Defining Embedding Distortion for Intra Prediction Mode-Based Video Steganography

In this paper,an effective intra prediction mode-based video strganography is proposed.Secret messages are embedded during the intra prediction of the video encoding without causing large embedding impact.The influence on the sum of absolute difference(SAD)in intra prediction modes(IPMs)reversion phenomenon is sharp when modifying IPMs.It inspires us to take the SAD prediction deviation(SPD)to define the distortion function.What is more,the mapping rule between IPMs and the codewords is introduced to further reduce the SPD values of each intra block.Syndrome-trellis code(STC)is used as the practical embedding implementation.Experimental results demonstrate that our proposed steganographic scheme presents high undetectability compared with existing IPMs-based steganographic approaches.It also outperforms these schemes on stego video quality.

Prediction of Protein OmpH in Structure of C47-8 Pasteurella multocida

[Objective] This study aimed to predict the structure of protein OmpH from Pasteurella multocida C47-8 （PmC47-8） strain of yak. [Method] Online BLAST, signal peptide prediction, secondary structure prediction and protein characteristics of sequencing result of gene OmpH from PmC47-8 strain were analyzed. [Result] The similarities of gene OmpH from PmC47-8 with the published 81 OmpH genes were between 84% and 99%; a signal peptide was found with the cleavage sites between 20 and 21 in the polypeptide; secondary structure prediction showed that folding structure accounted for 49.8% and loop structure for 50.2%; it predicted that there were 7 O-glycosylation sites in OmpH protein with the amino acid residual sites of 2, 45, 48, 330, 716, 721, 723, respectively, and 2 N-glycosylation sites with the amino acid residual sites of 15 and 35. [Conclusion] This study lays the foundation for the study on the immunity of OmpH gene from yak.

Parallelization of intra prediction algorithm based on array processor

For the characteristics of intra prediction algorithms, the data dependence and parallelism between intra prediction models are first analyzed. This paper proposes a parallelization method based on dynamic reconfigurable array processors provided by the project team, and uses data level parallel(DLP) algorithms in multi-core units. The experimental results show that Y-component of peak signal to noise ratio(Y-PSNR) is improved about 10 dB and the time is saved 63% compared with high-efficiency video coding(HEVC) test model HM10.0. This method can effectively reduce codec time of the video and reduce computational complexity.

Real-time crash prediction on freeways using data mining and emerging techniques

Recent advances in intelligent transportation system allow traffic safety studies to extend from historic data-based analyses to real-time applications. The study presents a new method to predict crash likelihood with traffic data collected by discrete loop detectors as well as the web-crawl weather data. Matched case-control method and support vector machines （SVMs） technique were employed to identify the risk status. The adaptive synthetic over-sampling technique was applied to solve the imbalanced dataset issues. Random forest technique was applied to select the contributing factors and avoid the over-fitting issues. The results indicate that the SVMs classifier could successfully classify 76.32% of the crashes on the test dataset and 87.52% of the crashes on the overall dataset, which were relatively satisfactory compared with the results of the previous studies. Compared with the SVMs classifier without the data, the SVMs classifier with the web-crawl weather data increased the crash prediction accuracy by 1.32% and decreased the false alarm rate by 1.72%, showing the potential value of the massive web weather data. Mean impact value method was employed to evaluate the variable effects, and the results are identical with the results of most of previous studies. The emerging technique based on the discrete traffic data and web weather data proves to be more applicable on real- time safety management on freeways.

Yield strength prediction of rolled Al-(1.44-12.40)Si-0.7Mg alloy sheets under T4 condition

The effects of Si content on the microstructure and yield strength of Al-(1.44-12.40)Si-0.7 Mg(wt.%)alloy sheets under the T4 condition were systematically studied via laser scanning confocal microscopy(LSCM),DSC,TEM and tensile tests.The results show that the recrystallization grain of the alloy sheets becomes more refined with an increase in Si content.When the Si content increases from 1.44 to 12.4 wt.%,the grain size of the alloy sheets decreases from approximately 47 to 10μm.Further,with an increase in Si content,the volume fraction of the GP zones in the matrix increases slightly.Based on the existing model,a yield strength model for alloy sheets was proposed.The predicted results are in good agreement with the actual experimental results and reveal the strengthening mechanisms of the Al-(1.44-12.40)Si-0.7 Mg alloy sheets under the T4 condition and how they are influenced by the Si content.

Bi-variable damage model for fatigue life prediction of metal components

Based on the theory of continuum damage mechanics,a bi-variable damage mechanics model is developed,which,according to thermodynamics,is accessible to derivation of damage driving force,damage evolution equation and damage evolution criteria. Furthermore,damage evolution equations of time rate are established by the generalized Drucker＇s postulate. The damage evolution equation of cycle rate is obtained by integrating the time damage evolution equations,and the fatigue life prediction method for smooth specimens under repeated loading with constant strain amplitude is constructed. Likewise,for notched specimens under the repeated loading with constant strain amplitude,the fatigue life prediction method is obtained on the ground of the theory of conservative integral in damage mechanics. Thus,the material parameters in the damage evolution equation can be obtained by reference to the fatigue test results of standard specimens with stress concentration factor equal to 1,2 and 3.

计及转移效用与不确定性的移动式储能系统日前-日内市场竞标策略

为激励移动式储能系统(mobile energy storage system,MESS)参与电力市场,并在增加自身盈利的同时,在一定程度上缓解电力阻塞,计及转移效用与不确定性,提出一种MESS日前日内两阶段市场竞标策略。首先,在日前阶段,构建MESS参与电力市场双层投标模型,上层旨在决策MESS的时空分布及功率,下层为电力市场出清模型;其次,在日内阶段,采用多场景随机优化方法模拟、分析日内不确定性,并以日前荷电水平和转移计划为参考,基于模型预测控制方法构建MESS参与日内电力市场双层投标模型,上层旨在动态调整MESS实时功率,下层亦为电力市场出清模型;进一步,利用KKT条件和互补松弛理论将双层竞标模型转化为单层线性优化模型,以实现高效求解;最后,以国内某城域互联电力交通网络设计典型仿真案例。仿真结果表明,所提策略能够实现可调配资源的最大化利用,有效缓解电力系统输电阻塞,促进清洁能源消纳。

Edge Feature Based Fast Mode Decision Algorithm for H.264 Intra Prediction

A fast intra mode decision algorithm is proposed in this paper to reduce the complexity of H. 264 encoder. The proposed algorithm adopted the pre-processing method based on edge feature in pictures to filter out some impossible prediction modes. Context information and pre-computed threshold are used to determine whether it is necessary to check the DC mode. This method is able to get rid of most of candidate modes so that only 66--150 modes are left for the final mode decision, instead of 592 modes in the case of full search （FS） method of H. 264. Simulation results demonstrate that the coding time of the proposed algorithm falls down 71.7% compared with FS method, while the performance loss is trivial compared with FS mode decision scheme.

Impact of Subsurface Entrainment on ENSO Prediction: 1997-98 El Nio

Twenty-one-year hindcasts of sea surface temperature (SST) anomalies in the tropical Pacific were performed to validate the influence of ocean subsurface entrainment on SST prediction.A new hybrid coupled model was used that considered the entrainment of subsurface temperature anomalies into the sea surface.The results showed that predictions were improved significantly in the new coupled model.The predictive correlation skill increased by about 0.2 at a lead time of 9 months,and the root-mean-square (RMS) errors were decreased by nearly 0.2°C in general.A detailed analysis of the 1997-98 El Nio hindcast showed that the new model was able to predict the onset,peak (both time and amplitude),and decay of the 1997-98 strong El Nio event up to a lead time of one year,factors that are not represented well by many other forecast systems.This implies,in terms of prediction,that subsurface anomalies and their impact on the SST are one of the controlling factors in ENSO cycles.Improving the presentation of such effects in models would increase the forecast skill.

Improved fast inra prediction algorithm of H.264/AVC

With advanced prediction modes of intra prediction, intra coding of H.264/AVC offers significant coding gains compared with previous video coding standards. It uses an important tool called Lagrangian rate-distortion optimization (RDO)technique to decide the best coding mode for a block, but the computational burden is extremely high. In this paper, we proposed an improved fast intra prediction algorithm including block type selection and mode decision algorithm based on analysis of edge feature of a block. Our algorithm filters out unlikely block type and candidate modes to reduce the RDO calculations. Experimental results showed that the proposed algorithm can reduce the computation complexity of intra prediction from 52.90% to 56.31%, with 0.04 dB PSNR degradation and 2% increase of bit rate.

H.264编码器中Intra-Buffer的硬件设计

提出了高性能的Intra-Buffer的硬件设计方案,引入了仲裁机制,提高了编码器运行的速度,并且在FPGA上实现了硬件设计方案。

On numerical earthquake prediction

Can earthquakes be predicted？ How should people overcome the difficulties encountered in the study of earthquake prediction？ This issue can take inspiration from the experiences of weather forecast. Although weather forecasting took a period of about half a century to advance from empirical to numerical forecast, it has achieved significant success. A consensus has been reached among the Chinese seismological community that earth- quake prediction must also develop from empirical fore- casting to physical prediction. However, it is seldom mentioned that physical prediction is characterized by quantitatively numerical predictions based on physical laws. This article discusses five key components for numerical earthquake prediction and their current status. We conclude that numerical earthquake prediction should now be put on the planning agenda and its roadmap designed, seismic stations should be deployed and observations made according to the needs of numerical prediction, and theoretical research should be carried out.

Energy Balance-related Behaviors Are Related to Cardiometabolic Parameters and Predict Adiposity in 8-14-year-old Overweight Chinese Children One Year Later

To identify target energy balance-related behaviors（ERBs）,baseline data from 141overweight or obese schoolchildren（aged 8-14years old）was used to predict adiposity[body mass index（BMI）and fat percentage]one year later.The ERBs included a modified Dietary Approach to Stop Hypertension diet score（DASH score）,leisure-time physical activity（PA,days/week）,and leisure screen time（minutes/day）.Several cardiometabolic variables were measured in the fasting state, including systolic blood pressure （SBP）, diastolic blood pressure （DBP）, blood glucose （GLU）, total cholesterol （TC）, triglycerides （TG）, low-density lipoprotein （LDL-C）, and high-density lipoprotein （HDL-C）.

Parameter Self - Learning of Generalized Predictive Control Using BP Neural Network

This paper describes the self—adjustment of some tuning-knobs of the generalized predictive controller(GPC).A three feedforward neural network was utilized to on line learn two key tuning-knobs of GPC,and BP algorithm was used for the training of the linking-weights of the neural network.Hence it gets rid of the difficulty of choosing these tuning-knobs manually and provides easier condition for the wide applications of GPC on industrial plants.Simulation results illustrated the effectiveness of the method.

Formation permeability evaluation and productivity prediction based on mobility from pressure measurement while drilling

Based on the measurement mechanism of mobility in pressure measurement while drilling, through analyzing a large number of mobility data, it is found that under the condition of water-based mud drilling, the product of mobility from pressure measurement while drilling and the viscosity of mud filtrate is infinitely close to the water phase permeability under the residual oil in relative permeability experiment. Based on this, a method converting the mobility from pressure measurement while drilling to core permeability is proposed, and the permeability based on Timur formula has been established. Application of this method in Penglai 19-9 oilfield of Bohai Sea shows:(1) Compared with the permeability calculated by the model of adjacent oilfields, the permeability calculated by this model is more consistent with the permeability calculated by core analysis.(2) Based on the new model, the correlation between the calculated mobility of well logging and the actual drilling specific productivity index bas been established. Compared with the relationship established by using the permeability model of an adjacent oilfield, the correlation of the new model is better.(3) Productivity of four directional wells was predicted, and the prediction results are in good agreement with the actual production after drilling.

HEVC视频加密技术综述

针对视频数据在传输和存储过程中存在被非法获取和恶意破坏的问题,从高效视频编码(HEVC)标准和加密技术出发,对HEVC视频编码标准下的加密技术进行综述。回顾了视频编码技术的发展历程,介绍了HEVC视频编码标准,讨论了视频加密技术常见攻击方法及性能评估指标,全面梳理与详细分析了不同视频加密技术性能及其优缺点,展望了视频加密技术的发展趋势,旨在为视频加密技术的研究和应用提供参考。

急诊科危重症患者院内转运不良事件的风险预测模型构建

目的分析急诊科危重症患者院内转运不良事件风险因素,构建风险预测模型。方法采用方便抽样法选取2021年10月至2023年2月某院急诊科进行院内转运的870例危重症患者的临床资料,采用单因素和多因素Logistic回归分析建立风险预测模型,以受试者工作特征(receiver operating characteristic,ROC)曲线下面积(area under curve,AUC)评价模型预测效果。结果英国国家早期预警评分(national early warning score,NEWS)、血氧饱和度、急诊B超、血管活性药物、机械通气是急诊科危重症患者发生病情不良事件的独立风险因素;血氧饱和度、携氧装置、Ⅲ类管路、护工参与转运是技术不良事件的独立风险因素(均P<0.05)。AUC分别为0.813,0.756。结论构建的急诊科危重症患者院内转运不良事件风险预测模型具有一定的参考价值。

一种基于H.264 Intra帧的差错隐藏方法

为了充分利用H.264新特性带来的冗余信息对视频传输中的错误进行隐藏,提出了一种新的基于Intra帧的差错隐藏方法,根据丢失块周围子块的预测模式推断出丢失块中各子块的预测模式,再根据推断的预测模式重建丢失块.试验表明,这种方法能很好地预测出丢失块的预测模式,并能适应不同内容类型的图像,差错隐藏的效果明显.

一种用于AVS-M视频编码的快速帧内预测模式判断算法

AVS－M作为中国具有自主知识产权的移动视频压缩标准，是采用基于块的混合编码方法，其帧内预测针对4×4块进行。由于AVS—M对亮度块考虑9种预测模式，从而导致最优预测模式判断的计算相当复杂。为了提高编码速度，提出通过计算块内下采样像素点代价，然后确定候选预测模式集的方法来实现帧内预测模式的快速判决。仿真结果表明，该快速算法在保证编码性能几乎不变的前提下可使得全帧内编码的总时间减少约20％－30％。

基于Hough变换的3D-HEVC深度图快速帧内预测方法

最新的3D高效视频编码(3D-HEVC)能高效地压缩三维视频数据,但其深度图中的帧内预测计算复杂度高。为了降低3D-HEVC中深度图帧内预测编码时间,提出了一种基于Hough变换的3D-HEVC深度图快速帧内预测方法。采用Canny对3D-HEVC深度图提取边缘信息,当深度图中当前预测单元(PU)分块内部不存在边缘时,跳过帧内预测中深度建模模式(DMM);再对边缘信息二值图进行Hough变换检测直线,若有1条直线穿过当前PU分块,则根据直线的位置和角度仅计算遍历5个近似角度的DMM1模式,否则跳过DMM1模式的遍历。实验结果显示,相比最新的3D-HEVC国际标准,该方法在保持视频质量和比特率基本无损的前提下,平均降低了40.8%的编码时间。