The role of situation awareness in accidents of large-scale technological systems

In the last two decades, several serious accidents at large-scale technological systems that have had grave consequences, such as that at Bhopal, have primarily been attributed to human error. However, further investigations have revealed that humans are not the primary cause of these accidents, but have inherited the problems and difficulties of working with complex systems created by engineers. The operators have to comprehend malfunctions in real time, respond quickly, and make rapid decisions to return operational units to normal conditions, but under these circumstances, the mental workload of operators rises sharply, and a mental workload that is too high increases the rate of error. Therefore, cognivitive human features such as situation awareness (SA)—one of the most important prerequisite for decision-making—should be considered and analyzed appropriately. This paper applys the SA Error Taxonomy methodology to analyze the role of SA in three different accidents: (1) A runaway chemical reaction at Institute, West Virginia killing two employees, injuring eight people, and requiring the evacuation of more than 40,000 residents adjacent to the facility, (2) The ignition of a vapor cloud at Bellwood, Illinois that killed one person, injured two employees, and caused significant business interruption, and (3) An explosion at Ontario, California injuring four workers and caused extensive damage to the facility. In addition, the paper presents certain requirements for cognitive operator support system development and operator training under abnormal situations to promote operators’ SA in the process industry.     

岩溶塌陷倾向性等级的KPCA-SVM预测模型

为了快速、有效地预测岩溶塌陷倾向性等级,在统计分析大量观测实例的基础上,选取岩性系数、岩体结构系数、地下水系数、覆盖层系数、地形地貌系数和环境条件系数作为特征指标。利用核主成分分析(KPCA)方法在高维空间提取岩溶塌陷影响因子的主成分,将获取的主成分作为支持向量机(SVM)的特征向量,建立基于KPCA的岩溶塌陷倾向性等级的SVM预测模型。将12组观测数据作为学习样本对模型进行训练。采用回代估计法进行回检,误判率为0。利用训练好的模型对2组待判样本进行预测。结果表明:经KPCA后指标个数减少,相关性降低,SVM运算的复杂度降低。用该模型所得预测结果的准确率为100%。     

Evaluating Alternative Temporal Survey Designs for Monitoring Wetland Area and Detecting Changes Over Time in California

Evaluation of wetland extent and changes in extent is a foundation of many wetland monitoring and assessment programs. Probabilistic sampling and mapping provides a cost‐effective alternative to comprehensive mapping for large geographic areas. One unresolved challenge for probabilistic or design‐based approaches is how best to monitor both status (e.g., extent at a single point in time) and trends (e.g., changes in extent over time) within a single monitoring program. Existing wetland status and trends (S&T) monitoring programs employ fixed sampling locations; however, theoretical evaluation and limited implementation in other landscape monitoring areas suggest that alternative designs could increase statistical efficiency and overall accuracy. In particular, designs that employ both fixed and nonfixed sampling locations (alternately termed permanent and temporary samples), termed sampling with partial replacement (SPR), are considered to efficiently and effectively balance monitoring current status with detection of trends. This study utilized simulated sampling to assess the performance of fixed sampling locations, SPR, and strictly nonfixed designs for monitoring wetland S&T over time. Modeled changes in wetland density over time were used as inputs for sampling simulations. In contrast to previous evaluations of SPR, the results of this study support the use of a fixed sampling design and show that SPR may underestimate both S&T.     

战场环境下装备保障信息系统安全风险与防护

目的研究战场环境下装备保障信息系统的安全问题。方法从装备保障及装备保障信息系统的概念、分类和复杂战场环境下装备保障信息系统所面临的安全威胁入手,依照五分法把装备保障信息系统安全风险划分为5个等级,推导出风险评估模型,提出实施装备保障信息系统安全防护的技战术策略。结果战场环境下,为确保整个作战进程中装备保障活动安全、有效、稳定地进行,装备保障信息系统防护必须遵循统一协调、综合利用的积极防护原则,采用有效的风险控制措施加以应对。结论通过积极探索和发展装备保障信息安全与防护理论,找准战场环境信息防护中存在的薄弱环节,制定了装备保障信息安全防护策略,加强装备保障信息系统的安全管理工作,最终提高我军装备保障信息系统的防护能力。     

云南昌宁玉地里温泉水文地球化学特征及形成模式

以水化学及同位素技术为基础,对昌宁县玉地里温泉的地质及地热特征进行了研究,并取得了一些重要的认识.通过对比研究该温泉地下热水1980年和2012年的水文地球化学数据,发现经过30多年的循环演化,其水化学类型仍为HCO3-Na型.δD和δ18O同位素为该温泉首次获得,数据显示地下热水具有现代大气降水的氢氧同位素组成特征,属断裂带对流型深循环低温地下热水系统,其补给源区位于东部和南部山区,热储层和盖层的构造及岩性特征与地下热水的深循环和化学组成有着密切联系.     

Towards a new climate economics:research areas and prospects

International cooperation to address climate change now stands at a crossroads.With a new international regime for emissions reduction established by the Durban Platform, "New Climate Economics(NCE)" has become a research hotspot.The need for urgent action to combat climate change has prompted discussion on reforms of economic growth patterns and the energy system.The industrial civilization,therefore,now faces a transition towards a new pathway for ecological sustainability.NCE explores new economic concepts,theories,and analytical methods to design a balanced pathway for sustainable growth and emission reduction.Instead of getting trapped in discussions on allocation of emission reduction responsibilities and obligations among countries,NCE pays more attention to developing win-win multilateral cooperation mechanisms that facilitate collaborative RD and knowledge sharing.In addition,NCE studies incentives for low-carbon transition,turning carbon emission reduction into a domestic need for countries to increase their international competitiveness.To achieve the 2°C target,most countries around the world face challenges of insufficient emission allowances to cover expected emissions associated with their projected economic growth.As carbon emissions rights becomes an increasingly scarce resource,increasing the carbon productivity of the economy turns to be the critical path to address the dilemma of green or growth.NCE studies the historical evolution of carbon productivity for countries at different development stages as well as ways to enhance such carbon productivity.This type of study provides invaluable lessons for emerging economies to reach their own emission peaks without losing the momentum of growth.Replacing fossil fuels with new and renewable energy has proven to be an inevitable choice for reshaping the energy system and addressing climate change- it has already become a global trend.NCE studies incentives for new energy technology innovation and deployment provided by carbon pricing,and sheds light on the co-benefits of climate change mitigation,such as resource conservation,environmental protection,and energy security.The role of carbon pricing in promoting intemational RD cooperation and technical transfer will also be studied.The shift in consumption patterns is another key factor enabling a low-carbon transformation.Therefore,NCE also explores the theoretical work on new values of wealth,welfare and consumption,new lifestyles in the context of ecological civilization,concepts and implementation of low-carbon urban planning in developing countries,and the impacts of consumption pattern changes on social development,material production,and urban infrastructure construction.     

有机化学品不同温度下(过冷)液体蒸气压预测模型的建立与评价

(过冷)液体蒸气压(PL)是评价化学品在环境中分配、迁移和归趋行为的重要参数。PL具有较强的温度依附性。发展一种能够精确预测不同环境温度下化学品PL的方法,有助于填补化学品生态风险评估的大量数据缺失。本研究收集整理了661种有机化合物在不同温度下(200~830 K)共计10 478个log PL值。在此基础上,采用偏最小二乘(PLS)回归和支持向量机(SVM)方法,构建了PL的线性和非线性预测模型。结果表明:2种模型均具有良好的拟合度、稳健性及预测能力,SVM模型的预测性能略高于PLS模型(PLS:R2adj.tra=0.912,RMSEtra=0.477,Q2ext=0.910;SVM:R2adj.tra=0.997,RMSEtra=0.092,Q2ext=0.967)。机理分析表明,温度是影响PL的主要因素,温度越高,蒸气压越大;其次,X1sol也影响PL大小,X1sol用来描述分子间的色散作用,分子间色散力越小,蒸气压越大;此外,化合物的氢键个数、极性和分子构型等因素也影响PL大小。采用Wiliams plot方法表征了PLS模型应用域。所建立的模型可用来预测烷烃、烯烃、醇、酮、羧酸、苯、酚、联苯、卤代芳香烃、含N化合物及含S化合物在不同温度下的PL数据。     

Prioritisation of citizen‐centric information for disaster response

In the aftermath of a disaster event, and in the absence of trained professionals, many responsibilities are assumed by uninjured citizens who are willing and able to help, such as care of the injured or search and rescue. These citizens are constrained by communications and logistics problems but are less equipped to deal with them as most often they are cut off from any coordinated assistance. The method proposed in this study would increase the survivability of those injured or trapped by a disaster event by providing a facility to allow citizens to coordinate and share information among themselves. This is facilitated by the proposed deployment and the autonomous management of an ad hoc infrastructure that liaises directly with survivors without central control. Furthermore, as energy concerns present critical constraints to these networks, this research proposes a system of categorising information elements within the network to ensure efficient information exchange.     

Land-use forecasting and hydrologic model integration for improved land-use decision support

This paper develops a methodology for integrating a land-use forecasting model with an event scale, rainfall-runoff model in support of improving land-use policy formulation at the watershed scale. The models selected for integration are loosely coupled, structured upon a common GIS platform that facilitates data exchange. The hydrologic model HEC-HMS is calibrated for a specific storm event that occurred within central Washington State. The land-use forecasting model, What If? is implemented to forecast future spatial distributions of low-density residential land-uses under low and high population growth estimates. Forecasted land-use distribution patterns for the years 2015, 2025, and 2050 are then used as land-use data input for the calibrated hydrologic model, keeping all other parameters constant. Impacts to the stream discharge hydrograph are predicted as the study area becomes increasingly developed as forecasted by What If?. The initial results of this integration process demonstrate the synergy that can be generated through the linkage of the selected models. The ability to quantifiably forecast the potential hydrologic implications of proposed land-use policies before their implementation offers land-use decision-makers a valuable tool for discerning which proposed land-use alternatives will be effective at minimizing storm water runoff.     

Environmental risk perception, environmental concern and propensity to participate in organic farming programmes

This paper aims to identify the factors underlying farmers' propensity to participate in organic farming programmes in a Romanian rural region that confronts non-point source pollution. For this, we employ structural equation modelling with latent variables using a specific data set collected through an agri-environmental farm survey in 2001. The model includes one 'behavioural intention' latent variable ('propensity to participate in organic farming programmes') and five 'attitude' and 'socio-economic' latent variables ('socio-demographic characteristics', 'economic characteristics', 'agri-environmental information access', 'environmental risk perception' and 'general environmental concern'). The results indicate that, overall, the model has an adequate fit to the data. All loadings are statistically significant, supporting the theoretical basis for assignment of indicators for each latent variable. The significance tests for the structural model parameters show 'environmental risk perception' as the strongest determinant of farmers' propensity to participate in organic farming programmes.