Interval Time Series Analysis with an Application to the Sterling-Dollar Exchange Rate

Traditional econometrics has long employed ＂points＂ to measure time series data. In real life situations, however, it suffers the loss of volatility information, since many variables are bounded by intervals in a given period. To address this issue, this paper provides a new methodology for interval time series analysis. The concept of ＂interval stochastic process＂ is formally defined as a counterpart of ＂stochastic process＂ in point-based econometrics. The authors introduce the concepts of interval stationarity, interval statistics （including interval mean, interval variance, etc.） and propose an interval linear model to investigate the dynamic relationships between interval processes. A new interval-based optimization approach for estimation is proposed, and corresponding evaluation criteria are derived. To demonstrate that the new interval method provides valid results, an empirical example on the sterling-dollar exchange rate is presented.     

PDE-Based Medial Axis Extraction and Shape Manipulation of Arbitrary Meshes

Shape skeletonization （i.e., medial axis extraction） is powerful in many visual computing applications, such as pattern recognition, object segmentation, registration, and animation. In this paper, the authors expand the use of diffusion equations combined with distance field information to approximate medial axes of arbitrary 3D differential properties. It offers an alternative solids represented by polygonal meshes based on their but natural way for medial axis extraction for commonly used 3D polygonal models. By solving the PDE along time axis, this system can not only quickly extract diffusion-based medial axes of input meshes, but also allow users to visualize the extraction process at each time step. In addition, the proposed model provides users a set of manipulation toolkits to sculpt extracted medial axes, then use diffusion-based techniques to recover corresponding deformed shapes according to the original input datasets. This skeleton-based shape manipulation offers a fast and easy way for animation and deformation of complicated mesh objects.     

Designing a Hybrid Intelligent Mining System for Credit Risk Evaluation

In this study, a novel hybrid intelligent mining system integrating rough sets theory and support vector machines is developed to extract efficiently association rules from original information table for credit risk evaluation and analysis. In the proposed hybrid intelligent system, support vector machines are used as a tool to extract typical features and filter its noise, which are different from the previous studies where rough sets were only used as a preprocessor for support vector machines. Such an approach could reduce the information table and generate the final knowledge from the reduced information table by rough sets. Therefore, the proposed hybrid intelligent system overcomes the difficulty of extracting rules from a trained support vector machine classifier and possesses the robustness which is lacking for rough-set-based approaches. In addition, the effectiveness of the proposed hybrid intelligent system is illustrated with two real-world credit datasets.     

Systemic Intervention in a University Department: Reflections on Arrested Action Research

This paper reflects on my experience as an insider researcher attempting to use critical systems ideas and practices to promote quality improvement in a university engineering department. Reflection is a key part of learning. This paper is intended to contribute to critically, self-reflective learning for the community of systems practitioners. These reflections on my questions about participation, ethics, politics of process, and the choices and actions resulting from them may help others to formulate their own. The complexity of systems practice places substantial demands on the researcher, particularly in the case of insider, practitioner research. Nevertheless, the exploration of critical systems approaches to critique boundaries and structure ‘problems’ in the core aspects of higher education in locally meaningful ways should continue. While demanding, it still can work to promote learning about authentic quality.     

A STAGE-STRUCTURED SI ECO-EPIDEMIOLOGICAL MODEL WITH TIME DELAY AND IMPULSIVE CONTROLLING*

This paper formulates a robust stage-structured SI eco-epidemiological model with periodic constant pulse releasing of infectious pests with pathogens. The authors show that the conditions for global attractivity of the ＇pest-eradication＇ periodic solution and permanence of the system depend on time delay, hence, the authors call it ＂profitless＂. Further, the authors present a pest management strategy in which the pest population is kept under the economic threshold level （ETL） when the pest population is uniformly persistent. By numerical analysis, the authors also show that constant maturation time delay for the susceptible pests and pulse releasing of the infectious pests can bring obvious effects on the dynamics of system.     

ACCURACY ANALYSIS FOR QUASI-CAREY ELEMENT*

In this paper, a new triangular element （Quasi-Carey element） is constructed by the idea of Specht element. It is shown that this Quasi-Carey element possesses a very special property, i.e., the consistency error is of order O（h^2）, one order higher than its interpolation error when the exact solution belongs to H^3（Ω）. However, the interpolation error and consistency error of Carey element are of order O（h）. It seems that the above special property has never been seen for other triangular elements for the second order problems.     

Hopf bifurcation and chaos of financial system on condition of specific combination of parameters*

Exponential stability of the first order singular distributed parameter systems is discussed in the light of degenerate semi-group methods, which is described by the abstract developing equation in Hilbert space. The necessary and sufficient conditions concerning the exponential stability of the first order singular distributed parameter systems are given.     

Robust model predictive control of continuous uncertain systems*

The authors concern robust model predictive control for linear continuous systems with polytopic uncertainties and input constraints. At each sampling time, a piecewise constant control sequence is obtained by solving a set of linear matrix inequalities. The sufficient conditions on the existence of the model predictive control are given, and the robust stability of the closed-loop systems is guaranteed. A simulation example illustrates the efficiency of the proposed method.     

Participatory Sustainability Impact Assessment: Scientific Policy Advice as a Social Learning Process

This paper deals with the development of scientific policy advice by providing a methodology to foster a social learning process. The methodology, called participatory Sustainability Impact Assessment (pSIA), aims to structure complex problem situations, to clarify interests and basic assumptions, to interpret scientific studies, to develop impact assessment, and to explore sensitivity of uncertainty and lack of information. In pSIA workshops the participants are supposed to build conceptual models with different modelling methods, like System Dynamics, Value Chain Analysis, and Morphological Analysis. A case study is presented that describes a workshop series with political as well as academic actors, applying the pSIA approach to an impact assessment of Economic Partnership Agreements between the European Union and the Eastern and Southern Africa Region.

Conflict Pattern Analysis: Preparing the Ground for Participation in Policy Implementation

The participation of non-state actors in implementation processes is often understood as a means to increase compliance efficiency. But the implementation of spatial policies frequently focuses on pre-established goals, processes and instruments and thus renders difficult open discourse and shared decision-making. This paper introduces conflict pattern analysis (CPA) as a tool that supports the analysis of the actual actor constellation in order to define efficient approaches that avoid common problems of participatory processes. CPA is a semi-formalised method that helps to identify key-actors, their relations and interaction amongst each other as well as their core beliefs, interests and resources. It aggregates this information to interaction patterns that can be compared, classified and linked to different participatory methods on a theoretically informed basis. Particularly on the local and regional level, this could be the first step for successful (participatory) implementation strategies.