Clustering in weighted networks

In recent years, researchers have investigated a growing number of weighted networks where ties are differentiated according to their strength or capacity. Yet, most network measures do not take weights into consideration, and thus do not fully capture the richness of the information contained in the data. In this paper, we focus on a measure originally defined for unweighted networks: the global clustering coefficient. We propose a generalization of this coefficient that retains the information encoded in the weights of ties. We then undertake a comparative assessment by applying the standard and generalized coefficients to a number of network datasets.     

Disaster response on September 11, 2001 through the lens of statistical network analysis

The rescue and relief operations triggered by the September 11, 2001 attacks on the World Trade Center in New York City demanded collaboration among hundreds of organisations. To shed light on the response to the September 11, 2001 attacks and help to plan and prepare the response to future disasters, we study the inter-organisational network that emerged in response to the attacks. Studying the inter-organisational network can help to shed light on (1) whether some organisations dominated the inter-organisational network and facilitated communication and coordination of the disaster response; (2) whether the dominating organisations were supposed to coordinate disaster response or emerged as coordinators in the wake of the disaster; and (3) the degree of network redundancy and sensitivity of the inter-organisational network to disturbances following the initial disaster. We introduce a Bayesian framework which can answer the substantive questions of interest while being as simple and parsimonious as possible. The framework allows organisations to have varying propensities to collaborate, while taking covariates into account, and allows to assess whether the inter-organisational network had network redundancy—in the form of transitivity—by using a test which may be regarded as a Bayesian score test. We discuss implications in terms of disaster management.     

Study of the behaviour of flexible production systems using neural nets

Owing to high development and acquisition costs, production systems require very detailed analysis for pre-design specifications, and an adjustment in operating philosophies. Detailed simulation models are one of the most important instruments to achieve this goal; normally the simulator must be custom-built, based on an accurate study of the specific industrial problem. The proposed management and economical analysis uses mathematical meta-models obtained from experimental designs produced by the simulator; today the detail level and precision required is very high, so these kinds of meta-model operate very close to their limit. Here we present a new methodology based on artificial neural networks that produces new types of meta-models which can correctly represent complex industrial systems. In this work we propose an application of this methodology together with a detailed analysis of the model development phase to highlight the potential of this instrument.     

Learning to negotiate network relations: social support among working mothers living in poverty

This study promotes our understanding of the complex and dynamic role that social support networks play in the everyday life of working mothers living in poverty, by focusing on the processes of negotiation involved in the creation, maintenance and mobilization of social ties. It is based on semi-structured interviews with 12 Israeli-Jewish working mothers who participated in an economic empowerment workshop. Findings indicate that the participants received much social support from relatives, friends and community activists. However, they further reveal the hard hidden work of negotiation and the process of learning involved in obtaining support. Particularly important in this context of poverty was the need to learn how to ask for support by overcoming feelings of shame and concerns about respectability, and to reduce social burdens by, among other things, refusing to participate in the ‘gift economy’ and limiting constraining social relationships. Finally, this study shows how the seemingly divergent interpretations of negotiation in social-exchange theory and symbolic interactionism (reaching an agreement that maximizes benefits versus preserving the relationship) often converge in everyday life situations.     

Good health and the bridging of structural holes

Bridges that span structural holes are often explained in terms of the entrepreneurial personalities or rational motivations of brokers, or structural processes that lead to the intersection of social foci. I argue that the existence and use of bridges in interpersonal networks also depends on individuals’ health. Poor health may make it more difficult to withstand the pressures and to execute some of the common tasks associated with bridging (e.g., brokerage). I examine this possibility using egocentric network data on over 2500 older adults drawn from the recent National Social Life, Health, and Aging Project (NSHAP). Multivariate regression analyses show that both cognitive and functional health are significantly positively associated with bridging, net of sociodemographic and life-course controls. The relationship between functional (kinesthetic) health and bridging appears to be partially mediated by network composition, as older adults who have poorer functional health also tend to have networks that are richer in strong ties. Several potential mediation mechanisms are discussed. Cognitive function remains significantly associated with bridging net of network composition, suggesting that the inherent challenges of maintaining bridging positions may be more difficult to cope with for those who have cognitive impairments than for those who have functional impairments such as limited mobility. An alternative explanation is that cognitively impaired individuals have more difficulty recognizing (and thus strategically using) bridges in their networks. Theoretical implications and possibilities for future research are discussed.     

On the Nonlinear Predictability of Stock Returns Using Financial and Economic Variables

In a recent article by Qi, neural networks trained by Bayesian regularization were used to predict excess returns on the S&P 500. The article concluded that the switching portfolio based on the recursive neural-network forecasts generates higher accumulated wealth with lower risks than that based on linear regression. Unfortunately, attempts to replicate the results were unsuccessful. Replicated results using the same software, approach and data detailed by Qi indicate that, in fact, the switching portfolio based on the recursive neural-network forecasts generates lower accumulated wealth with higher risks than that based on linear regression.     

How to make e-Procurement viable for SME suppliers

Due to their common role as suppliers, small and medium-sized enterprises (SMEs) are especially challenged by today's turbulent business conditions. In order to meet this challenge, short-term WWW-based enterprise cooperations are regarded as an appropriate way to enhance the competitive strength of SMEs. Hence, the Institute of Machine Tools and Industrial Management (IWB) operates three so-called competence networks for engineering (www.engineering-net.de), rapid prototyping (www.rp-net.de) and manufacturing (www.produktionsnetz.de) services. For the purpose of an applied research project, more than 80 participating SME suppliers have been included in these specialized virtual markets, which are based on the core competencies of the cooperating SMEs. Additionally, the platform (www.virtueller-markt.de) enables customers to configure their specific supply chains via the above-mentioned competence networks. The presented paper depicts how to establish and operate these competence networks as well as how to configure supply chains via these virtual markets.     

Duality of departmental specializations and PhD exchange: A Weberian analysis of status in interaction using multilevel exponential random graph models (mERGM)

Weber proposes that lifestyle similarities preserve status by producing interactional closure between status similar actors. I investigate this theory on academic status hierarchies by conceptualizing sub-disciplinary specializations as departmental lifestyles and PhD exchange networks as interdepartmental interactions. Multilevel exponential random graph models (mERGM) reveal that the more specializations departments share, the more likely they are to exchange personnel. On the flip side, departments that do not share specializations are less likely to exchange doctoral candidates. Moreover, shared specializations are key determinants of closure between elite departments. These results support Weber’s theory and suggest that shared specializations preserve existing patterns of inequality between elite and non-elite departments.     

固气相变蒸发热的计算

用固体的Einstein模型与Debye模型分别导出相应模型的固气相变的蒸发热和蒸发压公式，并对其做数值计算。结果表明，蒸发热与温度之间近似呈线性关系,之与工程上经验近似是一致的。     

基于贝叶斯正则化的TDBPNN模型在中国外贸预报中的应用及评估

基于相空间重构的非线性预报思想,建立一个时滞的BP神经网络模型(TDBPNN),采用贝叶斯正则化方法提高BP网络的泛化能力,并将该模型应用于中国进出口贸易的预测,结果证明改进的TDBPNN模型具有较好的泛化能力,准确拟合了进出口贸易发展的历史值和趋势。区别于一般的预测评价,认为非线性预测不仅要注重数据拟合和精度改进,而且应该能够反映被预报系统的非线性特征。在分析模型预测精度的同时,通过计算拟合序列和原序列的非线性特征量进行模型评价,证实预测模型能够合理地“捕捉”到产生原序列的非线性系统的动力学特征。