Construction of an Evaluation Indicator System for Civic and Political Applications in Professional Practice Courses Based on CIPP:Taking the VBSE Practical Training Course as an Example

This study takes the virtual business society environment(VBSE)practical training course as a case study and applies the theoretical framework of the context,input,process,product(CIPP)model to construct an evaluation indicator system for the application of civic and politics in professional practice courses.The context evaluation is measured from the support of the VBSE practical training course into course civic and politics,teachers’cognition,and the integration of course objectives;the input evaluation is measured from the matching degree of teachers’civic and political competence,and the matching degree of teaching resources;the process evaluation is measured from the degree of implementation of civic and politics teaching and the degree of students’acceptance;and the product evaluation is measured from the degree of impact of civic and politics teaching.

Environmental input-output model and its analysis with a focus on the solid waste management sectors

An environmental input output model (EIOM) was introduced to the regional solid waste management sectors, which can reflect the direct and indirect relations between the environment and the regional economy development. Some details about how to use the EIOM was discussed. The EIOM was applied to the Changsha City in China. The example results indicate that much useful information related to the environment and the regional economy development can be gained from the solution of the EIOM. Thus, the EIOM can be used as a useful tool for the sustainable development planning including the solid waste management sectors.

T-Y TUBE MODEL OF HUMAN ASCENDINGAORTIC INPUT IMPEDANCE

This paper proposed a T- Y tube model to simulate foe input impedance of arterial system. It improves and extends the asymmetric T-tube model which was firstproposed by O' Rourke[1] and developed laier by Liu et al.[2]. Based on foe asymmetricT-tube model. a T-Y tube model was proposed by adding branching tubes whichrepresem the iliac arteries.All the tubes are considered to be uniform,viscoelasticlongitudinally tethered cylindrical tubes.The upper tube terminates with a windkesselmodel, while the terminal arterioles of the lowr tube are expressed as a resistance.After proper eraluation of the parameters.the impedance of the arterial system iscalculated under normal physiological and hypertensive condition.The model canpredict impedance in good agreement with the experimentally obtained data no matterin normal physiological condition or in pathological condition In comparison with theasymmeric T-tube model,T- Y tube model is closer to anatomy structure of the human arlerial system and at the sametime much simpler than the extremely complex multiplebranching tube model Therefore it will be a valuable model in studying the influencesof various parameters on aorta impedance and ventricular-vascular coupling.

New model reference adaptive control with input constraints

A new scheme of adaptive control is proposed for a class of linear time-invariant（ LTI） dynamical systems,especially in aerospace,with matched parametric uncertainties and input constraints. Based on a typical and conventional direct model reference adaptive control scheme,various modifications have been employed to achieve the goal. ＂C omposite model reference adaptive control＂of higher performance is seam-lessly combined with ＂positive μ-mod＂,which consequently results in a smooth tracking trajectory despite of the input constraints. In addition,bounded-gain forgetting is utilized to facilitate faster convergence of parameter estimates. The stability of the closed-loop systemcan be guaranteed by using Lyapunov theory.The merits and effectiveness of the proposed method are illustrated by a numerical example of the longitudinal dynamical systems of a fixed-wing airplane.

Nonlinear Systems Identification via an Input-Output Model Based on a Feedforward Neural Network

This paper develops a feedforward neural network based input output model for a general unknown nonlinear dynamic system identification when only the inputs and outputs are accessible observations. In the developed model, the size of the input space is directly related to the system order. By monitoring the identification error characteristic curve, we are able to determine the system order and subsequently an appropriate network structure for systems identification. Simulation results are promising and show that generic nonlinear systems can be identified, different cases of the same system can also be discriminated by our model.

A Study on the Importance of Language Input in Second Language Acquisition(SLA)

Input theory as a theoretical foundation in language teaching plays an important role in SLA.Though a wealth of re⁃search has been done by linguists to demonstrate the importance of language input in SLA,little has been written about the type and amount of language input for successful SLA,especially its processing model while acquiring a second language.This paper first discusses the Krashen’s input hypothesis in language learning,and then an introduction to Chaudron’s processing model of in⁃put is made.In the final part,the author explains the acquisition process based on word acquisition and grammar acquisition and concludes that in the process of acquiring a second language,the language learners reconstruct a new cognitive model by taking in consistent comprehensible language input.

Tool Condition Monitoring Based on Nonlinear Output Frequency Response Functions and Multivariate Control Chart

Tool condition monitoring(TCM)is a key technology for intelligent manufacturing.The objective is to monitor the tool operation status and detect tool breakage so that the tool can be changed in time to avoid significant damage to workpieces and reduce manufacturing costs.Recently,an innovative TCM approach based on sensor data modelling and model frequency analysis has been proposed.Different from traditional signal feature-based monitoring,the data from sensors are utilized to build a dynamic process model.Then,the nonlinear output frequency response functions,a concept which extends the linear system frequency response function to the nonlinear case,over the frequency range of the tooth passing frequency of the machining process are extracted to reveal tool health conditions.In order to extend the novel sensor data modelling and model frequency analysis to unsupervised condition monitoring of cutting tools,in the present study,a multivariate control chart is proposed for TCM based on the frequency domain properties of machining processes derived from the innovative sensor data modelling and model frequency analysis.The feature dimension is reduced by principal component analysis first.Then the moving average strategy is exploited to generate monitoring variables and overcome the effects of noises.The milling experiments of titanium alloys are conducted to verify the effectiveness of the proposed approach in detecting excessive flank wear of solid carbide end mills.The results demonstrate the advantages of the new approach over conventional TCM techniques and its potential in industrial applications.

On time-step in structural seismic response analysis under ground displacement/acceleration

There are two models in use today to analyze structural responses when subjected to earthquake ground motions, the Displacement Input Model （DIM） and the Acceleration Input Model （AIM）. The time steps used in direct integration methods for these models are analyzed to examine the suitability of DIM. Numerical results are presented and show that the time-step for DIM is about the same as for AIM, and achieves the same accuracy. This is contrary to previous research that reported that there are several sources of numerical errors associated with the direct application of earthquake displacement loading, and a very small time step is required to define the displacement record and to integrate the dynamic equilibrium equation. It is shown in this paper that DIM is as accurate and suitable as, if not more than, AIM for analyzing the response of a structure to uniformly distributed and spatially varying ground motions.

Iterative learning control of SOFC based on ARX identification model

This paper presents an application of iterative learning control (ILC) technique to the voltage control of solid oxide fuel cell (SOFC) stack. To meet the demands of the control system design, an autoregressive model with exogenous input (ARX) is established. Firstly, by regulating the variation of the hydrogen flow rate proportional to that of the current, the fuel utilization of the SOFC is kept within its admissible range. Then, based on the ARX model, three kinds of ILC controllers, i.e. P-, PI- and PD-type are designed to keep the voltage at a desired level. Simulation results demonstrate the potential of the ARX model applied to the control of the SOFC, and prove the excellence of the ILC controllers for the voltage control of the SOFC.

Spatio-temporal Changes and Associated Uncertainties of CENTURYmodelled SOC for Chinese Upland Soils, 1980-2010

Detailed information on the spatio-temporal changes of cropland soil organic carbon(SOC) can significantly contribute to the improvement of soil fertility and mitigate climate change. Nonetheless, information and knowledge on the national scale spatio-temporal changes and the corresponding uncertainties of SOC in Chinese upland soils remain limited. The CENTURY model was used to estimate the SOC storages and their changes in Chinese uplands from 1980 to 2010. With the Monte Carlo method, the uncertainties of CENTURY-modelled SOC dynamics associated with the spatial heterogeneous model inputs were quantified. Results revealed that the SOC storage in Chinese uplands increased from 3.03(1.59 to 4.78) Pg C in 1980 to 3.40(2.39 to 4.62) Pg C in 2010. Increment of SOC storage during this period was 370 Tg C, with an uncertainty interval of –440 to 1110 Tg C. The regional disparities of SOC changes reached a significant level, with considerable SOC accumulation in the Huang-Huai-Hai Plain of China and SOC loss in the northeastern China. The SOC lost from Meadow soils, Black soils and Chernozems was most severe, whilst SOC accumulation in Fluvo-aquic soils, Cinnamon soils and Purplish soils was most significant. In modelling large-scale SOC dynamics, the initial soil properties were major sources of uncertainty. Hence, more detailed information concerning the soil properties must be collected. The SOC stock of Chinese uplands in 2010 was still relatively low, manifesting that recommended agricultural management practices in conjunction with effectively economic and policy incentives to farmers for soil fertility improvement were indispensable for future carbon sequestration in these regions.

Improvement of Ecological Footprint Method and Application in Henan Province

The measure of sustainable development has always been an important and difficulty subject, and the major evaluation model has three types: indicators based on system theory and methods, indicators relied on economic valuation of the environment, sustainability indicators including biophysical assessments. The ecological footprint analysis initiated by William E. Rees, one of the indicators including biophysical assessments, gets rid of the defects of the other models. Ecological footprint has gradually become popular on account of the measuring indexes based on scientific theory, innovative thought-way and its wide adaptability. This paper introduces the conception and computation method, making a progress and making up for the method of ecological footprint, and finally, makes an application analyses through Henan province regional sustainable development.

A Sensitivity Study of Single Column Model

A single column model (SCM) is constructed by extracting the physical subroutines from the NCAR Community Climate Model version 1 (CCM1).Simulated data are generated by CCM1 and used to validate the SCM and to study the sensitivity of the SCM to errors in its input data.It is found that the SCM temperature predictions are moderately sensitive to errors in the input horizontal temperature flux convergence and moisture flux convergence.Two types of error are concerned in this study,random errors due to insufficient data resolution,and errors due to insufficient data area coverage.While the first type of error can be reduced by filtering and/or increasing the data resolution,it is shown that the second type of error can be reduced by enlarging the data area coverage and using a suitable method to compute the input flux convergence terms.

Impacts of household living consumption on energy use and carbon emissions in China based on the input–output model

China must urgently accelerate its decrease of energy use,optimize its energy structure,reduce CO2 emissions,and promote the early realization of an ecological civilization.Simultaneously,meeting the growing consumer demand is one of the reasons for the increase in energy use.This study investigates the impacts of household consumption on energy use and CO2 emissions from the perspective of the lifestyle of Chinese residents.On the basis of the input–output model of 30 provinces,we analyze the current situation of energy use and CO2 emissions in different regions(spatial scale)with economic development and income improvement(time scale),investigate the pulling effect of household consumption in different provinces on industrial sectors,examine the influencing factors of indirect CO2 emissions from food,clothing,housing,and transportation in key regions,and explore the policy implications of the transition to a low-carbon lifestyle in different provinces.Results show that the fuel structure of Chinese residents should be optimized further.Total household energy consumption and total CO2 emissions considerably increased.In 2012,total household energy consumption accounted for nearly 30%of total energy consumption,while indirect CO2 emissions accounted for 66.3%of total household emissions.With regard to the structures of indirect household energy consumption,the housing sector accounted for the largest proportion,reaching 23.4%in indirect energy consumption in 2012.The pulling effect of the housing sector on industrial sectors was also evident.The decomposition analysis showed that the rapid increase in indirect household CO2 emissions was primarily due to the increase in per capita living expenditure.The consumption structures in different provinces produced various impacts,and the energy intensity effect was identified as an important factor for reducing indirect household CO2 emissions.

EFFICIENCY DECOMPOSITION WITH SHARED INPUTS AND OUTPUTS IN TWO-STAGE DEA

Data envelopment analysis （DEA） is an effective non-parametric method for measuring the relative efficiencies of decision making units （DMUs） with multiple inputs and outputs. In many real situations, the internal structure of DMUs is a two-stage network process with shared inputs used in both stages and common outputs produced by the both stages. For example, hospitals have a two-stage network structure. Stage 1 consumes resources such as information technology system, plant, equipment and admin personnel to generate outputs such as medical records, laundry and housekeeping. Stage 2 consumes the same set of resources used by stage 1 （named shared inputs） and the outputs generated by stage 1 （named intermediate measures） to provide patient services. Besides, some of outputs, for instance, patient satisfaction degrees, are generated by the two individual stages together （named shared outputs）. Since some of shared inputs and outputs are hard split up and allocated to each individual stage, it needs to develop two-stage DEA methods for evaluating the performance of two-stage network processes in such problems. This paper extends the centralized model to measure the DEA efficiency of the two-stage process with non split-table shared inputs and outputs. A weighted additive approach is used to combine the two individual stages. Moreover, additive efficiency decomposition models are developed to simultaneously evaluate the maximal and the minimal achievable efficiencies for the individual stages. Finally, an example of 17 city branches of China Construction Bank in Anhui Province is employed to illustrate the proposed approach.

区域贸易视角下中国省域隐含土地流动研究

With the continuous enhancement of regional connectivity,the indirect use of land resources through the pathways of trade in goods and services plays an increasingly important role in the overall utilization of land resources.Despite this,relevant research in this field is still in its infancy,and few papers have addressed this issue.This paper uses a multi-regional input–output model to calculate the embodied land in the 30 provinces(autonomous regions and municipalities)and eight regions of China from the perspective of regional trade and further analyzes the spatial pattern of characteristics associated with embodied land flows.The results show that the amount of embodied land occupied by China’s inter-regional trade accounts for 21.39%of the country’s total land,and an average of 38.54%of China’s provincial land demand is met by land exports from other provinces.More than 80%of land consumed by Beijing,Tianjin,and Shanghai is from other provinces.The provinces of Heilongjiang,Inner Mongolia,Xinjiang,and Hebei are the largest net exporters of cultivated land,forest and grazing and aquatic land,fishery land,and built-up land,respectively(the outflows account for 42.26%,27.53%,38.66%,and 35.28%of the corresponding land types in the province);and Guangdong,Shandong,and Zhejiang are the main net importers.The flow of agricultural land(cultivated land,forest land,grazing land,and aquatic land)generally shows a shift from west to east and from north to south.The regions in northeast and northwest China have the largest scale of agricultural land outflows,mainly into East and South China.In addition,8.43%of cultivated land,7.47%of forest land,6.41%of grazing land,6.88%of aquatic land,and 18.35%of built-up land in China are provided for foreign use through international trade.This paper provides feasible ideas and a theoretical basis for solving the contradiction between land use and ecological protection,which could potentially help to achieve sustainable land use in China.

A New Method to Calculate Investment Multiplier

Based on the analysis of Keynesian investment theory, this paper puts forward the method of calculating investment multiplier with partial\|closed input\|output model, and by using 1995 input\|output table of China, calculates the investment multiplier.

New Results on PWARX Model Identification Based on Clustering Approach

This paper deals with the problem of piecewise auto regressive systems with exogenous input(PWARX) model identification based on clustering solution. This problem involves both the estimation of the parameters of the affine sub-models and the hyper planes defining the partitions of the state-input regression. The existing identification methods present three main drawbacks which limit its effectiveness. First, most of them may converge to local minima in the case of poor initializations because they are based on the optimization using nonlinear criteria. Second, they use simple and ineffective techniques to remove outliers. Third, most of them assume that the number of sub-models is known a priori. To overcome these drawbacks, we suggest the use of the density-based spatial clustering of applications with noise(DBSCAN) algorithm. The results presented in this paper illustrate the performance of our methods in comparison with the existing approach. An application of the developed approach to an olive oil esterification reactor is also proposed in order to validate the simulation results.

Temporal variation in modal properties of a base-isolated building during an earthquake

Temporal variation of dynamical modal properties of a base-isolated building is investigated using earthquake records in the building. A batch processing least-squares estimation method is applied to segment-wise time-series data. To construct an input-output system,an auto-regressive model with exogenous input (ARX) of second-order including a forgetting coefficient as a weighting coefficient is used for the estimation of modal parameters. The fundamental and second natural frequencies and the damping ratios of the fundamental and second natural modes of the base-isolated building are identified in the time domain. The identified results are consistent with the results obtained from the micro-tremor vibration data,forced-vibration test data and earthquake records in the present base-isolated building in the case of taking into account the amplitude-dependency of the isolators and viscous dampers. It is finally pointed out that several factors,e.g.,amplitude dependency of the isolator and damper system and special characteristics of the series-type viscous damper system,may be related complicatedly with the temporal variation in modal properties of the above-mentioned system.

Hybrid Method: Review, Modularization and Application

The objective of this approach is to introduce the idea of modular design into the construction of hybrid model, thus, each step has it own unique function, the entries of superior data decrease and the directions of data flow are more clear. Although the approach itself cannot guarantee the accuracy of the target table which depends on the accuracy of the survey data, experience of experts and assumption in deriving, it does can help constructors to arrange their thoughts, thereby subjective errors could be brought down significantly. As an example, a case analysis is employed to show the effectiveness of the method in detail.

Impact of fossil fuel subsidy reform in China:estimations of household welfare effects based on 2007–2012 data

Changing the energy subsidy mechanism is a priority of China’s ongoing market-based energy reform.Using the 2007–2012 empirical data,this paper applies an input–output model to evaluate the welfare effects,that is,the expenditure increments of five income groups in 28 provinces,associated with the possible policy scenario of removing the subsidies for fossil fuels.The key findings of this study include,first,that the total indirect welfare effects(i.e.the additional money spent on non-energy commodities)are two-to-three times as large as the direct ones(i.e.the additional money spent on energy).Second,removing the oil subsidy leads to an additional expenditure of 19.74 CNY annually for each resident,which is much larger than the effect of removing the natural gas and coal subsidies.Third,the composition of the indirect effect varies significantly among income groups,because food expenditure contributes to approximately two-thirds of the total indirect effect on average.Finally,the welfare effect is very sensitive to the income level.To promote the smooth reform of the fossil fuel subsidies,we suggest that the government should deal with the coal industry initially,pay special attention to the indirect expense increase,and compensate low-income households for the welfare losses.