Adaptive steganography algorithm in digital image based on Arnold transform by Qi LI, Xin LIAO, Guo-qing QU, Guo-yong CHEN, Jiao DU

“…Previous adaptive steganography algorithms were based on ordinal and full-embedding method.However,these algorithms might cause the concealment of secret information not good enough.Therefore,a random and non-fully embedding method was proposed to improve the concealment.The image system parameters could be obtained,so that the image full capacity was exactly greater than the length of information for non-full embedding.Moreover,these parameters made steganography more flexibility by reducing the modifications of image.Then,secret information embedding sequence was scrambled based on Arnold transform for the purpose that the steganalyst cannot detect out information orderly.Therefore,the secret information can be more concealed,which can improve the security of the algorithms.Experimental results show that the algorithm not only improves the concealment of steganography but also reduces stego distortion,and random non-full embedding operating can be applied to many other similar algorithms.…”
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Differential fault attack on FeW by Min XIE, Jiaqi LI, Feng TIAN

“…In order to evaluate the security of the lightweight block cipher FeW,a differential fault attack method was proposed and discussed using a single byte random fault model.In this method,a single byte random fault was introduced on the right side of the last round of FeW to recover the key based on the statistical characteristics of S-box difference distribution,and the difference information was obtained using the characteristics of the linear diffusion function.The experiment results show that the complete key recovery can be achieved with an average of 47.73 and 79.55 fault injections for FeW-64-80 and FeW-64-128 respectively.If 2<sup>10</sup>exhaustive calculations are added to the key recovery process,the number of average fault injections required can be reduced to 24.90 and 41.50.This attack is effective on FeW.…”
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Stochastic Inversion Method for Concrete Dams on the Basis of Bayesian Back Analysis Theory by Chongshi Gu, Xin Cao, Bo Xu

“…Fast Fourier transform algorithm is introduced to generate random fields for SFEM analysis. The case study shows that the proposed inversion method can reflect the random characteristics of concrete dams, the mechanical parameters obtained are reasonable, and the inverse model is feasible.…”
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A Dynamic and Energy-Efficient Clustering Algorithm in Large-Scale Mobile Sensor Networks by Changlin Ma, Nian Liu, Yuan Ruan

“…Random mobility and energy constraint are two main factors affecting system performance in mobile sensor networks, which cause many difficulties to system design. …”
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Vulnerability Analysis of Interdependent Scale-Free Networks with Complex Coupling by Chunjie Cao, Zhiqiang Zhang, Jingzhang Sun, Xianpeng Wang, Mengxing Huang

“…Recent studies have shown that random nodes are vulnerable in interdependent networks with simple coupling. …”
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A Frequency Domain Method for the Generation of Partially Coherent Normal Stationary Time Domain Signals by David O. Smallwood, Thomas L. Paez

“…The factors of the spectral density matrix, [U(f)] and [S(f)], are then used to generate a frame of random data in the frequency domain. The data is transformed into the time domain using an inverse FFT to generate a frame of data in the time domain. …”
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Chaining ＆ counter-based block cipher mode for authentication by HUANG Yu-hua1, HU Ai-qun2, WANG Jian-dong1

“…For raising the operation efficiency of block cipher algorithms,a fast authentication mode based on chaining ＆ counter（CCTR） was put forward;and its security was proved.Its speed was about 30% faster than that of authentication modes in common use（for example,CBC-MAC）.The dependence test results accord with the demands.The CCTR mode is complete;its degree of avalanche effect is about 0.999 3;its degree of strict avalanche criterion is 0.992 or so.The frequency test results indicate that the output generated by the CCTR mode had uniformity.The binary matrix rank,Run,spectral,non-overlapping template matching,overlapping template matching,Maurer’s universal statistical test,Lempel-Ziv compression,linear complexity,serial,approximate entropy,cumulative sums,random excursions and random excursions variant tests results fulfilled the requirements all.Therefore,the CCTR mode has good pseudo-randomness,which the security of CCTR mode is verified by way of statistical evaluation.…”
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STUDY ON WEAR RELIABILITY OF SYNCHRONIZER SLIDERS OF THE TRACKED VEHICLE by AN Hai, ZHOU Ling, YAN ZhaoYi, SUN Peng

“…Moreover,a new hybrid reliability model and its convergence iteration algorithm are proposed based on the case that truncated random variables,fuzzy random variables,and interval variables are coexisting is studied. …”
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Distributed Asynchronous Fusion Algorithm for Sensor Networks with Packet Losses by Tianpeng Chu, Guoqing Qi, Yinya Li, Andong Sheng

“…This paper is concerned with the problem of distributed estimation fusion over peer-to-peer asynchronous sensor networks with random packet dropouts. A distributed asynchronous fusion algorithm is proposed via the covariance intersection method. …”
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Wrapping and unwrapping multifractal fields: Application to fatigue and abrupt failure fracture surfaces by Samy Lakhal, Laurent Ponson, Michael Benzaquen, Jean-Philippe Bouchaud

“…We develop a spectral procedure to generate multifractal random fields in any dimensions d, parameterized by their roughness exponent H, intermittency exponent λ, and multifractal range ξ. …”
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Stochastic Finite Element Simulation of Uncertain Structures Subjected to Earthquake by Subrata Chakraborty, Santi Sekhar Dey

“…The earthquake induced ground motion is treated as stationary random process defined by respective power spectral density function. …”
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Statistical analysis of time series with scaling indices by Harald Atmnaspacher, Werner Ehm, Herbert Scheingraber, Gerda Wiedenmann

“…The key idea is to use the distribution of scaling indices obtained from a delay representation of the empirical time series to distinguish between random and non-random components. Statistical tests for this purpose are designed and applied to specific examples. …”
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Deterministic Sensing Matrices in Compressive Sensing: A Survey by Thu L. N. Nguyen, Yoan Shin

“…One of the most concerns in compressive sensing is the construction of the sensing matrices. While random sensing matrices have been widely studied, only a few deterministic sensing matrices have been considered. …”
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Explore the factors related to the death of offspring under age five and appraise the hazard of child mortality using machine learning techniques in Bangladesh by Ashikur Rahman, Md. Habibur Rahman

“…The k-fold cross-validation approach demonstrated the Random Forest model’s superior performance, and achieved the highest AUC (0.701). …”
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Peningkatan Performa Ensemble Learning pada Segmentasi Semantik Gambar dengan Teknik Oversampling untuk Class Imbalance by Arie Nugroho, M. Arief Soeleman, Ricardus Anggi Pramunendar, Affandy Affandy, Aris Nurhindarto

“…Metode ensemble learning yang digunakan adalah Random Forest dan Light Gradien Boosting Machine (LGBM). …”
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Numerical Simulations of the Lunar Penetrating Radar and Investigations of the Geological Structures of the Lunar Regolith Layer at the Chang’E 3 Landing Site by Chunyu Ding, Yan Su, Shuguo Xing, Shun Dai, Yuan Xiao, Jianqing Feng, Danqing Liu, Chunlai Li

“…The present study aims to explain the geological structural information contained in the channel 2 LPR (lunar penetrating radar) data. In this paper, the random medium theory and Apollo drilling core data are used to construct a modeling method based on discrete heterogeneous random media, and the simulation data are processed and collected by the electromagnetic numerical method FDTD (finite-difference time domain). …”
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Application of a theoretical simulator to the optimisation of risk-based invasive species surveillance by Thomas I. Gibson, Rebecca S. Millard, Isla MacMillan, Nick Taylor, Mark Thrush, Hannah Tidbury

“…Three potential surveillance scenarios were modelled: random, risk-based and heavy risk-based surveillance, each with three distributions of combined NIS risks of introduction and establishment: exponential, random and uniform. …”
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