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.     

Tax Evasion: Models with Self-Audit

Different from traditional tax audit, supervision with self-audit is a combination of audit by the taxpayer himself and audit by the tax authority. This paper mainly studies a taxpayer＇s optimal policy of tax evasion under supervision with self-audit and its related properties, in order to deduce some effective suggestions and theoretical bases to restrain tax evasion. Assuming that only a certain proportion of evaded tax can be discovered when the audit is executed, the authors first formulate a static model with self-audit. This model is divided into two stages. At the first stage, taxpayers declare their taxes, then the tax authority chooses audit objects, based on a known probability, and announces the result; if the taxpayer is chosen, he will enter the second stage, during which he has a chance to pay the evaded tax and the corresponding late fees and then is audited by the tax authority. The authors show the existence and uniqueness of the optimal amount of tax evasion at the first stage and the optimal proportion to self-expose at the second stage. The authors also discuss the related properties of the interior solution, and do elasticity analyses on some parameters. Besides, the authors extend the static model into the corresponding two-period model, and study the existence and uniqueness of the solution of the extended model. Finally, under the assumption that tax evasion can only be discovered with a certain probability when the audit is executed, the authors formulate another static model with self-audit and investigate its properties.     

Process capability analysis and estimation scheme for autocorrelated data

<正>Autocorrelation is prevalent in continuous production processes,such as the processes in the chemical and pharmaceutical industries.With the development of measurement technology and data acquisition technology,sampling frequency is getting higher and the existence of autocorrelation cannot be ignored.This paper analyzes five estimation schemes of process capability for autocorrelated data.Comparisons among these schemes are discussed for small sample and large sample.In conclusion,this paper gives a procedure of process capability analysis for autocorrelated data.     

Clustering patents using non-exhaustive overlaps

Patent documents are unique external sources of information that reveal the core technology underlying new inventions.Patents also serve as a strategic data source that can be mined to discover state-of-the-art technical development and subsequently help guide R&D investments.This research incorporates an ontology schema to extract and represent patent concepts.A clustering algorithm with non-exhaustive overlaps is proposed to overcome deficiencies with exhaustive clustering methods used in patent mining and technology discovery.The non-exhaustive clustering approach allows for the clustering of patent documents with overlapping technical findings and claims,a feature that enables the grouping of patents that define related key innovations.Legal advisors can use this approach to study potential cases of patent infringement or devise strategies to avoid litigation.The case study demonstrates the use of non-exhaustive overlaps algorithm by clustering US and Japan radio frequency identification (RFID) patents and by analyzing the legal implications of automated discovery of patent infringement.     

Connecting informal networks to management of tacit knowledge

The relationship between tacit knowledge and informal networks has not been fully explored.Tacit knowledge cannot be well managed directly,because it is deeply embedded in individual actions and experiences.This study proposes an approach to managing informal networks as a new middle way to facilitate the sharing and transferring of tacit knowledge,owing to the fact that tacit knowledge is mostly shared and transferred through informal networks.To support the idea of the approach,an empirical case study of applying the approach to management of a large scientific project is also included.Our findings suggest that informal networks play essential roles for management of tacit knowledge,and thus good management of informal networks can lead to efficient sharing and transferring of tacit knowledge.     

Measuring and locating zones of chaos and irregularity

The new measures computed here are the spectral detrended fluctuation anatysls （sDFA） and spectral multi-taper method （sMTM）. sDFA applies the standard detrended fluctuation analysis （DFA） algorithm to power spectra, sMTM exploits the minute increases in the broadband response, typical of chaotic spectra approaching optimal values. The authors chose the Brusselator, Lorenz, and Duffing as the proposed models to measure and locate chaos and severe irregularity. Their series of chaotic parametric responses in short time-series is advantageous. Where cycles have only a limited number of slow oscillations such as for systems biology and medicine. It is difficult to create, locate, or monitor chaos. From 50 linearly increasing starting points applied to the chaos target function （CTF）; the mean percentage increases in Kolmogorov-Sinai entropy （KS-Entropy） for the proposed chosen models; and p-values when the models were compared statistically by Kruskal-Wallis and ANOVA1 test with distributions assumed normal are Duffing （CTF： 31%： p 〈0.03）; Lorenz （CTF： 2%： p 〈0.03）, and I3russelator （CTF： 8%： p 〈0.01）. Principal component analysis （PCA） is applied to assess the significance of the objective functions for tuning the chaotic response. From PCA the conclusion is that CTF is the most beneficial objective function overall delivering the highest increases in mean KS-Entropy.     

Film Use to Promote Understanding in Change and Diffusion of Innovation

The paper explores cinematic films as a pedagogical tool to promote critical thinking and student discussions in a doctoral-level learning, design, and technology seminar course at a major U.S. research university. These discussions focused on systemic change and systemic thinking concepts. The authors offer evidence from the literature that supports films’ power as a visual metaphor and neurocognitive stimulator to promote development of new perspectives in graduate students on case studies through articulation, reflection, and explanation of their thought processes on change and diffusion of innovation. There are theoretical, political, social, and technological issues that create tensions during any systemic change effort. The goal of using film in this seminar is to equip students with the requisite skills, theoretical frameworks, and interpersonal experiences needed to address these issues within organizations and communities. The change expected from systemic thinking is for students to think more deeply about the interconnectedness of systems and the importance of bottom-up change efforts that consider the perspective of all stakeholders.