Numerical study of soil heterogeneity effects on contaminant transport in unsaturated soil (model development and validation)

The movement of chemicals through soil to groundwater is a major cause of degradation of water resources. In many cases, serious human and stock health implications are associated with this form of pollution. The study of the effects of different factors involved in transport phenomena can provide valuable information to find the best remediation approaches. Numerical models are increasingly being used for predicting or analyzing solute transport processes in soils and groundwater. This article presents the development of a stochastic finite element model for the simulation of contaminant transport through soils with the main focus being on the incorporation of the effects of soil heterogeneity in the model. The governing equations of contaminant transport are presented. The mathematical framework and the numerical implementation of the model are described. The comparison of the results obtained from the developed stochastic model with those obtained from a deterministic method and some experimental results shows that the stochastic model is capable of predicting the transport of solutes in unsaturated soil with higher accuracy than deterministic one. The importance of the consideration of the effects of soil heterogeneity on contaminant fate is highlighted through a sensitivity analysis regarding the variance of saturated hydraulic conductivity as an index of soil heterogeneity. © 2011 John Wiley & Sons, Ltd.

Innovative capabilities, entrepreneurial process and the dynamic growth of university spin-outs: A process-oriented study with evidence from China

This research aims to develop a conceptual framework in order to enquire into the dynamic growth process of University Spin-outs (hereafter referred to as USOs) in China, attempting to understand the capabilities configuration that are necessary for the dynamic growth. Based on the extant literature and empirical cases, this study attempts to address the question how do USOs in China build and configure the innovative capabilities to cope with the dynamic growth. This paper aims to contribute to the existing literature by providing a theoretical discussion of the USOs' dynamic entrepreneurial process, by investigating the interconnections between innovation problem-solving and the required configuration of innovative capabilities in four growth phases. Further, it presents a particular interest on the impact to the USOs' entrepreneurial innovation process by the integrative capabilities, in terms of knowledge integration, alliance, venture finance and venture governance. To date, studies that have investigated the dynamic development process of USOs in China and have recognized the heterogeneity of USOs in terms of capabilities that are required for rapid growth still remain sparse. Addressing this research gap will be of great interest to entrepreneurs, policy makers, and venture investors. ©2009 IEEE.

Non-aqueous phase liquid behavior in the subsurface: Transportation, source zone characterization and remediation

Contaminant behaviour in soils and fractured rock is very complex, not least because of the heterogeneity of the subsurface environment. For non-aqueous phase liquids (NAPLs), a liquid density contrast and interfacial tension between the contaminant and interstitial fluid adds to the complexity of behaviour, increasing the difficulty of predicting NAPL behaviour in the subsurface. This paper outlines the need for physical model tests that can improve fundamental understanding of NAPL behaviour in the subsurface, enhance risk assessments of NAPL contaminated sites, reduce uncertainty associated with NAPL source remediation and improve current technologies for NAPL plume remediation. Four case histories are presented to illustrate physical modelling approaches that have addressed problems associated with NAPL transport, remediation and source zone characterization. © 2006 Taylor & Francis Group, London.

Cluster analysis of heterogeneous rank data

Cluster analysis of ranking data, which occurs in consumer questionnaires, voting forms or other inquiries of preferences, attempts to identify typical groups of rank choices. Empirically measured rankings are often incomplete, i.e. different numbers of filled rank positions cause heterogeneity in the data. We propose a mixture approach for clustering of heterogeneous rank data. Rankings of different lengths can be described and compared by means of a single probabilistic model. A maximum entropy approach avoids hidden assumptions about missing rank positions. Parameter estimators and an efficient EM algorithm for unsupervised inference are derived for the ranking mixture model. Experiments on both synthetic data and real-world data demonstrate significantly improved parameter estimates on heterogeneous data when the incomplete rankings are included in the inference process.

Scalable robustness for consensus protocols with heterogeneous dynamics

It is shown in the paper how robustness can be guaranteed for consensus protocols with heterogeneous dynamics in a scalable and decentralized way i.e. by each agent satisfying a test that does not require knowledge of the entire network. Random graph examples illustrate that the proposed certificates are not conservative for classes of large scale networks, despite the heterogeneity of the dynamics, which is a distinctive feature of this work. The conditions hold for symmetric protocols and more conservative stability conditions are given for general nonsymmetric interconnections. Nonlinear extensions in an IQC framework are finally discussed. Copyright © 2005 IFAC.

A policy dimension required for technology roadmapping: Learning from the development of emerging wind energy industry in China

Innovation policies play an important role throughout the development process of emerging industries. However, existing policy studies view the process as a black-box, and fail to understand the policy-industry interactions through the process. This paper aims to develop an integrated technology roadmapping tool, in order to facilitate the better understanding of policy heterogeneity at the different stages of new energy industries in China. Through the case study of Chinese wind energy equipment manufacturing industry, this paper elaborates the dynamics between policy and the growth process of the industry. Further, this paper generalizes some Chinese specifics for the policy-industry interactions. As a practical output, this study proposes a policy-technology roadmapping framework that maps policy-market-product- technology interactions in response to the requirement for analyzing and planning the development of new industries in emerging economies (e.g. China). This paper will be of interest to policy makers, strategists, investors, and industrial experts. © 2011 IEEE.

Understanding university academics' internal and external knowledge interactions in different disciplines: evidence from university in South Korea

Most of the literature on the role of universities in innovation assumes that academics¡¯ knowledge interacts only with industry and knowledge transfer occurs only or mainly in the technological and scientific fields. We question these assumptions, suggesting academics¡¯ internal and external knowledge interact across disciplines. Using national survey data, this paper tries to show the heterogeneity of university teachers¡¯ knowledge interactions across wider disciplines. Also, this paper explores the patterns of university academics¡¯ internal knowledge interactions with other academics within academia and the university academics¡¯ external knowledge interactions with industry, such as small and medium enterprises (SMEs) and major Korean firms, Chaebols. We found that there are heterogeneities of academics¡¯ knowledge interactions across the disciplines.

Optimal design of Functionally Graded Materials using a procedural model and Particle Swarm Optimization

A new method for the optimal design of Functionally Graded Materials (FGM) is proposed in this paper. Instead of using the widely used explicit functional models, a feature tree based procedural model is proposed to represent generic material heterogeneities. A procedural model of this sort allows more than one explicit function to be incorporated to describe versatile material gradations and the material composition at a given location is no longer computed by simple evaluation of an analytic function, but obtained by execution of customizable procedures. This enables generic and diverse types of material variations to be represented, and most importantly, by a reasonably small number of design variables. The descriptive flexibility in the material heterogeneity formulation as well as the low dimensionality of the design vectors help facilitate the optimal design of functionally graded materials. Using the nature-inspired Particle Swarm Optimization (PSO) method, functionally graded materials with generic distributions can be efficiently optimized. We demonstrate, for the first time, that a PSO based optimizer outperforms classical mathematical programming based methods, such as active set and trust region algorithms, in the optimal design of functionally graded materials. The underlying reason for this performance boost is also elucidated with the help of benchmarked examples. © 2011 Elsevier Ltd. All rights reserved.

An Online Expectation-Maximization Algorithm for Changepoint Models

Changepoint models are widely used to model the heterogeneity of sequential data. We present a novel sequential Monte Carlo (SMC) online Expectation-Maximization (EM) algorithm for estimating the static parameters of such models. The SMC online EM algorithm has a cost per time which is linear in the number of particles and could be particularly important when the data is representable as a long sequence of observations, since it drastically reduces the computational requirements for implementation. We present an asymptotic analysis for the stability of the SMC estimates used in the online EM algorithm and demonstrate the performance of this scheme using both simulated and real data originating from DNA analysis.