of individual nodes. Community embedding is useful as a natural community representation for applications, and it provides an exciting opportunity to improve community detection. Specifically, we see the interaction between community embedding and detection as a closed loop, through node...

Network embedding has shown its effectiveness in embedding homogeneous networks. Compared with homogeneous networks, heterogeneous information networks (HINs) contain semantic information from multi-typed entities and relations, and are shown to be a more effective model for real world data. The existing network embedding methods fail to explicitly capture the semantics in HINs. In this paper, ...

In this paper, the authors examine embedding efficiency, which influences the most concerned performance of steganography, security, directly. Embedding efficiency is defined as the number of random message bits embedded per embedding change. Recently, matrix embedding has gained extensive attention because of its outstanding performance in boosting steganographic schemes’ embedding efficiency....

The aim of image steganalysis is to detect the presence of hidden messages in stego images. We propose a blind image steganalysis method in Contourlet domain and then show that the embedding process changes statistics of Contourlet coefficients. The suspicious image is transformed into Contourlet space, and then the statistics of Contourlet subbands coefficients are extracted as features. We us...

In this paper we present a new accurate steganalysis method for the LSBreplacement steganography. The suggested method is based on the changes that occur in thehistogram of an image after the embedding of data. Every pair of neighboring bins of ahistogram are either inter-related or unrelated depending on whether embedding of a bit ofdata in the image could affect both bins or not. We show that...

We present a steganalysis scheme for LSB matching steganography based on feature vectors extracted from integer wavelet transform (IWT). In integer wavelet decomposition of an image, the coefficients will be integer, so we can calculate co-occurrence matrix of them without rounding the coefficients. Before calculation of co-occurrence matrices, we clip some of the most significant bitplanes of ...