Dimensional Synthesis for 3-PRS Mechanism Based on Identifiability Performance

Many performance indices for parallel mechanism are put forward in the phase of dimensional synthesis,except for identifiability index,which determines the difficulty of kinematical calibration.If the dimensional parameters are inappropriately selected,the existing methods for optimizing identifiability will not effectively work.Thus,with the aim of studying identifiability optimization in dimensional synthesis for 3-PRS mechanism,kinematics with structural errors is analyzed to provide theoretical bases for kinematical model.Then through a comparison of two 3-PRS mechanisms with different dimensional parameters,identifiability performance is proved to be necessary and feasible for optimization in the phase of dimensional design.Finally,an index δ is proposed to scale the identifiability performance.With the index,identifiability analysis and dimensional synthesis simulation in the whole workspace is completed.The index is verified to be correct and feasible,and based on the index,a procedure of dimensional synthesis,as well as an example set of non-dimensional parameters of 3-PRS mechanism,is proposed.The proposed identifiability index and design method can effectively introduce identifiability optimization into dimensional synthesis,and will obviously benefit later kinematical calibration.

Parameter Identifiability and Parameter Estimation of a Diesel Engine Combustion Model

In this paper an original method based on the link between a piecewise identifiability analysis and a piecewise numerical estimation is presented for estimating parameters of a phenomenological diesel engine combustion model. This model is used for design, validation and pre-tuning of engine control laws. A cascade algebro-differential elimination method is used for studying identifiability. This investigation is done by using input-output-parameter relationship. Then these relations are transformed by using iterated integration. They are combined with an original numerical derivative estimation based on distribution theory which gives explicit point-wise derivative?estimation formulas for each given order. Then new approximate relations, linking block of parameters and outputs (without derivative) are obtained. These relations are linear relatively to the blocks of parameters and yield a first estimation of parameters which is used as initial guess for a local optimization method (least square method and a local search genetic algorithm).

Identifiability Analysis of Load Model Parameters by Estimating Confidential Intervals

The identification of load model parameters from practical measurement data has become an essential method to build load models for power system simulation,analysis and control.In practical situations,the accuracy of the load model parameters identification results is impacted by data quality and measurement accuracy,which leads to the problem of identifiability.In this paper,an identifiability analysis methodology of load model parameters,by estimating the confidential intervals(CIs)of the parameters,is proposed.The load model structure and the combined optimization and regression method to identify the parameters are first introduced.Then,the definition and analysis method of identifiability are discussed.The CIs of the parameters are estimated through the profile likelihood method,based on which a practical identifiability index(PII)is defined to quantitatively evaluate identifiability.Finally,the effectiveness of the proposed analysis approach is validated by the case study results in a practical provincial power grid.The results show that the impact of various disturbance magnitudes,measurement errors and data length can all be reflected by the proposed PII.Furthermore,the proposed PII can provide guidance in data length selection in practical load model identification situations.

Fitting dynamic models to epidemic outbreaks with quantified uncertainty:A primer for parameter uncertainty,identifiability,and forecasts

Mathematical models provide a quantitative framework with which scientists can assess hypotheses on the potential underlying mechanisms that explain patterns in observed data at different spatial and temporal scales,generate estimates of key kinetic parameters,assess the impact of interventions,optimize the impact of control strategies,and generate forecasts.We review and illustrate a simple data assimilation framework for calibrating mathematical models based on ordinary differential equation models using time series data describing the temporal progression of case counts relating,for instance,to population growth or infectious disease transmission dynamics.In contrast to Bayesian estimation approaches that always raise the question of how to set priors for the parameters,this frequentist approach relies on modeling the error structure in the data.We discuss issues related to parameter identifiability,uncertainty quantification and propagation as well as model performance and forecasts along examples based on phenomenological and mechanistic models parameterized using simulated and real datasets.

Parameter uncertainty and identifiability of a conceptual semi-distributed model to simulate hydrological processes in a small headwater catchment in Northwest China

Introduction:Conceptual hydrological models are useful tools to support catchment water management.However,the identifiability of parameters and structural uncertainties in conceptual rainfall-runoff modeling prove to be a difficult task.Here,we aim to evaluate the performance of a conceptual semi-distributed rainfall-runoff model,HBV-light,with emphasis on parameter identifiability,uncertainty,and model structural validity.Results:The results of a regional sensitivity analysis(RSA)show that most of the model parameters are highly sensitive when runoff signatures or combinations of different objective functions are used.Results based on the generalized likelihood uncertainty estimation(GLUE)method further show that most of the model parameters are well constrained,showing higher parameter identifiability and lower model uncertainty when runoff signatures or combined objective functions are used.Finally,the dynamic identifiability analysis(DYNIA)shows different types of parameter behavior and reveals that model parameters have a higher identifiability in periods where they play a crucial role in representing the predicted runoff.Conclusions:The HBV-light model is generally able to simulate the runoff in the Pailugou catchment with an acceptable accuracy.Model parameter sensitivity is largely dependent upon the objective function used for the model evaluation in the sensitivity analysis.More frequent runoff observations would substantially increase the knowledge on the rainfall-runoff transformation in the catchment and,specifically,improve the distinction of fast surface-near runoff and interflow components in their contribution to the total catchment runoff.Our results highlight the importance of identifying the periods when intensive monitoring is critical for deriving parameter values of reduced uncertainty.

ON IDENTIFIABILITY FOR MULTIDIMENSIONAL ARMAX MODEL

This paper gives a definition of identifiability for multidimensional linear input-output systems and presents a necessary and sufficient condition for its satisfaction.For a class of identifiable systems it is also shown that the unknown coeffcients of the system can consistently be estimated by a recursive algorithm.

Analysis on Genetic Diversity of 40 Flowering Cherry Cultivars and Construction of Molecular ID Based on SSR Markers

Studying on the genetic diversity and genetic relationship of flowering cherry cultivars is extremely important for germplasm conservation, cultivar identification and breeding. Flowering cherry is widely cultivated as an important woody ornamental plant in worldwide, especially Japan, China. However, owning to the morphological similarity, many cultivars are distinguished hardly in non-flowering season. Here, we evaluated the genetic diversity and genetic relationship of 40 flowering cherry cultivars, which are mainly cultivated in China. We selected 13 polymorphicprimers to amplify to allele fragments with fluorescent-labeled capillary electrophoresis technology. The population structure analysis results show that these cultivars could be divided into 4 subpopulations. At the population level, Na and Ne were 6.062, 4.326, respectively. Ho and He were 0.458 and 0.670, respectively. The Shannon’s information index (I) was 1.417. The Pop3, which originated from P. serrulata, had the highest Ho, He, and I among the 4 subpopulations. AMOVA showed that only 4% of genetic variation came from populations, the 39% variation came from individuals and 57% (p < 0.05) came from intra-individuals. 5 polymorphic SSR primers were selected to construct molecular ID code system of these cultivars. This analysis on the genetic diversity and relationship of the 40 flowering cherry cultivars will help to insight into the genetic background, relationship of these flowering cherry cultivars and promote to identify similar cultivars.

Ad Blockers & Online Privacy: A Comparative Analysis of Privacy Enhancing Technologies (PET)

Online tracking mechanisms employed by internet companies for user profiling and targeted advertising raise major privacy concerns. Despite efforts to defend against these mechanisms, they continue to evolve, rendering many existing defences ineffective. This study performs a large-scale measurement of online tracking mechanisms across a large pool of websites using the OpenWPM (Open Web Privacy Measurement) platform. It systematically evaluates the effectiveness of several ad blockers and underlying Privacy Enhancing Technologies (PET) that are primarily used to mitigate different tracking techniques. By quantifying the strengths and limitations of these tools against modern tracking methods, the findings highlight gaps in existing privacy protections. Actionable recommendations are provided to enhance user privacy defences, guide tool developers and inform policymakers on addressing invasive online tracking practices.

Identifiability and Solvability in Inverse Linear Quadratic Optimal Control Problems

In this paper, the inverse linear quadratic(LQ) problem over finite time-horizon is studied.Given the output observations of a dynamic process, the goal is to recover the corresponding LQ cost function. Firstly, by considering the inverse problem as an identification problem, its model structure is shown to be strictly globally identifiable under the assumption of system invertibility. Next, in the noiseless case a necessary and sufficient condition is proposed for the solvability of a positive semidefinite weighting matrix and its unique solution is obtained with two proposed algorithms under the condition of persistent excitation. Furthermore, a residual optimization problem is also formulated to solve a best-fit approximate cost function from sub-optimal observations. Finally, numerical simulations are used to demonstrate the effectiveness of the proposed methods.

Identifiability of intermediate variables on causal paths

We discuss the discovery of causal mechanisms and identifiability of intermediate variables on a causal path. Different from variable selection, we try to distinguish intermediate variables on the causal path from other variables. It is also different from ordinary model selection approaches which do not concern the causal relationships and do not contain unobserved variables. We propose an approach for selecting a causal mechanism depicted by a directed acyclic graph （DAG） with an unobserved variable. We consider several causal networks, and discuss their identifiability by observed data. We show that causal mechanisms of linear structural equation models are not identifiable. Furthermore, we present that causal mechanisms of nonlinear models are identifiable, and we demonstrate the identifiability of causal mechanisms of quadratic equation models. Sensitivity analysis is conducted for the identifiability.

IDentifier DNA分型盒(炎黄34)的法医学验证及应用评估

目的 测试IDentifier DNA分型盒(炎黄34)的技术性能指标,评估其法医学应用价值。方法 根据《法庭科学人类荧光标记STR复合扩增检测试剂质量基本要求》(GB/T 37226—2018),从种属特异性、分型准确性、灵敏度、适应性、耐受性、一致性、均衡性、反应条件验证、混合样本、稳定性、批间差11个方面对IDentifier DNA分型盒(炎黄34)进行测试。比较IDentifier DNA分型盒(炎黄34)与Power Plex~?Fusion 6C系统、Versa Plex~?27PY系统、Veri Filer~(TM) Plus PCR扩增试剂盒的系统效能。使用IDentifier DNA分型盒(炎黄34)检测日常案件中的拭子类生物检材,观察其STR检验结果 。结果 IDentifier DNA分型盒(炎黄34)具有良好的种属特异性、分型准确性、适应性、耐受性和均衡性,灵敏度可达0.062 5 ng,能检测案件中不同类型的检材、降解检材及混有抑制剂的检材,对混合比例为4∶1以内的样本均能获得完整分型。该试剂盒的系统效能非常高,TDP可达1-1.08×10~(-37),CPE_(trio)和CPE_(duo)分别可达1-5.47×10~(-14)和1-6.43×10~(-9)。针对案件中的接触类生物检材,其有效检出率可达21.05%。针对亲缘关系鉴定,单亲鉴定和全同胞鉴定的系统效能均得到了有效提高。结论 IDentifier DNA分型盒(炎黄34)的上述性能指标符合要求,可用于个体识别及亲权鉴定,适合在法庭科学领域应用。

A Novel Method in Wood Identification Based on Anatomical Image Using Hybrid Model

Nowadays,wood identification is made by experts using hand lenses,wood atlases,and field manuals which take a lot of cost and time for the training process.The quantity and species must be strictly set up,and accurate identification of the wood species must be made during exploitation to monitor trade and enforce regulations to stop illegal logging.With the development of science,wood identification should be supported with technology to enhance the perception of fairness of trade.An automatic wood identification system and a dataset of 50 commercial wood species from Asia are established,namely,wood anatomical images collected and used to train for the proposed model.In the convolutional neural network(CNN),the last layers are usually soft-max functions with dense layers.These layers contain the most parameters that affect the speed model.To reduce the number of parameters in the last layers of the CNN model and enhance the accuracy,the structure of the model should be optimized and developed.Therefore,a hybrid of convolutional neural network and random forest model(CNN-RF model)is introduced to wood identification.The accuracy’s hybrid model is more than 98%,and the processing speed is 3 times higher than the CNN model.The highest accuracy is 1.00 in some species,and the lowest is 0.92.These results show the excellent adaptability of the hybrid model in wood identification based on anatomical images.It also facilitates further investigations of wood cells and has implications for wood science.

从城市意象的角度对成都平乐古镇景观意象的解析

1平乐古镇概况平乐古镇位于四川省成都市所辖邛崃市西南部,迄今已有2000多年历史。古镇区存有明清时期的建筑235.4km2,保存完好程度达85%。平乐古镇历史街区主要集中在沿白沫江两岸的核心范围内。平乐古镇景观空间形态分为通道、边界、区域、中心节点、标志物5类(表1)。

乙嘧酚磺酸酯中杂质的GC-MS分析

The structure of bupirimate was identified by using MS and NMR.The structures of 10 impurities were identified by using GC-MS.The method provides a powerful tool for structure analysis special in complex samples.

蓝牙服务搜索的设计与实现

本文介绍蓝牙技术中服务搜索基本功能及其实现 .通过对蓝牙硬拷贝电缆替代课题研究中服务搜索的设计和实现 ,提供了一个在蓝牙环境下的服务搜索的方法和思路 .

数字版权保护中DCI编码方案及数字证书研究

数字版权标志符为数字内容在互联网上提供唯一的版权身份标志,为确保在网络环境中能够精准定位和检索数字作品、确认版权主体提供了技术基础。建立数字版权标志符体系是我国数字版权管理发展的迫切要求。通过研究DCI(数字版权标志符)的概念、设计原则,分析了国外相关研究的现状,提出了适合我国版权保护的DCI编码方案,并给出了应用于移动互联网的加密机制、数字证书及DCI嵌入方案。研究结果表明,采用上述方法,兼容性好,易于与国际上的DOI(digital object identifier)接轨,加密机制及数字证书的设计适合在移动互联网上应用。

Identification of variable coefficients for vibrating systems by boundary control and observation

We consider the identification problem of coefficients for vibrating systems described by a Euler-Bernoulli beam eq~. ation Or a string equation, with one end clamped and with an input exerted on the other end. For the beam equation, the observations are the velocity and the angle velocity at the free end, while for the string equation, the observation is the velocity at the free end. In the framework of well-posed linear system theory, we show that both the density and the flexural rigidity of the beam, and the tension of the string, can be uniquely determined by the observations for all positive times. Moreover, a general constructive method is developed to show that the mass density and the elastic modulus of the string are not determined by the observation.

贵州汉族人群15个STR基因座遗传多态性研究

目的对贵州汉族人群在Identifiler体系中的15个短串连重复序列(STR)基因座进行遗传多态性调查。方法采用荧光标记STR-PCR复合扩增、毛细管电泳基因分型技术,对1 000名贵州汉族人群无关个体进行15个STR基因座的基因分型,计算其等位基因频率、杂合度(H)、匹配概率(PM)、个人识别力(DP)、非父排除率(PE)、多态信息总量(PIC)、父权指数(PI)等多态性参数,并进行统计学分析。结果在贵州汉族人群1 000名无关个体中共检出178个等位基因,其频率分布为0.000 5~0.531 5。15个STR基因座的基因型分布进行χ~2检验符合Hardy-Weinberg平衡定律(P>0.05)。杂合度为0.603 0~0.880 0;个人识别力为0.786 1~0.966 6,累积DP>0.999 999 999;匹配概率为0.033 4~0.213 9,累积PM=1.198×10^(-17);三联体非父排除率为0.294 5~0.754 8,累积CPE=0.999 998 925;二联体非父排除率为0.195 9~0.571 6,累积CPE=0.999 760 600;多态信息含量为0.545 1~0.849 2,累积PIC=0.999 999 999;亲权指数为1.2 594~4.1 667。结论贵州汉族人群检测的15个STR基因座具有高度多态性,是较理想的遗传标记,统计的等位基因频率等基础数据可为本地区的个人识别、三联体亲子鉴定及群体遗传学研究提供依据,但在二联体亲子鉴定中运用存在一定风险。

Office Word文档溯源方法研究

基于最广泛使用的Microsoft Office Word文件结构格式分析,集中关注编辑过程还原主题,立足document.xml与core.xml文件内容,挖掘OOXML格式中独特的RI值变化规则,进而完成文件来源的取证分析,并通过自主研发的软件使得分析工作智能化工具化。电子数据取证实践证明,所述方法准确高效。

教师绩效评估中的评估者目标对评估结果的影响研究

目前,在绩效评估研究中缺乏评估者目标理论的实证研究。本研究在"假设对象"(Paper People)的实验情境下,通过509名大学生被试对教师绩效的评估,探讨了评估者目标对评估结果的影响,并验证了Murphy等人开发的评估者目标问卷的信效度。研究表明:绩效评估中确定不足目标对总体评估结果有负向影响,确定优势目标对总体评估结果有正向影响;确定优势目标越高,总体准确度越低;确定不足目标对区分被评个体有正向影响。