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This paper presents an efficient JPEG steganography method based on heuristic optimization and BCH syndrome coding. The proposed heuristic optimization technique significantly decreases total distortion by inserting and removing AC coefficients 1 or -1 in the most appropriate positions. The implemented data hiding technique is based on structured BCH(More)
In this article, a new Bose-Chaudhuri-Hochquenghem (BCH)-based data hiding scheme for JPEG steganography is presented. Traditional data hiding approaches hide data into each block, where all the blocks are not overlapping each other. However, in the proposed method, two consecutive blocks can be overlapped to form a combined block which is larger than a(More)
Traditional cancer treatments have centered on cytotoxic drugs and general purpose chemotherapy that may not be tailored to treat specific cancers. Identification of molecular markers that are related to different types of cancers might lead to discovery of drugs that are patient and disease specific. This study aims to use microarray gene expression cancer(More)
In this paper, we propose a risk-sensitive hinge loss function-based cognitive ensemble of extreme learning machine (ELM) classifiers for JPEG steganalysis. ELM is a single hidden-layer feed-forward network that chooses the input parameters randomly and estimates the output weights analytically. For steganalysis, we have extracted 548-dimensional merge(More)