情感诉求对交通安全广告效果的影响

为检验交通公益广告中情感诉求变化对广告效果的影响,采用试验法操作广告情感诉求类型,使用眼动技术和Go/no-go联想测验(GNAT),通过比较不同效价和唤醒度的情感诉求广告对受众的注意力和内隐态度的影响,评估交通安全广告情感诉求类型的说服效果。研究发现:被试对低唤醒广告文字区的眼动注视时间和注视点个数显著长于/多于对高唤醒广告文字区的注视时间和注视点个数;被试观看高唤醒消极的广告后,正确驾驶行为的积极态度显著下降,而低唤醒消极/高唤醒积极/低唤醒积极的公益广告对于被试的内隐态度的改变没有显著差异。结果表明,高唤醒度积极广告能够提升受众的注意力,而高唤醒度消极广告则会损害受众对正确驾驶行为的内隐态度。     

Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization

Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

Ambient Air Quality Monitoring Network Design for Assessing Human Health Impacts from Exposures to Airborne Contaminants

Existing methods of establishing ambientair quality monitoring networks typically evaluateonly parameters related to ambient concentrations ofthe contaminant(s) of interest such as emissionsource characteristics, atmospheric transport anddispersion, secondary reactions, depositioncharacteristics, and local topography. However,adverse health risks from exposures to airbornecontaminants are a function of the contaminant andthe anatomic and physiologic characteristics of theexposed population. Thus, ambient air qualitymonitoring networks designed for the protection ofpublic health or for epidemiological studiesevaluating adverse health impacts from exposures toambient air contaminants should account for bothcontaminant characteristics and human healthparameters. A methodology has been establishedwhich optimizes ambient air quality monitoringnetworks for assessments of adverse human healthimpacts from exposures to airborne contaminants byincorporating human health risk assessmenttechniques. The use of risk assessment techniquesas the basis for designing ambient air qualitymonitoring networks will help to target limitedfinancial and human resources to evaluate humanhealth risks from exposures to airbornecontaminants.     

Determining Ecoregions for Environmental and GMO Monitoring Networks

A representative environmental monitoring network at the regional scale cannot use raster-based or random sampling designs, but requires a stratified sampling procedure integrating different information layers, and it has to occur in ecologically differing homogeneous regions (ecoregions). These we have determined using a set of spatial strata with ecological variables which we analysed with classification and regression trees (CART). We present a framework for environmental monitoring, that covers different scales, and we transfer the framework to a potential GMO (genetically modified organisms) monitoring network. We use ecoregion and other environmental strata together with existing environmental monitoring networks to determine GMO monitoring sites more precisely.     

Effectiveness evaluation of water-sprinkling in controlling urban fugitive road dust based on TRAKER method: A case study in Baoding, China

Fugitive road dust (FRD) contributes a great deal to urban rainwater and air pollution and is commonly controlled by water-sprinkling in most Chinese cities. However, there is a lack of information on its effectiveness. We used the Testing Re-entrained Aerosol Kinetic Emissions from Roads (TRAKER) method to monitor different types of roads in Baoding city before and within 1 hr after water-sprinkling and obtained the road dirtiness index (a) and PM concentration in the road environment ($T_{\mathrm{T}}^{*}$), to evaluate the removal efficiency for PM deposited on the road surface (${\eta }_a$) and the reduction efficiency for the PM concentration in the road environment (${\eta }_{\text{PM}}$). The results give that the ${\eta }_a$ for three types of roads is ranked: branch road (87%-–100%) > major arterial road (80%-83%) > minor arterial road (68%-77%), and the ${\eta }_{\text{PM}}$ ranked: minor arterial road (70%) > branch road (46%-58%) > major arterial road (37%-53%). The ${\eta }_a$ and ${\eta }_{\text{PM}}$ varied non-linearly with time and presented a quadratic curve. The average effective control time (${\eta }_{\mathit{a}}$> 0) was 62 min on the major and minor arterial roads, and much longer than 1 hr on branch roads. The ${\eta }_{\text{PM}}$ values diminished completely by 72 min on average from the end of sprinkling for the three types of roads. Water-sprinkling can remove PM₁₀ particles from the road surface and reduce their concentration in the road environment more thoroughly than PM_2.5. Our findings could be helpful for controlling urban FRD emissions more efficiently and precisely.     

Rural landscape planning case study of Nanhua State Farm

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Ecological networks and greenways in Europe: reasoning and concepts

The paper gives an overview of approaches towards ecological networks throughout Europe.It does not intend to present a complete picture,but to highlight comon developments within countries and regions and show common principles and differences between countries and regions that have to be taken into account when developing a joint European intiative,Countries or regions that have not been included can be active in the same way ,but information was not accessible to be authors for different reasons.This overview shows the comparable trends in decline of landscapes and the diversity in approaches to biodiversity conservation and nature conservation planning.Understanding the differences and common issues are of utmost imprtance to generalise common principles and to understand the way neighbours and other European partners approach problems.     

人工智能在金属塑性加工领域中的应用

概述了人工智能及其 2个主要分支 (专家系统和人工神经网络 ) ,讨论了遗传算法与专家系统集成以及神经网络与模糊逻辑、专家系统集成的必要性和集成方法 ,分别介绍了专家系统和人工神经网络在塑性加工领域中的应用现状。     

Prediction of the concentration of chlorophyll-α for Liuhai urban lakes in Beijing City

Introduction The eutrophication of fresh w ater has becom e a m ain w ater environm ental problem in the w orld. The m ain negative im pacts of fresh w ater eutrophication are w ater quality deterioration and the decrease of hydrophytes and aquatic specie…