G.: JPEG steganalysis using empirical transition matrix in block dct domain

Abstract — This paper presents a novel steganalysis scheme to effectively attack the JPEG steganographic schemes. The proposed method exploits the correlations between block-DCT coefficients in both intra-block and inter-block sense. We use Markov empirical transition matrices to capture these dependencies. The experimental results demonstrate that the proposed scheme is superior to the existing steganalyzers in attacking OutGuess, F5, and MB1

Data Hiding in Film Grain

Abstract. This paper presents a data hiding technique based on a new compression enhancement called Film Grain Technology. Film grain is a midfrequency noise-like pattern naturally appearing in imagery captured on film. The Film Grain Technology is a method for modeling and removing the film grain, thus enhancing the compression efficiency, and then using the model parameters to create synthetic film grain at the decoder. We propose slight modifications to the decoder that enable the synthetic film grain to represent metadata available at the decoder. We examine a number of implementation approaches and report results of fidelity and robustness experiments

Trajectory Modulation for Impact Reducing of Lower-Limb Exoskeletons

Lower-limb exoskeletons have received considerable attention because of their effectiveness in walking assistance and rehabilitation for paraplegic patients. Excessive foot–ground impacts during walking make patients uncomfortable and even lead to injury. In this paper, we propose an optimized knee trajectory modulation (OKTM) for foot–ground impact reduction. The OKTM can reduce the peak of ground reaction force (PGRF) by knee-joint trajectory modulation based on a parameters-optimizing spring-damping system. In addition, a hip trajectory modulation (HTM) is presented to compensate for torso pitch deflections due to the OKTM. Unlike traditional mechanical-device-based methods, the proposed OKTM and HTM require no bulky mechanical structures, and can adaptively adjust parameters to adapt to different impacts. We demonstrated the efficiency of the proposed approach in both simulations and experiments for engineering verifications. Results show that the approach can effectively reduce PGRF

Steganalysis based on multiple features formed by statistical moments of wavelet characteristic functions

Abstract. In this paper 1, a steganalysis scheme based on multiple features formed by statistical moments of wavelet characteristic functions is proposed. Our theoretical analysis has pointed out that the defined n-th statistical moment of a wavelet characteristic function is related to the n-th derivative of the corresponding wavelet histogram, and hence is sensitive to data embedding. The selection of the first three moments of the characteristic functions of wavelet subbands of the three-level Haar wavelet decomposition as well as the test image has resulted in total 39 features for steganalysis. The effectiveness of the proposed system has been demonstrated by extensive experimental investigation. The detection rate for Cox et al.’s non-blind spread spectrum (SS) data hiding method, Piva et al.’s blind SS method, Huang and Shi’s 8 × 8 block SS method, a generic LSB method (as embedding capacity being 0.3 bpp), and a generic QIM method (as embedding capacity being 0.1 bpp) are all above 90 % over all of the 1096 images in the CorelDraw image database using the Bayes classifier. Furthermore, when these five typical data hiding methods are jointly considered for steganalysis, i.e., when the proposed steganalysis scheme is first trained sequentially for each of these five methods, and is then tested blindly for stegoimages generated by all of these methods, the success classification rate is 86%, thus pointing out a new promising approach to general blind steganalysis. The detection results of steganalysis on Jsteg, Outguess and F5 have further demonstrated the effectiveness of the proposed steganalysis scheme.

Biflavonoids from Selaginella doederleinii as Potential Antitumor Agents for Intervention of Non-Small Cell Lung Cancer

Four new biflavonoids (1–4) were isolated from Selaginella doederleinii together with a known biflavonoid derivative (5). Their structures contained a rare linker of individual flavones to each other by direct C-3-O-C-4′′′ bonds, and were elucidated by extensive spectroscopic data, including HRESIMS, NMR and ECD data. All isolates significantly inhibited the proliferation of NSCLC cells (IC50 = 2.3–8.4 μM) with low toxicity to non-cancer MRC-5 cells, superior to the clinically used drug DDP. Furthermore, the most active compound 3 suppressed XIAP and survivin expression, promoted upregulation of caspase-3/cleaved-caspase-3, as well as induced cell apoptosis and cycle arrest in A549 cells. Together, our findings suggest that 3 may be worth studying further for intervention of NSCLC