A new class of distances appropriate for measuring similarity relations between sequences, say one type per distance, is studied. We propose a "normalized information distance," based on the noncomputable notion Kolmogorov complexity, and show that it in this minorizes every computable distance (that is, universal discovers all similarities). demonstrate metric call . This theory forms foundation practical tool. To evidence generality robustness, we give two distinctive applications widely...

Abstract Motivation: Genomics and proteomics studies routinely depend on homology searches based the strategy of finding short seed matches which are then extended. The exploding genomic data growth presents a dilemma for DNA search techniques: increasing size decreases sensitivity whereas decreasing slows down computation. Results: We present new algorithm ‘PatternHunter’ that uses novel model increased hit-processing techniques significantly speed. At Blast levels sensitivity,...

In the past two decades, reversible data hiding (RDH), also referred to as lossless or invertible hiding, has gradually become a very active research area in field of hiding. This been verified by more and papers on increasingly wide-spread subjects RDH that have published these days. this paper, various algorithms researches classified into following six categories: 1) image spatial domain; 2) compressed domain (e.g., JPEG); 3) suitable for semi-fragile authentication; 4) with contrast...

Due to their good rotational invariance and stability, image continuous orthogonal moments are intensively applied in rotationally invariant recognition processing. However, most produce numerical instability, which impacts the reconstruction performance. In this paper, a new set of moments, polar harmonic Fourier (PHFMs), free instability is designed. The radial basis functions (RBFs) PHFMs much simpler than those Chebyshev-Fourier (CHFMs), Fourier-Mellin (OFMMs), Zernike (ZMs),...

Arc-annotated sequences are useful in representing the structural information of RNA sequences. In general, secondary and tertiary structures can be represented as a set nested arcs crossing arcs, respectively. Since functions largely determined by molecular confirmation therefore structures, comparison between has received much attention recently. this paper, we propose notion edit distance to measure similarity two incorporating various operations performed on both bases (i.e.,...

In this paper, a novel code division multiplexing (CDM) algorithm-based reversible data hiding (RDH) scheme is presented. The covert are denoted by different orthogonal spreading sequences and embedded into the cover image. original image can be completely recovered after have been extracted exactly. Walsh Hadamard matrix employed to generate sequences, which overlappingly without interfering each other, multilevel embedding utilized enlarge capacity. Furthermore, most elements of mutually...

While existing watermarking attack methods can disturb the correct extraction of watermark information, visual quality watermarked images will be greatly damaged. Therefore, a concealed based on generative adversarial network and perceptual losses for robust is proposed. First, image utilized as input networks, its generating target (i.e. attacked image) original image. Inspired by U-Net network, networks consist encoder-decoder architecture with skip connection, which combine low-level...

An efficient predictor is crucial for high embedding capacity and low image distortion. In this letter, a ridge regression-based precision error prediction algorithm reversible data hiding proposed. The regression penalized least-square algorithm, which solves the overfitting problem of method. Reversible based on minimizes residual sum squares between predicted target pixels subject to constraint expressed in terms L2-norm. Compared least-square-based predictor, can obtain more small...

Some research progress has been made on fractional-order continuous orthogonal moments (FrCOMs) in the past two years. Compared with integer-order (InCOMs), FrCOMs increase number of affine invariants and effectively improve numerical stability. However, existing types are still very limited, which all planar image oriented. No report stereoscopic images is available yet. To this end, paper, corresponding to various InCOMs first deduced, then, they combined trinion theory construct (TFrCOMs)...

Convolutional recurrent networks (CRN) integrating a convolutional encoder-decoder (CED) structure and have achieved promising performance for monaural speech enhancement. However, feature representation across frequency context is highly constrained due to limited receptive fields in the convolutions of CED. In this paper, we propose (CRED) boost along axis. The CRED applies recurrence on 3D maps axis following each convolution, therefore, it capable catching long-range correlations...

An important phase of sensor networks operation is deployment sensors in the field interest. Critical goals during include coverage, connectivity, load balancing, etc. A class work has recently appeared, where mobility leveraged to meet objectives. In this paper, we study using mobile sensors. The distinguishing feature our that model have limited mobilities. More specifically, consider restricted a flip, distance flip bounded. We call such as flip-based Given an initial field, problem...

Most current reversible data hiding (RDH) techniques are designed for uncompressed images. However, JPEG images more commonly used in our daily lives. Up to now, several RDH methods have been proposed, yet few of them investigated the adaptive embedding as lack accurate measurement distortion. To realize and optimize performance, this article, a novel scheme based on multiple histogram modification (MHM) rate-distortion optimization is proposed. Firstly, with selected coefficients,...

This article proposes a novel grayscale image steganography scheme that is capable of hiding an encrypted secret into cover the same size. The using chaos encryption technology before being hidden. and are then transformed steg by convolutional neural network (CNN). Also, generative adversarial (GAN) adopted to produce more realistic image, whose appearance difficult distinguish from image. composed three CNNs which regarded as network, discriminative extracting respectively. Additionally,...

Deep complex U-Net structure and convolutional recurrent network (CRN) achieve state-of-the-art performance for monaural speech enhancement. Both deep CRN are encoder decoder structures with skip connections, which heavily rely on the representation power of complex-valued layers. In this paper, we propose a block attention module (CCBAM) to boost layers by constructing more informative features. The CCBAM is lightweight general can be easily integrated into any We integrate enhance their...

Finger veins are widely used in various fields due to their high safety. Existing finger vein recognition methods have some shortcomings, such as low accuracy and large model size. To address these a multi-scale feature bilinear fusion network (MSFBF-Net) was designed. First, the extracts global features local detail of performs linear obtain second-order with richer information. Then, mixed depthwise separable convolution replaces ordinary convolution, which greatly reduces computational...

Aiming at the problem of most Robust Reversible Data Hiding (RRDH) schemes failing to anti geometric deformation attacks, a new RRDH algorithm based on Polar Harmonic Fourier Moments (PHFMs) is presented in this paper, thereby enhancing both robustness embedded data and perceptual quality data-embedded image. Firstly, by leveraging anti-geometric transformation high-fidelity features PHFMs, image transformed into its frequency domain for RRDH. Then, quantitation index modulation (QIM)...

Face Recognition (FR) systems, while widely used across various sectors, are vulnerable to adversarial attacks, particularly those based on deep neural networks. Despite existing efforts enhance the robustness of FR models, they still face risk secondary attacks. To address this, we propose a novel approach employing "strengthened face" with preemptive defensive perturbations. Strengthened ensures original recognition accuracy safeguarding systems against In white-box scenario, strengthened...