Reversible data hiding based on RSBEMD coding and adaptive multi-segment left and right histogram shifting

By leveraging the secret data coding using the remainder storage based exploiting modification direction (RSBEMD), and the pixel change operation recording based on multi-segment left and right histogram shifting, a novel reversible data hiding (RHD) scheme is proposed in this paper. The secret data are first encoded by some specific pixel change operations to the pixels in groups. After that, multi-segment left and right histogram shifting based on threshold manipulation is implemented for recording the pixel change operations. Furthermore, a multiple embedding policy based on chess board prediction (CBP) and threshold manipulation is put forward, and the threshold can be adjusted to achieve adaptive data hiding. Experimental results and analysis show that it is reversible and can achieve good performance in capacity and imperceptibility compared with the existing methods.     

Representation of the non-dominated set in biobjective discrete optimization

This paper introduces several algorithms for finding a representative subset of the non-dominated point set of a biobjective discrete optimization problem with respect to uniformity, coverage and the ϵ-indicator. We consider the representation problem itself as multiobjective, trying to find a good compromise between these quality measures. These representation problems are formulated as particular facility location problems with a special location structure, which allows for polynomial-time algorithms in the biobjective case based on the principles of dynamic programming and threshold approaches. In addition, we show that several multiobjective variants of these representation problems are also solvable in polynomial time. Computational results obtained by these approaches on a wide range of randomly generated point sets are presented and discussed.     

Filament content threshold for activated sludge bulking: artifact or reality?

An often-noted feature of activated sludge settleability is the existence of a threshold content of filamentous bacteria, below which filaments have a relatively small effect on settleability, and above which settleability is much more sensitive to filament content. This concept has historically been based on an apparent inflection point in settleability/filament content curves. However, this was demonstrated to be an artifact of data presentation on semi-logarithmic scales. Analyses of several published data sets indicated that there was little or no evidence of a threshold effect when data were presented on linear scales, particularly around the 150 mL/g sludge volume index (SVI) "threshold". Rather, there appears to be a generally continuous (and often nearly linear) relationship between filament content and SVI, suggesting that the threshold effect, as commonly perceived, is not accurate. A modified empirical model of filament content and settleability was also presented.     

9Cr与CrMoV异种焊接接头疲劳裂纹扩展门槛值研究

裂纹扩展抗力是材料的内在属性,Paris的重要贡献是将ΔK引入疲劳裂纹扩展的研究,表明疲劳裂纹扩散的控制参数是应力强度因子ΔK。本试验异种焊接接头采用钨极氩弧焊(TIG)进行打底焊接,而后采用埋弧自动焊进行多层多道焊接,焊后进行相应的回火处理,之后随炉自然冷却。实验材料为9Cr钢母材、Cr Mo V母材和两侧的热影响区及焊缝区。按照降K法进行测试,应力比分别设定为0.5、0.7、0.9,在近门槛值区域进行多次测量,通过线性回归法拟合出直线方程,由此计算出疲劳扩展门槛值,可反映该焊接条件下9Cr与Cr Mo V异种材料接头的疲劳裂纹扩展行为。     

建成环境与交通需求管理的协同效应研究展望

作为促进绿色出行的重要举措,已 有诸多研究分析建成环境或交通需求管理 对出行行为的影响,但大多数忽视了两者之 间的协同作用。准确分析建成环境、交通需 求管理对出行行为的影响机制,以及其协同 效应,能够为促进我国大城市绿色出行、贯 彻绿色发展理念提供理论支撑和精准施策 依据。本文基于当前研究现状,对建成环境 与出行行为、交通需求管理与出行行为的影 响,以及建成环境和交通需求管理的协同作 用研究进行了总结,并结合我国大城市建成 环境和居民出行特征对学术研究热点问题 进行展望。     

Bayesian threshold selection for extremal models using measures of surprise

Statistical extreme value theory is concerned with the use of asymptotically motivated models to describe the extreme values of a process. A number of commonly used models are valid for observed data that exceed some high threshold. However, in practice a suitable threshold is unknown and must be determined for each analysis. While there are many threshold selection methods for univariate extremes, there are relatively few that can be applied in the multivariate setting. In addition, there are only a few Bayesian-based methods, which are naturally attractive in the modelling of extremes due to data scarcity. The use of Bayesian measures of surprise to determine suitable thresholds for extreme value models is proposed. Such measures quantify the level of support for the proposed extremal model and threshold, without the need to specify any model alternatives. This approach is easily implemented for both univariate and multivariate extremes.     

Channel length influenced contribution of hole and electron trapping effect to threshold voltage stability in organic field effect transistors

Effect of channel length on hysteresis and threshold voltage shift in copper phthalocyanine (CuPc) based organic field effect transistors was studied. Contrary to expectation, longer channel length devices exhibited minimum threshold voltage shift. Influence of channel length on the contribution of hole and electron trapping to threshold voltage stability was determined. Shortest channel length devices exhibited highest electron trapping effect while longest channel devices exhibited minimum hole as well as electron trapping. Lower hole trap effect for longer channel length devices was suggested to be due to reduced longitudinal field between source and drain electrodes while minimum electron trapping was attributed to suppression of drain current by increased hole trap centres.     

Stochastic resonance in parallel concatenated turbo code decoding

In an array of threshold devices, we examine the effect of noise in improving performance of turbo code decoding. Such a phenomenon of noise-enhanced effect is termed stochastic resonance (SR). When signal is subthreshold, SR is observed by using Gaussian noise during iterative decoding. That is, the minimal bit error ratio (BER) is achieved at some non-zero noise intensity level. Besides, the larger the number of threshold devices is, the more remarkable the SR effect becomes. Especially when noise intensity is nearly optimal, BER approximates to zero after a few decoding iterations. Moreover, when Gaussian mixture noise is utilized, suprathreshold stochastic resonance (SSR) occurs in turbo decoding. These results show the beneficial effect of noise in channel coding and decoding.