基于Null Importance和Stacking模型的知识追踪研究

为应对基于游戏的学习平台在知识追踪应用方面的不足,本研究利用Field Day Lab提供的教育游戏用户日志进行深入分析。采用方差法和Null Importance方法对数据集进行降维处理,并结合K折交叉验证与LightGBM算法,建立了一个高效的预测模型。此外,通过集成Logistic模型,构建起Stacking模型。研究表明,该模型在验证集上的Macro-F1值显著提升至0.699,同时也在测试集上显示出优异的泛化能力。本研究为教育游戏领域的知识追踪提供了创新方法,并为游戏开发与教育实践提供了宝贵参考,支持教育游戏的开发者为学生创造更有效的学习体验。

Research on a Monte Carlo global variance reduction method based on an automatic importance sampling method

Global variance reduction is a bottleneck in Monte Carlo shielding calculations.The global variance reduction problem requires that the statistical error of the entire space is uniform.This study proposed a grid-AIS method for the global variance reduction problem based on the AIS method,which was implemented in the Monte Carlo program MCShield.The proposed method was validated using the VENUS-Ⅲ international benchmark problem and a self-shielding calculation example.The results from the VENUS-Ⅲ benchmark problem showed that the grid-AIS method achieved a significant reduction in the variance of the statistical errors of the MESH grids,decreasing from 1.08×10^(-2) to 3.84×10^(-3),representing a 64.00% reduction.This demonstrates that the grid-AIS method is effective in addressing global issues.The results of the selfshielding calculation demonstrate that the grid-AIS method produced accurate computational results.Moreover,the grid-AIS method exhibited a computational efficiency approximately one order of magnitude higher than that of the AIS method and approximately two orders of magnitude higher than that of the conventional Monte Carlo method.

Development of endemicity and conservation importance indices for tropical forests and the floral diversity assessment of Mt.Natoo in Benguet,Philippines

The scientific community faces the challenge of measuring progress toward biodiversity targets and indices have been traditionally used.However,recent inventories in secondary tropical mountain forests using traditional biodiversity indices have yielded results that are indistinct with primary ones.This shows the need to develop complementary indices that goes beyond species count but integrates the distribution and conservation status of the species.This study developed endemicity and conservation importance index for tropical forest that incorporated the distribution and conservation status of the species.These indices were applied to Mt.Natoo,a remnant primary mossy forest in Buguias,Benguet,Philippines,that resulted to endemicity index of 81.07 and conservation importance index of 42.90.Comparing these with secondary forest sites with comparable Shannon-Wiener,Simpson,Evenness and Margalef’s indices,our endemicity and conservation indices clearly differentiates primary forest(our study site)with higher values from secondary forests with much lower values.Thus,we are proposing these indices for a direct but scientifically-informed identification of specific sites for conservation and protection in tropical forests.Additionally,our study documented a total of 168 vascular plant species(79 endemic and 12 locally threatened species)in Mt.Nato-o.Majority are of tropical elements for both generic and species levels with some temperate elements that could be attributed to the site's high elevation and semi-temperate climate.These are important baseline information for conservation plans and monitoring of tropical mossy forests.

The Importance of Breathing Training in Folk Dance Teaching

The importance of breathing training in dance teaching is reflected in the two aspects of enhancing the quality of dance movements and sublimating the connotation of dance movements.For example,high-quality breathing can help performers complete the dance movements and improve the coordination of the movements;at the same time,the unique body rhythm formed by breathing can strengthen the visual effect of the performance and convey its spirit and soul to the audience.This requires folk dance teachers to carry out relevant training and teaching activities based on the categories and skills of dance breathing,such as changing students’ideological cognition,developing periodic breathing training courses,providing personalized guidance to students,and allowing students to adjust their learning and practice methods in the evaluation.

Active Kriging-Based Adaptive Importance Sampling for Reliability and Sensitivity Analyses of Stator Blade Regulator

The reliability and sensitivity analyses of stator blade regulator usually involve complex characteristics like highnonlinearity,multi-failure regions,and small failure probability,which brings in unacceptable computing efficiency and accuracy of the current analysismethods.In this case,by fitting the implicit limit state function(LSF)with active Kriging(AK)model and reducing candidate sample poolwith adaptive importance sampling(AIS),a novel AK-AIS method is proposed.Herein,theAKmodel andMarkov chainMonte Carlo(MCMC)are first established to identify the most probable failure region(s)(MPFRs),and the adaptive kernel density estimation(AKDE)importance sampling function is constructed to select the candidate samples.With the best samples sequentially attained in the reduced candidate samples and employed to update the Kriging-fitted LSF,the failure probability and sensitivity indices are acquired at a lower cost.The proposed method is verified by twomulti-failure numerical examples,and then applied to the reliability and sensitivity analyses of a typical stator blade regulator.Withmethods comparison,the proposed AK-AIS is proven to hold the computing advantages on accuracy and efficiency in complex reliability and sensitivity analysis problems.

基于Null Importance与GS-LGBM的糖尿病视网膜病变因素分析与风险预测

目的:通过机器学习算法分析糖尿病视网膜病变(DR)关键因素,构建DR风险预测模型,为DR的预防和诊断提供参考。方法:采用国家人口健康科学数据中心的《糖尿病并发症预警数据集》,基于Null Importance方法去除噪声特征,筛选出与DR有关的关键因素;基于GridSearch优化LGBM模型参数,构建GS-LGBM DR风险预测模型。以准确率、精确率、召回率、F1分数、AUC值作为评价标准,与XGBoost、随机森林、Logistic以及未调优的LGBM模型进行比较。结果:Null Importance方法筛选出30个关键因素;与XGBoost、随机森林、Logistic以及未调优的LGBM模型相比,本研究所构建的GS-LGBM DR风险预测模型各评价指标均最优,其在测试数据上的AUC值高达0.897。结论:相较传统的DR预测模型,经过超参数优化后的模型具有更好的DR风险预测能力,更有助于DR的临床诊断。

A Two-Step Algorithm to Estimate Variable Importance for Multi-State Data:An Application to COVID-19

Survival data with amulti-state structure are frequently observed in follow-up studies.An analytic approach based on a multi-state model(MSM)should be used in longitudinal health studies in which a patient experiences a sequence of clinical progression events.One main objective in the MSM framework is variable selection,where attempts are made to identify the risk factors associated with the transition hazard rates or probabilities of disease progression.The usual variable selection methods,including stepwise and penalized methods,do not provide information about the importance of variables.In this context,we present a two-step algorithm to evaluate the importance of variables formulti-state data.Three differentmachine learning approaches(randomforest,gradient boosting,and neural network)as themost widely usedmethods are considered to estimate the variable importance in order to identify the factors affecting disease progression and rank these factors according to their importance.The performance of our proposed methods is validated by simulation and applied to the COVID-19 data set.The results revealed that the proposed two-stage method has promising performance for estimating variable importance.

Importance of Urban Wetland Parks under the Development of Green Healthy Cities:A Case Study of Nanjing City

Wetlands are widely distributed all over the world,and have many wildlife resources,which are the main pieces of the puzzle for natural resource conservation and sustainable development on earth and have important irreplaceability.In this paper,through questionnaire survey,field research,literature review,etc.,importance weight analysis was conducted by using principal component analysis,and field survey and questionnaire were carried out to collect data on ecological environment function,environmental protection function,landscape beautification function,disaster prevention and mitigation function of urban wetlands.The problems in wetland parks of Nanjing were discussed,such as lack of awareness of landscape planning,deficient late management of wetland parks,weak ability of sustainable development,and unreasonable landscape layout and function.Finally,corresponding solutions were proposed,such as adhering to the planning and design of urban wetland parks with green as the base and health as the basis,persisting in the construction of a wetland system with high biodiversity and near-natural characteristics,adhering to the principle of sustainable development,adopting the construction idea of symbiosis and circulation of urban wetland parks,strengthening education and publicity work,and paying attention to the organic combination of system protection and coordinated construction.The research can build a new development direction for the model of urban wetland parks and green healthy cities,and provide theoretical support for urban sustainable construction.

A Neighborhood Rough Set Attribute Reduction Method Based on Attribute Importance

Attribute reduction is a hot topic in rough set research. As an extension of rough sets, neighborhood rough sets can effectively solve the problem of information loss after data discretization. However, traditional greedy-based neighborhood rough set attribute reduction algorithms have a high computational complexity and long processing time. In this paper, a novel attribute reduction algorithm based on attribute importance is proposed. By using conditional information, the attribute reduction problem in neighborhood rough sets is discussed, and the importance of attributes is measured by conditional information gain. The algorithm iteratively removes the attribute with the lowest importance, thus achieving the goal of attribute reduction. Six groups of UCI datasets are selected, and the proposed algorithm SAR is compared with L2-ELM, LapTELM, CTSVM, and TBSVM classifiers. The results demonstrate that SAR can effectively improve the time consumption and accuracy issues in attribute reduction.

Face tracking algorithm based on particle filter with mean shift importance sampling

The condensation tracking algorithm uses a prior transition probability as the proposal distribution, which does not make full use of the current observation. In order to overcome this shortcoming, a new face tracking algorithm based on particle filter with mean shift importance sampling is proposed. First, the coarse location of the face target is attained by the efficient mean shift tracker, and then the result is used to construct the proposal distribution for particle propagation. Because the particles obtained with this method can cluster around the true state region, particle efficiency is improved greatly. The experimental results show that the performance of the proposed algorithm is better than that of the standard condensation tracking algorithm.

Thorium and Its Future Importance for Nuclear Energy Generation

Thorium was discovered in 1828 by the Swedish chemist Jons J. Berzelius. Despite some advantages over uranium for use in nuclear reactors, its main use, in the almost two centuries since its discovery, thorium was restricted to use for gas mantles, especially in the early 20th century. In the beginning of the nuclear era, many countries had interested on thorium, particularly during the 1950-1970 period. There are about 435 nuclear reactors in the world nowadays. They need more than 65,000 tons of uranium yearly. The future world energy needs will increase and, even if we assumed a conservative contribution of nuclear generation, there will be a significant increasing in the uranium prices occur, taking into account that uranium, as used in the present thermal reactors, is a finite resource. Thorium is nearly three times more abundant than uranium in the Earth＇s crust. Despite thorium is not a fissile material, ^232Th can be converted to ^233U （fissile） more efficiently than ^238U to ^239pu. Besides this, since it is possible to convert thorium waste into non-radioactive elements, thorium is an environment-friendly alternative energy source. Thorium fuel cycle is also inherently resistant to proliferation. Some papers evaluate the thorium resources in Brazil over 1,200,000 metric t. Then, the thorium alternative must be seriously considered in Brazil for strategic reasons. In this paper a brief history of thorium is presented, besides a review of the world thorium utilization and a discussion about advantages and restrictions of thorium use.

Dynamic Importance Analysis of Machining Center

As an important part of CNC machine tools,machining center’s reliability,efficiency and accuracy measure the machining level of a CNC machine tool.Therefore,the research on the importance of CNC machine tools is particularly important.However,as a complex mechanical and electrical equipment,the traditional reliability importance analysis method is too simple.In order to solve this problem,this passage proposes to establish the reliability model of each part of the machining center,and then analyze its dynamic importance,which improves the limitation of only reliability importance analysis.Through the analysis the reliability importance and criticality importance,and then rank the result of importance analysis,finally it can get that the ranking results of the key components accord with the fact,so the results can provide support for the importance research of machining center.

Dandyism in Oscar Wilde's The Importance of Being Earnest

In The Importance of Being Earnest,Oscar Wilde constructs a dandies’world,in which the persons mock at everything and subvert everything.This research analyzes the dandyish features of the character with the aid of Charles Baudelaire’s definition of dandy and dandyism,and studies Wilde’s subversion of the preexistent binary oppositions by referring to Jonathan Culler’s interpretation of Jacque Derrida’s deconstruction,and points out that Wilde’s writing in Earnest is a deconstructionist writing.He abandons all the so-called essential matters and only focuses on linguistic surface and comic effect.His stance of dandyism challenges the main-stream social norms at his time and foresees the coming artistic trend.

Resilience based importance measure analysis for SoS

In a system of systems(SoS),resilience is an important factor in maintaining the functionality,stability,and enhancing the operation effectiveness.From the perspective of resilience,this paper studies the importance of the SoS,and a resilience-based importance measure analysis is conducted to provide suggestions in the design and optimization of the structure of the SoS.In this paper,the components of the SoS are simplified as four kinds of network nodes:sensor,decision point,influencer,and target.In this networked SoS,the number of operation loops is used as the performance indicator,and an approximate algorithm,which is based on eigenvalue of the adjacency matrix,is proposed to calculate the number of operation loops.In order to understand the performance change of the SoS during the attack and defense process in the operations,an integral resilience model is proposed to depict the resilience of the SoS.From different perspectives of enhancing the resilience,different measures,parameters and the corresponding algorithms for the resilience importance of components are proposed.Finally,a case study on an SoS is conducted to verify the validity of the network modelling and the resiliencebased importance analysis method.

Accumulation of Organic Matter in Infertile Red Soils and Its Ecological Importance

Field experiments on the decomposition of organic materials and the accumulation of organic carbon ininfertile red soils were conducted at the Ecological Experimental Station of Red Soil, the Chinese Academyof Sciences, and the potential of CO2 sequestration by reclamation and improving the fertility of these soils was estimated. Results showed that in infertile red soils, the humification coefficients of organic materials were rather high, ranging from 0.28 to 0.63 with an average of 0.43, which was 41% higher than those incorresponding red soils with medium fertility. This was mainly attributed to the high clay content, highacidity and low native organic matter content of infertile red soils. Compared to those in correspondingnormal red soils, the decomposition rates of organic materials were significantly lower in infertile red soilsin the first 2 yearst thereafter no significant difference was observed between those in the two kinds of soils.Depending on the kind and amount of organic manure applied, the soil properties and the rotation systems,annual application of organic manure with a rate of 4500 to 9000 kg ha-1 increased the organic carboncontent in surface 20 cm of infertile red soils by 2.1~7.5 g kg-1 with an average of 4.7 g kg-1 within the first5 years. The organic carbon content in infertile red soils which received organic manure annually increasedlinearly in the first 10 years, thereafter it slowed down, implying that the fertility of the infertile red soilscould reach middle or high level in 1O years if the soil was managed properly It was estimated that throughexploitation of wastelands, re-establishment of fuel forests and improvement of soil fertility, soils in red soilregion of China could sequester an extra 1.50 × 1015 g of atmospheric CO2.

Concepts of keystone species and species importance in ecology

This paper discussed the keystone species concept and introduced the typical characteristics of keystone species and their identification in communities or ecosystems. Based on the research of the keystone species, the concept of species importance (SI) was first advanced in this paper. The species importance can be simply understood as the important value of species in the ecosystem, which consists of three indexes: species structural important value (SIV), functional important value (FIV) and dynamical important value (DIV). With the indexes, the evaluation was also made on species importance of arbor trees in the Three-Hardwood forests (Fraxinus mandshurica, Juglans mandshurica, and Phellodendron amurense) ecosystem.

Phytochemical overview and medicinal importance of Coffea species from the past until now

Coffea(coffee) species are grown in almost all countries along the Equator. Many members of the genus have a large production history and an important role both in the global market and researches. Seeds(Coffeae semen) are successfully used in food, cosmetic, and pharmaceutical industries due to its caffeine and high polyphenol content. Nowadays, the three best-known coffee species are Arabic(Coffea arabica L.), Robusta(Coffea robusta L. Linden), and Liberian coffees(Coffea liberica Hier.). Even though, many records are available on coffee in scientific literature, wild coffee species like Bengal coffee(Coffea benghalensis Roxb. Ex Schult.) could offer many new opportunities and challenges for phytochemical and medical studies. In this comprehensive summary, we focused on the ethnomedicinal, phytochemical, and medical significance of coffee species up to the present.

Particle filter with importance density function generated by updated system equation

The current measurement was exploited in a more efficient way. Firstly, the system equation was updated by introducing a correction term, which depends on the current measurement and can be obtained by running a suboptimal filter. Then, a new importance density function(IDF) was defined by the updated system equation. Particles drawn from the new IDF are more likely to be in the significant region of state space and the estimation accuracy can be improved. By using different suboptimal filter, different particle filters(PFs) can be developed in this framework. Extensions of this idea were also proposed by iteratively updating the system equation using particle filter itself, resulting in the iterated particle filter. Simulation results demonstrate the effectiveness of the proposed IDF.

Importance Sampling Method in V-Space

Based on the observation of importance sampling and second order information about the failure surface of a structure, an importance sampling region is defined in V-space which is obtained by rotating a U-space at the point of maximum likelihood. The sampling region is a hyper-ellipsoid that consists of the sampling ellipse on each plane of main curvature in V-space. Thus, the sampling probability density function can be constructed by the sampling region center and ellipsoid axes. Several examples have shown the efficiency and generality of this method.

Importance measure of system reliability upgrade for multi-state consecutive k-out-of-n systems

Importance measures in reliability systems are used to identify weak components in contributing to a proper function of the system. Traditional importance measures mainly concerned the changing value of the system reliability caused by the change of the reliability of the component, and seldom considered the joint effect of the probability distribution, improvement rate of the object component. This paper studies the rate of the system reliability upgrading with an improvement of the component reliability for the multi-state consecutive k-out-of-n system. To verify the multi-state consecutive k-out-of-n system reliability upgrading by improving one component based on its improvement rate, an increasing potential importance （IPI） and its physical meaning are described at first. Secondly, the relationship between the IPI and Birnbaum importance measures are discussed. And the IPI for some different improvement actions of the component is further discussed. Thirdly, the characteristics of the IPI are analyzed. Finally, an application to an oil pipeline system is given.