An effective automatic detection system for multi-protocol attack

Since there exists multi-protocol attack when several security protocols are co-executed in a computer network, an automatic detection system for multi-protocol attack (ADMA) is proposed. The system is composed of two parts named protocol search subsystem and attack verification subsystem. According to the consistency condition of the type of encrypted messages between the target protocol and the secondary protocol, the protocol search subsystem can automatically search for the candidate secondary protocols, which may be used to attack the target protocol. By improving the SAT-based model checking, attack verification subsystem can automatically verify whether multi-protocol attack exists between the target protocol and the candidate secondary protocols or not. The experiment results show that ADMA system can implement automatic detection for multi-protocol attack, and some new multi-protocol attacks are found in the detection.     

Application of Uncertain Model in Urban River Quality Simulation

Owing to the fluctuation of water quality in urban river which polluted by drainage along river, one-dimension uncertain water quality model embeded neural network is established. Genetic algorithms and a modified fitness function are used to optimize parameters of the uncertain model. Examples illustrate that the uncertain model has higher prediction accuracy with the average accuracy over 80% than the certain model, and is more sensitive to the fluctuation of pollutants discharged into the river. The uncertain model has a significant advantage of prediction and could better adapt to the changing urban water environment, especially at points close to the pollution sources.     

Investigations on Effect of Solution Concentration and Temperature on Rate of Concrete Sulfate Attack

Through many tests and standard analysis,the effects of solution concentration and temperature on rate of concrete sulfate attack were investigated.The test results show that when solution concentration and temperature are lower than certain value,the speed of attack is accelerated with increasing concentration and temperature,however,higher temperature and concentration of solution may decrease the rate of attack.The speed of attack of sodium sulfate is faster than the one of attack of magnesium sulfate under various factors.It is suitable to adopt the coefficient of tensile as the accelerated assessing criterion for the attack of sodium sulfate.The coefficient of tensile and compressive strength should be considered together for the attack of magnesium sulfate.     

Hyperspectral laser-induced fluorescence imaging for assessing apple fruit quality

Chlorophyll fluorescence is a promising technique for postharvest quality research, and reported studies were mainly based on the fluorescence kinetic analysis method, which has not been quite satisfactory for measuring fruit quality. This paper reports on using a hyperspectral imaging technique for measurement of laser-induced fluorescence from apple fruit for predicting multiple fruit quality parameters. A continuous wave blue laser (408 nm) was used as an excitation source for inducing fluorescence in apples. Fluorescence scattering images were acquired from ‘Golden Delicious’ apples by a hyperspectral imaging system at the instance of laser illumination (0 min) and after 1, 2, 3, 4, and 5 min of illumination. The hyperspectral fluorescence image data were represented by mean, maximum, and standard deviation spectra. Standard tests were performed on measuring fruit skin and flesh color, firmness, soluble solids content, and titratable acid. A hybrid method of combining principal component analysis and neural network modeling was used for developing prediction models to predict fruit quality parameters for each of the six illumination time periods. Fluorescence emission decreased steadily during the first 3 min of illumination and was stable within 5 min. The 0-min fluorescence prediction models had somewhat poorer prediction results for individual quality parameters except skin hue than did the models of longer illumination time. The differences were minimal in the model prediction results from the fluorescence data at 1, 2, 3, 4 or 5 min of illumination. Overall, excellent predictions were obtained for apple skin hue with the correlation coefficient of prediction of 0.94. Relatively good predictions were obtained for fruit firmness, skin chroma, and flesh hue with values for the correlation coefficient being equal to or greater than 0.74 for 1 min of illumination or longer times, and poorer correlations were found for soluble solids content, titratable acid, and flesh chroma. Hyperspectral laser-induced fluorescence imaging is potentially useful for assessing selected quality parameters of apple fruit and further research is needed to improve fluorescence measurement for better prediction of fruit quality.     

基于遗传算法结合偏最小二乘的潮土碱解氮高光谱特征及含量估测

提取土壤碱解氮特征光谱是利用高光谱数据进行其含量估测的关键。对山东省典型潮土土壤样本测试高光谱并进行变换;采用遗传算法（GA）结合偏最小二乘法（PLS）,在筛选潮土碱解氮含量特征谱区的基础上,构建潮土碱解氮含量偏最小二乘（PLS）回归估测模型;优选最佳模型并与相关分析、逐步回归分析和单纯偏最小二乘回归分析的模型进行比较。结果表明：潮土碱解氮特征波段为449~469nm,988~1001nm,1065~1078nm,1716~1736nm,1912~1925nm,2213~2233nm,2262~2275nm;基于各输入光谱特征谱区构建的估测模型决定系数R²均较高,其中基于反射率一阶导数光谱筛选的特征谱区,构建的模型精度最高,数据点（147个）为原始全谱的7.17%,建模R²达到0.97,均方根误差RMSE为4.78mg/kg,验证R²为0.95,RMSE为5.49mg/kg,对潮土碱解氮含量具有较好的预测准确性;在光谱变换形式中,反射率的一阶导数表现最佳;方法比较显示采用遗传算法结合偏最小二乘（GA-PLS）获得较高预测精度的同时,可简化模型。说明遗传算法结合偏最小二乘法（GA-PLS）,可有效筛选土壤碱解氮的特征波段,减少模型参与变量,提高估测精度。     

Local Nonlinear Forecasting of Short-term Power Load Forecasting

The nearest points in phase space are determined by Euclid distance in chaotic local prediction. The prediction accuracy depends on quality of the nearest points. But the shortest distance does not imply better forecasting effect. While false nearest neighboring point or high embedding dimensions appear evolvement track of some nearest neighboring point should be apart from prediction point. Because it is difficult for Euclid distance to reflect the correlation degree between the nearest points and prediction point. So the idea of combining Euclid distance with correlation degree is put forward. The method is applied to short-term electrical load forecasting. The result of load series forecasting by the presented method is more effective to improve prediction accuracy.     

国内外气候模式对黑龙江省汛期降水预测分析

为了评估季节气候模式及多模式集合对黑龙江省汛期降水的跨季节预测能力,最终提高黑龙江省汛期气候预测准确率。基于1983—2017年中、美、欧三种季节气候模式的资料,将多模式集合预报技术应用于黑龙江省汛期降水预测,采用距平相关系数(ACC)、趋势异常综合检验(Ps)评估、分级评分(Pg)评估和距平符号一致率(Pc)4种定量评估方法全面评估了上述3种季节气候模式及多模式集合对黑龙江省汛期降水的跨季节预测能力,并最终给出适合于黑龙江省汛期降水的客观预测方法。结果表明：各家模式对黑龙江省汛期降水有一定的跨季节预报能力,但对于降水趋势的异常量级预测能力相对较差。各家模式预测评分比较来看,EC模式预测评分相对更好,在预测业务中可以重点考虑；多模式超级集合预测评分高于日常业务质量评分和多模式等权集合平均的预测评分,可以在汛期气候预测中参考。     

基于量子多种群遗传算法的蛋白质二级结构预测

为进一步提高蛋白质二级结构的预测精度,将量子计算和多种群算法融入到传统的遗传神经网络算法中。同时考虑到氨基酸残基的众多理化性质是形成蛋白质二级结构的主要驱动力,构象偏好也是影响蛋白质二级结构形成的重要因素,提出了一种新的基于理化性质和构象信息编码的量子多种群遗传算法。该方法蕴含了丰富的生物信息,可以有效减少网络系统的不确定性。用PDBselect25中的24条蛋白质进行测试,结果表明该算法可以有效的预测蛋白质的二级结构,平均预测精度达到72.10%,分别比SNN、DSC、PREDSATOR方法提高了7.80%、3.70%和3.41%。该方法采用混合编码的形式进行编码,在每个种群内部引入量子计算,形成了以多种群遗传算法来带动量子计算,量子计算反作用于多种群算法的双重优化的方法,可有效提高蛋白质二级结构预测的精确度。     

大攻角及桥面粗糙度对扁平钢箱梁涡振性能的影响

为探究大攻角及桥面粗糙度对扁平钢箱梁涡振性能的影响,对寸滩长江大桥主梁进行了风洞试验。应用Matlab软件模拟桥面粗糙度变化范围,根据模拟结果选取对应的砂纸在试验中模拟桥面粗糙度,分析了攻角及桥面粗糙度对扁平钢箱梁涡振区间及幅值的影响。试验研究表明:在大攻角下扁平钢箱梁的涡振振幅和范围明显增大,对桥址位于山区等容易发生大风攻角的地区的桥梁应进行大攻角试验。扁平钢箱梁的涡振响应随着桥面粗糙度增大而减小。正攻角范围内,桥面粗糙度对涡振响应的影响随着攻角减小而增大。桥面粗糙度发生变化时,扭转涡振响应更加敏感,变化幅度大于竖向涡振响应变化幅度。     

陕西苹果花期预测模型研究

为了增强陕西各苹果产区精确防御花期冻害的能力,有效提高苹果产量和品质,促进陕西苹果产业稳定、持续、健康发展,依据统计分析原理,对陕西各苹果产区花期和花期前的各项气温因子进行详细的相关性分析。结果显示：陕西苹果花期前0~5℃的活动/有效积温与真实花期的相关性好于0~5℃天数与真实花期的相关性;0~5℃的活动/有效积温越靠近真实花期,其与真实花期的相关性越显著;从0℃至5℃各活动/有效积温与苹果花期的相关性呈增高趋势;各有效积温因子与苹果花期相关性好于活动积温因子与苹果花期的相关性。基于以上分析结果,分果区建立了陕西苹果的花期预测模型,并通过回代和预测对模型进行检验。检验结果显示平均误差小于3天,预测结果可为实际生产中苹果花期防灾减灾工作的开展提供参考。     

大豆亲本间遗传距离与杂种优势的相关性研究

为提高杂交育种效率,有必要对杂种优势预测进行探索。本研究选用国内外不同地区10份材料,按NCⅡ不完全双列杂交法组配45个杂交组合,利用SSR分子标记遗传距离预测大豆亲本间杂种优势。结果表明：10份亲本中检测到417个多态性等位基因变异,多态性位点变化范围为2~5个,遗传相似系数(GS)变幅为0.520~0.695,平均GS值为0.5996。10份供试材料被分为两大类,F₁杂种优势值从3.4%~42.1%,F₁性状均具有不同程度正向杂种优势。其中,单株粒数杂种优势与遗传距离的相关系数为0.461,达显著水平。其余8个农艺、品质性状与遗传距离的相关系数未达显著水平。初步认为,利用该174个SSR分子标记检测亲本间遗传差异,对本研究10份大豆亲本间杂种优势预测效果不显著。利用分子标记遗传距离预测大豆亲本杂种优势的方法有待进一步研究。     

近红外光谱无损检测石榴中花色苷含量研究

以全国不同地区的97个石榴为样本,研究近红外光谱无损检测石榴中花色苷的含量,探讨了不同数据处理和回归方法对建模效果的影响。结果表明,对原始光谱进行一阶微分、标准多元离散校正法处理后,采用偏最小二乘法建立的石榴花色苷含量预测模型,预测偏差为0.148,预测标准差(SEP)为1.47,相关系数为0.829,模型预测良好,说明近红外光谱无损检测石榴的品质是可行的。     

Sulphate Attack Resistance of the Concrete with Additives and Its Assessment

The influence of three kinds of additives: silica fume,slag and fly ash on the sulphate attack resistance of concrete were studied.The experiment results show that these three kinds of additives can improve sulphate attack resistance of the concrete and the order of their efficiency from high to low is silica fume,slag and fly ash;the development of mortar expansion value is closely related to the degree of sulphate attack resistance of the concrete;integrated assessing two concrete properties: mortar expansion value and compressive strength ratio can more exactly assess the sulphate attack resistance of the concrete.     

基于ARMA模型的地表水水质预测方法研究?

选用合适的模型提高预测的精度和可靠性,为区域水环境管理提供科学依据,是水质预测要解决的关键问题。为了解决这一问题,根据辽河流域的实际,运用自回归滑动平均(ARMA)模型对辽河流域东陵大桥监测断面CODMn的水质变化趋势进行预测。结果表明：综合自相关函数、偏相关函数以及BIC原则,ARMA(1,1)模型能够更好地用于东陵大桥断面水质预测。拟合结果显示,相对误差在2.60%~25.98%之间,平均相对误差为13.69%,说明该模型能够充分利用近期水质资料信息,以精确预测未来水质变化趋势。而对东陵大桥监测断面CODMn的预测显示,未来CODMn呈现出增长态势,辽宁水环境管理任务仍然很重。最后,就ARMA模型应用于水质预测的问题和发展方向进行了探讨。     

Virtual Construction Model and Simulation Analysis for Equipment Management of Earthmoving Operations

Based on Petri net theory and workflow model, a 9 tuple colored Petri net simulation model of earthmoving operations was presented focusing on the equipment management in the earthmoving construction. The dynamic changes of workflow and information flow in the construction process were illustrated in the model, and the constraint relationship between equipment and construction conditions was taken into account. Based on the information of the number of equipment and cost, the simulation for the construction situation, estimated completion time, cost, and equipment productivity were conducted. The model was operated based on the CPN Tools platform. And sensitivity analysis and model validation on the model were carried out by simulating the data collected in a real case, which demonstrates that the model can improve the accuracy of the simulation results in the earthmoving operation construction process.     

A Dynamic Model for Water and Nitrogen Limited Growth in Spring Wheat to Predict Yield and Quality

Annual variation of bread wheat ( Triticum aestivum L.) yield and quality has caused problems for agronomic policy in northern regions. Yield prediction methods based on visual assessment of crop may be inaccurate as they are not based on quantitative data. The aim of this study was to develop a simple dynamic model, based on daily climatological data, enabling prediction of crop growth, and changes in crop yield, and grain protein concentration and starch quality. The model was built using field data collected in 1972–88. Spring wheat cultivars included in the study were Kadett and Ruso. The calibration of growth and Hagberg falling number (used as a measure of starch quality) sub-models resulted in a highly significant positive correlation between measured and calculated values. The calibration of nitrogen sub-models failed, however, with poor correlation between measured and calculated values. The model was tested against independent field data collected during 1989–90, and results correlated with calibration results. The yield predictions based on independent field data were accurate, and the same as or similar to field trial results. However, the independent Hata revealed flaws in soil-water and Hagberg falling number sub-models.     

Using visible and near infrared diffuse transmittance technique to predict soluble solids content of watermelon in an on-line detection system

Sugar content is one of the most important factors determining the eating quality of watermelon fruit. In order to detect the fruit soluble solids content (SSC) on-line, this work develops a nondestructive on-line detection prototype system using visible and near-infrared (Vis/NIR) technology. For the acquisition of the diffuse transmittance spectrum of watermelon, the conveyor was set at a speed of 0.3 m/s and ten 150 W tungsten halogen lamps were used as the light source. The crucial model for SSC value prediction was optimized by chemometrics. Partial least squares regression (PLSR), stepwise multiple linear regressions (SMLR), Monte-Carlo uninformative variable elimination (MC-UVE) and genetic algorithms (GA) were applied to the spectra in the range of 687–920 nm. The data pre-processing methods were optimized to transmittance spectra with baseline offset correction (BOC), and the BOC-MC-UVE-SMLR calibration model was the best with a correlation coefficient (r_pre) of 0.70, root mean square error of prediction (RMSEP) of 0.33 °Brix for the prediction set. In on-line testing of 30 samples, the r_pre was 0.66 and RMSEP was 0.39 °Brix. The results showed that a nondestructive on-line SSC value determination prototype based on Vis/NIR technology was feasible.     

河南省粮食产量影响因素和预测方法

粮食生产是国民经济重要的组成部分,粮食产量对于保证我国的粮食安全具有重要意义。旨在提高粮食产量预测的科学性和准确性,在分析现有预测方法的基础上,文中将灰色理论和神经网络有机地结合在一起,通过灰色理论关联度分析,在众多影响粮食产量的因素中确定出主要的、客观的因素指标,通过这些指标利用人工神经网络具有的非线性建模和极高的拟合精度特点,应用到粮食产量预测中去。结果表明：人工神经网络预测的最大误差1.21%,平均误差0.63%。预测精度较高。为粮食产量预测提供了一种科学的、有效的预测方法。     

Detection of donor effects in a rye introgression population with genome‐wide prediction

Introgression populations are developed to make genetic resources for breeding purposes available. In the case that the number of donor segments exceeds the number of lines, genome‐wide prediction (GWP) methods are suggested as promising for the analysis of such populations. Our objectives were to characterize a rye introgression population with the Rye5K SNP assay and to apply a GWP model with a modification of the restricted maximum likelihood procedure that yields heteroscedastic variances to detect significant donor effects. The introgression lines (ILs) carried on average 4.6 donor segments with a mean length of 27 cM and represented 94% of the donor genome. Two donor effects were detected that significantly increased thousand‐kernel weight. We found four donor effects for protein, total pentosan and starch content that can improve baking quality. Three donor effects for protein content were observed for improving feeding purposes and one donor effect for starch content to improve ethanol production. The effects were localized to small genomic regions. Consequently, these ILs can improve rye breeding by directly employing them in breeding programmes for variety development.     

Predicting the DNA splice sites with conditional random field

Predicting the DNA splice sites has become the most attractive and important issue in the field of genome information research due to its great help to find gene coding area.Current gene recognition algorithms mainly consider the global features of the coding area,instead of the specific information of the splicing sites,which are usually unable to recognize the splicing sites accurately.A new method based on the conditional random fields (CRFs) is proposed for splice sites prediction.CRFs can capture long distance dependent relationships between labels and avoid label bias.Experimental results show that CRFs is suitable for splice sites prediction and can improve performance.