Autoregressive modelling in vector spaces: An application to narrow-bandwidth spectral estimation

A generalisation of the Burg algorithm to vector spaces is described. This can be used to subsample time series that have narrow frequency bandwidth, thereby reducing the computation time and the complexity of the autoregressive model required. The technique is preferable to conventional subsampling.     

重金属污染物动态吸附试验及数学模拟

本文采用泥沙动力学中Ｒｏｕｓｅ等人用来研究泥沙浓度沿垂线分布的装置。对泥沙吸附重金属污染物进行了动态模拟。试验分有底泥和无底泥两种情况。研究中发现在Ｒｏｕｓｅ装置的水力、泥沙条件下泥沙吸附重金属污染物达到平衡状态需要６小时以上，由极坐标下的重金属迁移转化数学模型方程，在本文具体试验条件下进行数值求解，计算结果和试验结果合良好，说明数学模型是正确合理的试验是可靠的。计算时依据室内静态试验结果，对动态     

Delivering Improvement from Truth — the Fragile Link Between Analysis and Effective Change

In the history of operations research in industry there has been an abundance of analyses and recommendations produced in millions of man hours by dedicated OR specialists. And yet the net improvement is significantly lower than expected. There are numerous reasons for this shortfall: incomplete analysis, too much theory, incomplete implementation, unreliable recommendations, or a combination of some of these reasons.
By describing several examples, the major reasons for the fragility of the link between recommendation and implementation will be reviewed. What has to be done today to increase the likelihood of implementing an OR recommendation and thus improve the performance of an industrial entity by using the power of OR tools will then be described.     

Boundary Constrained Swept Surfaces for Modelling and Animation

Due to their simplicity and intuitiveness, swept surfaces are widely used in many surface modelling applications. In this paper, we present a versatile swept surface technique called the boundary constrained swept surfaces. The most distinct feature is its ability to satisfy boundary constraints, including the shape and tangent conditions at the boundaries of a swept surface. This permits significantly varying surfaces to be both modelled and smoothly assembled, leading to the construction of complex objects. The representation, similar to an ordinary swept surface, is analytical in nature and thus it is light in storage cost and numerically very stable to compute. We also introduce a number of useful shape manipulation tools, such as sculpting forces, to deform a surface both locally and globally. In addition to being a complementary method to the mainstream surface modelling and deformation techniques, we have found it very effective in automatically rebuilding existing complex models. Model reconstruction is arguably one of the most laborious and expensive tasks in modelling complex animated characters. We demonstrate how our technique can be used to automate this process.     

SQL extension for spatio-temporal data

An SQL extension is formalized for the management of spatio-temporal data, i.e. of spatial data that evolves with respect to time. The extension is dedicated to applications such as topography, cartography, and cadastral systems, hence it considers discrete changes both in space and in time. It is based on the rigid formalization of data types and of SQL constructs. Data types are defined in terms of time and spatial quanta. The SQL constructs are defined in terms of a kernel of few relational algebra operations, composed of the well-known operations of the 1NF model and of two more, Unfold and Fold. In conjunction with previous work, it enables the uniform management of 1NF structures that may contain not only spatio-temporal but also either purely temporal or purely spatial or conventional data. The syntax and semantics of the extension is fully consistent with the {SQL:2003} standard.     

Modelling of induced aeration in turbine aerators by use of radial basis function neural networks

Gas induction in agitated vessels with turbine impellers can be modelled accurately by means of radial basis function neural nets. The results obtained with the radial basis neural net were significantly better than those obtained by multivariate regression models or standard back propagation neural nets. Moreover, by using the radial basis function neural net model, it was possible to conduct a sensitivity analysis of the variables affecting aeration. Increased medium density showed a strong adverse effect, while variation of the viscosity can cause an increase or a decrease in the rate of aeration, depending on the prevailing process conditions.     

Possibilities and problems with the use of models as a communication tool in water resource management

Politicians and policy-makers, as well as modellers, often nurses an expectation that model derived results is an objective source of information that can be used to support decisions. However, several prerequisites have to be dealt with in order to ensure that models can be used as legitimate and efficient tools in water resource management. Based on empirical material from recent studies on the use of models in stakeholder dialogues, mainly focusing on catchment nutrient transport, two central problems are identified: (a) Models are laden with choices and thus depend on assumptions and priorities of modellers. (b) There are several factors that influence ability and willingness of stakeholders (as information recovers) to criticize or accept results of the modelling exercise. Recognized factors likely to influence stakeholders' acceptance of model derived results include issues at stake, stakeholders' ability to criticize model derived information, and their trust in the institutions that have developed or applied the used models. Identified prerequisites for successful use of models in integrated water resource management include: consideration of user relevance, awareness of and preparedness to handle constraints linked to communication of model-based results, transparency of used models and data and of involved uncertainties, mutual respect between experts and stakeholders and between involved stakeholder groups, a robust institutional network, and sufficient time for dialogues. Development and use of strategies for participatory modelling, based on a continuous dialogue between experts and stakeholders is recommended as a way to facilitate that the prerequisites for a successful use of models in water resource management are fulfilled.     

Forecasting Canadian nuclear power station construction costs

Because of the huge volume of capital required to construct a modern electric power generating station, investment decisions have to be made with as complete an understanding of the consequences of the decision as possible. This understanding must be provided by the evaluation of future situations. A key consideration in an evaluation is the financial component. This paper attempts to use an econometric method to forecast the construction costs escalation of a standard Canadian nuclear generating station (NGS). A brief review of the history of Canadian nuclear electric power is provided. The major components of the construction costs of a Canadian NGS are studied and summarized. A database is built and indexes are prepared. Based on these indexes, an econometric forecasting model is constructed using an apparently new econometric methodology of forecasting modelling. Forecasts for a period of 40 years are generated and applications (such as alternative scenario forecasts and range forecasts) to uncertainty assessment and/or decision-making are demonstrated. The indexes, the model, and the forecasts and their applications, to the best of the author's knowledge, are the first for Canadian NGS constructions.