Trust model based on individual experience

To improve the accuracy of node trust evaluation in a distributed network, a trust model based on the experience of individuals is proposed, which establishes a new trust assessment system by introducing the experience factor and the comparative experience factor. The new evaluation system considers the differences between individuals and interactive histories between nodes, which solves the problem that nodes have inaccurate assessments due to the asymmetry of nodes to a certain extent. The algorithm analysis indicates that the new model uses different deviating values of tolerance evaluation for different individuals and uses different updating values embodying node individuation when updating feedback credibility of individuals, which evaluates the trust value more reasonably and more accurately. In addition, the proposed algorithm can be used in various trust models and has a good scalability.

Modeling and simulation for individualized therapy of amisulpride in Chinese patients with schizophrenia:focus on inter interindi⁃vidual variability,therapeutic reference range and laboratory alert level

OBJECTIVE To explain the high inter-individual variability and the frequency of exceeding the therapeutic reference range and the laboratory alert level of amisulpride,a popula⁃tion pharmacokinetic model in Chinese patients with schizophrenia was built based on therapeu⁃tic drug monitoring data to guide individualized therapy.METHODS Plasma concentration data(330 measurements from 121 patients)were ana⁃lyzed using a nonlinear mixed-effects model⁃ing approach with first-order conditional estima⁃tion with interaction(FOCE I).The concentra⁃tions of amisulpride were detected by HPLC-MS/MS.Age,weight,sex,combination medication history and renal function status were evaluated as main covariates.The model was internally val⁃idated using goodness-of-fit,bootstrap and nor⁃malized prediction distribution error.Recom⁃mended dosage regimens for patients with key covariates were estimated on the basis of Monte Carlo simulations and the established model.RESULTS A one-compartment model with first-order absorption and elimination was found to adequately characterize amisulpride concentra⁃tion in Chinese patients with schizophrenia.The population estimates of the apparent volume of distribution(V/F)and apparent clearance(CL/F)were 12.7 L and 1.12 L·h-1,respectively.Age sig⁃nificantly affected the clearance of amisulpride and the final model was as follow:CL/F=1.04×(AGE/32)-0.624(L·h-1).To avoid exceeding the lab⁃oratory alert level(640μg·L-1),the model-based simulation results showed that the recommended dose of amisulpride was no more than 600 mg per day for patients aged 60 years,800 mg per day for those aged 40 years and 1200 mg per day for those aged 20 years,respectively.CON⁃CLUSION Dosage optimization of amisulpride can be carried out according to age to reduce the risk of adverse reactions.The model can be used as a suitable tool for designing individual⁃ized therapy for Chinese patients with schizo⁃phrenia.

Modeling and Analyzing Dynamic Response for An Offshore Bottom-Fixed Wind Turbine with Individual Pitch Control

The asymmetric or periodically varying blade loads resulted by wind shear become more significant as the blade length is increased to capture more wind power.Additionally,compared with the onshore wind turbines,their offshore counterparts are subjected to additional wave loadings in addition to wind loadings within their lifetime.Therefore,vibration control and fatigue load mitigation are crucial for safe operation of large-scale offshore wind turbines.In view of this,a multi-body model of an offshore bottom-fixed wind turbine including a detailed drivetrain is established in this paper.Then,an individual pitch controller(IPC)is designed using disturbance accommodating control.State feedback is used to add damping in flexible modes of concern,and a state estimator is designed to predict unmeasured signals.Continued,a coupled aero-hydro-servo-elastic model is constructed.Based on this coupled model,the load reduction effect of IPC and the dynamic responses of the drivetrain are investigated.The results showed that the designed IPC can effectively reduce the structural loads of the wind turbine while stabilizing the turbine power out-put.Moreover,it is found that the drivetrain dynamic responses are improved under IPC.

Modelling the Effect of Self-Immunity and the Impacts of Asymptomatic and Symptomatic Individuals on COVID-19 Outbreak

COVID-19 is one of themost highly infectious diseases ever emerged and caused by newly discovered severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).It has already led the entire world to health and economic crisis.It has invaded the whole universe all most every way.The present study demonstrates with a nine mutually exclusive compartmental model on transmission dynamics of this pandemic disease(COVID-19),with special focus on the transmissibility of symptomatic and asymptomatic infection from susceptible individuals.Herein,the compartmental model has been investigated with mathematical analysis and computer simulations in order to understand the dynamics of COVID-19 transmission.Initially,mathematical analysis of the model has been carried out in broadly by illustrating some well-known methods including exactness,equilibrium and stability analysis in terms of basic reproduction number.We investigate the sensitivity of the model with respect to the variation of the parameters’values.Furthermore,computer simulations are performed to illustrate the results.Our analysis reveals that the death rate from coronavirus disease increases as the infection rate increases,whereas infection rate extensively decreases with the increase of quarantined individuals.The quarantined individuals also lead to increase the concentration of recovered individuals.However,the infection rate of COVID-19 increases more surprisingly as the rate of asymptomatic individuals increases than that of the symptomatic individuals.Moreover,the infection rate decreases significantly due to increase of self-immunity rate.

Lewin Behavior Model-Based Study on Influence Factors of Individuals to Mobile Service Demand

How to fmd main influence factors of individuals to mobile service demand is investiga- ted. The empirical research is conducted in the sample of high-value customers in China mobile market. Based on Lewin behavior model, this pa- per establishes factors-matrix from personal and environmental dimensions. Relationships among multiple factors are tested in the structural equa- tion model and their impacts on customers＇ de- mands are elaborated. Findings indicate that opera- tional convenience and business brand image have significant effects on sample users＇ demands. Fur- thermore, annual income, gender, occupation, the needs of access to information and the needs of enriching and improving social relationships are al- so important factors for high-value users. The re- suits may provide further insights into mobile service demand and the model can be popularized to other behavior researches.

Development and evaluation of an individual tree growth and yield model for the mixed species forest of the Adirondacks Region of New York, USA

Background： Growth and yield models are important tools for forest planning. Due to its geographic location, topology, and history of management, the forests of the Adirondacks Region of New York are unique and complex. However, only a relatively limited number of growth and yield models have been developed and/or can be reasonably extended to this region currently. Methods： in this analysis, 571 long-term continuous forest inventory plots with a total of 10 - 52 years of measurement data from four experimental forests maintained by the State University of New York College of Environmental Science and Forestry and one nonindustrial private forest were used to develop an individual tree growth model for the primary hardwood and softwood species in the region. Species-specific annualized static and dynamic equations were developed using the available data and the system was evaluated for long-term behavior. Results： Equivalence tests indicated that the Northeast Variant of the Forest Vegetation Simulator （FVS-NE） was biased in its estimation of tree total and bole height, diameter and height increment, and mortality for most species examined. In contrast, the developed static and annualized dynamic, species-specific equations performed quite well given the underlying variability in the data. Long-term model projections were consistent with the data and suggest a relatively robust system for prediction. Conclusions： Overall, the developed growth model showed reasonable behavior and is a significant improvement over existing models for the region. The model also highlighted the complexities of forest dynamics in the region and should help improve forest planning efforts there.

An imputation/copula-based stochastic individual tree growth model for mixed species Acadian forests： a case study using the Nova Scotia permanent sample plot network

Background： A novel approach to modelling individual tree growth dynamics is proposed. The approach combines multiple imputation and copula sampling to produce a stochastic individual tree growth and yield projection system. Methods： The Nova Scotia, Canada permanent sample plot network is used as a case study to develop and test the modelling approach. Predictions from this model are compared to predictions from the Acadian variant of the Forest Vegetation Simulator, a widely used statistical individual tree growth and yield model. Results： Diameter and height growth rates were predicted with error rates consistent with those produced using statistical models. Mortality and ingrowth error rates were higher than those observed for diameter and height, but also were within the bounds produced by traditional approaches for predicting these rates. Ingrowth species composition was very poorly predicted. The model was capable of reproducing a wide range of stand dynamic trajectories and in some cases reproduced trajectories that the statistical model was incapable of reproducing. Conclusions： The model has potential to be used as a benchmarking tool for evaluating statistical and process models and may provide a mechanism to separate signal from noise and improve our ability to analyze and learn from large regional datasets that often have underlying flaws in sample design.

Steady States in SIRS Epidemical Model of Mobile Individual

We consider an epidemical model within soclally interacting mobile individuals to study the behaviors of steady states of epidemic propagation in 2D networks. Using mean-field approximation and large scale simulations, we recover the usual epidemic behavior with critical thresholds δc and pc below which infectious disease dies out. For the population density δ far above δc it is found that there is linear relationship between contact rate λ and the population density δ in the main. At the same time, the result obtained from mean-field approximation is compared with our numerical result, and it is found that these two results are similar by and large but not completely the same.

Quantitative Structural Models to Assess Credit Risk on Individuals

Default Probabilities quantitatively measures the credit risk that a borrower will be unable or unwilling to repay its debt. An accurate model to estimate, as a function of time, these default probabilities is of crucial importance in the credit derivatives market. In this work, we adapt Merton’s [1] original works on credit risk, consumption and portfolio rules to model an individual wealth scenario, and apply it to compute this individual default probabilities. Using our model, we also compute the time depending individual default intensities, recovery rates, hazard rate and risk premiums. Hence, as a straight-forward application, our model can be used as novel way to measure the credit risk of individuals.

Interpersonal Perception in Virtual Groups: Examining Homophily, Identification and Individual Attraction Using Social Relations Model in Network

With the penetration of the Internet, virtual groups have become more and more popular. The reliability and accuracy of interpersonal perception in the virtual environment is an intriguing issue. Using the Social relations model (SRM) [1], this paper investigates interpersonal perception in virtual groups from a multilevel perspective. In particular, it examines the following three areas: homophily, identification, and individual attraction, and explores how much of these directional and dyadic relational evaluations can be attributed to the effect of the actor, the partner, and the relationship.

The Game Model Analysis between the Individual and the Group

This paper analyses the game model between the individual and the group that has the characteristics of Stackelberg model in traditional game theory and replicator dynamic model in evolutionary game theory. In the first phase of game, the bounded rationality group players adopt the replicator dynamic behavior. Secondly, the full rationality individual player decides the own response function by the strategies distribution of group players. The shortsighted individual player will take the risk-dominant strategy. This model has some unique characteristics.

Individual and Systemic Factors of Under-five Mortality in Nigeria:A Cox Proportional Hazard Model

Despite considerable efforts to reduce under-five mortality nationwide,Nigeria has fallen short of achieving the Millennium Development Goals(MDGs)target of 67 deaths per 1,000 live births by 2015.Of all the documented factors of under-five mortality,little evidence exists on the impact of systemic barriers and individual factors(maternal health-seeking behaviour)on under-five mortality in Nigeria.The study used a nationally representative sample from Nigeria Demographic and Health Survey(NDHS)2013 dataset.The target population was 20,192 women aged 15-59 years who had given birth to 31,480 children five years before the survey.Stata software was used for data analysis.The risk of death was estimated using Cox proportional hazard models and results are presented as hazards ratios(HR)with 95%confidence intervals(CI).Findings from the overall Model I-IV revealed individual factors(maternal health-seeking indicators)as significant factors of under-five deaths(p<0.05).Children whose mothers received antenatal care coverage(ANC)outside health care facilities(HCF)(HR:1.60,CI:1.0-2.4,p<0.05);or delivered outside HCF(HR:1.02,CI:0.7-1.5,p<0.05)had elevated hazard risk of death before age five.Conversely,children who were presented for postnatal check within two weeks of delivery(HR:0.60,CI:0.5-0.8,p<0.05),or delivered within the longer birth interval(HR:0.67,CI:0.6-0.8,p<0.001)had significantly lower hazard risk of death before age five.As part of systemic factors,children whose mothers were covered by health insurance scheme had significantly(HR:0.52,CI:0.2-1.2,p<0.001)lower risk of death when compared with their counterparts without health insurance coverage.The study emphasized the need to revitalize strategies and programs to improve women health seeking behaviour and investment in the health sector through health insurance,infrastructure,and supplies.

An Individual-Based Modeling Approach to Investigate Sympatric Speciation via Specialized Resource Usage

An individual-based model, EcoSim, was employed to investigate if specialized resource use could promote sympatric speciation. Prey individuals in the original version of EcoSim were supplied with a single primary food resource. A dual resource version with different food resources (Food 1 and Food 2) was also developed to create favorable conditions for the emergence of specialized food consumption among prey individuals. The single resource version was used as the control to determine the impact of the presence of multiple food resources on the occurrence of sympatric speciation. Each unit of Food 2 contained a higher amount of energy than Food 1, and Food 1 was more accessible than Food 2. Initially, prey individuals mostly fed on Food 1. How-ever, after the emergence of food specialization, the consumption rate of Food 2 signifi-cantly exceeded the consumption rate of Food 1;although prey individuals more frequently encountered Food 1. While sympatric speciation was observed in the dual resource version runs, we could not identify any sympatric species in the single resource version runs. Machine learning techniques were also employed to identify the most influential initial conditions leading to sympatric speciation. According to the obtained results, in most lineages sympatric speciation occurred at the beginning of the food specialization pro-cess. When the lineage had a high special diversity, the lineage needed two different criteria to diverge sympatrically: possessing high genetic diversity and a large population size. In support of previous findings, this study demonstrated that the most accurate determination of initial conditions leading to sympatric speciation can be obtained from lineages that are at the beginning of the divergence process. In conclusion, this study indicated that divergent foraging behavior could potentially lead to the sympatric emergence of new species in the absence of geographic isolation.

A basal area increment model for individual trees in mixed continuous cover forests in Iranian Caspian forests

The aim of this study was to develop and test a new basal area growth model in mixed species continuous cover forests in northern Iran.Weanalyzed 421 core samples from 6 main species in the forest area to develop our growth model.In each plot,we measured variables such as total tree height(m),diameter at breast height(DBH)(cm)and basal area of larger trees as cumulative basal areas of trees(GCUM)ofDBH[5 cm.The empirical data were analyzed using regression analysis.There was a statistically significant nonlinear function between the annual basal area increment,as the dependent variable,and the basal area of the individual trees and competition as explanatory variables.Reference area from the largest trees,was circular plot with area of 0.1 ha.GCUM was estimated for trees of DBH>5 cm.Furthermore,we investigated the dependencies of diameter growth of different species on stand density at different levels of competition,and diameter development of individual trees through time.The results indicate that competition caused by larger neighborhood trees has a negative effect on growth.In addition,the maximum diameter increment is affected by competition level.Therefore,the maximum diameter increment of species occurs when the trees are about 35–40 cm in dense-forest(40 to 0 m^2 per ha)and when the trees are about 60 to 70 cm in very dense forest(60 to 0 m^2 per ha)which is more likely to Caspian natural forests with high level density due to uneven-aged composition of stands.

从TVAAS到Individual Growth:美国田纳西州增值性教师评价发展新趋势

TVAAS是美国田纳西州创立的增值性教师评价方式,其核心特征是以学生成绩增幅衡量教师效能.TVAAS考虑到学生的原有基础与进步幅度,引导教师关注学生的成长状态.但是,TVAAS仍然存在分数价值导向、评价过程缺乏透明度以及无法为非测试型教师创造公正合理的成长分数等问题.学生成长档案袋评价是田纳西州增值性评价的新发展,它以学生作品为依据,以教师自评为基础,以同行评审为矫正,为非测试型教师提供了一个更为真实与个性化的评价经历.TVAAS与学生成长档案袋评价模式互为补充,使每位教师都能获得基于自身教学实际的个人增值(individual growth).

Epidemic spreading in scale-free networks including the effect of individual vigilance

In this paper, we study the epidemic spreading in scale-flee networks and propose a new susceptible-infected- recovered （SIR） model that includes the effect of individual vigilance. In our model, the effective spreading rate is dynamically adjusted with the time evolution at the vigilance period. Using the mean-field theory, an analytical result is derived. It shows that individual vigilance has no effect on the epidemic threshold. The numerical simulations agree well with the analytical result. Purthermore, we investigate the effect of individual vigilance on the epidemic spreading speed. It is shown that individual vigilance can slow the epidemic spreading speed effectively and delay the arrival of peak epidemic infection.

Study on individualized information service for the reader in the library based on the network

With the massive increase of digital resource based on the network,it becomes very important that how to help readers acquire the information needed according to the individualized requirement and interest in an accurate,convenient and prompt method. Therefore,it is very urgent to investigate individualized information service of library. In this paper,based on the development of the individualized information service for the reader in the college library,the individualized information service is clarified by using three perspectives,including establishment of individualized information demand model,integration of internal and external resource and protection of the reader privacy. Finally,the corresponding strategy and related measure are presented.

Individual tree segmentation and biomass estimation based on UAV Digital aerial photograph

Digital aerial photograph(DAP)data is processed based on Structure from Motion(Sf M)algorithm and regional net adjustment method to generate digital surface discrete point clouds similar to Light Detection and Ranging(LiDAR)and digital orthophoto mosaic(DOM)similar to optical remote sensing image.In this study,we obtained highresolution images of mature forests of Chinese fir by unmanned aerial vehicle(UAV)flying through crossroute flight,and then reconstructed the threedimensional point clouds in the UAV aerial area by SfM technique.The point cloud segmentation(PCS)algorithm was used for the individual tree segmentation,and the F-score of the three sample plots were 0.91,0.94,and 0.94,respectively.Individual tree biomass modeling was conducted using 155 mature Chinese fir forests which were correctly segmented.The relative root mean squared error(rRMSE)values of random forest(RF),bagged tree(BT)and support vector regression(SVR)were 34.48%,35.74%and 40.93%,respectively.Our study demonstrated that DAP point clouds had great potential to extract forest vertical parameters and could be applied successfully in individual tree segmentation and individual tree biomass modeling.