基于双导联ECG和多变量回归模型的远程心电诊断算法研究

目的研究适于远程心电诊断、高精度的心电信号 (ECG)直接分类方法 ,以克服接收端因信号重建而延误时间的问题。方法收集MIT BIHdatabase中正常窦性心律 (NSR)、心房早期收缩 (APC)、心室早期收缩 (PVC)、心室性心动过速 (VT)、心室纤维性颤动 (VF)和室上性心动过速 (SVT)各 30 0例进行分类研究。提出一种融合双导联ECG信号的多变量回归 (MAR)模型对心电信号直接进行分类 ,包括 :心电数据的MAR建模 ,利用MAR模型系数及其K L变换系数实施非线性二次判别函数 (QDF)法分类。结果文中方法快捷方便 ,分别获得了 98.3%至 1 0 0 %的分类精度。结论MAR建模法特别适合于远程心电诊断 。

循环流化床床温的多变量建模

针对循环流化床锅炉床温对象,分析一次风对其的影响,提出了一种逆向响应模型结构,结合给煤量对床温的影响,建立了包含惯性权重因子的两入一出多变量模型。对现场历史数据的筛选和预处理,采用粒子群优化算法辨识多模型结构中的待定参数及惯性权重因子,并通过另外三段不同负荷段的历史数据完成模型验证。最后将多变量模型和单结构模型进行对比,多变量模型精度更高,适用性更广,为实现循环流化床锅炉床温的优化控制奠定了基础。

基于现场数据和主元分析的主汽温系统多变量建模

针对主汽温系统具有的多变量、强耦合的特点,采集大量现场运行数据,利用主元分析原理,从影响主汽温的11个过程变量中提取5个主要变量,作为模型输入,同时,将机理建模、试验建模和智能优化算法建模相结合,利用现场数据建立主汽温系统多入单出的多变量模型,解决了在生产现场不允许或没有条件进行大范围频繁阶跃扰动试验的问题,克服了多变量智能寻优时,初始值范围和模型结构不确定的困难,建立出可以用于主汽温系统控制研究的多变量模型。

焙烧烟气负压的多变量解耦控制

阳极焙烧烟气负压是一个多变量耦合的控制对象,为实现其精确控制,依据现场实际测得的负压数据,辨识出烟气负压的控制模型,以此模型为初始预测模型,提出了一种多变量预测函数解耦控制算法,对焙烧9个烟道烟气负压进行多变量预测函数解耦控制仿真和实际应用,并与原有PID控制进行了试验比较,表明这种控制方法的控制精度和鲁棒性优于原有的PID控制方法,具有很好的控制效果。

灰色多变量GM(1,N)幂模型及其应用

针对多变量少数据的系统建模问题,提出了灰色多变量GM(1,N)幂模型及其派生模型GM(1,N,x(1))幂模型,给出了其参数估计算式和近似时间响应式,在此基础上,分两种情况讨论了模型的参数优化方法,并通过数值模拟和应用实例验证了新模型的有效性.结果表明:传统的GM(1,N)模型是GM(1,N)幂模型的特殊形式,GM(1,N)幂模型能够更好地描述系统特征行为序列与其影响因素序列的非线性关系,从而有效地提高传统灰色多变量系统建模的精度.

胆管闭锁:755例肝移植患儿的临床特点、危险因素以及预后情况

Objectives: To test the hypothesis that risk analysis from the time of listing for liver transplantation (LT) focuses attention on areas where outcomes can be improved. Study design: Competing outcomes and multivariate models were used to determine significant risk factors for pretransplantation and posttransplantati on mortality and graft failure in patients with biliary atresia (BA) listed for LT and enrolled in the Studies of Pediatric Liver Transplantation (SPLIT) regist ry. Results: Of 755 patients, most were infants (age < 1 year). Significant wait ing list mortality risk factors included infancy and pediatric end-stage liver disease (PELD) score ≥20, whose components were also continuous risk factors. S urvival posttransplantation (n = 567) was 88%at 3 years. Most deaths were from infection (37%). Posttransplantation mortality risk factors included infant rec ipients, height/weight < -2 standard deviations (SD), use of cyclosporine versu s tacrolimus and retransplantation. Graft failure risks included height/weight < -2 SD, cadaveric partial donors,donor age ≤5 months, use of cyclosporine vers us tacrolimus, and rejection. Conclusions: Referral for LT should be anticipator y for infants with BA with failed portoenterostomies. Failing nutrition should p rompt aggressive support. Post-LT risk factors are mainly nonsurgical, includin g nutrition, the relative risk of infection over rejection, and the choice of im munosuppression.

Multivariable Fuzzy Predictive Control Based on the Modified CPN Model

Through modifying the CPN model, a kind of multivariable fuzzy model is put forward, and the matching fuzzy multistep predictive control algorithm is deduced based on the model. The modified model works in a competitive output manner which results in its local representation property. While studying on line, only a few parameters need to be regulated. So the model has the merits of fast learning and on line self organizing modeling. The control algorithm is simple, adaptive and useful in multivariable and time delay systems. Applying the algorithm in a paper making system, simulation shows its good effect.

Differences in the predictive value of red cell distribution width for the mortality of patients with heart failure due to various heart diseases

Background Increased red blood cell distribution width （RDW） is associated with adverse outcomes in patients with heart failure （HF）. The objective of this study was to compare the differences in the predictive value of RDW in patients with HF due to different causes. Methods We retrospectively investigated 1,021 HF patients from October 2009 to December 2011 at Fuwai Hospital （Beijing, China）. HF in these patients was caused by three diseases; coronary heart disease （CHD）, dilated cardiomyopathy （DCM） and valvular heart disease （VHD）. Patients were followed-up for 21 ~ 9 months. Results The RDW, mortality and survival duration were significantly different among the three groups. Kaplan-Meier analysis showed that the cumulative survival decreased significantly with increased RDW in patients with HF caused by CHD and DCM, but not in those with HF patients caused by VHD. In a multivariable model, RDW was identified as an independent predictor for the mortality of HF patients with CHD （P 〈 0.001, HR 1.315, 95% CI 1.122-1.543）. The group with higher N-terminal pro-brain natriuretic peptide （NT-proBNP） and higher RDW than median had the lowest cumulative survival in patients with HF due to CHD, but not in patients with HF due to DCM. Conclusions RDW is a prognostic indicator for patients with HF caused by CHD and DCM; thus, RDW adds important information to NT-proBNP in CHD caused HF patients.

Development of a multivariate empirical model for predicting weak rock mass modulus

Estimating weak rock mass modulus has historically proven difficult although this mechanical property is an important input to many types of geotechnical analyses. An empirical database of weak rock mass modulus with associated detailed geotechnical parameters was assembled from plate loading tests per- formed at underground mines in Nevada, the Bakhtiary Dam project, and Portugues Dam project. The database was used to assess the accuracy of published single-variate models and to develop a multivari- ate model for predicting in-situ weak rock mass modulus when limited geoteehnical data are available. Only two of the published models were adequate for predicting modulus of weak rock masses over lim- ited ranges of alteration intensities, and none of the models provided good estimates of modulus over a range of geotechnical properties. In light of this shortcoming, a multivariate model was developed from the weak rock mass modulus dataset, and the new model is exponential in form and has the following independent variables： （1） average block size or joint spacing, （2） field estimated rock strength, （3） dis- continuity roughness, and （4） discontinuity infilling hardness. The multivariate model provided better estimates of modulus for both hard-blocky rock masses and intensely-altered rock masses.

Patient and physician perception of natural orifice transluminal endoscopic appendectomy

AIM:To investigate perception of natural orifice transluminal endoscopic surgery(NOTES)as a potential technique for appendectomy.METHODS:One hundred patients undergoing endoscopy and 100 physicians were given a questionnaire describing in detail the techniques of NOTES and laparoscopic appendectomy.They were asked about the reasons for their preference,choice of orifice,and extent of complication risk they were willing to accept.RESULTS:Fifty patients(50%)and only 21 physicians(21%)preferred NOTES(P<0.001).Patients had previously heard of NOTES less frequently(7%vs73%,P<0.001)and had undergone endoscopy more frequently(88%vs 36%,P<0.001)than physicians.Absence of hernia was the most common reason for NOTES preference in physicians(80%vs 44%,P= 0.003),whereas reduced pain was the most common reason in patients(66%vs 52%).Physicians were more likely to refuse NOTES as a novel and unsure technique(P<0.001)and having an increased risk of infection(P<0.001).The preferred access site in both groups was colon followed by stomach,with vagina being rarely preferred.In multivariable modeling,those with high-school education[odds ratio(OR):2.68,95% confidence interval(CI):1.23-5.83]and prior colonoscopy(OR:2.10,95%CI:1.05-4.19)were more likely to prefer NOTES over laparoscopic appendectomy.There was a steep decline in NOTES preference with increased rate of procedural complications.Male patients were more likely to consent to their wives vaginal NOTES appendectomy than male physicians(P=0.02).CONCLUSION:The preference of NOTES for appendectomy was greater in patients than physicians and was related to reduced pain and absence of hernia rather than lack of scarring.

英语与格交替原型使用特征的多变量统计建模

本文以构式变体模型理论为视角,基于大规模语料库标注数据,采取多重对应分析法,对英语与格交替原型使用特征进行多变量统计和可视化分析。研究发现:英语与格交替构式变体虽然语义相近,但其原型使用特征存在明显差异。具体而言,双宾构式的原型使用特征为:与事为代词、表征已知信息、有生事物、有定事物、句法较简单;受事为非代词、表征未知信息、无定事物、抽象事物、句法较复杂且长度长于与事。介词与格构式的原型使用特征为:受事为代词、表征已知信息、有定事物、具体事物、句法较简单;与事为非代词、表征未知信息、无定事物、句法较复杂且长度长于受事。

Prediction of rock mass rating using fuzzy logic and multi-variable RMR regression model

Rock mass rating system （RMR） is based on the six parameters which was defined by Bieniawski （1989） [1]. Experts frequently relate joint and discontinuities and ground water conditions in linguistic terms with rough calculation. As a result, there is a sharp transition between two modules which create doubts. So, in this paper the proposed weights technique was applied for linguistic criteria. Then by using the fuzzy inference system and the multi-variable regression analysis, the accurate RMR is predicted. Before the performing of regression analysis, sensitivity analysis was applied for each of Bieniawski parameters. In this process, the best function was selected among linear, logarithmic, exponential and inverse func- tions and finally it was applied in the regression analysis for construction of a predictive equation. From the constructed regression equation the relative importance of the input parameters can also be observed. It should be noted that joint condition was identified as the most important effective parameter upon RMR. Finally, fuzzy and regression models were validated with the test datasets and it was found that the fuzzy model predicts more accurately RMR than reression models.

MPC of distillation column with side reactors for methyl acetate

This paper focuses on the dynamic control of distillation column with side reactors(SRC) for methyl acetate production. To obtain the optimum integrated structure and steady state simulation, the systematic design approach based on the concept of independent reaction amount is applied to the process of SRC for methyl acetate production. In addition to the basic control loops, multi-variable model predictive control modular with methyl acetate concentration and temperature of sensitive plate is designed. Then, based on process simulation software Aspen Plus, dynamic simulation of SRC for methyl acetate production is used to verify the effectiveness of the control scheme.

Analysis of Soil Water Dynamics in a Tropical Rain Forest Soil （Arinic lixisol）, Abeokuta, Nigeria

Soil water dynamics in the dominant lwo soil series （Arinic lixisol） were evaluated at the Federal University of Agriculture, Alabata, Abeokuta, Nigeria. Field capacity, infiltration and water retention characteristics were evaluated in situ for a period of 161 d in the dry season for two root zone depths. Results show that the Iwo soil series has a field capacity ranging from 2.6%-5.5% at 0-45 cm and 45-90 cm root zone depths, respectively. The soil is quick draining with high infiltration rate and very poor water retention capacity confirming that the soil will require a short irrigation interval of about 2-3 d since available water for plant growth in predominantly sandy soils ranges between 2%-8%. Based on the foregoing, sprinkler irrigation is best suited for the lwo soil series, it should, however, be noted that the water application rate must be less than the infiltration rate of the soil in order to prevent surface ponding and runoff. A multivariate model relating soil moisture content with soil moisture tension and soil temperature calibrated within the study had very low model accuracy of 56% and 45% for the two root zone depths, respectively, implying the need for further studies.

Social demographic factors and leisure time physical activity influencing the self-rated health and happiness of Chinese people

Background and aims:The holistic definition of health is not merely the absence of disease or infirmity,but a state of complete physical,mental,and social well-being.However,related research on the influencing factor of self-rated health and happiness have generally remained separate.Therefore,this study aimed to 1)find individual level determinants of the two facets of health;and 2)investigate the covariance of the two facets of health within individual levels.Methods:Multivariate multilevel analysis of self-rated health and happiness at level 1,were nested within 10,968 people at level 2.Data were obtained from the 2015 Chinese General Social Survey.Results:Lower happiness and self-rated health were found in 1)females;2)the elderly;3)people with a lower educational level;4)people who were presently single;5)people with a lower self-rated economic status;6)people who resided in urban areas;and 7)people with sedentary lifestyles as compared to those in other categories of the same variable.After adjusting the related individual level determinants,the correlation coefficient of two facets of health at the individual level is 0.19,which indicates that no robust covariance was observed.Conclusions:The current study indicates the existence of disparity in the subjective physical and psychological dimensions of health among the elderly in China.Our findings emphasize the importance of paying attention to different aspects of health simultaneously in investigations and the benefits of leisure time activities.

Probability modeling for robustness of multivariate LQG designing based on ship lateral motion

The robustness of LQG designing for latitudinal movement of ship is mainly discussed, when its hydrodynamic parameters fluctuate around criterion value at random on the proportional distributing. When a given ship state at the speed of 18 kn and the course of 45° under Rank 5 state of sea, and the hydrodynamic parameters of the ship fluctuate at random on the proportional distributing with a range of ± 10% , ± 20% , ± 30% , the robustness of muhivariate LQG designing for ship is analyzed with applying the probability modeling of relative controlling effect, The result of simulating shows that when the hydrodynamic parameters of ship fluctuates the relative controlling effect of the LQG designing submit to normal distribution and the mean value of relative controlling effect has no remarkable changes comparing to that without perturbation of hydrodynamic parameter,

A special hierarchical fuzzy neural-networks based reinforcement learning for multi-variables system

Proposes a reinforcement learning scheme based on a special Hierarchical Fuzzy Neural-Networks (HFNN)for solving complicated learning tasks in a continuous multi-variables environment. The output of the previous layer in the HFNN is no longer used as if-part of the next layer, but used only in then-part. Thus it can deal with the difficulty when the output of the previous layer is meaningless or its meaning is uncertain. The proposed HFNN has a minimal number of fuzzy rules and can successfully solve the problem of rules combination explosion and decrease the quantity of computation and memory requirement. In the learning process, two HFNN with the same structure perform fuzzy action composition and evaluation function approximation simultaneously where the parameters of neural-networks are tuned and updated on line by using gradient descent algorithm. The reinforcement learning method is proved to be correct and feasible by simulation of a double inverted pendulum system.

Linear Transformation Theory of Quantum Field Operators and Its Applications

We extend the linear quantum transformation theory to the case of quantum field operators. The corresponding general transformation expressions of CPT transformations and gauge field transformations are considered as its applications.

Conceptual Modelling and Data Based Techniques to Understand Urban Water Use and Wastewater Production

A systems approach is used to describe the generation and variation of wastewater in an urban area. This is a multivariable system and its combined response at the outlet of this system, which is usually the entrance ofa wastewater treatment plant, depends on a number of environmental （precipitation and temperature） as well as social （size of the urban area, population changes, water consumption per capita） variables. There is a large number of available models and tools for describing the urban water system, however, the interactions between the individual components are rarely considered within the same modelling framework. In this paper a parsimonious methodology is proposed in order to understand and estimate the wastewater generation and its characteristics in an urban area using any information provided by the available data. The model incorporates both the flows of stormwater discharge and wastewater production that arrive to the wastewater treatment plant. A state dependent variable is introduced to simulate the consumptive uses in the urban area. Data availability and system＇s complexity affect the ability to achieve enhanced model performance, however, in the presented case study, preliminary results from the application of the presented model in the Greater Athens Area illustrate the potential of the conceptual modelling approach.

Variable Rate Technology and Cotton Yield Response in Texas

Variable Rate Technology （VRT） takes within-field variability into consideration and aims to match resource application to crop requirement. Even though Texas is the most important cotton producing state in the US, the rate of VRT adoption is very low here. Hence, analyzing the factors influencing the adoption and providing a regional estimate of the impact of VRT adoption on cotton yield is very important. This study used the 2009 Southern Cotton Precision Farming Survey to analyze the farm and farmer characteristics affecting the adoption of VRT among Texas cotton farmers and to empirically estimate the impact of adoption of VRT on cotton yield in Texas. A two-stage least square procedure with a logistic regression model in the first stage and a multiple linear regression model in the second stage was used to analyze the data. The study revealed that there are significant regional differences in adoption pattern within the state of Texas; and the farmers from the coastal region, where there is higher within-field variability, were more likely to adopt VRT compared to other regions. Younger farmers, farmers managing larger farms, and farmers who use computers for farming operations were more likely to adopt VRT. The results also showed that, on an average, the adoption of VRT does not lead to significant yield improvements for cotton in Texas. Since the impact of VRT adoption on yield is not significant, the source of economic advantage of VRT adoption in Texas may be the reduction of input cost.