Enhancing urban infrastructure investment planning practices for a changing climate.

Climate change raises many concerns for urban water management because of the effects on all aspects of the hydrological cycle. Urban water infrastructure has traditionally been designed using historical observations and assuming stationary climatic conditions. The capability of this infrastructure, whether for storm-water drainage, or water supply, may be over- or under-designed for future climatic conditions. In particular, changes in the frequency and intensity of extreme rainfall events will have the most acute effect on storm-water drainage systems. Therefore, it is necessary to take future climatic conditions into consideration in engineering designs in order to enhance water infrastructure investment planning practices in a long time horizon. This paper provides the initial results of a study that is examining ways to enhance urban infrastructure investment planning practices against changes in hydrologic regimes for a changing climate. Design storms and intensity-duration-frequency curves that are used in the engineering design of storm-water drainage systems are developed under future climatic conditions by empirically adjusting the general circulation model output, and using the Gumbel distribution and the Chicago method. Simulations are then performed on an existing storm-water drainage system from NE Calgary to investigate the resiliency of the system under climate change.     

Evaluating the impact of CASE: an empirical comparison of retrospective and cross-sectional survey approaches

The purpose of this paper is to evaluate two methods of assessing the productivity and quality impact of Computer Aided Software Engineering (CASE) and Fourth Generation Language (4GL) technologies: (1) by the retrospective method; and (2) the cross-sectional method. Both methods involve the use of questionnaire surveys. Developers' perceptions depend on the context in which they are expressed and this includes expectations about the effectiveness of a given software product. Consequently, it is generally not reliable to base inferences about the relative merits of CASE and 4GLs on a cross-sectional comparison of two separate samples of users. The retrospective method that requires each respondent to directly compare different products is shown to be more reliable. However, there may be scope to employ cross-sectional comparisons of the findings from different samples where both sets of respondents use the same reference point for their judgements, and where numerical rather than verbal rating scales are used to measure perceptions.     

Presupposition failure — A comedy of errors

Presuppositions of utterances are the pieces of information you convey with an utterance no matter whether your utterance is true or not. We first study presupposition in a very simple framework of updating propositional information, with examples of how presuppositions of complex propositional updates can be calculated. Next we move on to presuppositions and quantification, in the context of a dynamic version of predicate logic, suitably modified to allow for presupposition failure. In both the propositional and the quantificational case, presupposition failure can be viewed as error abortion of procedures. Thus, a dynamic assertion logic which describes the preconditions for error abortion is the suitable tool for analysing presupposition.     

Delay-dependent state estimation for delayed neural networks

In this letter, the delay-dependent state estimation problem for neural networks with time-varying delay is investigated. A delay-dependent criterion is established to estimate the neuron states through available output measurements such that the dynamics of the estimation error is globally exponentially stable. The proposed method is based on the free-weighting matrix approach and is applicable to the case that the derivative of a time-varying delay takes any value. An algorithm is presented to compute the state estimator. Finally, a numerical example is given to demonstrate the effectiveness of this approach and the improvement over existing ones.     

The organisational learning effects of management accounting information under advanced manufacturing technology

This study empirically examined the organisational learning effects of the nonfinancial performance information provided by management accounting information systems (MAISs) under advanced manufacturing technology (AMT). In this study, a target costing system and the frequent and quick reporting of information were considered the facilitators of learning. First, we examined the relationships between AMT level and the amount of nonfinancial performance information produced by MAISs. The empirical results showed that there are significant positive relationships between the level of AMT and nonfinancial performance information. With a systems approach, we also proved the impact of the relationships among AMT levels, nonfinancial performance information and learning facilitators on the organisational performance of a firm. The results of our research suggest that under a high level of AMT, for the provision of information to result in an increase of performance through organisational learning, a target costing system must be introduced and a large amount of information should be provided frequently and quickly. The results of this study also showed that although AMT level may be low, fairly well-arranged facilitators and a moderately large amount of information may be necessary for the improvement of performance. In conclusion, effective organisational learning depends on the provision of relevant information as well as efficient learning support mechanisms.     

Automatic conversion from lexical words to prosodic words for mandarin text-to-speech system

In real speech, not like lexical words (LWs), prosodic words (PWs) are basic rhythmic units. The naturalness of a Text-to-Speech (TTS) system is directly influenced by the segmentation of the PWs. Most of the PWs are the combination of several LWs. In this paper, three Lexical Combination Models are proposed to combine LWs into PWs, including a Directed Acyclic Graph Model, a Segmentation Model and a Markov Model (MM). To cope with the situation where some long LWs should be segmented into two or more PWs, a Lexical Split Model (LSM) is applied to the long LWs. Experimental results prove that relatively constant results with various training data can be obtained from a MM. The Transformation-Based Error Driven Learning (TBED) algorithm, for its high performance of individual property, is applied in combination with the MM to improve the precision of PW segmentation. Experiments show that among the three proposed models, the MM combined with TBED and LSM, leads to the best performance, in which a precision of 93.00% and a recall of 93.23% are achieved. The perception test indicates that by using PWs as the lowest prosodic units a speech sounds more natural and acceptable than by using LWs. This paper is supported by NSFC Project (60503071); 973 Natural Basic Research Program of China (2004CB318102); Postdoctor Science Foundation of P. R. China (20070420275).     

Critical Configurations for 1-View in Projections from ℙ<Superscript>k</Superscript> → ℙ<Superscript>2</Superscript>

In this paper we describe, from a theoretical point of view, critical configurations for the projective reconstruction of a set of points, for a single view, i.e. for calibration of a camera, in the case of projections from ℙ^k to ℙ² for k ≥ 4. We give first a general result describing these critical loci in ℙ^k, which, if irreducible, are algebraic varieties of dimension k−2 and degree 3. If k=4 they can be either a smooth ruled surface or a cone and if k = 5 they can be a smooth three dimensional variety, ruled in planes, or a cone. If k≥ 6, the variety is always a cone, the vertex of which has dimension at least k − 6. The reducible cases are studied in Appendix A. These results are then applied to determine explicitly the critical loci for the projections from ℙ^k which arise from the dynamic scenes in ℙ³ considered in [13]. Marina Bertolini is currently Associate Professor of Geometry at the Department of Mathematics at the Università degli Studi di Milano, Italy. Her main field of research is Complex Projective Algebraic Geometry, with particular interest for the classification of projective varieties and for the geometry of Grassmann varieties. On these topics M. Bertolini has published more than twenty reviewed papers on national and international journals. She has been for some years now interested also in applications of Algebraic Geometry to Computer Vision problems. Cristina Turrini is Associate Professor of Geometry at the Department of Mathematics of Università degli Studi di Milano, Italy. Her main research interest is Complex Projective Algebraic Geometry: subvarieties of Grassmannians, special varieties, automorphisms, classification. In the last two years she has started to work on applications of Algebraic Geometry to problems of Computer Vision. She is author or co-author of about thirty reviewed papers. She is also involved in popularization of Mathematics, and on this subject she is co-editor of some books.