Recent studies have indicated that the architectures of convolutional neural networks (CNNs) tailored for computer vision may not be best suited to image steganalysis. In this letter, we report a CNN ...architecture that takes into account knowledge of steganalysis. In the detailed architecture, we take absolute values of elements in the feature maps generated from the first convolutional layer to facilitate and improve statistical modeling in the subsequent layers; to prevent overfitting, we constrain the range of data values with the saturation regions of hyperbolic tangent (TanH) at early stages of the networks and reduce the strength of modeling using 1×1 convolutions in deeper layers. Although it learns from only one type of noise residual, the proposed CNN is competitive in terms of detection performance compared with the SRM with ensemble classifiers on the BOSSbase for detecting S-UNIWARD and HILL. The results have implied that well-designed CNNs have the potential to provide a better detection performance in the future.
In the past more than one decade, hundreds of reversible data hiding (RDH) algorithms have been reported. Via exploring the correlation between the neighboring pixels (or coefficients), extra ...information can be embedded into the host image reversibly. However, these RDH algorithms cannot be accomplished in encrypted domain directly, since the correlation between the neighboring pixels will disappear after encryption. In order to accomplish RDH in encrypted domain, specific RDH schemes have been designed according to the encryption algorithm utilized. In this paper, we propose a new simple yet effective framework for RDH in encrypted domain. In the proposed framework, the pixels in a plain image are first divided into sub-blocks with the size of m\times n . Then, with an encryption key, a key stream (a stream of random or pseudorandom bits/bytes that are combined with a plaintext message to produce the encrypted message) is generated, and the pixels in the same sub-block are encrypted with the same key stream byte. After the stream encryption, the encrypted m\times n sub-blocks are randomly permutated with a permutation key. Since the correlation between the neighboring pixels in each sub-block can be well preserved in the encrypted domain, most of those previously proposed RDH schemes can be applied to the encrypted image directly. One of the main merits of the proposed framework is that the RDH scheme is independent of the image encryption algorithm. That is, the server manager (or channel administrator) does not need to design a new RDH scheme according to the encryption algorithm that has been conducted by the content owner; instead, he/she can accomplish the data hiding by applying the numerous RDH algorithms previously proposed to the encrypted domain directly.
Potassium ion batteries (KIBs) have emerged as a promising energy storage system, but the stability and high rate capability of their electrode materials, particularly carbon as the most investigated ...anode ones, become a primary challenge. Here, it is identified that pitch‐derived soft carbon, a nongraphitic carbonaceous species which is paid less attention in the battery field, holds special advantage in KIB anodes. The structural flexibility of soft carbon makes it convenient to tune its crystallization degree, thereby modulating the storage behavior of large‐sized K+ in the turbostratic carbon lattices to satisfy the need in structural resilience, low‐voltage feature, and high transportation kinetics. It is confirmed that a simple thermal control can produce structurally optimized soft carbon that has much better battery performance than its widely reported carbon counterparts such as graphite and hard carbon. The findings highlight the potential of soft carbon as an interesting category suitable for high‐performance KIB electrode and provide insights for understanding the complicated K+ storage mechanisms in KIBs.
The cycling stability of anode materials in potassium‐ion batteries (KIBs) is challenged by the large size of K+ itself. The findings not only demonstrate the promising potential of soft carbon as a category suitable for high‐performance KIB electrodes, but also provide insights into the complicated K+ storage mechanisms in carbon anodes of KIBs.
Image Description With Polar Harmonic Fourier Moments Wang, Chunpeng; Wang, Xingyuan; Xia, Zhiqiu ...
IEEE transactions on circuits and systems for video technology,
12/2020, Volume:
30, Issue:
12
Journal Article
Peer reviewed
Due to their good rotational invariance and stability, image continuous orthogonal moments are intensively applied in rotationally invariant recognition and image processing. However, most moments ...produce numerical instability, which impacts the image reconstruction and recognition performance. In this paper, a new set of invariant continuous orthogonal moments, polar harmonic Fourier moments (PHFMs), free of numerical instability is designed. The radial basis functions (RBFs) of the PHFMs are much simpler than those of the Chebyshev-Fourier moments (CHFMs), orthogonal Fourier-Mellin moments (OFMMs), Zernike moments (ZMs), and pseudo-Zernike moments (PZMs). For the same degree, the RBFs of the PHFMs have more zeros and are more evenly distributed than those of the ZMs and PZMs. Therefore, PHFMs do not suffer from information suppression problem; hence, the image description ability of the PHFMs is superior to that of the ZMs and PZMs. Moreover, the RBFs of the PHFMs are always less than or equal to 1.0 near the unit disk center, whereas those of the OFMMs, PZMs, CHFMs, and radial harmonic Fourier moments (RHFMs) are infinite (implying numerical instability). This indicates that PHFMs can outperform these moments in image reconstruction tasks. We theoretically and experimentally demonstrate that PHFMs outperform the above moments in reconstructing images and recognizing rotationally invariant objects considering noise and various attacks. This paper also details the significance of the PHFM phase in image reconstruction, angle estimation using PHFMs, and the accurate moment selection of the PHFMs.
In the present work, molecular dynamics simulations are carried out based on the bead‐spring model to indicate how the entanglement lockup manifests in the late stage of fast Rouse‐Weissnberg number ...(WiR>>1) uniaxial melt stretching of entangled polymer melts. At high strains, distinct features show up to reveal the emergence of an increasingly tightened entanglement network. Chain tension can build up, peaking at the middle of the chain, to a level for chain scission, through accumulated interchain interactions, as if there is a tug‐of‐war ongoing for each load‐bearing chain. Thanks to the interchain uncrossability, network junctions form by the pairing of two or more hairpins. It is hypothesized that the interchain entanglement at junctions can lockup through prevailing twist‐like interchain couplings as long as WiR > 9. In this limit, a significant fraction of chains act like cyclic chains to form a network held by interchain uncrossability, and appreciable chain tension emerges.
Molecular dynamics simulations are used to indicate how the entanglement lockup manifests in the late stage of fast Rouse‐Weissnberg number (WiR>>1) uniaxial melt stretching of entangled polymer melts. At high strains, chain tension can build up, peaking at the middle of the chain, through accumulated interchain interactions, as if there is a tug‐of‐war ongoing for each load‐bearing chain. The interchain entanglement due to uncrossability can lockup through prevailing twist‐like interchain couplings as long as WiR > 9. The maximum chain tension can reach a level high enough for scission.
Histogram shifting (HS) embedding as a typical reversible data hiding scheme is widely investigated due to its high quality of stego-image. For HS-based embedding, the selected side information, ...i.e., peak and zero bins, usually greatly affects the rate and distortion performance of the stego-image. Due to the massive solution space and burden in distortion computation, conventional HS-based schemes utilize some empirical criterion to determine those side information, which generally could not lead to a globally optimal solution for reversible embedding. In this paper, based on the developed rate and distortion model, the problem of HS-based multiple embedding is formulated as the one of rate and distortion optimization. Two key propositions are then derived to facilitate the fast computation of distortion due to multiple shifting and narrow down the solution space, respectively. Finally, an evolutionary optimization algorithm, i.e., genetic algorithm is employed to search the nearly optimal zero and peak bins. For a given data payload, the proposed scheme could not only adaptively determine the proper number of peak and zero bin pairs but also their corresponding values for HS-based multiple reversible embedding. Compared with previous approaches, experimental results demonstrate the superiority of the proposed scheme in the terms of embedding capacity and stego-image quality.
In recent years, generative adversarial networks (GANs) have been widely used to generate realistic fake face images, which can easily deceive human beings. To detect these images, some methods have ...been proposed. However, their detection performance will be degraded greatly when the testing samples are post-processed. In this paper, some experimental studies on detecting post-processed GAN-generated face images find that (a) both the luminance component and chrominance components play an important role, and (b) the RGB and YCbCr color spaces achieve better performance than the HSV and Lab color spaces. Therefore, to enhance the robustness, both the luminance component and chrominance components of dual-color spaces (RGB and YCbCr) are considered to utilize color information effectively. In addition, the convolutional block attention module and multilayer feature aggregation module are introduced into the Xception model to enhance its feature representation power and aggregate multilayer features, respectively. Finally, a robust dual-stream network is designed by integrating dual-color spaces RGB and YCbCr and using an improved Xception model. Experimental results demonstrate that our method outperforms some existing methods, especially in its robustness against different types of post-processing operations, such as JPEG compression, Gaussian blurring, gamma correction, and median filtering.
In the past two decades, reversible data hiding (RDH), also referred to as lossless or invertible data hiding, has gradually become a very active research area in the field of data hiding. This has ...been verified by more and more papers on increasingly wide-spread subjects in the field of RDH research that have been published these days. In this paper, the various RDH algorithms and researches have been classified into the following six categories: 1) RDH into image spatial domain; 2) RDH into image compressed domain (e.g., JPEG); 3) RDH suitable for image semi-fragile authentication; 4) RDH with image contrast enhancement; 5) RDH into encrypted images, which is expected to have wide application in the cloud computation; and 6) RDH into video and into audio. For each of these six categories, the history of technical developments, the current state of the arts, and the possible future researches are presented and discussed. It is expected that the RDH technology and its applications in the real word will continue to move ahead.
Zingiber officinale Roscoe, colloquially known as ginger, is a crop of significant medicinal and culinary value that frequently encounters adversity stemming from inhospitable environmental ...conditions. The MYB transcription factors have garnered recognition for their pivotal role in orchestrating a multitude of plant biological pathways. Nevertheless, the enumeration and characterization of the MYBs within Z. officinale Roscoe remains unknown. This study embarks on a genome-wide scrutiny of the MYB gene lineage in ginger, with the aim of cataloging all ZoMYB genes implicated in the biosynthesis of gingerols and curcuminoids, and elucidating their potential regulatory mechanisms in counteracting abiotic stress, thereby influencing ginger growth and development.
In this study, we identified an MYB gene family comprising 231 members in ginger genome. This ensemble comprises 74 singular-repeat MYBs (1R-MYB), 156 double-repeat MYBs (R2R3-MYB), and a solitary triple-repeat MYB (R1R2R3-MYB). Moreover, a comprehensive analysis encompassing the sequence features, conserved protein motifs, phylogenetic relationships, chromosome location, and gene duplication events of the ZoMYBs was conducted. We classified ZoMYBs into 37 groups, congruent with the number of conserved domains and gene structure analysis. Additionally, the expression profiles of ZoMYBs during development and under various stresses, including ABA, cold, drought, heat, and salt, were investigated in ginger utilizing both RNA-seq data and qRT-PCR analysis.
This work provides a comprehensive understanding of the MYB family in ginger and lays the foundation for the future investigation of the potential functions of ZoMYB genes in ginger growth, development and abiotic stress tolerance of ginger.
An efficient predictor is crucial for high embedding capacity and low image distortion. In this letter, a ridge regression-based high precision error prediction algorithm for reversible data hiding ...is proposed. The ridge regression is a penalized least-square algorithm, which solves the overfitting problem of the least-square method. Reversible data hiding based on ridge regression predictor minimizes the residual sum of squares between predicted and target pixels subject to the constraint expressed in terms of the L2-norm. Compared to a least-square-based predictor, the ridge regression-based predictor can obtain more small prediction errors, proving that the proposed method has a higher accuracy. In addition, the eight neighbor pixels of the target pixels and their two different combinations are selected as training and support sets, respectively. This selection scheme further improves the prediction accuracy. Experimental results show that the proposed method outperforms state-of-the-art adaptive reversible data hiding in terms of prediction accuracy and embedding performance.
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