Phenomenological compensation of thermally caused position and orientation errors of rotary axes

Thermal errors of machine tools are one of the major sources of inaccuracy. Therefore, the reduction of temperature induced deviations or the compensation of the resulting tool center point (TCP) errors have been of strong interest to the manufacturing industry for a couple of years. Up to now, the observation of the environment, the main spindle, the linear axes and the machine bed were in the focus of research, but with the rising demand for 5-axis machine tools and the increasing requirements regarding their accuracy, the analysis of the thermal behavior of rotary axes becomes more and more important. This paper gives an overview of corresponding thermal measurements of machine tools. The thermal behavior of rotary and swiveling axes is analyzed in detail. A simulation model and an approach for a phenomenological compensation of the TCP error are introduced and verified by measurements.     

Experience,but not distance,influences the recruitment precision in the stingless bee <Emphasis Type="Italic">Scaptotrigona mexicana</Emphasis>

Recruitment precision, i.e. the proportion of recruits that reach an advertised food source, is a crucial adaptation of social bees to their environment. Studies with honeybees showed that recruitment precision is not a fixed feature, but it may be enhanced by factors like experience and distance. However, little is known regarding the recruitment precision of stingless bees. Hence, in this study, we examined the effects of experience and spatial distance on the precision of the food communication system of the stingless bee Scaptotrigona mexicana. We conducted the experiments by training bees to a three-dimensional artificial patch at several distances from the colony. We recorded the choices of individual recruited foragers, either being newcomers (foragers without experience with the advertised food source) or experienced (foragers that had previously visited the feeder). We found that the average precision of newcomers (95.6 ± 2.61%) was significantly higher than that of experienced bees (80.2 ± 1.12%). While this might seem counter-intuitive on first sight, this “loss” of precision can be explained by the tendency of experienced recruits to explore nearby areas to find new rewarding food sources after they had initially learned the exact location of the food source. Increasing the distance from the colony had no significant effect on the precision of the foraging bees. Thus, our data show that experience, but not the distance of the food source, affected the patch precision of S. mexicana foragers.     

灾变性事件引起的消费品产业链价格波及效应研究

为了研究地震等灾变性事件对于消费品产业链内价格传递和市场的影响,本文利用从2008年2月至2009年3月四川省江油市畜产业链进行实证研究,使用向量纠错模型（VECM）和历史分解图（HDG）分析了价格调整的动态效果和沿产业链的因果关系。结果表明,价格的调整关于速度和大小都是不对称的,外生震荡对于该产业链的不同层面产生不同影响,导致价格差益的扩大和价格不完全传递。该方法能够有效地分析灾变事件条件下消费品产业链内价格波及效应问题。     

人误因素树构建技术研究

运用人误因素辨识多视图法进行因素辨识,建立了详细的因素辨识表;把人的行为分为5个阶段,即系统状态监测阶段,目标分析阶段,方案确定阶段和行为执行阶段.分别分析各个阶段可能的人误原因及模式;以组织视图为例,根据因素辨识和人误原因及模式分析结果,阐述人误因素树的构建过程,最终得到了1个完整的人误因素树.     

基于CREAM和贝叶斯网络的空管人误概率预测方法

针对研究管制人因可靠性时存在的模糊性和片面性问题,采用认知可靠性与失误分析方法（CREAM）中的扩展预测法,计算10项管制通用任务的人误概率;在此基础上,以管制行为形成因子作为根节点构建贝叶斯网络,建立其与情景控制模式的不确定关系模型,对管制员在多任务中的人误概率进行预测。研究结果表明:在由相同评判者给出行为形成因子影响效应的前提下,由CREAM扩展预测法和构建贝叶斯网络的方法预测得到的多数任务的人误概率差异较大,从方法的客观性、合理性和适用性角度分析,贝叶斯网络在研究该问题时更具优势。     

基于改进的SPAR-H化工实验室人因可靠性分析

近年来化工实验室事故屡禁不止,其中人的不安全行为是导致事故发生的主要原因.为评估实验人员可靠性,进一步管控化工实验室人的不安全行为,基于标准化工厂人因可靠性分析(SPAR-H)方法,结合化工实验室人因失误的特点,确定了更加适用于化工实验室的人因可靠性分析方法.首先依据"S-O-P"认知模型对人因失误类型进行划分;然后基...     

上海市能耗与GDP大气污染的协整关系研究

采用计量经济学中的协整理论考察上海市能源消费量与经济增长、废气排放量、二氧化硫排放量之间的关系。结果显示,上海市能源消费只与经济增长、废气排放量之间存在长期协整关系,并建立了相应的长期均衡方程及误差修正模型。另外,对1978～2003年的能源消费与经济增长之间进行Granger因果关系检验,提出实现上海市经济-能源-环境和谐发展的措施。     

Harmony Hurts: Participation and Silent Conflict at an Indonesian Fish Pond

Participatory environmental and resource management is premised on open communication to reach consensus. However, deliberate and open communication cannot adequately address silent conflict. This begs two questions. First, how is the existence of covert communication and silent conflict to be recognized and addressed? Second, how are the wider social relations and traditions that encompass communication and conflict to be described and explained? These questions revolve around communicative power. Communication of environmental knowledge is deeply embedded in social power structures, with direct implications for participatory resource planning and implementation. Ethnographic research conducted at a failed community-managed fish farming project in Southeast Sulawesi, Indonesia shows that a culture of harmony and respect for authority can silence environmental conflict in the hierarchical “community.” Three propositions are offered. First, communication amnesia and exclusion jeopardize participation. Second, cultures of harmony and silent conflict shape planning processes and outcomes. Third, the weak use manipulation and communication strategy to acquire a “voice” while preserving harmony. These propositions address five unresolved issues in participatory resource management: analysis of groups, contextuality, social relationships, nonparticipants, and informal communication. Power, tradition, and social networks affect the valuing of knowledge relative to the power of different individuals and institutions to communicate priorities, values, and needs. These factors are critical to the inclusion of both participants and nonparticipants.     

Communicative Aspects of Environmental Management by Objectives: Examples from the Swedish Context

Management by objectives (MBO) is a technique for integrating ecological concerns into national political and administrative structures. Politicians determine environmental objectives and interim targets to be implemented and assessed by civil servants in national, regional, and local contexts. Well-developed organizational communication is a prerequisite for MBO. However, communication-related obstacles can arise when using MBO in public environmental management. We examine communicative aspects of environmental MBO, looking specifically at the implementation, administration, and assessment of Swedish environmental quality objectives. Our argument is illustrated by quotations from individual and focus group interviews. We conclude that communicative problems may arise, because different actors interpret messages from different perspectives, depending on their agendas, prior knowledge and experience, and positions in the administrative system. It is crucial to recognize the dialogical aspects of communication, by involving the receiver of a message in a process of response. In addition, the different timeframes underlying different arguments could contribute to misunderstandings between actors involved in handling environmental issues. In assessing the achievement of environmental objectives, indicators are used as communicative tools. It is important to investigate whether and how these indicators contribute to the de- and recontextualization of environmental objectives.     

Anaerobic tapered fluidized bed reactor for starch wastewater treatment and modeling using multilayer perceptron neural network

Anaerobic treatability of synthetic sago wastewater was investigated in a laboratory anaerobic tapered fluidized bed reactor(ATFBR) with a mesoporous granular activated carbon(GAC)as a support material.The experimental protocol was defined to examine the effect of the maximum organic loading rate(OLR),hydraulic retention time(HRT),the efficiency of the reactor and to report on its steady- state performance.The reactor was subjected to a steady-state operation over a range of OLR up to 85.44 kg COD/(m~3.d).The COD removal efficiency was found to be 92% in the reactor while the biogas produced in the digester reached 25.38 m~3/(m~3·d) of the reactor. With the increase of OLR from 83.7 kg COD/(m~3.d),the COD removal efficiency decreased.Also an artificial neural network(ANN) model using multilayer perceptron(MLP)has been developed for a system of two input variable and five output dependent variables. For the training of the input-output data,the experimental values obtained have been used.The output parameters predicted have been found to be much closer to the corresponding experimental ones and the model was validated for 30% of the untrained data.The mean square error(MSE)was found to be only 0.0146.