城市排水系统中雨水存储装置的预设模型研究

建立一个概念上的模型去评价雨水储水箱在以前雨水排放系统中的作用．雨水储水箱模型中的流出量就转化为等量的降雨量．根据这种单一降雨情况下的降雨强度，持续时间／频率的关联性（IDF-关联性），开发出针对暴雨处理的模型．

基于多重预设广义频率响应函数模型的故障诊断方法

为了避免在基于非线性谱分析的故障诊断中估计被分析系统当前的广义频率响应函数(GFRF) ,提出了一种基于多重预设GFRF模型的故障诊断方法 .该方法使用不同的预设GFRF模型来表征系统的各种工作模态 ,并根据各预设模型与系统当前状态的匹配程度来判定系统故障 .应用这一方法对实际的车辆减震弹簧的故障进行了诊断 ,测试结果表明 ,该方法对于工程应用是可行的 ,且该方法能避免在线估计GFRF ,具有在线计算量小。

预设路径模型及其在认知心理学研究中的应用

预设路径模型(Fixed-links modeling)是在结构方程模型框架下发展出的用于分析心理学实验数据的统计模型。该类模型的主要特征是根据前期理论基础和实验设计,通过预先设定模型中显变量与潜变量之间的因素载荷矩阵实现对显变量方差的拆分。因素载荷矩阵的设定主要基于实验水平与所表征的心理过程之间的关系,选取相应函数来表征不同实验水平之间的变化趋势。该模型在表征工作记忆、注意和学习的内部加工过程及揭示不同认知过程的具体联系中发挥了重要作用。

非线性系统故障诊断的Volterra模型方法

针对非线性系统的故障诊断问题,系统地总结了基于Volterra级数模型的故障诊断的理论与方法。由于Volterra级数模型可以完全描述非线性系统的传递特性,因而可将其应用于系统的故障诊断,即在系统工作过程中,通过分析故障发生前后Volterra模型中非线性因素的变化来判知系统的故障。在介绍了这一新的故障诊断理论的基本思想后,结合减震弹簧的疲劳诊断,总结了当前的两种主要研究方法,即基于非线性谱分析的故障诊断方法和基于多重预设Volterra模型的故障诊断方法。阐述了这两种方法的工作原理和实现方法,指出了今后在这一方向上需要进一步研究解决的问题。

基于Volterra级数和方波脉冲函数变换的非线性系统模型辨识与故障诊断

本文采用Volterra级数和方波脉冲函数变换技术对一类非线性系统的数学模型进行了辨识,导出了相应的辨识公式。在此基础上,提出了系统的多重预设模型的故障诊断方法。

考虑燃烧作用的隧道火灾三维数学模型

采用预设概率密度函数模型考虑燃烧的过程，构建了一种描述隧道火灾过程中燃油燃烧、烟气流动和传热的三维数学模型。应用该模型模拟了台缙高速公路苍岭特长隧道在释热率为50MW、风速分别为0～2m／s条件下的火灾过程，并通过室内模型燃烧试验验证了其有效性。与相同条件下热源模型计算结果的比较表明：无论通风条件如何，燃烧释放的大量烟气均会在火源上方形成一高速烟流区，而热源模型由于忽略了燃烧过程，在风速≥1m／s的条件下将无法刻画出该区域。高速烟流区抑制了纵向风流与高温烟流的混合，控制着火源近区的流场结构，是造成烟气回流和分层运动现象的主要因素之一。

数字法学研究现状的再反思——法学理论向何处去?

伴随着数字技术的迅猛发展,我国数字法学的研究成果颇丰。但数字法学理论未形成体系,主要表现在研究方向零散,基础性、原创性的研究内容少,数字法学研究框架缺位等方面。现有研究成果偏重于概念创造而非转化应用,研究者对于数字权力争夺的重要性认识不足,缺少对于技术变革的深层次法哲学思考,导致学术创作有脱离实践的风险。造成此研究现状的原因主要有数字法学理论研究与实际相结合的紧密程度不足、法学研究者学术背景结构单一、学术评价标准导向不足等。为促使数字法学理论有效引领我国数字化转型实践,必须坚持数字法学研究的中国化方向,坚持从实际出发解决现实问题。同时扩展学术成果评价体系的标准与内容,正确引领学术研究方向。

产品信息、预设同侪反应与购买意愿——基于社交网络情景

社交网络情景下产品信息已成为消费者认知产品的重要线索和窗口。作为理性的个体,消费者往往会综合考虑多种类型的产品信息以降低购买风险,但目前尚没有研究将产品信息作为一个整体、综合的概念探究其对购买意愿的影响。此外,虚拟的社交网络情景下,个体更倾向于根据预设他人反应决定自身的态度或行为,由此产生的影响即为预设影响,这种影响在新情景下变得更加普遍和重要。然而,目前有关预设影响的研究还是营销学研究中的空白点。结合社交网络情景,兼顾产品信息是一个综合的概念,从信息创建主体和信息性质两个维度划分产品信息的类型。在此基础上,结合预设影响模型和社交网络情景下预设影响变得更加普遍和重要这一客观现象,以及消费者因对产品的相似偏好而属于同侪关系而非一般的人际关系,采用实验的方法进一步对以预设同侪反应为中介变量的产品信息影响购买意愿的机理进行探索。研究结果表明,不同主体创建的产品信息、不同性质的产品信息及二者的交互项均对购买意愿有显著影响,由此4种类型的产品信息对购买意愿的影响程度由大到小依次为用户描述型信息、企业描述型信息、用户推荐型信息和企业推荐型信息;预设同侪反应在产品信息与购买意愿的关系中起中介作用;而且预设同侪反应在用户描述型信息与购买意愿的关系中所起的中介作用最大,在企业描述型信息与购买意愿的关系中所起的中介作用次之,在企业推荐型信息与购买意愿的关系中所起的中介作用最小,而在用户推荐型信息与购买意愿的关系中并不具有中介作用。理论上,对不同类型产品信息在营销学中的重要性有了新的认识,对消费者购买意愿的形成过程进行了新的解读,尝试将预设同侪反应这一社会心理学的概念引入营销学领域,不但是对相关研究成果的丰富,而且验证了社交网络情景下预设影响在营销领域的存在性和重要性。实践上,为企业有效利用产品信息进行产品推广、实施病毒营销策略和细分市场战略具有重要的启示作用。

A Summary of Studies on Prediction of Urban Construction Land Scale

Research results of prediction of urban construction land scale were sum- marized from the aspects of influencing factors of construction land expansion and prediction models of construction land scale, and their characteristics and deficiencies of these studies were analyzed to provide reference for deep research on pre- diction of urban construction land scale in China. The results show that there are few studies on basic theories about total scale of construction land presently, and there is no theoretical framework in studies on influencing factors. A single model has been used to conduct prediction on a small scale in most studies, but there have been few studies on iarge-scale prediction based on comprehensive benefit. Therefore, it is necessary to strengthen the exploration of basic theory and mechanism of urban construction land prediction, study iarge-scale prediction based on comprehensive benefit, and strengthen the comprehensive application of econometric analysis, spatial analysis and information technology analysis.

Design and Analysis of Integrated Predictive Iterative Learning Control for Batch Process Based on Two-dimensional System Theory

Based on the two-dimensional （2D） system theory, an integrated predictive iterative learning control （2D-IPILC） strategy for batch processes is presented. First, the output response and the error transition model predictions along the batch index can be calculated analytically due to the 2D Roesser model of the batch process. Then, an integrated framework of combining iterative learning control （ILC） and model predictive control （MPC） is formed reasonably. The output of feedforward ILC is estimated on the basis of the predefined process 2D model. By min- imizing a quadratic objective function, the feedback MPC is introduced to obtain better control performance for tracking problem of batch processes. Simulations on a typical batch reactor demonstrate that the satisfactory tracking performance as well as faster convergence speed can be achieved than traditional proportion type （P- t-we） ILC despite the model error and disturbances.

Soft-sensing Design Based on Semiclosed-loop Framework

Soft-sensing is widely used in industrial applications. The traditional soft-sensing structure is open-loop without correction mechanism. If the working condition is changed or there is unknown disturbance, the forecast result of soft-sensing model may be incorrect. In order to obtain accurate values, it is necessary to carry out online correction. In this paper, a semiclosed-loop framework (SLF) is proposed to establish a soft-sensing approach, which estimates the input variables in the next moment by a prediction model and calibrates the output variables by a compensation model. The experimental results show that the proposed method has better prediction accuracy and robustness than other open-loop models.

Comparative Study of Response Surface Designs with Errors-in-Variables Model

This paper investigates the scaled prediction variances in the errors-in-variables model and compares the performance with those in classic model of response surface designs for three factors.The ordinary least squares estimators of regression coefficients are derived from a second-order response surface model with errors in variables.Three performance criteria are proposed.The first is the difference between the empirical mean of maximum value of scaled prediction variance with errors and the maximum value of scaled prediction variance without errors.The second is the mean squared deviation from the mean of simulated maximum scaled prediction variance with errors.The last performance measure is the mean squared scaled prediction variance change with and without errors.In the simulations,1 000 random samples were performed following three factors with 20 experimental runs for central composite designs and 15 for Box-Behnken design.The independent variables are coded variables in these designs.Comparative results show that for the low level errors in variables,central composite face-centered design is optimal;otherwise,Box-Behnken design has a relatively better performance.

Identity-Based Proxy Verifiably Encrypted Signature Scheme

A Verifiably Encrypted Signature (VES) plays an essential role in the construction of a fair data exchange. The paper proposes an Identity-based Proxy Verifiably Encrypted Signature (IPVES) to combine the advantages of a proxy signature and a VES in order to delegate the signing capability of the VES of an entity called the original signer to another entity, called the proxy signer. In this IPVES scheme, the original signer delegates his/her signing capability to the proxy signer. The proxy signer issues a signature by using a proxy signing key, encrypts the signature under a designated public key, and subsequently convinces a verifier that the resulting ciphertext contains such a signature. We prove that the proposed IPVES scheme is secure in a random oracle model under the computational Diffie-Hellman assumption.

Toward an RSU-unavailable Lightweight Certificateless Key Agreement Scheme for VANETs

Vehicle ad-hoc networks have developed rapidly these years,whose security and privacy issues are always concerned widely.In spite of a remarkable research on their security solutions,but in which there still lacks considerations on how to secure vehicleto-vehicle communications,particularly when infrastructure is unavailable.In this paper,we propose a lightweight certificateless and oneround key agreement scheme without pairing,and further prove the security of the proposed scheme in the random oracle model.The proposed scheme is expected to not only resist known attacks with less computation cost,but also as an efficient way to relieve the workload of vehicle-to-vehicle authentication,especially in no available infrastructure circumstance.A comprehensive evaluation,including security analysis,efficiency analysis and simulation evaluation,is presented to confirm the security and feasibility of the proposed scheme.

Immobilization of Lactobacillus rhamnosus TISTR108 on Crude Pectin of Krung Kha Mao Leaves （Cissampe/os pareira L.） to Produce Lactic Acid in Longan Juice

L-（＋）-lactic acid production was studied by immobilized Lactobacillus rhamnosus T1STR108 on crude pectin from Krung Kha Mao Leaves. Central composite design was employed to determine the maximum lactic acid production of 42.88 g L-1 in predicted model with the factors at 4.11 g L1 of pectin, 6.05 mLLl inoculum and 1.09 mm of bead diameter. Statistical analyses demonstrated very high significance for the regression model, since the F-value computed 116.09 was much higher than the tabulated F-value 2.08 for the lactic acid production at 5% level for linear and quadratic polynomial regression models. The highest experimental lactic acid production was 43.57 g L^-1 at 96 h of fermentation, 1.58% higher than the predicted value.

Numerical Simulation of Multi-Directional Random Wave Transformation in a Yacht Port

This paper extends a prediction model for multi-directional random wave transformation based on an energy balance equation by Mase with the consideration of wave shoaling, refraction, diffraction, reflection and breaking. This numerical model is improved by 1) introducing Wen's frequency spectrum and Mitsuyasu's directional function, which are more suitable to the coastal area of China; 2) considering energy dissipation caused by bottom friction, which ensures more accurate results for large-scale and shallow water areas; 3) taking into account a non-linear dispersion relation. Predictions using the extended wave model are carried out to study the feasibility of constructing the Ai Hua yacht port in Qingdao, China, with a comparison between two port layouts in design. Wave fields inside the port for different incident wave directions, water levels and return periods are simulated, and then two kinds of parameters are calculated to evaluate the wave conditions for the two layouts. Analyses show that Layout I is better than Layout II. Calculation results also show that the harbor will be calm for different wave directions under the design water level. On the contrary, the wave conditions do not wholly meet the requirements of a yacht port for ship berthing under the extreme water level. For safety consideration, the elevation of the breakwater might need to be properly increased to prevent wave overtopping under such water level. The extended numerical simulation model may provide an effective approach to computing wave heights in a harbor.

Modified molecular matrix model for predicting molecular composition of naphtha＇

To improve the naphtha composition prediction model based on molecular type homologous series matrix （MTHS）, this paper puts forward a novel molecular matrix to characterize the naphtha composition and the norreal distribution hypothesis to better describe the molecular composition distribution within each homologous series of the molecular matrix. Through prediction calculation of eight groups of naphtha samples and eight groups of gasoline samples, it is verified that the normal distribution hypothesis is more applicable than gamma distribution hypothesis for the prediction model. According to the prediction results of the samples, the restrain range of normal distribution parameters during model computing process is summarized. With the bulk properties of naphtha samples and the value range of distribution parameters as input conditions, this study utilizes the improved novel molecular matrix to predict the composition of naphtha samples. As the results show, the novel molecular matrix can predict more detailed composition information of naphtha and improve prediction accuracy with less unknown parameters.

Partially Decentralized Controller Design via Model Predictive Control

An expansion procedure to design partially decentralized controllers via model predictive control is proposed in this paper. Partially decentralized control is a control structure that lies between a fully decentralized structure and a fully centralized one, and has the advantage of achieving comparable performance as a fully centralized controller but with simpler structure. The proposed method follows the expansion method proposed in a previous paper where internal model control (IMC) was used to design controllers for non-square subsystems. The method requires computing the pseudo-inverse of a non-square matrix via pseudo-inverse factors. Instead, the proposed method uses dynamic matrix control (DMC) to design PID controllers for non-square subsystems without using additional factors. The effectiveness of the proposed method is demonstrated on several chemical examples. Simulation results show that the proposed method is simple and can achieve better performance.

Process Optimization of Ultrasonic Extraction of Puerarin Based on Support Vector Machine

In ultrasonic extraction technology, optimization of technical parameters often considers extraction medium only, without including ultrasonic parameters. This paper focuses on controlling the ultrasonic extraction process of puerarin, investigating the influence of ultrasonic parameters on extraction rate, and empirically analyzing the main components of Pueraria, i.e., isoflavone compounds. A method is presented combining orthogonal experi- mental design with a support vector machine and a predictive model is established for optimization of technical parameters. From the analysis with the predictive model, appropriate process parameters are achieved for higher extraction rate. With these parameters in the ultrasonic extraction of puerarin, the experimental result is satisfactory. This method is of significance to the study of extracfing root-stock plant medicines.

Application of cluster analysis to preventive maintenance scheme design of pavement

To quantitatively identify the maintenance demand for each highway segments in the pavement maintenance scheme design,a mathematical model of uniform segment division was established and an approach of applying cluster analysis theory to the uniform segment division and evaluation of pavement maintenance demand was proposed.The actual maintenance project of a highway carried out in Guangdong province was cited as an example to demonstrate the validity of the proposed method.It is proved that the cluster analysis can eliminate human factors in classification without being constrained by the quantities of samples,considering multiple pavement distress indexes and the continuity of samples.Thus it is evident that cluster analysis is an efficient analytical tool in uniform segment division and evaluation of maintenance demand.